https://cpw.cvlcollections.org/files/original/2d59e5fafd2e5842d038f579f4cc177b.pdf 681428411006d3aa48f1b49af24be111 PDF Text Text ����Colorado Division of Wildlife Wildlife Research Report 'July 2001 and July 2002 JOB PROGRESS REPORT State of Colorado Work Package No. _-,,0,-,,6~6.=.2 Task No. Division of Wildlife - Mammals Research _ 2 Preble's Meadow Jumping Mouse Conservation Effects of Resource Addition on Preble's Meadow Jumping Mouse (Zapus hudsonius preblei) Movement Patterns Period Covered: July 1,2000 - June 30, 2002 Author: Anne Trainor Personnel: T. M. Shenk, G. C. White, K. Wilson Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT Preble's meadow jumping mouse (Zapus hudsonius preblei; PMJM) is federally listed as threatened . under the Endangered Species Act (ESA). Habitat conservation plans (HCPs) as defined in Section 10 of \ the ESA, allow for 'take' of species and their habitat on private property. HCPs attempt to minimize take and provide for mitigation. Collection of reliable information and an increased understanding of PMJM habitat requirements are essential for the development of effective mitigation strategies for this species. Thus, our objectives are to (1) determine how the presence of resource additions influences the distribution of individual PMJM within a population, and (2) to quantify and compare microhabitat characteristics among areas PMJM used heavily to areas of no use. A manipulation experiment will be conducted in sections of riparian habitat and adjacent grasslands in Douglas County, Colorado in 2002 and 2003 . ....... _ ----- -- -- rlill~11~il~~II~~~~~~f1~li I~ffll~irnr BDOW016bOO ", . ��3 Research Prospectus Effects of Resource Addition on Preble's Meadow Jumping Mouse (Zapus Izudson ius prebleii Movement Patterns Anne Trainor, Tanya Shenk, and Kenneth Wilson Problem: The U.S. Fish and Wildlife Service (USFWS) listed the Preble's meadow jumping mouse (Zapus hudsonius preblei; PMJM) as a threatened species in 1998 under the Endangered Species Act (USFWS 1999). Upon listing, little was known about the biology and habitat requirements of this subspecies within its range along the Front Range of Colorado and southeastern Wyoming. Since listing, a number of projects (e.g., long-term monitoring, surveying, and movement studies) have collected valuable information throughout Colorado (Schorr 2001, Meaney 2000, Shenk and Sivert 1999). However, information on specific habitat requirements and their relationship to the distribution, density, survival and reproduction of PMJM is still lacking. The threatened status of PMJM requires management decisions be made despite our limited knowledge. In particular, the species and its habitat are subject to habitat conservation plans (HCPs). HCPs are written for endangered and threatened species to compensate for authorized "take" with mitigation practices (Bingham and Noon 1998). HCPs require the use of the "best available" science to determine the biological needs of target species (Harding et al. 2001). Collection of reliable information for the species will improve the mitigation practices developed for HCPs. Well-designed habitat manipulation experiments provide the strongest inference to determine cause and effect relationships. Understanding of the species habitat requirements will enable the development of effective mitigation strategies. A manipulation experiment will be conducted in Douglas County, Colorado (Columbine Open Space) during 2002 and 2003 to advance our understanding ofPMJM habitat requirements. We will manipulate sections of the riparian habitat and adjacent grassland within the 100-year flood plain. The site will be manipulated by adding patches (3 m x 2.43 m) of artificial resources (food and cover). Time limitations (2 field seasons are inadequate for vegetation to establish) and funding (cost of planting and sustaining vegetation) will restrict this manipulation experiment to simulating habitat with temporary structures and food supplementation. The treatments will be placed in areas of low use based on past monitoring studies conducted by the Colorado Division of Wildlife (CDOW) during 1998-2000 within 60 m of East Plum Creek. PMJM will be radio tracked before and after the manipulation to determine if PMJM locations can be altered through the addition of resources. Research Objectives: We propose two primary objectives: 1) determine how the presence of resource additions influences the distribution of individual PMJM within a population, and 2) quantify habitat characteristics of PMJM on a microhabitat scale. Desired outcome: We want to examine if the distribution of individual PMJM can be altered in response to the addition of resources (food and cover) and to quantify relevant microhabitat characteristics where PMJM have been detected. Approach: A field experiment will be conducted during 2002-2003 (June-August) to test ifPMJM can be attracted to areas where they have not previously been detected within the 100-year flood plain. Study Site- Riparian habitat within the Columbine Open Space, owned by Douglas County Open Space managed by the CDOW and the adjacent grassland. Columbine Open Space was selected �4 because PMJM were monitored for 3 years by the CDOW (1998-2000), providing site-specific information on PMJM locations before this manipulation experiment. Methods- PMJM will be trapped using non-folding Sherman live traps (7.6 em x 8.9 ern x 22.9 ern) placed 5 m apart along approximately 0.5 km transects adjacent to both sides of East Plum Creek for a minimum of 5 consecutive nights. Trapping procedures will be in accordance with the guidelines published by the USFWS (1999). Species other than PMJM will be recorded with trap location and immediately released. The following information will be recorded for captured PMJM: unique identification, trap location, weight, sex, age, and reproductive condition. PMJM will be scanned for a passive integrated transponder (PIT) tag. Newly captured individuals will have a unique PIT -tag injected and individuals 2:.18grams will be anesthetized with isoflurane to fit a l-g radio transmitter (Holohil Systems Ltd Ontario, Canada). All methods were approved by the Animal Care and Use Committee of Colorado State University (Authorization Number A3572-01). Radio telemetry will be used to monitor locations of individuals for a 2 l-day period, the battery life of the radio transmitters. Observers will attempt to stay approximately 3 m from the radio-tagged individual to avoid influencing PMJM movement. Observations taken 3 m or greater from PMJM did not influence movement (T. Shenk, CD OW personal comm.). The following information will be recorded at each relocation: individual identification, time, weather, and surrounding vegetation. All data will be combined into a geographical information system (GIS) database using ArcView®3.2 (Environmental Systems Research Institute, Redlands, California, U.S.A.). The manipulation experiment will consist of 5 phases: 1) select areas of little or no previous use by PMJM based on CDOW location data (1998-2000) collected at Columbine Open Space, 2) record pre-treatment location data of radio-tagged individuals for 6 nights, 3) select placement of treatment plots based on pre-treatment and CDOW location data, 4) add resources to treatment plots, and 5) record post-treatment location data of radio-tagged individuals. Two sessions (June and July) of the manipulation experiment will be conducted each year. A digital map with a grid cell size of 9 m x 9 m has been constructed for the entire study site with ArcView®3.2 (Environmental Systems Research Institute, Redlands, California, U.S.A.) software. CDOW location data was pooled into a single coverage over the grid to establish areas 2:.1,000 m2 containing only low use cells «2 locations/cell based on CD OW location data) within the l Ofl-year flood plain. Location of treatments will be selected with a stratified random design from a set of candidate cells meeting a criteria developed based on PMJM biology (sparse vegetation and little food source) within 60 m of East Plum Creek, and low historical use. The artificial cover, simulating vertical complexity, will be constructed with wheat straw and tree branches distributed in a patch (3 m x 2.43 m). Burlap cloth will be suspended 30 em over the tree branches and straw. Food supplements composed of an equal mixture of whole wheat, dehydrated alfalfa pellets and sweet feed will be placed on cardboard trays (0.16 m x 0.3 m) within the straw and branches as an attractant and a source of high protein. The dimensions of the treatments were selected to balance the manageability of construction and decrease the chance of inter and intraspecies domination within a treatment. Quantification of microhabitat variables in areas of high use will be examined by comparing a random sample of cells (9 m x 9 m) containing 2:.99 % ofPMJM locations for each session and a random sample of cells with no locations detected. Two line transects will be randomly placed in each selected cell with 6 quadrat frames (50 em x 20 em) evenly distributed per line transect (Daubenmire 1959). The variables measured in each cell will include percent bare ground, shrub, grass, and forb cover and vegetation composition . . :~. - �5 Analysis- The location data will be analyzed with linear regression. The response variable will be the number of locations detected in a cell. A suite of candidate models will be developed as predictors of the response variable. Akaike's information criterion (AIC) will be applied to select the best "approximating" model (Burnham and Anderson 2002). The independent habitat variables of interest for the models include distance from the center of the cell to the nearest water, area and juxtaposition of nearest shrub, and presence of wetland grasses in the cell. Additional variables to be included in the models are period (pre- or post-treatment), sex, session, and year. The microhabitat data collected from the Daubenmire plots will be analyzed with Proc GLM (SAS 2002) to test for differences in means among areas of high use and no use by PMJM. Schedule: Fall 2001.. Spring 2002 Summer 2002 Fall 2002 Spring 2003 Summer 2003 Fall 2003 Winter 2004 Formation of committee and write study plan development Completion of study plan and preparation for field season Begin data collection Begin data analysis Continue data analysis, begin thesis and complete comprehensive oral examination Complete data collection Complete data analysis Complete thesis Budget: Fiscal Year 2001-02 Refurbished Holohil radio collars Technicians Housing Vehicles Supplies Computer Tuition GRA Faculty Support FY 2001-02 Total $2,000 1@$1,250/month for 3 months $833/month for 3 months 1@$200/month for 3 months (including mileage) $700 $2,000 $2,880 $1,300/month for 12 months $3,830.00 $33,779 Fiscal Year 2002-03 Refurbished Holohilradio PIT tags Technicians Technicians Supplies Housing Vehicles Stipend Tuition Faculty Support FY 2002-03 Total $500 $1,000 1@$1,250/month for 3 months 1@$1,250/month for 2 months $500 $833/month for 3 months 1@$200/month for 3 months (including mileage) $1,300/month for 12 months $679.00 $3830.00 $31,458 collars �6 Fiscal Year 2003-04 Stipend FY 2003-04 Total Project Total $I,300/month for 8 months $10,400 $75,637 Potential cooperators: Funding is provided by the CDOW; Douglas County has given permission to use the Open Space; Colorado State University has provided office space, equipment, computers, and adviser. Alternative and obstacles: Alternatives considered include modeling habitat utilization at a microhabitat and site specific scales. Potential obstacles include 1) low number of radio-tagged PMJM resulting in low power for the manipulation experiment, 2) other species deterring PMJM from using the additional resources, and 3) radio-tagged mice do not detect the additional resources. PMJM have demonstrated general site fidelity to daytime nesting sites and nighttime feeding sites (Shenk and Sivert 1999). It is possible PMJM have established use areas and do not easily alter their use patterns. Literature Cited: Bingham, B. B., and B. R. Noon. 1998. The use of core areas in comprehensive mitigation strategies. Conservation Biology 12:241-243. Burnham K. P., and D. R. Anderson. 2002. Model selection and multimodel inference. Second edition. Springer, New York, New York, USA. Daubenmire, R. 1959. A canopy-coverage method of vegetational analysis. Northwest Science 33:4364. Harding, E., E. Crone, B. D. Elderd, J. M. Hoekstra, A. J. McKerrow, J. D. Perrine, J. Regetz, L. J. Rissler, A. G. Stanley, E. L. Walters and NCEAS Habitat Conservation Plan Working Group. 200l. The scientific foundations of habitat conservation plans: a quantitative assessment. Conservation Biology 15:488-500. Meaney, C. A. 2000. Monitoring for Preble's meadow jumping mice along South Boulder Creek and Four Ditches. Boulder, Colorado, USA. Report prepared for the Colorado Division of Wildlife. SAS Institute. 2002. SAS Version 8.2. SAS Institute, Cary, North Carolina, USA. Schorr, R. 200l. Meadow jumping mice (Zapus hudsonius preblei) on the U.s. Air Force Academy, El Paso County, Colorado, USA. Shenk, T. M., and M. Sivert. 1999. Movement patterns of Preble's meadow jumping mouse (Zapus hudson ius preblei) as they very across time and space. Annual Report to the Colorado Division of Wildlife. Fort Collins, Colorado, USA. U. S. Fish and Wildlife Service. 1999. Interim Survey Guidelines for Preble's meadow jumping mouse. U.S. Fish and Wildlife Service. Denver, Colorado, USA. �7 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 PROGRESS REPORT State of_' --!:C~o!.!,;lo~r~a;!:::.do!<._ _ Work Package No. __ ----"-0-"'-67.!....:0~ Task No. ----"- Division of Wildlife - Mammals Research Lynx Conservation _ _ Post-Release Monitoring of Lynx Reintroduced to Colorado Period Covered: January 1, 2001 - December 31, 2001 Author: Tanya M. Shenk, Ph. D. Personnel: A. B. Franklin, L. Gephert, R. Kahn, A. Keith, D. Kenvin, G. Miller, J. Olterman, M. Secor, C. Wagner, S. Wait, G. C. White, D. Younkin Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT , . In an effort to establish a viable population of lynx (Lynx canadensis) in Colorado 96 lynx were reintroduced into southwestern Colorado in 1999 and 2000. Release protocols were evaluated by monitoring released individuals through radiotelemetry. Numbers of mortalities and causes of death were documented and this information used to modify subsequent release protocols in an effort to attain the highest probability of survival for released lynx. In general, release protocols were modified by increasing length of time lynx were kept at the Colorado holding facility, delaying time of release to spring, and releasing non-pregnant females. Mortality due to starvation decreased as earlier protocols were modified. A suite of hypotheses was developed to model early survival and factors that may have influenced survival, including sex, age on capture, pregnancy, time spent in the Colorado holding facility, and release time. Models were evaluated using AICc model selection and model averaging used to estimate survival rates. There have been 39 confirmed deaths. Human-caused mortality factors such as gunshot and vehicle collision are the highest cause of death for lynx> 8 months post-release. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns. Initial dispersal movement patterns and distances traveled by lynx released in 1999 were highly variable and " more extreme than movements of lynx released in 2000. Movement patterns suggest lynx are pairing in March, but successful reproduction has not been documented to date. Snow-tracking results indicate the priniary winter prey are snowshoe hare (Lepus american us) and red squirrel (Tamiasciurus hudsonicus), with waterfowl arid other mammals and birds forming a minor part of the winter diet. Site-scale habitat data collected from snow-tracking efforts indicate Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) are the most common forest stands used by lynx in southwestern Colorado. There is a seasonal trend in use of willows (Salix spp.) with use peaking in November and being at its lowest in May and June. J I, ,~ .. iiiiiilifi BDOW01bb01 ��9 Post-Release Monitoring of Lynx Reintroduced to Colorado Annual Progress Report for the U. S. Fish and Wildlife Service December 2001 Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished Manipulation or interpretation of these data beyond that contained in this report should be labeled as such, and is discouraged Tanya M. Shenk Mammals Research Colorado Division of Wildlife Abstract In an effort to establish a viable population of lynx (Lynx canadensis) in Colorado 96 lynx were reintroduced into southwestern Colorado in 1999 and 2000. Release protocols were evaluated by monitoring released individuals through radiotelemetry. Numbers of mortalities and causes of death were documented and this information used to modify subsequent release protocols in an effort to attain the highest probability of survival for released lynx. In general, release protocols were modified by increasing length of time lynx were kept at the Colorado holding facility, delaying time of release to spring, and releasing non-pregnant females. Mortality due to starvation decreased as earlier protocols were modified. A suite of hypotheses was developed to model early survival and factors that may have influenced survival, including sex, age on capture, pregnancy, time spent in the Colorado holding facility, and release time. Models were evaluated using AICc model selection and model averaging used to estimate survival rates. There have been 39 confirmed deaths. Human-caused mortality factors such as gunshot and vehicle collision are the highest cause of death for lynx >8 months post-release. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns. Initial dispersal movement patterns and distances traveled by lynx released in 1999 were highly variable and more extreme than movements of lynx released in 2000. Movement patterns suggest lynx are pairing in March, but successful reproduction has not been documented to date. Snow-tracking results indicate the primary winter prey are snowshoe hare (Lepus americanus) and red squirrel (Tamiasciurus hudsonicus), with waterfowl and other mammals and birds forming a minor part of the winter diet. Site-scale habitat data collected from snow-tracking efforts indicate Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) are the most common forest stands used by lynx in southwestern Colorado. There is a seasonal trend in use of willows (Salix spp.) with use peaking in November and being at its lowest in May and June. Introduction In an effort to establish a viable population of lynx (Lynx canadensis) in Colorado (Seidel et al. 1998), 41 lynx were reintroduced into southwestern Colorado in the winter and spring of 1999 and an additional 55 lynx were released in April and May of2000. Post-release monitoring of these lynx is crucial to evaluating the progress of this reintroduction effort. The monitoring program also provides information and data critical for improving release techniques to ensure the highest probability of survival for each individual lynx released in the Colorado effort, and perhaps in other reintroduction efforts. The post-release monitoring program for the reintroduced lynx has 2 primary goals. The first goal is to determine how many lynx remain in Colorado and their locations relative to each other. Given this information and knowing the sex of each individual we can assess whether these lynx can form a breeding core from which a viable population might be established. From these data we can also describe general movement patterns and habitats used. The second primary goal of the monitoring �10 program is to estimate survival of the reintroduced lynx and, where possible, determine cause of mortality of reintroduced lynx. Such information will help in assessing and modifying release protocols and management of lynx once they have been released. . Additional goals of the post-release monitoring program for lynx reintroduced to the southern Rocky Mountains include refining descriptions of habitat use and movement patterns, determining hunting habits, and obtaining information on reproduction. When the lynx establish home ranges that encompass their preferred habitat, more emphasis will be placed on refining descriptions of movement patterns and habitat use. Lynx is listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.) (D. S. Fish and Wildlife Service 2000). As a listed species, information specific to the ecology of the lynx in its southern range such as habitats used, movement patterns, mortality factors, survival, and reproduction in Colorado will be needed to develop recovery goals and conservation strategies for this species specific to its southern Rocky Mountain range. Thus, an additional objective of the post-release monitoring program is to develop conservation strategies relevant to lynx in Colorado Objectives The initial post-release monitoring of reintroduced lynx will emphasize five primary objectives: 1. Assess and modify release protocols to enure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival of lynx reintroduced to Colorado. 5. Estimate reproduction oflynx reintroduced to Colorado. Three additional objectives will be emphasized after lynx display site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of lynx conservation strategies in the southern Rocky Mountains. Study Area Five areas throughout Colorado were evaluated as potential lynx habitat (Byrne 1998). Criteria investigated in these 5 areas for comparison were (I) relative snowshoe hare densities (Reed at aI., unpublished data), (2) road density, (3) size of area, (4) juxtaposition of habitats within the area, (5) historical records of fynx observations, and (6) public issues: Based on results from this analysis, the San Juan Mountains of southwestern Colorado were selected as the release area for reintroducing lynx, Ten release sites within the San Juan Mountains were selected based on land ownership and accessability during time of release for the 41 animals released in 1999. Of the 55 lynx released in spring 2000, 45 were released at Rio Grande Reservoir and 10 lynx were released at 3 sites west of the Continental Divide. Based on current locations of the majority of the released lynx, the core research area remains in the southern San Juan Mountains. Methods Reintroduction Effort A total of96 lynx were released at selected areas in the San Juan Mountains of southwestern Colorado (Table 1). Estimated age, sex and body condition were ascertained and recorded for each lynx prior to release (see Wild 1999). Specific release sites were selected based on land ownership and accessibility during times of release. Lynx were transported from the holding facility to the release site in cages (usuallyl, occasionally 2 lynx per cage). Release site location was recorded in Universal �11 Transverse Mercator (UTM) coordinates and identification of all other lynx released at the same location, on the same day, was recorded. Behavior of the lynx on release and movement away from the release site were documented. Table 1. Colorado lynx reintroduction effort. Assessment of Release Protocols Year Females Males TOTAL In 1999, lynx were released under 5 41 22 1999 19 different release protocols (Table 2). Protocol 1 2000 55 20 35 called for the immediate release of females once TOTAL 96 57 39 they passed veterinary inspection in Colorado. Males were to be held for a period of weeks until females established a territory, and then males were to be released near female territories. Four lynx were released under this protocol with poor survival. Protocol 2 was developed whereby lynx were held at the Colorado holding facility for a minimum of3 weeks and fed high quality diets to encourage weight gain. Nine lynx were released under Protocol 2. After a starvation death under Protocol 2, Protocol 3 was developed, requiring the 3-week minimum holding time and high-quality feeding of Protocol 2 plus a release date no earlier than May 1. A spring release would assure that lynx were released when prey was most abundant (i.e., young of the year would be most abundant and hibernating and migratory prey would be available). Twenty lynx were released under Protocol 3. Additionally, 6 females were released under Protocol 3 that were known to be pregnant (Protocol 3P) and 2 that were possibly pregnant (Protocol 3P?). An assessment of the fates of each lynx under all 5 release protocols used in 1999 led to release protocols for lynx released in 2000. Release protocols 2 and 3 resulted in the fewest post-release (up to 8 months after release date) starvation mortalities. The common element in both protocols was increased captivity time in the Colorado holding facility. The single starvation mortality for lynx released under Protocol 2 in 1999 was also the only juvenile released under that protocol and the only animal released in February (the other 8 Protocol 2 lynx were released in March 1999). Thus, all lynx released in 2000 were released under either Protocol 2 or 3 but not before April 1. Because of the high percentage of starvation mortalities in females pregnant on release, we also attempted to avoid reintroducing lynx that were known to be pregnant. This was best accomplished by trying to have animals captured for the reintroduction effort in Canada prior to their breeding season. Table 2. Release protocols for lynx released in southwestern Colorado in 1999 and 2000. Protocol Description 1 Release females as soon as they pass veterinary inspection in Colorado. Release males once females appear to have settled into an area. 2 Release males or females after they have been held in Colorado holding facility for a minimum of 3 weeks and fed a high quality diet. 3 Release males or females after they have been held in Colorado holding facility for a minimum of 3 weeks, fed a high quality diet, and released no earlier than May 1. 3P Pregnant females released under Protocol 3. 3P? Possibly pregnant females released under Protocol 3. To evaluate the efficacy of the changes in release protocols we developed a series of a priori hypotheses concerning factors that affected lynx survival up to 8 months post-release. These factors included (1) the timing of release (winter vs spring), (2) age oflynx released (adults vs. kittens), (3) sex of lynx released, (4) whether or not females were released while pregnant and the interaction of pregnancy and age of the female (adult vs. kitten), and (5) the duration of holding time in the Colorado facility. A series of 11 models were developed using various combinations of these factors. We used �12 AICc (Burnham and Anderson 1998) as the model selection criterion to select the model that best explained the data. Movement Patterns To determine general movement patterns and habitats used by reintroduced lynx, regular locations of released lynx were collected through a combination of aerial, satellite and ground radiotracking. Locations and general habitat descriptions at each location were recorded and mapped. Frequent flights (at least 2 times per week) were critical during the initial post-release periods because of the greater likelihood of dispersal and mortality in reintroduced carnivores during this period. Every effort was made to locate every lynx each flight during this period. All 41 of the lynx released in the winter and spring of 1999 were fitted with Telonics™ VHF radio-collars, equipped with a mortality switch that activates if the collar remains motionless for 4 hours or more. Fifty-one of the 55 lynx released in the spring 2000 were fitted with Sirtrack™ dual satelliteNHF radio-collars (the other 4 lynx were fitted with Telonics™ VHF collars). These collars also had a mortality indicator switch that operated on both the satellite and VHF mode. The satellite component of each collar was programmed to be active for 12 hours per week. The 12-hour active periods were staggered throughout the week, with approximately 7 collars being active each day of the week. Signals from the collars allowed for locations of the animals to be made via Argos, NASA, and NOAA satellites. The location information was processed by ServiceArgos and distributed to the CDOW through e-mail messages. Survival and Mortality Factors When a mortality signal (75 ppm vs. 50 ppm for the Telonics™ VHF transmitters, 20 bpm vs. 40 bpm for the Sirtrack™ VHF transmitters, 0 activity for Sirtrack™ PTT) was heard during either satellite, aerial or ground surveys, the location (UTM coordinates) was recorded. Ground crews then located and retrieved the carcass as soon as possible. The immediate area was searched forevidence of other predators and the carcass photographed in place before removal. Additionally, the mortality site was described, habitat associations, and exact location were recorded. Any scat found near the dead lynx that appeared to be from the lynx was collected. All carcasses were transported immediately to the Colorado State University Veterinary Hospital for a post mortem exam to 1) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, and 3) archive samples for future reference (research or forensic). The gross necropsy and histology were performed by, or under the lead and direct supervision of a board certified veterinary pathologist. At least one research personnel from the Colorado Division of Wildlife involved with the lynx program was also present. The protocol followed standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing (see Shenk 1999 for details). Some additional data/samples were routinely collected for research, forensics, and archiving, Other-data/samples were collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). The CDOW retained all samples and carcass remains with the exception of tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, and other diagnostic samples. Survival rates of lynx reintroduced to Colorado were estimated using the Kaplan-Meier method with staggered entries (Pollock et al. 1989) in Program MARK (White and Burnham 1999). Recaptures Recaptures were attempted on lynx that were either in poor body condition or need to have their radio collars replaced. Methods of recapture included trapping using a Tomahawk™ live trap baited with a rabbit, and darting lynx with Telazol (3 mg/kg) using a Dan-Inject CO2 pistol (modified from Poole et al. 1993 as recommended by M.Wild, DVM). Hounds trained to pursue felids were also used to tree lynx for capture. Treed lynx were immobilized with Telazol or medetomidine (0.09mg/kg) and �13 ketamine (3 mglkg) administered intramuscularly (1M) with either an extendible pole-syringe or a pressurized syringe-dart fired from a Dan-Inject air pistol. Immobilized lynx were monitored continuously for decreased respiration or hypothermia. If lynx exhibited decreased respiration Zmg/kg of Dopram was administered under the tongue. If respiration was severely decreased, the animal was ventilated with a resuscitation bag. If medetomidinelketamine were the immobilization drug, the antagonist Antisedan was administered. Hypothermic (body temperature < 95° F) animals were warmed with hand warmers and blankets. While immobilized, the lynx were fitted with a replacement VHF/satellite collar and blood and hair samples were collected. Once the animal was processed recovery was expedited by injecting the antagonist Antisedan 1M if medetomodinelketemine was used for immobilization. The lynx was monitored until it was sufficiently recovered to move safely on its own. No antagonist is available for Telezol so lynx anesthetized with this drug were monitored until the animal recovered on its own. If captured and in poor body condition the lynx was anesthetized with Telezol (2 mglkg) and returned to the Colorado holding facility for rehabilitation. Reproduction Reproductive status of all female lynx was determined prior to release through radiographs. Pregnancy was confirmed through radiographs if the bones of the fetuses had begun to ossify. All females known to be pregnant or thought to possibly be pregnant on release were monitored closely from their release through the following August to determine reproductive success. Females remaining within a limited area immediately after release through August were located and observed to look for accompanying kittens or a den site. Females that had been released in 1999 and were alive in spring 2000 were monitored for proximity to males during breeding season and for site fidelity to a given area during the denning period of May and June 2000. Each female lynx from the 1999 releases was directly observed in summer 2000 over 3-5 different visits to look for accompanying kittens or evidence of denning. Each female alive in May 2001 that exhibited stationary movement patterns in June 2001 was observed in summer or fall 2001 to look for accompanying kittens. Females were also snow-tracked in winter months to look for accompanying kitten tracks. Hunting Behavior Snow-tracking of released lynx provided preliminary information on hunting behavior by documenting location of kills, food caches, chases, and diet composition estimated through scat analysis. Snow-tracking was conducted during February-May 1999 (Year 1), November 1999 - May 2000 (Year 2), and November 2000 - April 2001 (Year 3). Prey from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. Scat samples were collected wherever found and labeled with location and individual lynx identification. Only part of the scat was collected, the remainder was left where found so as not to interfere with the possibility that the scat was being used by the animal as a territory mark. Habitat Use Gross habitat use was documented by recording canopy vegetation at aerial locations. More refined descriptions of habitat use by reintroduced lynx were obtained through snow-tracking and sitescale habitat data collection. Specific objectives for the site-scale habitat data collection included: 1. Describe and quantify site-scale habitat use by lynx reintroduced to Colorado. 2. Compare site-scale habitat use among types of sites (e.g., kills vs. long-duration beds). 3. Compare site-scale habitat use between sexes. 4. Compare habitat use over years. 5. Develop methodology that will result in data that will be comparable to data collected in studies investigating the ecology of snowshoe hare in Colorado. �14 Snow-tracking Locations from aerial- and satellite-tracking were used to help ground-trackers locate lynx tracks in snow. Snowmobiles, where permitted, were used to gain the closest possible access to the lynx tracks without disturbing the animal. From that point, the tracking team used snowshoes to access tracks. Once tracks were found, the ground crew back- or forward-tracked the animal if it was far enough away not to be disturbed. Back-tracking generally avoided the possibility of disturbing the lynx by moving away from the animal rather than towards the animal. However, monitoring of the lynx through radiotelemetry was used to assure that the ground crew was staying a sufficient distance away from the lynx in the event the lynx might double back on its tracks. Radio-telemetry was also used in forward-tracking to make sure the team did not disturb the animal. If it appeared the lynx began to move in response to the observers, the observers stopped following the tracks. If the lynx began to move and the movement did not appear to be a response to the observers, the ground crew continued following the track. An attempt was made in Year 1 and Year 2 to track each lynx. In Year 3 we attempted to track all lynx within the Core Release Area. Ground crews were instructed to track lynx only where it was safe to travel. Restrictions to safe travel included avalanche danger and extremely rugged terrain. Ground crews worked in pairs and were fully equipped for winter back-country survival. Data Collection For each day of tracking the date, lynx being tracked, slope, aspect, UTM coordinates, elevation, general habitat description, and summary of the days tracking were recorded. Aspect was defined as the direction of 'downhill' or 'fall line' on a slope. This is the direction along the ground in a dihedral angle between the horizontal and the plane of the ground surface. Units were compass direction that most closely defined the cardinal points (e.g., N, NW, etc.). Slope was defined as the dihedral angle between the horizontal and the plane of the ground surface (e.g., 45° ). There were 4 levels of intensity of human activity recorded. They included: 1. None: track was not found off an existing snowmobile, ski, or snow shoe track. Distance to nearest human track is greater than 1.0 km 2. Low: track was found near low human activity (e.g., existing snowmobile or ski track) 3. Medium: track found near medium human activity (detected the presence of other people in the area during tracking effort). 4. High: track found near high human activity (e.g., detected presence of many people nearby, near major road, near housing). There were 2 categories for recording detection of tracks of other species. They included "M" for tracks from multiple animals of the same species and "T" for detection of tracks of only a single animal of the species. Once a track was located there were 2 types of 'sites' that were encountered. Site I areas needed documentation but either did not reflect areas lynx selected for specific habitat features, or sites that occurred too frequently to measure each in detail. Site II areas were places where lynx may have selected habitat features. At each of the 2 types of sites the date, lynx tracked, slope, aspect, forest structure class, UTM coordinates, and elevation was recorded. Forest structure classes included grass/forb, shrub/seedling, sapling/pole, mature, and old growth as defined in Table 3. For Site I areas, the only additional data that was collected was identification of what the site was used for (e.g., short-duration .bed), and a brief description of the site. These sites included the start and end of the track being followed, the location of scat, and short-duration beds defined as being small in size (approximating an area a lynx would crouch), and with little ice formed in the bed indicating little time spent there. The Site II areas included areas that might reflect specific habitat features lynx selected for. These sites required habitat sampling (see below) and included locations where the following were found: kills, start of chases, territory marks (e.g., spray sites, buried scat, scat placed on prominent locations), long-duration beds (encompasses an area where a lynx would have lain for an extended period, iced bottom), travel (ifno other sites sampled in last hour), and road crossing (both sides of road). �15 Table 3. Definitions of forest structure classes used to describe habitat sites (Thomas 1979). Forest Structure Class Definition Grass/forb The grass/forb stage is created naturally by a catastrophic event, such as wildfire, and is typified by the near complete absence of snags, litter or down material in the aspen and ponderosa pine types, or vice versa in the lodgepole or subalpine forest types. Shrub/seedling The shrub/seedling stage occurs when tree seedlings or shrubs grow up to 2.5 ern at diameter breast height (DBH), either naturally or artificially through planting. Sapling/pole The sapling/pole stage is a young stage where tree DBH's range from 2.5-17.5 em with tree heights ranging 1.8-13.5 m. These trees are 5-100 years of age, depending on species and site condition. Mature The mature stage occurs when tree diameters reach a relatively large size (25-50 em) and the trees are usually 90 or more years old. Forest stands begin to experience accelerated mortality from disease and insects. Old-growth The old-growth stage occurs when a mature stand is at advanced age (100 years for aspen or 200 years for spruce), is very slow growing, and has advanced degrees of disease, insects, snags, and down, dead material. An exception to this occurs in ponderosa pine and aspen types where these old-growth stands typically experience low densities of down dead material or snags. Description of the Habitat Plot A habitat sampling plot was completed wherever a Site II was encountered. The habitat plot consisted of a 12 m x 12 m square defined by a series of 25 points placed in 5 rows of 5 with the center point being on the object that defined the site (e.g., a kill) (Figure 1). Each point was 3 m apart. The 12 m x 12 m sampling square exceeded the minimum requirement of 0.01 ha. Recommended by Curtis (1959) for sampling trees. Measurements taken at each of the 25 points included: 1. Snow depth - measured vertically by an avalanche probe marked in cm. f················6·-------fj------Tg··------ir--·1 2. Understory - measured from top of snow to 150 cm above snow in a column of 3-cm radius t t around the avalanche probe. Because understory t t ~ t measurements were influenced by vegetation outside the perimeter of the 25 sampling points (12 m x 12 t ~ t m) the area used for estimating undersory cover was t 15 m by 15 m. At each point, crews recorded all shrubs, trees and coarse woody debris (CWD) that fell within this column and was visible above the 12 m snow. Crews also recorded number of branches of 15 m each species that fell within the column at 3 different height categories (0-0.5 m, 0.51-1.0 m, 1.01-1.5 m). 3. Overstory: measured at 150 cm above snow with a sighting tube. The tube was made of PVC pipe, with a curved viewing end and a crosshair made of wire on the opposite end. The sighting tube Figure 1. Design of site-scale habitat sampwas attached to the avalanche probe used to measure ling plot. Each point was 3 m apart. The object snow depth. Species that hit the crosshair were that triggered the habitat sampling (e.g., a kill) recorded at each of the 25 points in the vegetation was located at the center point. plot. Ganey and Block (1994) found this method of -- - •• -.-. - -.-.- �16 measuring canopy cover (with z 20 sample points per plot; Laymon 1988) provided greater precision among observers. 4. Species composition: all the different species of tree or shrub that hit. the crosshair of the sighting tube at each of the 25 points were recorded. . Tree composition of the vegetation plot was recorded by species and diameter at breast height (DBH). Snow depth was used in conjunction with this recorded DBH to estimate true DBH. Within the 12 m x 12 m square all conifers and deciduous trees were recorded by DBH size class (A = 0-15 cm, B = 15.1-30 ern, C = 30.1-45 em, D = 45.1-60 cm, E = »60 ern). Area for the tree composition analysis was 12 m x 12 m. Understory was estimated as: (1) percent occurrence within the vegetation plot (number of points with understory/total number of points surveyed) and (2) mean percent occurrence and variance by species and height category over the total points sampled within the vegetation plot. Overstory was estimated as percent occurrence over the vegetation plot (number of points with overstory/total number of points surveyed). Results Assessment of Release Protocols A total of 41 lynx were released in Colorado in 1999 under 5 different release protocols (Table 2). Release protocols were modified as new information became available from monitoring the released lynx through radio-telemetry and snow-tracking. Each modification of the release protocols decreased the percent of animals dying from starvation (Table 4). Three of the 4 animals released under Protocol 1 died of starvation within 6 weeks of their release and the fourth was recaptured and returned to the holding facility where she recovered and was later re-released. Reevaluation of the condition of animals released under the Protocol 1 suggested that these animals might not have been in optimal physical condition when released. Therefore, Protocol 2 was initiated. Most lynx gained considerable body weight while in captivity (Wild 1999). Nine lynx were released under this second protocol. Of these, 1juvenile female died of starvation 7 weeks after release. After the starvation death under Protocol 2, Protocol 3 was developed (3-week minimum holding time, high quality diet, no release prior to May 1). Twenty lynx were released under Protocol 3 with no starvation deaths of these animals occurring within 6 months post-release. Six females were released under Protocol3P (known to be pregnant) and 2 under Protocol3P? (possibly pregnant). Two ofthe 6 pregnant lynx released died of starvation within 6 months post-release. An assessment of the fates of each lynx under all 5 release protocols used in 1999 led to release protocols for lynx released in 2000. Release Protocols 2 and 3 resulted in the fewest starvation mortalities up to 8 months after release date. The common element in both protocols 2 and 3 was increased captivity time in the Colorado holding facility. The single starvation mortality for lynx released under Protocol 2 in 1999 was also the only juvenile released under that protocol and the only animal released in February (the other 8 Protocol 2 lynx were released in March 1999). Thus, all lynx released in 2000 were released under either Protocol 2 or 3 but not before April 1. Because of the high percentage of starvation mortalities in females pregnant on release, we also attempted to avoid reintroducing lynx that were known to be pregnant. This was best accomplished by trying to have animals captured for the reintroduction effort in Canada prior to their breeding season. A series of 11 models (Table 5) were developed using various combinations of the hypothesized factors that may have affected survival up to 8 months post-release: (1) whether the release was in winter or spring (ReI), (2) whether the released lynx was an adult or kitten (age), (3) sex of lynx released (sex), (4) whether or not females were released while pregnant (preg) and the interaction of pregnancy and age of the female (adult vs. kitten), and (5) the duration of holding time in the Colorado facility (DCF). Survival time and DCF were modeled with and without a log transformation (Ln) because of possible threshold effects over time. We used AICc as the model selection criterion to select the model that best explains the data (Table 5). The model that best fit the data was {S(age+preg+Rel+LnT +LnDCF}, �17 which suggested pregnancy had a deleterious effect on survival of females, with the effect being stronger on kittens than adults (Figure 2). This model also indicated that winter releases led to higher mortality than spring releases for both non-pregnant kittens (Figure 3) and non-pregnant adults (Figure 4), with no sex effects on either age class. Lastly, long stays in the Colorado holding facility increased survival if the duration was at least 21 days with no significant decrease or increase in survival for stays longer than 21 days (Figures 2,3,4). Table 4. Starvation mortalities and recaptures of poor body condition lynx reintroduced to Colorado under the 5 release 2rotocols over 2 years. Number of. Starvation Mortalities 75 Number of Recaptures in Poor Body Condition % Failure of Release Protocol Release Protocol Year Total Number Released 1 1999 4 2 1999 9 3b Ie 11 0 11 2 0 2 3 % Mortality 3 100 2 2000 41 Ie 3 1999 20 0 0 0 0 3 2000 10 0 0 0 0 3P? 1999 2 0 0 0 0 3P? 2000 3 0 0 0 3P 1999 6 0 2d 33 33 3P 2000 1 0 0 0 '0 0 within 8 months of release. b 1 juvenile, 2 adults. juvenile. d adults. 3 C Table 5. Model selection results of the a priori models concerning the effects of age, sex, pregnancy, season of release, and amount of time spent in the Colorado holding facility on survival of lynx 8 months 2ost-release. Ranking based on AICc values. #. AlCc Model AICc Weight Pars. Deviance l>.AICc {S(age+preg+Rel+LnT+LnDCF} 200.120 0 0.28305 6 188.036 {S(age*preg+Rel+LnT+LnDCF} 201.027 1.91 0.10908 7 187.914 {S(age+preg+Rel+ T+LnDCF} 202.702 2.58 0.07784 6 190.618 {S(age+preg+Rel+ T+T2+LnDCF} 203.225 3.10 0.05993 7 189.113 {S(age+Rel+preg+LnDCF} 203.266 3.15 0.05871 5 193.206 {S(age+preg+Rel+T'+T2'+LnDCF} 204.069 3.95 0.03930 7 189.957 {S(age+preg+Rel+T"+T2"+LnDCF} 204.936 4.82 0.02547 7 190.824 {S(age*preg +Rel+LnDCF} 205.265 5.14 0.02161 6 193.181 {S(age*Rel+preg+LnDCF} 205.289 5.17 0.02135 6 193.205 {S(age+Rel+preg+DCF} 205.609 5.49 0.01819 5 195.549 {S(age+Rel+preg+DCF+DCF2} 205.760 5.64 0.01687 6 193.676 .•.. : �18 -; Adults Kittens > 'E = IJ.l •• > ::: ~ :; e = u Two-week Interval Figure 2. Effects of pregnancy and time spent in the Colorado holding facility on survival of pregnant kittens and adult females. Winter Release Spring Release Two-week Interval Figure 3. Effects of release season and time spent in the Colorado holding facility on survival of non-pregnant kittens. Winter Release Spring Release Two-week Interval Figure 4. Effects of release season and time spent in the Colorado holding facility on survival of non-pregnant adults. �19 Movement Patterns A total of2,158 aerial VHF locations for all 96 reintroduced lynx have been collected to date (Figure 5, Figure 6). An additional 4,020 satellite locations (1,375 satellite locations if multiple locations for a single night were averaged and counted as only 1 location) for 49 of the 51 lynx fitted with dual collars have been collected. Two satellite collars never worked after the lynx were released. The majority of movements in 1999 away from the an area encompassed by alOO-km radius area centered on the release sites (Core Release Area) were to the north (Figure 5), although some movements occurred to the south into New Mexico and west into Utah as well. A single male from the 1999 releases traveled to Nebraska where he was shot in violation of Nebraska regulations. Initial dispersal habitats used by lynx released in 1999 were highly variable, from high elevation Engelmann spruce/subalpine fir to Nebraska agricultural lands. Dispersal movement directions for lynx released in 2000 were similar to those of lynx released in 1999 (Figure 6). Most movements away from the Core Release Area were to the north. However, more animals remained within the Core Release Area. Numerous travel corridors have been used repeatedly by more than one lynx, possibly suggesting route selection based on olfactory cues. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-SilvertonLizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast through the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. Such movement patterns have also been documented by native lynx in Wyoming and Montana (Squires and Laurion 1999). Most lynx currently being tracked are within the Core Release Area (Figure 7). Mortalities occurred throughout the areas through which lynx moved. However, mortalities occurred in New Mexico in higher proportion to all lynx locations in that area than elsewhere (Figure 8). Survival and Mortality Factors Of the 96 lynx released, 39 mortalities have been recorded to date. From the 1999 releases (41 animals) we have had 24 known mortalities (Table 6). From the 2000 releases (55 animals) we have 15 known mortalities (Table 6). Of the total 9 confirmed starvation deaths, 3 were associated with animals released in less than ideal body condition (released under Protocol 1) and 2 were lynx less than l-year old (Table 4). Fourteen of the mortalities died of unknown causes. In 4 of these cases starvation could be ruled out as cause of death by evidence of good body condition through examination of bone marrow. Pneumonic plague could be ruled out in all 14 cases. Delayed retrieval of carcasses resulted in advanced deterioration of the body, making determination of cause of death impossible. Necropsy results for 3 female lynx released in 2000, indicate they died from pneumonic plague. Two of these lynx were in good condition, with abdominal fat, no muscle wasting, and fat in the bone marrow. The only gross lesions were an acute fibrinous pneumonia (i.e., lung infection of short duration). These lynx had probably only been sick a few days before they died. A third female was In poorer body condition when found. Plague was diagnosed by flourescent antibody tests and isolation of Yersinia pestis from lung and spleen samples. A fourth lynx was also diagnosed with plague after she was hit by a car. A male lynx, recaptured near Laramie, Wyoming, tested positive for plague titers but did not have active plague. Thus, he had been exposed to plague but either did not contract the disease or recovered from the disease. Recaptures Seven lynx have been recaptured and 6 subsequently re-released since their initial release. Lynx BC99F6 was released in 1999 under Protocol 1. Her behavior and incidental sightings by the public suggested the lynx was in poor condition. We trapped her using a Tomahawk™ live trap baited with rabbit. She was recaptured the first night (March 25, 1999) we set the trap. On capture, we found she was severely emaciated. We anesthetized her with Telezol (2 mglkg) and returned her to the Colorado holding facility. She was rehabilitated through diet. The lynx gained weight steadily and was re-released on May �20 .•. locations of lynx .Released in·1999 /\/HighWoYS . .. Ie] Colorado -Counties [=:J t.e~ M~~.ico Counti~ f····--1 Wyoming Counties NHebraskll CountieS .. • s _- 300 o Figure 5. Locations oflynx released in 1999, obtained through aerial telemetry. 600 Kilometers �21 ~ .•. I -""'-' •. .:' /\/ of. in YH rtocattonslynx released 2000 .prJ 'locations of lynx relea~ed.ln 2'000 Highways: ·Co).mties li New MeXico Courifies i - . i Wyoming',Counties • c::J'·C.olo"rado N .~eb_ra~ka:C,ounti~ ./>..../ Utah .C~\Jnti~s :.N W*E s _- 300 o 300 600 .Kilometers Figure 6. Locations of lynx released in 2000. Gray circles indicate locations obtained from satellite collars. Black circles are locations obtained through aerial telemetry. �22 Last Known Locati,ons • alive • collar off .A missing /\/ Highways ..... , ~.olorado counties if New Mexico'Counlies o '--' r A " I J '""Y~ I : r--r-~-, I ,I ~ I r-' ' \ i \ ! .. , i \ s I ! rl .r I ii .. _,- o I .~ _-r- ! ' I I '\_r-,~_:j .1 300, \ 1 I , .J J h~~-rY-.f-.T\]:f, I I f \ r. ., _,!-ri 300 600 Kilometers Figure 7. Last known locations of lynx. Circles depict locations of lynx currently being tracked. Triangles are last known locations of missing lynx. �23 • l,'; -Mortality'location's of lynxr elea.sed-In 2000· ., 'Mort.~Jj_ty·:locations.of_l_ynx released-in .1999' /\/Highways " CJ .cctcracc -ccurrtles 'c:J ~,~w.Mex.ico· Counties N: W*.·.···.. E . .' s Figure 8. Locations oflynx mortalities. Circles depict mortalities oflynx released in 1999, triangles depict mortalities from lynx released in 2000. I �24 Table 6. Causes of death for lynx released into southwestern Colorado in 1999 and 2000. 1999 1999 2000 2000 2000 Cause Male Female Male Female Unknown Starvation 6 1 1 1 Road-kill 2 2 1 2 Shot 1 1 Human-caused a 1 1 Trauma - unknown cause 1 Possible predation 1 Plague 3 Unknown 2 3 2 2 Unknown - not starvation b 1 2 1 Total Mortalities 17 4 10 1 7 Total 9 5 5 2 1 1 3 9 4 39 a Cut collar found, no carcass. b Starvation ruled out by condition of bone marrow. 28, 1999. She was hit by a car on Interstate 70 on July 19,1999. Necropsy results indicated she was in excellent body condition at her time of death. Lynx AK99M9 was released on May 12, 1999 and recaptured on March 24, 2000. Field observations by the lynx monitoring crew suggested that the lynx was severely emaciated. Live-trapping the lynx failed, so the lynx was darted with Telazol (3 mg/kg) using a Dan-Inject CO2 pistol. Physical examination revealed severe emaciation (6 kg). The lynx was returned to the Colorado holding facility and rehabilitated through diet. The lynx gained weight steadily and was re-released on May 3, 2000 but has not been located since and is listed as missing. Lynx AK99F2 was released on May 7, 1999 and recaptured on April 18,2000. Field observations by the lynx monitoring crew suggested that the lynx was emaciated. She was live-trapped with a Tomohawk™ live trap with one night's effort. On capture, we found she was emaciated. We anesthetized her with Telezol (2 mg/kg) and returned her to the Colorado holding facility. She was rehabilitated through diet. The lynx gained weight steadily and was re-released on May 22,2000. This lynx is currently in the Core Release Area. Lynx BCOOF7 was released on April 2, 2000 and recaptured on February 11,2001. She was severely emaciated and was captured by anesthetizing her with Telazol delivered IM by a jab-pole. She was returned to the Frisco Creek Wildlife Rehabilitation Center but died that night from emaciation and hypothermia. Lynx BCOOM13 was released on April 2, 2000 and recaptured on March 21, 2001 near Laramie, Wyoming. He had been observed by ahomeowner on his porch. We recaptured the lynx because this type of behavior was not considered normal. On examination he was in good body condition. After a period of observation this lynx was re-released at the Rio Grande Reservoir on April 24, 2001. This lynx . had previously been listed as one of our 15 missing lynx as he had not been located since Sept 2000. This lynx is currently in the Core Release Area Lynx YK99F5 was recaptured on Apri119, 2001 to have her radio collar changed. She was captured in a live trap baited with one of her own kills. She was in very good body condition. We anesthetized her with Telazol (3mg/kg), processed and released her on the same site where she was captured. Only her cut collar was found on October 17, 2001, cause of death is assumed human-caused. Lynx AK99F5 was treed by hounds and anesthetized with Telazol (3 mg/kg) on September 2, 2001. Her collar was exchanged, hair and blood samples were collected. She was in very good body condition and showed no evidence of lactation. She was re-released on the site she was recaptured once she recovered from the Telazol. This lynx remains in the same area as her recapture, within the Core Release Area. �25 Reproduction Six lynx released in 1999 were known to be pregnant (Table 2, Release Protocol 3P), and 2 other females released may have been pregnant (Table 2, Release ProtocoI3P?). Three of the 6 lynx known to have been pregnant on release in 1999 died within 2 months after release: 2 starved and 1 was killed on the road. Long-distance movements and lack of stationary movement patterns of the other 3 lynx known to have been pregnant on release in 1999 suggests these females did not have young with them by July 1999. Of the 2 females that might have been pregnant, movement patterns were not suggestive of a female rearing young. It is not known if any other females bred and/or had young once released, however no females snow-tracked in Year 2 had young with them. Beginning in March 2000 both male and female lynx began to exhibit extensive movements (> 100 km) away from areas they had used throughout the winter. For example, 1 male moved from the area near Frisco he used in the winter to the area west of Lizardhead Pass, a straight line distance of approximately 270 km (Figure 9). Such movements by both females and males put them in close « 5 km) proximity to a lynx of the opposite sex. These extreme movements may have been related to breeding behavior. All 7 females alive in spring 2000 were documented in close « 5 km) proximity to a male during the breeding season and could have bred. Two isolated males did not move during March or April and thus were not in close proximity to a known female during the breeding season. This was a male that had used the area in and adjacent to the northwest comer of Rocky Mountain National Park and a male that used the area around Cuchara, Colorado throughout the winter. The 7 females in the wild during breeding season 2000 were monitored for site fidelity to a given area during the denning period of May and June. Each of these 7 females was directly observed in summer 2000 over 3-5 different visits to look for accompanying kittens. No kittens were found. The question of whether they successfully bred or had kittens at some point in 2000 is unknown. However, no kittens were found during the following winter through snow-tracking. From radiographs taken of the 35 females released in 2000, after breeding season, 1 female was known to be pregnant and 3 were possibly pregnant. Movement patterns suggested none of these 4 females had kittens with them by July 2000. Of the 49 lynx being tracked on a regular basis during the March 2001 breeding season, there were 29 females and 20 males. We documented movements that may have been related to breeding. The largest movement observed was a male that moved to Laramie, Wyoming and was subsequently recaptured, rehabilitated and re-released in the Core Release Area in Colorado after the breeding season. Other movements were of a much smaller scale, 10-30 km. These movements were primarily movements of males towards a female. We documented 10 potential 'pairs' where a pair was defined as a male and female within 5 km of each other and in the same drainage. More pairs could have occurred which we did not document from aerial- or ground-tracking because of the time delays between lynx locations. To date, no reproduction has been documented in 2001 from direct observations of females. Snow-tracking efforts this winter will focus initially on females in an attempt to document possible kittens through tracks. Current Status Of the total 96 lynx released we have 39 known mortalities (Table 7). We currently are listing 16 lynx as missing - 11 males, 5 females. We have not heard signals on 13 (11 males, 2 females) of these lynx since at least December 2000. The remaining 3 missing lynx are females that have been lost for less than 1 year. Possible reasons for not locating these missing lynx include (1) long distance dispersal, beyond the areas currently being searched, (2) radio failure, or (3) destruction of the radio (e.g., run over by car). We continue to search for all missing lynx during both aerial and ground searches. There have been 4 incidents where lynx missing for over a year have returned to the Core Release Area and are now once again being monitored on a regular basis. Thus, it is premature to consider missing lynx as lost to the Colorado lynx program. However, of the 16 missing lynx, 3 have collars whose battery life expired spring 2001 and will probably never be located through telemetry. At least 1 of the missing lynx is a mortality where we know a collar was found on a road kill but the collar was not returned to the �26 1\/ Highways C:::J Colorado' Counties Lynx YK99M3 Movements 19990513 - 19990521 19990521 - 19990715 19990715 - 19990923 19990923-19991027 • 19991027 - 19991229 Ii 19991229 - 20000229 • 20,OOO~2~- 20000329 • 20000329 - 20000512 N W*E s _- 300 300 600 Kilomete Figure 9. Movements of a male lynx in breeding season 2000. Straight-line distance from winter use area to the area used during breeding season in approximately 270 km. The larger the circle the more recent the date, up to May 2000 �27 CDOW for identification. tracking 41 lynx. One female is known to have slipped her collar. Thus, we are currently Table 7. Current status of lynx reintroduced to Colorado. Females Males Unknown Released 57 39 Known Dead 27 11 1 Missing 11 5 Slipped Collar Tracking 24 17 a 1 is unknown TOTAL 96 39 16" 1 41 mortality. Hunting Behavior Snow-tracking of released lynx provided preliminary information on hunting behavior by documenting location of kills, food caches, chases, and through scat analysis. Prey from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. During Year 1 a total of 10 kills were located. All the snow-tracking effort was conducted on 9 lynx released under Protocols 1 and 2. Any lynx released under Protocol 3 were released too late to track. In Year 2, ground crews tracked 13 of the lynx released in 1999. Two other lynx were being located during this time but were not in areas covered by snow. We found 64 kills and collected 109 scat samples that will be analyzed for content. Lynx released in 2000 were released too late to snow track in Year 2. In Year 3, field crews snow-tracked 48 lynx, documented 86 kills and collected 189 scat samples. Data collected on kills (Figure 10) suggests the reintroduced lynx are feeding on their preferred prey species, snowshoe hare (Lepus american us) and pine (red) squirrel (Tamiasciurus hudsonicus) in similar proportions as those reported for northern lynx during lows in the snowshoe hare cycle (Aubry et aI., 1999). Caution must be used in interpreting the proportion of identified kills. Such a proportion ignores other food items that a~e consumed in their entirety. For example, through snow-tracking we have some evidence that lynx are mousing and several of the fresh 70 carcasses have yielded small mammals in 60 the gut on necropsy. 11211999 Eil1999-00 .2000-01 I However, the extent of small == 50 :2 mammals in the diet are not accurately ~ 40 portrayed by information collected based •• ~ 30 on prey remains in snow. Nearly all the E scat samples collected have been found 20 Z through snow-tracking efforts and thus will 10 be representative of winter diet only. The summer diet of lynx elsewhere has been o documented to include less snowshoe hare Snowshoe Red Cottontail Other and more alternative prey than in winter hare squirrel (Mowat et aI. 1999). = Spe cie s Habitat Use Gross habitat use was documented from 2441 aerial locations of lynx Figure 10. Winter diet of reintroduced lynx estimated from snow-tracking data. �28 collected from February 1999 through December 2001. Throughout the year 80 Engelmann spruce (Picea engelmannii) 70 / subalpine fir (Abies lasiocarpa) (SIF) was the dominant cover used by lynx = 60 .~ (Figure 11). A mix of Engelmann 50 ~ tJ spruce, subalpine fir and aspen 0 ~ 40 (Populus tremuloides) (SIF/A) was the =~tJ 30 second most common cover type used ••~ throughout the year. Various riparian p.. 20 and riparian mix areas was the third 10 most common cover type where lynx were found during the daytime flights. 0 Use ofSIF and SIF/A was similar J J A SON D J F M A M throughout the year. There was a trend Months in increased use of riparian areas beginning in July, peaking in NovemS/F Ii8iI S/F/A • Riparian ber, and dropping off December through June. Figure 11. Percent aerial locations in Engelmann spruce A total of 473 site-scale habitat SUbalpine fir forests (SIF), Engelmann spruce- subalpine firplots were completed in Year 3. The aspen forests (SIF/A), and riparian areas by month. majority understory species at all 3 heights was Engelmann spruce, followed by subalpine fir, willow (Salix spp.) and aspen (Figure 12). Various other species such as Ponderosa pine (Pinus ponderosa), lodgepole pine (Pinus contorta), cottonwood (Populus sargentii), birch 100 (Betula spp.) and others were also found in less than 5% of the habitat 90 IIlElLOW llilMEDIUM .HIGH I plots. Coarse woody debris was also 80 present in 10-35% of plots. If present, 70 willow provided the greatest percent cover within a plot (Figure 13) 60 ~ followed by Engelmann spruce, 50 ,_tJ ~ subalpine fir, aspen and coarse woody ~ 40 debris. 30 Engelmann spruce provided a mean of 35.87 % overstory within 20 86.68% of the plots (Figure 14). 10 Subalpine fir and aspen provided overstory for < 50% of the plots, but ES SF cwo WI AS LO when present provided approximately Species the same mean percent cover as Engelmann spruce (Figure 14). Willow and lodgepole pine provided fewer than 10% of the plots with Figure 12. Mean percent cover of habitat plot by understory cover, but when present provided tree/shrub species Engelmann spruce (ES), subalpine fir (SF), nearly the same percent cover as the willow (WI), aspen (AS), lodgepole pine (LO), and coarse other tree species (Figure 14). woody debris (CWD) if species is present. Mean percent The most common tree species cover is estimated for 3 height levels above the snow (low = in the habitat plots was Engelmann 0-0.5 m, medium = 0.51-1.0 m, high = 1.1-1.5 m). fIl - - I_ -= I �29 50 45 IBLOW MEDIUM .HIGH I 40 35 30 C '.'"".. 25 Po. '" 20 15 10 5 0 ES SF CWD WI AS LO Species Figure 13. Mean percent cover of habitat plots by understory tree or shrub species Engelmann spruce (ES), subalpine fir (SF), willow (WI), aspen (AS), lodgepole pine (LO), and coarse woody debris (CWD) if species is present. 100 90 80 70 lEI ES 60 C .. ".'".. ImEs Snag .SF DSF Snag .AS .AS Snag so c.. 40 .WI 30 IEILO 20 10 0 Percent Plots With These Species Mean Percent Cover if Species Present Figure 14. Percent plots with overstory tree species Engelmann . spruce (ES), subalpine fir (SF), willow (WI), aspen (AS), lodgepole pine (LO), and coarse woody debris (CWD). Mean percent overstory cover if tree species present. spruce (Figure 15). Subalpine fir and aspen were also present in> 35% of the plots. Most habitat plots were vegetated with trees ofDBH < 6" (Figure 15). As DBH increased, percent occurrence decreased within the plot. The larger DBH trees (> 18") within the plots were generally Engelmann spruce with fewer subalpine firs of that DBH class present in the habitat plots. No willow or aspen of DBH> 18" were present in any of the plots. Of the 5 most common tree species in the habitat plots, mean number of trees for each DBH size class ranged from 0.18 to 10.82. except for willow which averaged 74.83 plants per plot (Figure 16). Areas of willow used by lynx are typically dense willow thickets. Discussion Of the 96 lynx released in Colorado in 1999 and 2000 we are currently monitoring 41 lynx on a regular basis and an additional 16 lynx may still be alive, although not being monitored. We have 39 confirmed mortalities. Survival of lynx released in the second year has been higher than lynx released in the first year. Human-caused mortalities due to vehicle collision, gunshot, and the mortalities where only a cut collar was found comprise the greatest known cause of mortality for the reintroduced lynx (31 %). Mortalities due to starvation (23%) were minimized with improved release protocols. Only 2 of the 55 lynx released in 2000 died of starvation and 1 of those �30 died 8.5 months post-release. Three lynx died of plague, 1 road kill tested positive for plague, and 1 lynx had plague positive titers while healthy. Carnivores are most often exposed to plague by eating infected rodents or by being bitten by rodent fleas (Biggens and Kosoy 2001). Although it is known that felids are highly susceptible to plague (Aiello 1998), the 5 cases of plague in lynx reintroduced to Colorado are the first documented for this species. Dispersal movement patterns for lynx released in 2000 were similar to those of lynx released in 1999. However, more animals remained within the Core Release Area. This increased site fidelity may be due to the presence of con-specifics in the area on release. Numerous travel corridors have been used repeatedly by more than 1 lynx, possibly suggesting route selection based on olfactory cues. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-SilvertonLizardhead Pass for movements to the west, and southerly movements down the east side of WolfCreek Pass to the southeast to the Conejos River Valley. Lynx appear to remain faithful to an . area during winter months, and exhibit more extensive movements away from these areas in the summer. Most lynx currently being tracked are within the Core Release Area. During the summer of 2000 and 2001, several lynx that had been faithful to a 100 90 lEI0 - 6" DBH 6.1-12" DBH SO .12.1-1S" DBH E11S.1-24" DBH .> 70 24" DBH 60 ',_•=• 50 "" 40 .. " 30 20 10 0 ES SF CWD WI AS LO Species Figure 15. Percent of habitat plots with tree species Engelmann spruce (ES), subalpine fire (SF), willow (WI), aspen (AS), lodgepole pine (LO), and coarse woody debris (CWD) by diameter at breast height (DB H) size class. 100 90 1EJ0 - 6" DBH 6.1-12" DBH .12.1-18" DBH 818.1-24" DBH 80 .> 70 '.,_=. .. " 60 24" DBH 50 ll., 40 30 20 10 0 ES SF CWD WI AS LO Species Figure 16. Mean number of trees or shrubs in habitat plots with tree species Engelmann spruce (ES), subalpine fire (SF), willow (WI), aspen (AS), lodgepole pine (LO), and coarse woody debris (CWD) by diameter at breast height (DB H) size class. �31 given area during the winter months made large movements away from their winter-use areas. Extensive summer movements away from areas used throughout the rest of the year have been documented in native lynx in Wyoming and Montana (Squires and Laurion 1999). In winter, lynx reintroduced to Colorado appear to be feeding on their preferred prey species, snowshoe hare and red squirrel in similar proportions as those reported for northern lynx during lows in the snowshoe hare cycle (Aubry et ai., 1999). Caution must be used in interpreting the proportion of identified kills. Such a proportion ignores other food items that are consumed in their entirety and thus are biased towards larger prey and may not accurately represent the proportion of smaller prey items, such as microtines, in lynx winter diet. Through snow-tracking we have evidence that lynx are mousing and several of the fresh carcasses have yielded small mammals in the gut on necropsy. Nearly all the scat samples collected have been found through snow-tracking efforts and thus are representative of winter diet only. However, the summer diet of lynx has been documented to include less snowshoe hare and more alternative prey than in winter (Mowat et ai., 1999). Reproduction is critical to achieving a self-sustaining viable population of lynx in Colorado. Although females have been monitored and observed during each denning season, no kittens have been found to date. Snow-tracking has also not provided evidence that any of the females tracked had kittens with them. However, the question of whether they successfully bred or had kittens at some point is unknown. With only 7 females from the 1999 releases in the wild in spring 2000 it was expected that there might not be successful reproduction in 2000. However, the extreme movements observed by both females and males in March and April 2000 may have been related to breeding behavior. March and April are the natural breeding periods for northern lynx (Tumlison 1987). From observations of the 29 females alive in summer 2001, we have not yet documented kittens. We may still find evidence of kittens through snow-tracking efforts in winter 2001-02. Mowat et ai. (1999) suggest lynx and snowshoe hare select similar habitats except that hares select more dense stands than lynx. Very dense understory limits hunting success of the lynx and provides refugia for hares. Given the high proportion of snowshoe hare in the lynx diet in Colorado, we might then assume the habitats used by reintroduced lynx also depict areas where snowshoes hare are abundant and available for capture by lynx in Colorado. From both aerial locations taken throughout the year and from the site-scale habitat data collected in winter, the most common areas used by lynx are in stands of Engelmann spruce and subalpine fir. This is in contrast to adjacent areas of Ponderosa pine, pinyon juniper, aspen and oakbrush. The lack of lodgepole pine in the areas used by the lynx may be more reflective of the limited amount oflodgepole pine in southwestern Colorado, the Core Research Area, rather than avoidance of this tree species. Hodges (1999) summarized habitats used by snowshoe hare from 15 studies as areas of dense understory cover from shrubs, stands that are densely stocked, and stands at ages where branches have more lateral cover. Species composition and stand age appears to be less correlated with hare habitat use than is understory structure (Hodges 1999). The stands need to be old enough to provide dense cover and browse for the hares and cover for the lynx. In winter, the coverlbrowse needs to be tall enough to still provide browse and cover in average snow depths. Hares also use riparian areas and mature forests with understory. Site-scale habitat use documented for lynx in Colorado indicate lynx are most commonly using areas with Engelmann spruce understory present from the snow line to at least 1.5 m above the . snow. The mean percent understory cover within the habitat plots is typically less than 15% regardless of understory species. However, if the understory species is willow, percent understory cover is typically double that,.with mean number of shrubs per plot approximately 80, far greater than for any other understory species. ' In winter, hares browse on small diameter woody stems «0.25"), bark and needles. In summer hares shifts their diet to include forbs, grasses, and other succulents as well as continuing to browse on woody stems. This shift in diet may express itself in seasonal shifts in habitat use, using more or denser coniferous cover in winter than in summer. The increased use of riparian areas by lynx in Colorado from July to November may reflect a seasonal shift in hare habitat in Colorado. Major (1989) suggested lynx hunted the edge of dense riparian willow stands. The use of these edge habitats may allow lynx to hunt �32 hares that live in habitats normally too dense to hunt effectively. The use of riparian areas and riparianEngelmann spruce-subalpine fir and riparian- aspen mixes documented in Colorado may stem from a similar hunting strategy. However, too little is known about habitat use by hares in Colorado to test this hypothesis at this time. Lynx also require sufficient denning habitat. Denning habitat has been described by Koehler (1990) and Mowat et al. (1999) as areas having dense downed trees, roots, or dense live vegetation. No den sites have been located as yet in Colorado for comparison. Through extensive monitoring of released animals we were able to continuously evaluate and modify release protocols to improve survival of released lynx. The primary element in later, more successful release protocols was increased time in captivity at the Colorado holding facility. Increasing the amount of time lynx were held in the Colorado holding facility provided each lynx with an opportunity to increase body weight and acclimate to the climate, elevation, and local conditions of the environment they would be released into. Although most lynx were housed in individual pens, with a few sharing a pen with one other lynx, the holding facility also allowed the lynx to hear and smell each other throughout this acclimation period. Such contact may have provided time for social interactions to occur. Such social interactions may improve the likelihood these animals could form a breeding population. If additional lynx are released in Colorado the following guidelines are recommended in establishing release protocols. Translocated animals should be adults and females should not be pregnant on release. Once lynx are moved from their place of origin they should be held a minimum of 3 weeks in a local holding facility to provide a high quality diet for gaining optimal body condition prior to release in the new area, acclimation time to adjust to local conditions, and possible social interactions. Animals should be released in the spring to ensure the highest prey abundance in the release area. These release protocol guidelines may also prove useful if other states attempt lynx reintroductions or augmentations. Future Research Future research will include the continued monitoring of lynx released in Colorado that have remained in the Core Release Area. Such monitoring will include continued data collection and analysis on survival and mortality factors, reproduction, habitat use, winter and summer diet, and movement patterns. If additional funding becomes available, reintroduced lynx that have moved beyond the Core Release Area should also be monitored, particularly those lynx using areas near the Interstate Highway 70 corridor. We will continue to attempt to recapture lynx to replace radio collars that are either malfunctioning or scheduled to stop functioning. Any Colorado born lynx will be radio collared once they reach a minimum of 10 months of age. Studies have been initiated to refine mark-recapture techniques to estimate abundance of lynx from hair-snag data. Such an approach would provide a non-invasive technique for estimating abundance. A snowshoe hare ecology study was initiated in 2001 to describe density of hares in various forest stands and which habitats and topographic features are most important to hare density and survival. From this research, management prescriptions may be designed to better manage forests for optimal hare populations. Maintaining abundant and widespread snowshoe hare populations is essential to establishing lynx in Colorado. Through funding provided by Colorado Department of Transportation (CDOT) a detailed analysis of lynx movement patterns as they relate to highways has been initiated. The feasibility of augmenting this reintroduction effort by releasing additional animals from Canada and Alaska is being considered by CDOW to improve the likelihood of establishing a viable population of lynx in Colorado. Funding is being sought to develop protocols for collecting data on lynx summer diet by using dogs trained to locate lynx scat. �33 If viable, self-sustaining populations of lynx are established in Colorado, habitat manipulation studies will be needed to more fully understand how lynx respond to their habitat and how best to alter habitats to maintain and enhance lynx populations. Acknowledgments The lynx reintroduction program involved the efforts of literally hundreds of people across North America, in Canada and the U. S. Any attempt to properly acknowledge all the people who played a role in this effort is at risk of missing many people. The following list should be considered to be incomplete. CDOWCLAWS Team (1998-2001): Bill Andree, Tom Beck, Gene Byrne, Bruce Gill, Mike Grode, Rick Kahn (Program Leader), Dave Kenvin, Todd Malmsbury, Jim Olterman, Dale Reed, John Seidel, Scott Wait, Margaret Wild. CDOW: John Mumma (Director 1996-2000), Conrad Albert, Jerry Apker, Cary Carron, Don Crane, Larry DeClaire, Phil Ehrlich, Lee Flores, Delana Friedrich, Dave Gallegos, Juanita Garcia, Drayton Harrison, Jon Kindler, Ann Mangusso, Jerrie McKee, Melody Miller, Mike Miller, Kirk Navo, Robin Olterman, Jerry Pacheo, Mike Reid, Ellen Salem, Eric Schaller, Mike Sherman, Jennie Slater, Steve Steinert, Kip Stransky, Suzanne Tracey, Anne Trainor, Brad Weinmeister, Nancy Wild, Perry Will, Brent Woodward, Kelly Woods, Kevin Wright. Lynx Advisory Team (19982001): Steve Buskirk, Jeff Copeland, Dave Kenny, John Krebs, Brian Miller (Co-leader), Mike Phillips, Kim Poole, Rich Reading (Co-leader), Rob Ramey, John Weaver. U. S. Forest Service: Kit Buell, Joan Friedlander, Jerry Mastel, John Squires, Fred Wahl. U. S. Fish And Wildlife Service: Lee Carlson, Gary Patton (1998-2000), Kurt Broderdorp. State Agencies: Gary Koehler (Washington). National Park Service: Steve King. Colorado State University: Alan B. Franklin, Gary C. White. Colorado Natural Heritage Program: Rob Schorr, Mike Wunder. Alaska: ADF&G: Cathie Harms, Mark Mcnay, Dan Reed (Regional Manager), Wayne Reglin (Director), Ken Taylor (Assist. Director), Ken Whitten, Randy Zarnke, Other:Ron Perkins (trapper), Dr. Cort Zachel (veterinarian). British Columbia: Dr. Gary Armstrong (veterinarian), Mike Badry (government), Paul Blackwell (trapper coordinator), Trappers: Dennis Brown, Ken Graham, Tom Sbo, Terry Stocks, Ron Teppema, Matt Ounpuu. Yukon: Government: Arthur Hoole (Director), Harvey Jessup, Brian Pelchat, Helen Slama, Trappers:Roger Alfred, Ron Chamber, Raymond Craft, Lance Goodwin, Jerry Kruse, Elizabeth Hofer, Jurg Hofer, Guenther Mueller (YK Trapper's Association), Ken Reeder, Rene Rivard (Trapper coordinator), Russ Rose, Gilbert Tulk, Dave Young. Alberta: Al Cook. Northwest Territories: Albert Bourque, Robert Mulders (Furbearer Biologist), Doug Steward (Director NWT Renewable Res.), Fort Providence Native People. Colorado Holding Facility: Herman and Susan Dieterich. Pilots: Dell Dhabolt, Larry Gepfert, Al Keith, Jim Olterman, Matt Secor, Whitey Wannamaker, Dave Younkin. Field Crews: Bryce Bateman, Bob Dickman, Denny Morris, Gene Orth, Chris Parmater, Jake Powell, Jeremy Rockweit, Jennifer Zahratka. Photographs: Tom Beck, Bruce Gill, Mary Lloyd, Rich Reading, Rick Thompson. Funding: CDOW, GOCO, Turner Foundation, U.S. Forest Service, Vail Associates. Literature Cited Aiello, S. E., editor 1998. The Merck Veterinary Manual. Eighth Edition. Merck & Co., Inc. Whitehorse Station, New Jersey. Aubry, K. B., G. M. Koehler, J. R. Squires. 1999. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Biggins, D. E. and M. Y. Kosoy. 2001. Influences of introduced plague in North American mammals: implications from ecology of plague in Asia. Journal of Mamma logy 82: 906-916. Burnham, K. P. and D. R. Anderson. 1998. Model Selection and Inference: A Practical InformationTheoretic Approach. Springer-Verlag, New York, New York. �34 Byrne, G. 1998. Core area release site selection and considerations for a Canada lynx reintroduction in Colorado. Report for the Colorado Division of Wildlife. Curtis, J. T. 1959. The vegetation of Wisconsin. University of Wisconsin Pres, Madison. Ganey, J. L. and W. M. Block. A comparison of two techniques for measuring canopy closure. Western Journal of Applied Forestry 9:1: 21-23. Hodges, K. E. 1999. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163-206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Koehler, G. M. 1990. Population and habitat characteristics oflynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. Laymon, S. A. 1988. The ecology of the spotted owl in the central Sierra Nevada, California. PhD Dissertation University of California, Berkeley, California. Major, A. R. 1989. Lynx, Lynx canadensis canadensis (Kerr) predation patterns and habitat use in the Yukon Territory, Canada. M. S. Thesis, State University of New York, Syracuse. Mowat, G., K. G. Poole, and M. O'Donoghue. 1999. Ecology of lynx in northern Canada and Alaska. Pages 265-306 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53: 7-15. Poole, K. G., G. Mowat, and B. G. Slough. 1993. Chemical immobilization of lynx. Wildlife Society Bulletin 21:136-140. Seidel, J., B. Andree, S. Berlinger, K. Buell, G. Byrne, B. Gill, D. Kenvin, and D. Reed. 1998. Draft strategy for the conservation and reestablishment of lynx and wolverine in the southern Rocky Mountains. Report for the Colorado Division of Wildlife. Shenk, T. M. 1999. Program narrative: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Report for the Colorado Division of Wildlife. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. Thomas, J. W. Ed. 1979. Wildlife habitats in managed forests - the Blue Mountains of Oregon and Washington. USDA Agricultural Handbook No. 553. U. S. Government Printing Office. Washington, D. C. Tumlison, R. 1987. Mammalian Species: Felis lynx. American Society ofMammalogists. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife andplants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. White, G. C. and K. P. Burnham. 1999. Program MARK: Survival estimation from populations of marked animals. Bird Study 46 (suppl):120-138. Wild, M. A. 1999. Lynx veterinary services and diagnostics. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. �35 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 JOB PROGRESS State of Colorado Division of Wildlife - Mammals Research Work Package No. _--'0"-'6'-"7-"0 Task No. REPORT _ 2 Period Covered: July 1,2000 Lynx Conservation Ecology of Snowshoe Hares (Lepus americanus) in Colorado - June 30, 2002 Author: Steven W. Buskirk and Jennifer L. Zahratka Personnel: T. M. Shenk, Ph.D. ABSTRACT Despite what is known about Canada lynx (Lynx canadensis) and snowshoe hare (Lepus americanus) ecology in Canada and Alaska, a paucity of information exists in the contiguous United States. With the listing of the Canada lynx as threatened under the Endangered Species Act in 2000 the need for more knowledge about lynx and their prey become more pressing. The recent reintroduction of Canada lynx to southwestern Colorado (1999) by the state has furthered increased this need. The development of reliable knowledge about snowshoe hare ecology will be key to the recovery and deli sting of lynx. Two habitat factors are generally considered overriding in their importance to the abundance and fitness of snowshoe hares: the density of small -diameter (generally < 5 mm) woody stems within reach of the snow surface for food, and the abundance of somewhat larger-diameter woody structure for overhead cover. This project focuses on two central conceptual issues. First, how do site conditions produce woody stems of suitable diameters and heights above the snow for food for snowshoe hares in late winter, and how do, site conditions provide overhead cover suitable for hares? Second, do snowshoe hares in fact attain their highest densities in these presumptive high-quality habitats? Ecological information gained about snowshoe hares will be valuable not only to the recovery of Canada lynx in Colorado, but also throughout the range oflynx in the southern U.S. I . --_._-_. __ .. .- 1~~~I~I~~lmilil\lill~[I~~llii BDOW016770 ��37 Ecology of Snowshoe Hares (Lepus Americanus) in Colorado Steven W. Buskirk and Jennifer L. Zahratka Department of Zoology and Physiology, University of Wyoming Laramie, Wyoming 82071 Introduction The snowshoe hare (Lepus americanus) is a widely distributed and well-studied leporid of North American boreal forests. Scientists have long been interested in the snowshoe hare and its cyclic relationship with the Canada lynx (Lynx canadensis). The snowshoe hare is the obligate primary prey item of the lynx, which was listed as threatened under the Endangered Species Act in 2000. Data dealing with the ecology, particularly the habitat ecology, of southern snowshoe hare populations is lacking, especially in the southern Rocky Mountains. Indeed, only a single study (Dolbeer and Clark 1975) described the habitat associations of hares in the southern Rocky Mountains, but only in the most cursory fashion. The reintroduction of Canada lynx to the southern Rocky Mountains in 1999-2000 has further stimulated the need for understanding the habitat requirements of snowshoe hare populations. Therefore, data from the southern Rocky Mountains is critical for understanding the ecology of snowshoe hares in their southern range. The abundance and fitness of snowshoe hares depend on the protection afforded by plants as well as their suitability as foods for hares. Although food is an obvious requirement for snowshoe hare survival, snowshoe hares rarely starve to death. Instead, predation is the overwhelming proximate cause of death for snowshoe hares (Hodges 2000b) and food shortage only predisposes them to predation. The cover afforded by large-diameter woody structure provides horizontal and vertical protection from predators (Wolff 1980). Also, small-diameter « 5-mm) (Grigal and Moody 1980) woody stems < 45 cm from the snow surface (Bider 1961) are an important food source (Hodges 2000a). Whereas largediameter woody stems presumptively provide protection from predation, small-diameter woody stems presumptively provide nutrition. Therefore, we assume that woody structure in two different size classes meets the needs of snowshoe hares for habitat. Winter is a critical time of year for snowshoe hare survival because fewer woody stems of either size class are available in winter than in other seasons, and herbaceous plants are not available. Understanding how the density of woody stems of different sizes, tree dominants, and successional stage affect densities of snowshoe hares is key to effective management of snowshoe hare habitats in the southern Rocky Mountains. Therefore, we investigated two conceptual issues relating to snowshoe hare habitat in late winter. First, how do site conditions produce woody stems of suitable diameters and heights above the snow surface for food and how do site conditions provide suitable protective cover for hares? Second, do snowshoe hares in fact attain their highest densities in these presumptive high-quality habitats? Study Area Location . The study area was a broad area of southwestern Colorado on the Gunnison and Rio Grande National Forests, which we studied during January - April 2002. Within our study area, we established two study sites: one was a 1963-km2 area centered over Taylor Park Reservoir on the Gunnison National Forest (390 50' N, 106034' W); the second was the Divide District (4,089 krrr') of the Rio Grande National Forest (370 40' N, 106040' W) centered directly north of South Fork, Colorado. The Gunnison study area represents the southernmost extent of naturally occurring lodgepole pine. In coniferous forests of the Rocky Mountains, lodgepole pine is an important habitat type for lynx and �38 snowshoe hares. The Rio Grande study area is lower in elevation and contains ponderosa pine, also widely distributed in the Rocky Mountains, and therefore of interest in our study. Topography The landscape of southwestern Colorado is characterized by high, rugged mountains, wide plateaus, and gaping river valleys. Elevation of the Gunnison study site ranged from 2850 m to 3480 m. On the Rio Grande study site the elevation ranged from 2460 m to 2580 m. Our spruce-fir sites occurred at elevations of 3210 - 3480 m, our lodgepole pine sites occurred at 2850 - 3100 m, and our ponderosa pine sites occurred at 2460 - 2580 m. Climate Southwestern Colorado exhibits an arid and temperate climate; strong local variation responds to elevation and aspect. The mean temperature in Gunnison, Colorado from January - April is In South Fork, Colorado the mean temperature from January - April is O°C (National Weather Service, Gunnison, CO, unpublished data). Unlike areas of the Western Slope where more precipitation falls as winter snow than as summer rain, the monsoon season in southwestern Colorado brings most yearly precipitation in late summer. The mean monthly precipitation in Gunnison, Colorado for January - April is 1.6 em. In South Fork, Colorado the corresponding mean is 1.5 em (National Weather Service, Gunnison, CO, unpublished data). -rc. Methods Trapping grid selection Our study area comprised the Gunnison and Rio Grande National Forests, within which trapping grids were chosen using a GIS database of national forest lands with Common Vegetation Unit (CVU) coverage using the Integrated Resource Inventory protocol (IRI) made available by each of the forests. Two sets of criteria, applied sequentially, were used to select the site of the trapping grids. The first set of criteria was based upon the CVU coverages using GIS: 1. Species dominants represented were lodgepole pine, Engelmann spruce, ponderosa pine and riparian (Salix spp.). 2. For forests, structural stage considered was mature (structural stage 4). 3. Vegetation polygons were candidate if ~30 m, but ~ 1 km from an improved road. 4. Vegetation polygons were candidate if ~25 ha. 5. Vegetation polygons were candidate if sufficient to admit a 330 m x 550 m (16.5-ha) trapping grid with a 50-m buffer between the edge of-the trapping grid and the nearest edge 'ofthe . polygon. Fifteen of the candidate polygons were selected randomly. Within each of these random polygons a 330 m x 550 m rectangle was placed at a randomly generated orientation (0 - 180°). All potential ponderosa pine sites on the Gunnison National Forest were excluded using these criteria. All potential riparian sites on the Rio Grande were excluded using these criteria and no lodgepole pine was available on the Rio Grande to evaluate by CVU layers. Potential sites were visited in random order, at which time we applied the second set of criteria: 1. Forested sites were excluded if ~40% of the trapping grid was dominated by a cover type other than the nominal species dominant. 2. Candidate sites were excluded if inaccessible by snowmobile and snowshoes. 3. Candidate sites were excluded if they held any unmapped roads. 4. Candidate sites were excluded iflogging or thinning had occurred within them. �39 5. Candidate sites were excluded if avalanche danger was present. 6. Candidate sites were excluded if trapping grids were <500 m from a grid that had already been included. The first three from each species dominant to meet these criteria were included as trapping grids. Because of the availability of suitable sites, and for logistical reasons, all three spruce-fir trapping grids, all three lodgepole pine trapping grids and all three riparian trapping grids were selected on the Gunnison National Forest. Only the three ponderosa pine trapping grids were selected on the Rio Grande National Forest. After visiting fourteen sites mapped as lodgepole pine on the Gunnison National Forest, three were found that met our criteria. Fifteen sites mapped as spruce-fir on the Gunnison National Forest were evaluated before three were found that met our criteria. Ten sites tentatively mapped as riparian on the Gunnison were visited, but none were found that met our criteria. Fifteen sites mapped as ponderosa pine-dominant on the Rio Grande National Forest were visited before three were found that met our criteria. Trapping and handling All methods related to trapping and handling were approved by the University of Wyoming Animal Care and Use Committee and by the Colorado Division of Wildlife Animal Care and Use Committee. Snowshoe hares were trapped using Tomahawk Model 204 live traps (18 ern x 18 em x 51 ern) placed on trapping grids of 84 traps (7 lines of 12 traps each), with 50-m spacing for a trapping grid size of 16.5 ha (Fig. 1). Three replicates for each species dominant were sampled for 6 trap nights, which we assumed to be a closed population for the purposes of mark-recapture models. No reproduction occurred during our winter field season. The trapping grid size and method were developed by Scott Mills and Paul Griffin, University of Montana; we used these methods to maximize comparability between our study and theirs. Upon visiting a suitable site, the trapping grid was flagged and numbered using the UTM coordinates generated by a GPS receiver and a compass bearing (Fig. 1). Traps were placed in suitable habitat within 2 m of the flagging and if necessary, covered with tree branches to provide cover for captured hares. Traps were baited with a mixture of pellets of Timothy grain, alfalfa, com, and oats (TACO), alfalfa pellets and apples (P. Griffin, pers. comm.). Traps were checked as early as possible each morning and re-baited as needed. Once a snowshoe hare was captured, a pillowcase with a drawstring was placed over the front door of the trap. The hare was persuaded into the bag by gently tipping the trap, blowing on the hare, or making 'noise. Once the hare was in the bag it was immediately weighed using a 2500-g Pesola spring scale. The hare was then carefully placed between the legs of a kneeling handler with the head facing towards the handler. The second handler marked the hare using a sterile passive-integrated transponder (PIT) tag. One tag was injected subcutaneously with a sterile needle between the shoulder blades. Both ears of the snowshoe hare were also marked using a permanent black marker for short-term identification. After the first day of any trapping session (i.e. on traps days 2-6) every snowshoe hare was scanned with a 125-kHz Mini-portable reader to determine whether the hare was a recapture or a new capture. ill the event the snowshoe hare was preyed upon and partially ingested, the earmarks were checked. Each snowshoe hare was sexed by turning the hare on its dorsal side and protruding the genitalia. The forefinger and middle finger were used to apply slight pressure to the vent area just above the anus. Snowshoe hares were then released away from handlers. Snowshoe hares that suffered severe trap or predation injuries were euthanized with a l-ml intrathoracic injection of sodium pentobarbital. Each carcass was necropsied and the liver and kidneys preserved for metals analysis. After necropsy and tissue collection, euthanized animals were disposed of by cremation or deposited in a landfill. Any non-target species caught -intraps were immediately released. �40 Diet Within spruce-fir stands, where captures were expected to be more common, we marked trap bait in order to determine whether feces collected from traps contained any bait. TACO and alfalfa pellets were marked with a light dusting of fluorescent, non-toxic powder (DayGlo). Fecal pellets were then collected from the inside of each live-trap where a snowshoe hare was captured. Every fecal pellet within the trap was collected, placed in a brown paper bag and allowed to dry at room temperature. After collection the fecal pellets were placed under an ultraviolet light to show presence or absence of any fluorescent marker ingested by the hares. Samples will be submitted to the Wildlife Habitat and Nutrition Lab at Washington State University, Pullman, W A for analysis. Measurement of fecal pellets Each fecal pellet was measured to the nearest 0.1 mm using SPI dial calipers. The sizes of all fecal pellets were recorded, and the mean pellet size for each individual hare was calculated. Vegetation measurements Habitat attributes were estimated at two levels: at each trap site and at each trapping grid. Within each trapping grid, vegetation plots were sampled from 15 trap sites, similar to the design ofS. Mills (Fig. 1). Methods developed by T. Shenk (Colorado Division of Wildlife) to monitor habitat use by reintroduced lynx to Colorado were followed, with some minor modifications (Fig. 2). Accordingly, a 12-m x 12-m square of 25 points was placed in 5 rows of 5 (3 m apart), centered over the trap location (Fig. 2). The measurements taken at each of the 25 points included: 1. Snow depth (em), as measured by a calibrated avalanche probe. 2. Understory measured in a column of 3-cm radius around an avalanche probe. a. All live or dead stems and coarse woody debris (CWD) that fall within the 3-cm radius column using the standardized four-letter genus-species code at 3 height categories (00.5 m, 0.51-l.0 m, l.01-l.5 m) above the snow surface. b. Each of the above stems classified in 3 different diameter categories « 5 mm, 5.1-10 mm, 1O.l-15 mm) measured at the point where the stem hit the avalanche probe. 3. Overstory was measured using a sighting tube ("moosehorn") attached to the avalanche probe. a. Species that hit the crosshairs inside the sighting tube were recorded. Multiple hits by the same species were only recorded once. 4. Every shrub within the plot along with its species and diameter at breast height was recorded (dbh). 5. Every tree within the plot along with its species and dbh was recorded. 6. Every snag within the plot along with its dbh was recorded. 7. Every sapling within the plot along with its species was counted. 8. All coarse woody debris (CWD) deemed usable by snowshoe hare for cover or food (i.e., available above the snow) was recorded along with its diameter. At all of the 84 trap sites within the trapping grid, including the 15trap sites sampled as described above, the following data were measured: l. Snow depth (em), as measured by a calibrated avalanche probe. 2. Species of, dbh of, and distance to the closest woody stem in two categories: z lO em -7.0 and :?: 7.1 em at the snow surface. 3. Canopy cover for the center of the trap site, as estimated by the use of a spherical densiometer, in the four cardinal quadrants (NW, NE, SE, SW). The following rules were used for unusual events: 1. If a point in a vegetation plot lay within a tree bole, the tree species and the dbh was written on the data form. �41 2. A snag was defined as any dead tree bole >45 from the horizontal. angle were considered CWD. 0 0 Dead boles <45 vertical 3. The mid-point diameter was measured of exposed CWD partially covered by snow. 4. If a leaning tree fell partially outside the 12 m x 12 m sampling plot it was included if>50% of the tree lay within the sampling plot. Results Captures of snowshoe hares by trapping grid and tree species dominant are summarized in Table 1. A total of 28 hares were captured in 4620 trap nights of effort. Mean dbh and density of trees, by species, for the nine trapping grids in three tree species domiriant categories are summarized in Tables 23. Snow depths, and densities of various vegetative structures for the nine trapping grids (15 -point protocol) in three tree species dominant categories are summarized in Table 4. Corresponding data for the 84-point protocol are summarized in Table 5. Literature Cited Bider, J. R. 1961. An ecological study of the hare Lepus americanus. 39:81-103. Canadian Journal of Zoology Dolbeer, R. A., and W. R. Clark. 1975. Population ecology of snowshoe hares in the central Rocky Mountains. Journal of Wildlife Management 39:535-549. Grigal, D. F., and N. R. Moody. 1980. Estimation of browse by size classes for snowshoe hare. Journal of Wildlife Management 44:34-40. Hodges, K. E. 2000a. The ecology of snowshoe hares in northern boreal forests. Pages 117-161 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado. Hodges, K. E. 2000b. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado. Hoover, R. L., and D. L. Wills. 1987. Managing forested lands for wildlife. Pages 455-477. Colorado Division of Wildlife, Eastwood Printing and Publishing, Denver, Colorado. Wolff, J. O. 1980. The role ofhabittl patchiness in the population dynamics of snowshoe hares. Ecological Monographs 50: 111-130. �42 Figure 1. Schematic of 300 m x 550 m trapping grid to be used for estimating population density of snowshoe hares in southern Colorado. Asterisks (*) indicate the location of the 15 vegetation plots centered on trapping points. Pound signs (#) indicate where the point-quarter method will be used on all other trap locations. 1# 2# 3# 4# 5# 6# 7# 8# 9* 10# 11* 12# 13* 14# 15# 16# 17# 18# 19# 20# 21# 22# 23* 24# 25* 26# 27* 28# 29# 30# 31# 32# 33# 34# 35# 36# 37* 38# 39* 40# 41* 42# 43# 44# 45# 46# 47# 48# 49# 50# 51* 52# 53* 54# 55* 56# 57# 58# 59# 60# 61# 62# 63# 64# 65* 66# 67* 68# 69* 70# 71# 72# 73# 74# 75# 76# 77# 78# 79# 80# 81# 82# 83# 84# �43 Figure 2. Schematic of 12 m x 12 m vegetation plot centered on each of the 15 trap sites (Fig. 1) used in measuring habitat variables for snowshoe hares in southwestern Colorado, late winter 2002. The trap location is at the center of the vegetation plot. 12m �44 Table l. The number of snowshoe hare captures (1st, 2nd, and 3rd), and total captures on nine trapping grids in three species dominant categories, and trapping effort (trap-nights), southwestern Colorado, late winter 2002. pt Total TrapTrapping grid 2nd 3rd number LPI LP2 LP3 SFI SF2 SF3 PPI PP2 PP3 capture Tree species dominant Pinus contorta 1 Picea engelmannii, Abies lasiocarpa Picea engelmannii, Abies lasiocarpa 5 3 capture 0 0 0 2 0 Pice a engelmannii, Abies lasiocarpa 15 6 Pinus ponderosa 0 0 0 0 0 0 Pinus contorta 1 Pinus contorta 3 Pinus ponderosa Pinus ponderosa capture 0 0 0 0 0 2 0 0 0 capture nights 504 504 504 504 588 504 504 504 504 1 3 1 7 3 23 0 0 0 Table 2. Mean diameter at breast height (dbh) by tree species for 15 trap locations on nine trapping grids in three species dominant categories, southwestern Colorado, late winter 2002. All measurements are in em ± SE (where n> 1). Picea Trapping grid engelmannii number LPI LP2 LP3 SFI SF2 SF3 PPI PP2 PP3 Abies lasiocarpa Pinus contorta NA NA NA NA NA NA 14±1 14±1 15±1 23±3 14±1 20±2 13±2 10±1 11±2 NA NA MA NA NA NA NA NA NA NA NA NA Pinus ponderosa Populus tremuloides Psuedotsuga menziesii Juniperus scopulorum NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 27±3 25±3 21±2 11±1 6 3 21±2 18±1 20±3 9±2 8 NA Table 3. Mean density by tree species for 15 trap locations on nine trappinggrids in three species l dominant categories, southwestern Colorado, late winter . 2002. All measurements ate in trees ha- . . Picea Trapping grid engelmannii number LPI LP2 LP3 SFI SF2 SF3 PPI PP2 PP3 NA NA 5±5 704±149 1231±159 1194±178 NA NA MA Abies lasiocarpa Pinus contorta NA NA NA 1273±171 1218±231 1310±313 227±64 449±171 449±112 NA NA NA NA NA NA NA NA NA Pinus ponderosa Populus tremuloides Psuedotsuga menziesii Juniperus scopulorum NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 46±19 93±24 120±27 28±19 5±5 5±5 125±15 14±7 69±22 51±27 5±5 NA �45 Table 4. Mean snow depth, tree density, sapling density, shrub density, and snag density for 15 trap locations on Colorado, late winter, 2002. All measurements are in em ± SE. Species dominant categories are listed in Table 1. Trapping grid number Snow depth at time of sampling ± SE Tree density (ha") Sapling density (ha-l) Shrub density (ha-l) Snag density (ha-l) LP 1 LP2 LP3 SF 1 SF 2 SF 3 PP 1 PP2 PP 3 37±1 38±2 32±1 70±4 70±3 75±3 0 0 0 1273±171 1218±231 1314±312 931±150 1680±215 1643±180 250±76 116±28 194±31 569±203 333±148 759±203 546±134 749±254 630±154 273±165 481±161 148±67 NA NA NA NA NA NA 315±1l4 722±305 921±434 620±139 278±95 431±98 162±50 282±44 417±108 162±67 379±125 277±133 Table 5. Mean snow depth, mean canopy cover, mean diameter at breast height (dbh), and mean distances to nearest stem in two diameter categories for 84 trap locations on nine trapping grids in three species dominant categories, southwestern Colorado, late winter 2002. All measurements are in em ± SE, except canopy cover, which is % ±SE. Trapping grid number LP 1 LP2 LP3 SF 1 SF2 SF 3 PP 1 PP2 PP3 Species dominant Pinus contorta Pinus contorta Pinus contorta Picea engelmannii, Abies lasiocarpa Picea engelmannii, Abies lasiocarpa Picea engelmannii, Abies lasiocarpa Pinus ponderosa Pinus ponderosa Pinus ponderosa Snow depth at time of sampling Canopy cover dbhofwoody stems> 7 em Distance to nearest stem 1-7 cmdbh Distance to nearest stem >7 cmdbh 40±1 38±2 40±1 73±2 73±2 79±1 69±2 79±2 15±1 17±1 18±1 28±2 352±35 303±26 351±52 313±38 116±7 146±1l 163±14 216±19 66±1 75±2 24±1 238±21 165±16 75±2 85±2 21±1 153±13 145±1l 0 0 0 37±4 24±3 48±3 27±1 25±1 26±1 490±41 382±35 479±46 422±37 551±43 291±32 ��47 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 PROGRESS State of --'=C""'o'-'-'lo"'r..!:a""-do"'-_ 'Work Package No. __ Task ....:::3;..>::0..:::.0 ..•.. 1 . Period Covered: Division of Wildlife - Mammals Research _ Deer Conservation _ Mule Deer Life Cycle - Neonatal Fawn Survival _ Research and Development ~l_· Federal Aid Project_~W'_-_!..18~S;:_-~R'__ REPORT July 1,2001 - June 30, 2002 Author: T. M. Pojar and D. C. Bowden Personnel: W. Andelt, R Arant, D. Baker, T. Baker, B. Banulis, T. Beck, C. Bishop, G. Bock, D. Bowden, P. Burke, T. Burke, M. Caddy, D. Coven, B. Diamond, B. Dreher, J. Ellenberger, M. Farnsworth, J. Foster, V. Graham, J. Griggs, D. Gustine, P. Hayden, B. Hoffner, B. Lamont, M. King, K. Larsen, M. Mclain, H. McNally, G. Miller, M. W. Miller, E. Myers, J. Olterman, M. Potter, J. Risher, D. Schweitzer, D. Steele, J. Skinner, T. Spraker, D. Swanson, B. Watkins, G. White, S. Znamenacek. '. The following is an abstract and manuscript now in preparation for submission to the Journal of Wildlife Management describing the neonatal fawn survival study on the Uncompahgre Plateau. Because of requests by reviewers or editors some aspects of the presentation and analysis may be modified. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such, and is discouraged. Abstract: Declining mule deer (Odocoileus hemionus) populations resulting from apparent low recruitment brought management and political focus on neonatal fawn survival. Mule deer fawns on the Uncompahgre Plateau (S,9S7 km" in west central Colorado were captured at mean age of3 days (range . from newborn to 6 days) and collared withmortality sensing drop-off radio collars. Two hundred thirty fawns were radioed with samples of SO, 88, and 92 during 1999, 2000, arid 2001, respectively. '. Designated neon,ate survival period was from capture to 14 December. Survival was different among years (X} = 6.160, P = 0:046) with annual survival (Kaplan-Meier, 9S% CL) of 0.321 (0.12S-0.S17); 0:"589(0.474-0.703), and 0.S94 (0.472-0.716) for 1999, 2000, and 2001, respectively; the 3-year mean survival was O.SOl. Combined 3-year cause-specific mortality (9S% CL) was sick/starve 0.171 (0.1160.226), Coyote 0.126 (0.078-0.174), bear 0.040 (0.012-0.068), feline 0.032 (0.006-0.0S7), trauma 0.043 (0.014-0.072), and unknown 0.047 (0.016-0.077). Neither an predation combined (coyote, bear, and feline) (P = 0.379) nor coyote predation alone (P > 0.989) differed among years. Mortality in the sick/starve category is the only source that approached significance among years (P = 0.070). The major difference was in"1999 with 0.318 mortality due to sick/starve compared to O.llS and 0.148 in 2000 and 2Q01, respectively. Historic December (1990-99) fawns per 100 does ratios (f:d) were significantly correlated with thepreceding June precipitation (P = 0.004) but not with June temperature (P = 0.441). June prec;ipitati()n for 1999was 3.66 em and was 1.04 and 0.86 ern in 2000 and 2001, respectively, which ~ "- ... ,'. \ .' .;'-,' ...~." ._ .... .....• ',~' "._ �48 may have contributed directly or indirectly to the differences in sick/starve mortality. Three-fourths of mortality from predation (75.0%) and sick/starve (73.7%) had taken place by 31 July with 76.3% of mortality from all sources occurring by 31 July. Mean fawn weights at capture were 4.35 kg, 4.50 kg, and 4.13 kg for 1999, 2000, 2001, respectively and were different among years (P = 0.044). There was also a difference in hind foot length among years (P = 0.002) with mean length of26.14 em, 26.62 em, and 25.63 em for 1999,2000, and 2001, respectively. Weight and hind foot means were different between 2000 and 2001 (P> 0.017) with 1999 not different from either 2000 or 2001 (P < 0.017) using mean separation procedure controlled with Bonferonni significance level. Mean capture date was 19 June (4.83 days SD) and median capture date was 19 June (range 9 June to 6 July) with 94.78% of all captures occurring between 13-30 June. This implies that most does were bred during their first estrous cycle. Neonatal survival through 14 December does not completely account for observed low f:d ratios. Fetus mortality during late pregnancy or mortality of fawns at birth (before they could be detected for capture) is implicated as a potential cause of poor recruitment. . r-'- ! .. ·l .. . j.,. I L I L. [--~ .. I ( .[ :: ', ./ ' . ..... �49 NEONATAL MULE DEER FAWN SURVIVAL AND CAUSE SPECIFIC MORTALITY T. M. Pojar and D. C. Bowden There is evidence that the mule deer populations in Colorado, as well as other western states, have declined during recent years due mostly to low fawn survival and subsequent low population recruitment (Unsworth et al. 1999). December f:d ratios on the Uncompahgre Plateau (5,957 km" in west central Colorado have declined (t = -3.41, P = 0.004) by an average of 1.8 fawns: 100 does per year from 1982-1998 where December ratios ranged from a high of 79f: 100d in 1982 to a low of 32f: 100d in 1997 (White et al. 2001). Declining deer densities and long-term decline in f:d ratios have resulted is much debate and concern among managers, sportsmen, administrators, and politicians. Gill et al. (2001) offers several potential causes for long-term decline in deer density: 1) habitat deterioration, 2) competition, 3) disease, 4) predation, and 5) hunting. Specifically, low December ratios could be the result of: 1) low pregnancy rate, 2) reduced fetal production, 3) prolonged breeding (fawning) season due to low buck to doe ratios, 4) late term mortality of fetuses and weak or stillborn fawns, or 5) low neonatal fawn survival through December. A popular perception is that predation especially by coyotes (Canis latrans), but also by black bear (Ursus americanus) and felines (Felis concolor and F. rufus), is a major contributing factor in apparent low neonatal fawn survival. Pregnancy and fetal rates have been relatively constant for this species at population densities encountered during recent decades. During the 1960s and 1970s when deer populations were thriving in Colorado pregnancy rates in the following habitats were: 1) front-range foothills 92.0% (n=163) (Medin and Anderson 1979),2) high mountain park 94.0% (n=134) (Gill 1971), and western slope pinyonjuniper 89.0% (n = 47) during 1973 and 82.0% (n = 83) during 1978 (Bartmann 1998). During 1963-71, a penned herd that was fed alfalfa hay ad libitum and a 16% protein supplement ranging from 0.23 to 0.90 kg per deer-day averaged 94.7% pregnancy (n=135) (Robinette et al. 1973). Fetal rates, as the other major component of reproductive rates, for adult does were 1.83 (n = 41) during 1961-1965 in frontrange foothills habitat (Medin and Anderson 1979) and 1.82 (n = 114) in high mountain park habitat during 1969-1971 (Gill 1971) in Colorado. To determine if both pregnancy and fetal rates of adult does have not changed since the 1960s and 1970s and to have specific information from the Uncompahgre Plateau, a separate preliminary study examined these factors using transrectal ultrasound. A sample of 40 does was examined in February 1999. Pregnancy rate (93%) did not differ from the historic rate of 94%, (n = 328, X/ = 0.07, P = 0.791) and the fetal rate (1.70) was not less than the historic rate of 1.87 (n = 307, Z = 0.412, P = 0.681) (Andelt, Pojar, and Johnson, unpublished data). Density dependent effects of population growth follows the progression of reduced juvenile survival, increased age at first reproduction followed by a decline in reproductive rates of mature females late in the progression to carrying capacity and, finally, reduced adult survival (Eberhardt 1977). Juvenile survival is highly variable and sensitive to population density and stochastic environmental factors whereas, adult female survival is robust against most limiting factors (Gaillard et al. 1998, White and Bartmann 1998). Therefore, the most obvious area of investigation was to examine the survival and mortality sources of neonate fawns. The primary objectives of this study were to estimate neonatal fawn survival from birth (time of capture) to 14 December and cause-specific mortality to determine the contribution of summer fawn mortality to December f:d ratios on the Uncompahgre Plateau. Timing of births (captures), as an index of fawning season compression was a secondary objective; this relates to cohort exposure to predation (predator swamping). Extent and timing of the various mortality sources are described. �50 STUDY AREA The Uncompahgre Plateau was formed by a structural up-lift; it runs generally southeast to northwest with a crest, a_break in the up-lift, roughly bisecting it forming drainages to the northeast and southwest. The small communities of Gateway and Ridgeway are on the northwest and southeast perimeter, respectively, with the larger communities of Montrose and Delta along the east boundary (Figure l ). The terrain slopes generally to the northwest along the crest with the highest point being Horsefly Peak at 3,147 m and the lowest, 1,389 m, near Gateway. Along the crest, the terrain slopes gently to the northeast where many tributaries to the Gunnison and Uncompahgre rivers have worn deep canyons; the Unaweep Canyon along the northwest boundary of the area averages 914 m deep (Young and Young 1984). Southwest of the crest terrain drops abruptly because the plateau cap lifted and tilted to the northeast giving a gentle slope to the northeast and a steep drop-off to the southwest (Marshall 1998) with drainages flowing to the San Miguel and Dolores rivers. The latitude is from 38° 1.23' to 38° 59.05' and the longitude ranges from 107° 45.52' to 108° 58.80'. Normal annual precipitation (1971-2000 mean) is29.l1 em with most precipitation in late summer and fall (July-October); the 30-year mean low temperature (-2.78° C) was in January and the high (22.86° C) was in July. These weather statistics were taken from 5 stations on the perimeter of the plateau and would best represent winter range; summer range is at higher elevations and would have lower temperatures and higher precipitation. The study area includes Game Management Units 61 and 62 (5,957 krrr') and is designated as Data Analysis Unit D-19. Vegetation types are agricultural along the major river drainages and as elevation increases the following types are encountered: saltbrush-greaswood (Atriplex canescens and Sarcobatus vermiculatus), mature pinyon-juniper (Pinus edulis and Juniperus osteosperma) forest interspersed with big sagebrush (Artimisia tridentata) parks, Gambel oak (Quercus gambelii), ponderosa pine (Pinus ponderosa), and spruce-fir (Picea-Abies). The oak, pine, and spruce-fir communities are interspersed with aspen (Populus tremuloides) with some areas of pure aspen stands bordered by areas of mountain shrub and high mountain grass-forb meadows. There are vast stands of aspens on the rugged southwest slopes of the Uncompahgre. The oak, pine, spruce-fir, and aspen types are the major summer range and fawning habitat for mule deer and are generally above 2,438 m. Winter range can be from the oakmountain shrub community (depending on winter severity) decreasing in elevation to the agricultural lands along major drainages (Figure 1). Livestock grazing began in 1881 immediately after the Ute Tribe was expelled from the Uncompahgre Plateau (Anderson et al. 1992). Large herds of cattle were brought in from Texas, Kansas, and Mexico and within 20 years the town of Placerville (on the south end of the Uncompahgre Plateau) became " ... the largest cattle-shipping point in the world" (Marshall 1998:59). Severe overuse by livestock continued for 70 plus years, at least until 1951, accompanied by extreme overpopulation of deer beginning in the 1940s until liberal harvests during the 1950s and 1960s reduced the deer population (Kufeld 1979). Range condition around 1900 was described as being eaten " ... down to the nub" (Marshall 1998:59). Still, by about 1944 the range was described as appearing as having " ... had a band of sheep "caked" on it" (anonymous, c.a. 1944:8). Sharp stocking rate declines began in 1948 and " ... have remained relatively constant near their lowest rates from 1951 to the present" (Kufeld 1979: 13). The overstocking oflivestock from 1881 to 1948 and deer from the 1940s to the 1960s has been alleviated; however, reduction in grazing pressure does not necessarily result in range condition improvement because the range may stabilize at a lower successional state (LaycockI991). Timber harvest has been a factor in the past and continues to the present. Roads and rural subdevelopments are expanding especially in the southern area of the plateau. Summer and winter recreation, including sightseeing, camping, biking, hunting, all terrain vehicle, and snowmobiling and cross-country skiing are common human activities (Uncompahgre Plateau Partners 2002). This study was approved by Colorado State University and Colorado Division of Wildlife animal care and use committees under Protocol Number 99-063A-01. �51 METHODS The fawning area generally included the entire summer range of the plateau above 2,438 m. Mature does (n = 74) that had been radioed during the ultrasound reproductive study and during a separate survival study were tracked to more precisely identify fawning habitat during the first year of capture efforts. Fawns of radioed does were not necessarily targeted for capture. Searches for parturient does were from the ground, either on foot or by vehicle. Behavior and physical features were clues to identifying parturient does. Does that were alone, had udder development, and sunken flanks were prime candidates for initiating an intense search for bedded fawns within a 50± m radius of where the doe was first spotted. Searches were terminated if young were not found within about a half-hour. Bedded fawns were approached from the rear, avoiding eye contact, quickly approaching for the last couple meters. Upon placing a hand (latex gloved) on it's back, the fawn would freeze. Immediately upon capture, it was blindfolded and hobbled; processing took:s.. 5 minutes and included weighing, hind foot measurement, and attaching the radio collar. Age of the fawn was estimated by condition of the umbilical cord, pelage, hoof condition, and behavior. Before release, the fawn was examined for signs of dehydration, sickness (diarrhea or respiratory discharge), or physical deformities. Attempts were made to leave the fawn at the same site where it was captured. Radio collars (weighing < 110 g) were expandable from 22 em to 33 em and designed to drop off at approximately 6 months. Mortality sensor was set at 2 hours. Once radioed, each fawn was tracked to determine live status at least twice a day and sometimes as many as 6 times per day through 1 September and then once a day, excluding weekends, through 14 December. Determination of live status was done from distances (0.5-5.0+ km) sufficient to minimize disturbance to either the fawn or doe. Mortality signals were investigated immediately upon detection. The site and evidence was surveyed and a determination of cause was assigned as best as evidence offered. If no carcass was present and evidence indicated predation or scavenging, criteria offered in the literature was used to help assign a specific predator (White 1973, Wade and Bowns 1984, Acorn and Dorrance 1990, and Andelt et al. 1998). Most of these; however, deal with adult or domestic animals (except White 1973) and other geographic areas but were used anyway to help evaluate on-site evidence. Ground cover and vegetation was too thick to find actual tracks so, in addition to the above, the following general criteria were used. Coyote kill/scavenge sites typically had only shards of bones, tufts of hairlhide, usually> 1 feeding site within 30 m, and sometimes fawn parts buried in mineral soil. Bear sites were identified by one relatively large feeding site (1-5 m diameter) with the fawn hide nearby and usually intact and inverted (Schlegel 1976); bear usually defecate near their feeding site. The presence of hooves and small leg and cranial bones typify black bear kill sites (Bertram and Vivion 2002:751). Felines (Mt, Lion and bobcat) drag their prey from the kill site to a protected feeding area and cover any remains with litter and duff. Deaths due to vehicle collisions, entanglement in fences, accidents, or human caused (poaching) were categorized as trauma deaths. The unknown category included collars that were found with no carcass parts or other evidence of the fawn in the vicinity. It is possible the collar was carried from a kill site by an avian or terrestrial predator/scavenger. This category undoubtedly includes some collars that were slipped either by maternal grooming or a lucky stroke by a hind foot. Even if the collar had bite marks or blood on it, it was classified as unknown because assigning it to any of the 3 major terrestrial predators would be quite uncertain. Ballard et al. (1999) chose to construe this line of evidence as coyote predation because coyotes are known to prey on fawns in summer. Whole carcasses that were found were examined for external evidence of sickness such as diarrhea or respiratory discharge or external injuries. Proximate site characteristics were described as with other mortalities. Whole carcasses were field classified as sick/starve but the mortality category was changed to trauma if necropsy revealed internal injury from trauma. During the first year, carcasses were frozen and transported to the necropsy laboratory within 5-7 days. Protocol for 2000 and 2001 provided for the carcass to be iced and transported to the laboratory within 2 hours of discovery. A trained pathologist did all necropsy and tissue collections. Details of laboratory procedures, tissue sample collection, diagnostic techniques and disease detection results are found in Myers (2001). �52 Thymus glands were not weighed during the first year of our study but the attending pathologist made a subjective judgment on the condition and size of the thymus at necropsy. During the last 2 years, thymus glands were weighed to the nearest hundredth of a gram. Data interms of survival time were censored 'if the radio dropped off before 14 December. If a radio was not heard and could not be accounted for, survival time data were censored on the last day the radio was heard. All survival time data associated with radios recovered and assigned to the "unknown" category were censored. The key assumptions of a survival study are: 1) animals are sampled randomly, 2) experimental unit survival times are independent, 3) capture and carrying a radio package does not affect survival, 4) the censoring mechanism is random, and 5) emigration is zero (Pollock et al. 1989, Tsai et al. 1999). Because there is high probability of mortality soon after birth in mule deer and because the fawning season is temporally compressed (about 2 weeks), staggered entry of subjects was not used. The time origin for the nonparametric Kaplan-Meier (Kaplan and Meier 1958) survival estimator was the date when the first fawn was radioed. Staggered exits from mortalities and censoring were incorporated in the calculations of survival and confidence limits followingPollock et al. (1989). Large-sample Chi-square tests were used to compare yearly Kaplan-Meier estimates of survival rates. Fisher's Exact Test was used for tests of association and Log Rank statistic was used to compare mortality distributions among years (Cantor 1997). ANOVA and pair-wise mean comparisons were made following the Bonferroni inequality to compare fawn weight and hind foot measurements. The 0.05 significance level was used for all tests. RESULTS During 3 fawning seasons 230 fawns were radio collared with 50, 88,92 captured during 1999, 2000, and 2001, respectively (Table 1). Mean capture date was 19 June (4.83 days SD) and median capture date was 19 June (range 9 June to 6 July) with 94.78% of all captures occurring between 13-30 June. Mean fawn weights at capture were 4.35 kg, 4.50 kg, and 4.13 kg for 1999,2000,2001, respectively and were different among years (P = 0.044). There was also a difference in hind foot length among years (P = 0.002) with mean length of26.14 em, 26.62 em, and 25.63 em for 1999,2000, and 2001, respectively. Both weight and hind foot means were different between 2000 and 2001 (P < 0.017) with 1999 not different from either 2000 or 2001 (P> 0.017). During the first year, the attending pathologist diagnosed 8 of 15 (53%) fawns in the sick/starve mortality category with "severe thymic atrophy". Mean thymus weight was 2.62 g (SD 2.90, n = 10) and 1.96 g (SD 2.40, n = 10) for 2000 and 2001, respectively. These means were not different (P = 0.584) and were combined for a 2-year mean of 2.29 g (SD 2.62, n = 20). Mean June precipitation was 3.66 em in 1999 and 1.04 and 0.86 in 2000 and 2001, respectively. June precipitation on the Uncompahgre Plateau during 1990-1999 was negatively correlated with subsequent December f:d ratios (P = 0.004) but was not correlated with June temperature (P = 0.441). Survival was different (X/ = 6.160, P = 0.046) among years with annual survival (95% CL) of 0.321 (0.125-0.517),0.589 (0.474-0.703), and 0.594 (0.472-0.716) for 1999,2000, and 2001, respectively. Sick/starve was the only cause-specific mortality that approached significance among years (P = 0.070) (Table 2). The major difference was in 1999 with 0.318 mortality due to sick/starve compared to 0.115 and 0.148 in 2000 and 2001, respectively. The 3-year combined mortality due to sick/starve was 0.171 (0.116-0.226). Coyote predation was 0.126 for combined 3-year data and was highly consistent (P = 0.989) among years. Likewise, bear and feline caused mortality was consistent among years (Table 2) and was 0.040 (0.012-0.068) and 0.032 (0.006-0.057), respectively. All predation combined did not differ among years (P = 0.379). Trauma, which included roads, fences, injury, etc. was 0.043 (0.014:-0.072) and unknown causes accounted for 0.047 (0.016-0.077) of the 3-year mortalities. The temporal distribution of mortalities was consistent among years (X/ = 0.680, P = 0.712) with 76.3% . of all mortalities occurring by 31 July. This is the result of the major sources of mortality, sick/starve (73.7%) and predation (75.0%), taking place by 31 July. �53 DISCUSSION Fawn capture effort was focused on the high elevation summer range generally above 2,438 m. How well the sample of fawns captured in this area represents the entire Uncompahgre Plateau population is of major importance. Mule deer tend to be seasonally migratory in the mountainous areas of Colorado (Garrott et al. 1987). However, in the Colorado eastern foothills the majority of the herd may remain at lower elevations yearlong (Kufeld et al. 1989). In Idaho, 26% of a herd that wintered in broad agricultural valleys and low elevation rangelands stayed on the wintering area yearlong (Brown 1992). Wintering area of the Uncompahgre Plateau herd includes some low elevation valleys but raises quickly into sagebrush and pinyon-juniper habitat (Figure 1). To determine how representative the fawns captured at high elevations were of the entire population we used the elevations of winter-captured does (n = 95) during 1997-2000 and their subsequent aerial relocations during mid-May (n = 64) and late-May (n = 144). The mean elevations for capture, mid-May (May 18-21), and late-May (May 28-31) relocations were 1,927 m, 2,551 m, and 2,603 m, respectively with a highly significant difference (P S 0.001); mean of winter capture locations was different (P < 0.05) from the relocations. The 95% kernel home range of all does relocated during midor late-May closely matches the 95% kernel home range of all fawn capture sites (Figure 1). This indicates this population generally fits the near-total migratory pattern described by Garrott et al. (1987). Does had about 3 more weeks to complete their migration to summer/fawning areas, which would have reduced the May relocation home range size because does do not settle on their fawning area and reduce their individual home range until about 3-5 days of parturition (Haegel et al. 1985). The aerial trapping operation did not attempt to capture does among farmsteads along the river bottoms and agricultural lands. These lands compose 6% of the total area (Figure 1). During the 5 years prior to this study, the sex ratio of the Uncompahgre Plateau deer herd averaged 12.3 bucks per 100 does (Colorado Division of Wildlife data). Later mean parturition date, a less synchronized birthing pulse, and lower pregnancy rates resulting in reduced recruitment are some of the postulated consequences of low sex ratios (Squibb 1985, White et al. 2001). In a controlled experiment with elk, the calving season was later by 17 days and extended by 30 days when breeding was done by yearlings compared to 5-year-old bulls; pregnancy rate was 89% with yearlings and 97% with 5year-olds (Noyes et al. 1996). In a free-ranging elk herd, bulls> 1 year old did 76% of the breeding with yearling bulls making an appreciable contribution to successful breeding in this herd and " ... completely compensating for the absence of older bulls" (Squibb 1985:750). Low sex ratios could have a greater impact on deer compared to elk because deer have a tending-bond breeding system and elk form harems (Kie and Czech 2000). Examination of 20 years of sex ratio data and fawn to doe ratios provided no evidence to indicate that sex ratios observed across the state affected population productivity in Colorado mule deer (White et al. 2001). Our data support the contention that low sex ratios did not adversely affect herd productivity. Mean capture date was 19 June in this study, which is similar to the mean fawning date of 18 June (n=215) for a captive herd in Colorado (Robinette et al. 1973). Ninety-five percent of our captures were within a 2-week period, between 13 and 30 June, providing evidence that most does were bred during their first estrus. Estrous cycle is 23-29 days for mule deer and 97% conceive during their first cycle (Anderson and Wallmo 1984). Survival of individual fawns is related to the interaction of nutrition, cover, and climate Picton (1979). On northern ranges, deer are frequently subjected to rigorous winters resulting in chronic malnutrition of does and subsequent stillbirths, weak fawns, and lactation failure (Verme 1969). Although the 3 winters encountered during this study were milder than normal, this population seems to fit the description of a herd that is stressed during winter. During our searches of fawning areas we discovered a total of 9 fawns that were stillborn or died within minuteslhours of birth. In addition, we found one doe that was so weakened from trying to deliver dead twin fetuses that she was captured, restrained, and the fetuses delivered; the doe apparently survived as she was not found in the vicinity the next day. Two mature does were killed or scavenged by bear; one was prime aged (3-4 years old) and the other was of unknown age. Both were found during the peak of fawning - 18 and 19 June. Bear are �54 known to prey on both fawns and adult deer (Behrend and Sage 1974, Conger and Giusti 1992, Verspoor 1983) but bear rarely prey upon healthy adult deer (Verspoor 1983). The best speculation is that the does were in a difficult delivery, as the above mentioned doe, or had died from delivery complications and were scavenged. . During extended periods of damp cool weather fawns may have a higher incidence of exposurerelated complications and deaths (Ginnett and Young 2000). Cool dry summer weather in the northern regions of mule deer range enhanced fawn survival (Picton 1979). Mortality due to sick/starve during 1999 was 0.312 compared to 0.115 and 0.148 for 2000 and 2001, respectively. In an attempt to discover possible causes for the higher sick/starve mortality in 1999 compared to 2000 and 2001, we examined June precipitation and temperature and fawn weights and skeletal development as gauged by hind foot length. We speculated that fawning-season weather might be a factor or that fawn robustness, as measured by fawn weights and skeletal development, might differ among years. Since the 1999 fawn size indicators were not different from the other 2 years when sick/starve mortalities were much lower, it cannot be concluded that fawn size affected the proportion of fawns dying of sickness or starvation. Mean birth weight of fawns from a captive herd was 3.69 kg (n= 172) (Robinette et al. 1973) and is less than means we observed. This is expected because these were nearly true birth weights and our measurements were taken at mean age of 3 days and fawns can gain 0.29 kg per day during their first 12 days (Robinette et al. 1973). Given these weight comparisons, there is no evidence to suggest that fawn weight was a factor in the difference in fawn mortality due to sick/starve among years. Thymus gland development in cervids of similar size to mule deer (fallow deer (Dama dama) and sitka deer (Cervus nippon), follows a pattern of growth during fetal development then remains relatively constant from birth to puberty (Chapman and Twigg 1990). In mule deer (as in other cervids) it then declines into adulthood with seasonal peaks and troughs in summer and winter, respectively (Anderson et al. 1974). Measurements of thymus glands of fawn, yearling, and adult mule deer, Browman and Sears (1956) observed annual cycles of highs in summer and lows in winter with fawns having the highest values of the 3 ages. Thymic atrophy is generally the result of chronic stress and can be seasonal (related to photoperiod or climate) or due to immediate stress such as inanition and disease (Chapman and Twigg 1990). White-tailed deer (0. virginianus) on low energy diets had lower (P < 0.05) thymus weights than deer on high energy diets (Lawrence et al. 1986). Ozoga and Verme (1978) conclude that the thymus provides a reliable index to physiological status and Lawrence et al. (1986) suggest thymus weight of adult does could be used in management decisions. Neonatal white-tailed fawns that were dying of disease or malnutrition had "extremely small" thymus glands averaging 1.3 g (range 0.5-3 .Og, n = 14) compared to healthy fawns of similar age (X = 9.7 g, range 4.3-23.7 g, n = 7) (Ozoga and Verme 1978:794). Our combined 2-year mean thymus weight of 2.29 g (SD 2,.22, n = 20) is similar to the mean of 1.3 g for fawns near death from disease or starvation observed by Ozoga and Verme (1978). In Colorado Anderson et al. (1974) collected 13 mule deer fawns (6 male and 7 female) from 1 to 5 months old; their mean thymus weight was 9.22 g (SD 2.88, n = 13) and was comparable to the healthy fawns sampled by Ozoga and Verme (1978). There were only 3 measurements in our sample of sick/starve fawns that approached the means observed by Anderson et al. (1974) or Ozoga and Verme (1978) for healthy fawns. In 2000 a fawn 68 days old died (6 September) of a hemorrhagic condition and had thymus weight of 8.00 g and a second fawn 69 days old died (8 August) of pneumonia with a thymus weight of7.95 g. Both had fat reserves but were judged to be less than optimal. In 2001, a fawn 21 days old died (7 July) of a hemorrhagic condition and had a thymus weight of 8.28 g; it was judged to have poor fat reserves. Excluding these 3 values, the mean for fawn thymus weight in this study was 1.26 g (SD 0.85, n = 17). The obvious reduced thymus size of fawns dying of sickness or starvation in this study should serve as a point of concern for managers. The reduced thymus size was probably initiated during the fetal stage of development and would indicate the stress factor was affecting the dam. Inanition has been shown to result in reduced thymus size in deer (Lawrence et al. 1986, Ozoga and Verme 1978) so the nutritional status of does during pregnancy, and especially during the last trimester, should be investigated. Fawns dying of sickness and starvation in 2000 and 2001 was nearly half the mortalities �55 attributed to this cause in 1999. The weather during fawning seasons of2000 and 2001 was warm and dry possibly allowing fawns that were not robust to stresses to survive. This study was not designed as a manipulative study where some factor or factors were controlled or manipulated and the impact on fawn survival measured. Coyote predation on neonatal fawns was a popular theory and the opportunity arose to examine the effects of coyote control on a small portion of the study area. The area, 130 km (2% of the total area) included 3 sheep operations on private land. These ranches were used as lambing and summer ranges so coyotes were killed before the sheep were moved onto the area. Coyotes were killed from January trough September with most kills during winter and spring mostly by aerial gunning with a few kills from the ground. There was an active predator (coyotes and bear) control program during 1994 through 2001 on this area with a total of 187 coyotes and 17 bear killed (Animal and Plant Health Inspection Service, Wildlife Services records, Grand Junction, Colorado). During the 3 years of the fawn survival study there were 53 coyotes and 11 bear killed in the predator control area. Forty fawns were collared on this corresponding area allowing a comparison of fawn survival on and off the control area. Seven fawns were killed by predators inside the control area (4, coyote; 1, bear; and 2 feline) and 37 outside the area (24, coyote; 8 bear; and 5 feline). Comparison of predator kills inside and outside the area resulted in a Fisher's Exact Test result with P = 0.830; limiting the test to only coyote kills the results offered no evidence of an association between coyote control and fawn survival (P = 0.794). For fawn survival study results to be comparable they should be similar in the following: 1) fawn age at capture, 2) equipment and handling procedures, 3) tracking frequency, 4) nutritional status of does, 5) vegetation and hiding cover, 6) predator density, and 4) mortality identification criteria. Although it is impossible to match all of the above for comparisons, generalizations may be useful to assess the possible impact of the various mortality sources, particularly predators, on neonatal fawns. In Montana Hamlin et al. (1984) radioed 91 fawns over a 6-year period (1976-1981) and tracked them at 2-3-day intervals. Fawns up to 3 weeks old were included in their sample (Riley and Dood 1984). Mortalities were categorized as either "probable or known coyote involved deaths" or "other". They found no whole carcasses, which may be the result of tracking them on 2-3 day intervals allowing scavengers (including coyotes) time to find the carcass. Eighteen of20 deaths (90%) were attributed to coyotes and 2 (2.2%) were listed as "other". Eighteen mortalities of91 radioed fawns (19.8%) were assumed to be coyote-caused and total survival was 78.0%, which is higher than we observed. Their sample of fawns was most likely older than our sample. They used aerial observers to spot fawns indicating that the fawns were old enough to be trailing the does and ground crews used long-handled hoop nets to capture the fawns indicating the fawns were no longer in the hiding phase. A sample of older fawns would miss mortalities immediately after parturition and result in a higher survival rate compared to a sample of younger fawns such as ours. A fawn survival study on a 51.8 km Steens Mountain study area in Oregon during 1971-74 had a sample of 106 neonate fawns aged 1-14 days old and were monitored every 3-4 days (Trainer 1975). Mortality attributed to coyotes was 10.3% and-for all predators it was 15.1%. Disease and starvation mortality accounted for 9.4% of the total; survival was 72.6%. Preliminary results of an Idaho study with a sample of 69 fawns during 1998-99 exhibited a loss to coyotes of 13% and total predators (coyotes and lions) of32%. Overall survival was 44.9%. These results are not directly comparable to our study because coyotes and lions were controlled on a portion of the area. Given the shortcomings of comparing results of studies where protocol is not similar, neonatal fawn mortality attributed to coyotes is in the range of 10-20% for the various studies. Survival is highly variable ranging from 44.9% to 78.0%; the range in survival is undoubtedly heavily influenced by differences in age of fawns at capture (beginning of monitoring). Neonatal survival through 14 December does not account for observed low f:d ratios. In addition to pregnancy and fetal rates from the preliminary productivity study in February 1999, data available for this herd included random quadrat-based population size and herd structure estimates in December 1999. Survival estimates for bucks, does, and fawns during winter of 1999-2000 based on radioed animals �56 (Bruce Watkins, Colorado Division of Wildlife, Montrose, personal communication) were available. We used this information and incorporated our observed year 2000 summer fawn survival (0.5887) to calculate the expected f:d ratio for December 2000. Our calculations included 10% lower fetal rates of primaparous does (Robinette et al. 1973, Trainer et al. 1981) and a differential of viable neonates of96% for multiparous does and 82% for primaparous does (Robinette et al. 1973). They did not have an estimate of fetal rate, but the birth rate of 1.92 fawns per doe is similar to the maximum fetal rate for mule deer (Jensen and Robinette 1955). Hamlin and Mackie (1989) estimated 80% viable neonates for all-age does; this estimate includes fetal and neonate mortality. Using differential viable rates of Robinette et al. (1973)(96% and 82%) the projected December f:d ratio was 75 and using all-age estimated viable rate of Hamlin and Mackie (1989) (80%) the projected December f:d ratio was 64. Both of these projections were higher than the observed f:d ratio of 51 as estimated by a random quadrat helicopter survey in December 2000. Our data are most comparable to those of Hamlin and Mackie (1989) because theirs was a wild population. The herd studied by Robinette et al. (1973) was a fed captive population but indicates that a proportion of fawns born are not viable for various reasons even in a well nourished herd. Assuming the f:d ratio of 51 from the helicopter survey is unbiased, mortality of 37% from February when fetal rates via ultrasound were taken and June when fawns were captured would be necessary to match the observed f:d ratio. This indicates fetal or early neonate mortality that could be caused by inanition of the does, disease, or effects of poisonous plants. The importance of nutrition in reproductive success and recruitment is well documented. However, in the study by Robinette et al. (1973) fawn weights did not vary with nutrition level of does. The fawn weights in our study were comparable to those of other studies (Robinette et al. 1973, Stieigers and Flinders 1980, Trainer et al. 1981, and others). Apparently, fawn weights do not provide a useful index of doe nutritional status. Although fawns are born at relatively uniform weights the nutritional status of the doe can affect fawn survival through indirect effects such as susceptibility to predation and disease. The dam can be directly affected by failure to conceive, resorption of fetuses, and inability to nourish offspring (Dietz and Nagy 1976). What appears to be excessive fetal and neonate mortality from early pregnancy to a few days postparturition and discovery of 9 under-sized (X = 1.67 kg, n 7) stillborn fawns may be indicative of an under nourished adult population. Increased loss to sickness and starvation during 1999 when June precipitation was higher that the other 2 years may also indicate that neonates are in a compromised condition and not robust to stresses. Hemorrhagic diseases (HD), bluetongue (BT) and epizootic hemorrhagic disease (EHD), of the genus Orbivirus are present in the Uncompaghre Plateau mule deer herd (Myers 2001). These diseases are capable of causing significant mortality and Howerth et al. (2001) cite literature documenting many outbreaks in Western North America dating back to 1886. In temperate regions, mortalities from hemorrhagic disease usually occur in late summer, before first frost, and epidemics can develop when conditions are favorable to the vector, Culicoides spp. These outbreaks are usually sporadic (Howerth et al. 2001) and localized with total mortality estimated at < 1% for mule deer (Thome et al. 1988). Infection with BT or EHD in mule deer may be asymptomatic, result in chronic disease, nonfatal infections, or sudden death (Howerth et al. 2001). Fever, internal bleeding, and shock resulting in death characterize hemorrhagic diseases (Shope 1967). Death may happen so suddenly that some animals may die" ... while walking or running" while others struggle in lateral recumbency position (Thome et al. 1988:115). Because this disease strikes quickly, animals in good physical condition may be found dead from HD (Chalmers et al. 1964). Only 1 positive result based polymerase chain reaction (PCR) test was obtained for HD during our 3-year study. The low detection rate may be because these are RNA viruses and are very unstable in an open environment (Myers 2001). There may have been other deaths from HD based on the time of year, hemorrhagic condition, and the relatively good condition of the fawn at death indicating a sudden death. Five fawns that died between 18 August and 4 October satisfy the above criteria. An adult female found near (100 m) one of the fawns tested positive by PCR for EHD. -= �57 Hemorrhagic disease is present on the Uncompahgre Plateau but it is hard to assess the impact on the mule deer population. It is unlikely that an epidemic ofHD occurred during this 3-year study. There were no reports of numerous dead deer as was the case in other epidemics (Chalmers et al. 1964, Thome et al. 1988) and field personnel did not observe any abnormal concentrations of mortalities of either radioed fawns or unmarked deer during late summer. Diseases that affect the reproductive capacity of a host population are most liable to have a noticeable impact on that population (Anderson and May 1979). Bovine viral diarrhea virus (BVDV) infections produce abortions, fetal malformations, stillbirths, weakened neonates, and immunosuppression in domestic livestock (Baker 1995, Van Campen et al. 2001a). There is a> 60% prevalence of BVDV titers in the adult population of deer on the Uncompahgre Plateau (Myers 2001). A mule deer population from northwestern Wyoming, USA, also had a 60% prevalence ofBVDV titers (Van Campen et aI2001a), and a serological survey of 4 western national parks resulted in 59% prevalence in mule deer (Aguirre et al. 1995). Viral isolation (VI) is the most reliable method to determine exposure to BVDV and isolations from wild ruminants are rare (Van Campen et al. 2001a, Van Campen et al. 2001b). Isolates were obtained from 2 fawns in our study. These fawns died in the same general area « 500 m apart) and within 2 days of each other, 17 and 19 July. Diseases that have low mortality and produce immunity with exposure are self-limiting (Myers 2001). In closed herds with no previous exposure, introduction of BVDV can result in the loss of75% of the first neonate cohort after exposure through abortions, stillbirths, and compromised immune response (Hana Van Campen, personal communication). With a high proportion of the Uncompahgre Plateau deer herd having titers, and presumed immunity to BVDV, this disease should not have a significant impact on the overall herd performance. However, its presence is certainly a depressant to some unknown degree. Other than the 2 fawns that provided VI of BVDV, there were 2 other fawns with symptoms of being exposed to BVDV in utero. One was hydrocephalic (1.90 kg) and the other had skeletal deformities (2.09 kg) both characteristic of BVDV exposure. BVDV was isolated from a stillborn fawn from northern New Mexico that had an atrophied thymus and weighed 2.3 kg (Hibler 1981). The high prevalence of BVDV in the 2 above mentioned mule deer populations suggests that this virus circulates in these populations (Van Campen et al. 2001 b) without exposure to outside sources such as cattle herds. High prevalence of titers to BVDV does not necessarily mean a population suffers significant consequences. In immunocompetent cattle the majority of infections (70-90%) are subclinical (Baker 1995). So unless the immune response of mule deer is compromised from some other cause, the impact of BVDV may not produce significant or detectable manifestations in population performance. Ingestion of poisonous plants can impair reproductive functions of domestic livestock (Panter et al. 2002). Some of the plants poisonous to livestock are found on the Uncompahgre Plateau and could conceivably also affect the wild ruminants of the plateau. Lupines (Lupinus spp.) can cause skeletal defects through the effects of alkaloids that are toxic to fetuses (Panter et al. 2002). We found a stillborn fawn (2.09 kg) with "Multiple congenital skeletal defects, including flexion contraction, limbs, neck, and thoracic spine" (from lab report) with minimally deformed joints and normal limb bones; all of these symptoms fit lupine poisoning as described by (Panter et al. 2002). In the year following our study, another stillborn fawn with severe skeletal deformities was found (Chad Bishop, Colorado Division of Wildlife, Montrose, personal communication). Both of these fawns came from the same general area of the plateau where lupine is common. Livestock loses to poisonous plants is associated with range in poor condition (Ralphs 2002) and this area is heavily grazed. We have observed some possible pre-natal mortality from poisonous plants; it could be one of many mortality sources but it is unlikely this is a major factor in herd recruitment. MANAGEMENT IMPLICATIONS Conditions of Western ranges have changed dramatically from pristine times (Vale 1975) through an era of extensive overgrazing to the current level of management. The era of unsustainable livestock grazing promoted shrub and forb growth to the benefit of deer (Clements and Young 1997) and led to the �58 eruption of mule deer populations (Gruell 1986). Subsequent management and wild fire control has resulted in over-mature shrubs and invasion of woody species into shrub communities reducing carrying capacity for deer (Gruell 1986). This trend continues. Nutrition is key to recruitment. It is a very common conclusion that although predators can cause a short-term effect on a deer population, alternate prey species abundance dictates the density of coyotes (Hamlin et al. 1984). Increases in vegetation production has a positive effect on abundance of alternate prey species (Hamlin et al. 1984) and may explain why Salwasser (1979) observed that coyote densities and fawn survival trend in unison. Most current land use patterns in the West are detrimental to deer and rather than control of hunting pressure or predators " ... deer numbers are ultimately governed by quality and quantity of habitat" (Connolly 1981 :238). Peek et al. (2002) and Salwasser et al. (1978) suggest that long-term decline of deer populations is not the result of predation but the result of deteriorating forage conditions. Given the high reproductive potential of mule deer, it seem reasonable that improving range conditions on the Uncompahgre Plateau and other mule deer ranges of the West would be the most fruitful for increased and long-lasting improved recruitment. Ballard et al. (2001: 112) state that "The relationship between predators and their prey is a very complex issue". They list numerous possible causes for deer declines including habitat loss (i.e. food and cover), disease, predation, competition, and others. The results of the Uncompahgre Plateau study do not provide evidence to suggest that predators are the cause of low recruitment in this particular herd. Coyote predation accounted for 0.126 of the neonatal mortality with bear and feline predation accounting for 0.040 and 0.032, respectively. Whether or not this degree of predation would warrant a control program would be a societal value judgment based on both the cost and the ethics of killing one species to favor another. Although there have been no studies that demonstrate predator reduction resulted in more mule deer in the possession of hunters (Ballard et al. 2001), that is obviously the ultimate objective of predator control. Predator control is a value judgment and has segments of the public sharply divided on the need or desirability for such a program. This study has provided information for a particular study area on the extent of fawn mortality from various causes that should be of assistance to the entities that make management decisions. ACKNOWLEDGMENTS This study was a contribution of Federal Aid Project W-1S3-R. We especially thank the fawn capture crew members. They exhibited the patience and persistence necessary to capture, handle, and radio track a reasonable sample of fawns, which contributed to the value of the study: T. Baker, B. Banulis, P. Burke, B. Diamond, B. Dreher, J. Foster, J. Griggs, D. Gustine, B. Hoffner, B. Lamont, H. McNally, J. Risher, E. Scott, J. Skinner, D. Swanson, and S. Znamenacek. We thank W. Andelt for input during the early phases of the study. Local Division of Wildlife field personnel were instrumental in gaining permission on private land and for helpful information on field access in addition to helping capture fawns: R Arant, G. Bock, M. Caddy, D. Coveri, J. Ellenberger, V. Graham, M. King, M. Mclain, K. Miller. Others that assisted in fawn capture: T. Burke, and D. Steele. We thank D. Moreno for providing predator kill figures for the area of interest. The following were instrumental in establishing field handling procedures of fawn carcasses and necropsy protocol: D. Gould, K. Larsen, G. Mason, M. W. Miller, E. Myers, B. Powers, T. Spraker, and H. Van Campen. D. Schweitzer did most of the necropsies. M. Farnsworth and S. Strain provided assistance in graphic presentation and analysis. Aircraft piloting for radio tracking, field assistance, and general support of the project provided by J. Olterman is appreciated; R. B. Gill provided administrative support and G. Miller provided administrative support and editorial comments. Planning and statistical consultation by G. White improved the overall results. M. Potter provided late season radio tracking and radio retrieval. We thank colleagues T. Beck, and C. Bishop for many helpful suggestions and discussions and for their field assistance. The interest, support, and commitment for the duration of the project by B. Watkins were valuable contributions. We thank the various reviewers of the manuscript for their constructive criticism and suggestions. �59 LITERATURE CITED Acorn, R. C., and M. J. Dorrance. 1990. Methods of investigating predation oflivestock. Alberta Agriculture Protection Branch. Edmonton. Canada. Aguirre, A. A., D. E. Hansen, E. E. Starkey, R. G. McLean. 1995. Serologic survey of wild cervids for potential disease agents in selected national parks in the United States. Preventive Veterinary Medicine 21:313-322. Andelt, W. F., M. 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Assessing the role of selected infectious disease agents in neonatal mule deer fawn mortality on the Uncompahgre Plateau of Western Colorado. M. S: Thesis, Colorado State University, Fort Collins, Colorado, USA. �61 Noyes, J. H., B. K. Johnson, L. D. Bryant, S. L. Findholt, J. W. Thomas. 1996. Effects of bull age on conception dates and pregnancy rates of cow elk. Journal of Wildlife Management 60:508-517. Ozoga, J. J. and L. J. Verme. 1978. The thymus gland as a nutritional status indicator in deer. Journal of Wildlife Management 42:791-798. Panter, K. E., L. F. James, D. R. Gardner, M. H. Ralphs, J. A. Pfister, B. L. Stegelmeier, and S. T. Lee. 2002. Reproductive losses to poisonous plants: Influence of management strategies. Journal of Range Management 55:301-308. Peek, J. M., B. Dennis, and T. Hershey. 2002. Predicting population trends of mule deer. Journal of Wildlife Management 66:729-736. Picton, H. D. 1979. A climate index and mule deer fawn survival in Montana. International Journal of Biometerorology 23(2):115-122. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Ralphs, M. H. 2002. Ecological relationships between poisonous plants and rangeland condition: A review. Journal of Range Management 55:285-290. Riley, S. J. and A. R. Dood. 1984. Summer movements, home range, habitat use, and behavior of mule deer fawns. Journal of Wildlife Management 48:1302-1310. Robinette, W. L., C. H. Baer, R. E. Pillmore, and C. E. Knittle. 1973. Effects of nutritional change on captive mule deer. Journal of Wildlife Management 37:312-326. Salwasser, H. J. 1979. Ecology and management of the Devil's Garden Interstate deer herd and range. Dissertation, University of California, Berkeley, USA. __ , S. A. Holl, and G. A. Ashcraft. 1978. Fawn production and survival in the North Kings River deer herd. 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Uncompahgre Plateau Partners (BLM, CDOW, Public Lands Partnership, USFS). 2002. Uncompahge Plateau Project (UP) Plan: A collaborative approach to restore and maintain the ecosystem heath of the Uncompahgre Plateau in western Colorado. Available at the Colorado Division of Wildlife Service Center, Montrose, Colorado, USA. Unsworth, J. W., D. F. Pac, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Vale, T. R. 1975. Presettlement vegetation in the sagebrush-grass area of the Intermountain West. Journal of Range Management 28:32-36. Van Campen, H., K. Frolich, and M. Hofinann. 2001a .. Pestivirus infections. Pages 232-244 in E. S. Williams and I. K. Barker, editors. Infectious diseases of wild mammals. Iowa State University Press, Ames, Iowa, USA. __ , J. Ridpath, E. Williams, J. Cavender, J. Edwards, S. Smith, and H. Sawer. 2001b. Isolation of bovine viral diarrhea virus from a free-ranging mule deer in Wyoming. Journal of Wildlife Diseases 37:306-311. Verme, L. J. 1969. Reproductive patterns of white-tailed deer related to nutritional planes. Journal of Wildlife Management 33:881-887. �62 Wade, D. A., and J. E. Bowns. 1984. Procedures for evaluating predation on livestock and wildlife. Texas Agricultural Experiment Station Bulletin B-1429, College Station. White, G. C. and R. M. Bartmann. 1998. Mule deer management - What should be monitored? Pages 102-116 in J. C. De Vos, Jr., editor. Proceedings of the 1997 deer-elk workshop, Rio Rico, Arizona. Arizona Game and fish Department, phoenix, Arizona, USA. ___, D. F. Freddy, R. B. Gill, and J. H. Ellenberger. 2001. Effect of adult sex ratio on mule deer and elk productivity in Colorado. Journal of Wildlife Management 65:543-551. . White, M. 1973. Description of remains of deer fawns killed by coyotes. Journal of Mammalogy 54:291-293. Young, R. G. and J. W. Young. 1984. Colorado West land of geology and wildflowers. Artistic Printing, Salt Lake City, Utah, USA. Table 1. Fate of neonatal mule deer fawns from capture (mean 3 days old) to 14 December, Uncompahgre Plateau, west central Colorado, USA, 1999-2001. Mortality Causes Sick/Starve Coyote Bear Feline Trauma Unknown Total mortality Surviving Total sample Censored 1999 2000 2001 Total 15 6 3 4 1 2 31 19 50 12 10 11 3 2 4 5 35 53 88 11 13 11 3 1 4 3 35 57 92 20 38 28 9 7 9 10 101 129 230 43 Table 2. Chi-square comparison of mortality source proportion by year for mule deer neonates from capture (mean 3 days old) to 14 December on the Uncompahgre Plateau, west central, Colorado, USA. Kaplan-Meier staggered exits to account for censored subjects were used. . . Mortality Causes 1999 2000 Sick/starve Coyote Bear Feline Trauma Unknown 0.318 0.126 0;060 0.083 0.025 0.042 0.115 0.129 0.034 0.023 0.048 0.058 2001 0.148 0.121 0.033 0.012 0.047 0.037 )(1- 5.330 0.023 0.416 2.330 0.568 0.388 P 0.070 0.989 0.812 0.312 0.753 0.824 ..f �63 Figure 1. Uncompahgre Plateau mule deer Data Analysis Unit, D-19, is shown outlined in red. The 95% kernel home range for radioed does aerial located on May 18 and May 31 is outlined in black with black dots representing individual locations. Fawn capture locations are seen as white dots and the 95% kernel home range outlined in white. Blue shading shows pinyon-juniper type and higher elevation vegetative types (summer range) are shown in green, yellow, and brown. Agricultural land is in pink. See text for type descriptions. I. ��, / 65 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 JOB PROGRESS REPORT Suteof ~C~o=lo=r=a=d=o Work Package No. ----"'-30"""'0~1'__ _ Deer Conservation _ Task No. ~------------~------------4 Project NO. Mammals Research Program Effect of Nutrition and Habitat Enhancements on Mule Deer Recruitment and Survival Rates W_,_,__-_.o..;15""'3"--"'-'R,__ _ Research and Development Period Covered: July 1,2001 - June 30, 2002 Authors: C. J. Bishop and G. C. White Personnel: D. L. Baker, T. D. 1. Beck, G. Bock, S. K. Carroll, D. Coven, K. Crane, D. J. Freddy, L. Gepfert, R. B. Gill, R. Harthan, M. McLain, E. P. Myers, G. C. Miller, J. Olterman, J. A. Padia, T. M. Pojar, C. M. Solohub, B. E. Watkins, CDOW; L. H. Carpenter, WMI; J. Sazma, B. Welch, BLM, Montrose, CO. ABSTRACT ""'\ .. _--" .. To further understand the factors that caused deer numbers to decline in western Colorado during the 1990s, we designed and initiated a field experiment to measure deer population parameters in response to nutrition and habitat enhancement treatments. During November 2000 - March 2002, we captured and radio-collared 112 mule deer in a treatment unit and 109 mule deer in a paired control unit during winter . on the Uncompahgre Plateau in southwest Colorado. We enhanced the nutrition of deer in the treatment unit by providing a safe, pelleted supplemental feed on a daily basis from December through April each winter .. Early winter fawn:doe ratios were measured using helicopter and ground classification surveys the year following treatment delivery to determine whether fawn production and survival increased as a result of enhanced nutrition of adult females. Based on multiple age classification surveys, we concluded that the winter nutrition enhancement treatment did not cause an increasein neonatal production and survival during2001. However, fawn production and summer-fall survival were atypically good during 2001, and not representative of most years during the past decade when the population declined. We also measured overwinter fawn survival rates in response to the treatment. The simplest model which effectively explained survival (X25J = 51.87, P = 0.440) included treatment (X21 = 9.95, P = 0.002) and early winter fawn mass (X2J = 8.33, P = 0.004). From December 1,2001, through May 31,2002, the survival rate of fawns was significantly greater (X2J = 13.216, P < 0.001) in the treatment unit (0.865, SE = 0.056) than in the control unit (0.510, SE = 0.080); and fawns that survived the winter averaged 2.9 kg heavier than fawns that died (FJ = 6.11, P = 0.016). Early winter fawn mass was not different among treatment and control fawns (FJ = 0.36, P = 0.550), thus the effect of the treatment was not confounded with fawn mass. Simply, heavier fawns in both experimental units had higher survival probabilities. During winter 200 1:-02,which was a mild to average winter, the nutrition enhancement treatment clearly improved overwinter fawn survival, and thus yearling recruitment. We will continue this portion of the research for 2 more years. The results reported here are preliminary and should be treated as such. - ~: <- :'.'. . . ��67 EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES C. J. Bishop and G C. White P. N. OBJECTIVES 1. To determine experimentally whether enhancing mule deer nutrition during winter and early spring by supplemental feeding increases December fawn:doe ratios and overwinter fawn survival. 2. To determine experimentally to what extent habitat treatments replicate the effect of enhanced nutrition from supplemental feeding. SEGMENT OBJECTIVES 1. Capture and radio-collar target sample of adult female mule deer and 6-month-old fawns. 2. Deliver nutrition enhancement treatment to all deer occupying the treatment area. 3. Measure overwinter adult female and fawn survival rates and early winter fawn:doe ratios in the treatment and control areas. INTRODUCTION Mule deer numbers apparently declined during the 1990's throughout much of the West, and have clearly decreased since the peak population levels documented in the 1940's-60's (Gill et al. 1999, Unsworth et al. 1999). Biologists and sportsmen alike have concerns as to what factors may be responsible for declining population trends. Although previous and current research indicates that multiple interacting factors are responsible, habitat and predation have received the focus of attention. A number of studies have evaluated whether predator control increases deer survival, yet results are highly variable (Connolly 1981, Ballard et al. 2001). Together, predator control studies with adequate rigor indicate that predation effects on mule deer are variable as a result of time-specific and site-specific factors. Studies which have demonstrated deer population responses to predator control treatments have failed to determine whether predation is ultimately more limiting than habitat. Numerous research studies have evaluated mule deer habitat quality, but virtually no studies have documented population responses to habitat improvements. In many areas where declining deer numbers are of concern, predation is common yet habitat quality appears to have declined. The question remains as to whether predation, habitat, or some other factor is more limiting to mule deer in these situations, and whether habitat quality can be improved for the benefit of deer. It may also be that no single factor is any more or less important than another, and that a more comprehensive understanding of multi-factor interactions is paramount. We designed a field experiment to measure deer population responses to nutrition and habitat enhancement treatments, to further understand the causative factors underlying observed deer population dynamics. We are conducting the study on the Uncompahgre Plateau, where several predator species (i.e. coyotes, mountain lions, and bears) are present in abundant numbers. In addition to predation, myriad diseases in combination proximately affect survival of the Uncompahgre deer population (Pojar 2000, RE. Watkins, unpublished data). Predator numbers have not and will not be manipulated in any manner during the course of the study. All factors have been left constant with the exception of deer nutrition and habitat. Deer nutrition is being enhanced by providing supplemental feed to deer during the winter. If December fawn:doe ratios and overwinter fawn survival improve as a direct result of the nutrition enhancement treatment, then we can presume that deer nutrition is ultimately more limiting than . predation or disease. The second phase ofthe field experiment will incorporate habitat manipulation �68 treatments, which will consist of prescribed fire or mechanical techniques to set back succession of pinyon-juniper habitat in an effort to improve the vigor and quality of winter habitat for mule deer. Deer population responses will be measured in relation to the habitat manipulations in the same manner as the supplemental feed. Thus, the experiment allows us to determine whether nutritional quality of habitat is ultimately more limiting than other factors in a late-seral pinyon-juniper/sagebrush landscape, and if so, whether habitat can be effectively improved for mule deer. The results will also advance our current understanding of multi-factor interactions, with direct implications for mule deer management. MATERIALS AND METHODS Experimental Approach Experimental Design and Study Area We non-randomly selected four areas on the Uncompahgre Plateau to create 4 experimental units (A-D) (Fig. 1). Treatments were randomly assigned to the experimental units. The following criteria were used to select experimental units: 1.) _Deer densities (~50-80 deer/mi"): areas were selected where deer densities were sufficient to meet sample size requirements within the experimental unit, while simultaneously selecting areas that would require feeding less than ~500 animals during a normal winter 2.) Buffer zones: areas were selected such that experimental units would be separated by several miles of non-treatment area (buffers) to prevent deer from occupying more than one experimental unit 3.) Similarity: areas were selected that comprise relatively similar habitat complexes and deer densities that are representative of the overall area 4.) Elk populations: areas were selected to minimize the number of elk present during normal winters Units A and B are receiving the nutrition enhancement treatment in a cross-over experimental design, and are being used to address P.N. Objective 1. Unit A served as the treatment unit, while Unit B served as the control, for the first 2 years of research (2000 - 2002). Beginning November 2002, Unit B will receive the treatment while Unit A will serve as the control. Upon completion ofP.N. Objective 1, Units C and D will be used to conduct phase 2 of the research, or P.N. Objective 2. Habitat in one unit will be manipulated to set back plant succession (treatment), while habitat in the other unit will remain unchanged (control) throughout the experiment. 2001-02 2002-03 2003-04 Control- 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 Figure 1. Schematic representation of experimental units and associated treatments. The nutrition enhancement cross-over design will encompass 4 years; monitoring in the habitat manipulation experimental unit and paired control area will encompass'approximately 6 years. �69 The 2 experimental units (A and B) receiving the nutrition enhancement treatment are (Figs. 2 and 3): (1) The Colona Tract of the Billy Creek State Wildlife Area (2) Bureau of Land Management lands adjacent to Shavano Valley as defined by the following: Within Dry Creek Basin Quadrangle (USGS 7.5 Minute), includes Sections 6 and 7 in T. 48 N.-R. 10 W. and Sections 1,2, 10, 11, 12, 13, 14, 15 in T. 48 N.-R. 11 W. This area roughly includes 38°25'00" - 38°27'30" Latitude and 108°00'00" - 108°04'30" Longitude. Gunnison County Figure 2. Location of Colona and Shavano (Units A and B) experimental units in Game Management Unit 62 on the Uncompahgre Plateau, southwest Colorado. �70 Figure 3. Colona and Shavano experimental units (Units A and B), located in Game Management Unit 62 on the Uncompahgre Plateau, southwest Colorado. Polygons represent the nucleus of each experimental unit, which is where animals have been collared and the nutrition enhancement treatment delivered. �71 Response Variables The primary response variable is fawn:doe ratios measured during December and January following the previous winter's treatments. The fawns counted during early winter age classification were born the summer following the winter treatments, and classified when they were 6 months of age. Thus, we are measuring the effect of enhanced adult doe nutrition during winter on subsequent fawn production and survival. Fawn:doe ratios are currently being measured in Units A and B corresponding to P.N. Objective 1. The second response variable is overwinter fawn survival, measured from radio-collared fawns during the winter in direct response to the enhanced winter nutrition treatment. We are also measuring overwinter and annual survival of adult does as a function of enhanced winter nutrition. Sample Size The primary response variable is the mean fawn:doe ratios of the radio-collared does wintering on the experimental unit of interest. We desired to detect an effect size, i.e., an increase in fawn:doe ratios in response to the treatments, in the range of 15 to 20 fawns per 100 does. These values were based on simple population models with overwinter fawn survival of 0.444, adult female survival of 0.853, and December fawn:doe ratios of 66 fawns per 100 does to obtain a stationary population (Unsworth et al. 1999). Based on surveys ofDAU D-19 from 1992-96, the standard deviation of the fawn:doe ratio for groups with at least one adult female was 57, with a mean of 41. Using an expected standard deviation of 57, the standard error of the mean fawn:doe ratio for 40 radio-collared does is 57/(40112) = 9.0, which is the expected standard deviation of measured fawn:doe ratios on each of the experimental units. We assessed power of the proposed experiment using SAS Analyst". We used a two-sample z-test with a sample size of 4, representing the years of the study where treatment effects will be measured. The power of the design to detect an increase of 20 fawns per 100 does is about 0.87. A sample size of 40 fawns per experimental unit per year provides a power of 0.81 to detect a difference of 0.15 in survival between 2 experimental units if survival on the control unit is 0.40. We expected to see an increase in fawn survival (effect size) of approximately 0.15, because this was the difference measured in the density reduction experiment conducted by White and Bartmann (1998). Capture Methods Deer were captured using baited drop nets (Ramsey 1968, Schmidt et al. 1978) and helicopter net guns (Barrett et al. 1982, van Reenen 1982). Drop nets were baited with certified weed-free alfalfa hay and apple pulp. Drop nets were used as the principal capture technique during a 3-week capture period; helicopter net-gunning was used at the end of the capture period to secure the remainder of deer needed to meet our target sample sizes. All deer were hobbled and blind-folded after being captured. All deer captured via drop nets were carried away from the net to an adjacent handling site using stretchers. Deer were fitted with leather radio collars equipped with mortality sensors, which cause an increase in pulse rate after remaining motionless for 4 hours. Permanent collars were placed on adult females, while temporary collars were placed on fawns. To make collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars 2::6months post-capture. A rectangular piece of flexible plastic (Ritchey" neck band material) engraved with a unique identifier was stitched to the side of each collar. The unique identifier consisted of 2 symbols for adult females, and only 1 symbol on 2 different colors of plastic for fawns. The identifiers were necessary to visually identify deer from the ground. This has allowed us to effectively document use of the treatment, measure fawn:doe ratios from the ground, and assess experimental unit population size via mark-resight estimators. We recorded the weight, hind foot length and chest girth of each deer, and collected blood samples from most does and fawns to evaluate disease prevalence. �72 Measurement of Fawn:Doe Ratios and Overwinter Survival Each winter we used the radio-collared does to measure fawn:doe ratios in each experimental unit. The resulting fawn:doe ratio is a measurement of the previous year's treatment effect. We measured fawn:doe ratios using 2 techniques: (1) We located the sample of radio-collared does in each experimental unit from a fixed-wing airplane, and used the set of locations to define boundaries for the experimental unit. Shortly after (i.e. 1-2 days), we used a helicopter to systematically fly the defined unit and classify all deer groups encountered. For each group, we documented whether a radio-collared doe was present. (2) We located each radio-collared doe by radio telemetry from the ground. The group of deer with the collared doe was counted and classified by age and sex. Both methods have been employed to gather as much information as possible to determine whether there was a treatment effect. The "true" value cannot be measured perfectly because of the inherent biases and potential sources of error associated with each technique. Thus, by employing both techniques, we have a greater chance of fully understanding whether the treatment caused an effect. We measured survival by radio-monitoring collared deer to determine fate (live/mortality). We also attempted to determine the cause of each mortality, with a primary goal of distinguishing between predation and non-predation mortality causes. Deer were radio-monitored on a daily basis during the winter, which typically allowed us to arrive at mortality sites within 24 hours. Treatment Delivery Deer nutrition was enhanced in the treatment area by providing a safe, pelleted supplemental feed. The supplemental feed was developed through extensive testing with both captive and wild deer (Baker and Hobbs 1985, Baker et al. 1998), and has been safely used in both applied research and management projects. Pellets were distributed daily using 4wd pickup trucks and ATV s on primitive roads throughout the experimental unit to provide a food source for the entire deer population in the treatment unit. Each 501b. bag of pellets was carried :s;200m from the truckiATV and distributed by hand in approximately 2030 small piles of feed in a linear fashion. Numerous bags were distributed in successive order allowing us to create a line of feed that spanned most of the treatment area, which prevented animals from concentrating in any single location. This feeding technique also prevented dominant animals from restricting access to the food supply because of the large area over which pellets were distributed. We attempted to supply pellets ad libitum such that a small residual remained when the next day's ration was provided. Collared deer were closely monitored to ensure that treatment deer remained in the experimental unit and actually consumed the feed, and to make sure that non-treatment deer remained in the control unit, which they did. Treatment deer that did not regularly consume the feed were withdrawn from the sample for purposes of measuring treatment effects. The pelleted ration was commercially produced in the form of2xlxO.5-cm wafers (Baker and Hobbs 1985). Feed constituents (i.e. digestibility, protein, gross energy etc.) vastly exceeded those of typical winter range deer diets; exact constituent values are provided by Baker et al. (1998). When provided ad libitum, the feed should have allowed deer to meet or exceed nutritional requirements for growth and maintenance (Ullrey et al. 1967, Verme and Ullrey 1972, Thompson et al. 1973, Smith et al. 1975, Baker et al. 1979, Holter et al. 1979). The basis for feeding such high quality pellets was to ensure that the treatment (enhanced nutrition) was effectively delivered to the deer. Our intent was not to determine the exact level of nutrition necessary to increase fawn recruitment, but rather to determine if nutrition is a limiting factor to recruitment. If nutrition is in fact limiting, we will rely on the habitat manipulation treatment to evaluate what exactly can be done via management to increase fawn survival and recruitment. �73 Habitat Manipulations In order to accomplish P.N. Objective 2, habitat will be manipulated in experimental unit D through collaboration with the Uncompahgre Ecosystem Restoration Project (UP), which comprises personnel from the Division of Wildlife, U.S. Forest Service, Bureau of Land Management, Public Lands' Partnership, and a variety of other public and private stakeholders. The UP committee is using an experimental landscape approach to manipulate various habitats in a mosaic pattern throughout the Uncompahgre Plateau. We will focus our intensive deer monitoring on one of these habitat manipulations that will be conducted in experimental unit D. This portion of the research has not yet been initiated. A complete description of our planned protocols to accomplish P.N. Objective 2 is provided in the Program Narrative (Bishop and White 2000). Statistical Methods Once data collection is completed for the full study, we will test for differences in fawn:doe ratios between experimental units and years using the following statistical model: Yijk = Ji + ex; + Pk + aPik + ei(jk), where Yijk = fawn:doe ratio for the ith deer group in treatment combination}k; i = 1,2, ... ,njk(deer groups);} = 1, 2, 3, 4 experimental units (control, supplemental feed, habitat manipulation); k= 1,2,3,4 (6) years; aPik = interactions among experimental units and years; and ei(jk) = random error associated with Yijk. A similar model will be used to analyze overwinter fawn survival, but a logit-link function will be used in place of the identity link function in the above general linear model. A similar model will also be used to test for differences in fawn weights, except the response variable will be fawn mass, and sex and fate (i.e. lived or died) will be included in the model as independent variables. For this progress report, a preliminary fawn:doe ratio analysis was completed using PROC MIXED in SAS (SAS Institute 1997). We used a reduced model with experimental unit as the lone independent variable, and considered experimental unit as a fixed effect and radio-collared does within an experimental unit as random effects. Survival rates were calculated using a Kaplan-Meier survival analysis (Kaplan and Meier 1958, Pollock et al. 1989), and contrasted among experimental units and sexes using a chi-square analysis. We modeled winter fawn survival with a product multinomial model (Grizzle et al. 1969) using PROC CATMOD in SAS (SAS Institute 1989a). Survival was modeled as a function of experimental unit, sex, and capture mass. We used a general linear model in PROC GLM in SAS (SAS Institute 1989b) to test for differences in fawn mass between experimental units, sexes, and fates (i.e. lived or died). Other results in this report are presented as data summaries incorporating means and standard errors, or in some cases, raw data values. These results are incomplete and preliminary in nature, and should be treated as such. RESULTS AND DISCUSSION Deer Capture During November-December 2000, we captured and radio-collared 73 adult female mule deer: 37 in the treatment unit and 36 in the control unit. Due to budgeting constraints, we were unable to capture and radio-collar fawns. During November-December 2001, we captured and radio-collared an additional 32 adult females to replace mortalities from the previous year and to buffer our sample size, resulting in a total of 45 radio-collared does in each experimental unit. We also captured and radio-collared 80 fawns: 40 in each experimental unit. During February 28 - March 1,2002, we captured an additional 36 does (18 in each experimental unit) as part of a related research project (Bishop et al. 2002). In total, we radiomonitored 221 mule deer (141 adult does and 80 fawns) during November 2000-June 2002. �74 Treatment Delivery 2000-01 From December 15,2000, through April 19, 2001, we distributed 88 tons of the pelleted ration. For most of the winter and spring, on average, we distributed 0.85 tons of feed each day throughout 22 feeding sites across the 2.3 mi' treatment unit. Deer were fed ad libitum because there was always residual feed remaining the next day during the feeding routine. Each sack was distributed in approximately 20-30 distinct, small piles, resulting in >1000 small piles of feed throughout the treatment unit. This effort allowed deer to effectively access the feed in small groups, and no aggression was ever observed among deer seeking access to the feed. By distributing the feed in this manner, we were able to avoid the negative aspects associated with large-scale feeding operations. Deer adapted to the pelleted supplement right away and utilized it extensively throughout the winter. We continually monitored deer use of the feed from ground observation points, where we obtained 440 visual observations of radio-collared does consuming the feed. These observations, coupled with daily radio-monitoring and periodic aerial relocations, indicate 32 of the 37 radio-collared treatment does spent the entire winter and spring within the boundaries of the treatment unit and received the supplement on a daily basis. Mark-resight population estimates from March helicopter (489 deer, SE = 62) and ground (494 deer, SE = 81) surveys, coupled with feed consumption, indicate we fed roughly 450 to 500 deer during most of the winter and spring. Feed consumption declined coincident with spring green-up, although deer continued to use the feed through mid-late April, at which point they began migrating to summer range. We also fed approximately 25 to 30 elk, but the elk did not affect deer access to the feed. Deer in the control experimental unit did not receive feed or any other treatment. Based on helicopter mark-resight surveys, the deer density in the treatment unit in December was 120 deer/mi' (SE = 9), but increased shortly after and was 213 deer/mi' (SE = 27) in March. Deer densities in the control unit changed little from 83 deer/mi' (SE = 12) in December to 101 deer/mi2 (SE = 14) in March. 2001-02 From December 15, 2001, through April 25, 2002, we distributed 194 tons of the supplement throughout the treatment unit. For most of the winter and spring, we distributed 2.0-2.1 tons of feed each day. The dramatic increase in supplement distribution from the previous year occurred because a large number of elk descended into the Uncompahgre Valley during mid-late fall/early winter. Elk arrived in unusually large numbers throughout much of the valley prior to the onset of treatment delivery. Once feeding was initiated, approximately 300-500 elk adapted to the feed and remained in or around the 2.3 mr' treatment unit throughout most of the winter. Given myriad logistical and budgetary constraints, 2.1 tons was the maximum amount of feed we could routinely deliver on a daily basis. Feed was not delivered ad libitum to all deer and elk in the treatment unit throughout the winter because residual feed was rarely observed during the next day's distribution. However, daily field observations indicate most deer approached ad libitum consumption of the supplement. In contrast to the previous winter, deer were waiting for the daily supplement to arrive each morning. Deer then consumed the supplement immediately after it was distributed. Elk were rarely observed utilizing the feed until late morning or afternoon, and elk continued to forage in fields below the treatment unit, whereas deer did not. We observed numerous radio-collared deer consuming the pelleted supplement each day; not all of these observations were recorded because of time constraints with distributing the feed. Given this time limitation, we still recorded 818 observations of radio-collared deer consuming the supplemental feed (497 collared doe observations and 321 collared fawn observations). Most days, > I 00 and sometimes 200-300 deer were observed utilizing the pellets during the course of distributing the supplement. These observations rarely included elk; thus, deer-elk competition was minimized because of temporal differences in feeding, and deer clearly had first access to the feed. �75 Fawn:Doe Ratios In December 2000, at the beginning of the study and prior to the first year's treatment delivery, fawn:doe ratios were similar in the 2 experimental units. Pre-treatment fawn:doe ratios were 52.6 fawns: 100 does (SE = 5.3) in the treatment unit, and 51.6 fawns: 100 does (SE = 5.0) in the control unit. In late December 2001 and early January 2002, following the first year's treatment, we conducted 2 age classification helicopter surveys in the treatment and control units. On 12/23/01, we observed 52.8 fawns: 100 does (SE = 6.7) in the treatment unit, and 36.7 fawns: 100 does (SE = 3.8) in the control unit. On 1/8/02, we observed 54.7 fawns: 100 does (SE = 6.6) in the treatment unit, and 50.5 fawns: 100 does (SE = 6.0) in the control unit. During December 2001 - February 2002, we obtained fawn:doe ratio estimates from ground observations of radio-collared deer groups for both treatment and control deer. This survey resulted in 61.2 fawns:l00 does (SE = 7.8) in the treatment unit, and 74.5 fawns: 100 does (SE = 8.5) in the control unit, although the result was not statistically significant (t74 = 1.16, P = 0.249). The fawn:doe ratio results are conflicting, and clearly do not provide evidence that there was any treatment effect. In short, we conclude that the nutrition enhancement treatment did not cause an increase in neonatal production and survival during 200l. However, our results, in conjunction with a December estimate of 64 fawns: 100 does for the entire Uncompahgre deer population (B.E. Watkins, unpublished), indicate fawn production and survival was good during 2001. The observed fawn:doe ratios coupled with overwinter fawn survival and annual adult survival rates indicate the deer population is growing. Considering the past 1-2 decades, this was an atypically good year for the Uncompahgre deer population. It would appear that whatever set of environmental conditions have led to a declining deer population were not present during 2001 in the same manner as in the past. Our main interest lies in observing the effect of the treatment on the deer population in a year where fawn:doe ratios are lower for the population as a whole, similar to what they have been much of the past 15 years. Our results point out the inherent difficulties and biases associated with precisely measuring fawn:doe ratios, particularly in this research study. Ratios obtained from helicopter surveys were based on 2 shortduration flights over small spatial units. Helicopter surveys were complicated by high deer densities in heavy cover, making both deer detection and fawn:doe classifications a considerable challenge. There is a variety of potential biases that may have affected the helicopter surveys, including differential sightability of does and fawns, and incorrectly classifying yearling bucks as adult does. These biases are likely real considering the higher ratios measured during the ground classifications based on the radiocollared does. Ground fawn:doe ratio observations of radio-collared doe groups were made using spotting scopes and field glasses, where we commonly studied the deer for some time. Incorrect classifications during these surveys were likely minimal. For example, small-antlered yearling bucks (e.g. 3 - 6" spikes) were detected from the ground, whereas they were clearly missed on occasion during helicopter surveys. The ground classifications were also preferable to the helicopter surveys in that we obtained repeated observations. We recorded as many as 5 separate ratio observations per radio-collared doe. Overall, we believe the ground fawn:doe ratio estimates, based on individual radio-collared does, provided less biased measurements. Given the inherent difficulties of measuring fawn:doe ratios, and the lack of a clear indication as to the effectiveness of the treatment, we initiated a second study using vaginal implant transmitters in order to capture and radio collar newborn fawns from the radio-collared treatment and control does (Bishop et al. 2002). This new aspect of the research will allow us to gain better estimates of the treatment effect on subsequent fawn production and survival, evaluate cause-specific mortality oftreatmentlcontrol neonates, and simultaneously provide a greater understanding as to the mechanisms affecting the deer population. Survival Adult Females During winter 2000-01 (Dec 1, 2000 - May 3 1, 2001), the adult doe survival rate of deer in the treatment unit (0.968, SE = 0.032) was greater (X2) = 2.649, P = 0.104) than the survival rate of deer in the control �76 unit (0.861, SE = 0.058). However, annual adult doe survival rates (Dec 1, 2000 - Nov 30, 2001) were similar among the treatment and control deer (Trt: Set) = 0.839, SE = 0.066; Control: Set) = 0.833, SE = 0.062; X21 = 0.004, P = 0.947). Thus, mortalities of control deer occurred primarily during the winter months, while treatment does died primarily during the summer and fall months. During winter 2001-02 (Dec 1, 2001 - May 31, 2002), the adult doe survival rate of deer in the treatment unit (0.942, SE = 0.030) was once again greater (X21 = 3.116, P = 0.078) than the survival rate of deer in the control unit (0.848, SE = 0.044). At this preliminary stage in the research, the nutrition enhancement treatment has apparently increased survival of adult females during the winter, but the overall annual survival among treatment and control does has not varied. The annual survival rate of does measured thus far aligns with expected survival based on other studies (Unsworth et al. 1999, B.E. Watkins, unpublished). Fawns During winter 2001-02 (Dec 1,2001 - May 31,2002), the survival rate of fawns was significantly greater 2 (X 1 = 13.216, P < 0.001) in the treatment unit (0.865, SE = 0.056) than in the control unit (0.510, SE = 0.080) (Fig. 4). The simplest model which effectively explained survival (X2S1 = 51.87, P = 0.440) included treatment (X21 = 9.95, P = 0.002) and early winter mass (X21 = 8.33, P = 0.004). Fawns receiving the nutrition enhancement treatment, and heavier fawns, had higher survival probabilities. During winter 2001-02, which was a mild to average winter, the nutrition enhancement treatment clearly improved overwinter fawn survival, and thus yearling recruitment. 1 -n--~---~-·· - -. -- .- - - I I • - -. -1 L 0.9 0.8 - . - - . - - - - - - - - - - - - - -- -- . ~ 1 I L..., 0~7 J, I- I I .1 ;1 .i 0.9 .. I "L - - - Colona (Treatment) 0~5 --Shavano (C on t ro l) 004 , 12/1 12./16 12!.H 1115 .1130 .2/14 311 , 3/16 3/31. '. 4J15 4/30 .r 5.115. 5130 Figure 4. Overwinter fawn survival (Dec 1, 2001 - May 31, 2002) in a nutrition enhancement treatment unit (S(t) = 0.865, SE = 0.056) and a control unit (S(t) = 0.510, SE = 0.080), Uncompahgre Plateau, southwest Colorado. Causes of Mortality Adult Females During winter 2000-01, only one adult doe from the treatment unit died, which was road-killed in early May. During June - August, 2001, an additional 4 treatment deer died: 2 from unknown causes that were �77 not predator-related, 1 from a prolapsed uterus, and 1 unknown. In contrast, 5 adult does from the control area died during winter 2000-01: 3 from malnutrition, 1 from mountain lion predation, and 1 was roadkilled. One additional deer from the control area died during August 2001 from an unknown cause that was not predator-related. During winter 2001-02, 3 adult does from the treatment unit died: 1 from secondary causes related to chronic arthritis, 1 from predation, and 1 road-killed. The predation and road kill mortalities occurred in mid-late May after deer had left the treatment unit. In June, 2 more treatment adult does died during the fawning period. One doe died while giving birth, and the second doe died from an unknown cause seemingly related to birthing. This second doe, based on a field necropsy, had considerable fat and seemed otherwise healthy. On March 1, 2002, we measured 2 fetuses in utero (Bishop et al. 2002), yet the doe had only 1 fetus in utero when she died. Given her good condition, it is unlikely the second fetus was reabsorbed, which indicates she had already passed the first fetus and died prior to giving birth to the second. During winter 2001-02, 7 adult does from the control unit died: 4 died from mountain lion predation, 1 from entanglement in a fence, 1 from an unknown, non-predator mortality, and 1 unknown. No additional control does died during the month of June. Fawns Five fawns in the treatment unit died during winter 2001-02: 2 from malnutrition/sickness and 3 from disease. Of the 2 fawn mortalities caused by malnutrition/sickness, 1 was a result of basic malnutrition and occurred on December 31, 2001. The other fawn had a combination of heavy parasite loads, scours, and general poor condition. Each of the 3 fawns that died from disease had adequate fat stores. At least one of these fawns died as a result of pneumonia. In the control unit, 19 fawns died during the winter: 5 from malnutrition, 6 from mountain lionlbobcat predation, 4 from coyote/canine predation, 3 unknown predation mortalities, and 1 unknown. A majority of the fawns killed by predators had virtually no femur marrow fat remaining, indicating the predation was likely compensatory in nature. Fawn Mass During winter 2001-02, the early winter mass of radio-collared fawns varied significantly between sexes (FI = 15.32, P < 0.001) and fates (FI = 6.11, P = 0.016). Males averaged 3.6 kg heavier than females, and fawns that survived the winter averaged 2.9 kg heavier than fawns that died. Early winter mass was not different among experimental units (FJ = 0.36, P = 0.550), thus the effect of the treatment was not confounded with fawn mass. The interaction of experimental unit x sex x fate was also significant (FJ = 5.80, P = 0.019), while all other 2-way interactions were not significant. The 3-way interaction occurred because in the control experimental unit, female fawns that survived were not heavier than female fawns that died (Survived: x = 31.0 kg, SE = 1.77; Died: x = 31.5 kg, SE = 1.03); whereas male fawns that survived were considerably heavier than male fawns that died (Survived: x = 38.0 kg, SE = 0.83; Died: x = 32.7 kg, SE = 1.35). In contrast, in the treatment experimental unit, weight differences were more pronounced between surviving and non-surviving females (Survived: x = 33.1 kg, SE = 1.00; Died: x = 28.2 kg, SE = 2.75) than between surviving and non-surviving males (Survived: x = 35.0 kg, SE = 0.87; Died: x = 34.5 kg, SE = 1.21). The importance of early winter fawn mass as a predictor of overwinter survival has been documented previously (White et al. 1987, Bishop 1998, White and Bartmann 1998, Unsworth et al. 1999). �78 LITERATURE CITED Baker, D. L., and N. T. Hobbs. 1985. Emergency feeding of mule deer during winter: tests ofa supplemental ration. Journal of Wildlife Management 49:934-942. Baker, D. L., D. E. Johnson, L. H. Carpenter, 0. C. Wallmo, and R. B. Gill. 1979. Energy requirements of mule deer fawns in winter. Journal of Wildlife Management 43:162-169. Baker, D. L., G. W. Stout, and M. W. Miller. 1998. A diet supplement for captive wild ruminants. Journal of Zoo and Wildlife Medicine 29: 150-156. Ballard, W. B, D. Lutz, T. W. Keegan, L. H. Carpenter, and J. C. deVos, Jr. 2001. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin 29:99-115. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bishop, C. J. 1998. Mule deer fawn mortality and habitat use, and the nutritional quality of bitter brush and cheatgrass in southwest Idaho. Thesis, University ofIdaho, Moscow, Idaho, USA. Bishop, C. J., D. J. Freddy, and G. C. White. 2002. Effects of enhanced nutrition of adult female mule deer on fetal and neonatal survival rates. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R, Progress Report. Fort Collins, CO USA. Bishop, C. J., and G. C. White. 2000. Effects of habitat enrichment on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R-13, Progress Report. Fort Collins, CO, USA. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in 0. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, Nebraska, USA. Gill, R. B., T. D. I. Beck, C. J. Bishop, D. J. Freddy, N. T. Hobbs, R. H. Kahn, M. W. Miller, T. M. Pojar, and G. C. White. 1999. Declining mule deer populations in Colorado: reasons and responses. A report to the Colorado Legislature. Colorado Division of Wildlife, Denver, Colorado, USA. Grizzle, J. E., C. F. Starmer, and G. G. Koch. 1969. Analysis of categorical data by linear models. Biometrics 25:489-504. Holter, J. B., H. H. Hayes, and S. H. Smith. 1979. Protein requirement of yearling white-tailed deer. Journal of Wildlife Management 43:872-879. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 53:457-481. Pojar, T. M. 2000. Investigating factors contributing to declining mule deer numbers. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R-13, Progress Report. Fort Collins, CO, USA. Pollock, K. H., S. R. Winterstein, C ..M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. SAS Institute. 1989a. SAS/STAT® user's guide, version 6, fourth edition. Volume 1. SAS Institute, Cary, North Carolina, USA. SAS Institute. 1989b. SAS/STAT® user's guide, version 6, fourth edition. Volume 2. SAS Institute, Cary, North Carolina, USA. SAS Institute. 1997. SAS/STAT® Software: Changes and Enhancements through Release 6.12. SAS Institute, Cary, North Carolina, USA. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep- trapping techniques. Wildlife Society Bulletin 6: 159-163. Smith, S. H., J. B. Holter, H. H. Hayes, and H. Silver. 1975. Protein requirement of white-tailed deer fawns. Journal of Wildlife Management 39:582-589. Thompson, C. B., J. B. Holter, H. H. Hayes, H. Silver, and W. E. Urban, Jr. 1973. Nutrition of whitetailed deer. I. Energy requirements offawns. Journal of Wildlife Management 37:301-311. �79 Ullrey, D. E., W. G. Youatt, H. E. Johnson, L. D. Fay, and B. L. Bradley. 1967. Protein requirement of white-tailed deer fawns. Journal of Wildlife Management 31 :679-685. Unsworth, J. W., D. F. Pac, G. Co White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63 :315-326. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. Verme, L. 1., and D. E. Ullrey. 1972. Feeding and nutrition of deer. Pages 275-291 in D. C. Church, editor. Digestive physiology and nutrition of ruminants. Volume 3 - Practical Nutrition. D. C. Church, Corvallis, Oregon, USA. White, G. C., and R. M. Bartmann. 1998. Effect of density reduction on overwinter survival of freeranging mule deer fawns. Journal of Wildlife Management {52:214-225. White, G. C., R. A. Garrott, R. M. Bartmann, L. H. Carpenter, and A. W. Alldredge. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Management 51:852-859. ��81 I ,--L i Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 FINAL REPORT State of .....:::::C""o~lo~r_=ad~o"'__ _ Work Package No ..__ -==3""'O""-'o..t_I Division of Wildlife - Mammals Research _ Deer Conservation '~!' Task No. 4.:..._ _ Pilot Study - Use of Ultrasound and Vaginal Implants ( I I.. Federal Aid Project_---'W'-'--'-1""'8""'5_,-R""-- _ Research and Development i \ I I. Period Covered: Authors: Personnel: I t.• July 1,2.0.01 - June 30,2002 C. J. Bishop, D. J. Freddy, and G. C. White, Ph.D. D. L. Baker, T. Baker, R. Bavin, T. D. I. Beck, S. K. Carroll, D. Coven, K. Crane, M. Del Tonto, L. Gepfert, J. Grigg, M. McLain, G. C. Miller, M. W. Miller, J. Olterman, J. A. Padia, T. M. Pojar, J. Risher, C. M. Solohub, M. Thonhoff, B. E. Watkins, L. Wolfe, CDOW; T. R. Stephenson, California Dept. ofFish and Game; R. C. Cook, National Council for Air and Stream Improvement. ABSTRACT " Field research of mule deer could be greatly enhanced if newborn fawns could be captured from specific adult females from which data has already been collected. We evaluated the logistical feasibility and effectiveness of using vaginal implant transmitters (VITs) to determine the location and timing of birth of specific, radio-collared adult female mule deer. The VITs were manufactured by Advanced Telemetry Systems, Inc. (Isanti, MN). We placed VITs in 36 adult female deer on February 28 and March 1,2.0.02. At this time, we recorded data such as fetal rate, body condition, body mass, and serology from a blood sample. In June 2002, we intensively radio-monitored the VITs to determine when they were expelled from the deer. When a VIT was shed, we immediately located it to determine whether a birth site was present and to locate/capture neonates. The proportion ofVITs that were expelled at or near the birth site with the transmitter functioning correctly was .0.33 (SD = 0.083). Of36 VIT trials, 3 were censored, 7 were shed prematurely, 15 had battery failures, and 11 were successful (9 of which led to birth sites and subsequent fawn captures). In spite of the high VIT failure rate, we captured and radio-collared a total of 54 fawns from 38 adult does during June 11 - July 1,2.002. Twenty-six fawns were captured from 17 of the 36 VIT does and 28 fawns were captured from 21 radio-collared does that did not have VITs. Contrary to our own expectations, we successfully captured fawns from radio-collared does by relocating the does on a routine basis. However, this technique was inefficient and required a total capture effort of 1700 man-hours (212 man-days) during a 22-day period, or roughly 4 man-days/fawn. The VIT battery failures were clearly the main problem we experienced, which can be corrected. The amount of time and effort saved by the 11 successful VITs justifies their use, particularly with continued refinement of the VIT design. ��8-3 EFFECTS OF ENHANCED WINTER NUTRITION OF ADULT FEMALE FETAL AND NEONATAL SURVIVAL RATES: A PILOT STUDY TO ADDRESS FEASIBILITY MULE DEER ON C. J. Bishop, D. J. Freddy, and G. C. White PROJECT OBJECTIVE 1_ To evaluate the feasibility of utilizing ultrasound techniques and vaginal implant transmitters in adult female mule deer to measure stillborn fetus mortality and to locate and capture specific neonate fawns. SEGMENT OBJECTIVES 1. Prepare a 'Program Narrative for a l-year pilot study. 2. Conduct the l-year pilot study to evaluate logistical feasibility offield techniques, collect data necessary for subsequent sample size calculations, and to obtain preliminary biological data. 3. Prepare a Job Final Report for the I-year pilot study. INTRODUCTION· Background The Colorado Division of Wildlife initiated 2 studies on the Uncompahgre Plateau in response to chronically low December fawn:doe ratios throughout the 1990's and an overall decline in total deer numbers. In 1997, an ongoing survival study was initiated to quantify overwinter fawn survival and annual adult survival rates, and to identify mortality agents (B.B. Watkins, Colorado Division ofWildlife, unpublished data). In 1999, another study began to quantify pregnancy/fetal rates and to measure survival rates and cause-specific mortality of neon.ate fawns (Pojar and Andelt 1999, Pojar 2000). These studies have provided several significant fmdings to date. First, overwinter survival rates of fawns, and annual survival rates of does and bucks, are above average when compared to measurements obtained elsewhere (Unsworth et al. 1999). Second, adult doe pregnancy rates (93%) and fetal rates (1.7 fawns/doe) in February are normal (Pojar and Andelt 1999). Third, summer fawn survival has been relatively low overall, with malnutrition/sickness and predation being the primary causes of mortality (Pojar 2000). Based on these findings, in utero fetus survival/summer fawn survival is clearly the limiting factor to population growth on the Plateau. Summer fawn survival has been measured directly, while the extent of in utero fetus mortality from February to birth has been back-calculated utilizing expected versus observed December fawn:doe ratios based on the observed summer fawn survival. Although this fetus mortality has not been measured directly, there is considerable evidence that some portion of viable fetuses in February are not surviving to birth. Given the magnitude of malnutrition/sickness observed in newborn fawns, the question of prepartum adult doe nutrition is paramount. Summer range habitat quality on the Uncompahgre Plateau is seemingly good, and arguably better than many other deer summer ranges throughout the intermountain West. However, lower transitional and winter range habitat quality appears to be limited in terms of forage diversity and quality. We understand the inherent limits in nutritional quality of winter range forage, but hypothesize that winter range habitat quality on the Plateau may not be meeting the minimum nutritional requirements of pregnant adult does. �84 In 2000, we initiated a research study on the Uncompahgre Plateau to evaluate the effects of enhanced nutrition of mule deer during winter on fawn production and survival (Bishop and White 2000, Bishop and White 2002). The objectives of this research are twofold: 1) to determine experimentally whether enhancing the nutrition of deer during winter and early spring by supplemental feeding increases overwinter fawn survival and/or December fawn:doe ratios the following December; and 2) to determine experimentally to what extent habitat treatments replicate the effect of enhanced nutrition from supplemental feeding. We are addressing these objectives by radio-collaring adult does and 6-month old fawns in a treatment experimental unit and a control experimental unit. The current phase of the experiment uses supplemental feed as a nutrition enhancement treatment, while the second phase will use habitat manipulations (e.g. prescribed fire, mechanical) as the treatment. The main focus of this research is to determine whether a decline in winter range habitat quality has been a causative factor of poor December fawn recruitment on the Uncompahgre Plateau during the past decade. More specifically, we are determining whether nutrition enhancements and/or habitat treatments on winter range cause an increase in fawn:doe ratios the following December. Our primary response variable is December fawn:doe ratios measured from radio-collared does in the treatment and control units. December fawn:doe ratios represent a combined approximation of fawn production (# fetuses produced and successfully brought to term) and survival (% of newborn fawns surviving from birth to December). Fawn:doe ratios are influenced by the number of yearling females in the population, the proportion of small yearling bucks that may be misidentified as does, doe harvests etc. Irrespective of these inherent biases, low December fawn:doe ratios typically indicate either poor fawn production, low summer fawn survival, or a combination of both. To improve our current study design evaluating the importance of habitat/nutrition, we initiated a l-year pilot study in an attempt to obtain separate, direct measurements of in utero fetus survival and summer fawn survival for treatment and control does. These direct measurements, if obtainable, would be preferable to December fawn:doe ratios, and would provide a better understanding of the effect, if any, of the nutrition enhancement treatment on the deer population. The purpose of the pilot study was to evaluate the logistical feasibility of field techniques necessary to accomplish the research, and to collect data for subsequent sample size calculations assuming the research progressed into a full-scale study. In order to directly measure in utero fetus survival and summer fawn survival of radio-collared does from the treatment and control areas, we needed to record winter fetal rates of the collared does, and then locate and capture the collared does' fawns the following June. Winter fetal rates can be measured using established ultrasound techniques. However, there are no established techniques for locating and capturing a large sample of newborn fawns from specific, individual does. Previous attempts to capture neonates from radio-collared does in forest-shrub habitats have been largely unsuccessful (M. A. Hurley, Idaho Dept. ofFish and Game, pers. comm.; T. M. Pojar, Colorado Division of Wildlife, pers. comm.). There are 2 major problems: 1) there is no effective way to determine when any given doe will give birth to her fawn(s); and 2) it is often very difficult to find a fawn simply based on locating the doe, because the fawns are often bedded in heavy cover some distance from the doe (e.g. 50-100 yards). To overcome these problems, we conducted a I-year research study to evaluate the use of vaginal implant transmitters in adult does as a technique to determine both the timing and location of birthing. Vaginal Implant Transmitters For some time, radio-transmitter implants in the vaginas of deer have been considered as a technique for. locating and capturing newborn fawns from radio-collared does immediately following parturition. Early attempts to employ this technique were largely unsuccessful in terms of both effectiveness and animal �85 welfare concerns (Garrott and Bartmann 1984, Giessman and Dalton 1984, Nelson 1984). This early technique used sutures to partially close the vulva in order to retain the transmitter in the vagina. More recently, Bowman and Jacobsen (1998) developed and employed a modified vaginal implant transmitter (VIT) for white-tailed deer, which met better success. This transmitter had plastic wings to retain the transmitter in the vagina until parturition; thus, no sutures were used. They found no indications that animals were negatively impacted by the newly designed VIT; however, retention rate of implants to parturition was only 75%, and sample sizes were small. Within the last 2 years, several studies have been initiated using (modified) VITs to study white-tailed deer (M. Carstenson and G. D. Delguidice, University of Minnesota, pers. comm.), black-tailed deer (N. Pamplin and D. Jackson, Oregon State University and Oregon Dept. ofFish and Wildlife, pers. comm.), and elk (J. Noyes and B. Johnson, Oregon Dept. ofFish and Wildlife, pers. comm.; J. Vore, Montana Fish, Wildlife, and Parks, pers. comm.) These ongoing studies have found greater success with VITs in terms of retention to parturition, and have not documented any detrimental effects to the animals. Given the success at finding birth sites and fawns, these studies do not indicate that vaginal implants cause major problems with in utero fetus survival or birthing. MATERIALS AND METHODS Experimental Design and Study Area This research was conducted in conjunction with our ongoing research study evaluating the effects of enhanced winter nutrition on overwinter mule deer fawn survival and early winter fawn:doe ratios. The research is being conducted in 2 experimental units on winter range on the Uncompahgre Plateau. The 2 units are receiving a nutrition enhancement treatment in a cross-over experimental design. Unit A served as the treatment unit, and Unit B served as the control, for the first 2 years of research (2000 - 2002). Beginning November 2002, Unit B will receive the treatment while Unit A will serve as the control. Bishop and White (2002) provide a complete description of the experimental design and study area. The 2 experimental units (A and B) receiving the nutrition enhancement treatment are (Fig. 1): (1) The Colona Tract of the Billy Creek State Wildlife Area (2) Bureau of Land Management lands adjacent to Shavano Valley as defined by the following: Within Dry Creek Basin Quadrangle (USGS 7.5 Minute), includes Sections 6 and 7 in T. 48 N.-R. 10 W. and Sections 1,2, 10, 11, 12, 13, 14, 15 in T. 48 N.-R. 11 W. This area roughly includes 38°25'00"38°27'30" Latitude and 108°00'00" - 108°04'30" Longitude. In late April and May, prior to fawning, deer from the winter range experimental units migrate to summer range. The summer range study area encompasses 800 me covering the southern portion of the Uncompahgre Plateau and adjacent San Juan Mountains to the south and east (Fig. 1). Winter range elevations range from 1830 m (6000 ft) in Shavano Valley to 2318 m (7600 ft) adjacent to the Dry Creek Rim above Shavano Valley. Winter range habitat is dominated by pinyon-juniper with interspersed sagebrush adjacent to agricultural fields in the Shavano and Uncompahgre Valleys. Summer range elevations occupied by deer range from 1891 m (6200 ft) in the Uncompahgre Valley to 3538 m (11,600 ft) in Imogene Basin southwest of Ouray, CO. Summer range habitats are dominated by sprucefir, aspen, ponderosa pine, Gambel oak, and to a lesser extent, sagebrush and pinyon-juniper at lower elevations. �86 Sample Size The main objective of the pilot study was to assess "success/failure" ofVITs from an equipment functionality and field logistics standpoint. Our first definition of success/failure was the proportion of vaginal implant transmitters that were expelled at the birth site with the heat sensor functioning correctly (transmitter success rate). We set our sample size based on an initial assumption that 0.90 of the transmitters would function correctly, which necessitated 36 radio-collared does to estimate the transmitter success rate with a 95% confidence interval of +/- 0.10. Our second definition of success/failure was the proportion of successful fawn captures that occurred from the sample of36 does (fawn capture success rate). We defined a successful fawn capture as locating and capturing at least 1 fawn from a doe equipped with a vaginal implant. Prior to the study, we assumed a 0.80 rate of finding at least 1 fawn/radio-collared doe. With 36 radio-collared does, this would allow us to measure a fawn capture success rate with a 95% confidence interval of +/- 0.13. This level of precision was sufficient for us to evaluate the overall success/failure of vaginal implant transmitters as a field technique for locating and capturing newborn fawns from specific radio-collared does. Capture and Handling Techniques On February 28 and March 1, 2002, we captured a total of 36 adult female deer utilizing helicopter net guns (Barrett et al. 1982, van Reenen 1982). Eighteen deer were captured in the nutrition enhancement treatment unit, and 18 in the control unit. Captured deer were ferried by the helicopter to a central processing location. Most deer captured in each experimental unit were chemically immobilized using a combination ofketamine and xylazine to facilitate the ultrasound and VIT insertion procedures. Ketamine and xylazine were mixed in a 5:1 ratio (200:40 mg/ml), and administered intravenously at a dosage rate of approximately 1.5-2.0 ml/45 kg animal body mass. Immediately prior to release, drug effects were (partially) reversed with an intravenous injection of yohimbine at a rate of -12 mg/45 kg animal body mass. Each deer was aged based on tooth replacement and wear, and only deer ~.5 years old were retained. For each captured deer, we used ultrasonography to measure pregnancy status, fetal rate, and body condition. If the doe was pregnant, she was theri radio-collared using a fixed length, permanent collar. Each radio collar had Ritchey® neck band material stitched to the left side with a unique identifier engraved on it for visual identification purposes. We then inserted the VIT and released the deer. We performed the ultrasound and VIT insertion procedures in a 10 x 12 ft wall frame tent located at the processing site to avoid problems associated with weather conditions and helicopter rotor wash. We also recorded the weight of each deer, recorded a body condition score, and collected a blood sample for serology tests. Ultrasonography We estimated body fat using an Aloka 210 (Aloka, Inc., Wallinford, Conn.) portable ultrasound unit with a 5 MHz linear transducer. Maximum subcutaneous fat thickness on the rump was measured immediately cranial to the cranial process of the tuber ischium. Proper orientation was assured by scanning along a line between the spine, at its closest point to the tuber coxae (hip bone), and the caudal process of the tuber ischium (pin bone). A small area of hair was shaved to ensure contact between the transducer and the skin. A conducting gel was applied to the shaved area and fat thickness was measured using electronic calipers. We quantified reproductive status using a 3 MHz linear transducer. To permit transabdominal scanning, a portion of the abdomen was shaved caudal to the last rib and Ieft of the midline, and gel was applied. Both uterine horns were systematically scanned to identify fetal numbers ranging from 0 to 3. Upon identification of a fetus, we measured, whenever possible, eye diameter, crown-rump length, biparietal �87 Figure 1. Map showing the locations of the Colona and Shavano experimental units (Units A and B) on winter range, and the location of deer summer range, on the Uncompahgre Plateau, southwest Colorado. The summer range study area was defined by the summer distribution of deer that were captured on the winter range experimental units. �88 distance, and skull length. In most cases, we only obtained an eye diameter measurement. measurements were collected to estimate fetal age and parturition date. Vaginal Implant Transmitters Morphometric (VITs) The VITs we used were manufactured by Advanced Telemetry Systems, Inc. (Isanti, MN). The VIT was 76 mm long, excluding antenna length, and had 2 plastic wings with a width of 57 mm when fully spread apart. The plastic wings were used to retain the transmitter in the vagina until parturition. The VIT weighed 15 grams and contained a 10-28 lithium battery. The diameter of the transmitter/battery was 14 mm, and was encased in an impermeable, water-proof, electrical resin. The transmitter contained an embedded heat-sensor which dictated the frequency pulse rate. When the heat sensor dropped below 86°F, synonymous with transmitter expulsion from the deer, the pulse rate changed from 40 PPM to 80 PPM. The VIT was inserted into deer using a vaginoscope (Jorgensen Laboratories, Inc., Loveland, CO) and alligator forceps. The vaginoscope was 6" long with a 5/8" internal diameter and had a machined end (smooth surface) to minimize trauma when inserted into the vagina. A discreet mark was placed on the applicator showing the appropriate distance it should be inserted into the deer. The length of a typical mule deer vaginal tract was obtained by taking measurements from road-killed deer and/or other fresh deer carcasses obtained in the study area. Prior to use in the field, VITs were sterilized using a Chlorhexidine solution, air-dried, and sealed in a 3" x 8" sterilization pouch. Sterilization containers with Chlorhexidine solution were used on site during capture to sterilize the vaginoscope and alligator forceps between each use. A new pair of nitrile surgical gloves was used to handle the vaginoscope and VIT for each deer. To insert a VIT, the plastic wings were folded together and placed into the end of the vaginoscope. We then liberally applied sterile KY Jelly to the scope and inserted it into the deer's vagina to the point where the mark on the applicator was reached. The alligator forceps, which extended through the vaginoscope to hold the VIT, was held firmly in place while the scope was pulled out from the vagina. This procedure pushed the VIT out of the scope into the vagina, and the plastic wings spread apart to hold the transmitter in place. The transmitter antenna was typically flush with the vulva, but on occasion extended up to 1 ern beyond the vulva. The tip of the antenna was encapsulated is a wax bead to protect the deer. Adult Doe Monitoring From March through May, we regularly monitored the radioed does as part of our current research experimental design, which included daily monitoring for live/death status (Bishop and White 2002). We also used aerial telemetry to relocate each of the does every couple of weeks during the remainder of the winter. Fetus Survival and Neonate Capture During June 10-30,2002, we relocated each of the radio-collared does having a VIT each morning using a fixed wing aircraft. Flights began at 6:00 AM and were usually completed by 10:00-11 :00 AM. The early flights were crucial for detecting fast signals because shed VITs were often warmer than 86 OFby mid-day, which caused them to switch back to a slow ("pre-birth") pulse. When a fast ("postpartum") pulse rate was detected, we located the VIT from the ground to determine whether it was shed at the birth site. If the transmitter was located at the birth site, we identified whether any fawn( s) were stillborn. If the fawn(s) were no longer present at the birth site, or could not be found in the vicinity of the birth site, we located the radio-collared doe and searched for fawns at her location. All personnel involved wore surgical gloves to help minimize human scent when handling fawns. For each doe, we attempted to document whether any fawns were stillborn, locate each of her fawns, radio-collar and weigh the fawns, record basic vegetation characteristics of the birth site, and promptly exit the site. We attempted to �89 account for each doe's fetuses in order to evaluate the efficacy of using this technique to quantify in utero fetal survival from February to birth. We then radio-monitored each of the radio-collared fawns on a daily basis to measure survival rates of treatment and control fawns and to assess cause-specific mortality. We also periodically located other radio-collared does that did not have VITs and attempted to capture their fawns to help achieve our targeted sample size. Each of these does were part of the nutrition enhancement research, and were present on either the treatment or control experimental unit during winter. RESULTS AND DISCUSSION VIT Effectiveness The proportion ofVITs that were expelled at or near the birth site with the transmitter functioning correctly was 0.33 (SD = 0.083). Of36 VIT trials, 3 were censored, 7 were shed prematurely, 15 had battery failures, and 11 were successful. Censors: Two adult does died in May well before fawning and were still carrying the VITs. One doe was never relocated after leaving winter range. These 3 deer were censored because there was no test of whether the VIT functioned correctly or not. Premature Sheds: Three VITs were shed in Mayor early June well before fawning (May 18, May 19, and June 6). The other 4 VITs were shed during the fawning period, but at least 1-2 days before the respective does gave birth. Battery Failures: With only 1 exception, all battery failures occurred just before or during the fawning period. This was the glaring problem with the VIT success rate. The battery we had hoped to use had a warranty life of 116 days and a capacity of232 days. Unfortunately, this battery was discontinued by Advanced Telemetry Systems (ATS) just before our research study began due to poor results. The battery we subsequently used in the VITs had a warranty life of only 94 days, and a capacity of 188 days. We needed our batteries to last 120 days for this research. ATS had found good results with this shorter life battery, and recommended its use because it typically lasted well beyond the warranty battery life. We knew this was a risk at the onset of the research, but had confidence the batteries would last the necessary 120 days based on ATS recommendations. Had the batteries not failed, we likely would have had a 60-70% success rate. Successes: We had 11 transmitters function correctly. One transmitter was still in the doe and functioning at the end of our capture period. Of the remaining 10 VITs, 9 allowed us to efficiently locate and capture fawns, typically at the birth site, and account for each of the given doe's fetuses measured in February/March. We located 14 fawns, one of which was a stillborn, from these 9 VITs. Our fawn capture success rate for the 33 available does was 0.61 (SD = 0.086), meaning we captured at least 1 fawn from 61 % of the VIT radio-collared does. In 3 instances, we opportunistically located a VIT with a failed battery by radio-tracking the doe and searching for her fawns. In total, we located 30 fawns from VIT does, 3 of which were stillborn, and 1 we weren't able to radio-collar. Fawn Capture We captured and radio-collared a total of 54 fawns from 38 adult does (1.42 fawns/doe) during June 11July 1,2002 (Fig. 2). We found 4 stillborns at birthsites, and 2 suspected stillborns at or near birthsites which could have been early neonate mortalities. We captured 30 fawns from treatment does and 24 from control does. Twenty-six fawns were captured from 17 of the VIT does (1.53 fawnsNIT doe) and 28 fawns were captured from 21 radio-collared does that did not have VITs (1.33 fawns/non- VIT doe). We documented a total of 62 live fawns from the 38 does (1.63 fawns/doe), although we only captured 54 fawns because 1 fawn from a set of twins escaped on multiple occasions. �90 Capture Effort The 15 VIT battery failures caused considerable problems during the fawn capture. As it turned out, VITs helped us capture only 13 fawns and locate 1 stillborn fawn. The other 41 fawns and 5 stillborns were captured/located by routinely radio-tracking collared does and searching for fawns at their locations. This required an intensive field effort. We worked approximately 1700 man-hours (212 man-days) during a 22-day period to capture the 54 fawns, or roughly 4 man-days/fawn. Our objective pre-fawning was to capture 55 fawns; thus, even with the VIT failures, we were able to capture the necessary fawns from radio-collared does. The field effort would have been considerably less had we not had the battery failures. 8 7 "C 6 ~ .;.... = .•... 5 .=Q.. o 4 "" :: ~. ~ 3 ~ :tI: i 1 0 6/10/02 I I 6/13102. II 6/16/0.2 6/19102 I 6/2210.2 6/25/02 I I 6/28/02. 7/1102 Figure 2. Number of newborn fawns captured by day during June l l-July 1,2002. All fawns were captured from radio-collared does throughout the southern portion of the Uncompahgre Plateau and adjacent San Juan Mountains in southwestern Colorado. Fetus Survival In February-March 2002, we measured an average of 1.80 fetuses/doe (SE = 0.14, n = 36), which included 1.77 fetuses/doe (SE = 0.14, n = 18) in the treatment unit and 1.83 fetuses/doe (SE = 0.15, n = 18) in the control unit. In June 2002, considering all does that we located any fawn from, whether live or stillborn, we observed 1.42 (SE = 0.11, n = 43) live fawns/doe postpartum. This rate includes the 6 stillborns, and should represent a conservative estimate of live fawns/doe postpartum because we inevitably failed to locate all live fawns from each doe. In other words, this estimate would treat any unaccounted fetuses (from the February measurement) as if they were stillborns. For does that did not have VITs, and thus we did not have a winter fetus rate measurement, singletons would infer that either the deer only had 1 fetus, or that the other fetus died. It is likely that many of these singletons had a twin that we did not locate. This equates to a conservative fetus survival rate estimate 0[0.79 (SE = 0.063). We accounted for all the fetuses of 14 VIT does in June 2002,8 of which were the direct result of the VIT �91 functioning correctly. Of these 14 does, the fetus survival rate was 0.86 (SD = .096). This data point lacks precision and may potentially be biased because we did not account for an adequate number of fetuses due to the VIT failures. Of 10 VITs that functioned correctly and were shed during fawning, we accounted for all recorded fetuses in 8 ofthe deer. One of the other 2 VITs that functioned correctly allowed us to account for 2 of 3 fetuses measured in February. Clearly, to gain a more reliable estimate of fetus survival, a high percentage of the VITs must function correctly so that more birth sites can be located, and more fetuses can be accounted for. Neonate Survival We accomplished our neonate capture objectives even with the VIT failures; it simply required a greater effort. If this technique were incorporated into the nutrition enhancement experiment at full scale, we would need to capture approximately 80 newborn fawns (40 each from treatment and control does). Assuming we can purchase implants with longer-lived batteries, we could feasibly capture 80 fawns by increasing our sample size ofVIT does. CONCLUSIONS The VITs were largely successful except for the 15 battery failures. The battery problem can easily be corrected by working with Advanced Telemetry Systems to locate and utilize a reliable battery with a longer life. Such batteries exist, and have been used routinely in small mammal and avian radio transmitters. The 7 premature sheds were expected to some extent, and not a major concern. The VITs that did not fail were highly useful for determining the location and timing of birth, which is of critical importance for capturing fawns from individual, radio-collared does. We found the use ofVITs to be a successful field technique given our objectives, assuming a reliable, longer-lived battery can be incorporated into the current design. Literature Cited Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bishop, C. J., and G. C. White. 2000. Effects of habitat enrichment on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R-13, Progress Report. Fort Collins, CO, USA. Bishop, C. J., and G. C ..White. 2002. Effects of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R, Progress Report. Fort Collins, CO, USA. Bowman, J. L., and H. A. Jacobson. 1998. An improved vaginal-implant transmitter for locating whitetailed deer birth sites and fawns. Wildlife Society Bulletin 26:295-298. Garrott, R. A, and R. M. Bartmann. 1984. Evaluation of vaginal implants for mule deer. Journal of Wildlife Management 48:646-648. . Giessman, N. F., and C. J. Dalton. 1984. White-tailed deer fawn mortality in the southeastern Missouri Ozarks. Missouri Department of Conservation, Jefferson City, Pittman-Robertson Project W -13R-35. �92 Nelson, T. A. 1984. Production and survival of white-tailed deer fawns on Crab Orchard National Wildlife Refuge. Thesis, Southern Illinois University, Carbondale, IL, USA. Pojar, T. M. 2000. Investigating factors contributing to declining mule deer numbers. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R-13, Progress Report. Fort Collins, CO, USA. Pojar, T. M., and W. F. Andelt. 1999. Investigating factors contributing to declining mule deer numbers. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R-12, Progress Report. Fort Collins, CO, USA. Unsworth, J. W., D. F. Pac, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. �93 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 PROGRESS REPORT State of --"'C""o"-'lo"-'-r_",a",_do"'---_ Work Package ~30~0~1~ Task No. ---=.5 Federal Aid Project No. W-185-R Research and Development and the following non-Federal Aid projects 0661 Grouse Conservation 0664 Prairie Dog Conservation 0670 Lynx Conservation 0850 Peregrine Falcon Recovery 3006 Other Small Game Conservation Work Package No. Work Package No. Work Package No. Work Package No. Work Package No. _ Division of Wildlife - Mammals Research _ Deer Conservation Improved Population Modeling DEAMAN System Administration Period Covered: July 1,2001 - June 30, 2002 Author: G. C. White Personnel: C. Bishop, G. Miller, T. E. Remington, D. J. Freddy, T. M. Shenk, L. Stevens, J. Craig, R. Kahn, D. C. Bowden, F. Pusateri, J. Dennis, M. M. Conner, D. Walsh, B. Lubow. ABSTRACT Progress towards the objectives of this job include: Consulting assistance to CDOW on harvest surveys, terrestrial inventory systems, and population modeling procedures was provided. Estimates of spring and fall turkey, spring snow goose, sharptailed and sage grouse, chukars, ptarmigan, Abert's squirrels, and general small game harvest were computed from survey data, and programs and harvest estimates provided to CDOW via email and CD ROM. Computer code written in SAS to compute these estimates and display results graphically was also provided. Computer code was also written in SAS to estimate the compliance rate of Colorado small game license holders with the Harvest Information Program. The DEAMAN software package for the storage, summary, and analysis of big game population and harvest data was revised further as a Windows 95/98INT/2000IMEIXP program. The capability to incorporate data on radio-collared animals to estimate survival with the Kaplan-Meier estimator and display movement data was added, and distributed to terrestrial biologist via the WWW at http://www.cnr.colostate.edu/~gwhite/deaman. A 3-day workshop was conducted with CDOW Terrestial Biologists in the use ofDEAMAN and population modeling procedures, mainly to instruct personnel on the use of spreadsheet models for ungulate population dynamics. In addition, numerous questions were answered via meetings with biologists, and via email. A paper, coauthored with Bruce Lubow, was published in the Journal of Wildlife Management on past efforts to develop a realistic mule deer population model based on data collected with current CDOW procedures. Data from the Piceance Basin were used to illustrate the modeling technique. The full �94 citation is: White, G. C., and B. Lubow. 2002. Fitting spreadsheet population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. A paper on use of population viability analyses applicable to animals monitored with mark-encounter data was published with T. M. Shenk and A. B. Franklin. The full citation is: White, G. C., A. B. Franklin, and T. M. Shenk. 2002. Estimating parameters ofPVA models from data on marked animals. Pages 169-190 in S. R. Beissinger and D. R. McCullough, editors. Population Viability Analysis. University of Chicago Press, Chicago, Illinois, USA. A paper on analysis of radio-tracking data for estimation of survival pertinent to monitoring the reintroduced lynx population in Colorado was published with T. M. Shenk: White, G. C., and T. M. Shenk. 2001. Population estimation with radio-marked animals. Pages 329-350 in J. J. Millspaugh and J. M. Marzluff, editors. Design and Analysis of Wildlife Radiotelemetry Studies. Academic Press, San Diego, California, USA A paper on the estimation of population size from correlated sampling unit estimates of the variable of interest was submitted to the Journal of Wildlife Management. The methodology developed in this paper is proposed for use in ajoint ColoradolUtah survey of the colony area of white-tailed and Gunnison prairie dogs in western Colorado and eastern Utah. The full citation is: Bowden, D. C., G. C. White, A. B. Franklin, and J. L. Ganey. 2003. Estimating population size with correlated sampling unit estimates. Journal of Wildlife Management 67: 1-1O. A paper on the estimation of survival of Greater Sage-grouse in North Park, Colorado, was submitted to the Journal of Wildlife Management: Zablan, M. A., C. E. Braun, and G. C. White. 2003. Estimation of northern sage-grouse survival in North Park, Colorado. Journal of Wildlife Management 67:144154. Assistance in the analysis of candidate systems to estimate deer abundance in GMU 10 was provided. A research study to examine the impact of nutrition on the decline of mule deer fecundity during the last 20 years was continued. I have provided input on estimation of the number of deer on the feed sites, and developed an estimator of fawn survival rates based on radio-collared does and fall and spring fawn:doe ratios. Data were collected and analyzed on spatial distribution, movement of radio-collared animals, and population sizes related to estimating the spread and impacts of chronic wasting disease in deer populations. A report summarizing these findings was provided to CDOW personnel involved with the study. A graduate research project by Dan Walsh to evaluate utility of lek counts of Greater Sage-grouse in Middle Park is ongoing. Mark-resight methods are being used to estimate lek attendance and population size. Preliminary results of this work were reported at the Sage-grouse Working Group Meeting on Population Analysis held June 24-25,2002, in Torrey, Utah. Computer programs to assist researchers with field data collection of feeding rates of tame Greater Sagegrouse were written for the HP Jornada Pocket Computer. In addition, a program for computing triangulation locationsof radioed animals was-written for the HP Jornada Pocket Computer for use in the field to evaluate -interactively and graphically the quality of triangulated locations. A model of the Colorado peregrine falcon population was constructed from estimates of surviyal and reproduction derived from banded birds (1973-2001) and monitored nests(1989-2001). Data were supplied by Jerry Craig. Survival estimates for 0-1, 1-2, and 2+ year old birds were 0.544, 0.670, and 0.800, respectively, with standard errors of 0.0765, 0.091, and 0.0544. Average young produced per pair was 1.660 (SE = 0.0443), but there was considerable variation across years (min = l.388, SE = 0.1548, in 1995; max = 2.122, SE = 0.1393, in 2000). Based on a population model constructed from these estimates, the annual rate of population increase was 1.028957 for females first reproducing at 3 years of age, and 1.080316 for females first reproducing at 2 years of age. Given these high rates of population increase, some take by falconers could be accommodated by the Colorado peregrine population. An analysis to estimate the effort required to estimate the percent of eastern Colorado inhabited by blacktailed prairie dogs was completed and results provided to CDOW personnel involved with the effort. For the first 5 strata surveyed, I have computed estimates of prairie dog co lony areas to assist the CDOW personnel conducting the survey. Results to date suggest the survey is working well. �95 CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSES G. C. White PROJECT OBJECTIVES Assess the status of Colorado peregrine falcon population based on parameters estimated from banded birds and monitored nests. SEGMENT OBJECTIVES 1. Develop a model of the Colorado peregrine falcon population based on survival and reproduction estimates derived from banded birds (1973-2001) and monitored nests (1989-2001). : 2. Using this model, determine the impact oflimited take by falconers on Colorado peregrine populations. RESULTS AND DISCUSSION Methods Survival Rate Estimation A total of938 peregrines were banded as nestlings during the interval 1974-2000. From these, 11 live resightings and 53 dead recoveries were obtained. Survival was estimated with Program MARK (White and Burnham 1999) using the joint live and dead recoveries model of Burnham (1993). Program MARK uses the Seber (1970) parameterization for dead recoveries in the Burnham model, so parameters for survival (S), probability that a band from a dead bird is recovered (r), and the probability of a live bird being resighted and the band read (p). The fidelity parameter (F) was fixed to 1 because of the sparseness of the data. Reproduction A total of 142 nesting sites were monitored for the number of young fledged starting in 1973 through 2001, although the number of sites increased with year as the breeding population increased in Colorado. Only data from 1989 through 2001 were used in the analysis presented here because I wanted at least 30 nests per year to estimate the effects modeled. Mean number of young fledged per site was estimated by year. Estimates of the variance components by site and year was estimated with PROC MIXED of SAS (Littell et al. 1996). Structures considered for the variance of the repeated observations within sites were first order autoregressive, first order heterogeneous autoregressive, compound symmetry, heterogeneous compound symmetry, exponential local effects, also known as dispersion effects, in a log-linear variance model, and a null structure with zero covariances and constant variances across years, also commonly known as the variance components structure (Littell et al. 1996). Random effects considered in the models were year and site effects. A fixed effect for even and odd years was also included in the models because there is a defined sequence of a year of high reproductive output, followed by a year of low reproductive output, followed by another year of high reproductive output, etc. The even/odd year fixed effect models this oscillating reproductive output. Selection among models for both survival and reproduction parameter estimation was performed with the AlCc criterion recommended by Burnham and Anderson (1998). �96 Population Model A model of the female segment of the Colorado peregrine population based on the estimates of survival and reproduction was constructed in an Excel spreadsheet, and also as a SAS program. The model included 4 age classes (No, NI, N2, and N3), even though the survival estimates used in the model had survival the same for all birds 3+ years old. The parameters in the deterministic model were number of fledglings per reproducing female (F), proportion of fledglings that are female (assumed to be SR = 0.5), survival for 4 age classes (So, SI, S2, and S3), and the proportion of females that breed on their second birthday (B2)' In addition, a parameter for the proportion of fledglings removed by falconers was included in the model to allow the estimation of the effects of human take (1). The difference equations for the transition from year t to year t+1 in model were: Nl.1+l=No, I So, A stochastic model was developed from the above deterministic model by replacing the mean fledglings per female with a value randomly drawn from the observed values for the years 1989 through 2001. The VLOOKUP function of Excel was used to randomly select one ofthe 13 observed values for each year in the model. That is, the fledgling rate was sampled with replacement from the observed values. This stochastic reproduction model was also extended to incorporate demographic stochasticity in the survival process. Instead of multiplying the population segment by a fixed survival rate to obtain the number of survivors, the process is treated as a binomial process, with the number of survivors drawn from a binomial distribution with the appropriate survival rate. However, given the size of the peregrine population in Colorado, demographic stochasticity had little or no effect on the model predictions. Results Survival Rate Estimation The encounters of.marked birds were sparse, and thus preclude complex models involving both time and age effects. The a priori list of models considered (Table 1) included models to evaluate age differences in survival for birds during their first 4 years of life, arid time-specific effects in survival, live resighting rate, and dead recovery rate. The minimum AlCc models all included time-specific variation in the band recovery rate, but did not suggest time-specific variation was required to model the live resighting rates. The minimum AICc model was {S(a2) p(.) r(t)} , with the second best model {S(a3) p(.) r(t)} only 0.388 units above the minimum. I chose to use estimates from the 3-age model because this model is more realistic biologically, and the small difference in AICc values does not suggest that the 2age class model is much better than the 3-age class model. Parameter estimates for the 3-age class model (Table 2) are reasonable in that survival increases with age, but all have large standard errors. Reproduction Estimation Average number of fledglings produced per nest during the interval 1989-2001 was 1.66059 with SE 0.044296 (Table 3). However, as shown in Table 3, there is considerable variation from year to year in the number of fledglings per breeding pair. �97 Model selection results (Table 4) for estimation of the variance components for site and year suggest that a first order autoregressive variance structure is required. Based on the minimum AICc model with the AR(l) variance structure, the estimate of the variance component for year was 0.01609, for site was 0.08438, with a residual variance component of 1.6069. The autocorrelation coefficient between consecutive years within a site as 0.1109. Thus, the variance components due to year and site were relatively minor compared to the residual variance in young fledged per breeding pair. The even/odd year effect was estimated as 0.2482 with a SE of 0.1 065 (P < 0.0403). Thus, the magnitude of the every-other-year oscillation is estimated to be 0.2482 young per nest. Population Model The deterministic population model provided an estimate of A = 1.028957 with T= 0 and F= 0 for the survival parameter values in Table 2 and fledglings per reproducing female of 1.66059, estimated as the mean fledgling rate for the 1989-2001 interval. Thus, the model predicts that the Colorado peregrine population is increasing 2.9% per year, even with no 2-year old birds reproducing. The effect of reproduction from 2-year birds is shown in Figure 1, and suggests that if all of the 2year old birds breed, A == 1.080316. Results from the model with stochastic reproduction provided estimates of A consistent with the deterministic model, e.g., for 10,000 simulations, A = 1.0290287 with SE = 0.000631839, giving a 95% confidence interval of 1.0277902 to 1.0302673 that encompasses the value estimated from the deterministic model. The large standard errors of the parameter estimates used to build the population model (Tables 2 and 3) suggest that the estimate of A obtained will also have a large standard error. I used Monte Carlo simulation techniques to draw values of each of the survival and reproduction parameters from a normal distribution with mean equal to the parameter estimate and standard deviation equal to the standard error of the parameter estimate. With a single set of parameters so obtained, 10,000 values of A were averaged to obtain a mean for that parameter set. This process was repeated for 1000 parameter sets to obtain a SD of A of 0.0612896. This value can be interpreted as a SE of the estimated A that accounts for the SE of the input parameters. Average standard errors from the 10,000 simulations for the 1000 parameter sets was 0.0015142, suggesting that the preceding SD is not affected by the small amount of variation associated with each of the 1000 estimates. Discussion The best AICc model for estimation of survival required 28 parameters to estimate time-specific band recovery rates, ret). A more parsimonious model would provide estimates of survival with better precision. One approach to obtaining a more parsimonious model would be to include a covariate that models the variation in ret). The estimated rate of increase from the population projection model is relatively high for a wildlife population. However, the number of nest sites monitored each year (Table 3) provides confirmation of the high estimates of A. An exponential model regression, 10g.,(No. Nest Monitored) /30 + /3] Year, was used to estimate the rate of increase of numbers of nest monitored. From this regression, PI = 0.07883 with SE = 0.00755 (P < 0.0001), giving an estimate of the annual rate of increase of the population (A) of exp(0.07883) = 1.082. This value exceeds the maximum value predicted from the population model even with 100% of the 2-year old birds breeding. Although the = �98 estimate obtained from the number of nests monitored suffers from confounding with monitoring effort and effort to find new nests, the results still suggest that the Colorado peregrine population has had a high annual rate of increase, and that the predictions from the population model described here are consistent with another estimate of A. The high annual rate of increase suggests that moderate take can be accommodated by the Colorado peregrine population without affecting the population growth rate. Based on the population model presented with no 2-year old birds breeding, A = 1 with 17.5% of the fledged young taken. With 50% of2-year old birds breeding, A = 1 with 26.7% of the fledged young taken, and with 100% of2year old birds breeding, A = 1 with 34.0% of the fledged young taken. Summary A model of the Colorado peregrine falcon population was constructed from estimates of survival and reproduction derived from banded birds (1973-2001) and monitored nests (1989-2001). Survival estimates for 0-1, 1-2, and 2+ year old birds were 0.544,0.670, and 0.800, respectively, with standard errors of 0.0765, 0.091, and 0.0544. Average young produced per pair was 1.660 (SE = 0.0443), but there was considerable variation across years (min = 1.388, SE = 0.1548, in 1995; max = 2.122, SE = 0.1393, in 2000). Based on a population model constructed from these estimates, the annual rate of population increase was 1.028957 for females first reproducing at 3 years of age, and 1.080316 for females first reproducing at 2 years of age. Given these high rates of population increase, some take could be accommodated by the Colorado peregrine population. Literature Cited Burnham, K. P. 1993. A theory for combined analysis of ring recovery and recapture data. Pages 199-213 in J.-D. Lebreton and P. M. North, editors. Marked individuals in the study of bird population. Birkhauser Verlag, Basel, Switzerland. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical information-theoretic approach. Springer-Verlag, New York, New York, USA. 353 pp. Littell, R. c., G. A. Milliken, W. W. Stroup, and R. D. Wolfinger. Models. SAS Institute Inc., Cary, NC, USA. 633pp. 1996. SAS® System for Mixed Seber, G. A. F. 1970. Estimating time-specific survival and reporting rates for adult birds from band returns. Biometrika 57:313-318. White, G. c., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. �99 Table 1. Set of a priori models considered in Program MARK (White and Burnham 1999) for estimation of survival of peregrines banded as nestlings with the joint live-dead model of Burnham (1993). Model names include survival (S), live resighting probability (P) and probability that the band from a dead bird is recovered (r). For survival, models with time-specific survival (t), constant survival (.), and 2 (a2), 3 (a3), and 4 (a4) age classes were considered. Constant and time-specific models for both p and r were also considered. The fidelity parameter (F) was fixed to 1 in all models. Model AICc Delta AICc AICc Weights Model Likelihood Num. Par Deviance 31 16l.38 {S(a2) p(.) r(t)} 710.841 0 0.46193 {S(a3)p(.) r(t)} 711.229 0.388 0.38047 0.8237 32 159.626 {S(a4) p(.) r(t)} 713.332 2.491 0.13294 0.2878 33 159.583 {S(.) p(.) r(t)} 716.701 5.86 0.02467 0.0534 30 169.377 {S(a3)p(.) r(.)} 742.565 3l.724 0 0 5 247.202 {S(a2) p(.) r(.)} 742.803 31.962 0 0 4 249.462 {S(t)p(.) r(.)} 744.811 33.97 0 0 30 197.487 {S(.) p(.) r(.)} 753.754 42.913 0 0 3 262.429 {S(a4)p(.) r(.)} 886.175 175.334 0 0 6 388.786 �100 Table 2. Parameter estimates from the 3-age class model {S(a3) p(.) rCt)} of peregrine falcons in Colorado, estimated from birds banded 1974-2000. Parameter Estimate SE F (fixed to 1) LCI UCI 0 Sage 0-1 0.543995 0.076538 0.394531 0.685934 Sage 1-2 0.669762 0.098121 0.459491 0.828723 Sage 2-3+ 0.800291 0.054382 0.672873 0.886454 P 0.005662 0.002265 0.002581 0.012374 r 1974 0 lE-07 -3E-07 3E-07 r 1975 0 5E-07 -l.lE-06 l.lE-06 r 1976 0 3E-07 -7E-07 7E-07 r 1977 0.42494 0.275041 0.07526 0.870289 r 1978 0.781612 0.215533 0.231516 0.977021 r 1979 0.20686 0.101744 0.071797 0.467918 r 1980 0.190922 0.093857 0.066924 0.437053 r 1981 0 0 -IE-07 lE-07 r 1982 0 0 0 0 r 1983 0.074126 0.052037 0.017792 0.261367 r 1984 0.035033 0.034906 0.004775 0.215516 r 1985 0 0 0 0 r 1986 0.042528 0.042355 0.00575 0.254375 r 1987 0 0 0 0 r 1988 0.042219 0.029772 0.010304 0.157271 r 1989 0.016702 0.016695 0.002311 0.11077 r 1990 0.019441 0.01942 0.002685 0.127406 r 1991 0.021935 0.021894 0.003025 0.142181 r 1992 0.142769 0.053181 0.066349 0.280741 r 1993 0.01603 0.01601 0.002223 0.106429 r 1994 0.055134 0.031693 0.017401 0.161262 r 1995 0.083715 0.041537 0.030642 0.208902 r 1996 0.034717 0.024458 0.008529 0.130709 r 1997 0.060956 0.034981 0.019218 0.176984 r 1998 0 0 0 0 r 1999 0.040953 0.041348 0.005395 0.251596 r2000 0.052539 0.053344 0.006742 0.311771 r2001 0.069547 0.07131 0.008547 0.39323 �101 Table 3. Summary of number of,young fledged Eer nest for Colorado Eeregrines, 1989-2001. Year Number of Nests Fledglings/Nest SD SE 1989 33 1.90909 1.35471 0.235825 1990 42 1.47619 l.15269 0.177864 1991 52 1.65385 1.16963 0.162198 1992 54 1.62963 1.29289 0.17594 1993 55 1.65455 1.36379 0.183893 1994 64 1.625 1.26617 0.158271 i995 67 1.38806 1.26677 0.154761 1996 83 1.71084 1.29285 0.141909 1997 71 1.42254 1.26109 0.149664 1998 81 1.95062 1.27379 0.141532 1999 88 1.59091 1.33594 0.142412 2000 98 2.12245 1.37927 0.139327 2001 90 1.35556 1.36003 0.14336 Mean 878 1.66059 1.31254 0.044296 Table 4. Model selection results for estimation of variance components of year and site with the MIXED procedure of SAS (Littell et al. 1996). Variance Structure Fixed Effects Random Effects AICc Delta AlCc AR(I) Even/Odd Years Year Site 2950.4 0 AR(l) Even/Odd Years 2951.8 1.4 AR(l) Year Site 2952.3 1.9 AR(l) Year 2953.7 3.3 Default Even/Odd Years Year Site 2954.6 4.2 CS Even/Odd Years Year Site 2954.6 4.2 Default Year Site 2956.5 6.1 CS Year 2956.5 6.1 CS Year Site 2958.5 8.1 AR(l) Site 2961.3 10.9 2962.8 12.4 AR(l) ARH(1) Even/Odd Years Year Site 2970.2 19.8 EXP(YEAR) Even/Odd Years Year Site 2973.6 23.2 �102 1.09 - 1.08 CIS "C .c ~ 1.07 Q) II) CIS 1.06 ... 1.05 Q) (,) -c: 0 1.04 Q) CIS ~ 1.03 1.02 0 0.2 0.4 0.6 0.8 1 1.2 Proportion of 2-year olds Breeding Figure 1. Predicted effect from the population model of the proportion of2-year old females breeding on the rate of increase in the population ( A ). �103 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 JOB PROGRESS REPORT State of Work Package Study No. Mammals Research ---'C""'o""'I""o"-'ra:o::d"_,,o"---_ ---=3::..,,0""'0'-'-1 ----"9 Deer Conservation _ _ Federal Aid Project No. W-153-R-13 Evaluation ofGnRH-PAP as a Long-term Fertility Control Agent in Female Mule Deer (Odocoileus hemionus hemionus) Research and Development Period Covered: July 1,2001 - June 30, 2002 Author: Dan L. Baker, Ph.D. Personnel: M. A. Wild, T. M. Nett, T. Davis, E. Jones, B. Hochmoth ABSTRACT We evaluated the effects of GnRH-PAP on mule deer pregnancy rates, duration of suppression of luteinizing hormone and progesterone secretion, blood chemistry and hematology, and reproductive behavior during 1 November to 30 December, 2001. Twenty-two adult female mule deer were assigned to one of 3 experimental groups. Nine female mule deer were treated with GnRH-PAP and 9 females served as untreated controls. The dose of GnRH-PAP used in this experiment did not lower pregnancy rates in female mule deer. Treated and control females tested positive for pregnancy specific protein B on all sampling dates and all delivered healthy fawns in July. At 30 days posttreatment, luteinizing hormone and progesterone were not different (P > 0.58) in treated and control mule deer. Reproductive behaviors of GnRH-PAP treated females were not different from controls. We conclude that the dose of GnRH-PAP administered in this experiment was ineffective in suppressing reproduction in female mule deer. ��105 EVALUATION OF GnRH-PAP AS A LONG-TERM AGENT IN FEMALE MULE DEER (ODoeO/LEUS FERTILITY CONTROL HEM/ONUS HEM/ONUS) Dan L. Baker P. N. OBJECTIVES 1. Develop a practical and acceptable technology for long-term control of fertility in female mule deer. 2. Demonstrate the feasibility of controlling mule deer population growth in a field application. SEGMENT OBJECTIVES 1. Evaluate the effectiveness of GnRH-PAP in preventing pregnancy in captive female mule deer. 2. Evaluate the duration of GnRH-PAP suppression ofLH and progesterone secretion in female mule deer. 3. Assess the behavioral and physiological side-effects (if any) of GnRH-PAP in captive female mule deer. INTRODUCTION Controlling the growth of animal populations is fundamental to maintaining proper balance between wildlife and the habitats they occupy. This is particularly true for wild ungulates. Overabundant ungulates can cause serious degradation of plant communities, and preventing such damage requires controlling their numbers. Hunting has traditionally been used to control ungulate populations but there are increasingly more situations where hunting is infeasible. Such areas include urban areas where safety of people and property may be threatened, or national parks and refuges where populations are managed primarily for non-consumptive uses like wildlife viewing and photography or on military installations and industrial parks because of concerns for security. In these situations, alternatives to hunting or culling as a means of controlling ungulate numbers are needed. Fertility control offers a potential alternative for controlling the growth of overabundant ungulate populations when traditional methods are infeasible or unacceptable (Kirkpatrick and Turner, 1985; Bomford, 1990; Garrot, 1995). However, current technology does not provide a means for controlling populations that is practical, economical and without undesirable side-effects (reviewed by Fagerstone et al.,2001). For most free-ranging wild ungulate populations, permanent sterilization has been proposed as the most efficacious approach to population management (Hone 1992, Garrot 1995, Hobbs et al. 2000). A promising new non-steroidal, non-immunological approach to permanent infertility involves analogs of gonadotropin-releasing hormone (GnRH). GnRH is a molecule produced in the hypothalamus of the brain. It directs specific cells in the anterior pituitary gland to synthesize and secrete two important reproductive hormones; follicle stimulating hormone (FSH) and luteinizing hormone (LH). These latter two hormones, known as gonadotropins, control the proper functioning of the ovaries in the female and the testes in the male. �106 Analogs of GnRH have the potential to permanently inhibit reproduction. By coupling a superactive analog of GnRH to a cytotoxin, it should be possible to specifically target that toxin to LH and FSHsecreting cells in the anterior pituitary gland (Collier and Kaplan 1984, Pastan et al. 1986). Therefore, a single GnRH-toxin conjugate has the potential to induce sterility in both sexes and numerous species of animals. There are many natural cytotoxins available for conjugating to GnRH. Toxins are composed of two subunits, a toxic subunit and a binding subunit. In order to target the toxin to specific cell types (rather than all cells) within the body, the binding subunit of the toxin can be removed and replaced by a molecule that will bind to only one cell type, in our case an analog of GnRH. This will target the toxin to gonadotropin secreting cells in the anterior pituitary gland. This approach has several potential advantages over other methods of contraception. These include: 1) a single treatment should permanently sterilize an animal; 2) the same treatment should be effective in both males and females and in different vertebrate species; 3) GnRH-toxin conjugate is a protein and is metabolized from the body within a few days of treatment, therefore it poses no threat to non-target species; 4) the small volume required for contraception facilitates microencapsulation syringe dart or biodegradable bullet. and administration by Proposed Research To our knowledge, only limited investigations have been conducted with GnRH-PAP in wild ungulates (Nett et al. 2001). In order to provide an estimate of the dose of GnRH-PAP conjugate required for contraception, it is essential that the potency of GnRH analog be determined in each species and at different phases of the reproductive cycle. We addressed this question in a series ofGnRH challenge trials with captive mule deer at the Foothills Wildlife Research Facility in Fort Collins, Colorado (Baker et al. 1996). In these experiments, we determined the most effective dose ofGnRH analog in female mule deer during the breeding season to be 1 f.Lg/50kg BW. This is the minimum dose of GnRH analog that will illicit maximum LH secretion. The next questions that needed to be answered were "how effective is GnRH-PAP in preventing pregnancy, how durable are its effects over time, and are there unacceptable side effects? The objective of this experiment is to begin to address these questions. Specifically, our objectives were: 1) to evaluate the effectiveness of GnRH-PAP in preventing pregnancy in mule deer; 2) to evaluate the duration of GnRH-PAP suppression ofLH and progesterone secretion; 3) to assess the behavioral and physiological side-effects (if any) of GnRH-P AP treatment. MATERIALS Reproductive AND METHODS Biology Mule deer (Odocoileus hemionus hemionus) are polytocous, multiovular, spontaneous ovulators that exhibit highly seasonal patterns of reproduction that are controlled by photoperiod regimens. The onset of the breeding season occurs during decreasing daily photoperiods of autumn and is preceded by a period of deep anestrous in summer (Plotka et aI.1977). The first ovulation of the breeding season is usually preceded by one or more silent ovulations associated with the formation of short-lived corpora lutea that serve to synchronize the first overt estrus within a herd (Thomas and McT.Cowan 1975). In temperate North America, the majority of conceptions occur in late November, but recurrent estrous �107 cycles of24 -28 days are possible through March if females fail to conceive (Knox et al. 1988). In early spring, coincidental with increasing day length, reproductive cycles cease and females remain anestrous until October. For pregnant females, parturition generally occurs in late Mayor early June, after a gestation period of about 200 days (Anderson and Medin 1966). Most females produce one fawn"when they are two years old, and one or two annually thereafter (Cowan 1956). Experimental Design We evaluated the effects of GnRH-PAP on mule deer pregnancy rates, duration of suppression ofLH and progesterone secretion, blood chemistry and hematology, and reproductive behavior during 1 November to 25 December 2002. Twenty-two adult female and 2 adult male mule deer were used in this experiment. Females were assigned to one of3 experimental groups based on their tractability for handling and blood sampling. Nine female mule deer (Group A) were treated with GnRH-PAP and 9 females (Group B) served as untreated controls and were used to compare pregnancy rates, blood chemistry and hematology, and reproductive behavior to those of treated animals. Immediately following the pretreatment GnRH challenge trial, and before catheters were removed, 9 females in Group A were administered an optimum dose of GnRH-PAP (1/-lgl50kgBW) N. Females in Groups A and B were maintained together with 2 adult male mule deer in a 2 hectare pasture. The remaining 4 females (Group C) served as untreated, non-pregnant controls and were placed in a separate pasture (0.5 ha) without direct contact with male deer. We compared LH and progesterone secretion of these females to those treated with GnRH-PAP (Group A). Sample size requirements were based on the variances observed in these measurements from previous studies with captive mule deer and expected effectiveness of treatment (Baker et al. 1996, Nett et al. 2001). Experimental Animals In order to meet sample size requirements calculated for this experiment (see pages 5-7), 5, adult, freeranging female mule deer were captured from urban areas of the front range of Colorado and transported to FWRF. We attempted to capture the most human-habituated deer as possible in order to minimize any stress related to captivity. All deer were captured and handled under the supervision of a veterinarian using one of several previously approved methods (Conner and Miller, CDOW ACUC 12-1999 & addenda); however thiafentanil oxalate (0.1 mglkg) was substituted for carfentanil citrate as a primary tranquilization drug. Once tranquilized, does were blindfolded, condition and vital signs checked, eartagged, collared, vaccinated with 7-way clostridial vaccine, treated with Ivermectin (0.1 mglkg) and long-acting penicillin. Each doe was then placed in a closed vehicle (covered horse trailer), and sedation reversed and blindfold removed. After release at FWRF, deer were observed daily for any signs of post-capture injuries. Response Measurements Hormonal evaluation. Prior to application of GnRH-PAP, we measured the LH response of each female in Groups A and C to a challenge dose of GnRH analog. Results from this trial provided a pretreatment baseline for comparison to future posttreatment LH responses. This and succeeding LH challenge trials were conducted as follows: On day 1 of the trial, deer were moved from 2 ha pastures to individual isolation pens, sedated (4-6 ml, 2:1 ketamine (200 mglml):xylazine hydrochloride (100 mglml, 1M), and fitted nonsurgically with indwelling jugular catheters. Animals were reversed with yohimbine (0.125 mglkg, N). On day 2, we administered GnRH analog (Irz /50 kg BW) through the cannula and �108 collect blood samples (5 ml) at 0,60, 120, 180,240,300,360, and 480 minutes postinjection. Following the last blood collection, catheters were removed and each animal given an antibiotic (ceftiofur, (1 mg/kg, N). Animals were then returned to 2 ha pastures. Serum wasstored at -20°C until analyzed for LH (Niswender et al. 1969). The duration of contraceptive effectiveness was assessed by conducting similar GnRH challenge trials each month from November, 2001 to December 2003. Analysis. Responsiveness of the pituitary to GnRH challenge was assessed in three ways: 1) maximum LH (ng/ml) response achieved postinjection minus baseline, 2) time required to reach maximum LH, and 3) total amount ofLH secreted (ng/mllmin). Pregnancy rates. We assessed contraceptive effectiveness by determining the pregnancy rates of treated (Group A) and control (Group B) deer. A single blood sample (10 ml) was taken viajugular venipuncture from each animal for pregnancy-specific protein B (PSPB) analysis approximately 60, 90, and 220 days post-conception (Willard et al. 1998). Animal handling and blood collections for PSPB followed methods previously described for hormonal assessment and were collected in conjunction with these measurements. Neonates born to any experimental animal were incorporated into the resident FWRF mule deer herd. General health. Limited knowledge of the effects of GnRH-PAP on nutrition, body weight dynamics, blood chemistry and general health of mule deer have been reported in a previous study at this facility (Nett et al. 2001). However, since a different toxin conjugate is being tested in this experiment, we evaluated these potential side-effects here as well. We assessed physiological side-effects of GnRH by comparing serum chemistry, hematology, and body weight dynamics of treated (Group A) and untreated, non-pregnant mule deer (Group C). Blood collections and body weight measurements were made in conjunction with GnRH challenge trials. Blood samples for hematology and serum chemistry analysis were collected prior to treatment and at 90 days posttreatment then submitted for analysis to Colorado State University, Veterinary Teaching Hospital, Clinical Pathology Laboratory, Fort Collins, Colorado, USA. Serum chemistry profiles were obtained using a Hatachi 917 auto analyzer (RochelBoehringer Mannheim, Indianapolis, Indiana, USA) for the following parameters: glucose, creatinine, phosphorus, calcium, magnesium, total protein, albumin, globulin, albumin/globulin ratio, bilirubin, creatinine kinase, aspartate aminotransferase, gamma-glutamyltransferase, sorbitol dehydrogenase, sodium, potassium, chloride, and biocarbonate. Values for the following hematological parameters were obtained using an ADVIA 120 auto analyzer (Bayer Corporation, Tarrytown, New York, USA): nucleated cells, neutrophils, lymphocytes, monocytes, eosinophils, plasma protein, erythrocyte, hemoglobin, packed cell volume, mean corpuscular volume, mean corpuscular hemoglobin concentration, platelets, and fibrinogen. Reproductive behavior. The effectiveness of GnRH-P AP as a fertility control agent is dependent upon permanent suppression of ovulation and steroidogenesis. Thus, we tested 2 hypotheses relative to the effects of leupro lide on reproductive behavior of mule deer: (1) because GnRH-PAP is expected to suppress gonadotrophin secretion and ovulation, we predicted that sexual interactions during the breeding season (Nov 1 - Dec 20) would be reduced in treated females (Group A) compared to untreated controls (Group B), and (2) once untreated females become pregnant, reproductive behaviors would cease and sexual interactions would be similar between untreated and treated females during the postbreeding season (Jan 10 - Mar 31). �109 To test these hypotheses, we examined the effects of GnRH -PAP on reproductive interactions of male and female deer during 2 time periods; breeding season (defined as the period November 1- December 20,2001) and postbreeding season (defined as the period January 10 - March 27, 2002). On November 1,2001, female deer in Group A were treated with GnRH-PAP and released with untreated controls (Group B) into 2 ha paddocks. Four days later (November 5), we placed 2 adult male mule deer with these groups and initiate behavioral observations. All females were individually identified with color/numeric-coded neck collars. Animals selected as treatments and controls were unknown to observers. Behavioral measurements were made from a distance of50-350 m from an elevated tower (10 m) using binoculars and a spotting scope during the day, and a spotlight and night vision scope at night. We recorded selected behaviors using a lap-top computer with a behavioral software program. We used focal animal sampling procedures to sample reproductive behaviors of all experimental animals . over a 24-hour period (Lehner, 1996). Previous studies (Baker et al. 2000) have shown that mule deer are most active in morning (0500-0800), late day (1400-1700) and night (2000-2400). Thus, time-of-day sampling periods was randomly assigned each week using a randomized block design. Each sampling period consisted of at least two hours of continuous observations. Sample size estimation for pregnancy rate and behavior measurements. Sample size calculations were based on results of previous investigations (Baker 2001). We used male pre-copulatory behavioral rates to estimate sample size because these rates were much higher than other rates (Table 1). Table 1. Behavior rates for mule deer (Baker 2001). Behavior Category Treatment Group Mean SE (# behaviors/day) Copulatory Control Leuprolide 0.20 0.29 0.17 0.24 8.28 22.18 1.77 2.50 0.22 1.35 0.34 0.47 2.00 2.96 0.41 0.58 Male Pre-Copulatory Control Leuprolide sa Female Pre-Copulatory Control Leuprolide sa General Breeding Control Leuprolide sa For control females, we directly bootstrapped a given sample size from the male pre-copulatory rates exhibited towards control does from the Table 1. That is, for a sample size of 6, we randomly selected 6 does (with replacement) for the given observation period, from the 8 control does. For treated does, we followed the same procedure except that we multiplied the response by the effect size. For example, for a +50% effect size, we multiplied the control response by 1.5. We then ran sample sizes for increased behavioral rates because this would be the most problematic to the animal. However, the power should be almost the same for a -50% effect size. We considered the higher behavior rates because increased behavior and corresponding energy output would be the most critical to the animal. This approach captured the day to day variability in behavior rates, because we bootstrapped for each observation period, but it assumes that the variability in behavior is the same for the control and treatment does. Next, we ran the procedure for 52 and 104 observation periods. We assumed 104 observation periods would be acceptable for 2 reasons. First, our proposed collection schedule was: �110 a. November - 4 weeks x 3 observation periods/day x 5 days/week = 60 obs periods b. December - 4 weeks x 2 observation periods/day x 5 days/week = 40 obs periods Total = 100 observation periods. Since power was not nearly as sensitive to the number of observation periods as to the number of animals used in the experiment; we decided that if we were somewhat below the 104 observations used in sample size simulations, it would not change the power meaningfully. Power results were based on the number of times an effect was detected during 100 simulations. Results from male precopulatory behavioral rates indicated that a sample size of 14 does (7 control and 7 treatment) should provide power of >90% to detect a 50% effect size. Table 2. Sample size calculations for a given effect size using male precopulatory behavior rates. Effec t size Sample Size * 25% 12 Number of Observation Periods 104 16 104 8 104 10 104 12 104 12 52 40% 9 104 50% 7 104 8 104 8 52 30% IX Power 0.05 0.10 0.05 0.10 0.05 0.10 0.05 0.10 0.05 0.10 0.05 0.10 0.05 0.10 0.05 0.10 0.05 0.10 0.05 0.10 57% 74% 81% 91% 68% 70% 72% 83% 90% 95% 68% 81% 91% 97% 94% 96% 97% 100% 74% 88% ~.-.:.•., ~ -'" * Sample size for each group, e.g. 12 means 12 treatment and 12 control does. The daily male precopulatory rate for the control group was 8.3 behaviors/day. For a 50% effect size, we could detect a difference between the control mean of 8.3 behaviors/day and a treatment mean of <4.2 and> 12.5 behaviors per day. For a 40% difference in behavior rates, we could detect a difference between the control mean of 8.3 behaviors/day and a treatment mean of <5 and> 11.6 behaviors per day. After estimating the number of animals needed to detect behavioral differences, we calculated power to detect differences in pregnancy rates. If we have 7 control and 7 treatment animals, and 1 treatment animal gets pregnant, and 1 control animal does not get pregnant, we had >95% power to detect this difference. Basically, to detect a difference in pregnancy rates in the case where 1 treatment animal gets pregnant, and 1 control animal does not get pregnant, we could have as low as 5 treatment and 5 control animals and still have >90% power to detect a difference. Thus, the sample size needed to detect �III differences in behavior rates was sufficient to detect differences in pregnancy rates. Our calculations indicated that the optimum sample size for these measurements to be 14 animals (7 control : 7 treated), however, there is a high probability of losing at least one or two animals per year to non-treatment related mortality. Therefore, in order to insure meaningful measurements over the 2-year investigation, we increased our sample size to 18 animals (9 control: 9 treated). Statistical Analysis We analyzed for differences among hormone levels using least squares analysis of variance for general linear models (SAS Institute 1993). Responses to treatments were analyzed with one-way analysis of variance for a randomized complete block design with repeated measures structure. Treatment effects were tested using the animal-with in-treatment variance as the error term. Time was treated as a withinsubject effect using a multivariate approach to repeated measures (Morrison, 1976). A "protected" least significant difference test (Milliken and Johnson 1984) was used to separate means when the overall Ftest indicated significant treatment effects (P < 0.05). We tested specific reproductive behavior hypotheses that mean behavior rate was not different between treatment and control groups for both the breeding and postbreeding seasons using an ANOV A model with a repeated measures structure. Similar to the hormonal analysis, time was be treated as a within subject effect using multivariate approach to repeated measures (Morrison, 1976). To test for treatment effects, we accounted for time-of-day, date effects and their interactions. PROC GENMOD (SAS Institute 1993) was used to estimate and test for differences in mean behavior rate by treatment, time-ofday, and date. Means and standard errors were estimated using least squares, and hypothesis tests were based on type III generalized estimating equations that account for correlation in repeated measurements. RESULTS AND DISCUSSION Pregnancy rates. This dose of GnRH-PAP did not lower pregnancy rates in female mule. Treated and control females tested positive for PSPB on all sampling dates and all delivered healthy fawns in July August,2002. All fawns were incorporated into the existing captive mule deer herd at the FWRF. Hormonal evaluation. GnRH-PAP did not cause a significant reduction in LH in treated female mule deer. Peak serum LH concentrations for treated animals, after 30 days posttreatment, averaged 8.6 ± 1.97 ng/ml and 9.7 ± 3.0 ng/ml for controls. Based on these responses, GnRH challenge trials were terminated at + 30 days posttreatment (4 Dec 2001). Reproductive behavior. We observed male to male dominance interactions immediately following their release into the pastures with treated and untreated females. Within 10 days, one male established dominance. Thereafter, the subdominant male retreated to remote locations within the pastures and rarely interacted with females or the dominant male for the remainder of the experiment. Contrary to our hypothesis, sexual interactions were not different (P > 0.65) during the breeding and post-breeding seasons between GnRH-treated females and untreated controls for any of the breeding behavior categories. We observed almost no sexual interactions between the dominant male and treated or untreated females during the postbreeding season. We conclude from these measurements that the dose of GnRH-PAP administered in this experiment was ineffective in suppressing reproduction in female mule deer. Future experiments should investigate the effects of higher-levels of GnRH-PAP on reproductive performance in this species. �112 LITERATURE CITED Anderson, A. E., and D. E. Medin. 1966. The breeding season in migratory mule deer. Outdoor Facts, Number 60, Colorado Division of Wildlife. Baker, D. L. 2001. Technical support for deer population management at the Rocky Mountain Arsenal National Wildlife Refuge, Denver, Colorado. Pages 215-232 in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W-153-R-4, SP 1, J1. Colorado Division of Wildlife, Fort Collins, Colorado, USA. ___ . 1996. Regulation of mule deer population growth by fertility control: laboratory, field, and simulation experiments. Pages 81-87 in Wildlife Research Report, Mammals Research, Federal Aid Projects, Job Progress Report, Project W -153-R-4, SP 1, II. Colorado Division of Wildlife, Fort Collins, Colorado, USA. Bomford, M. 1990. A role for fertility control in wildlife management? Department of Primary Industries and Energy Bureau of Rural Resources Bulletin No 7 Australian Government Publishing Service Canberra Australia .. Collier, R. J., and D. A. Kaplan. 1984. Immunotoxins. Scientific American 251 :64. Cowan, I. McT. 1956. Life and times of the coast black-tailed deer. Pages 56-78 in The Deer of North America, ed. W. P. Taylor. Wildlife Management Institute, Washington, D. C. Fagerstone K. A., M. Coffey, P. Curtis, R. Dolbeer, G. Killian, L. A. Miller, and L. Wilmot. 2001. Wildlife contraception. Wildlife Society Technical Review. Proceedings of the Wildlife Society 8th Annual Conference, Reno, USA. Garrot, R. A. 1995. Effective management of free-ranging ungulate populations using contraception Wildlife Society Bulletin 23 :445-452. Hone, J. 1992. Rate of increase and fertility controL Journal of Applied Ecology 29:695-698. Hobbs, N. T., D. C. Bowden, and D. L. Baker. 2000. Effects offertility control on populations of , ungulates: general, stage-structured models. Journal of Wildlife Management 64: 473-491. Knox, W. M., K. V. Miller, and R. L. Marchinton. 1988. Recurrent estrous cycles in white-tailed deer. Journal of Mamma logy 69:384-386. Lehner, P. N. 1996. Handbook of Ethological Methods. Second Edition. Cambridge University Press, , Cambridge, UK. Milliken, G. A., and D. E. Johnson. 1984. Analysis of Messy Data. Volume I Designed Experiments. Lifetime Learning Publications, Belmont,California, USA Morrison, D. F. 1976. Multivariate Statistical Methods. McGraw-Hill Book Co., New York, USA Pastan, L, M. C. Willingham, and D. J. FitzGerald. 1986. Immunotoxins. Cell 47:641-648. Plotka, E. D., U. S. Seal, G. C. Schmoller, P. D. Karns, and K. D. Keenlyne. 1997. Reproductive steroids in the white-tailed deer (Odocoileus virginianus borealis). 1. Seasonal changes in the female. Biology ofReproductio~:I16:340-3.43. ." , Thomas, D. C., and L MeT. Cowan. 1975. The pattern of reproduction in female Columbian black-tailed deer, Odocoileus hemionus columbianus. Journal of Reproduction and Fertility 44:261-272. Nett, T. M., D. L. Baker, and M. A. Wild. 2001. Evaluation of GnRH-PAP as a chemosterilant in captive mule deer (Odocoileus hemionus hemionus). Proceedings of the 5th International Symposium on Fertility Control in Wildlife, Kruger NationalPark, South Africa, August 19-22. Niswender G. D., L. E. Reichert, Jr., A.R. Midgley, and A. V. Nalbandov. ,,1969. Radioimmunoassay for bovine and ovine luteinizing hormone. Endocrinology 84:1166-1173. Willard, S. T., R. G. Sasser, J. T. Jaques, D. R. White, D. A. Neuendorff, and R. D. Randel. 1998. Early pregnancy detection and hormonal characterization of embryonic-fetal mortality in fallow deer (Dama dama). Theriogenology 49:861-869. ' �113 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 PROGRESS State of -'C"'-'o,,_,I""or!.!:a""'d'-"'o _ Work Package No. 3001 Task ~I~O~ Federal Aid Project Period Covered: Author: Personnel: REPORT Division of Wildlife - Mammals Research Deer Conservation _ W!..!..--I"'-'S,,-,05'-.-,..,R:......._ Chronic Wasting Disease in Mule Deer Monitoring & Management July 1,2000 through June 30, 2001 Michael W. Miller, D.V.M. T. R. Davis, L. L. Wolfe, T. H. Baker, K. T. Larsen, E. S. Williams Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT We continued conducting research on various aspects of chronic wasting disease (CWD) epidemiology and management. Results of original research, as well as two review articles, were published or accepted for publication during this segment, and citations are included in the body of the report. In addition to published studies, we completed a study of CWD pathogenesis in mule deer. Seven of 10 orally inoculated deer that survived> 12 mo postinoculation (PI) developed clinical CWD. Five of the seven deer that showed clinical signs either died or were euthanized in end-stage clinical CWD 20-26 mo PI; the other two were euthanized showing mild or marked clinical signs 20 mo PI according to the established sampling schedule. Based on observations of the seven deer that developed clinical CWD, earliest signs were first noticed in individuals about 14.5 to 19 mo PI (mean ± SE = 17.3 ± 0.7 mo PI). Early clinical signs were both subtle and inconsistent. As clinical disease progressed, behavioral changes and loss of body condition became more pronounced and more consistent. Ptyalism (drooling), polydypsia (excessive water consumption), and polyuria (excessive urination), widely regarded as "classic" signs of CWD, occurred relatively late in clinical courses and were not seen in all cases. Among the five deer that lived long enough to develop terminal CWD, clinical courses ranged from about 3.5 to 9.5 mo (mean ± SE = 5.7 ± 1.2 mo); the shortest clinical course (about 3.5 mo) was complicated by acute aspiration pneumonia. Immunohistochemistry and histopathology results are pending . .\ . ,:~ . . ~~-. i . I. ��115 INTRODUCTION We continued conducting research on various aspects of chronic wasting disease (CWD) epidemiology and management. METHODS Epidemiology & Management Two review articles on CWD epidemiology were accepted for publication during this segment in the Journal of Wildlife Management and in the Revue Scientifique et Technique Office international des Epizooties. Results of three earlier studies on CWD epidemiology were published during this segment in the Journal of Wildlife Diseases and the Journal of Wildlife Management. Pathogenesis & Diagnosis Results of two original studies on CWD diagnosis in mule deer were accepted for publication in the Journal of Wildlife Management and in The Veterinary Record. We completed a study of CWD pathogenesis in mule deer. The methods for this project were included in previous progress reports. We also initiated preliminary field work to develop and evaluate reliable methods for collecting tonsil biopsies from live mule deer for use as a diagnostic and management tooL No results are available for reporting in this reporting period. RESULTS AND DISCUSSION Epidemiology & Management Two review articles on CWD epidemiology were published during this segment: Williams, E. S., and M. W. Miller. 2002. Chronic wasting disease in deer and elk in North America. Revue Scientifique et Technique Office international des Epizooties 21:305-316. Williams, E. S., M. W. Miller, T. J. Kreeger, R. H. Kahn, and E. T. Thorne. 2002. Chronic wasting disease of deer and elk: A review with recommendations for management. Journal a/Wildlife Management 66:551-563. Results of three studies on CWD epidemiology were published during this segment: Conner, M. M., C. W. McCarty, and M. W. Miller. 2000. Detection of bias in harvest-based estimates of chronic wasting disease prevalence in mule deer. Journal of Wildlife Diseases 36:691-699. Gross, J. E., and M. W. Miller. 2001. Chronic wasting disease in mule deer: disease dynamics and controL Journal of Wildlife Management 65:205-215. Miller, M. W., E. S. Williams, C. W. McCarty, T. R. Spraker, T. J. Kreeger, C. T. Larsen, and E. T. Thorne. 2000. Epizootiology of chronic wasting disease in free-ranging cervids in Colorado and Wyoming. Journal of Wildlife Diseases 36:676-690. Pathogenesis & Diagnosis Nineteen of20 mule deer orally inoculated with 5 g brain homogenate from CWD-infected mule deer survived 2: 3 months postinoculation (PI) and were examined as described in the original study plan; �116 one fawn died <1 day PI of capture-related complications, and was not evaluated here. Of the 19 . remaining deer, one died from a cervical fracture at 3 mo PI and 12 others were euthanized at 3,6,9, 12, 16, or 20 mo PI according to the study schedule; the other 6 were allowed to survive to terminal stages of CWD or study termination. Seven of 10 orally inoculated deer that survived> 12 mo postinoculation (PI) developed clinical CWD; four of these were males and three were females. Of the three that did not show at least early clinical signs, two were euthanized 16 mo PI but the third appeared clinically normal when euthanized 26 mo PI. Five of the seven deer that showed clinical signs either died or were euthanized in end-stage clinical CWD 20-26 mo PI; the other two were euthanized showing mild or marked clinical signs 20 mo PI according to the established sampling schedule. Based on observations of the seven deer that developed clinical CWD, earliest signs (dullness in eyes, diminished alertness, misdirected behaviors, piloerection) were first noticed in individuals about 14.5 to 19 mo PI (mean ± SE = 17.3 ± 0.7 mo PI). Early on, clinical signs were both subtle and inconsistent. As clinical disease progressed, behavioral changes (e.g., blank staring, uncharacteristic or subdued responses to aversive stimuli, lowered head or other unusual postures, ataxia, inefficient foraging activity) and loss of body condition became more pronounced and more consistent. Ptyalism, polydypsia, and polyuria occurred relatively late in clinical courses, and were not seen in all cases. Among the five deer that lived long enough to develop terminal CWD, clinical courses ranged from about 3.5 to 9.5 mo (mean ± SE = 5.7 ± 1.2 mo); the shortest clinical course (about 3.5 mo) was complicated by acute aspiration pneumonia. Immunohistochemistry and histopathology results are pending. Results of two original studies on CWD diagnosis in mule deer were accepted for publication. One of these (Wolfe et al. 2001) represents the first report of a method for detecting CWD infection in live animals. These publications were: Miller, M. W., and E. S. Williams. 2002. Detecting PrPCWD in mule deer by immunohistochemistry of lymphoid tissues. Veterinary Record 151 :610-612. Wolfe, L. L., M. M. Conner, T. H. Baker, V. J. Dreitz, K. P. Burnham, E. S. Williams, N. T. Hobbs, and M. W. Miller. 2002. Evaluation of antemortem sampling to estimate chronic wasting disease prevalence in free-ranging mule deer. Journal of Wildlife Management 66:564-573. �117 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 JOB PROGRESS REPORT State of ...:::C'-'o'-'-lo""r:.,::a:=d=o __ ---'-__ Work Package No. ---'3:;;..0::..;0""'1'-- Task No. ----"A-=-- Project No. Mammals Research - Terrestrial Section Deer Conservation _ _ Deer Aerial Survey Population Estimation Rangely· Deer Data Analysis Unit D~6,GMu 10 ---'-W!....-....!..1 ~53"_-""'R,_-1"_4,__ _ Period Covered: July 1,2000 - June 30, 2001 Author: D. J. Freddy r Personnel: V. Graham, W. deVergie, J. Ellenberger, C. Wagner, P. Schnurr, R. Kahn, R. Velarde, G. Miller, T. Wygant, F. Pusateri of CD OW, Dr. G. White and M. Kneeland of Colorado State University, J. Unsworth, Idaho Department ofFish and Game, consultants V. Howard, Jr. and T. Bickle, Colorado Mule DeerAssociation, Colorado Bowhunters Association, Dynamic Aviation, and New Air Aviation. ABSTRACT Sportsmen expressed concerns about the credibility of Colorado's survey sampling methodology to estimate numbers of mule deer (Odocoileus hemionus) in specific populations. We therefore conducted an aerial survey in Colorado Deer Analysis Unit D-6 which was an area of concern to sportsmen. We used helicopters from 28 February to 5 March 2001 to count mule deer on randomly selected quadrats 0.25-mi2 or 1.00-mi2 in size distributed within 11 strata encompassing 364 mf of deer winter range composed of sagebrush (Artemisia tridentata) and pinyon-juniper (Pinus edulis-Juniperous osteosperma) habitats. From these counts, we estimated population size using standard stratified random sample estimators and the Idaho mule deer sightability model. Stratified population estimate was 6,782 ± 2,497 (90% CI) deer. Counts corrected for sightability increased the estimate to 11,052 ± 3,503 (90% CI) deer. Both aerial survey estimates buttressed population estimates of7,000 to 7,300 deer derived from computer models and were substantially greater than sportsmen's estimate of 1,750 deer. Cost of this validation exercise exceeded 50,000 $US. We interpreted this exercise as aforerunner of the public's interest in challenging agency integrity or methods used to estimate status of ungulate populations. We caution agencies to use tested methodology that can withstand dispassionate public scrutiny. Copies of this report containing the original colored versions of the figures are available for review from the Research Center Library, Colorado Division of Wildlife, 317 West Prospect Road, Fort Col/ins, CO, 80526, USA. All information in this report is preliminary and subject to further evaluation. ��119 PROJECT SUMMARY REPORT DEER AERIAL SURVEY POPULATION ESTIMATION RANGELY DEER DATA ANALYSIS UNIT D-6, GAME MANAGEMENTUNIT COLORADO DIVISION OF WILDLIFE PRESENTED APRIL 19, 2001 DOCUMENT PREPARED 10 TO INFORM COLORADO DIVISION OF WILDLIFE COLORADO WILDLIFE COMMISSION COLORADO MULE DEER ASSOCIA nON COLORADO BOWHUNTERS ASSOCIA nON Includes Draft Manuscript Subject to Future Editorial RevieW© REPORT PREPARED COLORADO BY DAVID J. FREDDY WILDLIFE RESEARCHER, MAMMALS RESEARCH DIVISION OF WILDLIFE, 317 WEST PROSPECT STREET, FORT COLLINS, RANGELY DEER AERIAL SURVEY POPULATION ESTIMATION DEER DATA ANALYSIS UNIT D-6, GAME MANAGEMENT 28 FEBRUARY - 5 MARCH 2001 CO 80526 UNIT 10, REPORT CONTENTS SECTION A -------- EXECUTIVE SUMMARY SECTION B -------- DRAFT TECHNICAL MANUSCRIPT SECTION C -------- 1. STRATIFIED RANDOM SAMPLING CALCULATIONS 2. MODIFICATION OF SAMPLE ~IZE DURING PROJECT SECTION D -------- 1. D-6, UNIT 10 DEER WINTER RANGE MAP 2. D-6, UNIT 10 DEER WINTER CONCENTRATION AREA MAP 3. D-6, UNIT 10 DEER WINTER SEVERE RANGE MAP SECTION E --------- 1. SAMPLING FRAME AND SAMPLING STRATA MAP 2. SAMPLING FRAME AND PRIMARY VEGETATION TYPES 3. YAMPA MONUMENT STRATA 1 AND 2 MAP 4. UTAH WHITE RIVER STRATA 3 AND 4 MAP 5. UPPER WHITE RIVER STRATA 5,6, AND 7 MAP 6. MASSADONA - DINOSAUR STRATA 10,11, AND 13 MAP 7. TWELVEMILE STRATA 12 MAP (Clarification: No strata numbered 8 & 9; 11 total strata) SECTION F ------- 1. SURVEY FLIGHT PROTOCOLS 2. SURVEY DATA FORM 3. SURVEY OBSERVER HELP SHEET SECTION G -------- SURVEY FLIGHT QUADRAT SAMPLE UNIT MAP INDEX SECTION H -------- 1. STRATIFIED RANDOM SAMPLE POPULATION ESTIMATE DATA AND CALCULATIONS 2. LETIER FROM IDAHO DEPARTMENT OF FISH & GAME SHOWING POPULATION ESTIMATE USING IDAHO SIGHTABILITY CORRECTIONS 3. COMPLETE DATA LISTING FOR AERIAL SURVEY 4. MAP SHOWING WHERE DEER WERE COUNTED 5. MAP SHOWING WHERE ELK WERE COUNTED 6. SUMMARY OF SPORTSMEN AND CDOW DEER POPULATION ESTIMATES FOR WESTERN COLORADO, DECEMBER 2000 �i1 120 SECTION A - EXECUTIVE SUMMARY DEER AERIAL SURVEY POPULATION ESTIMATION RANGELY DEER DATA ANALYSIS UNIT D-6, GAME MANAGEMENT UNIT 10 A. Sportsmen in Colorado alleged that estimates for numbers of mule deer in western Colorado were substantially over-estimated by the Colorado Division of Wildlife (CDOW). Sportsmen believed there were only 128,000 deer in Colorado in areas west of the Continental Divide where CDOW estimated 409,000 deer. This level of discrepancy also existed for specific deer populations such as in the Rangely Deer Analysis Unit D-6 where sportsmen estimated 1,750 deer compared to CDOW estimates of 7,000 deer. B. A series of meetings between CDOW and sportsmen from September 2000 through February 2001 did not resolve fundamental issues of sportsmen's mistrust of estimated deer population status. c. On February 16, 2001 CDOW Director Russell George authorized the Terrestrial Section to implement aerial surveys to estimate numbers of deer in Rangely Unit D-6 in accordance with survey methodologies agreed to by all interested parties, including participation in surveys by individuals independently representing sportsmen's concerns. Financial costs for the survey were paid primarily with Wildlife Commission Discretionary Funds with additional contributions from the Colorado Mule Deer Association and Colorado Bowhunters Association. D. CDOW conducted an aerial survey to estimate numbers of deer in D-6 using Colorado quadrat survey techniques that incorporated adjustments in estimated population size based on Idaho mule deer sightability models as requested by sportsmen. The survey was conducted 28 February to 5 March, 2001. E. Estimated numbers of deer in D-6 were 6,782 .:!:. 2,497 based on Colorado quadrat system and 11,052 .:!:. 3,503 when adjusted for the Idaho mule deer sightability model. Population estimates based on CDOW computer models were 7,000 to 7,312 deer. All estimates were substantially higher than the 1,750 deer estimated by sportsmen. F. Financial and personnel costs to design, implement, and analyze survey results likely exceed $50,000. Final costs estimates are not yet available. G. This validation exercise challenged the credibility of CDOW personnel and methodologies and the credibility of sportsmen groups. All parties participated within a certain level of risk. Not to be overlooked was a near fatal helicopter incident that threatened lives of personnel involved in an aerial survey conducted to alleviate mistrust among interested parties. H. We interpret this validation exercise as a potential forerunner of the public's interest in either challenging or understanding methods used to estimate status of wildlife populations. We can only caution that wildlife agencies should gather information using methodology that can withstand public scrutiny. We would hope that this exercise would restore a certain level of public confidence in the CDOW's efforts to manage wildlife in Colorado. �121 SECTION B - DRAFT TECHNICAL MANUSCRIPT April 18, 2001 Draft David J. Freddy Colorado Division of Wildlife 317 West Prospect Road Fort Collins, CO 80526 970-472-4346, FAX 970-472-4457 RH: Deer Population Estimates ESTIMATING MULE DEER POPULATION SIZE USING COLORADO QUADRAT SYSTEM CORRECTED FOR IDAHO MULE DEER SIGHTABILlTY: A SPORTSMEN'S ISSUE. DAVID J. FREDDY\ Colorado Division of Wildlife, Wildlife Research Center, 317 West Prospect Road, Fort Collins, CO 80526, USA GARY C. WHITE, Department of Fishery and Wildlife Biology, Colorado State University, Fort Collins, CO 80523, USA MARY C. KNEELAND, Colorado Division of Wildlife, Wildlife Research Center, 317 West Prospect Road, Fort Collins, CO 80526, USA VAN K. GRAHAM, Colorado Division of Wildlife, 711 Independent Avenue, Grand Junction, CO 81505, USA WILLIAM J. deVERGIE, Colorado Division of Wildlife, P.O. Box 1181, Meeker, CO 81641, USA JOHN H. ELLENBERGER, 81505, USA Colorado Division of Wildlife, 711 Independent Avenue, Grand Junction, CO JAMES W. UNSWORTH, Idaho Department of Fish and Game, 3101 South Powerline Road, Nampa, 10 83686, USA CHARLES H. WAGNER, Colorado Division of Wildlife, 346 Count Road 362, Hot Sulphur Springs, CO 80451· .. PAMELA M. SCHNURR, Colorado Division of Wildlife, 711 Independent Avenue, Grand Junction, CO 81505, USA V. W. HOWARD, JR., 1025 Hickory Drive, Las Cruces, New Mexico 88005, USA TOMMY S. BICKLE, P.O. Box 750, Hatch, New Mexico 87937, USA lCorresponding author. Abstract: Sportsmen expressed concerns about the credibility of Colorado's survey sampling methodology to estimate numbers of mule deer (Odocoi/eus hemionus) in specific populations. We therefore conducted an aerial survey in Colorado Deer Analysis Unit 0-6 which was an area of concern to sportsmen. We used helicopters from 28 February to 5 March 2001 to count mule deer on randomly selected quadrats 0.25-mi2 or 1.00-mi2 in size distributed within 11 strata encompassing 364 rnf of deer winter range composed of sagebrush (Artemisia tridentata) and pinyon-juniper (Pinus edulis-Juniperous osteosperma) habitats. From these counts, we estimated population size using standard stratified random sample estimators and the Idaho mule deer sightability model. Stratified population estimate was 6,782 ~ 2,497 (90% CI) deer. Counts corrected for sightability increased the estimate to 11,052 ~ 3,503 (90% CI) deer. Both aerial survey estimates buttressed population estimates of 7,000 to 7,300 deer derived from computer models and were substantially greater than sportsmen's estimate of 1,750 deer. Cost of this validation exercise exceeded 50,000 $US. We interpreted this exercise as a forerunner of the public's interest in challenging agency integrity or methods used to estimate status of ungulate populations. We caution agencies to use tested methodology that can withstand dispassionate public scrutiny. Key Words: bias, Colorado, helicopter surveys, Idaho, mule deer, Odocoi/eus hemionus, population estimates, sightability �122 Sportsmen in Colorado alleged that estimates for numbers of mule deer (Odocoi/eus hemionus) in western Colorado were substantially over-estimated by the Colorado Division of Wildlife (CDOW). For example during post-hunting season 2000, sportsmen believed there were only 128,000 deer in Colorado in areas west of the Continental Divide where CDOW estimated 409,000 deer. This level of discrepancy also existed for specific deer populations such as in the Rangely Deer Analysis Unit 0-6, where sportsmen estimated 1,750 deer compared to CDOW estimates of 7,000 deer after hunting season 2000 (Pers. comm. Colorado Mule Deer Association). These 4-fold differences in estimated numbers of deer explained why perceptions about the status of mule deer in Colorado varied between some sportsmen and CDOW. Sportsmen focused their concerns on the credibility of Colorado's quadrat survey sampling methodology to estimate numbers of deer in specific populations. This methodology, based on stratified random sampling theory (Thompson et al. 1998), was initially developed for helicopter counts of mule deer on t-rnf sample quadrat units used to estimate total numbers of deer in a population inhabiting extensive sagebrush habitats during winter (Gill 1969). This system was later expanded to estimate size of selected deer populations inhabiting pinyon-juniper habitats in western Colorado where quadrat sample unit size was reduced to 0.25-mi2 to compensate for the detrimental effects that dense pinyonjuniper canopy cover had on detecting and counting mule deer (Kufeld et al. 1980, Bartmann 1983, Bartmann et al. 1986). Aerial counting of deer using random quadrats provided estimates of deer numbers sufficiently suitable for herd management decisions but implementation costs prevented such systems from being employed in most deer management units in western Colorado (Gill et al. 1983). Alternative approaches to estimating trends in numbers of deer in every population included: intensively estimating numbers of deer, age and sex ratios, and survival rates in a few populations whose trends in population parameters could represent many deer populations inhabiting ecologically similar areas (White and Bartmann 1998, Bartmann 2000, Bowden et al. 2000); and, using computer modeling that incorporated measured parameters from appropriately similar ecological core areas in conjunction with less intense measurements of age and sex ratios and hunter harvests that could be obtained yearly for nearly every deer population (CDOW 1991, White and Bartmann 1998, Bartholow 2000,). The discrepancy in perceived numbers of deer in western Colorado more accurately reflected a concern about modeled as opposed to aerial survey estimates of deer population size because only about 10% of the deer populations were monitored using aerial quadrat sampling protocols. Nevertheless, sportsmen focused their concerns on aerial survey sampling' fearing that such techniques inflated estimates of deer numbers and therefore, misrepresented the declining plight of mule deer in western Colorado. Furthermore, sportsmen desired to assess the Idaho Mule Deer Sightability survey system (Ackerman 1988, Unsworth et al. 1994) as an alternative to Colorado's approach to estimating numbers of deer on the premise that the Idaho system would provide more acceptable estimates of deer numbers. This project was prompted by sportsmen's concerns about the legitimacy of deer population estimates based upon aerial surveys employing random sampling and counts of deer on sample quadrats. We conducted an aerial quadrat survey in a deer population unit of concern to sportsmen using Colorado quadrat survey techniques incorporating adjustments in estimated population size based on Idaho mule deer sightability models (Unsworth et al. 1994). Our survey and results were monitored by participating individuals independently representing sportsmen's concerns. We then compared estimates based on aerial surveys to ongoing population models used to guide management of deer. STUDY AREA We estimated numbers of mule deer inhabiting winter range in the Rangely Deer Analysis Unit 0-6 consisting of Game Management Unit 10 in northwestern Colorado near the town of Rangely. 0-6 includes 837 mi2 with large expanses of public lands administered by the U. S. Department of Interior Bureau of Land Management and National Park Service. Deer typically move onto winter range in November and begin returning to summer ranges in April. The project area is semi-desert with yearly precipitation ranging from 8 to 20 inches and winters having moderate temperatures and snow depths. Deer winter range occurs between 5,000 and 7,200 feet elevation and is a mixture of pinyon-juniper, sagebrush, and greasewood iSercobeius vermicu/atus) - desert shrub habitats and is shared with domestic sheep, cattle, and elk (Cervus e/aphus). During �123 winters with low snow depths, deer distribution could encompass 612 mf but under severe snow depth conditions, deer distribution may collapse to 106 rnf (CDOW 2001). Deer have been managed in D-6 under a limited permit hunting system since 1991 resulting in average yearly harvests of 118 bucks (range 70-252) and 60 antlerless does and fawns (range 2-132). Helicopter surveys of population ratios post-hunting season in December have shown 9-26 bucks: 100 does and 29-64 fawns: 100 does. Previous efforts to estimate population size of deer in D-6 involved assessing the practicality of using helicopter line transects (White et al. 1989) on a trial basis in 1990 and 1991 with resulting estimates of 21 ,630:t 12,321 and 13,596:t 5,427 (90% CI) deer, respectively (CDOW 1991). METHODS Sampling Protocols We estimated deer population size using stratified random sampling and counts of deer on randomly selected quadrat units (quadrats) (Thompson et al. 1998). Counts of animals on random units assume that units are completely searched by observers and allanimals present are detected and counted. These assumptions, therefore, assume 100% sightability of target animals and resulting estimates would not incorporate correction factors for animals not counted. We delineated our sampling area (frame) based upon the distribution of deer observed during systematic strip-surveys of potential winter range in the project area conducted with a Hiller 12-E Soloy helicopter on 6 February 2001. Using ESRI ArcVieW©, we delineated a frame of 364 rnf that encompassed the distribution of deer observed during the survey flight. Each cadastral square-mile within the frame was subjectively rated by flight observers as to high, medium, or low expected deer densities. Guidelines for relative deer densities were: >20 for high, 5-20 for medium, and < 4 deer/rnf for low. We then defined 11 strata based upon expected deer densities for the purpose of distributing quadrats through out the frame. Low, medium, and high density strata encompassed 113 mf (31 %), 157 mf (43%), and 94 rnf (26%), respectively, within the frame (Table 1). Proportions of vegetation types within each strata were estimated using ArcVieW© and Colorado GAP® vegetation coverage (Schrupp et al. 2000). We used 1- rnf quadrats in strata where open sagebrush-type habitats comprised> 50% of a stratum (Gill 1969) and 0.25-mi2 quadrats where pinyonjuniper habitats comprised> 50% of a stratum recognizing that tree canopy would hinder detection of deer (Bartmann 1983) (Table 1). We allocated quadrats among strata using optimum allocation (Thompson et al. 1998, pages 341342) with estimated variances based upon variance to mean ratios derived from quadrat sample units previously flown in Colorado since 1968 (Expected Standard Deviation 3.6379 + 1.0891 * [mean deer density], n 1,192 quadrats). We calculated number of quadrats needed to achieve precision of:t 20% of the mean population estimate with a 0.10 for potential population sizes ranging from 2,000 to 8,000 deer. We selected a sample size of 161 quadrats distributed among 11 strata for an expected population of 6,000 deer. We assumed the cost of flying 1-mi2 and 0.25-mi2 quadrats was the same based on a proportional per area basis (Table 1). We established a grid of point coordinates (UTM [x, y]; NAD 27, all standardized to Zone 13) every 0.25 mi within the frame using ArcVieW©. We then used the random number option in MS Excel97© to assign a random number to each grid point. Grid point random numbers were then ordered from low to high to initiate the process of randomly selecting locations for quadrats within strata, with quadrat location selection beginning with the lowest ordered grid point and continuing until all quadrats were assigned within each strata. We restricted locations of quadrats by defining a minimum distance between randomly selected grid points of 0.50 mi in strata using 0.25-mi2 quadrats and 1 mi in strata using t-rnf quadrats to reduce quadrats having common boundaries and to reduce clustering of quadrats within strata. Quadrats were irregular in shape with boundaries following terrain ridges and gullies or cultural features such as roads or trails that could be discerned on USGS 1:24,000 topographic maps and recognized by observers while flying in a helicopter (Freddy 1994, Unsworth et al. 1994). Quadrat polygons were digitized on digital topographic maps using ArcVieW© with quadrat area and perimeters calculated by ArcView©. Range of actual areas for 0.25-mi2 units was generally 0.22-0.28 mf and for 1mi2 units, 0.9-1.1 rnf', shaped with the intent to minimize perimeter to area ratios (Thompson et al. 1998). Randomly selected grid points had to be included within the defined quadrat and preferably centered = = = �124 within the quadrat. Flight path starting latitude-longitude coordinates, back-corrected for UTM Zone 12 or Zone 13 as necessary, were defined for each quadrat and labeled on flight navigation digital topographic maps printed in color using ArcVieW© layouts and MS PowerPoint97©. Flight Protocols We used Hiller 12-E Soloy (Hiller) and Bell Jet Ranger III (Ranger) helicopters to count deer on quadrats. While searching for deer, helicopters were flown at 35-50mph at 50-100 feet AGL. Observer, navigator, and pilot comprised flight crews, with observer and navigator having primary responsibilities to detect and count deer with the observer tape-recording all pertinent data. In the Hiller, the observer was seated in the starboard outside seat with the navigator seated in the middle. In the Ranger, the observer was seated in the port outside seat with the navigator in the port rear seat. Crews first flew boundaries of quadrats and then systematically searched the interior of quadrats using strips or strip-contours depending on steepness of terrain following standard procedures (Gill 1969, Kufeld et al. 1980, Freddy 1998, Unsworth et al. 1994). To optimize the visual scanning position of the observer when flying quadrat boundaries, the Hiller crew flew boundaries clock-wise and the Ranger crew flew boundaries counter-clockwise. Navigators and pilots determined proper starting locations of quadrats using previously calculated latitude-longitude coordinates entered into on-board Garmin Pilot III© global positioning units (GPS). Navigators then directed pilots along quadrat boundaries and suitable search paths within the quadrat using topographic maps and real-time flight traces recorded on GPS units. Navigators, observers, and pilots constantly adjusted flight speed, altitude and angle of attack to optimize viewing for the observer. Objectives were to fly quadrats to obtain 100% search coverage. Observers and navigators collectively detected and counted groups of deer on quadrats with the highest count by either person recorded by the observer. Observers and navigators collectively made decisions on whether to count deer detected near quadrat boundaries: groups moving onto quadrats when detected were considered outside quadrats; groups moving off quadats when detected were considered on quadrats; one-half of the deer in groups detected on boundaries were considered on quadrats. Observers and navigators also collectively kept mental track of group locations, movements and presence of unique antlered deer in groups to reduce chances of counting groups more than once. Flights were conducted when weather conditions were favorable. Flights were conducted only when wind speeds were low enough in the judgement of pilots to fly safely at desired slow airspeeds and low AGL. Lighting conditions varied from overcast to hazy or bright sunshine while snow cover background varied from 0 to 100 percent. Flights continued through short episodes of snow flurries provided safety was not compromised. For each quadrat, observers recorded flight conditions and total flight time. Idaho Sightability Protocols Sightability models correct for undercounting, or negative bias, that is generally associated with counts of ungulates (Caughley 1974, Bartmann et al. 1986, Samuel et al. 1987, Steinhorst and Samuel 1989, Unsworth et al. 1990, Otten et al. 1993, Pojar et al. 1995, White et al. 1989, Anderson and Lindzey 1996, Anderson et al. 1998, Cogan and Diefenbach 1998, Freddy 1998). To correct for potential negative bias in deer detected and counted on quadrats, we obtained values for sighting variables on each group of deer counted following guidelines for the Idaho mule deer sightability model (Unsworth et al. 1994). Sighting variables were total group size, behavior, vegetation type, and percent snow cover. Behavior of the most active deer when a group was first detected was recorded as bedded, standing, or moving. Although deer could have been detected in several vegetation types, we reduced types to broad categories to simplify the process of classifying vegetation: agricultural fields/open meadows; sagebrush, representing all low brush types; and pinyon-juniper, representing all pinyon or juniper dominated areas. Deer were not detected in tall conifer, aspen, or tall mountain brush habitats. Percent snow cover on the ground where each group was detected was classified as a categorical value of low (21-79%) or high t:: 80%}. The Idaho mule deer model most appropriate to correct undercounting deer was the spring sightability model which contained the following sighting variables (Unsworth et al. 1994: Jl = -0.254 + activity + vegetation class + snow cover + 0.047 * (group size) �125 Coefficients for each variable were developed in Idaho in similar but different vegetation and terrain types than might occur in Colorado. Knowing that Idaho coefficients may only approximate coefficients suitable for use in Colorado, we used the following Idaho coefficients for sighting variables (Unsworth et al. 1994): Activity: Bedded 0.000, Standing 1.56, Moving 4.43 Vegetation: Agriculture/meadow 0.00, Sagebrush -0.88, Pinyon-Juniper (Idaho Juniper/Mountain mahogany) -2.383 Snow Cover: Low 21-79% -1.37, High ~ 80% -0.60 = = = = = = = = Estimates of population size based on counts of deer on quadrats were corrected for sightability of each group using Idaho Aerial Survey© program for Windows© beta-version (Unsworth et al. 1994). Program Aerial Survey was limited to accepting only 10 defined strata from which to calculate population size. Our survey design incorporated 11 strata so we therefore, combined strata 1 and strata 2 (Table 1) into 1 strata to accommodate the program. We compared quadrat and quadrat sightability corrected population estimates using a standard z -test (Thompson et al. 1998). Both Idaho and Colorado systems were predicated on using stratified random sampling and thus, these systems complimented each other in conceptual design and application (Gill 1969, Unsworth et al. 1994). Modeling Protocols Estimating trends in deer population size over several years in 0-6 was an ongoing CDOW management evaluation process based upon computer modeling using POP-II software (Bartholow 2000). Computer models were constructed independently of data obtained during our aerial survey and by personnel who did not participate in the aerial survey. This model used yearly hunter harvest estimates (Steinert et al. 1994), deer survival rates (White et al. 1987), estimated post-season December doe:fawn and buck:doe ratios collected during yearly helicopter surveys (CDOW 1991), and winter severity values to estimate trends in population size. Such models provided an assessment of deer status independent of aerial quadrat surveys, and conversely, aerial quadrat surveys provided point estimates of population size to evaluate models. RESULTS We estimated deer density from 28 February to 5 March 2001 using about 35 hours of helicopter flight time to complete the survey (Table 2). Mechanical malfunctions with the Hiller resulted in using the Ranger more extensively than anticipated, altered availability of survey navigators and observers, and in conjunction with impending unfavorable weather, caused us to reduce sampling intensity in 3 strata in order to complete the survey (Table 1). Adjustments in flight crew members and survey sampling were completed with the approval of independent evaluators. Survey Population Estimates Estimated deer population size was 6,782 with 90% CL of 4,285 to 9,279 for Colorado quadrats assuming 100% sightability of deer (Table 3). Reduced sampling in strata 10, 11, and 13 (Table 1) likely contributed to increasing variability resulting in wide CI of.:!:.36% of the mean estimate. Additionally, deer also became more concentrated in their distribution after the 'sampling frame flight of 6 February due to increasing snow depths at upper elevation limits of winter range. This shift in deer distribution contributed markedly to not detecting deer on 66% of the quadrats. Using a 100% Idaho sightability model for deer, a point estimate of population size was 6,481 (Table 5). Colorado and Idhao 100% sightability population estimates would have been equivalent except the Idaho estimate was based only on 10 strata (strata 1 and 2 were combined, Tables 1, 4) instead of 11 Colorado strata due to limitations of program Aerial Survey©. Estimated deer population size was 11,052 with 90% CL of 7,549 t014,555 for Colorado quadrats corrected for the Idaho sightability mule deer model (Table 4). Confidence intervals represented+ 32% of the mean estimate. Idaho sightability increased the standard Colorado quadrat estimate by 1.63x resulting in population estimates tending to be statistically different (z 1.63, P 0.103). Within individual strata, sightability increased estimates by 1.37 to 6.26x (Table 4). The highest correction 6.26x occurred in strata 11-MDL and should be viewed cautiously and may reflect the sensitivity of sightability correction factors to low counts of deer on few sample units (Table 3). = = �126 The considerable increase in estimated population size due to sightability corrections reflected that 62% of the deer groups contained ~ 5 deer, 34% of the groups were in pinyon-juniper vegetation and 66% were in sagebrush-type vegetation, and 82% were detected in areas having low and broken snow cover on the ground (Table 2). In essence, many groups of deer were associated with a factor that decreased the sightability, or probability of detecting a group. Model Population Estimates Computer modeled point estimates of population size for post-season deer populations in 2000 ranged from 7,000 to 7,312 deer. Modeled estimates were similar in magnitude to aerial survey estimates and were within or nearly within the confidence intervals of all aerial survey estimates of population size. Modeled and aerial survey estimates were substantially larger than the population estimate promoted by sportsmen (Table 5). Flight Survey Variables Search times on quadrats were acceptable and comparable to previous surveys in Colorado. Flight crews spent 20.2 .:t. 1.1 (SE, n 38) and 6.4 .:t. 0.2 (SE, n 105) minutes on t-rnf and 0.25-mi2 quadrats, respectively. Search times were relatively proportional to total area searched. Wind and lighting conditions were conducive to effectively searching quadrats. Low percent snow cover or broken snow ground cover on many quadrats reduced the probability of detecting deer and made observers more dependent on deer movement to detect groups (Table 2). Compared to the Hiller, flight crews in the Ranger collectively had reduced visibility primarily because the navigator seated in the rear seat had a limited scanning view and could not as effectively help the primary observer detect or count deer. We would expect counts from the Ranger to be more negatively biased than from the Hiller (pers. comm. J. W. Unsworth). Conversely, the 200-shaft horsepower advantage of the Ranger allowed effective slow and low flying in steep and variable terrain. = = DISCUSSION We conducted an aerial survey in response to demands by sportsmen who strongly believed that methods used to estimate numbers of mule deer over-estimated deer numbers in Colorado. Resulting survey estimates of deer numbers, whether based on the Colorado quadrat system (Gill 1969, Kufeld 1980, Bartmann 1983, Bartmann et al. 1986) or quadrats adjusted for the Idaho mule deer sightablilty model (Unsworth et al. 1994), strongly indicated that sportsmen's estimates of deer numbers were substantially below likely true population size. Furthermore, aerial survey estimates supported population estimates derived in computer population models, and as such, supported the concept that models can provide reasonable estimates of population size to adequately guide decisions for managing mule deer. Colorado quadrats, as expected, provided lower estimates of deer numbers (6,782) than quadrats corrected for sightabiltiy factors (11,052). The Idaho mule deer model (Unsworth et al. 1994) increased estimates by 1.63x compared to the correction factor of 1.51 x developed for deer in pinyon-juniper habitats in Colorado (Bartmann et al. 1986). We are confident that Colorado quadrats, without sightability corrections, will provide conservative estimates of deer numbers when' proper and adequate sampling procedures and flight protocols are followed. Although applying a calibrated correction factor (Bartmann et al. 1986) would improve accuracy of population estimates, we question whether higher estimates would be more palatable to some sportsmen's groups. We fully recognize the limitations of our population estimates generated from this validation exercise. Our estimates were of low precision for which there a 2 primary reasons. Our efforts to estimate a sampling frame were based on only 1 aerial survey conducted quickly in response to time constraints invoked by pressure to obtain a population estimate. Normally, quadrat sampling frames are determined with several years of deer distribution data obtained when winter snow conditions would optimize counting deer. In Colorado, quadrat surveys would normally be flown in January when deer distribution and snow cover tend to be stable. In our specific case, major shifts in distribution of deer occurred after the distribution flight and prior to conducting the survey reducing the effectiveness of our sampling allocations. We then reduced sampling intensity in 3 strata to complete the survey with impending unfavorable weather conditions. �127 Observations also suggested that some deer moved off or outside of the frame which would inherently lower estimates of population size. Appropriateness of applying sightability correction factors developed in Idaho for Colorado deer in different habitats can be argued and therefore, the legitimacy of the resulting higher estimates may elicit even less confidence from concerned sportsmen. We foresee worthwhile potential research efforts emanating from this survey effort. Colorado and Idaho both use stratified random sampling procedures in their respective survey systems. However, Idaho often uses sampling units or quadrats having search areas> 3-mi2 while Colorado uses quadrats .:::.t-rnf'. Cooperative experiments designed to compare effects of sample unit size on population estimates and precision, especially if simultaneously compared against robust mark-resight estimators (Bartmann et al. 1987, Neal et al. 1993, Bowden and Kufeld 1995), may provide valuable insight into designing more efficient aerial survey systems. We believe lessons from this exercise apply more appropriately to human dimension rather than biological issues. Sportsmen demanded a validation process of aerial survey protocols based on their perceptions of deer numbers and not on technical demerits of the survey system in use or reasonably obtained estimates of deer population size. Such demands were not tempered by discussions between CDOW and sportsmen over several months that attempted to resolve mistrust by explaining population estimation procedures, limitations, and likely biases. The result was CDOW spending approximately $50,000 in operating and personnel expenses to estimate numbers of deer in a management unit having low priority for spending limited deer inventory resources. We suspect that our survey exercise minimally mediated concerns of some sportsmen. MANAGEMENT IMPLICATIONS Sportsmen challenged estimates of mule deer populations provided by CDOW and demanded a validation exercise to compare sportsmen's estimates of deer numbers in a specific population with estimates on record with CDOW. Subsequent aerial surveys conducted with sportsmen approval and independent oversight provided deer population estimates that substantiated previous CDOW estimates and that were at least 4x greater than the estimate provided by sportsmen. We interpret this validation exercise as a forerunner of the public's interest in either challenging or understanding methods used to estimate status of ungulate populations. We can only caution that if estimates of population status are part of a routine management process, that estimates should be based on tested methodology that can withstand public scrutiny. ACKNOWLEDGMENTS This project was funded by Colorado Division of Wildlife Federal Aid in Wildlife Restoration Project W153-R, Colorado Wildlife Commission game cash funds, and Colorado Mule Deer Association. We thank R. Kahn, R. Velarde, G. Miller, T. Wygant, and F. Pusateri and their staffs of Colorado Division of Wildlife for project support. We also thank Idaho Department of Fish and Game for allowing the cooperative efforts of J. W. Unsworth. We thank New Air Aviation and Dynamic Aviation for providing survey helicopters. This paper dedicated in memory of M. W. Gratson who contributed significantly to developing helicopter sightability correction protocols for aerial surveys in Idaho. �128 Table 1. Characteristics of sampling strata for estimating mule deer population size in Rangely Deer Anal~sis Unit 0-6, Colorado, Februa~-March 2001. Total Area2 Area3 Sample Stratal Density Strata PJ Open Unit Quadrat Sample" Sampled" Units Quadrats Quadrats Strata Name No. Rank Mi2 Size Mi2 {%} {%} Yampa Monument 1 Low 28.74 66 34 0.25 115 9 9 Medium 30.40 41 0.25 122 Yampa Monument 2 59 15 15 Low 31.64 10 1.00 32 Utah White River 3 90 5 5 Utah White River Medium 22.75 35 65 1.00 23 4 8 8 High 54.16 78 22 0.25 217 41 41 Upper White River 5 Medium 30.96 40 60 1.00 31 10 10 Upper White River 6 Upper White River Low 31.96 20 80 1.00 32 5 7 5 44.09 31 0.25 176 22 15 Massadona Dinosaur 10 Medium 69 20.07 38 0.25 80 Massadona Dinosaur 11 Low 62 6 1 40.46 46 0.25 Massadona Dinosaur 13 High 54 162 31 21 Twelvemile Medium 28.93 47 53 1.00 29 10 10 12 364.15 1018 Totals 11 161 143 "Strata numbered 8 and 9 did not exist; there were 11 total strata. 2Percent of strata area having pinyon-juniper canopy vegetation types. 'Percent of strata area in sagebrush or low brush vegetation types. 4Number of sample quadrat units assigned to each strata based on optimum allocation formulas. 5Represents number of sample quadrat units actually flown. Quadrats flown in strata 10, 11, and 13 were reduced by random selection to allow completion of aerial survey considering impending weather conditions. Table 2. Summary of aerial survey characteristics February-March 2001. Survey Characteristic for Rangely Deer Analysis Unit 0-6, Colorado, Data Summary Aerial Survey Flight Dates Total Sample Quadrats Flown Search Minutes Per Quadrat Observers for Counting Deer Navigators for Counting Deer Flight Wind Speed on Quadrats Flight Lighting on Quadrats Snow Cover on Quadrats Time Period Quadrats Flown 28 February - 5 March 2001; about 35 hours of helicopter flight time. 143; 38 sized t-rnr': 105 sized 0.25-mi2; 129 flown by Ranger (90%), 14 flown by Hiller (10%) 1-mi2 quadrats = 20.2 .±.1.1 (SE); 0.25-mi2 quadrats = 6.4 .±.0.2 (SE) deVergie = 112 quadrats (78%), Graham = 14 (10%), Ellenberger = 17 (12%) Freddy = 82 quadrats (57%), Bickle = 30 (21%), Graham = 17 (12%), Howard = 14 (10%) Low = 136 (95%), Moderate = 7 (5%), High = 0 (0%) Bright sunshine = 92 (64%), Dull sunshine = 7 (5%), Hazy sunshine = 44 (31%) Fresh snow = 4 (3%), Old snow = 139 (97%) 7 AM - 12 PM = 65 (45%), 12PM - 5PM = 78 (55%) Total Deer Counted on Quadrats Total Deer Groups Detected Deer Group Size by Quadrat Size Frequency of Group Sizes Group Size by Vegetation Class Group Size by Helicopter Type 1,180 seen on 48 of 143 sample quadrats 179; Average group size = 6.6 .±.0.6 (SE), range = 1 - 58 On t-rnf quadrats = 6.2.±. 0.6 (SE) (n = 94); On 0.25-mi2 quadrats = 7.1 .±.1.0 (SE) (n = 85) (1, n=27, 15%), (2, n=25, 14%), (3-5, n=59, 33%), (6-9, n=36, 20%), (10-19, n=22, 12%), (20-58, n=1b, 6%) In sagebrush = 7.2 .±.0.7 (SE) (n = 118), In pinyon-juniper = 5.4 .±.0.9 (SE) (n = 61) In Ranger = 7.0.±. 0.8 (SE)(n = 127), In Hiller = 5.6.±. 0.6 (SE) (n = 52) Deer Group Behavior at Detection Deer Group Vegetation Type Deer Group Snow Cover 123 (69%) Moving; 55 (31%) Standing; 1 «1%) Bedded 118 (66%) sagebrush-type; 61 (34%) pinyon-juniper; (0%) agriculture/meadows 146 (82%) low snow cover; 33 (18%) high snow cover Total Elk Counted 1,297 approximately; seen on 32 of 143 sample quadrats �129 Table 3. Summary for stratified random sample of mule deer counted Rangely Deer Analysis Unit 0-6, Colorado, February-March 2001. Strata Number With Abbreviated 2 3 4 UWLUWM Summary Statistics YML YMM Quadrat Sampled Units (uh) Deer Counted Per Stratum(Nh) 9 114 15 11 0.73 3 89 2156 0.25 9137 1.00 122 30 11 73 32 32 2 40 Mean Deer Per Quadrat (N, ba,) 12.67 Quadrat Unit Variance (S2Nh) 1116 Estimated Deer Per Stratum (N\) 1456 Stratum Variance (VarA)(N\) 1510126 Stratum Quadrat Size (Mi2). 0.25 Total Stratum Quadrat Units (Uh) 115 Stratum Area ( Mi2) 29 Quadrats With 0 Deer Counted 7 Percent Quadrats With 0 Deer 78 Total Deer Counted All Strata (sum Nh) Total Estimated Deer All Strata (sum N\) Total Variance All Strata (sum Var"[NAJ) Coefficient of Variation CVA(NA)% 90% Confidence Interval for NA[Lower][Upper] 95% Confidence Interval for NA[Lower][Upper] 5 31 6.20 54 196 8 66 8.25 181 188 7607 1.00 23 23 5 63 1,180 6,782 2,318,031 22.45 4,285 3,798 on sample 6 WRM 7 WRL 41 322 10 178 17.80 957 551 62121 1.00 31 31 4 40 5 112 22.40 198905 0.25 217 54 27 66 9,279 9,766 in Name and Density Ranking 5 WRH 7.85 214 1702 unit quadrats 760 716 131021 1.00 32 32 1 20 10 11 MDL MOM 15 10 0.67 7 118 12645 0.25 176 44 14 93 4 9 2.25 20 181 31002 0.25 80 20 3 75 13 MDH 21 133 6.33 274 1025 297438 0.25 162 40 15 71 Estimator Numbers of Mule Deer Estimated in Each Strata Numbered with Names Abbreviated 2 11 13 12 1 3 4 5 6 7 10 MDH YML YMM UWL UWM WRH WRM WRL MOM MDL TMM Colorado Quadrats Sightability Corrected Sightability Increase 1456 14221 0.92 196 293 1.49 188 375 1.99 1702 3183 1.87 Idaho Sightability Estimate Summary Statistics Total Deer Counted All Strata (sum Nh) Total Estimated Deer All Strata (sum NAJ Total Variance All Strata (sum VarA[N\]) 1,180 11,052 4,534,872 Coefficient of Variation CV"(NA) % 90% Confidence Interval for N" [Lower][Upper] 19.27 7,549 10 194 19.40 1020 561 55874 1.00 29 29 6 60 :!: 36% of Population Estimate :!: 44% of Population Estimate Table 4. Estimates of mule deer numbers in individual strata compared between Colorado quadrat quadrats corrected for Idaho mule deer sightability model and Idaho sightability estimate summary statistics for Rangely deer Analysis Unit 0-6, Colorado, February-March 2001. 89 12 TMM 551 851 1.54 716 1397 1.95 118 154 1.31 181 1133 6.26 Due to Sampling (4,365,014), (149,173), Model (20,685) 14,555 1025 1403 1.37 561 841 1.50 Sightability .:!: 32% of Population Estimate "Siqhtability corrected estimate based on pooling strata 1 and 2 resulting in no estimate for strata 2-YMM. and All Total 6,782 11,052 1.63 �130 Table 5. Summary of computer modeled, aerial helicopter survey, and sportsmen estimates of December post-hunting season mule deer population size in Rangely Deer Analysis Unit 0-6, Colorado, 1990 - 2001. Year 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2000 2000 2001 Computer' Model 8,017 8,016 7,563 7,917 9,141 9,171 8,409 7,801 7,856 8,176 7,312 Computer Model Aerial Survey 90 Percent Confidence Interval 21,6305 13,5965 9.309 - 33,951 8,169 - 19,023 6,7826 6,4817 11,0528 4,285 - 9,279 Sportsman Estimate" 1,750 7,549 - 14,555 6,9892 'Computer model constructed in February 2001 with POP-II software (Bartholow 2000) . 2Estimate represents a value projected for December 2001 given assumptions about likely deer recruitment and harvest June to December 2001. 3Computer model constructed in February 2000 with POP-II software (Bartholow 2000). 'Estimate represented a value projected for December 2000 given assumptions about likely deer recruitment and harvest June to December 2000. Estimate represents value contested by Colorado Mule Deer Association. 5Estimate from helicopter line transects (White et al. 1989) conducted on a trial basis. 6Estimate from Colorado helicopter quadrat survey technique assuming 100% deer sightability. 7Estimate from Colorado helicopter quadrat survey technique assuming 100% Idaho mule deer sightability model (Unsworth et al. 1994). 8Estimate from Colorado helicopter quadrat survey technique adjusted for Idaho mule deer sightability sightability correction factors (Unsworth et al. 1994). 9Estimate provided by Colorado Mule Deer Association on behalf of sportsmen. model incorporating �131 LITERATURE CITED Ackerman, B. B. 1988. Visibility bias of mule deer aerial census procedures in southeast Idaho. Dissertation, University of Idaho, Moscow, Idaho USA Anderson, C.R., Jr., and F. G. Lindzey. 1996. A sightability model for moose developed from helicopter surveys. Wildlife Society Bulletin 24:247-259. Anderson, C.R., Jr., D. S. Moody, B. L. Smith, F. G. Lindzey, and R. P. Lanka. 1998. Development and evaluation of sightability models for summer elk surveys. Journal of Wildlife Management 62:1055-1066. Bartholow, J. 2000. Pop-II for Windows©, version 1.0. Fossil Creek software. Fort Collins, CO USA Bartmann, R.M. 1983. Appraisal of a quadrat census for mule deer in pinyon-juniper vegetation. Colorado Division of Wildlife Game Information Leaflet 109. Colorado Division of Wildlife, Fort Collins, CO USA Bartmann, R.M. 2000. Colorado mule deer population monitoring system procedures, user's manual. Colorado Division of Wildlife, Fort Collins, CO USA Bartmann, R.M., L.H. Carpenter, R.A. Garrott, and D.C. Bowden. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. Bartmann, R.M., G.C. White, L.H. Carpenter, and R.A. Garrott. 1987. Aerial mark-recapture estimates of confined mule deer in pinyon-juniper woodland. Journal of Wildlife Management 51 :41-46. Bowden, D.C., and R.C. Kufeld. 1995. Generalized mark-sight population size estimation applied to Colorado moose. Journal of Wildlife Management 59:840-851. . Bowden, D.C., G.C. White, and R.M. Bartmann. 2000. Optimal allocation of sampling effort for monitoring a harvested mule deer population. Journal of Wildlife Management 64: 1013-1 024. Caughley, G. 1974. Bias in aerial survey. Journal of Wildlife Management 38:921-933. Cogan, R.D., and D.R. Diefenbach. 1998. Effect of undercounting and model selection on a sightabilityadjustment estimator for elk. Journal of Wildlife Management 62:269-279. Colorado Division of Wildlife. 1991. POPII simulation model, DEAMAN database manager, and POPMOD parameter estimation workshop manual. Colorado Division of Wildlife. Fort Collins, CO USA Colorado Division of Wildlife. 2001. WRIS database. Colorado Division of Wildlife, Grand Junction, CO,USA Freddy, D.J. 1994. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Game Research Report. July: 27-42. Colorado Division of Wildlife, Fort Collins, CO USA Freddy, D.J. 1998. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Game Research Report. July: 177-206. Colorado Division of Wildlife, Fort Collins, CO USA Gill, R. B. 1969. A quadrat count system for estimating game populations. Colorado Game, Fish, and Parks Game Information Leaflet 76. Colorado Division of Wildlife, Fort Collins, CO USA Gill, R.B., L.H. Carpenter, and D.C. Bowden. 1983. Monitoring large animal populations: the Colorado experience. Transactions North American Wildlife Conference 48:330-341. Kufeld, R.C., J.H. Olterman, and D.C. Bowden. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. Neal, AK., G.C. White, R.B. Gill, D.F. Reed, and J.H. Olterman. 1993. Evaluation of mark-resight model assumptions for estimating mountain sheep numbers. Journal of Wildlife Management 57:436-450. Otten, M. R. M., J. B. Haufler, S. R. Winterstein, and L. C. Bender. 1993. An aerial censusing procedure for elk in Michigan. Wildlife Society Bulletin 21 :73-80. Pojar, T.M., D.C. Bowden, and R.B. Gill. 1995. Aerial counting experiments to estimate pronghorn density and herd structure. Journal of Wildlife Management 59: 117 -128. Samuel, M.D., E.O. Garton, M.W. Schlegel, and R.G. Carson. 1987. Visibility bias during serial sruveys of elk in northcentral Idaho. Journal of Wildlife Management 51 :622-630. Schrupp, D.L., W.A. Reiners, T.G. Thompson, L.E. O'Brien, J.A. Kindler, M.B. Wunder, J.F. Lowsky, J.C. Buoy, L. Satcowitz, AL. Cade, J.D. Stark, K.L. Driese, T.W. Owens, S.J. Russo, and F. D'Erchia. 2000. Colorado Gap Analysis Program: A geographic approach to planning for biological diversity- Final Report. USGS Biological Resources Division, Gap analysis Program and Colorado Division of Wildlife, Denver, CO USA. �132 Steinert, S.F., H.D. Riffel, and G.C. white. 1994. Comparison of big game harvest estimates from check station and telephone surveys. Journal of Wildlife Management 57:336-341. Steinhorst, RK, and M.D. Samuel. 1989. Sightability adjustment methods for aerial surveys of wildlife populations. Biometrics 45:415-425. Thompson, W.L., G.C. White, and C. Gowan. 1998. Monitoring vertebrate populations. Academic Press, Inc., San Diego, California, USA. Unsworth, J.W., L. Kuck, and E.O. Garton. 1990. Elk sightability model validation at the National Bison Range, Montana. Wildlife Society Bulletin. 18:113-115. Unsworth, J.W., FA Leban, D.J. Leptich, E.O. Garton, and P. Zager. 1994. Aerial survey: user's manual, with practical tips for designing and conducting aerial big game surveys. Idaho Department of Fish and Game, Boise, 10 USA. White, G.C., and RM. Bartmann. 1998. Mule deer management-what should be monitored? Pages 104-118 in J.C. deVos, Jr., editor. Proceedings of the 1997 deer/elk workshop, Rio Rico, Arizona. Arizona Game and Fish Department, Phoenix, Arizona, USA. White, G.C., RA Garrott, RM. Bartmann, L.H. Carpenter, and A.W. Alldredge. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Managemetn 51 :852-859. White, G.C., RM. Bartmann, L.H. Carpenter, and RA Garrott. 1989. Evaluation of aerial line transects for estimating mule deer densities. Journal of Wildlife Management 53:625-635. ��•..... ..,. VJ ------+-------+----------- CALCULATIONS FO-lrf6h.1.=fr~~~~~ SAMPL~ QUADRATS AN~-S~~LE SIZES FOR ElcH STATUM ;----"-"-SAMPLE SIZES BASED ON FORMULAS ON PAGES-341 AND 342 FOR STRATIFIED RANDOM SAMPLING jjiFTRoMPSON, W.L., G.C. WHITE, AND C:-GOWAN. 1998. MONITORING VERTEBRATEPClFiuIATioNS:-ACliDENIiC PRESS, INC. ,SAN ---r--··---r---------- ----- I__ :DiEGO, CALIFORNIA, US4:- I SAMPL~ SIZE tACCtIATlk:J;~-~J ESTIMATES JVARIA_~~_g§_~~~T~!.1~Q-_~:~~:-:r;~----- E..NCOM~A.??g!:?._.!_1_~ijjLESA:n31% , MEDIUM DENS.!I,!,_!.!?.?_r~"ILES'2 (~3%) ~'!?JJLqHbENSTW94MiI.~A2 ._ ___ i __L_. . , .. -- .L 1· .. (26%). _.___ - ..-...- --- f------ -I _ GUESSED DEER DENSITY/MI 2 f STRATA - - --E;-STIMATEDVARIANCI3S (S) PER SAMPLE UNITSIZEPERREilliVe ==~==].Oo6 T9I6~[)_~.E..~ _ 1.5 -., --. --5--1--16_~~ .=-:--1895 4 11 i 21 :~~~+~i~~ ~~~~~ ~~--+--!~ ~=:==t 4153 I L _~ ~_~~±~ I ----1:Q~-T_ 5.2i -_:=;'::-__~_-5:06 i:~ ~ 7.99 i 6.63 i ~Q~ 15.62 ~ 636 __~}§ ...1.... _ I I ~l---'-""'-" ' I .---1------~---- ;:~~-..--- -'1~'~6- t- H~ -I·-~~:~~J ~~:~~ I I j DENSITY__ i t -----f- ----- - .. . _I i LOW DENSITY T MEDIUM DENSITY I HIGH DENSITY 1/4 ~1~2 UNIT 11 Mlh2 UNIT 11/4..Mi"2UNTTiTii.i1l'-2-UNTT-:_~f1/i ~!A2 UNIJU t'ilfTUNlr-; __ . I i --~-;:~--~~-..--=~---+- -=t-------~~~~ L.._ _ ' A HIGH IPROJECTED 94 MIA2 :P<?PU~:rION_ _ ,______ --~=---==f----~--~~i - -- MEDIUM 157 MI'2 .. ~~-I:---1 - -~- TVALUES IN TABLE A~E L1NKEDtND USED IN CALCULATIONS O~_t:J_~_Tl'_~(_3[-§ LOW IF TRUE P~~.~;~~-~--]~f13-Mf;;2 _._ -f- -------=+_ __. i__ _• ~.-__-__ -__-__-__-__-_-_-. I -- 1I ,, T_:_ _.._.4000TOTAL DEER --I ---------.+ - --__l:-~---..:.::..::::_- ___ ___ I ESTIMATED DEER DENSITIES BELOW ENCOMPASS RANGES OF DENSITIES SEEN ON PINYON-JUNIPER WINTER RANGES SAMPLED WITH QUADRAT SAMPLE UNITS IN COLORADO. -VALUES ALLOW ADJUSTMENTS IN SAMPLE SIZE CALCULATiONS BASED ON BE~T ESTI~TES OfVARIANCES(S),ASSociATED WITH D!FFEREtJlEXPE_CTED DEER bEriisITIES-AND 2DiFFERENi .§_I~EJ:)S~~l,_g..!!NITS. DENISITESON.1~_~!~_2UN!ISEQUALDENSITYPERMI'2/4. I i -- - --- ----.--+------ i --- -ESTIMATED SAMPLgY.~~I~t'!gE_$_EQB_§IB.AT6:~~SE-D~~REGRESSTON OFVARIA_NCE ST:N~~~~-~~~TION (Sf ---------9.~_~_f¥.'.H_Qg_5.~Q§!':!.sITY FOR 1192 QUADRAT DEER SAMPLE UNITS PREVIOUSLY FLOWN IN COLq_RADO. I ANALYSIS CONDUCTED BY G.C. WHITE. STRATA VARIANCE TO MEAN REGRESSION WAS S = 3.638 + 1.089 (MEAN DENSITY). ~§_E j_-·------l--· - ! 14._~~ 26.51 -- -- -I i -------- .. L __ _ __ : :---- i"-=~== ~ .._ ~~:~~-+-----t-----·-·_-----·1 ..... ·---- ---=t-·--:--t----l �\. ~.~~s~~1~~l~~~~~_;~~~TB·t~lT~-X¥~BNV1~1~~~Wt§.~~~P~~~ PoPS·i·~e;4ooo········ _ ..~. I (~~~~;;' ~_ i (~~~~~)- :l~i:~i'-_j~i~~H~~u"J-fJ~ l;~ ~~~ -'-"-"'"1"67-·--.--~.~~ ···---·-}~~~t-·····-·~~~l·..- -~~~. ~i~ ~~~I ----¥s; '4012 !!~ .-!~. ··-·····i~iii--·-.-.~Hif-·····-·-·-···i~!!~ ··--·"2!ff ~!~.~!~!!! . -_..-p~],~~~~~~; ~~ ~;~~; '-!f~!~:!f~~~~·t=~~··-· ENT UTAH-WHITE RIVER! ~ 3 . UPPERWHITE RivER" .-- '7-' M~g~M 1 LOW 1 32 32 ..- ···········-··~~7 I MASADONA·DINO MASADONA-DTNO-··-.TWELVEMILE MA!3.~q(?~~::!?INO TOTALS SUMS LOW 32 10 MEDIUM 44 11 LOW 20 -.----r.-;-;=--.-12 ....!J1ED~IJ~_. 29 13 HIGH 40 ..-.-- 11 --..··1018·-·· ._,__ ('--~. 32 176 80 29 162 POQSlje = 6000.:=~~=t=~=~~~~·::~~_. 879; 2531 2022 "-88S"25Sr·--·---·:2042· ·siiz--··-44071----···-···TI70i 7758 . 325 1314; 263 _?~§ZL._ .__ .-- ..-.---J9.~----6~1----.--~~~.-- - ., _- 5773 34540, - 379 1794 ..----~?2_1__ 7056 ..... 1.1)~?. 8035! - -~!~:!-.. 2636! 360 4052 11269, 165015434 20061 445 --- 2467 ·····-······--I········---·------·-· 12835 767 20329 23609~ 2395 35452 -'1'0247 ·-····-12163Sl 70268 1~~~~1 290 1410 -401 -609 1955 1~~~ 1'68 ...- 1~;~ 356 287 -·'12378 -'1811121 ~~-----=+==~--- -+-~~ ----:---:- ...._---- -~-~~~-== I-----·---··-····· ·r····· .: -- ... --_.- ..~..__._.__+.__ =====.=~~.r-.------r-. ._ --I--==:==r:::-~-=----+·· ..-~.T-I'-' .-1---- __ . .. . ' __ _._._ .._ ... .IQTA!"§SQUARED I 1 ~~.~~.~~1_1_ ..__. ._1 SA~JfpDrSIZE FORMULA FROM COCHRAN 1977 AND PAGE 341 THOMPSON ET AL. 1998 Toto'S.m," LQuadrat Units (u) = ~ I-------------[sum," ,(U•• 8,,)f_L __ ._~ •••••••• -.--- ••-------(eN/I)A2+ [.U~ (U.'8',.,» .__ ~1E~~~±1+ _. --..... .._._._.. . 105006872 i .---- , 163217028 1 _ I . t;=- ..-~~: ··-i-~-4~A~=f=t~-~-.-$--i_ =,-~-i-t 1 _ . I 1 -w Vl �W 0\ E~~~A~F--=--~=i~ - -___§'__ _ ---'~-~:l----m_:::~_-{_:_~~_-~~ I I --f------- -.-+---. ---1-_ - -l~::-::------ _=----------~t----------1T::~-=::==+=-= ~~~~~~~T~~~~~~~J~~~~s~f~~i~'!~~~ ~~I;;~g~~/~~:~ 9f_~~N f~~-.-=_~_'__ := ~~1p.'l'!!._=o.10.t=1.645df>12o __ . . ",T AIPha-=-:==~.Q~ct_::1.96 df>,120 1------- -- . .._... 1 ] -..; .••.• _._ .._.__ - L __ .. m~ 1-_ I .__ _J_ ----=L:: "'-'-"-' .---.-------.. ,-.-.f---, .---- , -------.~..... _.~-.I.._..... 1----------1 --_ I 1---- -.---.---...... .. _ I ------,-.------:---- -------, -----,-----=E..---:~~----.-J---f--A---- --, -----. -:-:--~-_ .--~-~=-! .. .. - _1 ----~---~_.:.: ; -- _ --j'- -- �CA[cULAfiNG~iUMBERhS~~~~rU~~S~~~INDI~ID~A~S~RATA···r~=--==·····I·:_- . r _nnn; ---.- ---f------.-.- - ----:- ~i,~~~tw~~*~~~~~::~~,,~~~Q~sf---~--~--:-:: ~:k--~ T~-==_="=:_ -==t_~--=~==._ ===_~~~r~==-_:__~:::: "1'·· - _un COSTTOFLY1/4MI"2QUADRAT INPINY6NJmfiPERVEGETATT6NABT20"MTNU'fESOn'iECfC~~_T1M~=~~L T StrataTest -+j ---1 SumColumnGi ---------f:-S-'T-RA-T-A-;iD-E-N-S-"I-TY-+-ror;""d-ToTALTU) r---7Uh-:s;;;;)t-SAMPLE % UNITS : % AREAMI"2 AREAMI"2 ··-----AREA-----·--1GiSNo:iiiir·RANK--, MILE"2'SAMPLEUNITSI VALUE i UNITS 'SAMPLED! SAMPLED ! FLOWN ~~~~~:~g~~~~~~ L--~--h1{g~M+' -~---H-}--+----~~;i ~~-=~===-==~~~I~::~=-------- ~; ----T~~------·1*_·--------1~:~~·------~ .--.------UTAH-WHITE RIVER 3 i LOW: 32 32 2871 5j --·-··-141·---·----14.3+--------5 .-. .-------·-----51---t·--·OTARN~jHITln~iVEfC·---T·-·l·MEDI OM··r········ i3--_J_-~3---··{----------479 i ------81- -- -..- - 331·················-33:1[·····- -·························8 ·······-·······-81·········-·····-··_······, UPPERWHITERIVER' 5 j HIGHi'--s4---217---r·-·--~7!-···----· ~~ l~.j _1.~~-----.---_~.9_.__ _._._.__ _._ ...i!. .. _ ~~~~~ ~~:~~~:~~~f-··~+·~fg~M·I····-···~}·--· -----~~-··-----·f····--..--·-..·--~~I· ..-··... ············-!~j-···-------·f~I-----·-·-iN+·-··-··--·········_1..~ ..··-···_··-·-_·-..-·--1· ~~~~~~~~-~!~~~~ 'M~g~Mi ~6 I ~06 1:6~1· 2~1----.---.-ll~--·--·-1¥~~f_-··-¥----·······1 1~ :.:.:~------- r ~.- MEDIUM""29! --·M~§AQ_Q[A~I5LB:Q=·~~iL _ __t!L~-+_. 40: TOTALSUMS 11 +~~4·149f 29---T 162 __ I 1018 .._!.__ __" "--~-----.l-- ...--1-------- 609T-19551 10i 31: ..1~ill__."._2.~_!J _ 33 19 33.1! 19.~ 10,' ~+-_ 10 31 : '---J~---:-.~:. --'--l---~-'~:::~~t:=~::::~~:::~::~~~-J==---===:J:~~+..------I .__._._162I=actualsum i INOTE:Duet~~a_t_h.erconpromisingabilityto completenecessary flx!ngof units on March3 and 4,2001, numberof sample UI:!its ' --_.-' i ._.._ 1 __ _ _._ _ L ~:;_~;:~Z=S~f1~!~~=~~~~;;,~-f:--···--·-··· =~=:= t- --------1== ---·---!----======l~=== ~~~lli~j&].r~~1~t.~~;:~:~~~~I,~T~!:~;hb~:~~~::~t!e~~hi~~~;d3c~~I;~M~l~M-!~~a~~'~;~~ia1~~~~~~~~~~!~~aa~~~!l>.---the total flownfor the entire Unit10was 143(ie..161.19did not equal 143 flown). I t I ! i i •.... W -...l �138 2. MODIFICATION OF SAMPLE SIZE DURING PROJECT ~i~~~~~~JE~~~;~~~!~=::f-~I ! DeCisions Made and Tech~ique of Random Subsample completed with V.W.:._Howard approval an9_su art _. . ~~Ie reduction was m?.de to allow completion of a reasonable number of sample units to __ . !_9btai~Cl_r::l_estimate within limited time frame and flyable weather patterns I ..._.._ .~ Used QuattrQ__~ample Tg.9.iRandom function to s""J~ct sUbsamQ.les within each of 3 strata-: . __ _ __ ' '__ J .l j . Howard, Bickle and Freddy discussed PI2fo.1}options for completing the Massadona Unit with reduced sampling_, inclusive of dropping entire strata and/or proportional reduction in samples within : eachof 3 strata. Reducing samples in each strata was considered preferabl~_to droppinq ~!r?ta. I _ . I- .' . --_._ , '--- . ...... '.,. .... . I' ---.-"Howard, Bickle and Freddy also discussed meri!? of doing or not doing the Yampa-Monument Strata under qiven time constraints. Howard thought this was the least priority of strata because 1 .' Sportsmen do not believe deer assbicated with the Monument a part of the· available huntable deer· 1population. However CDOW does include Monument deer in the Unit 10. · i deer population model. At this staqe of discussion Howard and Bickle comfortable with .. --I · !nc;t completinQ the Yampa-Monument strata. .- , ',-1 I I Massadona I High Densi!y Strata; Units Sorted/Ordered by Sample Tool Selection Order Sample Tool Set to assiqn random order to a sample of 31'and took first 21 because duplicate I I ' numbers will g~t assigned so ignored ties due to assiqned numbers I ..• -I ; Original High [Density [ouadrats 20-MDH ··26-MDH 15-MDH 8~MDH 10-MDH , 21-MDH 30-MDH '. 24-MDH · 31-MDH 19-MDH 7-MDH 16-MDH 3-MDH ) 4-MDH 11-MDH . 25-MDH 22-MDH "1"MDH 13-MDH '~:! . ! 9-MDH '::i 29-MDH 17-MDH 12-MDH 23-MDH 14-MDH '.'-~ ';: 1 18-MOH ; 28-MDH I 2-MDH 5-MDH 6-MDH f 27-MDH t- .,'j [ Quads Selection Order First 21 Number Assiqned Selected Numeric Using Quattro Listing By Random Equivalent Sample Tool Order 20. 1 1 26 3 2 3 151 3 .. 5 4 81 10. 5 5 21 6 6 . 730 7 .. 24 9 8 31 9 9 100 11 19 7 14 11 16 15 12 3 16 13 4 16 14 11 16 15 25 18 16 19 22 17 1 21 18 13. 21 19 9. 23 20. I 23 29~ 21 17 23 12 24 ! 25 23 14 26 18 26 --. 27 28 i 27 2 29 5 311 I 2~~ 31 I ~ ..- ! S j i --l I .__1 I ---_._j ! a I, ~.: -i .' .' f . ',' _ .. I i I , •• , I ! i i _. ~ f -+--_.i 1 I ---=1 I -- _'-1 ___ --~ . '-j �139 _____ ~_. •••• __ ••••• H • ••• _. ._. •• , •••••• _--- .• _•• _ •• .................- ~--;. _ _ __ -----:-.-- _._. __ •••• _ •••• _._ ••• ••••••••••• . -1-" ..--.- _ _ _.._ A~~.. ... ...•.•..... _ ..• .1.....•... _ __ •••••••• __ • • __ • __ _--,....-_ _.__. . ••••• _._ •••• •••••• 'M __._.. _·¥··--r···········_ _L __~__. _.•.....•.......... , .._..l _ _ __.__._I_. '.._ .__ .._._ ~.~- L.:.._._ _ _.._ :Massadon<!.JIi!.~_~ium Densi!i'..§J:!:~ta; Units Sorted/Ordt?re<!.!!ySal!!E.leT~ol S~!~~!ion Order l_$.?mpleTool Set to a?~gnI~mdom·order to a sample of 22 and took.Jl~§.~c_~~_q~pl!~9.!~ _, , _ . -·l..····· t~~='~t~=r=~-=~tQ a~ign~_~:~rn~~~ _==~;== . t . ;~~ r~~·----_1_ .. __ .. _[ ._ ....._ ------j--.--~ =~==:~==-- -_·----r:==-~-::::] ~~~~~-~~~I~~~~nA~~~e:ed ~:~~c~!~· ; Density l:!_~!llJg__ j USing Quattro By Random i Quadrats Equl'!.§lent LSar:rJ£!~_.IQ.2.L Order ._ 10-MDM 10 i 1·; 1. iii-MOM 11 i 2 2 . --.--~------ __ . -----~----_l .._.__... _.... __.._._..... ..-:.:_l_____ . .___l ! . I 7-MDM 71 i 20-MDM .._.?_Ol 211 3 4 5 3 ._-----j-_ ... __ ._---_._-_._._._---_._--_ .. _---_._-_ .. _. __ ... _.j 4 -'---+--,- .. - -- .-----+------.:-- ----i, 5 I 14-MDM 141 6. 6· r- 21-MDM 3-MDM I 13-MDM I .. . 31 13 -----~~------+-----~ 8t . 7 .. ---8"+----"--'-8+-------1--.'-'--· i-MOM 9-MDM 1 9 11 10 ~_12-MDM 12 18 17 151 15 17 11 12 ·13 ~;I ~~ I i8-MDM 17-MDM 2;_:g:: i6-MDM 2~ 16 L ~~~ 1~ : i9-MDM 19 ===:=======+-+_..:.. .; ....:.~ .:__ : 8~1r---~--9~·~·------~--~---+~--~4-------~----~ .. 181 ._.-_-]J . JI_:_~~~~j j t ----.-.. -.f-----+-.-. -.-- .__ ---~---~~----+------t . ---~~~~j·------~i~--;_--+------i~---_-_-_~~ __--·~~ 21 1 ~----~-------r---------r------+'----~----~----~---~T----~ I .. I 1 Massadona Low Density Strataj_J!_nitsSorted/Ordered by Sample Tool Selection Order .Sample Tool Set to assign random order to a sample of 6 and took first4 because duplicate numbers will oet asslqned so iqnored ties due to assioned numbers I _j . ] l --·--1! I r=-=-==<-:--+=:'=:-=-:--~=:-=:::==:-=----t-=:.J--'-=-'=':":_f------I-----+---+-'--iL .----1---+-----1------ - -i ---~~ ~~~~+-------~----------~+---------~-----+--~--~------~------+---~ .--.,.--------_+------+------+-----,---+-----1---_+--'-'--.. -.f--------+--------+------------+---------l------_+~-----j-------+_---_+------~ 1--------1---·-- �140 SECTION D 1. D-6, UNIT 10 DEER WINTER RANGE MAP Vegetation Types Within Mule Deer Winter Range in Game Management Unit 10, DAU .0-6, Colorado Vegetation based on Gap Analysis Winter Range Boundaries based on CDOW WRlS Data: Gap Vegetation Types Q Dry Land Crops _ Irrigated Q-ops [2Jj Foothills and Mountains o Mesic.Upland Shrub D Bitterbrush Shrub Big Sagebrush Saltbrush Fats and Flats D Greasewood Fans and Flats' _ JmiperWoodland _ Pinyon -Juniper Shrub Dominated Wetland "f _ A N Game Management Unit 10 COLO 139 2. D-6, UNIT 10 DEER WINTER CONCENTRATION AREA MAP Vegetation Types Within Mule Deer Winter Concentration Areas in Game Management Unit 10, DAU Dc6, Colorado Vegetation based on Gap Analysis Winter Range Boundaries based on CDOW WRIS Data GAP "vegetation Types lirigatedCrop Bitterbrush Shrub Big-Sagebrush Sahbrush Fans and Flats Greasewood Fans 3Dd Flats Juniper W oodlland' Pinyon - Juniper Shrub domio •• ed Wetland N Game ManagementUnit If �141 3. 0-6, UNIT 10 DEER WINTER SEVERE RANGE MAP Vegetation Types Within Mule Deer Severe Winter Range in Game Management Unit 10, DAU D-6, Colorado Vegetation based on Gap Analysis Winter Range Boundaries based on CDOW WRIS Data Gap VegetationTypes Irrigated Crop Bitterbrush Shrub Big Sagebrush Saltbrush.Fais and Flats Greasewood Fans and Flats Juniper Woodland Pinyon - Juniper Shrub Dominated Wetland N Game ManagementUnit 10 �142 SECTION E 1. SAMPLING FRAME AND SAMPLING STRATA MAP Sampling Frame Area, Sampling Strata, Quadrat Sample Units, and Random Sample Unit Points used Helicopter Counts of Mule Deer to Esitmate Population Size in Unit 10, DAU 0-6, Colorado. Grid Shows. Cadastral Sqnare Miles and Subjective Rating of Deer Density Based Upon a Helicopter Survey Flight on 6 February 2001. SamplingStrata and Sample Quadrant Units "y enpa- Monument (Low) Ya:opa ··Monument (Medium) Ilteh. White RiV" (Low) Utall Whit. RiV•• (Medium) Upper Whit. River (High) Upper Whit. River (Medium) Upper White Riv..-(Low) . Massadona - Dine (Medium) Massadona _Dine (Low) 'Iwelvemile (Medium) Massadona- Dino (High) Sample Quadrat Units _ Sample Quadrat Units Not Flown D Cadastral Mil. Grid c.;;:;;] S'I"'= E=c:=i'::· ====,,====,'D • Kilometers Sample Unit Points /\I Galle Management Unit 10 A 2. SAMPLING FRAME AND PRIMARY VEGETATION TYPES Sam piing Frame Area and Distribution of Pinyon Juniper and J.uniper Woodlands Within Strata used for Helicopter Counts of·Mule Deer to Estimate Population Su·e in Unit 10, DAU D-6, Colorado . ·0 .IT2l rumper Woodland ~ Piny'" _rllliiper �143 3. YAMPA MONUMENT STRATA 1 AND 2 MAP Yampa - Monument Sampling Strata Showing Grid of 1/4 Mile Points, Randomly Selected Poin ts, Sample Unit Points, and Quadra t Sam ple Units 1/4 Mile Square in Siae • .Circle 112 Mile in Diameter used to Restrict Distances Between Quadrat Units. Sampling simla and Sample Quadrant Uri.its Yampa. Monument (Low) Yenpa- Monument. (Medium) QUadrat Sample Units . •. Sample Unit·Points •. Randomly.Selected Points • 114Mil. Gridded Points o • 112 mile diameter 4. UTAH WHITE RIVER STRATA 3 AND 4 MAP Utah White River SamplingStrata Showing GrId of1/4 Mile Points, Randomly Selected Points, Sample Unit Points, and Quadrat Sample Units 1 Mile Square in Size. Circle 1 Mile. in Diameter used to Restr-ict Distances Between Quadrat Units. Sampling·Strnta;and Sample Quadrant Units . White River (Low) Utah White River (Medium) QUadrat Sample Units . • Sample Unit Points • Randomly Selected Points 114Mile Gridded Points N Game Management Unit 10 �144 5. UPPER WHITE RIVER STRATA 5, 6, AND 7 MAP Upper White River Sampling Strata Showing Grid of1/4 Mile Points, Randomly Selected Points, Sample Unit Points, and Quadrat Sample Units 1/4 and 1 Mile Square in Size. 'Circle '112and 1 Mile in Diameter used to Restrtct Distances Between Quadrat Units. sampling Strata and Sample Quadrant Uniis _UpperWhiteRiver (High) _UpperWhite River (Medium) Upper White.River (Low) Quadrat Sample Units o Sample Point Location o Randomly.Selected Sample Points 1J4 Square Mile Gridded Points c;:;;;J E===="========C==:::::J" 6. MASSADONA Miles A N'GameManagement UnitlO - DINOSAUR STRATA 10, 11, AND 13 MAP "Massadona - Dinosaur Sampling Strata Showing Grid of 1/4 Mile 'Points, Randomly Selected Points, Sample Unit Points, and Quadrat Sample Units 114 Mile Square in Size. Ctrcle 112 Mile in Diameter used to Restrict Distances Between QuadratUnits. Strata and Sample Quadrant U D~ Massadona.plno (Medium) MassadOna c:Dmo (Low) Mms.Ulooa'Dino (High) Qu~ Sample Units . .. . Qu~.Sample Units NotHoWD o o • Sample Unit 'Points Randomly Selected Points 1/4 Mile Gridded Points N Game ManogemenlUni; 10 �145 7. TWELVEMILE STRATA 12 MAP (Clarification: No strata numbered 8 & 9;11 total strata) Twelveniile Sampling Strata Showing Grid of 1/4 Mile Points, Randomly Selected Points, Sample Unit Points, and Quadrat Sample Units 1 Mile Square in Size. CircleI Mile in Diameter used to Restrict Distances Between Quadrat Units. Sampling Strata end Sample Quadrant Units_ Twelvemile (Medium) EJ Quadrat Sample Units i;;;;;=======0i;;'=======i3 • o Miles A Sample UnitPoints Randomly Selected Points 114 Mile Gridded Points N Game Management Unit 10, �146 SECTION F 1. SURVEY FLIGHT PROTOCOLS PROCEDURES FOR FLYING HELICOPTER SAMPLE QUADRATS GMU 10, DEER POPULATION ESTIMATE FEBRUARY 2001 COLORADO QUADRAT WITH IDAHO SIGHTABILITY CORRECTIONS D.J. FREDDY, MAMMALS RESEARCH, COLO. DIV. WILDLIFE J.W. UNSWORTH, IDAHO DEPT. FISH & GAME (PROVIDED SIGHTABILITY TECHNIQUE SUGGESTIONS) FEBRUARY 8, 2001 I. BACKGROUND INFORMATION: AREAS OCCUPIED BY DEER IN UNIT 10 WERE DELINEATED (364 SQUARE MILES) AND STRATIFIED ACCORDING TO RELATIVE DEER DENSITIES INTO HIGH, MEDIUM, AN LOW STRATA (11 STRATA) BASED ON A HELICOPTER SURVEY FLIGHT CONDUCTED BY V. GRAHAM (CDOW) IN FEBRUARY 6, 2001. THE OCCUPIED DEER RANGE DELINEATED REPRESENTS A CONDENSED PORTION OF THE EXTENSIVE WINTER RANGE AREA DELINEATED IN THE CDOW WRIS INVENTORY SYSTEM BECAUSE SNOW-DEPTHS HAVE CONCENTRATED DEER TO SOME EXTENT. SAMPLE UNITS, OR QUADRATS, WITH AN AREA SIZE OF 1 SQUARE MILE (USED IN OPEN VEGETATION HABITATS) OR 114 SQUARE MILE (USED IN PINYONJUNIPER FORESTED HABITATS) WERE SELECTED AT RANDOM WITHIN EACH STRATUM ACCORDING TO STANDARD STATISTICAL SAMPLING FORMULAS. BOUNDARIES OF ALL SAMPLE UNITS WERE BASED ON TOPOGRAPHIC OR CULTURAL FEATURES. FROM THE STRATIFIED RANDOM SAMPLE OF QUADRATS WE WILL OBTAIN 2 ESTIMATES OF POPULATION SIZE FOR THE 364 SQUARE MILE AREA SAMPLED: 1) AN ESTIMATE BASED ON UNADJUSTED COUNTS OF DEER ON QUADRATS, AND, 2) AN ESTIMATE BASED ON COUNTS. OF DEER ON EACH QUADRAT ADJUSTED FOR SIGHTING OR DETECTION PROBABILITY OF EACH GROUP OF DEER USING A SIGHTING BIAS CORRECTION FACTOR (IDAHO MULE DEER SIGHTABILITY MODEL). II. AIRCRAFT: THE PRIMARY HELICOPTER WILL BE A HILLER 12E SOLOY AND THE SECONDARY HELICOPTER WILL LIKELY BE FRENCH A-STAR OR TWIN-STAR, ALL TURBINE POWERED AIRCRAFT. THE HILLER PROVIDES THE BEST VISIBILITY PLATFORM FOR COUNTING DEER AND WILL BE USED PRIMARILY IN AREAS OF HIGHER DEER DENSITY. FLIGHT CREWS WILL CONSIST OF A PRIMARY OBSERVER, NAVIGATOR, AND PILOT. ALL 3 PERSONS SHOULD SIT ABREAST IN THE HELICOPTER WITH THE NAVIGATOR POSITIONED IN THE MIDDLE. THE HELICOPTER MUST HAVE FUNCTIONING INTERCOM HEADSETS SO THAT ALL 3 MEMBERS CAN READILY COMMUNICATE VOICE INSTRUCTIONS OR INFORMATION. SUNNY AND COOL DAYS WITH GOOD SNOW BACKGROUND AND LOW WIND SPEEDS ARE THE MOST DESIRABLE FLYING AND COUNTING CONDITIONS. HAZY OR FLAT LIGHTING ON OVERCAST DAYS IS ACCEPTABLE, BUT NOT PREFERRED. CREWS SHOULD AVOID PUSHING TO GET WORK ACCOMPLISHED IF THERE ARE CONSTANT SNOW FLURRIES OR WIND SPEEDS THAT NECESSITATE FLYING AT HIGHER SPEEDS AND ELEVATIONS ABOVE THE GROUND. III. SAFETY: HELicOPTERS WILL HAVE A SURVIVAL GEAR BAG FOR SUPPORTING 3 PERSONS, A FUNCTIONING ELT, FIRE EXTINGUISHER, AND PORTABLE PACKSET FOR EMERGENCY COMMUNICATIONS. IT IS RECOMMENDED FLIGHT CREWS PERIODICALLY REPORT THEIR GENERAL LOCATION TO COUNTY SHERIFF DISPATCH VIA HELICOPTER RADIO IF POSSIBLE. FLIGHT CREW MEMBERS ARE ENCOURAGED TO WEAR NOVEX FLIGHT SUITS AND CLOTHING MADE ONLY OF COTTON OR WOOL FIBERS, NO SYNTHETICS. PILOT, NAVIGATOR, AND OBSERVER MUST ALL WORK TOGETHER TO DETECT AND COMMUNICATE THE PRESENCE OF POWER LINES WITHIN THE WORKING AREA. IF BUILDINGS ARE IN THE AREA, ALWAYS ASSUME THAT A POWER LINE IS NEARBY. IF WEATHER CONDITIONS DETERIORATE, CREWS MUST RECOGNIZE THE CHANCE FOR ICING CONDITIONS OR VISIBILITY CONDITIONS THAT CAN GREATLY COMPROMISE SAFETY. PLANNING SHOULD INSURE THAT THE FUEL TRUCK AND DRIVER ARE AT A LOCATION KNOWN TO THE PILOT AND WITHIN 15-20 MINUTES FLIGHT TIME OF THE HELICOPTER'S ANTICIPATED DESTINATION AFTER FLYING FOR 1 HOUR AND 45 MINUTES. �147 IV. PERSONNEL: A. THE PRIMARY OBSERVER SHOULD BE A PERSON EXPERIENCED IN DETECTING AND COUNTING DEER FROM A HELICOPTER, CAPABLE OF CONCENTRATING AND FLYING SEVERAL HOURSIDAY FOR SEVERAL DAYS, CAPABLE OF MAKING RAPID DECISIONS REGARDING GROUP SIZE AND SIGHTABILITY VARIABLES, AND CAPABLE OF ACCURATELY RECORDING DATA ONTO A TAPE RECORDER AND TRANSCRIBING THAT DATA TO DATA FORMS. THE PRIMARY OBSERVER IS PRIMARILY RESPONSIBLE FOR DETECTING GROUPS FORWARD AND TO THE RIGHT OF THE AIRCRAFT AND TOTALLY RESPONSIBLE FOR RECORDING GROUP SIZE AND SIGHTING VARIABLES OF ANY DEER GROUP SEEN. THIS PERSON MUST WORK IN COORDINATION WITH THE NAVIGATOR AND PILOT TO POSITION THE AIRCRAFT AT A FAVORABLE ALTITUDE AND SPEED. THE PRIMARY OBSERVER IS RESPONSIBLE FOR RECORDING ALL DATA PERTINENT TO EACH QUADRAT AND SHOULD REFER TO THE OBSERVER 'CHEAT SHEET' FREQUENTLY TO INSURE THAT PROPER DATA ARE RECORDED. B. THE NAVIGATOR SHOULD BE A PERSON CAPABLE OF NAVIGATING THE HELICOPTER TO THE PROPER LOCATION OF EACH SAMPLE QUADRAT USING LATILONG COORDINATES AND TOPOGRAPHIC MAPS PREPARED FOR EACH QUADRAT. THE NAVIGATOR MUST BE ABLE TO DIRECT THE PILOT TO FLY THE CORRECT BOUNDARY OF THE QUADRAT BASED ON VISUAL INTERPRETATION OF THE TOPOGRAPHIC MAP AND THE TERRAIN OVER WHICH THE HELICOPTER IS FLYING. FURTHERMORE, THE NAVIGATOR IS RESPONSIBLE FOR DIRECTING THE FLIGHT PATH TRAVERSED THROUGH THE QUADRAT TO INSURE PROPER 100% COVERAGE AND COUNTING CONDITIONS. THE NAVIGATOR WORKS IN COORDINATION WITH THE PRIMARY OBSERVER AND THE PILOT. NAVIGATOR ASSISTS THE PRIMARY OBSERVER BY DETECTING GROUPS FORWARD AND TO THE LEFT OF THE AIRCRAFT, AND ASSISTS THE PRIMARY OBSERVER IN KEEPING DIFFERENT GROUPS OF DEER SEPARATE. THE NAVIGATOR SHOULD KEEP A RUNNING TALLY OF DEER COUNTED ON EACH QUADRAT USING A TALLY -WHACKER COUNTING DEVICE. THIS PROVIDES A BASIC BACKUP TO THE TAPE RECORDER OF THE PRIMARY OBSERVER. ALTHOUGH THE OBSERVER AND NAVIGATOR WILL USE THE PRESENCE OF DEER TRACKS IN SNOW AS AN INDICATOR THAT DEER ARE PRESENT, THE NAVIGATOR SHOULD MAKE SURE THAT GROUPS OF DEER ARE NOT ACTUALLY FOUND BY TRACKING DOWN INDIVIDUAL ANIMALS BY FOLLOWING SETS OF TRACKS WITH THE HELICOPTER. SIGHTABILITY MODELS ARE BASED ON VISUAL DETECTION OF ANIMALS, NOT FROM TRACKING. C. THE PILOT'S PRIMARY RESPONSIBILITY IS TO CONCENTRATE ON FLYING THE AIRCRAFT SAFELY AND IN A MANNER THAT SUPPORTS THE PRIMARY OBSERVER. THE PILOT WILL DETECT GROUPS OF DEER NOT SEEN BY THE PRIMARY OBSERVER OR NAVIGATOR. THE PILOT WILL RELAY INFORMATION TO THE NAVIGATOR ON GROUPS HE SEES AND THE OBSERVER AND NAVIGATOR WILL COLLECT THE DATA FOR SUCH GROUPS. V. DATA COLLECTED: A. QUADRAT: AT THE BEGINNING OF EACH QUADRAT SAMPLE UNIT, THE PRIMARY OBSERVER WILL RECORD THE QUADRAT IDENTIFICATION NUMBER, APPROXIMATE LAT/LONG STARTING POINT, GENERAL FLIGHT LIGHT, SNOW, AND WIND COUNTING CONDITIONS, AND CLOCK STARTING ENDING TIME FOR EACH QUADRAT. NAVIGATOR SHOULD ASSIST OBSERVER IN MAKING SURE THIS INFORMATION IS RECORDED. B. DEER: THE PRIMARY OBSERVER WILL COUNT EACH GROUP OF DEER DETECTED AND DETERMINE SIGHTING VARIABLES FOR EACH GROUP, REGARDLESS OF WHO FIRST DETECTS THE GROUP. ON THE TAPE RECORDER THE OBSERVER WILL SAY NEXT OR NEW GROUP OF DEER WHEN EACH GROUP IS DETECTED. THE OBSERVER WILL RECORD THE ACTIVITY OF THE DEER WHO IS MOST ACTIVE WHEN THE GROUP IS FIRST DETECTED, THE VEGETATION TYPE AND RELATIVE PERCENT SNOW COVER IN THE CIRCULAR AREA WITHIN 10 METERS (30 FEET) OF WHERE THE INITIAL DEER WAS DETECTED, AND THE TOTAL NUMBER OF DEER IN EACH GROUP. THESE 4 VARIABLES CONSTITUTE THE IDAHO SIGHTABILITY MODEL INPUT VARIABLES. SIGHTING VARIABLES: 1. DEER ACTIVITY IS EITHER BEDDED, STANDING, OR MOVING. THE ACTIVITY IS RECORDED FOR THE DEER WITHIN THE GROUP THAT IS MOST ACTIVE WHEN THE GROUP IS FIRST DETECTED. A DEER THAT IS GETTING UP FROM A BEDDED POSITION WHEN FIRST DETECTED IS RECORDED AS A STANDING DEER BECAUSE THE MOVEMENT OF THE DEER GETTING UP IS LIKELY WHY THE DEER WAS DETECTED. A DEER MUST REMAIN BEDDED FOR A BRIEF PERIOD AFTER INITIAL DETECTION TO BE RECORDED AS BEDDED. STANDING DEER MUST REMAIN RELATIVELY �148 MOTIONLESS RUNNING. AFTER INITIAL DETECTED, AND MOVING DEER ARE DEER THAT ARE WALKING TO 2. VEGETATION TYPE WILL BE ONE OF SEVERAL CATEGORIES AND OBSERVERS SHOULD DO THEIR BEST TO CLASSIFY VEGETATION PROPERLY TO THE MOST DOMINANT TYPE AT THE LOCATION WHERE GROUP FIRST DETECTED BUT DO NOT SPEND A GREAT DEAL OF TIME TRYING TO DIFFERENTIATE LOW BRUSH VEGETATION TYPES. IN ALL LIKELIHOOD DURING DATA SUMMARIES AND ANALYSES, VEGETATION TYPES WILL BE POOLED INTO LOW BRUSH TYPES VERSUS PINYON AND JUNIPER TYPES. VEGETATION TYPES WERE BASED ON CLASSIFICATIONS USED IN THE GAP DATABASE FOR UNIT 10. VEGETATION TYPES SAGEBRUSH BITTERBRUSH GREASEWOOD FLATS SALTBUSH FLATS PINYON-JUNIPER WOODLAND JUNIPER WOODLAND AGRICULTURAL AND NATURAL CLEARINGS RIPARIAN SHRUB TALL CONIFER SIGHT ABILITY CORRECTIONS FOR VEGETATION TYPES WILL MOST LIKELY BE BASED ON CORRECTION FACTORS DEVELOPED IN IDAHO FOR THEIR VEGETATION CLASSES OF 1) GRASS/OPEN/AGRICULTURE, 2) SAGEBRUSH, 3)JUNIPERIMOUNTAIN MAHOGANY, AND 4), POSSIBLY CONIFER. NO CORRECTION FACTORS HAVE BEEN DIRECTLY DEVELOPED FOR DEER IN OUR PINYON-JUNIPER OR JUNIPER WOODLAND HABITATS SO WE MUST USE IDAHO INFORMATION TO APPROXIMATE OUR VEGETATION CONDITIONS. 3. PERCENT SNOW COVER AT THE LOCATION WHERE EACH GROUP OF DEER IS FIRST DETECTED. SNOW COVER PERCENTAGES WILL BE CLASSIFIED BY THE OBSERVER AS LOW = 079%, AND HIGH >80% OF THE GROUND COVERED BY SNOW. THESE CLASSIFICATIONS MUST BE USED TO BEST MATCH THE IDAHO SIGHTABILITY MODEL. IDAHO DOES HAVE A SNOW COVER CLASSIFICATION OF 0-19% BUT THIS SITUATION APPLIES TO COUNTS OF DEER DURING SPRING-GREENUP WHEN DEER ARE IN LARGER GROUPS IN OPEN HABITATS. = 4. TOTAL NUMBER OF DEER IN EACH GROUP. A NUMERIC COUNT OF ALL DEER SEEN IN EACH GROUP. DEER W/LL NOT BE CLASSIFIED TO AGE OR SEX. VI. IN-FLIGHT PROCEDURES 1. NAVIGATOR AND OBSERVER WILL OBTAIN PROPER MAPS, ARRANGE IN ORDER OF NEED, AND DECIDE ON GENERAL ROUTE TO QUADRATS TO BE FLOWN DURING EACH FUEL LOAD. PRIMARY OBSERVER MAKES SURE THAT TAPE RECORDER IS FUNCTIONING AND ADDITIONAL BATTERIES AND TAPES ARE AVAILABLE .. NAVIGATOR SHOULD HAVE A SPARE TAPE RECORDER AVAILABLE. . 2. OBTAIN A GPS POSITION ATSTAR-QNG POINT AND NOTE A GENERAL CORNER, MAKE SURE CREW IS ON PROpER QUADRAT SAMPLE UNIT. . DESCRIPTION, ie SE OR NW 3. FLY PERIMETER OF QUADRAT FIRST IN A CLOCKWISE MANNER SO THE INSIDE OF THE QUADRAT IS TO THE RIGHT OF THE PRIMARY OBSERVER. FLIGHT SPEEDS SHOULD BE 40-50MPH AT ABOUT 100 FEET ABOVE TERRAIN. IF HIGHER SPEEDS ARE NEEDED TO BE SAFE DUE TO WIND SPEEDS, CONSIDER ABORTING THE FLIGHT. SOME QUADRATS INCLUDE LOWLAND PRIVATE LAND WITH HOUSES, LIVESTOCK, ETC. USE YOUR BEST JUDGEMENT AS TO WHAT AREAS YOU NEED TO FLY TO SEARCH FOR DEER AND AVOID BUILDINGS & LIVESTOCK. 4. DETERMINE STATUS OF GROUPS OF DEER ON PERIMETER. A. DEER MOVING OFF THE QUADRAT WHEN DETECTED ARE CONSIDERED ON THE QUADRAT, B. DEER MOVING ONTO THE QUADRAT WHEN DETECTED ARE CONSIDERED OFF THE QUADRAT. C. IF A GROUP IS STANDING ON THE PERIMETER BOUNDARY, COUNT THOSE DEER INSIDE THE QUADRAT. �149 D. RESIST THE TEMPTATION TO LEAVE THE PERIMETER TO COUNT A GROUP ON THE INSIDE OF THE QUADRAT BEFORE COMPLETING THE PERIMETER. USE YOUR BEST JUDGEMENT AT THE TIME OF DETECTION. 5. FLY INTERIOR OF QUADRAT. A. FLY THE INTERIOR OF THE QUADRAT SYSTEMATICALLY IN STRIPS OR STRIP-CONTOURS AT ABOVE RECOMMEND AIR SPEEDS AND AGL. USE PROMINENT TERRAIN FEATURES TO DIVIDE THE QUADRAT INTO SMALLER COUNTING BLOCKS AND SEARCH EACH SUB-BLOCK INTENSELY. IF YOU DECIDE TO FLY STRIP-CONTOURS, WORKING FROM THE LOWEST TO HIGHEST ELEVATION USUALLY WORKS BEST AS DEER ARE MORE RELUCTANT TO RUN UPHILL THAN . DOWNHILL. ON OPEN FLAT TERRAIN, SYSTEMATIC STRIPS WORK WELL WHEN USING LANDMARKS OR GPS LOCATIONS. TRY TO MENTALLY KEEP TRACK OF DEER GROUPS TO AVOID DOUBLE-COUNTING. B. BE PATIENT AND STRIVE FOR 100% COVERAGE OF THE QUADRAT. 6. WHEN MULTIPLE GROUPS OF DEER ARE DETECTED SIMULTANEOUSLY, FOLLOW THESES GUIDELINES. A. PRIMARY OBSERVER SHOULD BEGIN OBTAINING DATA ON GROUP NEAREST THE HELICOPTER AND USE HELICOPTER TO KEEP GROUPS SEPARATED. B. NAVIGATOR SHOULD FOCUS MOMENTARILY ON SECOND GROUP OBSERVED AND NOTE LOCATION, ACTIVITY AND NUMBER OF ANIMALS FIRST SEEN. C. AFTER COMPLETING DATA COLLECTION ON FIRST GROUP, PROCEED TO LOCATION OF WHERE SECOND GROUP FIRST SEEN, DETERMINE VEGETATION TYPE, AND SNOW COVER% AT SITE OF DETECTION, THEN FIND AND COUNT SECOND GROUP. 7. AFTER EACH GROUP OF DEER IS COUNTED, OBSERVER SHOULD VERBALLY NOTIFY NAVIGATOR OF GROUP TOTAL SO NAVIGATOR CAN RECORD A RUNNING SUM OF DEER COUNTED ON THE TALLY-WHACKER. AT THE END OF THE QUADRAT, OBSERVER SHOULD TAPE RECORD THE TALLY-WHACKER SUM AS A CRUDE CHECK ON THE NUMBER OF DEER DETECTED. NAVIGATOR COULD RECORD TALLY-WHACKER SUM ON THE FLIGHT MAP ON THE QUADRAT. 8. BEFORE LEAVING THE QUADRAT, MAKE SURE YOU HAVE NOT FAILED TO SEARCH ANY OBVIOUS GEOGRAPHIC PORTIONS OF THE QUADRAT. OBSERVER AND NAVIGATOR SHOULD AGREE THEY ARE DONE BEFORE PROCEEDING TO NEXT QUADRAT. VII. DATA TRANSCRIPTION 1. PRIMARY OBSERVERS WILL BE RESPONSIBLE FOR TRANSCRIBING THEIR TAPE-RECORDED DATA ONTO STANDARD DATA FORMS. ALL OBSERVERS WILL LABEL EACH OF THEIR TAPES AS TO THEIR NAME AND DATE. DATA SHOULD BE TRANSCRIBED THE SAME DAY AS COLLECTED. IT MAY BE POSSIBLE TO HAVE AN ADDITIONAL PERSON TRANSCRIBE THE TAPES TO SAVE TIME, AND SUCH PERSON WOULD NOTE ANY QUESTIONS THAT ONLY THE OBSERVER COULp ANSWER REGARDING ANY PROBLEMS ON THE TAPE RECORDINGS. 2. STANDARD DATA FORMS WILL BE AVAILABLE END C:\DEERCENSUS\QUADPROC.MEM AT PROJECT LOCATION. �150 2. SURVEY DATA FORM [)A.TARECr.RllNG FrnNI DEER GVlJ 102001 ~T JE(M'D'Y) JHER: LOT ------ Ha3BSlltvE:STARr TBvP.(F} _ END Sf\ONTYPE uorr CCM)' WN) NAVlGA.TCR a3SERIIER ------ 'N2E_CF_ STRATl.JfIII Ql.W) #. I ___ lltIIE STARr: LCRAN'GPS L<XAllQ\! QUAD ST.ARTlNGFONT: GRClJP 1\0. DEER ACTIVIlY \lEGE. o/cS-ON lYPE CCNER TOTAL GRCl.IP SIZE TOTAL DEER SEEN 1CXMv1MS: DEFlNllQ\JS: WI'D: Ught=!.., M:x:lerate=M, Strong=S; UGiT CCN): Bright=8, Hazy=H, OJII=D; SI\ONTYPE: Fresh =F less than 48hrs; Ocl=O dder than 48hrs. DEER ACllVllY: Bedded=8, Sanding=S, fv'bving=M; \lEGE. TYPE: Big Sagebrush=SG, Bitterbrush=8B, G-easev.ood Rats=GN, Saltbush Rats=SB, Pinyon-Jl..I1iper-PJ, Juniper \I\bocIand=JIN, Agrirulture & aearings=('A, Riparian Shrtb=RP, Tall Ca1ifer=TC PERCENT SI\ONOOIIER l...oN= L = 0-79%, Hgh = H = >80% TOT.lltvE: �151 3. SURVEY OBSERVER OBSERVER CHEAT QUAD STARTING HELP SHEET SHEET POINT GPS QUAD NUMBER QUAD TIME START/END QUAD WIND, LIGHT, SNOW TYPE GROUP INITIAL DEER ACTIVITY Bedded, Standing, Moving GROUP VEGETATION TYPE Sagebrush, Bitterbrush, Greasewood, Saltbush, PinyonJuniper, Juniper Woodland, Agriculture & Clearings, Riparian Shrub, Tall Conifer GROUP PERCENT SNOW COVER 0-79%=Low >80%=High TOTAL GROUP SIZE All deer counted in each group �152 SECTION G SURVEY FLIGHT QUADRAT SAMPLE UNIT MAP INDEX I uNil'--ioDEER-POPliLATION ESTIMATE FEBRUARY 2001 INDEX TO QUADRAT SAMPLE UNIT MAPS (QuadMapList.wb3) FLIGHT SEQUENCE IS ORDER OF FLYING UNITS WliHlN AN ENTIRE BLOCK AREA INDEPENDENT OF STRATA . 1 QUADRAT 11" x 17" FLIGHT II-STRA--=ruM', STRATUM NAME UNIT NO. MAP NO. SEQUENCE LOCALE DESCRIPTION 1 -,'--Yampa-Monument Low Density 1 YML 5 1 Bear Draw Mantle Ranch Rd. 5 2 Bear Draw Mantle Ranch Rd. 1 _ Yampa-Monument Low Density 2 YML 5 3 Dry Woman Canyon Mantle Rd 1 .! Yampa-Monument Low Density 3 YML 6 4 Dry Woman Canyon Mantle Rd 1 ! Yampa-Monument Low Density 4 YML 6 6 Schoonover Pasture Mantle Rd . 1 't Yampa-Monument Low Density 5 YML 5 1 Yampa-Monument Low Density 6 YML 6 Schoonover Pasture Mantle Rd 9 18 Sand Canyon Mantle Rd Yam_pa-Monument Low Density 7 YML 9 20 Chew Ranch l._ .. 1._.__.. Yampa-Monument Low Dens~~ 8 YML 10 22 Trail Draw Chew Ranch L.. L t--~mpa-Monument Low Densltv 9 YML I 9 Units r f-- r I r l__1_--. [._----_._- _. I~=:---~ -~--"i--a-m----pa---M-o·-n·-u-m-e-n-t-M-e-d-i-u-m-:'-D-e'-ns-i-ty_+-1-0-Y-M-M-+----t------+---J-O-h-n-s-o-n-c-a-n-yIO-n-M-an-t-le-R-d------i 6 7 9 . 2 .L Yampa-Monument Medium Density 11 YMM Johnson Draw Mantle Rd 6 6 8 ~_.1.. _. Yampa-Monument Medium Density 12 YMM Johnson Draw South Ma-ntie Rd 7 10 ! 2 Yampa-Monument Medium Density 13 YMM West Serviceberry Draw Mantle Rd 12 2 Yampa-Monument Medium Density 14 YMM Yampa River Overlook Mantle Rd 8 8 \ 2 Yampa-Monument Medium Density 15 YMM Marthas Peak Dangerous 11 8 13 _£... yar!!_P.a-Monument Medium Density 16 YMM Mantle Ranch Cave 8 14 t __ .. __ .~_. !_Ya~Qa-Monument Medium Density 17 YMM Rock Bench Very Steep p 1 9 15 2 '1 Yampa-Monument Medium Density 18 YMM Red Rock Ranch Site Stee 2 Yampa-Monument Medium Density 19 YMM . Pearl Park North' i 9 16 \ 17 .1 Yampa-Monument Medium Density 20 YMM -; Pearl:Park South . __j 9 21 10 __ r_--:-::-_i1_._..... _~_ . ._~_'( ?.!!!Ea-Monliment Med ~um Dens~ty .,:;2::;1:-;Y:-:,M;:::::M;-· -t-_-=-:__ --:--=Sc=a.:.:n.=.d-:Ce:=a:..:_n:..r,.::::ylo:::n...:.R""i:..:.m'--I-j 9 19 1_ ..__ . L __ ~-Yampa,Monument Medium. D,en,sitv 22 YMM Lower Sand Canyon 10 23 t 2 Yampa-Monument Medium Densitv 23 YMM Pool-Creek Rim . 10 24 [_Yampa-Monument Medium D.ensity 24 YMM Stateline Pool Creek L__ 1.- .. i i_. I --1. [·---·-2'::::'. __ l=:.:=-:=-~ ~._. . .. . 1_5_U-,~.-,its,--,__ _j_ I ! INDEX -ro-CiUAO-RA:(SAMPLE-UNIT-MAPS-I QUADRAT ,:S;:TU~__:,,' -::'~:;~:::::.n.", UNIT NO. 3 Utah White River Low Densitv Utah White River Low Density ---3'- ~~='::_T-=:::-r-. Utah White River Low Density ,, Utah White River Low Densitv .--. 3 , ._--------··1- 11" x 17" FLIGHT MAP NO. SEQUENCE i 9,UL 10-UL 11-UL 12-UL 13-UL 5 Units 11 12 13 13 15 2 5 7 6 13 l._..._.._______ ..... \------------ '. :-=-~ -------4 t --;' .. --- - -- Utah White River Medium Densitv Utah White River Medium Density Utah White River Medium Density Utah White River Medium Density Utah White River Medium Densil:}l - Utah White River Medium Density Utah White River Medium Density Utah White River Medium Density LOCALE DESCRI~TION ~ Stateline W.Drippina Rock Ck .~ Dripping Rock Ck O[!en Flats White River Drinnlno Rock Ridge Stateline Dripping Rock Ck White River Cliffs ---·--1 1-UM .;2-UM 3-UM 4-UM 5-UM 6-UM 7-UM 8-UM 8 Units 11 12 12 14 14 15 15 16 1 3 4 8 9_ 10 11 12 SnakeJohnReef W.Dinosaur Stateline Raven Ridge Raven Ridge'Morman Gap Raven Ridge South Raven Ridge South Raven Ridge Southeast Raven Ridge Hardware Draw RavenRldqe White River ., i i! ! i =J �153 ITNDEXTO QUADRAT-sAMPLTuNiTMAP-s--'---' ! [sTRA-i:GM I r----- STRATUM NAME . ..------ 1==: =~L~~=~~:f:= ~:::~ ;1:; l .__ . ~ ------1 :::-.:J _LOCALE DESCRIPTION ~::::~::::; --=-1 Upper White River High Density .?._._.... Upper White River_High Density 5 __ -f_J!Eper White River Hiah Densitv 3-WRH 4-WRH 5-WRH 24 23 23 54 53 52 North of main riqg_e Rldae North SIOPL__ On RidQe 5 I Upper Wh'" River Hlah Densitv ._._...__._5__ .._.J_J:!.P-p-er White River High Density _._._._5 _! Upper White River Hiah Densitv . §__ .L....!!Pper White River HiQh Densitv 5 Upper White River High Densitv _.QpperWhiteB_!ver High Density Upper White River High Density I .. _. §... .'_ .!:!pper White ~iver HJgh Densitv ! 5 Upper White River HiQh Densitv 5 ·=~~:_.1!pper White River Hiah Densitv ._5__ .__ ..._J!pperWhite River !::IiQhDensitv \ 5 Upper White River Hiah Densitv . !:l'p'perWhite River Hiah Densitv Upper White River Hlqh Density .!_!J.£ger White River HiQh Density ~. __§_ .I UpperWhite River HiQh Density 6-WRH 23 22 22 22 . 22 22 22 22 21 21 21 21 19 19 19 19 51 48 47 49 46 45 44 50 43 42 41 40 37 38 39 32 Da Whit. RI", 11 On White River -On White River _ North Slope Road South Slope Road On White River On White River _.North of Coal Rldae ._._._ North of White River On White River Cliff On White River Dirt Road--Main Road on Ridae On White River Cliff & Mine ~ Steep Gullies North of Mine SteeD Gullies Northwest of Mine-PinvonJulnper Ridoe Road ~ \._. ~ ._ . -.- ..-.-..--- -"-'j IQUADRAT 11" x 17" FLIGHT UNiT NO_ MAP NO. SEQUENCE r.=-=:§_ ..~--.- i- . ~. ._ ._ t=--- =-=- ~ ____ 5 7-WRH 8-WRH 9-WRH 10-WRH 11-WRH 12-WRH 13-WRH 14-WRH 15-WRH 16-WRH 17-WRH 18-WRH 19-WRH '20-WRH' 21-WRB Chase Ck ~~;~fC~::a?Ulley l!pperWhite,.River High Density 24-WRH 19 " 34 . L_. __L_Qp~tWbite,RiverHiQh Densltv 2S-WRH 18 ... 29 1 .. _ ._ .. _~ ._ .1~QPer Wt)iteRiver HiQhDensity 26.-WRH 19 36 L_ ..'j_.Jd".epe-rWhite River Hiah Densitv 27-WRH 19 35 i 5 _Q.eper White. River HiQh Density 28-WRH .18 28 ..!:!.r:!perWh~teR~verH~ghDens~tv 29-WRH 18 30 \ _. ..~__. . [..~p-er_Whlte RlverHiQh Densitv 30-WRH 18 27 ! .. _.. §__.. 1_ Upper WhiteRiver,Hlah Density 31-WRH 18 26 i ~__ .. !__ '!:!p'.Q.er White River High Density 32-WRH 17 25 1 5 i Upper White. River Biah.DensitY 33-WRH 17 24 f '_j.: -. _f:--upper White.:Rivet HiClhDens:~ 34-WRH 17 __ 20 I _§ _ .. l_.\:!£Q~~WhlteRiyerHlgh Densi 35-WRi;I: 17 21 _§_m... i ... 1!£~r White Riv!!IHigh Density 36-ViI'RH 17. 19 : ... L__ ._L..11.ERerWhite River High Density 37-WRH 18 22 5 l_Jp.p~r~~!~~!.v.~r l-lig!_l,:,Q~!lsity __ 38-WRH _ 18. 23 ! s i l_Jp~r..Y'{_!1ite_Ri~r. I-Jl9h Density 39-WRH _. 17 18. 5 \:Jp'p"~rY'{h!~.B:iY~r.f!!g~J:?en~i~y. 40-WRH ._:!1_I-__!J 5 \ Upper White River High DE!.~s..!!Y.--.-4.1-WR_H_ · ... _ ..1~. .__1§ ; '. _ . ._ _._.--'_. '-~its u .•. ~ -1 I [_.:.:__.._§__~= 1 I _ I i I l____.. _.__. _ -_ -.-._----_.-. __ - ------.- ---.~-,~---..-----~-----------------~-_+-------------.... .... iNDEX TO QUADRAT SAMPLE UNIT MAPS I I FTR: TU••. Jet. ---_ Coat Oil.F,UmMesa Coal Oil Rim East I Coal Oil Rim Mesa Northeast ChaseCk Mesa i Dead 000 Draw Mesa Cliff ._. I Chase Draw'Mesa __ ..··1 Upper Dead Dog DraYL..~._. _ Dead 000 Reservoir ._.. Dead Doa Reservoir -1 Nate Spring ReservoIr j . Nate Spring" ~~:~~] '.Nate Spring East . ..._.. 1 Nate Spring,North _ i Scullion Gulch Lincoln Reservoir] _ Scullion-Gulch North __ NateSpring North Pipeline I ~_. UpperNateSp!llliL ._.m~i . ._!:!p"p'erNat~__§pr.i!!g .1,1 r .. i _.j t, I J J -·~I:~;::~':~:~:~~~:~ ~:~~,~:~:::~;::~~ ~~: ;! I _ .. ~----'-,' __ -I-I QUADRAT 11"x 17" ... FLIGHT I·~--:-~'p-.e-~-w.i.::-' .. iT-t:-'-:..:T-IV U-eM'-'; -:~eA--:~~:-:-u:::.:-D-en-S-;lt'I__J~U~1No:.!:-~~1:'-':_,,~'?-.!. •. ~-'-'-M-'-~!..A2~:j:~0~.~~S~E~Q~IU~:~N~C;;E~~~~~~:L~:;;:o:.!:v-Av;;.~;.::~:~:~X""S::-:~I'-'R=-d!! !.!N-_-_-_.=-=-~ ._ ~~_.-_ .._-_~J!.R.J:!erWhite River MediumDens~~ Upper White River-Medium Densitv :~White River Medium Densitv 6 \_Upper White River Medium Densitv 6 ~~ Upper White River Medium Density ._6 __ Upper White River Medium Densitv 6 ' Upper White River Medium Densitv 6 --.-.....j- Upper White River Medium Density =-- ._1 __ - ---=LUppe,rWh-ite Rivet,MedIum'Densitv 6 ! _.. =:"1i " 28A 21 20 20 17 1.6 16 ·16 2 4 5 6 9 12 '13 14 10cWRM 10 Units 16 15 RedWash. ~oXEdler Ck . __ Red Wash· Prairie Doc Reservoir Raven Park Dam Scullion Gulch Raven Park Dam Scullion Gulch ..Rock ShaleReservoir .' Stinkino Water Ck -::-Stlnklno Water Ck "StlnkinQWater Ck ,.Stinking Water Ck 1 'i ." ~_ 7__ Upper·White River Low Densitv _.__ 7 ._..L_J:!p-per White.River Low Densitv ,7 UllperWhite River Low Densitv ---7 --.. Upper White River Low.Densitv L u~rWhiteRiverLow Density t1-- [-------..-.-:~= 2-WRM 3-WRM 4-WRM 5-WRM 6-WRM 7-WRM 8-WRM 9-WRM -'-__ '-'-'-.· 21 1-WRL 29 2-WRL 30-A 3-WRL 4-WRL 30 5-WRL 16 5 U L- _ -'-n_._i_ts __ L . S.Hwv40 Red Wash Hwv 40 Red Wash Red·Wash Reservoir #1 S_Hwv40 Skvline Reservoir W. of Stinklila Water Ck 3 7 8 10 11 J__ __ --.-_j_ _ __l �154 'INDE-x-r6-QuADRAT i STRATUM +- ----1 SAMPLE UNIT MAPS QUADRAT UNfT NO. STRATUM NAME 11" x 17" FLIGHT MAP NO. SEQUENCE 1 I LOCALE DESCRIPTION ! J------~~c~~--~~~~~~~_4--~~------~~~------~ ;~--- 10 1f-'~M~a~s~sa~d~o~n~-~D~in~o~M~e~d~lu~m~'~D~e~n~s~iWL_'_~1~-M~D7M~~~3~5---+--~57~--+_----~~~K~-~C~r~e~ek=-~~ __ ----1 I __ __!1~O __ ~.~M::z.as::::s~a"-"d,,-,,o~n,---:::D7'in!.:o::...M:=:-=e.::d~lu:..:.:m:.:...::D..::e.:.:n:::.si:=-W-!-~2-:-M~D=_M:=:-+--.:::3:::-5---+----,5:::8:-----l------M~ln:-:e~r:::.s-=D ..... _ r 10 I Massadon-Dino Medium Densitv 3-MDM 35 59 Miners Draw Road ~ 10 -i ~---j Lt' Massadon-Dino Medium Density 4-MDM 34 Middle Ck (Fly Contours 66 & 7700) 54 =~1i1~~~0·~-=-·~_·~J· ~::::~~~~~:~~ ~:~:~~ ~:~::~ ~~~~~ ~~ ~~ T~~:~~~~~~n~:n~~~;~~~;;s -_ Massadon-Dino Medium Density 7-MDM 28 20 Skull Ck Rim Massadon-Dino Medium Densitv 8-MDM 28 19 Skull Ck Rim Massadon-Dino Medium Density ·9-MDM 27 14 Three Snrinqs 1 ,10 Massadon-Dino Medium Density 10-MDM 27 13 Three Springs 1 , -~-.j__!===-=o.:=:-:::-=.:;:.=~==:=-t--7-':--::;:~+---7::--+--'-:'---I-------'-:::-==-=:=-==-----1 ff-__ ~10~ __ +~M~a~s~s~a~d~o~n~-D=_i~n~o~M~ed7.i~u.:.:m~D~en~s~i~ty-r~1~1~-M~D7M~---2~7~~----1~2:-----ir_------~.:.:M!.:a~s:=-s::.ad::.o~n7a~ ~ 10 Massadon-Dino Medium Density 12-MDM 27 11 East Massadona 10 Massadon-Dlno Medium Density 13-MDM 27 10 Horse Draw E.Massadona '.10 Massadon-Dino Medium Density i4-MDM 25 1 Lower 3 Springs Draw 10. Massadon-Dino Medium Density i5-MDM 25 3 Lower Peterson Draw 10 Massadon-Dlno Medium Density 16-MDM 25 9 : Peterson Draw Reservoir r-10 Massadon-Dino Medium Density 1'7-MDM 25 8 Peterson Draw 10 Massadon-Dino Medium Density 18-MDM 26 7 The Sloughs f--~1~O-' --:-~M~a~ss~a~d::'o~n-~D~in~o~M~e~d~iu~m~D~en~s~ity~~1~9~-M7.D~M~--~2~6~-r--~1~5---r----~S~k~u~II~C~k~R~lm~R~o-ad~----' _ .... l ~-~-~~~~~~~~~~-~~~--~~--~--~--~~~~~~~--.-! Massadon-Dino Medium Densltv 20-MDM 25 6 ----- 10 10 Massadon-Dino ____ 1_0 _____ .. Medium Density 21-MDM 26 16 Petes Post The Slouqhs Bear Canyon Sprin!1 ~~M!.:a~s~sa~d~o~n~-~D~in~o~M!.:e~d~ju~m.:.:...::D~e~n~s~ity~,_2~2~-~M~D~M~r_~2~8--_+--~18~--+_--------=U~Jp~Ple~r~S~k~u~lI~C~k~ ~ +=22::...;:U""oc.:..;it:;::.s-+ -!+--I r_--------~.------.-------------------.r-------+-------+--------r-----------------------------.~---.--11 Massadon-Dino Massadon-Dino ..-. Massadon-Dino Massadon"Dino Massadon-Dino ~·.-=.jL_-=- -11 " '-'--1-1-.-- -r··.. L:::=~1J..~-.1__ I....--~'!....-... Low Density Low Density Low Density Low Density Low. Density Massa_don-D!nOLOW_Den~_. 1 1-MDL 25 2 Peterson Draw Reservoir 2-MDL 25 4 North Peterson Reserv.oir 3-MDL 25 5 Wolf Creek Sprin!1 4-MDL 26 17 Petes Post Wolf Gk 5-MDO":L~+-__;3::.;40--+--__;5'-'-3---1-------=--=B=u~c'-,-'k'-w~a:::.:te:...;r:..:.D.::.r:..:.ac::'w:..:..:... __ --·-_~-: -_ ~i 6-MDL I' ". _._.. I-:_:=~_=~_=~ __._=-=~~=_·. -,-~~~ 35. _ _:__I_. 56 K·Creek .--'--============<_·-_-_-_-:-._-- __,-_-_:==___~:~:.l CiNDEXTO QUADRAT SAMPLE UNIT MAPS STRATUM NAME STRATUM -.---- ~_1.L .--. __ ~_ 12 , 12 r---12- 112 1'----'---- -._-... '-, I 12 12 12 --1-2---1 12 I I I Twelvemile Twelvemile Twelvemile Twelvemile Twelvemile Twelvemile Twelvemile Twelvemile Twelvernile Twelvemile . Medium Density Medium Density Medium Density Medium Density Medium Density Medium Density Medium Density Medium Density Medlum,Density Medium Density ." QUADRAT UNII'NO. 1-TMM 2-TMM 3-TMM 4-TMM 5-TMM 6-TMM 7-TMM 8.TMM 9~TMM 10-TMM 10 Units 11" x 17" FLIGHT MAP NO. SEQUENCE 1 1 2 2 2 3 3 4 4 4 ....._...l 1 2 3 4 5 6 7 8 9 10 .'_JI _oj LOCALE DESCRIPTION --_._--.! I , Yampa River Twelvemile Gulch Rd~--l N.Hwy 40 Radio Tower Road . N.Hwy 40 Radio Tower Road _~ N.Hwy 40 Buffalo Gulch ' __ 1 S.Hwy40 Springs Ridge .--..-.---1 N.Hwy 40 Buffalo Gulch i N.ElkSprings Buffalo Gulch Elk Springs Road ---'Elk S'prin'gs Road BayGiJlch NW-Eik Springs ::::J -- �155 . _._ ..-._-- .. '; I -- .-_._--------_._ .._-----------,----,------,----------------- flNoEX y6-Qt-A...,.D--=RA~-=T:-:S:-:A:-::M-:-::P::-:-L--=E:--:U7:N-::::IT::7:M--=A--=P-=S--+----+-----l-----+---------------I QUADRAT UNIT NO_ 11" X 17" FLIGHT MAP NO_ SEQUENCE LOCALE DESCRIPTION __.____j --_-1~-3;..--.---- i~'L , Massadon-Dino Hlqh Density 14-MDH . 30 34 Upper Red Wash Massadon-Dino High bensity 15-MDH 31· 36 Blue Mountain Town Site Massadon-Dino High Density 16-MDH 31 37 Willow Ck Hwy 40 east !--1"3--"- :_=__=_~M~a~s~s~a~d~o~n'-'-_=D~i~n"'o~-;..!.H;i:Q'-" -:_=D~e:n~s7'I'?_tv'LL----;..!.1,:,7:---:-7M~D~'-:H.!.--+-I_-----'_=3~1'=--=--=-:-=--=--=-~3-':-S~-------t+-_-_ -_-_-~s--;:j_QI~..:..=-e:..:;n"--"'c~ ..:..;e::.!r'=_-W~~iI~IO~W~:C~k-:H~iWV~~;-4..,.0~ -~_-_-I-j b n.. -1;_ r-~~-1~-.-_-._-~--~M~a~ss~a~d~o::.!n~--=D7in~o~H~~iiQ~lh~D~e~n~s~ity~-t_1~S~-M~D7H~-_731~~1__~3~9~-l_-~~S~)p~le~n~c=e~r~D~ra7w~H~WVL4.!.0~~_~ ! 13 i Massadon-Dino High Density 19-MDH 32 40 Spencer Draw West Hwy 40 13 __::::==·----'M:::-"-a~ss::.:a:O':d:'Oo:.:.n:....-D::-:.:.:.in~o:...cH:-:-i:-"7glh'-:D~e"-'n.:::s:.::ity'-'--t---::2:::0'-:-M=D-:-:H;-t--3'C'2:--!--4~2:._~I----.::D:':i:=n:!!o.:cH':"e'--'a:::d=-=Qlu.:..a.!.rt:..:e:':rs'--'-H-:-: L__ 13 Massadon-Dino -.-_-__ --_11-_~~.-._--_-.--._ __ Massadon-Dino __ Massadon-Dino I , 13 Hig.:;;h_:D::..;e:.;.n:;:s:.:.;itv:.L-_r-::2:..:.1__;:-M:.:,=cD.:..:H'-I-_-'3::..:2=---+_----C4:.;:3_-t __ ----.,._-=D:.:;in'--'-'o:o_:s:_:a::..:u:.:_r_:Q,,_,u::..:a:.:_r:....L.rv _ High Density 22-MDH 32 44 Dripping Rock Ck-Dlno Road __ High Density 23-MDH 33 45 Sand Ck _ _ _ __ -'M~a~ss~a::.!d::.!o::.!n~--=D:!!in.:::o~H~~iiQ~lh~D~e::.!n.:::s::.!ltv~_~2~4'--'-M~D.!.H~-~33~~-~4~6'---l_----.,.-~W~.~D::.!i:!!n~os~a::.!u::.!r--'H~w~vy~4~0-_ l__ ..1l__ ~~.L_~M~a~s:::s~a~d:::o!.!.n-_=DO!i!.!.no~H;:;ig"-'h::.:...::Dc::e.!!n:::si'?_tv'__ ~2:.::5_:-M'=D~H'-+---'3::.:3'--_j_-----::4'_':7---I----=L:::o.!!wc::e.:..r.!:S~PlriC!.!n.l:l..L.g,!.!N.!:W~o~f~D:::i~n~o:::!s!!.au~r'___1 "L-'---11 3 __ I! M~as~s::.:a::..:d""o"-'n'--'-D=_=i"-'n.:::.o--:-H:-:ciQ"-'lh::.:...::D-=-en:..:;s::.:i=-tv-t---:2:.::6:.-:M'=D::-:-7H-t-_--=3:.::3_-t_ __:_4!!S:___~-------,~U:I=pp4e~r:...:S~ip::.!lr.!!in?__g_~_- 3 I---7 Massadon-Dino High Densitv 27-MDH 33 49 Bull Canyon Rim t:: .. 13-····---1 7'a::":s"'s:'=a-=:d':::'o'-'-n---=DO!i'-'- "---!-7 .::o...:-H:-:-ig"'h::':"'::D'-=e:!!n':::'s7=-jjtv =-S--:'M':-:D=-=H:7-l--: '-=3--+-----=570--t----="--K:.::::.::-R=-'a'-'-n.:::.c!!.h-'--"''--''------M no 2 3 F1l---- t- --·~r:~~~~~.~~~~~~E::._:~ h [=~ ~_ Massadon-Dlno High Density 29-MDH 33 '_____":..:..!-=:~'-"nD'_"~t;:;:~c__,_ __ ;_;_--'- __ _ 51 Buckwater Draw ;_;_---' St_a_te_~_i~_~_r~_~_~_r_ee_k __ -__ -_- __ -l �.. VI 0'1 en ~~~~~~~~I~~~~Jc..~%~E~:r~jg~:su~~g~J~~~61-.1£~€~~DSJ'::~~:F~N,!'~~~S:;O~N~~~~;~9~~\~dASED - -.. --···----"f!...· .......... Stratum ------straillie'd'"R"'.n=d"'o=m·S"'am=pl"". _-.:._.__...._. Quadrat Statistical CalcufaHons Unit Cur 1Stiii'iJili Deer CountadJ QUldr'" Countedl Quadrat Unit Quadrat 1 YMl , 0 10 YMM "'--'0 11 YM'" 3 YMl 0 12 YMM ..........••...........• ~YML •..9 _._'3YMM _ 5 YML. 0 14 YIA'" 6 YMl a 15 VIAM ITMT' 101 16 VMM 8 YMl _)3 H Viol'" ----·--j·"l"Y"'MOi'-l ..-----.•. ____ 1-- ..•.• ..- ~~_----j..ill1.l 0 ~~~~~. ----··------------1----1 f----. ..... f-- .._....... '-_ • _._.. _ a a 4 g a 21 YMM 0 22 YIo1'" 23YMM 24 Y!Jt.! 5 0 Our Stratum' .... ,_. 9 1 0:T': _._.._._ . .,._ a _ --~-·t..~·-· 1---"- "'-"- ---..--... .... _.._.... .._ ..••.•_ .+-_ =t .. - ..-L ._._. I --- __ .. -'--. --~·+·-.. .. -. ------ - --.---1-j .. -----1-.. -. 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(5 Z en en m o -I (5 z ::I: �t ----_-~l=-±_=--1:_~::-1=-~.:__' -F :~-t~ EE=r?:.~-_~. J .. +_ .._ f T:I}~;~~~~~:~~i}.~;:::,(~~(~~-=l~~~~:~~~~:g~=:: -~T~-=-l:~J-~ ~-~ ~~~: _~~r~ - _=~-~ WHERE' - I I I I - §-_ I __ ._ I::J r I , . ;'~h'~:~~~~I~~;--=~---- I 1 T I i I Mean0", Per SampledUnit(1'1".) __ ~_~-",b~!_?! deer counledon_~,chsampledunliin each SIr,lum.· deer :()\J-,~edInu~.?L~a!~E'! -"~I~ __ 1-_ ____ _ ..1. __~::: _ ~eer Per SampleUn~V.rl~~.'_'{S".~I_ ~'d sampl. varl,nce ofde•• .'.'.'~_nled per .ompl. unllIn eAch 'Irol~,!,.cat:_'!!."'ed USIng Excel:::'~~_c"~~ for.amp'. v",.n~~'_I-_' .--1----- .. - -- _.. Total Sample ~~~~ Per Siralum (U..) :: total number 01polcnlioJ sample Units or quadrats In each Stratum j_ I I ~_ ! __ r TI ~~sted ~I!r Per Stratum (N)} "__ Stratum Variance Va£"l{N'\J l:l Tolal Deer Counlcd All Strata N (su_T N,J Estimated Percent 195'·1. Deer All Strata Nlo (sum W,J Variance Vsr"N" (sum V8r"'(N"'~)} Codiclen! or Variation CV'"(N"J Conndenoe Interval for Nit. Lower Upper cenneenee Interval ror W lower UDDP.f Total Estimated ~Q_% number of deer counted on each stllmpled unit In ea~_ Stratum IUJ(l.ut;:Ju.lJ _~_ .-=-I~~~Tn.I.11998P&g.3:-:·-=i ± I _ I -"lumofslldeetcountedlneachSlralum _ • ~um of all estimated S(talUm. thIS 1~_!~tim~~led populalfon number of deer In each = sum of aU estimated Stratum variance; . I I. ---~:~~~~=~_ -- b)' pot~_ntt~1 number multIplied 31tJndard e.slrmaltM:!Stratum variance for deer counled In eBen St~lum . -- -- --:::"',1' 1=-_ ]0131 ,. average ~ I >3. of sam~e~~ each Stratum s~e for ~OII 10 sampled __ - t h '1 _ _ 1__ _L_jj_ __ ~_~~ M-~:' __ ._ I _-.m'--~l·_'~~'::L~--·-t~·-~ i l _.__ ~ L___ =r__==r=_~~-_ ' __=:=10___ __~ --L-_.+- .• Sguar~_er"N" divided bvN" mull! lied by_100 10 ~.Pfes'S as a_~percentage :: PopulatlOn Eahmate (W) +/. (1 64rSguareRoot (Var"WI = Pooulauon Estimate W +1- 1.96 ·SQuareRooI (Var"N" I -E- _j __ __J..~_~__==c:__.~.._~---' _ __ ' J._...:..-r._l.__ --l_ I I _j L__j__ . t J ___ area -_I ~- .__ __ r. --_. I _.__ -=-.-l-... I .. 'T I L---i" ' _ ~ ..-...._ __ •.•••• __ ~L ----------r- I t --r- r-- ! .._.t J.. r ~....__._ _~u]._. .-._-.-._.._.I__ .,_._M' __ -----=c___ -==t... ., --.L-- .. _ -1-_..._..... t -------r! __ _L__ .. v_" __ •••••• _-1 _ ,_. U. -J �158 2. LETTER FROM IDAHO DEPARTMENT OF FISH & GAME SHOWING POPULATION April 5, 2001 v. W. Howard, Jr. 1025 Hickory Drive Las Cruces, NM 88005 Tommy S. Bickle P.O. Box 750 Hatch, NM 87937 Dear Drs. Howard and Bickle: Find enclosed 3 files representing the results of my analysis of the Colorado Unit 10 mule deer survey data. Colorado Division of Wildlife personnel flew the survey Feb 25 - Mar 5, 2001. The survey was flown using a stratified random sample. Eleven strata were delineated and sample unit size varied from V4 - 1 mi. 2. The 1/4 mi. 2 sampling units were used in the high canopy closure habitat types of pinyon-juniper and/or juniper woodland. The 1 mi. 2 sampling units were used in more open canopy types. One hundred and forty three units were sampled across the 11 strata and 1180 mule deer were observed. Because the Idaho Aerial Survey program has a ten strata maximum, 2 strata were combined for the analysis. Based only on the stratified random sample, without correction for visibility bias, the population estimate was 6481 mule deer. Using the Idaho Department ofFish and Game's Sightability Method the population estimate was 11,052 (90% CI 7549 - 14,555)- This represents a sightability factor of 1.7. Bartmann et aL (1986. Wildlife Society Bulletin 14:356-363) recommended a 1.5 .sightability factor for Colorado pinyon-juniper woodland. You can find a copy of the Idaho Aerial Survey software and a downloadable manual on the web at: http://members.nbci.comlfredJebanisurvey.html. Please call with any questions. Sincerely, James W. Unsworth Principal Wildlife Research Biologist Ce. G. Miller, CDOW �159 ESTIMATE USING IDAHO SIGHT ABILITY CORRECTIONS Aerial Survey for Windows, Version 1.00 Beta 6.1.4 (12-Feb-2000) Thursday, April OS, 2001 09:06 AM Model: Mule Deer, Hiller 12-E, Idaho (Spring) [Files] Title = C:\PROGRAM FILES\lDFG\AERIAL SURVEY\col02.ttl Summary = C:\PROGRAM FILES\lDFG\AERIAL SURVEY\coI02.sum Colorado Unit 10 Mule Deer Survey, Feb 28 - Mar 5, 2001 Section 1: Summary of Raw Counts Units Stratum Sampled Total ------ ------- --------------24 1 125 2 5 31 3 8 66 4 41 322 5 10 178 5 6 112 7 15 10 4 8 9 21 133 9 10 10 194 ------- ------------ --------143 Total 1180 Section 2: Summary of Raw Counts for Perfect Visibility Model This table projects the number of animals that would have been counted if every unit had been flown and visibility had been perfect (no animals obscured by vegetation, etc.) Strat No of Units Popn Sample Total ---- ------ -----------------------237 24 1234 1 2 32 5 198 3 23 190 8 1704 4 217 41 552 5 31 10 717 6 32 5 7 117 176 15 8 80 4 180 162 21 1026 9 10 29 563 10 ----- ---- ------ ------------------- ----- Total == 1019 143 6481 �.~---- 160 Section 3: Estimates for Total Number Total Stratum ------ Number of Units Popn. Sample Estimate ------------------ Variance ---------------Sampling Sigbtability Model ------ ------ -------- -------- -------------------------------------------------------- Bound 90% --------- ------- 1 2 3 4 5 6 7 8 9 10 237 32 23 217 31 32 176 80 162 29 24 5 8 41 10 5 15 4 21 10 1422 293 375 3183 851 1397 154 1133 1403 841 1158993 27155 25316 654838 154826 388737 21812 1219118 572711 141508 4492 2570 8143 44009 5916 14884 376 53969 10224 4590 349 218 1529 6681 538 1333 17 8787 784 449 1774 285 308 1382 661 1047 245 1862 1257 630 Total 1019 143 11052 4365014 149173 20685 3503 -_----_ _ .. .. - �w o o s: "'C r m -I m c » ~ r en :::! z G') "T1 o » m ;;a ;;a 5> r en c ~ m -< •.....• 0\ •.....• �,_. 0\ IV H JM UM UM 4 4 4 4 4 _4_ 3' 3" 3' I' 2 0 1 2 0 n 1 M i 3 0 y ET R e' r eL 1 60 .0 ... 1 PJ 1 . 3 0'. 102128120011 02l2er.!001 102l2812!iQ 1 1 1 'I A AlII El I 1 ~]_ ET ... _ 24 I I JR L~ I JR JR I w 0 50 """"0 19 ::::£ _ lUM '7UM .7UM PJ PJ aw .,aIM 3 3 18 5' 8" SG p. -~ 0To ,·VI s- o 0 ~ SI II ····yYHH '10:, 11 ·WRH. 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MAP SHOWING WHERE ELK WERE COUNTED Sampled Quadrats Showing Where Elk Were Observed and Counted During Helicopter of Mule Deer to Estimate Population Size in Unit 10, DAU D-6, Colorado. Counts Sampling Strata. and Sample Quadrant Units , -Monnmenr (Low) Yampa- Monwnent (Medium) Utah Wb ite River (Low) Utah White River (Medium) Upper White River (High) . Upper White River (Medium) Upper White ]Uver(Low) Massadc)na- Dino' (Mediuin) Massadona - Dino (Low) Twelvemile (Medium) • Massadona- Dino (High) E==:3::==i==:==:==:==:3::=::;::=:::::::lB A Miles '~:~b~ed �en UJ c: s:: s:: DEER POPULATION AND DENSITY ESTIMATES where a~licable DAU 0·1 0·2 0·3 0·6 0·7 0·8 0·9 0·11 0-43 0-41 0-42 Sportsman's Population Estimate Modeled Population Estimate' 4,100 13.500 37,800 1.800 7.000 67.000 6.000 13.500 12.000 7.700 13.800 7,900 7.300 31.500 10,000 4.900 5.900 2,400 6.700 5.000 3.900 2,400 31,000 0·18 0·12 0·13 0·14 0·15 0·38 0·51 0·20 0·21 0·23 0·19 0·39 0-40 0·25 0·24 0·29 0·52 0·30 0·35 0·37 D·53 13.300 2.700 1.750 17.500 8,000 7.800 5.100 1.750 3.700 2.300 2,700 8.300 2.200 1,200 2.650 1.750 2.200 1.850 1.600 900 6.100 1.100 3.800 3,600 9,200 1.970 2.400 3,300 1,750 750 1.100 3.000 11,800 5.300 34.000 12.500 9.300 20.800 7.600 2.000 3.200 TOTALS 128,420 408,600 1997 1998 24.i98 401 3,058 497 3.839 306 623 3.559 2.049 3.835 524 1.963 1,195 N/A J4.l:I57 11.016 N/A N/A 34,619 5,134 868 1.055 586 1.068 4.2~2 870 1.151 2.992 1,363 225 N/A 40,558 5.361 2.099 N/A 1190 1122 473 615 2014 345 35,346 36,545 17,352 1,432 N/A 605 1,355 2.972 926 522 639 N/A N/A 464 7.075 558 407 1.608 2,684 624 1,202 3,719 773 167 394 N/A 716 917 N/A 1,190 1999 mi2WRIS winter range 353 425 1005 170 387 187 488 539 156 128 301 490 232 124 280 310 1308 230 266 433 1,309 248 500 1.126 491 355 97 N/A 927 20,018 446 5.611 N/A 912 395 998 NfA NfA 25.128 » :::0 # of DeerClassified Qua rat Population Estimate N/A 1.065 1.344 1,860 365 4.342 784 1,107 2.745 N/A NfA 844 982 730 N/A N/A 2,091 1.071 740 643 N/A 352 481 N/A N/A 509 7,6,7 N/A Sportsman's Densitylmi2 WRIS winter range -< Modeled Density/mi2 WRIS winter range 3.45 11.34 11.85 5.71 2.85 33.69 3.81 11.38 33.27 17.00 31.76 11.94 45.29 35.66 42.25 14.96 56.44 64.10 38.28 19.60 4.90 28.88 40.32 13.93 7.74 23.70 8.69 22.66 18.35 5.07 10.29 9.56 12.30 5.53 15.40 14.10 9.38 8.80 3.57 9.46 14.92 5.71 2.90 4.66 4.78 14.29 8.31 7.94 4.80 2.93 3.56 2.11 11.34 13.04 44.36 12.24 25.97 50.40 18.60 18.47 15,48 5.63 32.99 7.40 23.54 7.03 Quadrat Densitymi2 WRIS winter range :EO m"TI UJUJ 21.57 -i"O mO ;;:0:::0 17.36 33.48 Zcri Os:: Om iz: ;;:Oz: 0» igc On Co - C 64.23 ~:E mC :5:m rom m:::o ;;:0"0 NO 0"0 0c: 19.21 Os;: -I (5 15.29 z: m UJ ::! S » -I m UJ "TI 0 :::0 • DOW 2000 Post· hunt Population Projections ml::d?er pop_den est.xls ·11/09/00 •.... 0\ 00 �169 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 JOB PROGRESS REPORT St&eof ~C~o~l~o~ra~d~o~ Work Package No. Study No. ..:::3~0~0=-2 ~RMN~~P~ _ Division of Wildlife - Mammals Research _ Elk Management _ Technical Support for Elk and Vegetation Management for Rocky Mountain National Park - Environmental Impact Statement Period Covered: July 1, 1999 - June 30, 2002 Author: Dan L. Baker, Ph.D. Personnel: M. Wild, T. Nett, D. Finley, M. Conner, 1. Ritchie, L. Wheeler, E. Jones, D. Hussain ABSTRACT Fertility control offers a potential alternative to traditional methods for regulating the growth of overabundant wild ungulate populations. However, current technology is limited due to practical treatment application, undesirable side-effects, and economic considerations. A promising non-steroidal, non-immunological approach to contraception involves potent GnRH agonist. During 1999-2002, we conducted a series of experiments to evaluate the effectiveness of a GnRH agonist (leuprolide) as a contraceptive agent in captive female elk. In experiment 1, we determined the optimum dose ofGnRH agonist treatment by measuring serum luteinizing hormone (LH) and progesterone (P4) response of female elk to 4 formulations of leu pro lide administered as subcutaneous bioimplants. In experiment 2, we evaluated the effects of leuprolide on elk pregnancy rates, duration of suppression of LH and P 4 secretion, and short-term behavioral and physiological side-effects. In experiment 3, we evaluated the effects ofleuprolide on pregnant elk, and in experiment 4, assessed the potential for delivering leuprolide remotely in a syringe dart. All concentrations ofleuprolide were equally effective in reducing serum LH and P 4 to non-detectable levels for the duration of the 130 day experiment. Leuprolide administered prior to the breeding season was 100% effective in preventing pregnancy in treated females. Serum LH and P 4 concentrations were reduced to baseline levels by day 92 and remained at these levels for 195-251 days posttreatment with a return to pretreatment concentrations the following breeding season. Reproductive behavior rates were similar for treated and untreated elk for all behavior categories for both the breeding and postbreeding seasons. Hematology and blood chemistry parameters of treated and untreated females were similar and seasonal intake and body weight dynamics appeared normal. Initial results indicate that leuprolide can be effectively delivered in a syringe dart but additional research is needed to confirm these observations. Thus, we conclude that leuprolide is a safe, effective contraceptive agent and has the potential for suppressing fertility in female wapiti for one breeding season. ��171 TECHNICAL SUPPORT FOR ELK AND VEGETATION MANAGEMENT FOR ROCKY MOUNTAIN NATIONAL PART ENVIRONMENTAL IMPACT STATEMENT Dan L. Baker P. N. OBJECTIVE Conduct captive elk experiments to implement fertility control as an alternative for managing elk in Rocky Mountain National Park. SEGMENT OBJECTIVES 1. Develop and test a reversible contraceptive agent for free-ranging elk. 2. Determine the duration of effectiveness of a selected contraceptive agent in captive elk. 3. Assess contraceptive effects on pregnancy, and behavioral and physiological side-effects in captive elk. 4. Develop and test a remote delivery system for administering the contraceptive agent to free-ranging elk. INTRODUCTION Overabundant wild ungulate populations have become a significant problem for natural resource managers in North America. Unregulated populations can cause adverse effects that are ecological, economic, or political in scope and resolving these issues often requires controlling animal abundance (Jewell and Holt 1981, Garrott et al. 1993, McCullough et al.1997, Smith 2001). In Rocky Mountain National Park (RMNP), Colorado, the impact of herbivory by elk has emerged as a fundamentally important problem for those who manage the Park and its wildlife (Hess 1993, Zeignefuss et al. 1996). In 1968, RMNP adopted a natural-regulation policy for management of ungulates (Cole 1971, Houston 1971) with the objective of allowing density dependent processes to regulate elk numbers within park boundaries and use sport hunting to harvest as many animals as possible in areas surrounding the Park. Recently, however, Park managers have become concerned that possible unnatural concentrations of elk may be altering natural plant communities and ecosystem sustainability. Soil conditions and the status of willow and aspen plant communities have declined. Wet meadow, dry grasssland, and alpine and subalpine sites show evidence of deterioration from overgrazing by elk (Singer et al. 1998, White et al. 1998). As a result of the decline in these vegetation types and the diversity of the animal species that are associated with them, the Park and other natural resource agencies are evaluating alternative management strategies for reducing elk densities within RMNP and the surrounding Estes Valley. One alternative being considered is controlling the fertility of female elk. Fertility control has been widely advocated as an alternative to lethal methods of population control for wildlife and considerable research has been directed toward development of different contraceptive agents (see reviews by Kirkpatrick and Turner 1985, Fagerstone et al. 2001). Field and laboratory studies have evaluated the efficacy of delivery of contraceptives to ungulates (Jacobsen et al. 1995, DeNicola et al. 1997, �172 Kirkpatrick et a1. 1997) and models have been developed to represent effects of fertility control on the population dynamics of individual species and populations (Garrott and Siniff 1992, Seagle and Close 1996, Hobbs et al. 2000). To date, most contraceptive research for wild ungulates has focused on the development of immunocontraceptive vaccines and steroidal hormonal agents. However, after more than 40 years of research, the success of these approaches have been primarily limited to captive wildlife and small localized urban populations of wild ungulates. To meet this challenge, new technologies and approaches are needed if fertility control is to become practical and acceptable management tool for controlling overabundant wildlife species. A promising new non-steroidal, non-immunological approach to contraception involves potent analogs of gonadotropin-releasing hormone (GnRH). GnRH is a molecule produced in the hypothalamus of the brain. It directs specific cells in the pituitary gland to synthesize and secrete two important reproductive hormones; follicle stimulating hormone (FSH) and luteinizing hormone (LH). These latter two hormones, known as gonadotrophs, control the proper functioning of the ovaries in the female and testes in the male. Chronic treatment with continuous, high doses of GnRH agonists results in temporary suppression of pituitary responsiveness and gonadotropin secretion. Resulting decreases in plasma LH and FSH in females leads to suppression of ovulation, estrus cyclicity, and gonadal steroidogenesis (Belchetz et al.1978, Evans and Rawlings 1994). Once GnRH agonist treatments are terminated, normal pituitary function is gradually restored (Bergfeld et al. 1996). GnRH agonists have been shown to inhibit ovulation in several domestic ungulate species including sheep (McNeilly and Fraser 1987), cattle (D'Occhio et al. 1996, D'Occhio and Aspden 1999), and horses (Montovan et al. 1990). However, studies on wild ungulates are limited (Becker and Katz, 1995; Brown et al. 1999) and none have demonstrated their effectiveness as a contraceptive agent. GnRH agonists provide a potential biotechnology for achieving a controlled, reversible suppression of fertility in both captive and free-ranging female wild ungulates. However, their practicality as a contraceptive agent is dependent on effective inhibition of reproduction without negative behavioral or physiological side-effects. During 1999-2002, we conducted a series of experiments with sustained release formulations of GnRH agonist in captive female elk to evaluate these factors. Specifically, our objectives were: (1) to evaluate the effectiveness ofGnRH agonist in preventing pregnancy, (2) to determine the duration ofGnRH agonist suppression ofLH and progesterone (P4) secretion, (3) to assess the behavioral and physiological side-effects (if any) of GnRH agonist treatments, and (4) '.to develop a remote delivery system for . administering the contraceptive agent to free-ranging animals. MATERIALS A. Experiment AND METHODS 1: Dose response 1. Objective Determine the minimum effective dose of GnRH agonist (leuprolide) that will induce halfmaximal release of luteinizing hormone in female elk during estrus and evaluate duration of effectiveness. �173 2. Methods We determined the optimum dose ofleuprolide (desGlylO-D-Leu6-LH-RH ethylamide acetate) required for suppression of serum LH secretion in 8 female elk (6-12 years of age; 240-300 kg). Females were monitored for occurrence of oestrus cycles by measuring serum progesterone concentrations at weekly intervals beginning 1 November 1998 and were considered reproductively active when concentrations were greater than 1 ng ml" for two consecutive sampling periods (Adam et al. 1985). Females were randomly selected to receive one of four doses (0, 45, 90, 180 mg leuprolide acetate) of 90 day sustained release leuprolide formulation using the ATRIGEL ® drug delivery system (Atrix Laboratories, Inc. Ft. Collins, CO, USA) (Dunn et al.l994). These formulations at lower doses have demonstrated a sustained release and activity in rats and dogs for a period of at least 90-120 days (Ravivarapu et al. 2000). On the day before treatment application, animals were moved from paddocks, weighed (± 0.5 kg), moved to individual isolation pens (5 xl0 m), sedated with xylazine hydrochloride (Rompun; Bayer AG, Leverkusen, Germany; 25-200 mg animal" i.m.) and fitted nonsurgically with indwelling jugular catheters. Sedation was reversed with yohimbine (30 mg) (Antagonil", Wildlife Laboratories, Fort Collins, CO, USA). The sampling period began the next day (20 November 1998) at 0900. A patch of hair (3 em in diameter) was shaved in the shoulder region of each female (controls did not receive a placebo formulation) and leuprolide formulations were injected under the skin using an 18 gauge needle and 3 cc syringe. Blood samples (5 ml) were collected at 0, 60, 120, 180,240,300,360,480 min, then at 12,24,36,48, 84, and 240 h postinjection. Catheters were flushed daily with sterile saline solution. Following the last blood collection, catheters were removed and animals returned to 5 ha paddocks. We compared the effective duration of leu pro Iide treatments by measuring pituitary responsiveness to an exogenous dose ofGnRH analogue (D-Ala6-GnRH-Pr09-ethylamide; Sigma Chemical Co., St. Louis, MO) administered at 35, 70, 110, and 130 days posttreatment. Animal handling and blood sampling protocols were similar to those previously described. We administered a previously determined dose (Baker et al. 1995) ofGnRH analog (1 f.1-g 50 kgBW-l) through the jugular cannula and collected blood samples at 0,30,60,90, 120, 180,240,300,360, 420, and 480 min postinjection. After collection, blood was held at 4 ° C for 24 h until serum was obtained by centrifugation. Serum was then stored at - 20° C until analyzed for LH. B. Experiment 2: Antifertility and behavioral effects on nonpregnant female elk 1. Objectives a. Determine the effectiveness of GnRH agonist in preventing pregnancy in female elk b. Determine the duration ofGnRH agonist suppression ofLH and P4 secretion c. Evaluate the behavioral and physiological side-effects (if any) of GnRH agonist treatments. 1. Methods We evaluated the effects of the optimum dose of leuprolide formulation established in Experiment 1, on elk pregnancy rates, duration of suppression ofLH and P 4 secretion, blood chemistry, and reproductive behavior during 2 November 1999 to 15 May 2000. Fourteen adult female (7-13 years of age; 240-320 kg) and 3 adult male elk (4-13 years of age; 375- 400 kg) �174 were used in this experiment. Females were assigned to one of 3 experimental groups based on their tractability for handling and blood sampling. Four elk cows (Group A) were treated with 32.5 mg of leuprolide and 5 cows (Group B) served as untreated controls and were used to compare pregnancy rates, blood chemistry, and reproductive behavior to those of treated females. These two groups of females were maintained together with 3 adult male elk in adjoining paddocks (2-ha each). The remaining 4 females (Group C) served as untreated, non-pregnant controls and were placed in a separate pasture (1 ha) without direct contact with male elk. We compared LH and progesterone secretion of these females to those treated with leuprolide (Group A). a. Pregnancy rates, hormonal measurements, and blood parameters. We determined the effects of leuprolide on pregnancy rates of treated and untreated elk by measuring pregnancy-specific protein B (PSPB)(BioTracking, Moscow, Idaho, USA) in serum at about 70, 160, and 215 days of gestation (Huang et al. 2000). We compared the effects of leuprolide on extent and duration ofLH and P 4 suppression in treated and untreated, nonpregnant elk during 2 November 1999 to 11 November 2000. GnRH challenge trials were conducted prior to application ofleuprolide treatments and at 30,90, 145, 180,225,250, and 373 days posttreatment. The fmal GnRH challenge trial was conducted to assess reversibility of treatment. Protocol for GnRH challenge trials followed procedures previously described in Experiment 1. We assessed physiological side-effects ofleuprolide by comparing serum chemistry, hematology, and body weight dynamics of treated (Group A) and untreated, non-pregnant elk (Group C). Blood collections and body weight measurement were made in conjunction with GnRH challenge trials. Blood samples for hematology and serum chemistry analysis were collected at 90 days posttreatment then submitted for analysis to Colorado State University, Veterinary Teaching Hospital, Clinical Pathology Laboratory, Fort Collins, Colorado, USA. Serum chemistry profiles were obtained using a Hatachi 917 auto analyzer (RochelBoehringer Mannheim, Indianapolis, Indiana, USA) for the following parameters: glucose, creatinine, phosphorus, calcium, magnesium, total protein, albumin, globulin, albumin/globulin ratio, bilirubin, creatinine kinase, aspartate aminotransferase, gamma-glutamyltransferase, sorbitol dehydrogenase, sodium, potassium, chloride, and biocarbonate. Values for the following hematological parameters were obtained using an ADVIA 120 auto analyzer (Bayer Corporation, Tarrytown, New York, USA): nucleated cells, neutrophils, lymphocytes, monocytes, eosinophils, plasma protein, erythrocyte, hemoglobin, packed cell volume, mean corpuscular volume, mean corpuscular hemoglobin concentration, platelets, and fibrinogen. b. Reproductive behavior. The effectiveness of the leuprolide formulation as a contraceptive agent is dependent upon suppression of ovulation and steroidogenesis for the duration of the breeding season. Thus, we tested 2 hypotheses relative to the effects of leuprolide on reproductive behavior of elk: (I) because leuprolide was expected to suppress gonadotrophin secretion and ovulation, we predicted that sexual interactions during the breeding season would be reduced in leuprolide treated females (Group A) compared to untreated controls (Group B), and (2) since depletion of the leuprolide implant (90 days) was expected prior to anoestrus (late March), we predicted that behavioral oestrus would resume in treated females (Group A) and the rate of sexual interactions would be higher than that for untreated controls (Group B) �175 To test these hypotheses, we examined the effects of leuprolide on reproductive interactions of male and female elk during 2 time periods; breeding season (defined as the period 10 November - 23 December 1999) and postbreeding season (defined as the period 7 February27 March 2000). On 2 November 1999, female elk in Group A were treated with leuprolide and released with untreated controls (Group B) into adjoining paddocks (2 ha each). Seven days later (10 November), we placed 3 adult male elk with these groups and initiated behavioral observations. All females were individually identified with color/numeric-coded neck collars. Animals selected as treatments and controls were unknown to observers. Behavioral measurements were made from a distance of 50-250m from an elevated tower (10 m) situated between adjacent pastures using binoculars and a spotting scope during the day, and a spotlight and night vision scope at night. We recorded selected behaviors using a laptop computer with a behavioral software program. We used focal animal sampling procedures to sample reproductive behaviors of all experimental animals over a 24 -hour period (Lehner 1996). Preliminary observations indicated that elk were most active in moming (0500-0800), late day (1400-1700) and night (2000-2400). Thus, time-of-day sampling periods were randomly assigned each week using a randomized block design. Each sampling period consisted of at least two hours of continuous observations. Based on previously reported elk breeding behavior (Morrison et al. 1960, Geist 1982, Rapley 1985), we identified and recorded 19 sexual interactions. Because sample sizes were small, we grouped individual behaviors into 4 general categories: male copulatory, male precopulatory, female precopulatory, and general breeding (Table 1). Copulatory, male precopulatory, and general breeding were interactions of a male directed toward a specific female, while female precopulatory behaviors were actions of a specific female towards a male. Thus, our experimental unit for analyses was the individual female in each breeding group. Behavioral interactions were generally short duration «30 sec) relative to sampling interval, therefore we recorded the number of occurrences of each event rather than length of time and calculated sexual interaction rates as acts per animal per hour, then multiplied hourly behavioral rates by 24 for a daily rate. Table 1. Description of elk reproductive behavior and associated behavior categories. Behavior category Reproductive behavior General breeding : Male directed behavior related to establishing, maintaining, and defending a group or harem offemale elk (e.g. herding guarding, tending) Male precopulatory Male courtship behavior directed toward an individual female to induce or detect oestrus or ovulation (e.g. urine testing, flehmen, tongue flick, lick, smell, or rub female's body, chivy) Female precopulatory Female courtship behavior directed toward dominant male to arouse copulatory behavior (e.g. lick and rub male, mount, lordosis, twitch hocks) Copulatory Male behavior directed toward a receptive female in oestrus (e.g. precopulatory mounts, intromission, pelvic thrust) ---------------------- �176 c. Hormone radioimmunoassay. Serum concentrations ofLH were quantified by means of an ovine (0) LH RIA (Niswender et al. 1969). Elk serum was demonstrated to inhibit binding of 125I-oLHto LH antiserum in a parallel manner. Likewise, when varying quantities of oLH standard (NIH-OLH-S24) were added to elk serum and samples were subjected to RIA, the values obtained were increased by the quantity of oLH added (,-2 = 0.99, slope = 0.92, SEb = 0.22, P = 0.002). These data indicate that the radioimmunoassay (RIA) provided a quantitative assessment ofLH in elk serum. The limit of sensitivity of the LH assay was 0.4 ng ml'. Serum concentrations of progesterone were determined by RlA (Niswender 1973). Sensitivity of the progesterone assay was 0.12 ng ml". Intra- and inter-assay coefficients of variation for each of these assays were less than 10%. d. Statistical analysis. Hormone concentrations are reported as untransformed arithmetic means ± standard error of the mean (SE). Responsiveness of the pituitary to GnRH analog challenge was assessed in two ways: 1) maximum response (highest concentration ofLH (ng ml") achieved postinjection minus baseline), and 2) total amount ofLH secreted (ng ml' min-I) estimated by calculating the area under the LH response curve (Abramowitz and Stegun 1968). We analyzed differences among hormone levels using least squares analysis of variance for general linear models (SAS Institute 1993). Responses to treatments were analyzed with one-way analysis of variance for a randomized complete block design with repeated measures structure. Levels of leuprolide formulations were treatments; individual animals were blocks. Factors in the analysis were dose and time. Treatment effects were tested using the animal-within-treatment variance as the error term. Time was treated as a within-subject effect using a multivariate approach to repeated measures (Morrison 1976). A "protected" least significant difference test (Milliken and Johnson 1984) was used to separate means when the overall F-test indicated significant treatment effects (P < 0.05). We tested specific reproductive behavior hypotheses that mean behavior rate was not different between treatment and control groups for both the breeding and postbreeding seasons using an ANOV A model with a repeated measures structure. Similar to the hormonal analysis, time was treated as a within subject effect using multivariate approach to repeated measures (Morrison 1976). To test for treatment effects, we accounted for time-of-day, date effects and their interactions. PROC GENMOD (SAS Institute 1993) was used to estimate and test for differences in mean behavior rate by treatment, time-ofday, and date. Means and standard errors were estimated using least squares, and hypothesis tests were based on type III generalized estimating equations that accounted for correlation in repeated measurements. D. Experiment 3: Antifertility effects on pregnant elk 1. Objectives a. Evaluate the effects ofGnRH agonist (leuprolide)on female elk treated during the first trimester of pregnancy. b. Assess nutritional, physiological, or behavioral side-effects that might result from treatment. �177 2. Methods a. Animals. We conducted controlled experiments with 12 adult female elk and 2 adult male elk at the Colorado Division of Wildlife's Foothills Wildlife Research Facility (FWRF), Fort Collins, Colorado during September 1,2000 to December 15, 2001. On September 1,2000, two intact male elk were released with 12 female elk. The purpose of mating was to confirm the reversibility of leuprolide from previous experimental treatments (Baker et al. 2002, in press). Pregnant animals from this mating would then provide the experimental elk for the experiment described in this study plan. b. Treatments. Approximately 60 days postconception (1 December for cows at FWRF), all females were evaluated for pregnancy and fetal age determined using transrectal ultrasonography (Willard et al. 1994). Using ultrasound and selected measurements reported for known-age embryos (Morrison et al. 1959), we estimated fetal ages of all pregnant elk. Eight elk with embryos estimated to be 60-75 days old were randomly selected to receive a subcutaneous implant containing 32.5 mg ofleuprolide formulation. Leuprolide was injected subcutaneously on the lateral thorax using an 18 g x 4 em needle. The remaining four pregnant elk were designated as untreated controls. Treatment and control elk were maintained in the same pastures, fed similar diets, and handled similarly throughout the study. All treatments were applied without tranquilization by moving elk from 5 ha pastures to individual isolation pens, then into a restraining chute, where treatments were applied, then returning elk back into 5 ha paddocks. Animals were observed daily by trained caretakers for general health and for signs of abortion or parturition. c. Sample size. Based on previous reproduction studies with captive elk at FWRF, 4-6 elk per treatment is the minimum sample size needed to provide biologically significant differences among treatment means (Baker et al. 1995, Baker et al. 2002, in press). We used an unbalanced experimental design to minimize the number of untreated pregnant control elk, since most neonates will be euthanized. Pregnant, control elk were needed to insure that treatment results were not biased due to handling procedures, and/or other uncontrolled variables. d. Measurements 1) Pregnancy Rates. We assessed contraceptive effectiveness by determining pregnancy status of all experimental elk. Using transrectal ultrasonography (Willard et al. 1994, 1998 ), we determined pregnancy rates of treated and control elk prior to treatment, and at 60, and 120 days posttreatment. On the day of pregnancy assessment, elk were moved from 5 ha pastures to a handling chute where they were sedated with xylazine hydrochloride (20-200 mg/animal, 1M), then scanned using real-time transrectal ultrasound to determine pregnancy status and/or fetal age. Elk were then reversed with yohimbine (0.125 mg/kg, N) and returned to their original pastures. We determined the reversibility of leuprolide by releasing a epididymectomized male elk with treated female elk in October 2001 and conducting a GnRH challenge trial (Baker et al. 1995) to measure LH and P4 levels. 2) Reproductive Behavior. The effects ofleuprolide on the breeding behavior of captive elk treated prior to the breeding season is known (Baker et al. 2002, in press), however, these reported effects mayor may not be extended to elk treated during early pregnancy. �178 Down-regulation of gonadotroph cells by the action of leu pro lide and subsequent reduced secretion ofLH could effectively inhibit progesterone secretion by the corpus luteum. If the effective action of leuprolide is luteolytic, then early embryonic loss could occur (Plotka et al. 1982, Asher et al. 1988, Flint et al. 1991). However, the efficacy of induction of luteolysis by leuprolide in Cervidae is unknown. Furthermore, it's not known if following early embryonic loss, whether female elk will regain normal estrus cycles and behavior. We evaluated these potential behavioral side-effects by monitoring maintenance and breeding behavior of male and female elk before and after leuprolide treatments. Each animal was individually identified using color-coded neck bands or ear tags. We tested the null hypothesis that the frequency of sexual interactions between males and females is similar before and after contraceptive treatment. e. Statistical Analysis. We analyzed data using least squares ANOV A for General Linear Models and the SAS Interactive Matrix Language. Response to contraceptive treatment was analyzed with a two-way factorial analysis of variance for a randomized complete block design with repeated measures structure. Factors in the analysis were treatment and time .. Treatment was tested using the animal-within-treatment variance as the error term. Time was treated as a within subject effect using a multivariate approach to repeated measures. We used orthogonal contrast to test for differences among individual means (Morrison 1976). E. Experiment 1. 4: Development of a remote delivery system Objective. Begin evaluating a remote delivery system by comparing effectiveness of subcutaneous and intramuscular administration of leuprolide formulation in suppressing reproduction in female elk. 2. Methods. a. Animals and treatment. We conducted a controlled experiment with 13 adult female elk (713 years of age; 250-300 kg), lintact male elk, and 1 epididymectomized male elk at the Colorado Division of Wildlife's Foothills Wildlife Research Facility (FWRF), Fort Collins, Colorado during 15 August 2001 to 28 March, 2002. Between 15 August and 1 September, 2001, the epididymectomized male elk was released with 13 adult female elk into 2 adjoining paddocks (2 ha). Females were monitored for occurrence of estrus cycles by measuring progesterone levels beginning 1September 200 land were 'considered reproductivelyactive when concentrations were greater than 1 ng/ml. Treatments were assigned as follows: 3 females were randomly selected to receive a subcutaneous formulation ofleuprolide (32.5 mg)(ATRlGEL, Atrix Laboratories, Inc. Fort Collins, Colorado, USA) by syringe injection; 3 elk were selected to receive an intramuscular leuprolide formulation (32.5 mg) via syringe injection; 4 elk received the leuprolide formulation via a 1 cc, PneDart dart (16 gauge, 3.39 em. needle) fired from a CO2 - powered Dan-Inject pistol, and 3 elk were designated as untreated controls. Treatments were applied as follows. On the day before application (6 September 2001), experimental elk were moved from pastures to individual isolation pens (5 m x 10 m), weighed (± 0.5 kg), sedated with xylazine hydrochloride (Rompun; Bayer AG, Leverkusen; 25-200 mglanimal, i.m) and fitted nonsurgically with indwelling jugular catheters. The next day, treatment and placebo treatments were administered. In order to accurately determine the precise dose of leuprolide formulation remotely delivered to each elk, syringe darts were �179 weighed (0.001 g) before and after injection. Prior to darting, elk were placed in a handling chute and lightly sedated with xylazine hydrochloride (15-20 mg/animal, i.v.). This dose allowed animals to remain standing in the chute and minimized excitation associated with discharge of the dart gun. With the exception of two animals, one dart per animal was fired from approximately 3 meters into the middle gluteus maximus muscle of the standing elk. Once all elk had been treated, sedation was reversed with yohimbine (30 mg) (Antagonil", Wildlife Laboratories, Fort Collins, Colorado, USA) and animals were returned to individual isolation pens. b. Measurements. Approximately 1 hour following treatment applications, we measured 24hour LH response of elk treated with the leuprolide formulation and untreated control elk. Blood samples (5 ml) were collected via jugular catheters at 0, 120, 180,240,300,360,480 min then at 10, 16, and 24 hr after injection. Catheters were flushed after each collection with sterile saline solution. After the last blood collection, catheters were removed and animals returned to 5 ha pastures. The effect of leuprolide formulation on the duration of suppression of LH was determined by periodically conducting pituitary stimulation trials. These trials were conducted during 29 October 2001 to 28 March 2002 to determine the capability of LH cells to respond to stimulation with an exogenous dose ofGnRH analog (D-Ala6-GnRH-Pro9ethylamide; Sigma Chemical Company, St. Louis, Missouri, USA). Pituitary stimulation trials were conducted with treated and control elk at 30,60,90, 120, 160, and 190 days posttreatment. Stimulation trials were conducted according to the following procedures: On the day of testing, treated and control elk were moved from 5 ha pastures to individual isolation pens, weighed, sedated (as previously described), and fitted nonsurgically with indwelling jugular catheters. GnRH analog (1 J-lg/50 kg body weight) was administered through the cannula and blood samples were collected (5 ml) at 0, 60, 120, 180,240,300, 360, and 480 minutes posttreatment. After collections, blood was stored at 4° C for 24 hours until serum was obtained by centrifugation (1500 RCF for 15 minutes). Serum samples for progesterone levels were also collected from each elk on each of these trial days. Serum was stored at -20° C until analyzed for LH and progesterone. Following the last blood collection, catheters were removed and elk were returned to the holding pastures. The effect of leuprolide formulation on reproduction in treated and control elk was determined by measuring pregnancy rates using the presence or absence of pregnancy specific protein B (PSPB) (BioTracking, Moscow, Idaho, USA) in serum collected at approximately 100 and 215 days of gestation (Huang et al. 2000). c. Statistical analysis. Responsiveness of the pituitary gland to GnRH analog. stimulation was assessed in two ways: (1) maximum response (highest concentration ofLH (ng/ml) achieved after injection minus baseline), and (2) total amount of LH secreted (ng/ml/min) estimated by calculating the area under the LH response curve (Abramowitz and Stegun, 1968). Differences among hormone concentrations were tested using least squares ANOV A for general linear models (SAS Institute, 1997). Responses to treatment were analyzed with oneway ANOV A for a randomized complete block design with repeated measures. Treatment effects were determined using the total animal-within-treatment variances as the error term. Time was treated as a within-subject effect, using a multivariate approach to repeated measures (Morrison 1976). A "protected" least significant difference test (Milliken and Johnson, 1984) was used to separate means when the overall Ftest indicated significant treatment effects (P < 0.05). �180 RESULTS A. Experiment 1: Dose response Administration of sustained release formulations of leuprolide to female elk resulted in an acute, transient rise in serum LH concentrations irrespective of dose. Maximum LH concentrations (15.6 ± 0.93 ng ml") occurred approximately 3 hours following treatment arid were similar across all treatment levels (Fig. 1). Following peak response, there was a rapid decline in LH to basal levels during the next 24 hours. Total LH secretion (ng ml' min-I) did not differ among treatments and all treatments resulted in higher LH secretion than controls (P s 0.002). Leuprolide reduced serum LH secretion to nondetectable levels in treated females for 130 days posttreatment (Fig. 2). Differences in mean maximum serum LH were significantly lower (P ~ 0.031) in treated elk compared to untreated controls at all sampling periods. For untreated females, mean maximum LH fluctuated from a high of 19.3 ± 4.2 to a low of 3.5 ± 0.06 ng ml". This variation was likely related to the phase of the oestrous cycle when control females were challenged with GnRH and the influence of fluctuating levels of estradiol and progesterone on LH secretion (Goodman and Karsch 1980). B. Experiment 2: Antifertility and behavioral effects on nonpregnant female elk a. Pregnancy rates, hormonal measurements, and blood parameters. Because Experiment 1 did not establish a minimum effective dose of leuprolide for LH suppression, we arbitrarily reduced the leuprolide formulation by approximately 20% below the lowest concentration tested in Experiment 1, to 32.5 mg. This dose of leu pro lide prevented pregnancy in all treated females (Group A) while the pregnancy rate of control females (Group B) was 100%. Treated females tested negative and controls positive for PSPB on all sampling dates. Estimated conception dates for pregnant elk ranged from 10 Novemberto 19 November 1999 and parturition occurred between 12 July and 26 July 2000. Leuprolide caused a significant reduction (P ~ 0.035) in mean maximum serum LH (Fig. 3) and P4 (Fig. 4) concentrations in treated females (Group A) with a return to pretreatment levels the following breeding season (11 November 2000). Serum LH was reduced to non-detectable concentrations by 92 days posttreatment and remained at this level until day 225. In one treated female, LH remained at baseline for 250 days posttreatment. Maximum LH response was lower (P ~ 0.012) in treated compared to non-pregnant controls (Group C) at 30,92, 135, 165, and 193 days following treatment. Serum LH of untreated elk declined significantly (P = 0.024) between April and May with the onset of anestrus, then returned to pretreatment levels indicative of estrus in November 2000. . Serum P4 levels of treated females followed a similar pattern to that observed for serum LH (Fig. 4). Progesterone levels were similar in treated and control elk until day 30, thereafter, serum progesterone remained at basal concentrations in treated females until day 225 of the trial, indicating that additional ovulations did not occur. Control females maintained increased serum P 4 content, reflecting continued regular estrous cycles within this group until day 165 (18 April) when the effects of anestrus reduced P4 to basal levels. Similar to serum LH, P4 content then increased during November 2000 to pretreatment concentrations in both treated and untreated elk (Fig. 4). We evaluated 13 hematology and 19 serum chemistry parameters in treated and untreated elk females. With the exception of creatinine kinase (CK), a muscle derived enzyme, all individuals were clinically similar. Elk in the treatment group showed moderately elevated CK levels (400-702 IV L-I). Creatinine kinase levels can increase in unconditioned animals following vigorous exercise and remain elevated for 4-6 hours (Lefebvre et al. 1994). Handling procedures for blood sampling in treated females were often �181 more physically rigorous than those for controls due to the need to separate females from males. Thus, the elevated CK levels in treated elk compared to controls likely reflect a bias due to a difference in animal handling prior to blood sample collections, rather than a treatment-induced response. b. Reproductive behavior. We observed male to male dominance interactions immediately following their release into the pastures with treated and untreated females. Within 2.5 weeks, one male established dominance over the other two. Thereafter, subdominant males retreated to remote locations in the pastures and rarely interacted with females or the dominant male for the remainder of the experiment. During the breeding season, we observed reproductive interactions of males and females on 34 days during 10 November to 23 December 1999. We analyzed 63 sampling periods (134.5 h): 20 periods at dawn (45.7 h), 6 at mid-day (13.5 h), 20 at dusk (42.8 h), and 17 at night (32.6 h). The average length of the observation periods was 2.1 (SE = 0.10) h. Postbreeding observations occurred on 14 days during 7 February to 27 March. We analyzed data from 16 sampling periods (54.7 h): 6 periods at dawn (22.5 h), 2 at mid-day (7.5 h), 7 at dusk (22.2 h), and 1 at night (2.5 h). Observation periods averaged 3.4 (SE = 0.24) h. Contrary to our first hypothesis, sexual interactions during the breeding season were not diminished in leuprolide-treated females compared to controls. Instead, breeding behavior rates were similar for treated and untreated females for all behavior categories (Fig. 5). Although we did not detect a significant treatment x time interaction, copulatory (P = 0.064), male precopulatory (P = 0.083), and female precopulatory (P = 0.072) behaviors approached significance and are notable. For these 3 behavior categories, the daily behavior rate decreased over time for untreated females, but remained constant for treated elk. We also failed to reject our second hypothesis. Treated females did not resume normal oestrus cycles during the postbreeding season and reproductive behavior rates did not increase compared to untreated controls. We observed almost no sexual interactions between the dominant male and treated or untreated females during the postbreeding season. There were no copulatory or female precopulatory behaviors recorded, and too few male precopulatory (s 0.l7 day") and general breeding (:;; 0.30 day') behaviors to analyze. C. Experiment 3: Antifertility effects on pregnant elk. Leuprolide administered has a 32.5 mg subcutaneous formulation to elk during the first trimester of pregnancy failed to induce fetal loss. Fetal age at the time of treatment of treated females ranged from 30 - 90 days of age and from 50 - 90 days for control elk. Treated and control females were positive for PSPB at all sampling dates during gestation and all produced a calf at parturition. Dystocia was observed in 3 of 6 females but did not appear to be related to treatment. During the breeding season reproductive behaviors were similar (P = 0.45) for treated and control female elk. We observed almost no sexual interactions during the postbreeding season. D. Experiment 4: Development of a remote delivery system. Administration of a 90-day sustained release formulation of leuprolide to female elk resulted in an acute, transient rise in serum LH levels irrespective of mode of delivery (Fig. 6). Maximum LH concentrations occurred approximately 3.5-4.5 h following treatment and were highest (84.9 ± 5.3 ng/ml) for the �182 intramuscular syringe treatment, followed by intramuscular dart (42.2 ± 15.8 ng/ml) and subcutaneous syringe (23.0 ± 5.1 ng/ml). Following peak response, there was a rapid decline in LH basal levels during the next 24 hours. Leuprolide reduced serum LH secretion to non-detectable levels in all treatment groups for 120 days posttreatment. Between 120 and 160 days posttreatment, LH levels in the intramuscular syringe and dart treatments increased substantially over the subcutaneous syringe treatment and control females and remained elevated for the duration of the experiment. In contrast, LH levels for the subcutaneous syringe group remained at basal levels (Fig. 6). Serum P4levels followed a different pattern than that observed for serum LH (Fig. 7). After 60 days posttreatment, P4 concentrations in all treatment groups declined to basal levels and remained at these levels for the remainder of the experiment. Regardless of mode of delivery, leuprolide formulation prevented pregnancy in all treatment groups, whereas pregnancy rate of control females was 100%. Leuprolide-treated females tested negative and controls positive for PSPB on both sampling dates. DISCUSSION Successful application of fertility control technology for wildlife is dependent on development of contraceptive agents that are safe, practical, and effective. Current technology is limited due to problems of treatment implementation and concerns for the health of target and non-target species. In the present study, we evaluated a promising non-steroidal, non-immunological contraceptive technology for controlling fertility in female elk. Administration of a sustained release formulation containing leuprolide to captive female elk prior to the breeding season, resulted in decreased LH and progesterone secretion, temporary suppression of ovulation and steroidogenesis, and effective contraception without detrimental behavioral or physiological side-effects. The acute increase in serum LH immediately following leuprolide treatment was consistent with previous studies in cattle (D'Occhio et al. 1996), sheep (Nett et al. 1981), horses (Montovan et al. 1990) and African elephants (Loxodonta africana) (Brown et al. 1993). There was little variation among elk in their serum LH response to different doses ofleuprolide, indicating either low variability in the amount and duration of agonist released or doses so high that any variation was masked. The minimum level of leuprolide needed to suppress estrus in female elk was not determined in this study. All doses of leuprolide were equally successful in reducing LH concentrations for the duration of the 130 trial. Additional research to establish a minimum effective dose of leupro Iide would enhance the economic practicality of this contracep~iv~ agent. The cessation of estrous cycles in females treated with leuprolide and the return to apparently normal ovarian function after depletion of the agonist implant was consistent with findings for females in other species (D'Occhio et al. 1996; Evans and Rawlings, 1994; Fraser et al. 1989). The effectiveness of leuprolide as a contraceptive agent is dependent on suppression of ovulation from the inception of the breeding season to the onset of anestrus, a period of approximately 200 days for elk. Leuprolide inhibited ovulation for> 190 days, 2 times longer that the formulated 90 day delivery period. The prolonged suppression of gonadotrophin secretion may occur for several reasons. Among these are that release of leu pro lide from the implant may have continued beyond the formulated 90 day period. Certainly, LH secretion remained suppressed for more that 130 days in Experiment l. Likewise, leuprolide treatment may have induced prolonged suppression of gonadotroph function (i.e. extending beyond the duration of the implant). In other ruminants, if gonadotroph function is suppressed for an extended duration.a recovery period of 30-60 days following removal of the suppression is necessary before pituitary content ofLH and gonadotropin secretion can return to normal levels (Nett 1987). Thus, �183 if duration ofleuprolide release from the implant was 130 days and recovery of gonadotroph function requires approximately 60 days, this would be sufficient to carry the reduced secretion of LH into the normal anoestrous period when secretion ofLH would be photoperiodically suppressed. If this is indeed true, then a single treatment should provide a contraceptive effect for approximately one breeding season. The effectiveness ofleuprolide in preventing pregnancy in female elk is conditional. Successful prevention of fertility was achieved by treating elk prior to the breeding season. The use of leuprolide as a contragestive in female elk during early pregnancy was unsuccessful. Since we did not measure LH responses to leuprolide treatment in pregnant elk, the mechanism for failure is unknown. We speculate that complete down-regulation ofLH receptors did not occur and LH levels were high enough to stimulate an LH surge and subsequent ovulation. The overall rates of sexual interactions between treated and control elk were not different during the breeding and postbreeding seasons. During the breeding season, the dominant male established and defended a single harem of treated and untreated females. Reproductive behaviors during the breeding season between the dominant male and harem females followed a pattern similar to that described for free-ranging elk (Geist 1982). Treated and untreated females were courted, bred, and defended with equal frequency, however the pattern of reproductive interactions changed over time. Once untreated females became pregnant, reproductive behavior rates decreased, whereas, copulatory, and male and female precopulatory rates remained constant over time in treated females. These extended sexual interactions were generally intermittent and may have been related to fluctuating levels of progesterone and oestradiol. Estrus can occur with relatively low estradiol concentrations, if coupled with low progesterone content. In domestic sheep, pre-exposure to progesterone stimulates estrus behavior at much lower concentrations of estradiol once progesterone is decreased in circulation (Robinson 1954). Therefore, since these animals had ovulated prior to leuprolide treatment, they became very sensitive to low levels of estradiol, and since ovulation and corpus luteum formation were blocked they continued to show estrus behavior with basal estradiol levels. Regardless of the mechanism involved, disruption of normal behavioral patterns are not a desirable sideeffect of contraceptive treatments. However, without carefully designed large-scale investigations with larger sample sizes, and under more natural conditions, we can only speculate on the significance of these behavioral alterations on the health and social organization of treated populations. Before leuprolide can be considered a practical and efficacious approach for wildlife contraception, development of a reliable remote delivery system is needed. Our pilot efforts to develop such a system were promising, however, the small sample size (n = 3) used in this experiment support only guarded optimism. It appears that the rise in LH levels observed in females treated with syringe dart delivery of leuprolide formulation were not high enough to stimulate ovulation and conception. Clearly, additional research with larger sample sizes is needed to confirm or reject these findings. CONCLUSION The objective of the work reported here was to evaluate the contraceptive potential of a GnRH agonist (leuprolide) formulation in female elk, provide evidence of physiological and behavioral side effects of treatment (if any), and assess the potential for remote delivery. We conclude that leuprolide administered as a controlled release formulation prior to the breeding season, offers a new approach to reversible contraception in wild ungulates that overcomes problems associated with existing technology. �184 First, leuprolide formulation improves practical application of contraception because a single treatment can induce infertility in females without relocating and treating specific individuals each year. Second, leuprolide acetate is a neuropeptide, thus the proteinaceous nature of this agent eliminates the possibility of passage through the food chain to non-target species. Third, behavioral side-effects were minimal. Sexual interactions of treated females were extended early in the breeding season but recurrent estrous cycling and ovulation did not occur. Fourth, there were no short-term physiological side-effects of treatment. Treated animals appeared healthy and seasonal intake and body weight dynamics normal. However, before this technology can be considered a practical and efficacious approach for wildlife, additional research is needed to ascertain minimum effective dose, verify effective treatment duration, and develop a remote delivery system for administering leuprolide formulation to unrestrained animals. ACKNOWLEDGMENTS Our research was supported by the U. S. National Park Service, Rocky Mountain National Park (Grant 1520-9-9002) and the Colorado Division of Wildlife (Federal Aid to Wildlife Restoration, Project 153R4). We thank Dr. Delwar Hussain and Dr. Richard Dunn at Atrix Laboratories, Ft. Collins, Colorado for the generous donation of the leuprolide acetate formulations used in these investigations and for their technical assistance in delivery technology. We gratefully acknowledge and appreciate the technical assistance of Joan Ritchie in overall organization and execution of blood sampling protocols and animal handling. 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Vegetation and elk responses following release from artificial controls within Rocky Mountain National Park, 1968-1996. Report to the Superintendent, Rocky Mountain National Park. �187 Fig.1 20 15 T l- I -1 E .s 0) /t j "!~ / 10 ~i ' # II J :::r:: __j f-- -g I / / ---e-- 90mg -T 180 mg - i \~" / / J> / (g.__ _ Jt:./ ~.•• "1 \ <, T--- 'Y-._ ~-~._ ~ - ::f~ 0 0 45mg '\ 1\ /J.. 1 -k- \\1 j \\ '\ ,'j_/ 5 Omg \ II l- ---- 2 3 4 5 7 6 ~ ---- - 12 24 8 Time (hours) Figure 1. Twenty-four hour profile of serum LH concentrations in untreated female elk (., n = 2) and elk treated with a sustained release formulation containing 45 (A ,n = 2),90 (0, n = 2), and 180 mg (T, n = 2) of leuprolide. Results are shown as ± SE. Fig.2 30 ---- Omg -.0\- - 45 mg -8-- 90mg ~ -1 0) .s 20 :r: _.J E ::::l E 'x ro 2 c ro Q) 2 ) 1.0 / / / \ 1 \ - 180mg I I 1 E -T T 1 \ \ 0 0 .5 1 35 Time (days) 75 110 130 Figure 2. Profiles of 130-day LH concentrations in untreated (., n = 2) female elk and elk treated with a sustained release formulation containing 45 (A ,n = 2),90 (0, n = 2), and 180 mg (T, n = 2) of leuprolide. Results are shown as ± SE. �188 Fig. 3 30 "....._ 25 E Ol c "-' 20 I ~ -, I _J E :J -, 15 E 'xro ~ -, ------- Leuprolide -, '\ _...._....G., - e- - Control 1 1 ~'"1---1\ (r- T 10 \ c \ ro \ Cl) ~ 5 \ 'S-_ .L 0 Pre1rmt 30 92 135 165 193 225 373 Time (days) Figure 3. Profiles of mean maximum serum LH concentrations for untreated female elk (., n = 4), and elk treated with a sustained release formulation containing 32.5 mg leuprolide (0, n = 4). Results are shown as ± SE. Fig. 4 2.40 ----- -& - Control Leuprolide ,........_ E 1.80 Ol c ...__, Cl) c I 1 Q 0 'Cl) 1.20 rJ) Cl) - ---o..._ •... 0 (L c Cil Cl) f 1 T Ol 0.60 . <, T '(Y 1 /~ -> T 1\ / / \ / . \ /J 1 / \ ~ \ \ 0.00 Pretrmt. 30 92 135 165 193 225 373 Time (days) Figure 4. Profiles of mean maximum serum progesterone concentrations for untreated female elk (., n = 4), and elk treated with a sustained release formulation containing 32.5 mg leuprolide (0, n = 4). Results are shown as ± SE. �189 Fig 5 10 ~ '>-. ro -a 8 ~ o .;:; ro 6 ..c _ Control _ Leuprolide ID ..0 ID CU 4 0::: .._ o 's ~ 2 ID CO o Gen. Breed. Male Precop. Female Precop. Copulatory Behavior Category Figure 5. Mean (± SE) reproductive behavior rates during the breeding season for untreated (n = 5) and leuprolide-treated (n = 5) female elk Results are shown as ± SE. Fig. 6 ___._ 90 c» - I 72 E I \ C) c <;» I / 54 _J ..:.::: ro Q) 0... I 36 I c ro Q) ~ 1M Dart I /f if 18 f\ -0-- 1M Syringe --.c- SC syringe ------SJ - Control 120 160 .. \ \ ,/I , \ \ \ \~ I ' 0 0 .5 1 30 60 90 190 Time (days) Figure 6. Profiles of me an maximum serum LH concentrations for untreated female elk (., n = 3), and elk treated with a 32.5 mg leuprolide formulation delivered intermuscularly via syringe dart (0, n = 3), intermuscular syringe (A, n = 3), and subcutaneous syringe (T, n = 3). Results are shown as ± SE. �190 Fig. 7 --e- 1M Dart ,..-... -I.:- - 1M syringe --3f -- SC syringe -e --E 0> c ..........- T --- (i) c ,._ 0 (i) +-' (/) - Control 2 / 1 1 _. T ____ ____ 1 T 1 160 190 • / (i) 0> ~ 0 ,._ 1 o, c ro (i) ~ 0 Pretrmt 30 60 90 120 Time(days) Figure 7. Profiles of mean maximum serum progesterone concentrations for untreated female elk (e, n = 3), and elk treated with a 32.5 mg leuprolide formulation delivered intermuscularly via syringe dart (0, n = 3), intermuscular syringe (.A.,n = 3), and subcutaneous syringe (T, n = 3). Results are shown as ± SE. �191 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 JOB PROGRESS REPORT Stareof ~C~o~l~o~ra~d~o~ _ Mammals Research Work Package ---=:::..30"'-'0"""2"-- _ Elk Conservation T~kNo. _=3 _ Pr~ectNo. W~-~1=53~-~R~-~14~1=5 Estimating Calf and Adult Survival Rates and Preznancv Rates of Gunnison Basin Elk _ Research and Development Period Covered: July 1,2000 - June 30, 2001, and July 1,2001 - June 30, 2002 Author: D. J. Freddy Personnel: D. Cole, N. Gallowich, D. Masden, L. Gepfert, J. Olterman, R. Basagoitia, L. Spicer, B. Carochi, J. Oulton, P. Mason, W_ Brown, V. Organek, J. Young, T. Beck, G. Dekleva, C. Mehaffey, D. Williams, J. Johnston, K. Buffington, K. Fanson, and R. Kahn of CD OW, Dr. G. e. White and Dr. M.e. Conner of Colorado State University, CDOW Gunnison Habitat Partnership Program, and contractors/ cooperators, Helicopters by OZ, Coulter Aviation, USFS, BLM, private land owners, and elk hunters. ABSTRACT We estimated survival rates and pregnancy rates of elk (Cervus elaphpus nelsonii) in the Gunnison Basin of Colorado during 2000 and 2001. During mid-December each year, we captured and radio-collared calves age 6 months and adult females age ~2 years and during November and December each year, we had hunters collect and submit reproductive organs from female elk harvested during laterifle seasons. During winter-spring, survival rates of calves were 0.89 ± 0.08 (CL) (n = 71),0.83 ± 0.09 (n = 75), and 0.86 ± 0.06 (n = 146) for 2000-01,2001-02, and both years combined, respectively. Survival of calves was not different between years (P = 0.2965) or sexes (P = 0.1456) but tended to be different among 3 management DAUs (P = 0.0737) with survival being lowest at 0.78 ± 0.12 in DAU E41. For years combined, 21 calves died with proximate causes of death being 53% predation-related, 24% malnutrition-related, 9% accidents, and 14% unknown causes. In 2000-01, calves tended to die after mid-March while in 2001-02, mortalities occurred from early January through May. Patterns of calf mortalities were not strongly associated with calf body mass. Calf body mass at capture averaged 99.1 ± 2.2 kg, ranged from 52.0 to 133.0 kg, and was not different between years or sexes (P> 0.259), but calves were larger in DAU E-41 (P = 0.003) where calf survival was lowest. Survival rate of adult females age ~2 years was 1.00 during winter-spring as no deaths occurred during 2000-01 (n = 39) and 2001-02 (n = 48) and annual survival was 0.92 ± 0.08 (n = 39) including hunting and other causes of death and 0.97 ± 0.05 (n = 37) including only natural deaths. Survival for yearling female elk, age 12-17 months, during summer-fall was 0.89 ± 0.10 (n = 38) including hunting and other causes of death and 1.00 (n = 34) including only natural deaths. Survival for the same cohort of yearling male elk during summer-fall was 0.86 ± 0.15 (n = 22) including hunting and other causes of death and 0.90 ± 0.13 (n = 21) including only natural deaths. Survival rates for both yearling female and male elk, age 18-23 1 .: j .,.------:----- �192 months, were l.00 (n = 34 F, n = 19 M) during winter-spring as no deaths occurred. Harvest removal rates during summer-fall 2001 were 0.05 for adult females, 0.11 for yearling females, 0.08 for all adult females age ;::12 months, and 0.06 for yearling males. Based on biological collections provided by hunters, pregnancy rate averaged 85% for all adult female elk age;::1 year (n = 89). Conceptions peaked 23 September, spanned 68 days, and followed an expected asymmetrical pattern in timing with 17% of the adult females likely conceiving after 10 October. Litter size was 1 in all uteri with detectable fetuses (n = 69) and female fetuses predominated with fetal sex ratio (37F:2IM) deviating from 50:50 (P = 0.036). Estimated percent total body fat based on kidney fat measurements indicated 65% of the adult females age;::1 year were in moderate, 30% in low, and <5% in very low or very good body condition. Probability (logit(P)) of adult females being pregnant was dependent on estimated percent total body fat (P = 0.033). Measures of reproductive and survival rate parameters were consistent with predictions of performance outcomes for adult female elk having low to moderate body condition status in the fall. More than likely, marginally deficient levels of seasonal nutrition were depressing optimal reproductive performance of adult female elk. All information in this report is preliminary and subject to further evaluation. �193 JOB PROGRESS REPORT ESTIMATING CALF AND ADULT SURVIVAL AND PREGNANCY RATES OF GUNNISON BASIN ELK POPULATIONS David J. Freddy P. N. OBJECTIVE Estimate survival rates of calf, adult female, and adult male elk and estimate pregnancy rates of adult female elk in Gunnison Basin elk populations for 3 years. SEGMENT OBJECTIVES 1. Prepare study plan program narrative. 2. Estimate calf, adult female, and adult male survival rates during winter, December-June. 3. Estimate adult male and female survival rates during summer-fall, June-November. 4. Estimate harvest removal rates for yearling and adult males and females. 5. Estimate pregnancy rates, fetal rates, conception dates, and body condition of female elk collected in December. 6. Summarize data in Research Progress reports and prepare peer-reviewed publications. INTRODUCTION The elk (Cervus eZaphpus neZsonii) resource has many benefits but frequent social, political, and economic conflicts suggest elk can reach "social" ifnot ''biological'' carrying capacities (Freddy et al. 1993). Recent controversy surrounding elk in the Gunnison Basin of Colorado (Roath et at 1999) exemplifies conflicting social and biological agendas regarding appropriate numbers of elk. The core of conflict in elk management often centers on establishing management objectives for numbers of elk that are agreeable to competing interests and then monitoring elk populations to demonstrate that objectives are achieved. This type of conflict is paramount in Colorado Division of Wildlife (CDOW) elk population Data Analysis Units (DAUs) E-25, E-41, and E-43 in the Gunnison Basin where a combination of resource carrying capacity objectives for elk on winter ranges and difficulties associated with knowingly achieving those objectives has fostered argumentative distrust among public groups and . management agencies. Accomplishing management by population objective can depend on reliably estimating elk population size which is expensive and intensive (Samuel et al. 1987, Bear et al. 1989, Unsworth et al. 1990, Anderson et at 1998, Cogan and Diefenbach 1998, Eberhardt et at 1998, Freddy 1998). Alternatively, population size and trend can be estimated using computer models that incorporate harvest, age and sex ratios, and survival rates (White 1992, Bartholow 1999). Model outputs are extremely sensitive to estimates of survival rates such that, reliable measurements of survival can greatly enhance the quality of models (Nelson and Peek 1982). We chose to estimate survival rates of calf and adult elk during winter and adults year-around to aid in developing improved population models for the Gunnison Basin elk. The Gunnison Basin in southcentral Colorado encompasses the entire headwaters of the main Gunnison River and the centrally �194 located town of Gunnison. Between 12-16,000 elk and 8-10,000 mule deer iOdocoileus hemionus) are thought to exist within the Basin. Elk are managed as 3 populations representing DAUs E-25 (Game Management Units [GMU] 66,67), E-41 (GMU 54), and E-43(GMUs 55,551). The 3 DAUs encompass about 9,291 km2 of which 3,648 km2 are considered potential winter range for elk (CDOW WRlS database). DAUs are contiguous with few major geographic barriers separating DAUs that would absolutely prevent interchange of elk among DAUs (see Program Narrative [PN] Appendix I Figure 1). The Basin represents a high altitude, cold winter range for both elk and mule deer which is similar to ecosystems in North Park, Middle Park, and the San Luis Valley, Colorado. The sagebrush (Artemisia tridentata) steppe winter ranges (2,250- 2,700 m elevation) can receive both extreme snow depths and cold temperatures that cause severe mortality among ungulates (Carpenter et al. 1984) while the conifer meadow and alpine summer ranges (3,000 - 4,200 m elevation) can be lush sources offorage subjected to periodic drought. Overall, these ranges collectively are thought to be less productive and nutritious for elk than the milder climate oakbrush-pinyon-juniper winter ranges and aspen and subalpine summer ranges of the Grand Mesa, Colorado where elk survival was measured from 1993-2000 (Freddy 2000). METHODS Capture Adult female (age ~2 years) and calf (age 6 months) male and female elk were captured and radiocollared using helicopter net-gunning from 16-22 December, 2000 and 16-20 December 2001 (Freddy 1993, see PN Appendix III). All radio-collars were 172-176 MHz and contained 4-6 hour mortality sensors (Lotek, Inc., see PN Appendix I). Calf collars were expandable allowing collars to remain on elk as they matured to adults (see PN Appendix I). Objectives were to capture and radio-collar 78 calves each year with 13 calves of each sex in each of the 3 Gunnison Basin DAUs. For adult females, objectives were to capture and radio-collar 39 during the first year with 13 in each DAU and in subsequent years, capture sufficient adult females to maintain ~13 adult radioed females in each DAU (see PN, Sample Sizes). Prior to capturing elk, the 3 DAUs demarcating the entire Gunnison Basin were divided into 10 geographic trap-zones (Figure 1 A-I, see PN Figure 1). Numbers of elk to be captured in each trap-zone within a DAU were based upon the proportion of elk observed in each trap-zone within each DAU during elk sex and age composition surveys conducted with a helicopter during December-J anuary post-harvest 1995-1999. We attempted, therefore, to distribute our sample of radioed elk across the landscape in proportion to relative elk numbers during early winter within each DAU. Elk were captured within a 3-km radius of.39 processing sites with some sites common to both years (Figure 1). Capture sites were systematically distributed within trap-zones within DAUs to radio-collar elk representing multiple segments of the entire Gunnison Basin population. Although our capture sites were not based on previously selected random coordinates, we believe we achieved a representative sample of elk from the population to provide relatively unbiased estimates of survival rates. Capture sites were accessed via vehicles when possible or by ferrying capture crews in the helicopter to more remote locations inhabited by elk. Calves were ferried by helicopter from individual elk capture locales to processing sites where body mass (kg), total body length (em), hind foot length (em), and rectal body temperature (F) were measured and then calves were radio-collared and released (see PN Appendix III). All body measurements were made with the same instrumentation by the same individuals both years. Adult females were captured, aged as 2-4 years, 5-9 years, and >9+ years old based on incisor replacement or relative wear, radio-collared, and released at location of capture. We avoided capturing yearling 18-month-old females. Photographs of �195 incisor replacement and wear by elk age-class were provided to handlers responsible for judging the age of adult elk prior to releasing adults. No ear-tags were applied to calf or adult elk. Calf body measurements were compared among years, sexes, and DAUs using SAS (1988, PROC FREQ, PROC GLM[ANOVAD. All capture protocols were approved by the CDOW Animal Care and Use Committee. Telemetry Monitoring We monitored life or death status of radioed elk daily from December through June from accessible roads using a truck equipped with magnetic-mounted omni-directional and 3-element hand-held Yagi antennas and at 1-4 week intervals from December through November using a Cessna 185 or 182 equipped with strut and/or belly mounted 'H' antennas. We used Lotek® SRX400 and Telonics® TR2 receiverscanners for monitoring telemetry signals. Elk survival data were compiled using the RADIOS module of the CDOW program DEAMAN® (White 1991). Mortality Assessments All suspected mortalities based on telemetry mortality signals were confirmed using ground searches. Once carcasses were located, criteria for assigning probable cause of death followed standardized written procedures that included assessment of body position and body condition, presence of bite or claw marks and sub-dermal hemorrhaging or gunshot wounds, presence of tracks or drag marks, and collection of organ, muscle, and femur marrow samples for laboratory analyses, if available (Wade and Browns 1982, Freddy 1998). Multiple photographs were taken of the carcass along with any potential evidence for assessing cause of death and when appropriate, an outside expert (T. D. 1. Beck, CDOW) was consulted to assess evidence. Field necropsies were performed to the extent possible depending on completeness of carcass. We routinely collected muscle samples from large muscle groups in the hind- and forequarters of carcasses when available to assess for evidence of capture myopathy (Lewis et al. 1977, Spraker 1982, Haigh and Hudson 1993). Histopathology assessments of organ and muscle samples were completed by the Colorado State University Veterinary Diagnostic Laboratory and analyses of percent femur marrow fat on a dry-matter basis were conducted by the CDOW research laboratory. Field technicians provided a standardized written summary for each death. The principal investigator made the final assessment for probable cause of death based upon field summaries, photographs, and laboratory analyses. Potential causes of death included malnutrition, predation by black bears (Ursus americanus), mountain lions, (Felis concolor), coyotes (Canis latrans), and domestic dogs (Canis jamiliaris), legal and illegal hunter harvest, accidental trauma, plant poisoning, capture-induced, and unknown (Freddy 1997). Causes of death were broadly summarized as malnutrition, predation, suspected malnutrition, suspected predation, accident.unknown, hunter harvest, and capture-induced. Mortalities classed as malnutrition were usually nearly intact carcasses with little or no evidence of predator presence whereas mortalities classed as predation usually had evidence of bite wounds and subdermal hemorrhaging indicating bites were inflicted on a live animal. In those cases classed as suspected malnutrition or suspected predation a preponderance of collective evidence was used to assign cause of death to the most likely class. Telemetry collars that prematurely slipped-off elk causing mortality signal to be emitted were confirmed by locating and retrieving the collar. a Elk were subjected to multiple hunting seasons during fall 2000 and 2001. These seasons with approximate dates were: archery, 25 August-23 September; muzzleloading, 8-16 September; elk-only, l317 October; deer-elk first combined, 20-26 October; deer-elk second combined, 3-9 November; deer-elk third combined, 10-14 November; late antlerless elk only, 24 November - 16 December in GMUs 54 and 55 (portions ofDAUs E-41 and E-43); and, late antlerless elk only, 1-31 December in GMU 66 (portion ofDAU E-25). �196 Survival Rates Survival rates of radioed elk were calculated for this report using the binomial estimator and in final analyses will be calculated using a Kaplan-Meier estimator without staggered entry (White and Garrott 1990). Binomial estimates of survival rates were calculated as mean survival (s) = [Alive / Alive+Dead collared elk], with a variance of[VAR(s) =(s )*(I-s) / n collars], and 95% confidence intervals of(s) ± [t a-0.05, n-l df *-[( VAR (S))). Survival rates were estimated for time intervals of winter-spring (15 December - 14 June), summer-fall (15 June - 14 December), and yearly (15 December - 14 December) which coincided with capturing and radio-collaring elk and thus represented a biological year. By definition, calf elk became 12-month-old yearlings on 15 June and calves surviving to this date were considered to be recruited into the population. For adult elk during time intervals that included hunting seasons, we calculated survival rates inclusive of natural and hunting related mortalities, exclusive of hunting mortalities, and exclusive of natural mortalities. Excluding, or censoring hunting mortalities, provided estimates of natural survival rates, while censoring natural mortalities but including hunting mortalities provided estimates of hunting removal rates calculated as f = (1 - s), with (s) being survival rate with natural mortalities censored. Chi-square contingency tests were initially used for comparing calf survival (alive or dead categories) between sexes, years, and DAUs (White and Garrott 1990, SAS 1988 PROC FREQ). Parameter estimates were expressed as means ± 95% confidence limits unless otherwise noted. Elk dying of suspected captured-induced trauma were censored from survival estimates. Deaths of calves or adults occurring within 1 week of capture were likely to be classed as capture-induced deaths unless field evidence strongly suggested a natural cause of death independent of capture. Capture-induced trauma could affect animals for up to 2-4 weeks post-capture so we routinely attempted to assess whether deaths were potentially capture-induced. We also censored elk having telemetry collars that electronically failed or slipped-offthe elk (White and Garrott 1990). Elk with failed or slipped collars were censored for an entire seasonal time interval for binomial survival estimates and will be censored on the date they were last known alive based on telemetry signals in Kaplan-Meier estimates of survival. Elk whose telemetry signals disappeared during hunting seasons continued to be monitored for several subsequent months over large geographic areas until such time these elk were judged to have likely been removed during hunting seasons. Radioed elk that disappeared during hunting seasons were assumed to be legally harvested. Reproductive Collections Fecundity of adult female elk (age ~1 year) was estimated by examining reproductive organs of antlerless elk harvested during limited-entry late-hunting seasons that occurred from mid-November through December in portions ofGMUs 54, 55, and 66. About 2-3 weeks prior to the beginning of seasons, we mailed permitted hunters collection packets' explaining procedures for obtaining reproductive organs and incisor teeth (for dental cementum aging) from harvested elk as done previously in Colorado (Freddy 1992). Additionally, we asked hunters to collect kidneys with associated fat from these elk to allow calculation of kidney-fat indices and estimates of percent total fat to better assess body condition of adult females in relation to reproductive status (Kohlmann 1999, Cook et al. 2001a, 2001b). Hunters were instructed to place samples in collection bags and leave specimens in protected containers that kept samples cool at several drop-off sites within the Gunnison Basin from which samples were picked-up almost daily by project personnel. Dental cementum aging was completed by the CDOW research laboratory . Pregnancy status of elk was determined as: pregnant was uterus with embryo, fetus or fetal membranes; not pregnant was no evidence of fetus, no active uterine tissue, and no active corpora lutea of pregnancy; suspected pregnant was active corpora lutea, apparently active uterine tissue but no visible embryo or fetus; and unknown was either incomplete sample or no sample available. Fresh fetuses were sexed, �197 weighed, and measured (Armstrong 1950, Morrison et al. 1959). Fetuses and questionable uteri were stored in 10% buffered formalin for reference examination. Morrison et al. (1959) graphically presented a logarithmic relationship between fetal crown-rump length (Y, dependent variable) and known fetal-age in days (X, independent variable) but did not present a standardized equation. To develop a standardized arithmetic equation for predicting fetal age, traditionally the unknown variable of interest, from fetal crown-rump length, traditionally the variable measured, we first used Morrison et al. data in MS-Excel® curve-fitter to develop 2 predictive polynomial equations. These equations were: (a) YCfetalcrown-rumpmm) = 0.0085X2CfetalagedayS) + 1.7603X57.034, ~ = 0.9969, for the complete 8 data points presented by Morrison et al. (1959), and (b) YCfetalcrownrumpmm) = 0.0 194X2Cfetal agedays)+ 0.2521X - 17.51, ~ = 0.9987, for 7 Morrison et al. (1959) data points with their late March data point excluded. We found equation (b) reduced the error in predicted crown-rump measurements by 2:50% over equation (a) when predicted crown-rump lengths were compared with Morrison et al. actual crown-rump lengths, especially for the critical 60-90 day fetal-age stage that was associated with fetal collections occurring in November-December. Because fetal age in days is what is estimated from measured crown-rump values, we input polynomial equations (a) and (b) into program DERNE® to solve for fetal-age days (X) in terms of crown-rump measurements (Y). These DERNE® equations were: for polynomial equation (a) XCfetal agedays)= ([ .[(3400000*YCfetalcrown_rumpmm) + 503781209) -17603] / 170}, and for polynomial equation (b) XCfetalage days)= {[ '[(7760000* YCfetalcrown-rumpmm) + 142256321) - 2521] /388}. We used DERNE® equation (b) to estimate elk fetal ages from crown-rump measurements. Fetal age in days was subtracted from date of hunter collection and then converted to calender and Julian dates of estimated conception. We measured total kidney fat mass and trimmed kidney fat mass after Riney (1955), Kohlmann (1999), and Cook et al. (2001a,b). We calculated modified total and trimmed kidney fat indices after Anderson et al. (1990), Kohlmann (1999), and Cook et al. (2001a,b). We estimated percent total body fat from measurements of kidney fat using simple linear equations that predicted percent body fat from kidney total fat mass (TFM), full kidney fat index (TF-KFI), and trimmed kidney fat index (TRF-KFI) presented by Cook et al. (2001a). We commonly received only 1 kidney fat mass submitted with reproductive samples so for those elk for which we received both kidney masses, we averaged kidney fat measurements to produce 1 value per elk (Cook et al. 2001a). Although TFM was potentially the best predictor of percent body fat of the measurements we made (see Cook et al. 2001a) we had no control on how well hunters collected all fat associated with kidneys so we conservatively viewed percent body fat estimates derived from trimmed kidney fat might be more accurate because we standardized the amount of fat measured among samples. All reproductive measurements were compiled in MS-Excel® and analyzed with SAS (1988, PROC FREQ, PROC UNNARIATE, PROC REG, PROC GLM[ANOVA], PROC LOGISTIC). General Elk Movements During aerial flights to monitor survival status of elk, we interpreted signal strength and direction to judge general locations of telemetry signals for each elk as to primary drainages or topographic features to describe general movements of elk to and from seasonal ranges. Elk that made large or unique movements, such as across main highways or DAD boundaries, were located relatively precisely from the airplane with the radius of location error likely <1,000 m. This location data was not gathered to assess specific habitats used but rather to describe the major movement patterns of these elk. Data will be summarized in future reports using ArcView 3.2®. �198 RESUL TS AND DISCUSSION Capture In 2000, we radio-collared 78 calves, of which 38 were males and 40 were females, and 39 adult females age 2.2 years. Frequency of age classes for adult females were: 2-4 years = 3, 5-9 years = 30, and >9 years = 6. We achieved our objective of capturing 13 adult females and 26 calves in each DAU and nearly balanced sex ratios among calves in each DAU (Table 1). Elk were captured at 20 different sites representing a broad geographic area in the Gunnison Basin (Figure 1, Appendix A). There were no acute deaths of calves during capture but 2 adult females died while being blindfolded and hobbled prior to radio-collaring. Upon necropsy, both adults had extensive hemorrhaging in the thoracic cavity but no hemorrhaging in the abdominal cavity and no obvious indications of cervical injuries. We surmised that the heart-lung complex received extensive shock from capture. In neither case did we believe the animals had experienced extreme physical exertion nor aspiration of rumen contents. At time of capture, snow depths were about 25 em and chase times appeared reasonable while ambient temperatures were 15 C and -2 C. Therefore, of 41 adult females captured and handled, 2 or 5% died of capture-induced injuries. Both adult elk were donated for human consumption. Subsequent to capture and radio-collaring, 1 male and 1 female calf died likely within 7 days of capture and were classified as capture-induced deaths and censored from the radioed-collaredpopulation of calves. Histopathology confirmed capturemyopathy in the male calf which had been killed by a mountain lion (Appendix B). At capture, rectal temperatures were 106.6 F (41.4 C) for the male and 105.5 F (40.8 C) for the female calves. Therefore, of 78 calves captured and handled, 2 or 2.6% died of capture-induced injuries resulting in a net sample of 76 radio-collared calves at the beginning of winter 2000. In 2001, we captured 80 calves, 40 males and 40 females, and 12 adult females age 2.2 years. Frequency of age classes for adult females were: 2-4 years = 0, 5-9 years = 10, and >9 years = 2. We achieved our objectives of26 calves of nearly balanced sex ratios in each DAU and maintained 2.13 radio-collared adult females in each DAU (Table 1). Elk were captured at 19 new and 3 previously used sites (Figure 1, Appendix A). There were no acute deaths of adult females or calves during capture. However, 2 female calves caught from the same group in trap-zone E and radio-collared died within 48-hours of capture and were classified as capture-induced deaths (Appendix C). One calf became entangled in a fence about 1 km from the capture site and the second calfwas euthanized by gun-shot about 0.5 km from the capture site because of obvious weakness following capture. At time of capture, snow depths were about 20 ern and capture chase times were < 1 minute at an ambient temperature of -4 C. Rectal temperatures of these calves at capture were 106.7 F (41.5 C) and 105.4 F (40.8 C), respectively. Two additional replacement female calves were captured from the same area prior to completing all capture activities. An additional male calf died within 3 days of capture and was classified as a capture-induced death even though a mountain lion had probably killed the calf (Appendix C). At capture, rectal temperature of .the male calf was 103.8 F (39.9 C), capture chase time seemed reasonable, and snow depths were about20 em. A1l3 calves were censored from the collared population of calves. Therefore, of 80 calves captured and handled, 3 or 3.8% died of capture-induced injuries resulting in a net sample of 77 radio-collared calves at the beginning of winter 2001. For both years, capture-induced deaths occurred in 3.2% of the calves and 3.8% of the adult females that were captured and handled. Collar Failures We experienced pre-mature expansion of 14 calf collars, 13 males and 1 female, that resulted in collars slipping off calves causing us to censor calves during winter-spring or as yearlings during summer-fall time periods. For calves collared in December 2000,5 males slipped collars between 30 April and 7 June 2001 and 3 males successfully recruited as yearlings, slipped their collars between 20 June and 20 July 2001. For calves collared in December 2001,2 males slipped collars between'20 May and 3 June 2002,3 males recruited as yearlings slipped their collars between 18 June and 17 July 2002, and 1 female recruited as a yearling, slipped her collar between 17 July and 22 August 2002. �199 Evidence suggested that amber latex tubing (3/8" O.D., 3/16" I.D, 3/32" wall thickness) used as a breakaway component to allow collar expansion pre-maturely deteriorated and broke allowing collars to expand and slip over the heads of calf and yearling elk. This calf collar design using the same or similar components had been previously used on 280 calves on the Grand Mesa, Colorado (Freddy 1997) where only 1 5-month-old male calf, 1 13-month-old male yearling, and 2 23- to 26-month-{)ld females slipped collars of which none were due to pre-mature breakage oflatex tubing. On Grand Mesa, evidence indicated that latex tubing deteriorated as planned 10 to 18 months post-application after males had grown spike antlers or heads of either sex had grown to retard collars from slipping over heads. Deterioration of tubing apparently occurred sooner in the Gunnison Basin, maybe because of colder temperatures or slightly higher effective UV light levels, and males were much more prone than females to slip collars. We also speculated that antlers of yearling males in Gunnison might possibly be shorter than Grand Mesa yearling males during early summer thus allowing collars to slip more readily in Gunnison. After 2000-01, we changed brands of latex tubing and maintained the same size of tubing for 2001-02 but the problem persisted to a lesser degree. In the future, we will change to a thicker latex tubing on male collars of either 1/8" or 3/16" wall thickness to reduce the problem of pre-mature expansion and the need to censor calves or yearlings from survival estimates but still maintain expansion capability so collars will adequately fit adult elk. We used radio-collar telemetry frequencies between 172 and 176 :MHz and found an increasing problem with white-noise interference at frequencies> 175:MHz. At times, interference prevented hearing radiocollars except at relatively close distances, especially during aerial surveys when radio-collars or interference could be heard over several kilometers of distance. Interference was most commonly associated with human developments but likely sources could not be identified. We therefore caution project leaders to assess potential interference problems when selecting collar frequencies> 175 :MHz. Weather Although official NOAA weather data has not been summarized as yet, winter-spring snow depths and summer-fall precipitation for both 2000-01 and 2001-02 were well below average for the entire Gunnison Basin. Both years were considered to represent drought conditions, not only for the Gunnison Basin, but most of southwestern Colorado. On most segments of winter range, snow depths generally did not exceed 30 em during either winter with 2001-02 having shallower average snow depths than 2000-01. During both winters, snow had melted from primary winter ranges by late-March to mid-April. Snow depths and persistence of snow cover varied greatly in the Basin. Snow depths tended to decrease from west to east and north to south such that the deepest snow occurred in E-25 (GMU 66), E-41(GMU 54), and E-43 (GMU 55) and the shallowest snow in E-25 (GMU 67) and in E-43 (GMU 551) (Figure 1). Winter temperatures were generally mild for the Gunnison Basin with daily minimums seldom below -26 C and generally >-18 C and daily maximums often >-6 C. Calf Survival Survival rates of all calves pooled among 3 DADs during winter-spring were 0.89 ± 0.08 (± CL, n = 71), 0.83 ± 0.09 (n = 75), and 0.86 ± 0.06 (n = 146) for 2000-01,2001-02, and both years combined, respectively (Table 2). Survival of all calves was not different between years (P = 0.2965, Table 4). Male calves had lower survival (0.78) than female calves (0.97) in 2000-01 (P = 0.0105) but not in 200102 or when years were combined (P 2:.. 0.1463, Tables 2, 4). The greatest discrepancy between sexes occurred in DAU E-25 where survival of males and females was 0.71 and 0.93, respectively (Table 3). In comparison, yearly calf winter-spring survival on Grand Mesa was 0.86 to 0.92 (n = 69-73) and averaged 0.89 (n = 280) during 4 consecutive winters (1993-94 - 1996-97) with no differences in survival among years or between sexes (Freddy 1997). �200 Among the 3 DADs, survival of all calves tended to be lower in E-41 (0.78) compared to E-25 (0.84) and E-43 (0.94) (P = 0.0737, Tables 3, 4). In paired comparisons between DADs, calf survival was lower in E-41(0.78) than E-43 (0.94) (P = 0.0213, Tables 3,4). During winter-spring, calves died due to predation, malnutrition, suspected predation or malnutrition, accidents, and of unknown causes. In 2000-01,8 calves died with proximate causes of deaths being 37.5% predator-related and 62.5% malnutrition-related. In 2001-02, 13 calves died with proximate causes of death being 62% predator-related, 15% accidents, and 23% unknown causes. For years combined, 21 calves died with proximate causes of death being 53% predation-related, 24% malnutritionrelated, 9% accidents, and 14% unknown causes (Figure 2). On average then, for each 100 calves entering the population on 15 December, we would expect 86 to survive to the following 15 June with 7 deaths predation-related, 4 deaths malnutrition-related, and 3 deaths from other causes. Mountain lions and black bears predated elk calves and coyotes were suspected predators in one death. Accidental deaths were associated with a haystack collapsing and trapping a calf while elk were feeding on hay and a calf apparently slipped off a deep snow-trail used by elk and became trapped upside down among deadfall trees. In comparison, estimated causes of calf mortalities (n = 31) on Grand Mesa were 65% predation-related, 26% malnutrition-related, and 9% of unknown causes (Freddy 1997). Calf mortalities tended to occur later and primarily after 16 March in the winter-spring of 2000-01 than in 2001-02 (Figure 3, A & B). Timing of deaths in 2000-01 was consistent with deaths directly associated with malnutrition or predation-related deaths of malnourished calves as winter progressed. In contrast, predation-related deaths occurred from January through May in 2001-02 with no deaths directly attributed to malnutrition in 2001-02 (Figures 2, 3). In comparison, calves died on Grand Mesa from January into late May but the majority died in March and April (Freddy 1997). Femur marrow fat of dead calves was 34% ± 25 (SD, n = 8) in 2000-01 and marginally lower (P = 0.11, t-test) than the 59% ± 35 (SD, n = 10) in 2001-02. In general, most calves dying from any cause had femur fat < 50% in 2000-01 and >55% in 2001-02 (Figure 4). For deaths attributed directly to predation, femur fat averaged 16% (n = 3) in 2000-01 and 91 % (n = 4) in 2001-02. In 2001-02, all deaths considered predation-related had femur fat >60% (n = 7), even deaths occurring in mid-May (Figure 4). In contrast, both accidental deaths in 2001-02 had femur fat <5% and likely represented calves already extremely malnourished prior to the end of February (Table 5). Importantly, Cook et al. (2000a) noted that femur fat values <85% in adult female elk were associated with total percent body fat < 5% indicating that nearly any loss of femur fat suggested an animal in poor physical condition. Although there were limited sample sizes both years, data suggested a different dynamic between years of mild winters. in 2000-01, calf surVival appeared more influenced nutrition and .relative. body condition, possibly representing either the previous summer or winter forage production. Predation appeared more compensatory related. In 2001-02, predation appeared more additive than compensatory because calves that died were possibly not predisposed by malnutrition. In both.years, overall calf survival remained high regardless of the proximate cause of mortality. We must also caution that predation-related deaths in early January 2002 could not be totally separated from possible captureinduced deaths as deaths likely occurred <2 weeks post-capture. by Adult Survival Survival rates for adult females age 2:2 years were l.00 during winter-spring as no deaths occurred during 2000-01(n = 39) and 2001-02 (n = 48). During summer-fall 2001, survival was 0.92 ± 0.08 (n = 39) when natural (I) and hunting deaths (2) were included. The one natural death occurred about July 1 of unknown causes in a female age 19 years based on dental cementum resulting in a natural summer-fall survival rate of 0.97 ± 0.05 (n = 37) (Table 6, Appendix D). Annual survival rates were 0.92 ± 0.08 (n = 39) including all causes of death and 0.97 ± 0.05 (n = 37) including only natural deaths (Table 6). In �201 comparison, natural survival of adult females was ?:_0.97in winter-spring and summer-fall during 7 consecutive years on Grand Mesa (1993-94 - 1999-2000) (Freddy 2000). Yearling Survival Survival rate for yearling female elk, age 12-17 months, was 0.89 ± 0.10 (n = 38) during summer-fall 2001 and because all 4 deaths were hunting-related, natural survival during sununer-fall was 1.00 (n = 34). Survival of the same cohort of yearling males was 0.86 ± 0.15 (n = 22) during summer-fall when natural (2) and hunting deaths (1) were included. Two yearling males died in July 2001 of suspected predation (Appendix D) resulting in a natural summer-fall survival rate of 0.90 ± 0.13 (n = 21) (Table 7). Survival of all females age ?:_12months during sununer-fall was 0.91 ± 0.07 (n = 77) inclusive of natural (1) and hunting deaths (6) and natural survival for these females was 0.99 ± 0.03 (n = 71, Table 6). Survival rates for both yearling female and male elk, age 18-23 months, was 1.00 (n = 34 F, n = 19 M) during winter-spring as no deaths occurred during 2001-02 (Table 7). Survival of all females age ?:_18 months during winter-spring 2001-02 was 1.00 (n = 82) as no deaths occurred (Table 6). Harvest Removal Harvest removal rates (f) during summer-fall 2001 were 0.05 for adult females, 0.11 for yearling females, 0.08 for all adult females age ?:_12months, and 0.06 for yearling males. Hunting mortalities for adult females consisted of 3 legally harvested (2 regular rifle, 1 late rifle) and 3 wounding losses (1 archery/muzzleloading, 2 regular rifle). Wounding loss thus equaled the legal harvest in this small sample situation. The one yearling male hunting mortality represented an illegal harvest that occurred during a late-season in December 2001 (Appendix D). With observed calf and adult female natural survival rates, computer models suggest that removal rates for adult females age ?:_12months in the Gunnison Basin would need to be ?:_15%per year to stabilize the population. Calf Body Size Calf body mass averaged 99.1 ± 2.2 kg and ranged from 52.0 to 133.0 kg for all calves and years (Table 8) with 7% of the calves having mass <80 kg (Figure 5). There were no effects of capture year, calf sex, or year-sex interaction on body mass (P..?:.. 0.259) although calves were 2.6 kg smaller in mass in 2001 and males were 1 kg larger than females. However, calf mass was different among management DAUs (P = 0.003). ill simultaneous paired comparisons, calves were larger in E-41 (104.4 kg) than in E-43 (96.8 kg) and E-25 (95.9kg) with no differences between E-43 and E-25. Calf mass was reasonably consistent within trapzones within DAUs, with mass tending to be larger in trapzones I and J (E-41) than in D (E-25) and F (E-43) (P = 0.090). Similar trends among years, sex, DAUs and trapzones occurred for calf total body length and hind-foot measurements with both measurements supporting that E-41 calves were largest (P < 0.002) (Table 8). Calf mortalities occurred across the range of calf body mass classes (Figure 5). Predation-related mortalities occurred in the most frequent mass classes between 80 and 119 kg, suggesting predators were taking calves with no particular selectivity. Except in one case, malnutrition-related mortalities occurred in calves < 99 kg in size. Calves <80 kg did not necessarily perish, although 2 of the 3 calves <60 kg died of malnutrition or accident (Figure 5). Survival of calves tended to be lower in E-41 (P = 0.0737), where calf mass was largest, compared to survival in E-25 and E-43 (Tables 3, 4, 8). ill E-41, mortalities were predator-related (45%), malnutrition-related (36%, including 1 accident where calf femur marrow was < 2%), and unknown (18%). On Grand Mesa, the larger mass of male calves also did not necessarily translate to higher survival rates compared to smaller female calves (Freddy 1997). ill the Gunnison Basin, male and female calves were 15% and 7% smaller, respectively than their counterparts captured and radio-collared on Grand Mesa 1993-94 - 1996-97. On Grand Mesa, body mass was 115 ± 2.5 kg for males (n = 138) 'and 106 ± 2.3 kg for females (n = 136) with an overall range in size �202 of 60 to 141 kg (Freddy 1997). Furthermore, unlike Gunnison, males were significantly larger (8%) than females on the Grand Mesa. Unfortunately, we cannot distinguish whether differences in mass reflect population or year effects. Elk Reproduction Samples Participation by successful hunters in providing biological samples from adult female elk harvested during late-seasons was disappointing. Of the estimated 665 adult females harvested during 2000-2001, we received some of the requested biological samples from 19% of the elk with reproductive organ and kidney fat samples representing only 13% of the elk. Importantly, rates of participation by hunters harvesting elk declined from 28 to 12% from 2000 to 2001 despite attempts to improve collection instructions and packets sent to hunters in 2001 (Table 9). Providing an incisor tooth from harvested elk was the most common biological sample collected by hunters. For many data summaries and analyses, reproductive data from both years was combined because 65% of the samples were obtained in 2000. Furthermore, approximately 80% of the samples came from elk harvested in GMU 66 and 20% from elk harvested in GMUs 41 and 55. Therefore, data summaries were inherently weighted to year 2000 and GMU66. Ages of adult female elk harvested ranged from 1 to 20 years with 63% estimated to be age 3 to 10 years. Yearlings ('"age 17-18 months) and females age 2:15 each represented 5% of the harvest. Because hunter selectivity and animal behavior may bias vulnerability of different elk age classes to harvest, the distribution of harvested age classes may biasly represent the age structure of the elk population (Table 10). Pregnancy Rates and Conception Dates Pregnancy rate for all adult females age 2:1 year was 85% (n = 89, Table 11). Pregnancy rate was 92100% for female age classes 3 to 14 years. Pregnancy rate was 67% in females age 2 and 50% in females age 2:15. Pregnancy rates across age classes were highly similar to rates measured in the ForbesTrinchera elk population of south-central Colorado (Freddy 1993b). The 100% pregnancy rate in yearlings could be questionable because pregnancy status was unknown in 67% of the submitted yearling samples. For age classes 2 and 3-4, pregnancy status was unknown in up to 44% of the animals. We might expect that in these younger age classes, uteri may be small, in-active and non-pregnant or in the early stages of pregnancy, creating more difficult circumstances for hunters to find and collect specimens. In comparison, for age classes 2: age 5, -:::.27%of the specimens were of unknown pregnancy status. Thus, there is the possibility that pregnancy rates for young elkage 1 to 4 could be overestimated due to collections biased against non-pregnant elk. Estimated conception dates followed an expected asymmetrical pattern (Flook 1970, Freddy 1993b,Noyes et al. 1996). Mode, median, and mean days of conception were 23, 26, and 29 September, respectively (n = 72, Figure 6). Conceptions spanned 68 days with 75% occurring in the 26-day interval from 8 September to 3 October. This conception pattern strongly suggested that most adult females conceived during their first estrus cycle at the expected time of year. Females conceiving after 10 October (n = 12, 17%) may have had a delayed first estrus or conceived during their second estrus cycle. Patterns and dates of conception were quite similar to estimates obtained for Forbes-Trinchera elk where post-season mature bull:cow rations commonly exceeded 35:100 (Freddy 1993b). The mirror-image asymmetrical distributions for conception dates (Figure 6) and calf body mass (Figure 5) indirectly suggest that smaller calves (7% < 80 kg) may be associated with adult females conceiving later in the fall (17% after 10 October). Females conceiving after 10 October were comprised of9% yearlings, 18% age 3-4, 45% age 5-7, and 27% age 2:15 years. All pregnant females 2: age 15 conceived after 16 October (n= 3). Later breeding by youngest and oldest age classes would not be unexpected but later conception by females age 5-7 may �203 indicate some nutritional or disturbance stress affecting timing of breeding in about 8(Yoofthe population. Overall, conception date was not dependent on adult female age (,-2 = 0.014, P = 0.173, n = 66). Pregnancy status was associated with ovarian mass of both ovaries combined. Total ovarian mass (g) was 5.37 ± 0.28 (CL, n = 59) and larger in pregnant than the 3.36 ± l.60 (n = 5) in non-pregnant elk (P = 0.025). Larger ovarian mass reflected the presence of active corpora lutea of pregnancy. Fetal Rates. Sex. Age. and Size Litter size was 1 fetus in uteri with detectable fetuses (n = 69). Fetal sex favored females (37F:2IM) for years combined which differed from a 50:50 ratio (i = 4.414, df= 1, P = 0.036). Female fetuses also dominated within each year (24F: 15M, 2000; 13F:6M, 2001) but such yearly ratios were not different from 50:50 (P 2: 0.108). Fetal sex could be determined in those fetuses near 2:70 mm crown-rump length based on external genitalia as also found by Morrison et al. (1959) and Kohlmann (1999). In general, fetal sex could not be determined in fetuses estimated to have been conceived after 10 October. i Fetal sex tended to be dependently associated with adult female grouped age class (Figure 7 [Right], = 10.885, df= 5, P = 0.054). Male fetuses predominated in adult females age 8-10 while females fetuses were most common within age classes 3-4, 5-7, and 11-14. Fetal sex ratio was equal in 2-year-old females which may have been conceiving for the first time. Male fetuses were also more predominate in elk age 2:8 years in the Forbes-Trinchera elk (Freddy 1993b). Kohlmann (1999) found male fetuses were more common in adult females having high kidney fat levels, and thus good body condition, and that adult females in good body condition conceived earlier in the breeding season. We could speculate that adult females age 8-10 had male fetuses because they were in better body condition at conception than other age classes due to their age and inherent larger body size that allowed them to withstand the rigors of a previous pregnancy and calf rearing and maintain access to better matriarchal habitats (CluttonBrock et al. 1982). In 2-year-old females, male fetuses may have been more common because these females likely had not gone through a previous pregnancy and subsequent calf-rearing prior to conception and thus were in better body condition. Although male fetuses predominated in those adult females conceiving 16-20 September just prior to the peak of conception, a pattern favoring male fetuses during early conceptions was not clearly evident (Figure 7 [LEIT]). Estimated fetal age averaged 69 and 76 days in 2000 and 200land was not different between years (P = 0.139). We found that fetal age predictive equation (b) (see ME1HODS) provided estimated dates of conception that occurred about 3-days earlier than equation (a) (paired t-test, P < 0.001). Fetal size compared favorably with fetuses measured in the Forbes-Trinchera elk population and appeared to be within an acceptable range of weight and skeletal. dimensions (Freddy 1993"b). There was a general pattern of fetuses in. 2001 beingslightly larger in crown-rump (P <0.080),hind-leg (P < 0.033), and hind-foot (P < 0.070) dimensions but not in body mass (P < 0.138) (Table 12). Fetal size is highly dependent on date of collection so absolute comparisons between years or among elk populations must include corrections for date of collection. Body Fat Condition and Reproduction Total fat kidney fat index values (TF-KFI) for adult females age 2:1 year averaged 106 and ranged from 29 to 306 (n = 84) which were similar to values for Oregon elk (Kohlmann 1999) (Table 13, Figure 8[LEFT]). The 25% quantile value was 63 which was slightly higher than the 50 reported by Kohlmann (1999). Other kidney fat values in Table 13 were presented for reference as these measurements were the basis for estimating percent total body fat (Cook et al. 200la), or body condition, in adult female elk. TF-KFI for calves averaged 44 (n = 6). �204 Estimates of percent body fat for all adult females age 2:1 year based on the 3 kidney fat measurements, TF-KFI, TRF-KFI, and TFM, averaged between 11.1 and 12.1% with a combined range of 5.4 to 18.5% (Table 14, Figure 8 [RIGHT]). Percent body fat of all adult females tended to be 1-2% higher in 2001 than 2000 for all estimators of body fat (P S 0.073, Table 14). For yearling females, specifically, percent body fat estimates averaged 10.7 to l3.0% with minimum-maximums of9 and 14% (n = 4) while body fat in calves was 4-7% (see Table 14 cautionary foot-note). Based on estimates of percent total body fat, about 65% of the adult females age 2:1 year were in moderate, 30% in low, and <5% in very low or very good body condition, and 0% in excellent condition (Figure 8 [RIGHT]). Relative condition class ratings were very low = <7% body fat, low = 7-10%, moderate = 10-15%, very good = 15-20%, and excellent = 20-25% (Cook, J. G. 2001 unpublished data). Kidney fat measurements provide the best predictive accuracy of percent total body fat at moderate levels of body condition and less accuracy at very high or very low levels of body condition (Cook et al. 2001a) so that our ability to detect outliers in body condition status may have been limited by measuring only kidney fat. Furthermore, percent total body fat levels in the excellent category may be rarely found in wild elk as these values were associated optimum nutrition in captive elk and likely represent the physiological maximums attainable by elk (Cook J. G., 2001 unpublished data). Probability of an adult female elk age 2:1 year being pregnant was dependent on estimated percent total body fat when body fat was based on TFM (g): (logit (pregnancy)) = -2.2835 + 0.3704* (X-percent body fat); P = 0.033, n = 68). Pregnancy probability was predicted to be 2:0.90 when percent total body fat was 2:12%, or 2: moderate body condition (Figure 9). Similar dependent relationships (logit P) could not be detected between pregnancy status and percent total body fat based on TI-KFI (P = 0.l30) and TRFKFI (P = 0.099), or on direct TF-KFI (P = 0.206) values. Cook et al. (2001a) indicated that TIM was the superior predictor of body condition within the kidney fat measurement alternatives. Kohlmann (1999), however, did find that probability of pregnancy ilogit P) increased with increasing TI-KFI values in Oregon elk (n = 1152). Similarly, Cook et al. (2001c) documented that low quality nutrition prior to breeding prevented or delayed conception in adult female elk and, furthermore, high pregnancy rates could be associated with marginally deficient nutritional conditions. Standard ANOVA results were consistent with logistic regression results. Estimated percent body fat was higher for pregnant than non-pregnant elk for body fat estimates based on TIM (P = 0.038) but not for body fat estimates based on TF-KFI and TRF-KFI (P 2: 0.112, Table 14). All estimates of percent body fat were not different among pregnant, non-pregnant and pregnancy status-unknown adult females (P 2: 0.149, Table 14). Furthermore, using linear regression, all estimates of percent body fat were not dependent on adult female age within pregnant (,-2 S 0.014, P 2: 0.315, n = 54) or non-pregnant elk (,-2 S 0.008, P 2: 0.543, n = 8). . . Probability of conceiving before or after the median date of conception was not dependent on percent total body fat based on TIM: t logit (Before) P =0.221, n = 53), indicating there was no detectable increased probability to conceive before the median date based on percent total body fat. Using linear regression, conception date was not dependent on percent body fat based on TF-KFI, TRF-KFI, or TIM (,-2 S 0.025, P > 0.141, df= 49) or dependent on 2-variable combinations of adult female dental cementum age and percent body fat (R2 S 0.031, P > 0.178, df= 49). Estimates of body fat for adult females conceiving after 10 October was about 11.1% for all 3 estimates of body fat. Overall, measured population performance of elk in the Gunnison Basin generally followed the predictions of proposed performance models for adult female elk in moderate or low body fat condition (B and C, below; Cook J.G. 2001 unpublished data). �205 The measured performance of elk in the Gunnison Basin could be summarized as: Pregnancy rates were 85%, about 17% of the females conceived after 10 October, adult female survival during mild winters was 100%, average mass of 6-month old calves was 99 kg with 7% of the calves weighing <80 kg and 21 % weighing> 110 kg, and survival of calves during mild winters was >83%; and compared to: Model A: If adult females in very good body fat condition. then we should expect: Pregnancy rates >90%, significant early breeding, high adult survival in harsh winters, > 110 kg calves in November; <5% of adult female Gunnison elk were classified in very good body fat condition. Model B: If adult females in moderate body fat condition. then we should expect: Pregnancy rates 2:90%, some delayed breeding, with high adult winter survival depressed somewhat in harsh winters, 90-110 kg calves in November; 65% of adult female Gunnison elk were classified in moderate body fat condition. Model C: If adult females in low body fat condition. then we should expect: Pregnancy rates 2:70-90%, more delayed breeding, with markedly lower adult winter survival in harsh winters, 70-100 kg calves in November; 30% of adult female Gunnison elk were classified in low body fat condition. Model D: If adult females in very low body fat condition. then we should expect: Pregnancy rates ,:::70%,delayed breeding up to 6 weeks, with low adult winter survival in harsh winters, 6090 kg calves in November; <5% of adult female Gunnison elk were classified in very low body fat condition. General Movements of Elk Insights into the general distribution and movements of elk in Gunnison Basin DADs (see PN Figure 1,) were obtained from approximate locations of radio-collared elk obtained during 44 aerial survey flights between December 2000 and June 2002. Maps of elk distribution are in process so only verbal descriptions will be presented at this time. Elk wintered in segments of winter range near where they were trapped in December as elk did not usually make large movements during winter. Movement from winter areas towards summer ranges began in April, proceeded in earnest in mid-May after snow had melted at higher elevations, and ended with elk arriving.on highest elevation summer ranges in July after calving and subsequent to snow melting on alpine ranges. Mov~nients from summer to winter ranges began in early September and continued through November with rates of movement most likely affected by hunting season activities and increasing snow depths. Elk essentially did not cross U.S. Highway 50 (Hy50) which separated the south (trap-zones A-E) and north (trap-zones F-J) (Figure 1) portions of the Gunnison Basin. Only 2 elk were known to cross this highway: an adult female in September 2001 moved from the Tomichi Dome area (trap-zone F) southwest to Sawtooth Mountain; and, a 24-month-old male in June 2002 moved from Tomichi Dome area (trap-zone F) to the southeast onto Sargents Mesa and then proceeded south over the La Garita Mountains to Alder Creek in the Rio Grande River drainage near South Fork, Colorado. Elk did move beyond the boundaries of the Gunnison Basin during winter and summer but only 2, at this time, have likely dispersed from the Gunnison Basin; an 18-month-old female moved from trap-zone H �206 north to Paonia Reservoir in November 2001 and a 24-month-old male moved trap-zone F south into the Rio Grande River drainage during June 2002. During summer, radioed elk were commonly found along the higher elevation divides associated with the boundaries of the Gunnison Basin DAUs, often in subalpine or alpine habitats from which they vacated in September while moving towards their winter ranges within the Gunnison Basin. These boundary areas included: upper and lower Cimarron and Little Cimarron rivers (west of trap-zone A); upper Rio Grande river in Rat Creek and near Continental and Rio Grande reservoirs (south of trap-zones A, B, C); Saguache Park (east of trap-zone D); Sargents MesaCameron Park (east of trap-zone E); upper Chalk creeks (northeast trap-zone F); upper forks of North Fork of Cottonwood, Lake Fork, Clear, and Castle creeks (east-northeast of trap-zone G); Anthracite creeks, Snowshoe and Cliff creeks, Coal Creek Basin, and Willow and Minnesota creeks (north of trapzones H, I, J); and, upper Smith Fork, Dyer, and Crystal creeks (west-northwest of trap-zone J). The greatest overlap of Gunnison Basin elk with elk from other management DAUs occurred during summer in the Big Blue Wildemess (west trap-zone A), in the upper Rio Grande River near Slumgullion-Spring Creek Pass and west of Continental Reservoir (south trap-zones A, B, C), and in the West Elk Wilderness (north trap-zones I, J). During winter, only a few elk remained outside of the Gunnison Basin DAUs, mainly in lower Cimarron creeks (west trap-zone A), just east of North Pass and Old Cochetopa passes (east of trap-zone E), near Paonia Reservoir (north trap-zone I, J), and in Smith Fork and Doug creeks near Crawford, Colorado (west trap-zone J). Some consideration should be given to re-aligning elk management DAUs in the Gunnison Basin based on observed movements of elk. There was a continuum of elk interchange among trap-zones on an west to east basis, especially during summer and to a lessor degree in winter. South ofHy50, elk in trap-zones A through E interacted with elk in adjacent trap-zones such that there was no clear demarcation of separate elk sub-populations across this area (Figure 1). Similarly, north ofHy50, elk in trap-zones J through F interacted with elk in adjacent trap-zones such that there was no clear demarcation of separate elk sub-populations across this area, although elk in trap-zones G and F only interacted with elk from trap-zone H in areas near Gothic, Colorado in the upper East and Slate rivers (Figure 1). Therefore, all areas south ofHy50 from Monarch pass on the east to the Cimarron Divide on the west (GMUs- part 551,67,66, and adding 65) could be treated as one DAD. Likewise, all areas north ofHy50 from Monarch Pass on the east to at least the Curecanti divide on the west (GMUs- part 551, 55, 54, and potentially adding 53 and 63) could be treated as one DAU. Elk that winter in GMUs 53 and 63 to the northwest of the Gunnison Basin likely have high interchange with elk from GMU 54 during summer in the West Elk Wilderness. SUMMARY In the Gunnison Basin, Colorado during winter-spring 2000-01 and 2001-02, survival rates of calves averaged 83-89% and tended to vary among elk management DAUs while survival rates of all age classes of adults were 100%. During summer-fall, survival rates were ?:_97%for adult females, 100% for yearling females, and 90% for yearling males when hunting deaths were excluded. Survival rates were comparable to survival rates previously estimated for elk inhabiting the Grand Mesa, Colorado. Harvest removal rates during summer-fall 2001 were 5% for adult females, 11 % for yearling females, 8% for all adult females age ?:_12months, and 6% for yearling males. Measures of reproductive and survival parameters were consistent with predictions of performance outcomes for adult female elk having low to moderate body condition status during fall. More than likely, marginally deficient levels of seasonal nutrition were depressing optimal reproductive performance of adult female elk. Consideration should be given to re-aligning management DAUs with observed distribution and movements of radioed elk. �207 LITERATURE CITED Anderson, A.E., D.C. Bowden, and D.E. Medin. 1990. Indexing the annual fat cycle in a mule deer population. Journal of Wildlife Managment 54:550-556. Anderson, C.R, Jr., D.S. Moody, B.L. Smith, F.G. Lindzey, and R. P Lanka. 1998. Development and evaluation of sightability models for summer elk surveys. Journal of Wildlife Management 62:9933991055-1066. Armstrong, RA. 1950. Fetal development of northern white-tailed deer. American Midland Naturalist 43:650-666. Bartholow, J. 1999. POP-II system documentation Windows™ Version 1.0. Fossil Creek Software, Fort Collins, Colorado USA. Bear, G.D., G.c. White, L.H. Carpenter, RB. Gill, and D.J. Essex. 1989. Evaluation of aerial markresighting estimates of elk populations. Journal of Wildlife Management 53:908-915. Carpenter, L.H., R B. Gill, D. L. Baker, and NT Hobbs. 1984. Colorado's big game supplemental winter feeding program. Colorado Division of Wildlife, Fort Collins, Colorado USA. Cogan, RD., and D.R Diefenbach. 1998. Effect of under counting and model selection on a sightabilityadjustment estimator for elk. Journal of Wildlife Management 62:269-279. Cook, R.C., J.G. Cook, D.L. Murray, P. Zager, B.K. Johnson, and M.W. Gratson. 2001a. Development of predictive models of nutritional condition for Rocky Mountain elk. Journal of Wildlife Management 65: 973-987. Cook, R.C., J.G. Cook, D.L. Murray, P. Zager, B.K. Johnson, and M.W. Gratson. 2001b. Nutritional condition models for elk: which are the most sensitive, accurate, and precise? Journal of Wildlife Management 65: 988-997. Cook, RC., D.L Murray, J.G. Cook, P. Zager, and S.L. Monfort. 2001c. Nutritional influences on breeding dynamics in elk. Canadian Journal of Zoology 79:845-853. Clutton-Brock, TH., F.E. Guinness, and S.D. Albon. 1982. Red deer behavior and ecology of two sexes. University of Chicago Press, Chicago, Illinois, USA. Eberhardt, L.L., R.A. Garrott, PJ. White, and PJ. Gogan. 1998. Alternative approaches to aerial censusing of elk. Journal of Wildlife Management 62:1046-1055. Flook, D .R. 1970. Causes and implications of observed sex differential in the' survival of wapiti. Canadian Wildlife Service Report Series 11. Ottawa, Ontario, Canada. Freddy, DJ. 1992. Effect of elk harvest systems on elk breeding biology. Colorado Division of Wildlife Research Report July:45-70. Fort Collins, Colorado, USA. July:45-70. Freddy, DJ. 1993. Program Narrative for Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July:83-II7. Fort Collins, Colorado, USA. Freddy, DJ. 1993b. Effects of elk harvest systems on elk breeding biology. Colorado Division of Wildlife Research Report July:50-65. Fort Collins, Colorado, USA. Freddy, D.J. 1997. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July:47-73. Fort Collins, Colorado, USA. Freddy, DJ. 1998. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July: 177-206. Fort Collins, Colorado, USA. Freddy, DJ. 2000. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July (2):239-258. Fort Collins, Colorado, . USA. Freddy, DJ., D.L. Baker, R.M. Bartmann, and RC. Kufeld. 1993. Deer and elk management analysis guide, 1992-1994. Colorado Division of Wildlife Division Report 17, Fort Collins, Colorado USA. �208 Haigh, J.e., and R.J. Hudson. 1993. Fanning wapiti and red deer. Mosby, Saint Louis, Missouri, USA, pages 187-192. Kohlmann, S.G. 1999. Adaptive fetal sex allocation in elk: evidence and implications. Journal of Wildlife Managment 63: 1109-1117. Lewis, RJ., G.A. Chalmers, M.W. Barrett, and R Bhatnagar. 1977. Capture myopathy in elk in Alberta, Canada: a report of three cases. Journal of The American Veterinary Medical Association 171:927-932. Morrison, J.A., CE. Trainer, and P.L. Wright. 1959. Breeding seasons in elk as determined from known-age embryos. Journal of Wildlife Management 23:27-34. Nelson, LJ., and J.M. Peek. 1982. Effect of survival and fecundity on rate of increase of elk. Journal of Wildlife Management 46:535-540. Noyes, J.H., B.K. Johnson, L.D. Bryant, S.L. Findholt, and J.W. Thomas. 1996. Effects of bull age on conception dates and pregnancy rates of cow elk. Journal of Wildlife Management 60:508-517. Roath, R., L. Carpenter, B. Riebsame, and D. Swift. 1999. Gunnison Basin habitat assessment projectFinal Report March 1999. Colorado State University, Department of Range Science, Fort Collins, Colorado USA. Riney, T. 1955. Evaluating condition of free ranging red deer (Cervus elaphus), with special reference to New Zealand. New Zealand Journal ofSciene and Technology 36:429-463. Samuel, M.D., E.O. Garton, M.W. Schlegel, and R G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. Journal of Wildlife Management 51 :622-630. SAS. 1988. SAS/STATuser's guide, release 6.03. SAS Institute, Inc. Cary, North Carolina USA. Spraker, T .R. 1982. An overview of the pathophysiology of capture myopathy and related conditions that occur at the time of capture of wild animals. Pages 82-118 in L. Nielsen, J. C. Haigh, and M.E. Fowler, editors. Chemical immobilization of North American Wildlife. Wisconsin Humane Society, Inc., Milwaukee, Wisconsin, USA. Unsworth, J.W., L. Kuck, and E.O. Garton. 1990. Elk sightability model validation at the National Bison Range, Montana. Wildlife Society Bulletin 18: 113-115. Wade, D.A., and J.E. Browns. 1982. Procedures for evaluating predation on livestock and wildlife. Texas- Agricultural Experiment Station Publication B-1429. White, G.c. 1991. DEAMAN database manager and population modeling procedures; Colorado Division of Wildlife User's manual and reference. Colorado State University, Fort Collins, Colorado USA. White, G.c. and RA. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, Inc., San Diego, California USA �209 Table 1. Number of male (M) and female (F) calf and adult female elk radio-collared in each DAD and trap-zone in the Gunnison Basin, December 2000 and 2001. Calf Elk Collared 2000 2001 Adult Female Elk Total Elk Collared Collared 2000-01 DAU-(GMUs) Trapzone M F Total M F Total M F Total 2000 E-25 (66, 67) A- Lake Fork 4 7 11 2 4 6 6 11 17 5 B- Cebolla 3 4 7 2 0 2 5 4 9 3 2 C - Huntsman 4 5 6 6 12 10 7 17 3 2 D- Sawtooth 2 3 2 4 6 4 5 9 2 s- 6 2 7 9 7 4 11 3 o subtotals E- 25 E-43 (55, 551) E - Razor 2 F - Tomichi 4 G- Almont 11 7 3 5 3 3 6 18 11 5 16 subtotals E-43 E-41 (54) 200 I 2000-01 2000 2001 6 16 7 5 10 4 5 8 14 3 5 7 .!l 19 39 32 2 3 5 7 3 8 6 18 16 34 8 2 10 26 18 27 27 54 .!l 1 l§ 39 II 5 10 7 14 7 H -Flat Top 2 4 6 3 3 6 5 7 12 4 I - Beaver 4 6 10 3 4 7 7 10 17 4 o 4 J - West Elk 7 3 10 7 6 13 14 9 23 5 2 7 15 15 .!l u 26 .!l.!l 26 26 26 52 11 1 l§ 39 29 38 40 78 40 80 78 80 158 39 12 51 117 92 subtotals E-41 Totals All Subtotals 40 a Includes 2 female calves that died of capture-induced causes within 24 hours of capture for which 2 additional female calves were captured from the same area and radio-collared prior to completing capture of all elk. The net beginning sample size was thereforell female calves for estimating survival rates in DAU E-43 in 2001. Table 2. Survival rates of elk calves age 6-11 months for males, females, and sexes combined from 15 December to 14 June in the Gunnison Basin, Colorado, 2000, 2001, and years pooled. Binomial estimator used to calculate survival rates and confidence limits for calves combined among DADs E-25, E-41, and E-43. Elk Calves Elk Calves 15 Dec 2000 - 14 June 2001 Survival Rate All Elk Calves 15 Dec 2001 - 14 June 2002 15 Dec - 14 June 2000 - 2002 Males Females All Males Females All Males Females All 0.78 0.97 0.89 0.84 0.82 0.83 0.81 0.90 0.86 Lower 95%CL 0.63 0.92 0.81 0.71 0.69 0.74 0.72 0.83 0.80 Upper 95%CL 0.93 1.00 0.96 0.96 0.94 0.91 0.91 0.97 0.91 n Collars 32 39 71 37 38 75 69 77 146 Collars Deployed 38 40 78 40 40 80 78 80 158 Collars Censored 6' Ib 7 3' 2d 5 9 3 12 Died 7 8 6 7 13 13 8 21 8 6 7 13 13 8 21 o o o o o o o Non-hunting Deaths Hunting Deaths 7 o o a Male calves censored: for post-capture induced mortalitv 173.082/00 on 12129/00 for ' slipped-collars, 173.170/00 on 517101,173.250/00 on 5/25/01,173.151100 on 6/7/01, and 173.220/00 on 6/ 1/01. 173.269/00 on 4/30/01, Female calves censored: for post-capture induced mortality 172.379/00 on 12/26/00. 'Male calves censored: for post-capture induced. mortality 174.720/01 on 12/19/01; for slipped-collars, 175.221/01 on 6/3/02. 174.099/01 on 5/20/02, and b d Female calves censored: for post-capture induced mortality 173.429/01 on 12/16/01 and 173.740/01 on 12/16/01. �210 Table 3. Survival rates of elk calves age 6-11 months for males, females, and sexes combined from 15 December to 14 June forDAUs E-25, E-4l, and E-43 in the Gunnison Basin, Colorado, 2000-01 and 2001-02 combined. Binomial estimator used to calculate survival rates and confidence limts. Elk Calves - DAU E-2S Elk Calves - DAU E-43 Elk Calves - DAU E-41 15 Dec - 14 June 00-01, 01-02 15 Dec - 14 June 00-01, 01-02 15 Dec - 14 June 00-01, 01-02 Males Females All Males Females All Males Females All 0.71 0.93 0.84 0.92 0.96 0.94 0.77 0.80 0.78 Lower 95%CL 0.47 0.82 0.73 0.82 0.88 0.87 0.60 0.63 0.67 Upper 95% CL 0.94 1.00 0.95 1.00 1.00 1.00 0.94 0.97 0.90 n Collars Collars Deployed 17 25 27 27 44 52 26 27 25 27 51 54 26 26 25 26 51 52 Collars Censored 8 0 8 1 2 3 0 Died 5 2 7 2 3 6 5 11 5 2 7 2 3 6 5 11 0 0 0 0 0 0 0 0 Survival Rate Non-hunting Deaths Hunting Deaths o Table 4. Comparisons of calf survival between years, sexes, and among DAUs in the Gunnison Basin, Colorado, 2000-01 through 2001-02 based upon chi-square (X2) contingency tests. Likelihood Ratio Ratio t Probability 0.2965 1.10 0.2942 0.1463 2.12 0.1456 6.56 0.D10S 7.07 0.0078 0.06 0.8009 0.06 0.8008 Calf Sexes Pooled DAU E-25 vs E-43 vs E-41 & Years Pooled 5.21 0.0737 5.71 0.0577 2 Calf Sexes Pooled DAU E-25 vs E-43 & Years Pooled 2.52 0.1123 2.56 0.1098 1 Calf Sexes Pooled DAU E-25 vs E-41 & Years Pooled 0.49 0.4827 0.50 0.4808 Calf Sexes Pooled DAU E-41 vs E-43 & Years Pooled 5.30 0.0213 5.59 0.0181 x 2 Calf Survival Rate Comparisons Value Probability Calf Sexes & DAUs Pooled 2000-01 vs 2001-02 1.09 Calf Male VS. Female All Years & DAUs pooled 2.11 Calf Male vs. Female in 2000-01 with DAUs pooled Calf Male vs. Female in 2001-02 with DAUs pooled df Table 5. Percent femur marrow fat in elk calvesdying from estimated causes of mortality during winter-spring Decemberto 14 June, 2000-01 and 2001-02 in the Gunnison Basin.Colorado. . Predation Samples Malnutrition Accidents Unknown 12/1510006/14/01 12/1510106114102 15.8 90.7 68.6 48.7 ).6 45.3 94.4 60.0 27.5 5.3 83.6 75.6 13.2 12/15100- 12/1510106/14/01 06/14/02 Estimated Mortali~ Causes Suspected Suspected Predation Malnutrition 12115/00- 12/1510112115100- 12/1510106114101 06/14/02 06114101 06114/02 42.8 78.5 15 12/15100- 12/1510106114/01 06114/02 12/15/0006/14/01 12/15/0106/14/02 27.1 0.0 ·77.7 Average Fat 24.8 86.8 42.8 n - samples 3.0 4.0 1.0 SD 17.8 SE 10.3 Min 13.2 83.6 Max 45.3 94.4 68.1 38.5 3.0 4.0 5.5 7.8 24.4 2.6 2.7 4.5 12.2 1.8 42.8 60.0 0.0 1.6 42.8 75.6 48.7 5.3 0.0 0.0 3.5 0.0 0.0 2.0 0.0 27.1 1.0 27.1 27.1 �211 Table 6. Survival rates for winter-spring (WS), summer-fall (SF), and annual (Ann) seasonal intervals from 15 December 2000 to 14 June 2002 for adult female elk age ~ years ::::,1year radio-collared in December 2000 and 2001 in the Gunnison Basin, Colorado. Binomial estimator used to calculate survival rates and confidence limts for elk combined among DADs E-25, E-41, and E-43. Adult Female Elk Seasonal Interval and Dates ~S SE 8DD WS 1211S/00 - 06/1S/01- 12/1S/00- 12/1S/01- 06/14/01 12/14/01 12/14/01 06/14/02 1.00 0.92 0.84 1.00 39 39 0 3' 0.92 0.84 1.00 39 39 0 3 1 2 1.00 FEMALES (::2 yrs old) Survival Rate Lower 9S%CL Upper 9S%CL n Collars Collars Deployed Collars Censored Died Non-hunting Deaths Hunting Deaths 39 39 0 0 0 0 FEMALES (::1 yr old) Survival Rate Lower 9S%CL Upper 9S%CL n Collars Collars Deployed Collars Censored Died Non-hunting Deaths Huntin Deaths a 2 1.00 0.91 0.84 0.97 77' 77 0 7 39 39 0 0 0 0 Adult female deaths: 172.7S8/00 48b 48 0 0 0 0 1.00 82 82 0 0 0 0 6 about 7/1101,174.478/00 legal rifle harvest, and 172.030/00 archery/muzzleloading wounding loss. bIncludes 12 additional adult females radio-collared 16-20 December 2001. c Includes 38 yearling females that survived as radio-collared calves. Table 7. Survival rates for winter-spring (WS) and summer-fall (SF) seasonal intervals from 15 December 2000 to 14 June 2002 for the cohort of 6-month old elk calves radio-collared in December 2000 in the Gunnison Basin, Colorado. Binomial estimator used to calculate survival rates and confidence limits for elk combined among DADs E-25, E-41, and E-43. Elk Age (months) and Seasonal Interval and Dates 6-11 mos 12-17 mos 18-23 mos 6-11 mos 12-17 mos WS SF WS WS SF WS 06/1S/01- 12/1S/01- 12/1S/00 06/1S/01- 12/1S/01- 06/14/01 12/14/01 06/14/02 06114101 12/14/01 06/14/02 Survival Rate 0.78 0.86 1.00 Survival Rate 0.97 0.89 1.00 Lower 9S%CL 0.63 0.71 Lower 9S%CL 0.92 0.79 Upper 9S%CL 0.93 1.00 Upper 9S%CL 1.00 0.99 n Collars 32 22 19 n Collars 39 38 34 Collars Deployed 38 2S 19 Collars Deployed 40 38 34 Collars Censored 6 3' 0 Collars Censored 0 0 Died 7 3 0 Died 1 4 0 7 2 1b 0 Non-hunting 1 0 0 0 Hunting Deaths 0 4' 0 12/1S/00 MALES Non-hunting Deaths Hunting Deaths 0 - , Yearling males censored: slipped collars, 173.091/00, FEMALES Deaths - 18-23 mos 173.391100, and 173. S 10/00 between 6/22/01 and 7120/01. b Yearling male illegally wounded and died about 12/10/01 during late-season for antlerless elk. e Yearling females 172.619/00 and 174.360/00 wounded during regular rifle seasons and 174.S60/00 regular rifle and late rifle seasons respectively, and assumed to be legally harvested. 173.S89/00 disappeared during �212 Table 8. Body mass (kg), total body length (em), and hindfoot length (em) of elk calves captured and radio-collared in mid-December 2000 and 2001 in the Gunnison Basin, Colorado. Summaries include only those calves contributing to estimates of survival during winter from 15 December to 14 June and exclude calves dying from capture-induced causes. Values represent average weight (Mean), sample size (n), standard error of the mean (SE), confidence interval of the mean (CI) , minimum (Min) , and maximum (Max) Mass (kg) Calf Groupings Total Body Length (em) HindfootLength (em) Gunnison Mean n SE 95%CI Min Max Mean n SE 95%CI Min Max Mean n SE 95%CI Min Max All Females 98.6 74 1.54 95.5 - 101.7 57.5 121.5 179.0 77 1.15 176.7 - 181.3 143.5 196.0 56.0 77 0.22 55.6 - 56.4 49.0 61.5 All Males 99.6 74 1.64 96.3 - 102.8 52.0 133.0 178.2 76 1.12 176.0 - 180.4 146.0 .196.0 56.4 76 0.30 55.8 - 57.0 47.5 65.0 65.0 All Calves 99.1 14 1.12 96.9 - 101.3 52.0 133.0 178.6 153 0.80 177.0 - 180.2 143.5 196.0 56.2 15 0.19 55.8 - 56.6 47.5 Females 2000 99.9 37 2.14 95.6 - 104.3 57.5 119.0 178.6 39 1.62 175.3 - 181.9 143.5 194.5 55.9 39 0.33 55.2 - 56.5 49.0 59.5 Males 2000 100.8 37 2.56 95.6 - 106.0 52.0 124.5 180.2 37 1.81 176.4 -183.8 146.0 196.0 56.1 37 0.47 55.2 - 57.1 47.5 60.5 All 2000 100.4 74 1.66 97.1 -103.7 52.0 124.5 179.3 76 1.20 176.9 - 181.7 143.5 196.0 56.0 76 0.28 55.4 - 56.6 47.5 60.5 Females 2001 97.3 37 2.22 92.8 - 101.8 57.5 121.5 179.5 38 1.66 176.1 -182.9 151.5 196.0 56.2 38 0.30 55.5 - 56.8 51.5 61.5 Males 2001 98.3 37 2.05 94.2 - 102.5 78.5 133.0 176.3 39 1.30 173.7 - 179.0 163.0 193.5 56.6 39 0.39 55.8 - 57.4 52.5 65.0 All 2001 97.8 74 1.50 94.8 - 100.8 57.5 133.0 177.9 77 1.06 175.8 -180.0 151.5 196.0 56.4 77 0.25 55.9 - 56.9 51.5 65.0 DAUE25 All Calves 95.9 48 1.67 92.5 - 99.3 64.5 118.0 176.6 50 1.25 174.0 - 179.1 151.5 194.5 55.4 50 0.30 54.8 - 56.0 49.0 59.0 DAUE43 All Calves 96.8 50 2.10 92.6 - 101.0 52.0 119.0 175.4 52 1.43 172.5 - 178.3 143.5 193.5 56.3 52 0.37 55.5 - 57.0 47.5 65.0 DAUE41 All Calves 104.4 50 1.81 100.8 - 108.1 57.5 133.0 184.0 51 1.15 181.6 - 186.3 157.0 196.0 56.9 51 0.25 56.4 - 57.4 52.0 60.5 E25 All Calves Trapzone A 97.6 17 2.47 92.4 - 102.9 81.0 118.0 179.6 17 1.98 175.4-183.8 166.0 194.5 55.8 17 0.50 54.7 - 56.8 51.5 59.0 E25 All Calves Trapzone B 96.2 7 3.27 88.2 - 104.2 86.0 109.0 177.1 7 1.66 173.0 -181.1 170.5 181.5 56.2 7 0.73 54.4 - 58.0 53.0 59.0 E25 All Calves Trapzone C 95.1 15 3.94 86.7 - 103.6 64.5 117.0 175.8 17 2.38 170.8 - 180.9 153.0 189.0 54.9 17 0.58 53.7 - 56.2 49.0 58.5 E25 All Calves Trapzone D 93.7 9 3.41 85.8-101.5 73.0 105.0 171.8 9 3.23 164.4 - 179.3 151.5 182.0 54.9 9 0.66 53.4 - 56.5 51.5 57.5 E43 All Calves TrapzoneE 100.4 6 4.68 88.4 - 112.5 87.5 117.0 178.6 7 2.62 172.2 - 185.0 167.5 188.0 55.9 7 0.38 55.0 - 56.9 55.0 58.0 E43 All Calves Trapzone F 93.1 10 6.17 79.1 -107.1 52.0 117.0 170.8 '11 3.90 162.1 -179.5 146.0 185.5 56.8 11 1.36 53.8 - 59.8 47.5 65.0 E43 All Calves Trapzone G 97.3 34 2.41 92.4-102.1 57.5 119.0 176.2 34 1.68 172.8 - 179.6 143.5 193.5 56.1 34 0.37 55.4 - 56.9 49.0 59.5 E41 All Calves TrapzoneH 100.1 11 6.37 86.0 - 114.4 57.5 133.0 181.6 11 3.56 173.7 - 189.5 157.0 193.5 56.3 11 0.71 54.7 - 57.9 52.0 60.0 E41 All Calves Trapzone I 104.9 17 2.60 99.4-110.5 85.5 121.5 185.0 17 1.86 181.0 - 188.9 167.0 196.0 57.3 17 0.40 56.5 - 58.2 54.5 60.0 E41 All Calves Trapzone J 106.1 22 1.79 102.4 - 109.8 89.0 124.5 184.3 23 1.39 181.5 - 187.2 169.0 196.0 56.9 23 0.33 56.3 - 57.6 54.0 60.5 - �213 Table 9. Numbers of adult female elk harvested during late-seasons in the Gunnison Basin, Colorado, NovemberDecember 2000 and 2001 with numbers and percent (%) of harvested adult females from which hunters provided any of the requested biological samples, reproductive organ samples, and kidney fat samples. Samples received for kidney fat expressed as fat with 1 kidney, fat with 2 kidneys; and elk with at least 1 kidney fat sample. Estimates of adult females harvested obtained from CDOW statewide harvest surveys. Late Season Year Adult Females Harvested Adult Females With Any Requested Samples Submitted Adult Females With Reproductive Organs Submitted Adult Females With Kidney Fat Samples Submitted 1 kidney; 2 kidneys; :::1 kidney 17 (6); 40 (14); 57 (20) 2000 291 (100) 81 (28) 58 (19) 2001 374 (100) 46 (12) 31 (8) 22 (6); 5 (1); 27 (7) All 665 (100) 127 ( 19) 89 (13) 39 (6); 45 (7); 84 (13) Table 10. Frequency (%) of dental cementum ages of adult female elk harvested in the Gunnison Basin, Colorado, November-December 2000 and 2001 based on useable incisor tooth samples submitted by hunters. Age Class of Adult Female Elk Based on Dental Cementum (years) Year 3-4 5-7 8-10 11-14 15-20 All 2000 5 7 12 20 10 14 6 74 2001 1 7 15 8 9 4 0 44 All 6 (5) 14 (12) 27 (23) 28 (24) 19 (16) 18 (15) 6 (5) 118 (100) 2 Table 11. Pregnancy rates (%) by age class of adult female elk in the Gunnison Basin, Colorado, NovemberDecember 2000-2001 based on samples submitted by hunters for years combined. Age of elk based on dental cementum. Pregnancy rates based only on numbers of known pregnant and non-pregnant elk per age class. Age Class of Adult Female Elk Based on Dental Cementum (years) Pregnancy Status 3-4 2 Non- Pregnant 0 3 5-7 8-10 11-14 0 1 1 15-20 Unknown Adult 3 4 13 76 (85) All Pregnant 2 (100) 6 (67) 14 (93) 21 (100) 13 (93) 12 (92) 3 (50) 5(56) Unknown 4 5 12 7 5 5 0 0 38 Total 6 14 27 28 19 18 6 9 127 Table 12. Measurements of elk fetal size in the Gunnison, Basin, Colorado during November-December 2000 and 200 L Values represent average size ( Y, mean), sample size (n), standard deviation of the mean (SD), confidence interval of the mean (CI), and minimum (min) and maximum (max) values. November-December Measurements X (n) SO 2000 November-December 95%CI min-max X (n) SO 2001 95%CI min-max Mass (g) Male 64.7(15) 51.0 36.5-92.9 12.4-167.0 119.3 (6) 95.9 18.7-219.9 46.4-289.1 Female 86.8 (24) 97.8 45.5-128.0 12.3-425.5 111.0 (13) 85.5 59.4-162.7 22.1-310.5 Unknown Sex 4.3 (7) 3.7 0.8-7.7 2.0-12.6 4.9 (3) 3.2 0.0-12.7 1.8-8.1 Crown-Ruml2 (mm) Male 114.5 (15) 30.4 97.7-131.4 73.6-165.0 138.6 (6) 31.0 106.1-171.2 11 1.6-186.5 Female 125.6 (24) 39.5 108.9-142.3 68.5-223.0 139.5 (13) 37.7 116.7-162.2 87.9-202.0 Unknown Sex 33.9 (8) 18.6 18.4-49.4 0.5-69.0 44.7 (3) 12.6 13.5-75.9 32.3-57.4 Hind-Leg (mm) Male 44.9 (15) 16.6 35.7-54.0 23.8-73.9 60.6 (6) 15.0 44.9-76.4 47.0-83.4 Female 50.7 (24) 20.3 42.2-59.3 23.6-103.9 59.4 (13) 19.0 47.9-70.9 36.1-91.2 Unknown Sex 24.0 (1) 17.4 (1) Hind-Foot (mm) Male .29.2 (15) 10.6 23.3-35.0 14.9-48.1 40.4 (6) 13.4 26.3-54.5 29.4-61.4 Female 34.7 (24) 16.5 27.7-41.6 14.8-79.9 39.8 (13) 14.8 30.8-48.7 21.4-64.6 Unknown Sex 13.9 (1) 11.5 (1) �214 Table 13. Summary values for total fat kidney fat index (TF-KFI), trimmed fat kidney fat index (TRF-KFI), kidney total fat mass (TFM g), and kidney trimmed fat mass (TRFM g) for adult female elk in the Gunnison Basin during November-December 2000-200 I. Kidney mass one and two could represent either the left or right kidney masses with kidney mass two associated with elk for which both kidney masses were collected by hunters during late antIerless-only hunting seasons. Values represent average size (X, mean), sample size (n), standard deviation of the mean (SD), confidence interval of the mean (CI), and minimum (min) and maximum (max) values. Kidney Mass One Kidney Mass Two Fat Value X (n) SD 95%CI Min-Max X (n) SD 95%CI Min-Max TI-KFI 10.5.8 (84) 54.5 93.9-117.6 29.1-30.6.1 91.0. (45) 37.5 79.8-10.2.3 33.4-165.3 29.1-212.8 70..3 (45) 26.5 62.3-78.3 30..4-136.1 TRF-KFI 78.4 (84) 35.5 70..7-86.1 TIM (g) 218.7 (84) 10.3.9 196.1-241.2 57.0.-551.0. 20.2.4 (45) 90..6 175.2-229.6 72.0.-486.0. TRFM (g) 163.6 (84) 70..4 148.4-178.9 48.0.-383.0. 156.8 (45) 66.3 136.9-176.7 69.0.-388.0. Table 14. Estimates of percent total body fat in adult female elk by pregnancy status and calf elk (sexes combined) in tile Gunnison Basin, Colorado during November-December 2000-2001. Percent body fat based on total fat kidney fat index (TF-KFI), trimmed fat kidney fat index 91RF-KFI), and total kidney fat mass (TFM g) after Cook et al2001a. Comparisons among mean values shown by P-values (ANOVA). Values represent average size (X, mean), sample size (n), and confidence interval of the mean (CI). % Body Fat TI-KFI % Body Fat TRF-KFI X 95%CI X (n) 95%CI X (n) % Body Fat TIM (n) Percent Body Fat 95%CI Max" Adult Females Pregnant 11.2(57) 10..6-11.8 12.1 (57) 11.5-12.8 11.3 (57) 10..8-11.9 7.0. (TI) 18.5 (TRF) Non-Pregnant 10..2 (11) 8.8-11.5 10..9 (11) 9.5-12.2 9.9 (11) 8.9-10..9 8.3 (TIM) 14.8 (TRF) Pregnancy Status Unknown 11.8 (16) 10..4-13.1 12.6(16) 11.1-14.1 11.1 (16) 9.6-12.5 5.4 (TIM) 15.3 (TRF) Pregnant vs. NonPregnant P = 0..143 P=o..1l2 P = 0..0.38 Pregnant vs. NonPregnant vs. Unk, P=o..193 P = 0..198 P = 0..149 AIl Adult Females 11.2 (84) 10..7-11.7 12.1 (84) 11.5-12.6 11.1(84) 10..6-11.6 5.4 (TIM) 18.5 (TRF) Adult Females 20.0.0. 10..7 (57) 10..2-11.3 11.6 (57) 11.0.-12.2 10..8 (57) 10..2-11.4 5.4 (TIM) 18.5 (TRF) Adult Females 20.0.1 12.1 (27) .11.1-13.1 13.1 (27) 12.1-14.1 11.7 (27) 10.,8-12.6 7.3 (TF) 17.0. (TRF) 20.0.0.vs. 20.0.1 P = 0..0.73 P = 0..0.10. P=o.o.o.9 7.1 (6) 4.1-10..1 7.3 (6)" 4.1-10..4 4.1 (6) 1.1-7.0. 0..2 (TIM) 10..4 (TF) Calves 20.0.0. 7.4 (2) 0..3-14.5 7.7 (2) 0..0.-23.4 3.8 (2) 0..0.-8.2 3A (TIM) 9.0. (TRF) Calves 20.0.1 7.0. (4) 1.2-12.8 7.0. (4) 1.1-10.3 4.2 (4) 0..0.-9.9 0..2 (TIM)' 1o..4"(TF) AIl Calves' • Estimates of percent body fat in calves should be viewed with caution as calibration equations developed by Cook et al. 20.0.1 were based only on adult female elk. b Minimum and maximum estimates of percent body fat obtained from either TF- KFI, TRF- KFI, or TFM estimators. �215 Gam~ ,Fig, t, '1\11 a i'iig:em ent Units (54"551); trapzones ih'Hni Olirinisor(Basinill2000 arid 2001. (A-J) , and elkcapture .site s CaptureBite. .Capture Sites: :,.,F •• "Jk~1 Flylrcl U ••• Year: . tI~~mbEr'3D[J :mi' ·:AL •• AI!,,!onJ."n5'ybr • D~(;CmbEr AT. '" 'D'~~rh~~r:ilIlD'3N12DQ' JUI'lIOI"'IITIbrat! " "" 'IV." .i:·aH~r-C:~·r!t:Sw'A CO •• C::tllnCreek co •• COW OUld"ll Wllo'!l . DC •• D.ry ~n:~k 'DO •• DUt::hO~d.. DoV- DlI:ull~C~cl:k ',DY'; "it1!Pl:one~ OU", .","'" orY'-Crel!t.U·pper -ec •. ee IC::tIn cri~k N ',FT•• n~1 Too Souh NO •• Horn Oula. " MR. •• HCltte OUq"I RMOI .. ~:II~·.O:tJd:. "kK_ C.~P :,":Kz:" . '0 "0 ~.m~ ~tI$h '~.w A · LC •• LO~IC~~M tiUd"I :IIP •• lIahfll:l'lIn' P~ •• pOle CtI:,ek 1, ','!'." Jlot:500n · PJdge kB •• fl~dup B .. P.l:d c re ee ~in " · Nf'; 'II.D •• Fled ue Ii F 101 Too Be •. ~p cree e c cen 00 •• SEers.~\Jd't 'au'. SI.CItt Creek ii ..~ri,er1bOl~e;s:·;,.· -,_. '-: '.', Tl!nmlll! EJiifrli .10 •• Tom~ Om.e ,...;.. · TT-. Thtlll: lbp :uua'~tN'~~~'::"u~ : J/Ul"; WJi:SoO"o\acti" WM ••..WIII~'Me~ DIU! :'_ ..:....._. ,:'.WW _1.NllowCr~~k i ', WY •• Wlm~ry,Hanc yo. Y!:~~r·O",Id"_I .. >(~.., ~1~"'II!ne I\l3PC' 20 Kilometers �216 Calf Elk Winter Mortalities Gunnison Basin, Colorado • Lion Predation D Black Bear Predation D Suspected Predation ~ m t;] rn 2. ated s of calf mortaliti during from 15 mber h 14 in the son Colorado, 2000-01, 2001-02, and years combined. Malnutrition Suspected Malnutrition Accident Unknown 5% n = 1 Figure Estim cause elk es r'-'-....._._....._._~ winter Dece '-'-'-r--.---r--.---r--rr---' throug June Gunni Basin, �217 3,-----------------------~----------_r--._----------------------------, Calf Elk Winter Mortalities Gunnison Basin, Colorado ~ ~ 2;------------------,--.-------------~ D Unknown § Accident D Malnutrition • .•.. Iii o Jan 1, 01 Dec 16,00 Mar 1 Jan 16 Feb 16 Predation Jun 1, 01 Apr 1 Mar 16 Apr 16 May 16 Beginning Date of Two Week Intervals December 2000 to June 2001 3-.------- 2+------ -o Iii 1+------- May 1 Apr 1 Dec 16, 01 Jan 16 Feb 16 Mar 16 Apr 16 Jun 1, 02 May 16 Beginning Date of Two Week Intervals December 2001 to June 2002 Figure 3. Timing and estimated causes of calf elk mortalities during winter from 15 December through 14 June in the Gunnison Basin, Colorado, 2000-01 and 2001-02. �218 100 l Calf Elk •Marrow 2000-01 X 2001-02 )1 Fat, Gunnison Basin, Colorado ~ ~ ~ r---1 80 r-. It' ~ m LL. [i] ~ ~ 60 I"V1 Iii :::iE .._ Predation Related :::I E Q) IV Malnutrition Related LL. c: ~ D ~ Q) ~ m Accident 0 Unknown 0 n, [i] IF 40 ® ~ 20 [i] [i] ® (x) o 12/16 1115 ~ 3116 2114 'I" 4/15 5115 6/14 Month and Day Figure 4. Percent femur marrow fat in calf elk mortalities by estimated cause and timing of deaths during winter from 15 December to 14 June in the Gunnison Basin, Colorado, 2000-01 and 2001-02. 30 d2~ ~ ~() ~~ • 2000-01 n=8 x 2001-02 n = 12 25 Predation Related _ 0 Malnutrition Related III 0 Unknown 0 Males n= 74 _c-. Accident o Females n= 74 []~ Z'l 20 ~ o • [] 015 .c r;;j - (.!j CD c-. r+- [] E ::s c-.- Z 10 5 G ~ ~ o ~ 5(}'59 6(}'69 _I]_ 70-79 r-- c-- - - c-- ~ '--~ ,'--80-89 9(}'99 100-109 110-119 .[l n 120-129 130-139 Calf Body Mass Class (kg) Figure 5. Distribution of male and female calf body masses and occurrence of calf mortalities by mass class, calf sex, and estimated cause of death during winter from 15 December to 14 June, Gunnison Basin, Colorado, 2000-01 and 2001-02. �219 20,----------------------------------------------------------------, Elk Conception Dates Gunnison Basin, Colorado 2000-2001, n = 72 - 16-+---------Mode = Sep23 ~ 12 -+---------- c: (J) ::::J 0" ~ LL 8+------ 4-+----- o Sep 1-5 Figure 6. Frequency of estimated conception dates in 5-day intervals for elk fetuses in the Gunnison Basin, Colorado, 2000-2001. Male Elk Fetuses Per Conception Oate Interval, Gunnison Basin 2000-2001 Male & Female Feluses Male Elk Fetuses Per Adult Female Age Class, Gunnison Basin 2000-2001 Per Interval Shown As (11) Male and Female o.,,.---------------__:_:_----, Fetuses ,. 0.6 0.'-1--------111--------_....-----1 : 10.' .!! i';0.4 ~ ~ ~ '2 £. £0.2 ~O.4 ~ 0.3-1--------111---111---111---111-----1 .- :; 0.3 a &. 0.2+--------11----11----11---11-----1 0.1 Per Age Interval Shown As (15) 0.7 +-----11----11----11----11---11-----1 I Sep6-10 Sopl1.15 oo.s SllP21-25 Sepl6-20 Scp26-30 I Oct6-10 , 0.1 I , II 3--4 ' .. I 5-7 11-14 8-10 I 15-20 Adult Female Dental Cementum Age Class . Figure 7. Proportions of male elk fetuses per conception date interval (LEFT) and per adult female age class (RIGHf), Gunnison Basin, Colorado, 2000-2001. �220 EsIImalesPer=t BodyFIlAdu~ FemaleElf. GunnisonBasIn,~ _r·Ooccmber n-84"" "Fot1F-KFl TRFl<R.lFII '" Adult Female Elk Tolal Kidney Fallndex, Gunnison Basin. n = 84 17 ., " . -- .. " 53'" 0 0 '" • 10 8 7 6 5 0 I i ,. " '" f-- 1D f-- 8 I •• 0 ac-es 01-79 41Jo-59 Total 180-199 140-159 100-119 60-99 121)..139 KldneyFallndex 160-179 Values I ~1, '0 I 250-299 10(1.249 ' 7-8.i J~349 (PerCtmt) 1G-1U o 0 0 15-1" _IIoitIFot Figure 8. Frequency of total kidney fat index values (TF-KFI) (LEFT) and percent total body fat estimates (RIGHI) for adult female elk age 2:,1year during November-December, Gunnison Basin, Colorado, 2000-2001. Body fat estimates based on TF-KFI, trimmed kidney fat index (TRF-KFI), and total kidney fat mass (TFM g), respectively, after Cook et al. 2001a. Percent body fat classes 0-6.9, 79.9, 10-14.9, 15-19.9, and 20-24.9 represent body condition classes very low, low, moderate, very good, and excellent, respectively, after Cook J.G. (2001 unpublished data). 0.9 --1-----------t---___..,,---:::;;i.or~ ~,...- ~--:;~"""-'----t----Body-CO-n-ditl-O-n--l ~~u~p~;r~c~D~nfl~d;en~~~L~lm~~~~::~t:::~~~~~=--~~~~~ O.B _, ••••• ---- f -: 0.7--1-----------r- ~~~-~-------+------~ .I' 1;~O.6 #'; ~~l' .• ao:'o~:~on I ! _§''fL_ OO.5--1--------~~~~~·~t---~I~-t---------+------~ I ~ .~.a~' / ~0.4--1------~~7__~~--t--',~Body~--r-------t--------~ c.. 'S> t ~••o I Condition Low 0.3+----9~'---,..;!'"-----t;'1'-----t-------t---------1 +e'li 02 C=~DI1 V.ryLow ~ I # •••• 0.1~~~~---------.~·--t------r-------t---------l .' tlm~ Low •• COnf!ll4'_ O~~~-~·r·~·~-r--r-r--r-~_r--~_r--~~----~--~_,-~_,-~_l o 2 4 6 Estimated B 10 12 14 Percent Body Fat in November-December 16 1B 20 Figure 9. Probability of adult female elk age 2:,1year being pregnant as predicted from percent total body fat based on total kidney fat mass (TFM g) measured in November-December, Gunnison Basin, Colorado,2000-2001. Probablility curve bracketed by approximate 95% confidence limits. Relative body condition rating classes from Cook J.G. (2001 unpublished data). Logistic regression was: logit (P) = -2.2835 + 0.3704 *(X-percent body fat); regression slope significantP = 0.033). �221 Appendix A. Locations of elk capture sites in the Gunnison Basin during December 2000 and 2001. AlIDTM coordinates are referenced to NAD 27 datum projection. Site Code WY WL WM DV TM WW PP AF TT HG WG CC NP LC AL RD WA BV DC RC CG YG KZ RV SU PR DG HR KK TO YP AT EC RB IT SG DY TF SC Trap Site WINNERY HOME WILSON GULCH WILLOW MESA BLUE DEVILS CREEK TENMILE SPRING WILLOWCK 1 POLECK 1 ALKALIFLYING M TABLE TOP HORN GULCH WOODS GULCH CABINCK NORTH PARLIN LOST CANYON GULCH ALMONT TAYLOR REDDEN FLATTOP WEST ANTELOPE CK BEAVER CK SWA DRY CREEK RED CREEK COW GULCH WILLOW YEAGER GULCH KEZAR BASIN NW ROAD BEAVER CK SUGARCREEK POISON RIDGE DUTCH GULCH HOME GULCH RAZOR CAMP KETTLE GULCH TOMICIDDOME YELLOWPINE RIDGE ALMONT TRIANGLE EAST CABIN CREEK ROUNDUP BASIN FLATTOP SOUTH STEERS GULCH DRY CREEK UPPER TENDERFOOT MESA SOAP CREEK COAL Trapzone A A A B B C C D E F F G G G G H J A B B C C D D E E F F G G G H J J Capture UTMx 299842 299987 302286 299507 307088 319409 329616 343809 352655 367555 357804 342564 351341 343419 343020 331774 325259 321816 313617 305342 302170 304088 311114 321992 325267 344624 342179 351874 349729 365097 359615 342507 344065 348075 333051 323101 313563 306929 299839 Capture UTMv 4229298 4232163 4248791 4221245 4252151 4250445 4246431 4238265 4249609 4255415 4263648 4267804 4265757 4275048 4287228 4282420 4274696 4266364 4262208 4263542 4248762 4233715 4257470 4235039 4252487 4223850 4256150 4237208 4250925 4256608 4264943 4287754 4270540 4270061 4281590 4270141 4262643 4264206 4265834 Capture UTMZone 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 Capture 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 Capture 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 �222 Appendix B Summary of calf elk mortalities in the Gunruson Basin, 15 December Trap- Tissue 0 14 June, 2000-01 Death Location Carcass Death Date Recovered Marrow Fat Samples Parasites Status Death Cause 12129/001/4101 5-Jan-01 WhiteCreamy 38.7% YesCM n/a Nearly Complete Capture Lion Related 12119-26/00 3-Jan-01 WhiteFirm Related 211-7/01 7-Feb-01 RedJelly 2115/01 15-Feb-01 F 3121/01 A No Elk ID Sex Mass zone 1 173.082100 M 92 B 2 172.379/00 F 127 H 3 173.640100 F 82 A 4 172.959/00 M 125 J 5 173.351/00 M 52 6 173.160100 M 94 7 173.300100 M 8 173.041/00 9 173.949/00 10 173.011/00 Mass Femur I UTMx UTMy Drainage 303163 4253981 Lake Gulch n1a Scavenged Capture 335406 4282773 FiatT op NoCM Moderate sarcocysts Partially Scavenged Lion Predation 304608 4243376 Lake Fork WateryPink 48.7% NoCM Moderate sarcocysts Carcass Complete Unk.-Suspect Starvation 304753 4261110 Red Ck 24-Mar-01 RedJelly 27.5% NoCM Normal sarcocysts Scavenged Unk-Suspect Starvation 360867 4262422 Yellow 3125/01 26-Mar-01 Red Jelly 42.8% No CM Moderate sarcocystsiNI Carcass Complete Stravation 298132 4230866 Dwyer Gulch 112 3/31/01 1-Apr-01 Red Jelly 0.0% No CM Severe sarcocystsiNI Carcass Complete Unk.-Suspect Starvation 308379 4263917 Dry Gulch M 97 4/13-14/01 15-Apr-01 Red Jelly 77.66% NoCM Severe sarcocystsiNI Nearly Complete Unk.-Suspect Starvation 320104 4270341 Beaver Ck M 107 4/20101 26-Apr-01 RedCreamy 45.27% NoCM Normal sarcocysts Scavenged Lion Predation 311827 4245467 Cebolla M 113 4/28-5/10101 2:>-May-01 Red Jelly nla Scavenged Bear Predation 300715 4268428 E Coal Ck. A = Weight of calf (kg) at capture; CM = capture myopathy; oen diIX C S ummary 0 f ca lf e lk morta lies m A~P1 Trap- Death e 94.7% 15.8% NI 13.15% n/a n/a Pine = no evidence of inflarnation around sarcocysts; n/a = samples not available. unruson B asm, 15 Decem b erto 14 J une, 2001 - 02 Femur Tissue Carcass Death Location No ElklD Sex Mass Zone Date Recovered Marrow Fat Samples Parasites Status Death Cause UTMx UTMy 1 173.429/01 F 100 E 121181 2001 20-Dec-01 Firm core, pink;87.45% NoCM unremarkable Carcass Complete Capture Related Fence Kill 351433 4245033 Prosser Ck 2 173.740101 F 101 E 121211 2001 21-Dec-01 Firm core, pink;66.5% MildCM n/a Carcass Complete Capture Related euthanized 353050 4250600 E. TableTop 3 174.720101 M 101 B 1212123/2001 26-Dec-01 Soft core, pink;88.87% NoCM Low Sarcosysts Partially Scavenged Capture Lion 302744 4230958 Skunk Ck 4 173.269/01 M 98 J 01/.21212002 14-Jan-02 n/a n/a Totally Scavenged Unk-suspect predation 300102 4267074 Pearson Pt. 5 172.350101 F 86 H 0113712002 6-Jan-02 Firm core, pink;78.50% NoCM unremarkable Partially Scavenged Bear Predation 334033 4282350 FlatTop 6 173.852101 F 101 I 1/4-91 2002 10-Jan-02 Firm core, pink;90.71% NoCM Low Sarcosysts Partially Scavenged Lion predation 321888 4275810 W.Antelope 7 175.181/01 M 91 A 1/15-215 12002 6-Feb-02 Firm, red; 68.56% n/a n1a Scavenged heavily Unk-suspect coyote predation 297064 4231180 Dwyer Gulch 8 172.170/01 F 58 H 1/20-211 2002 23-Jan-02 Jelly, red: 1.57% NoCM bronchopnuemonia Carcass Complete ·Accident-Haystack collapse 330243 4280937 Redden's 9 173.861/01 F 102 J 1125-28/ 2002 29-Jan-02 Firm core, pink:94.36% NoCM Moderate sarcocysts Partially Scavenged Lion predation 299250 4267725 Pearson 10 174.770/01 M 92 A 2121-281 2002 4-Mar-02 Soft core, red; 5.27% NoCM Moderate sarcocysts Carcass Complete Accident-fell, trapped 294622 4227200 ElkCk. 11 172.379101 F 81 G 2125-316 12002 7-Mar-02 n/a n/a nla Totally Scavenged Unknown 342715 4288645 AlmontTriangle 12 173.300/01 M none J 2127-3/6 12002 9-Mar-02 n/a n/a nla Not FoundSnow Unknown 299323 4268454 N.Pearson 13 173.632101 F 96 C 3120-25 12002 26-Mar-02 Firm core, pink: 83.60% NoCM Moderate sarcocysts Partially Scavenged Lion predation 322925 4232867 RoadBeaver 14 173.780/01 F 108 J 4/25-4130 12002 1-May-02 Firm core, pink; 27.08% n/a n/a Totally Scavenged Unknown 306109 4267739 Red Ck. 15 175.240101 M 100 C 5/15-20 12002 21-May-02 Red,firm core;60.02% nla n/a Totally Scavenged Unk-suspect predation lion 325443 4235881 N. RoadBeaver 16 174.180/01 M 95 E 5/15-201 2002 22-May-02 Firm core, pink;75.63% n/a n/a Totally Scavenged Unk-suspect predation lion 351363 4240438 Home Gulch Mass Ck n/a Related I lion Drainage Mt Mtn Ck PI. PI. Ck Ck = WeIght of calf (kg) at capture> CM = capture myopathy: n/a = samples not available Appen diIX D Summary 0 f a dul te lk morta ties in tlie Gunruson B asm 15 Decem b er 2000 to 14 June 2002 Death Location Femur Tissue Para- Carcass Death Date Recovered Marrow Fat Samples sites Status Death Cause UTMx UTMy Drainage H >06/22<7121/01 21-Jul-01 n/a nla n/a Decomposed Unknown 321262 4294461 S. Carbon M G >06122<7124101 24-Jul-01 77.46% nla nla Scavenged Unk-Suspect Predation 354289 4290527 Summerville M G >6122<7120/01 16-Aug-01 n/a n/a n/a Heavily Scavenged Unk-Suspect Predation 384766 4303460 Trap- Age@ No ElklD Death Sex zone 1 172.758/00 19 yrs F 2 173.330100 12 mos 3 173.340100 12mos Mortality Mtn. Ck. N> Cottonwood Ck. 4 172.030100 6yrs F C >9125<10118101 19-0ct-01 wh~e,solid 97.31% n/a n/a Heavily Scavenged Archery/Muzzle v.ound loss 322980 4227638 Swinehart 5 172.619/00 16mos F J >1 0/13<1 0/18/01 20-0ct-01 pink,crumbles 85.18% n/a n/a Complete Rifle wound 1st season loss 299161 4275164 CowCk. 6 174.478/00 5-9 yrs F G 10/1312001 17-0ct-01 n/a n/a n/a Hunter Kill Rifle 1st season Legal 341000 4242650 RockCk. 7 174.360100 17mos F G >11/8 <11/16101 17-Nov-01 white/gray, solid 95.18% n/a n/a Complete Rifle 4th season v.ound loss 346979 4279939 E. Beaver Ck. 8 174.140/00 18mos M C > 1215 <12128/01 29-Dec-01 white/pink, firm 86.27% n/a n/a Scavenged Late rifle 'M)undfillegal 308573 4242145 Lake City Cut-Off Gulch loss 9 173.589/00 18 mos F B > 12128/01 <113/02 n/a n/a n/a n/a nla Disappear Late Rifle season Legal n/a n/a Low Cebolla 10 174.560/00 17mos F J >10130101<121311 n/a n/a n/a nla nla Disappear 3rd rifle season Legal nla n/a WestBkCk 01 Age estimated USing dental cementum or known age as elk collared as calf. Ck �223 APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR RESEARCH FY 2000-01 - FY 2003-04 State of: Colorado Project No.: W-lS3-R-14 Work Package:_...::3:...::0-,,-0=2 __ Study No. : -=3"--__ ESTIMATING Cost Center 3430 Mammals Research Program Elk Conservation Estimating Calf and Adult Survival and Pregnancy Rates of Gunnison Basin Elk Populations CALF AND ADULT SURVIVAL AND PREGNANCY BASIN ELK POPULATIONS RATES OF GUNNISON Principal Investigators David J. Freddy, Wildlife Researcher, Mammals Research R Bruce Gill, Wildlife Research Leader, Mammals Research Cooperators Rick Kahn, Terrestrial Field State Coordinator John Ellenberger, State Big Game Coordinator Jim Olterman, Senior Biologist, West Region Don Masden, Gunnison Area Terrestrial Biologist Jim Young, Gunnison Area Wildlife Manager Gary C. White, Professor Wildlife Biology, Colo. St. Univ. David C. Bowden, Professor Statistics, Colo. St. Univ. STUDY PLAN APPROVAL Prepared by: Date: _ Submittedby: _ Reviewed by: _ Approvedby: _ _ Date: _ Date: _ Date: _ Date: _ Date: _ Biometrician Date: Research Leader November 2000 Final _ �224 PROGRAM NARRATIVE STUDY PLAN State of: Colorado Project No.: W-153-R-14 Work Package: 3002 Study No.: 3 Cost Center 3430 Mammals Research Program Elk Conservation Estimating Calf and Adult Survival and Pregnancy Rates of Gunnison Basin Elk Populations A. NEED Elk (Cervus elaphus nelsoni) are a high-profile and highly valued resource throughout much of Colorado because elk provide recreation for persons who hunt, watch, and photograph wildlife (Freddy et al. 1993). The elk resource has many benefits but frequent social, political, and economic conflicts suggest elk can reach "social" ifnot ''biological'' carrying capacities. Recent controversy surrounding management of elk in the Gunnison Basin of Colorado (Roath et al.1999) exemplifies conflicting social and biological agendas regarding appropriate numbers of elk. The core of conflict in elk management often centers on establishing management objectives for numbers of elk that are agreeable to competing interests and then monitoring elk populations to demonstrate that objectives are achieved. This type of conflict is paramount in Colorado Division of Wildlife (CDOW) elk population Data Analysis Units (DAUs) E-25, E-41, and E-43 in the Gunnison Basin (Fig. 1) where a combination of resource carrying capacity objectives for elk on winter ranges and difficulties associated with knowingly achieving those objectives has fostered argumentative distrust among public groups and management agencies. Accomplishing management by population objective can depend on reliably estimating elk population size. Estimating population size is expensive and intensive (Samuel et al. 1987, Bear et al. 1989, Unsworth et al. 1990, Anderson et al. 1998, Cogan and Diefenbach 1998, Eberhardt et al. 1998, Freddy 1998) and these factors often preclude routinely using tested inventory methodologies. Alternatively, population size and trend can be estimated using computer models that incorporate harvest, age and sex ratios, and survival rates (White 1992, Bartholow 1999). Model outputs are extremely sensitive to estimates of survival rates such that, reliable measurements of survival can greatly enhance the quality of models (Nelson and Peek 1982). Thus, estimating survival rates is fundamental to modeling elk popula~ions in the absence of routine measurements of population size. Estimating calf and adult female survival during winter and annual rates of survival for adult females are higher priorities than estimating adult male survival primarily because most males are harvested when they reach legal age and contribute little to long-term problems of population growth or decline. Models having valid estimates of survival along with currently obtained precise estimates of harvests and population composition would provide more defensible estimates of population size. Although small changes in adult female survival can have major effects on population growth or decline if compounded for several years, calf survival is likely more variable among years. The ability to detect changes in calf survival should be greater than detecting smaller, but important changes in adult female survival (White et al. 1987, Bartmann et al. 1992, Freddy 1998). Estimates of calf survival in Colorado during winter are limited to the Grand Mesa in west-central Colorado where yearly average survival varied between 0.86 and 0.92 from 1993-1996 (Freddy 1998, 67 calves/year). Applying these survival rates to other Colorado elk populations, especially those populations using winter ranges higher n::: '\, November 2000 Final �225 in elevation, colder, and more prone to significant snow depths such as in the Gunnison Basin, mayor may not be appropriate. Rates of survival on the Grand Mesa were higher than expected and considerably greater than 0.70-0.72 survival rate estimated for elk calves during winter in Yellowstone National Park (Houston 1982, Singer et al. 1997). Estimates of annual survival for radio-collared adult female elk in Colorado averaged 0.95 and ranged from 0.94-0.99, excluding hunting mortalities, for several populations inhabiting widely differing ecosystems (Petersburg and White 1998, Freddy 1999; n > 1,250 adult female-years). Because of the availability of these adult survival estimates, the need to estimate adult female survival is therefore less than the need to obtain additional estimates of calf survival, but ideally we would measure both calf and adult survival simultaneously to document relative differences in survival. A recent evaluation of existing population models for elk in the Gunnison Basin and subsequent development of new population models using estimates of calf and adult survival measured in Colorado altered population trajectories and relative size (Freddy 2000). Consequently, management objectives for Gunnison elk were amended to continue reducing numbers of elk in all DAUs. Controversy surrounding new models and management decisions reinforced the need to obtain measurements of elk survival specific to the Gunnison Basin. B. OBJECTIVE This project will obtain estimates of population parameters for elk in the Gunnison Basin. Major objectives are: 1) Estimate survival rates of elk calves during winter from 15 December-14 June within ±15% of the true survival rate at the 95% confidence interval for 3 consecutive years and identify probable sources of mortality. 2) Estimate winter (15 Dec-14 Jun) and yearly (15 Dec-14 Dec) survival rates of adult females for 3 consecutive years to assess whether the true survival rate is likely 2:0.95 and identify probable sources of mortality. 3) Estimate pregnancy rates of adult female elk harvested during November-December late hunting seasons for 3 consecutive years if late hunting seasons are scheduled. 4) Estimate hunting removal rates for adult females, yearling males, and when possible, adult males for 3 consecutive years. 5) Evaluate Gunnison elk population models using newly acquired survival rates. C. EXPECTED RESULTS OR BENEFITS This project will provide estimates of survival rates for calf and adult female elk and estimates of hunting removal rates for adult elk in the Gunnison Basin DAUs E-25, E-41, and E-43 for 3 consecutive years. These estimates will immediately assist the CDOW in refining population models for Gunnison elk and provide estimates of survival/removal that may be applicable to modeling other elk populations inhabiting similar habitats. In the process of estimating survival rates, probable causes of mortality will be identified which may provide insight into relative health status of elk. Additionally, estimates of pregnancy rates will provide documentation on the fecundity of these elk in relation to other elk populations in Colorado and other states. November 2000 Final �226 D. APPROACH EXPERIMENTAL DESIGN SURVIVAL RATES Radio-telemetry Equipment Survival rates will be estimated by marking elk with radio-telemetry collars that emit a mortality pulse code when collars remain motionless for 4-6 hours (White et a1.l987, Freddy 1993). Radios provide the ability to know the fate of individual animals (alive or dead) over discrete periods oftime (White and Garrott 1990). Radio-collaring does not likely bias estimates of survival by jeopardizing or enhancing the welfare of individuals when radio-collars weigh <0.8% of an ungulate's body weight (Garrott et al. 1985, White et al. 1987). Radio-collars similar to those previously designed and successfully used for calf and adult elk on the Grand Mesa, Colorado will be used in this project (Freddy 1993, Appendix I). Collars for male and female calves will allow for expansion to adult size while adult female collars will be of fixed circumference and fitted to each individual. Calf collars weigh 840 gm and represent <1 % of expected calf body weight while adult collars weigh 1.1 kg and represent <0.5 % of expected body weight. Collars will be white in color, have a unique black colored number/symbol embossed on bright yellow plastic material (Ritchey Manufacturing, Brighton, CO) attached to the dorsal surface of collar to enhance visual identification from helicopters (Appendix II), have unique frequencies between 172-176MHz, and a battery life of.:=::4years. Animal Capture We assume survival of those elk captured provides an unbiased estimate of population survival rates recognizing that individual behavior, social behavior, trapping methods and distribution of trapping effort all potentially bias those individuals actually marked (White et al. 1982). Recognizing these problems, elk will be captured with the intent of systematically marking elk throughout the distribution of elk in the Gunnison Basin. Each of the 3 DAUs, will be divided into trap-zones having multiple trap-sites. Capture quotas for calves and adults in trap-zones within each DAU will be proportional to expected elk density as estimated from yearly sex and age ratio classification flights conducted each January throughout the Gunnison Basin. Trap-zones will be initially defined as: 1) for DAU E-25: Big Blue Creek to Gunnison River (TzA), Gunnison River to Cebolla Creek (TzB), Cebolla Creek to Gold Basin Creek (TzC), and Gold Basin Creek to Cochetopa Creek (TzD), 2) for DAU E-43: Cochetopa Creek to Tomichi Creek (TzE), Tomichi Creek to Quartz Creek (TzF), Quartz Creek to East River (TzG), and 3) for DAU E-41: East River to Ohio Creek (TzH), Ohio Creek to Dry Creek (TzI), and Dry Creek to Curecanti Creek (TzJ). Elk will be captured using a Hughes 500 helicopter and net-guns (contracted services) (Freddy 1994). We will attempt to collar equal numbers of male and female calves. Helicopter trapping will occur in mid-December each year. Capture and handling procedures will follow protocols used to capture 257 calves and 46 adult females on the Grand Mesa (Freddy 1993-1996) and previously approved by CDOW Animal Care and Use Committee (Appendix Ill). Survival Monitoring Radioed elk will be monitored daily from the ground and bimonthly with aerial surveys (Cessna 185 or equivalent) to determine life/death status of elk. During hunting seasons, aerial surveys will be occur bimonthly in September and weekly during October and November. RADIOS database program will be used to maintain animal records. November 2000 Final �227 Suspected mortalities will be confirmed using ground searches. Criteria for assigning probable cause of death will include body position, presence of bite or claw marks and sub-dermal hemorrhaging, tracks, drag marks, and tissue samples if available (Wade and Browns 1982, Freddy 1998). Potential causes of death include starvation, accidental trauma, plant poisoning, predation by black bears, mountain lions, coyotes, and domestic dogs, and legal and illegal hunter harvest (Freddy 1997). Survival Sample Sizes and Tests Each year we will radio-collar 78 calves (39 male, 39 female) with 26 calves marked in each DAU and during the initial year, 39 adult females will be radio-collared with 13 in each DAU (Table 1). We anticipate >20 radioed female calves will be recruited to yearling adults each year resulting in >50 radioed adult females in the population to estimate adult survival in subsequent years. However, by not collaring known adult females each year, we run the risk of having biased estimates of adult female survival because the age structure of collared adult females will progressively be biased to younger aged females recruited from marked calves. An alternative would be to mark enough adult females in each subsequent year to replace those adult females marked in year 1 that had died the previous year. We anticipate needing to replace 15-20 older adult females per year to achieve this goal which will be dependent on future funding. If adult females could be replaced yearly, we would be able to separate year effects from age effects on survival rates. Approximately 30 yearling males will be available each year, 2001-2003, to estimate percent of yearling males illegally removed under a hunting system using antler-point regulations to protect yearlings. Approximately 30, 2:2-year-old males will be available each year, 2002-2004, to estimate percent of branch-antlered males removed with a hunting system using antler-point regulations. We chose to mark 78 calves per year and 39 adult females during the initial year because we will have acceptable confidence intervals about mean estimates of survival each year for all DAUs pooled into 1 elk population, have the potential to detect major differences in survival between years due to changes in winter severity when all 3 DAUs are pooled, and be able to detect major differences in survival between DAUs when data are pooled within DAUs for 3 years. The ability to detect differences between DAUs within years is desirable but economically prohibitive due to numbers of collared elk required (>47 per DAU per year). We anticipate yearly calf survival to be 0.70 to 0.90 and adult survival, exclusive of hunting-related deaths, to be 0.95 to 0.99. If calf survival is 2:0.70 (n = 78 calves), 95% confidence intervals (Zar 1984, 378) will be.:::: ±15% of the yearly mean survival rate. If adult female survival is 2:0.95 (n 2: 39 adults), 95 % confidence intervals will be .:::±1 0% of the yearly mean survival rate. Additionally, if adult female survival = 0.95 we expectto estimate yearly survival within ±5% of the true survival rate at alpha = 0.l0 when n 2: 50 adult females. November 2000 Final �228 Table 1. Elk calves (6 months old) and adult females ~12 months old) captured and radio-collared for Gunnison elk DADs E-2S, E-41, and E-43, December 2000-2002 (shaded cells). Adult females captured only during initial year, 2000. Numbers of radioed adult males and females in December years 2001-05 estimated by assuming survival rates between years: adult females net rate = 0.7, male and female calves to yearling adult age net rate = 0.8, yearling males to adult males net rate = 0.9, adult males net rate = 03 DAUE-25 Calves DAU E-41 Adults Calves DAU E-43 Adults Calves ALLDAUs Calves Adults Year M F M F M F M F M F M F 2000 13 "13 0 13 13 13 0 13 13 13 0 13 2001 .13 13 10 19 13 13 10 19 13 13 10 2002 13 13 13 23 13 13 13 23 13 13 2003 14 26 14 2004 4 18 2005 1 13 42' 112' ALL - 39· 39 39 39 Adults Totals M F M F All 39 39 0 39 117 19 39 39 30 57 165 13 23 39 39 39 69 186 26 14 26 42 78 120 4 18 4 18 12 54 66 1 13 1 13 3 39 42 42' 112' 42' 112' 126' 336' 696' 39 39 . - 117 117 '~""~~y a Represents elk-years and not necessanly numbers of individual radioed adult elk as adults survrve between years. Number of collars deployed in combination with actual survival rates determines our ability to detect differences in survival among years, DADs, or geographic areas. When survival rates are near 0.50, variance, or precision, about the mean survival estimate is largest, and thus the sensitivity to detecting differences in survival rates is least (Zar 1984). As survival rates approach 0.0 or 1.0, precision improves for a fixed sample size of collars, and sensitivity to detecting differences in survival increases. Given our assumptions about expected average survival rates and potential higher calf survival in DAD E-2S based on computer modeling (Freddy 2000), we estimated the statistical power (Snedecor and Cochran 1967; 113,221,269; pers. comm. D. Bowden) to detect differences in mean survival rates given specific hypotheses. We consider detecting differences in survival of 0.20 with statistical power of 0.80 at an alpha = 0.10 to be acceptable. Generalized hypotheses (S = survival rate) and power for detecting major differences in survival among years, DADs, age and sex classes, and geographic areas. '. -. (1) 110: Scalvesyearl = Scalvesyear2 = Scalvesyear3 for DAUs pooled each year. HA: Scalvesyearl Scalvesyear2 Scalvesyear3 for DAUs pooled each year. Power = 0.80 at alpha = 0.10 to detect differences in yearly survival of 0.15 between pairs of years given 78 collars per year and expected survival rates of 0.90 and 0.75. Power = 0.80 at alpha = 0.10 to detect differences in yearly survival of 0.15 between I year with lower survival and the average higher survival of the other 2 years given 78 collars per year and expected survival rates of 0.75 and 0.90. (2) 110: ScalvesDAUl = ScalvesDAU2 = ScalvesDAU3 for years pooled for each DAU. HA: ScalvesDAUl * ScaivesDAU2 * ScaivesDAU3 for years pooled for each DAU. Power = 0.80 at alpha = 0.10 to detect a difference in 3-year average survival of 0.15 between pairs of DADs given 26 collars per year-per DAD and expected yearly survival rates of 0.90 and 0.75. * November 2000 Final * �229 Power = 0.90 at alpha = 0.l0 to detect difference in 3-year average survival of 0.15 between 1 DAD with higher survival and the average lower survival of the other 2 DADs given 26 collars per year per DAD and expected yearly survival rates of 0.90 and 0.75. Power = 0.90 at alpha = 0.l0 to detect difference in 3-year average survival of 0.15 between 1 DAD with higher survival and the average lower survival of the other 2 DADs given 26 collars per year per DAD and expected yearly survival rates of 0.90 and 0.80 and 0.70 among DADs. (3) 110: Smale calves = Sfemale calves for years pooled for each sex. HA: Smale calves"" Sfemale calves for years pooled for each sex. Power = 0.90 at alpha = 0.10 to detect difference in 3-year average survival of 0.15 between sexes of calves given 35 collars per year per calf sex and expected survival rates of 0.75 for one sex and 0.90 for the other sex. (4) Ho: Sadultfemalesyearl = SadUItfemalesyear2 = Sadultfemalesyear3 for DAUs pooled each year. HA: SadUltfemales yearl "" Sadultfemales year2 "" Sadultfemales year3 for DAUs pooled each year. Power = 0.80 at alpha = 0.10 to detect difference in survival of 0.15 between pairs of years given 56 collars per year and expected survival rates of 0.95 and 0.80. Power = 0.80 at alpha = 0.10 to detect differences in yearly survival of 0.15 between 1 year with lower survival and the average higher survival of the other 2 years given 50 collars per year and expected survival rates of 0.80 and 0.95. (5) Ho: Scalves = Sadultfemales 110: Scalves "" Sadultfemales Power = 0.80 at alpha = 0.10 to detect difference of 0.15 between calf and adult female survival within each year given 56 collars per year per age class and expected survival rates of 0.80 for calves and 0.95 for adult females. Power = 0.90 at alpha = 0.l0 to detect difference in 3-year average survival of 0.10 between calves and adult females given 51 collars per year per age class and expected survival rates of 0.85 for calves and 0.95 for adult females. (6) 110: Scalves Gunnison = Scalves Grand Mesa for years pooled within each area. HA: Scalves Gunnison "" Scalves Grand Mesa for years pooled within each area. Power = 0.80 at alpha = 0.05 to detect difference in a 3-year average survival of 0.10 between calf survival in the Gunnison Basin and calf survival on the Grand Mesa given 66 collars per year per area and expected survival of 0.80 in the Gunnison Basin and 0.90 on the Grand Mesa. Survival will be estimated for calves and adults during winter-spring (15 Dec -14 Jun), for adults during summer-fall (15 Jun-14 Dec), and for adults during the year (15 Dec - 14 Dec). The yearly time period, or biological year, initiates with capture and release of marked elk into the population (White et al. 1987). Capture of elk will occur in mid-December instead of early December as on the Grand Mesa (Freddy 1993-1997) to accommodate capture services on other projects. We expect this change in capture dates to have minimal effects on estimates of survival as no natural deaths of calves or adults occurred during December on the Grand Mesa (Freddy 1999). We will use a staggered entry Kaplan-Meier analysis to estimate survival rates (SAS 1988, White and Garrot 1990, Bartmann et al. 1992). We will compare survival rates using chi-square analyses and conduct pair-wise comparisons using log-rank tests to compare survival of calves and adults among years for DADs combined, between DADs for years combined, between male and female calves, and between calves and adults. We will assess whether calf survival can be predicted from sex, body weight, hind November 2000 Final �230 foot length, total body length, and mean monthly snow depths and temperature using logistic regression (SAS 1988). Additionally, we will test for differences in survival of calf and adult elk between the Gunnison Basin and the Grand Mesa (Freddy 1998) potentially using beta-binomial distribution approaches outlined by Unsworth et al. 1999. Tests will be significant at alpha P S 0.10. PREGNANCY RATES Fecundity of adult female elk will be determined by examining reproductive organs of antlerless elk harvested during hunting seasons from mid-November through December. Initially, late seasons are scheduled to occur in 2000, but may continue in subsequent years depending upon population management objectives. Numbers of hunters will be controlled by limited permits issued each year. During 2000, we anticipate >650 hunters will provide 2:.200useable reproductive tracts from antlerless elk harvested in portions ofDAUs E-25, E-41, and E-43. Hunters will be mailed packets explaining procedures for collecting reproductive organs and incisor teeth from harvested elk as done previously in Colorado for Middle Park and Forbes-Trinchera elk collections (Freddy 1992, pers. comm. C. Wagner, CDOW). Additionally, we will ask hunters to collect kidneys and associated fat from harvested elk to allow calculation of kidney-fat indices to better assess body condition of adult females in relation to reproductive status (Kohlmann 1999). Hunters will be directed to leave collected organs at drop-off sites in Lake City, Colorado, Gunnison CDOW Service Center, Gunnison commercial meat-processors, and at CDOW Roaring Judy Hatchery. Fetuses will be sexed, weighed, and measured (Armstrong 1950) with conception dates estimated from fetal measurements (Morrison et a1.l959). Pregnancy status, fetal age, fetal sex, and conception dates will be related to female dental cementum age and kidney fat indices using regression analyses (SAS 1988). Additionally, comparisons to reproductive measurements on elk from Middle Park and ForbesTrinchera will be made. POTENTIAL ADDITIONAL EXPERIMENTS AND APPLICATIONS Management of elk in the Gunnsion Basin has contentiously focused on population status of elk, impacts of elk on plant communities, long-term carrying capacities for wild and domestic ungulates and seasonal patterns of habitat use (Carpenter et al. 1980, Roath et al. 1999). Expanding our understanding of these general topics can be greatly enhanced by effectively utilizing the radio-collared elk that will be available because of this project. Investigations regarding these topics could be initiated with additional funding, personnel, and agency cooperation. Potential investigations could address; a). Management objectives as of1999 are to reduce elk populations in DAUs E-25, E-41, and E43. Reductions are projected to be most severe in DAU E-25 and approach 50% over the next 5 years based on computer models. Reductions in DAUs E-41 and E-43 are projected to be <25% and completed in 2-3 years. If elk are indeed at biological carrying capacity and if reductions proceed in E-25, there may be the opportunity to conduct management experiments to assess whether calf survival and/or fecundity increase in response to lowered density. Radio-collaring and monitoring additional calves each year would be required. Estimated additional costs could approach $50,000. b). Population reductions may also create an opportunity to apply sampling systems developed to estimate elk density, including mark-resight estimators (Freddy 1998), to verify modeled population status and achievement of populations goals. Estimated additional costs would be in helicopter hours ($40,000) and additional radio-collared elk ($40,000) for mark-resight surveys. Additionally, sampling systems to estimate sex ratios could be implemented and evaluated in E25 with reallocation of existing survey monies plus an additional $10,000. November 2000 Final �231 c). Patterns of habitat use and forage removal could be investigated utilizing intensive measurements on selected range sites and monitoring of radioed elk and their associates. would be a major project and possibly approach $100,000 per year including additional personnel. This d). Seasonal movements and patterns of spatial use to document seasonal behavior of elk would require additional personnel and aerial fixed-wing costs of $40,000 per year. PROJECT SCHEDULE Fiscal Year 2000-01 Activitv/Objective Complete study plan; purchase radio-collars; Estimate pregnancy/fetal rates; Trap and radio-collar elk and estimate survival. Period Jul-Nov Nov-Dec Dec-Jun 2001-02 Estimate survival and hunting removal rates; Estimate pregnancy/fetal rates; Trap and radio-collar elk and estimate survival. Jul-Dec Nov-Dec Dec-Jun 2002-03 Estimate survival and hunting removal rates; Estimate pregnancy/fetal rates; Trap and radio-collar elk and estimate survival; assess potential for mark-resight estimates of elk density. Jul-Dec Nov-Dec Dec-Jun 2003-04 Estimate survival and hunting removal rates; complete data analyses, initiate manuscripts. Jul-Jun Estimated Annual Costs FTE Requirements PFTE = 1.00 TFTE= 0.83 TOTAL = 1.83 Budget Category (01) Personal Services (21) Operating Supplies and Services (21) Utilities (28) Travel Expenses (31) Capital Outlay Total Costs Costs $102,000 84,000 o 1,000 o $187.000 Costs anticipated to increase 5% each year in 2001-02, 2002-03, 2003-4 for inflation. November 2000 Final �232 Personnel Program Responsibilities David J. Freddy: Wildlife Researcher, Principal Investigator responsible for final project design, organizing field personnel, obtaining and organizing data, data analyses, financial control, and coordinating publications. R. Bruce Gill: Wildlife Research Leader, provides administrative support, input for study design, and liaison with other administrative sections within the Division of Wildlife. Rick Kahn, John Ellenberger, Jim Olterman, Don Masden, Jim Young: Provide coordination and support of Terrestrial managers and biologists and Area management staff and facilities. Gary C. White: Provide input for study design and statistical protocol, conduct data analyses, and provide software support. David C. Bowden: Provide input for study design and statistical protocol. E. LOCATION .The Gunnison Basin in south-central Colorado was selected for this project (Fig. 1). The Basin encompasses the entire headwaters of the main Gunnison River and the centrally located town of Gunnison. Between 12-16,000 elk and 8-10,000 mule deer (OdocoiZeus hemionus) are thought to exist within the Basin. Elk are managed as 3 populations representing DAUs E-25 (Game Management Units [GMU] 66,67), E-41 (GMU 54), and E43(GMUs 55, 551). The 3 DAUs encompass about 9,291 km2 of which 3,648 km2 are considered winter range for elk (CDOW WRIS database). DAUs are contiguous with no major geographic barriers separating DAUs that would prevent interchange of elk among DAUs. · t: · Ni ·· · co.~~ ..· ··.. ....------ ····I....·~~·~;les The Basin represents a high altitude, cold winter range for both elk and mule deer which 80 Km is similar to ecosystems in North Park, Middle Fig. 1. Location of the Gunnison Basin and elk Data Park, and the Scm Luis Valley, Colorado. Th~ Analysis Units E-25, E-41, and E-43 within Colorado. sagebrush steppe winter ranges (2,250- 2,700 m elevation) can receive extreme snow depths and cold temperatures that cause severe mortality among ungulates (Carpenter et al. 1984) while the conifer-alpine summer ranges (3,000 - 4,200 m elevation) can be subjected to drought. Overall, these ranges collectively are thought to be less productive and nutritious for elk than the milder climate oakbrush-pinyon-juniper winter ranges of the Grand Mesa where elk survival was measured from 1993-99. We anticipate dependable access to both private and public lands to conduct research activities and there is local, Area, and Regional CDOW support for conducting the project in this area. Additional financial and logistical support may be available from the Gunnison Habitat Partnership Committee. The airport and other businesses in Gunnison will provide readily accessible support services. November 2000 Final �233 F. RELATED FEDERAL AID PROJECTS Calf and adult elk survival rates were measured on the Grand Mesa, Colorado from 1993-99 under Federal Aid Research Project W-153-R (Freddy 1994-1999). . ,•. j" G. LITERATURE CITED Anderson, C.R, Jr., D.S. Moody, B.L. Smith, F.G. Lindzey, and R P Lanka. 1998. Development and evaluation of sightability models for summer elk surveys. Journal of Wildlife Management 62:1055-1066. Armstrong, R.A. 1950. Fetal development of northern white-tailed deer. American Midland Naturalist 43:650-666. Bartholow, J. 1999. POP-IT system documentation Windows™ Version 1.0. Fossil Creek Software, Fort Collins, Colorado USA. Bear, G.D., G.C. White, L.H. Carpenter, RB. Gill, and DJ. Essex. 1989. Evaluation of aerial markresighting estimates of elk populations. Journal of Wildlife Management 53:908-915. Bartmann RM., G.c. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121. Carpenter, L.H., D.L. Baker, and R.B. Gill. 1980. Tests of a nutritionally based big game habitat .' evaluation system. Colorado Division of Wildlife Unpublished Report. ColoradctDivision of . _- Wildlife, Fort Collins, Colorado, USA. Carpenter, L.H., R. B. Gill, D. L. Baker, and N.T. Hobbs. 1984. Colorado's big game supplemental winter feeding program. Colorado Division of Wildlife , Fort Collins, Colorado USA. Conner, M.M. 1999. Elk movement in response to early-season hunting in the White River Area, Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. Cogan, RD., and D.R. Diefenbach. 1998. Effect of under counting and model selection on a sightabilityadjustment estimator for elk. Journal of Wildlife Management 62:2~9-279. Eberhardt, L.L., R.A. Garrott, P J. White, and P J. Gogan. 1998. Alternative approaches to aerial censusing of elk. Journal of Wildlife Management 62:1046-1055. , Freddy, DJ. 1992.' Effect of elk harvest systems on elk breeding biology. Colorado Division of Wildlife Research Report July: 45-70. Fort Collins, Colorado, USA. July:45-70. . Freddy, DJ. 1993. Program Narrative for Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July: 83-117. Fort Collins, Colorado, USA. " Freddy, DJ. 1994. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July: 27-42. Fort Collins, Co10rado,USA. Freddy, D J. 1995. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July: 63-79. Fort Collins, Colorado, USA. Freddy, DJ. 1996. Estimating survival rates of elk and developing techniques to estimate population size. . Colorado Division of Wildlife Research Report July: 87-108. Fort Collins, Colorado, USA. Freddy, DJ. 1997. Estimating survival rates elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July: 47-73. Fort Collins, Colorado, USA. Freddy, DJ. 1998. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July: 177-206. Fort Collins, Colorado, USA. Freddy, D J. 1999. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Research Report July: (in press). Fort Collins, Colorado, USA. Freddy, DJ. 2000. Modeling elk populations in the Gunnison Basin, Colorado using POPIT and POPMOD software (draft in process). Colorado Division of Wildlife Special Report No.??, Fort Collins, Colorado USA. Freddy, D J., D.L. Baker, R.M. Bartmann, and R C. Kufeld. 1993. Deer and elk management analysis guide, 1992-1994. Colorado Division of Wildlife Division Report 17, Fort Collins, Colorado USA. of November 2000 Final �234 Garrott, RA., R.M. Bartmann, and G.c. White. 1985. Comparison of radio-transmitter packages relative to deer fawn mortality. Journal of Wildlife Management 49:758-759. Houston, D.B. 1982 .. ThenorthernYellowstone elk, ecology and management Macmillan Publishing Company, Inc. York, New York, USA. Kohlmann.SiG. 1999. Adaptive fetal sex allocation in elk: evidence and implications. Journal of . Wildlife Management 63: 1109-1117. Morrison, JA., C.E. Trainer, and PL. Wright 1959. Breeding seasons in elk as determined from knownage embryos. Journal of Wildlife Management 23:27-34. Nelson, LJ., and J.M. Peek. 1982. Effect of survival and fecundity on rate of increase of elk. Journal of Wildlife Management 46:535-540. . .. Petersburg, M., and G. White. 1998. Kaplan-Meier survival estimates for cow elk. Colorado Division of Wildlife Terrestrial Section Unpublished Memorandum, Fort Collins, Colorado USA. Phillips, G.B. 1998. Effects of human-induced disturbance during calving season on reproductive success of elk in the upper Eagle River Valley, Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. Quimby, D.C., and I.E. Gaab. 1957, Mandibular dentition as an age indicator in Rocky Mountain elk. Journal of Wildlife Management 21: 134-153. Roath, R.;;'L_Carpenter.B. ~epsame, and D. Swift. 1999. Gunnison Basin habitat assessment project'..,:FiP:alReport Match r"999. Colorado State University, Department of Range Science, Fort Collins, .....'. 'Colorado USA. Samuel, M.D., E.O. Garton, M.W: Schlegel, and R G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. Journal of Wildlife Management 51: 622-630. SAS. 1988. SAS/STAT user's guide, release 6.03. SAS Institute, Inc. Cary, North Carolina USA. Snedecor, G.W., and W.G. Cochran. 1967. Statistical methods; sixth edition. Iowa State University Press, Ames, Iowa, USA. Singer, F.J., A. Harting, KK Symonds, and M.B. Coughenour. 1997. Density dependence, compensation; and environmental effects on elk calf mortality in Yellowstone National Park. Journal of Wildlife Management 61:12-25. Unsworth, J.W., L. Kuck, and E.O. Garton. 1990. Elk sightability model validation at the National Bison Range, Montana. Wildlife Society Bulletin 18:113-115. Unsworth, J.W., D.F. Pac, G'C. White, and R.M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Wade, D.A., and J.B. Browns. 1982. Procedures for evaluating predation on livestock and wildlife. Texas Agricultural Experiment Station Publication B-1429. White, G.c. 1992. DEAMAN database manager and population modeling procedures; Colorado Division of Wildlife User's manual and reference. Colorado State University, Fort Collins, Colorado USA. White, G.c. and R.A. Garrott. 1990. Analysisof wildlife radio-tracking data. Academic Press, Inc., San Diego, California USA. White, G.c., D.R Anderson, KP. Burnham, and D.L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory LA-8787-NERP, Los Alamos, New Mexico, USA. White G.c., RA. Garrott, RM. Bartmann, LH. Carpenter, and A.W. Alldrege. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Management 51: 852-859. Zar, I.H. 1984. Biostatistical analysis, second edition. Prentice-Hall, Englewood Cliffs, New Jersey, USA. New November 2000 Final _. �235 APPENDIX I SPECIFICATIONS FOR RADIO-COLLARS Manufacturer: Lotek, Inc. Pulse Rate Normal: 60-65 ppm Pulse Rate Mortality: 120-130 ppm Motion Sensor Delay: 4-6 hrs Batteries: 4+ year life, 1 lithium D-cell calf collars Antenna: External whip, pvc coated Collar Material: 7.6 em (3") wide white colored smooth surfaced conveyor belting, 2 layers sewn together, 0.64 ern (114") total thickness Additional Material: Bright yellow with black core Ritchie All-Flex plastic material for identification symbol/number placed as a sleeve over top portion of collar (Ritchey Manufacturing, Inc., Brighton, CO). Collar Size: 61-81 em (24-32") adult females, individually fitted; 56-69 ern (22-27") expandable for female calves; 57-89 em (22.5-35") expandable for male calves. Collar Weight: 820 gm female calves; 840 gm male calves; 1.1 kg adult females .. November 2000 Final �236 APPENDIX II VISUAL IDENTIFICATION SYSTEM FOR RADIO-COLLARS Numbers, symbols, and letters will be used in ordered combinations to quickly allow identification of individual elk primarily during aerial surveys. No more than 2 characters will be used to identify an individual. Characters will be ordered and read from left to right on the collar from the perspective of looking down on the elk from the rear of the animal when approached by an observer in a helicopter. Numbers to be Used (8): 0, 1,2, 3, 4, 5, 6, and 7 Symbols to be Used (5): solid circle., solid square _, solid triangle A, solid hourglass sign +, (solid diamond potentially. ) Letters to be Used (9): A, C, F, H, J, K, N, P, X (T, V, Y potentially) X, plus Identification Combinations: Number combinations represent 56 individuals 10,20,30,40,50,60,70 11,21,31,41,51,61,71 12,22,32,42,52,62,72 13,23,33,43,53,63,73 14,24,34,44,54,64,74 15,25,35,45,55,65,75 16,26,36,46,56,66,76 17,27,37,47,57,67,77 Each Symbol paired with each Number represents 16 identification codes when ordered symbol-number and then number-symbol. Five symbols paired with 8 numbers represents 80 individuals. Examples: 7.and .7. Each Letter paired with each Number represents 16 identification codes when ordered letter-number and then number-letter. Nine letters paired with 8 numbers represents 144 individuals. Examples: A 7 and 7A. Each Letter paired with each Symbol represents 10 identification codes when ordered letter-symbol and then symbol-letter. Nine letters paired with 5 symbols represents 90 individuals. Examples: A. and .A. Therefore, a minimum of 370 different animals can be individually marked using this system. November 2000 Final �237 APPENDIX III HELICOPTER NET-GUNNING CAPTURE PROTOCOL FOR ELK Background: Helicopter net-gunning has been successfully and safely used to capture and radio-collar elk in Colorado during both winter and summer. This success has been in part due to following accepted protocols for handling elk (Colorado Division of Wildlife Animal Care and Use Committee Reviews and Approvals). Helicopter capture of elk on the Grand Mesa, Colorado during December 1993-1996, resulted in no acute or post-capture related deaths in 46 adult females and 1 acute death (broken neck, 0.4%) and 2 post-capture myopathy deaths (0.7%) in 258 calves captured and handled (Freddy 1996, 1997). During early December 1994-96 near Vail, Colorado, 2.2% of 185 adult females died from effects of helicopter capture (Phillips 1998). In the White River, Colorado, <1 % of 95 adult female elk captured during July and 4% of 32 adult females captured during August near Vail, Colorado died from effects of helicopter capture (Conner 1999, pers. comm. M. Conner, 1999, Phillips 1998). Captul'e Protocol: Capture of elk will follow procedures successfully used on the Grand Mesa (Freddy 1995). David J. Freddy is the principal investigator and will coordinate capture of elk. All persons involved in the capture operation, including the helicopter net-gunning crew, will be instructed on proper care and handling of elk to reduce stress and injury to elk. Capture Timing and Conditions: Elk are scheduled to be captured during mid-December in the Gunnsion Basin but there remains the possibility that capture could occur in early January depending on availability of contract helicopter services. During either month, cool ambient temperatures and moderate snow depths «60cm) contribute to successfully capturing elk by reducing threats of hyperthermia potentially induced by capture chases. We anticipate capturing elk when ambient temperatures are -18 - 3°C. Temperatures < -18°C (0° F) may restrict human efficiencies while temperatures >3°C (38° F) may induce hyperthermia in elk. No-fly Zones: Pursuit and capture of elk will not occur within 1,000m (0.5 miles) of human residences or other cultural developments such as well traveled roads, reservoirs, etc .. Notification of Affected Parties: Local residents and federal, state, and local agencies will be notified of the time and general area of capture activities. Notification will be via newspaper articles, public meetings, and other informal verbal communications. Emergency Services: Capture personnel will be instructed that the nearest medical and emergency services are located at the Gunnison Valley Hospital in Gunnison. Capture crews will have communications radio contact to CDOW service centers and emergency Colorado State Patrol. Radio Collars/Ear Tags: Expandable collars will be placed on male and female calves to accommodate neck growth as animals become adults (Appendix I). Collar design was previously used on 285 elk calves on the Grand Mesa with no known cases of expandable collars inducing trauma for up to 4 years of age on males and 7 years of age on females (Freddy 1999). Collars of fixed size will be placed on each adult female and individually fitted usually to 69-74 ern (27-29 in). Fixed collar design was previously used on 82 adult females with no known cases of trauma (Freddy 1999). No ear-tags will be used. Command Post: The principal investigator and handling crew will establish mobile command /handling sites that will be near actual locations of capture. The handling crew will be ferried by the capture helicopter as needed. At these command posts, elk calves will be weighed, measured, collared and released while adult female elk will be captured and released at the point of capture. This will facilitate efforts of the principal investigator to remain in contact with the helicopter net -gunning crew and make all decisions regarding care and welfare of captured elk. Chase Time: The helicopter crew will locate groups of elk and determine if calves and adult females are present. If the group is >20 animals, the helicopter will splinter the group into smaller groups within 1-2 minutes of detecting the initial group. The helicopter will then spend <5 minutes maneuvering a smaller group to a suitable capture site. Once a target animal is selected it will be actively pursued for::::l minute or until active panting is observed at which time the pursuit is terminated. Total time spent disturbing the initial group and target animal should be <10 minutes. No more than 2-3 animals will be taken from an November 2000 Final �238 initial group to avoid unnecessary chase time of non-target animals. Care will be taken by the helicopter crew to avoid chasing animals into fences, roads, rivers, or unfavorable terrain. Animal Care and Handlin~: Elk calves will be hobbled and blindfolded at the point of capture and then slung under the helicopter, one calf per ferry, to a nearby commandlhandling site where they will be measured, weighed, collared, and released at that site. Capture locales will be within 1-2 minutes of flying time or <3,000m (2 miles) of commandlhandling sites. Adult females will be blindfolded, hobbled, collared, aged, and then released at the point of capture by the net-gunning crew. Adult females will be assigned to an age class based on relative wear and height of incisors: yearling, 2-4 years, 5-9 years, and >9 years (Quimby and Gaab 1957). At the handling site, 3-4 persons will handle and release calves. Calves will be gently lowered to the ground by the helicopter near the handlers at which time handlers will check calf for injuries, remove netting, and check blindfold and hobbles for proper function. Rectal temperature will then be measured using a digital thermometer eF) while measurements of total body length (em), hind foot length (em) are being obtained. If rectal temperature is 2:41.9°C (107.4 OF)and heavy panting evident, the calf will be only collared and released and not weighed to reduce handling time. Previous experience on the Grand Mesa indicated calves survive when rectal temperatures briefly approach 42.2°C (108°F) (Freddy, unpubl. data). The 2 cases of capture myopathy on the Grand Mesa were males with rectal temperatures of 42.2 and 41.5°C (100th and 90th quantiles, respectively), ambient air temperatures -2.2 and 3.9°C «50th and 90th quantiles, respectively), and below average body weights <108kg. Assuming acceptable body temperature, the calf will be weighed (kg) by gently sliding the calf into a weigh-bag which will support the entire weight of the calf while the calf is hoisted by a pulley and suspended from a scale affixed to a portable steel quad-pod. Care will be taken to always support the spine and neck of the calf during the weighing process. Once weighed, calves will be lowered to the ground, slid out of the bag, radio-collared, hobbles removed, blindfold removed, and released towards the direction from which they were ferried by the helicopter. Previous experience on the Grand Mesa indicated calves readily find and join elk groups after being released. Total time to process and release calves should be.::::8minutes. If ambient air temperature exceeds 3.3°C (38 OF), capture activities will likely be halted, especially if snow is not present to help cool captured elk. Injured Animals: We expect <3% serious injury/mortality rate. Capture techniques will be constantly monitored and changed if necessary to insure that minor injuries to animals do not chronically occur. However, any debilitating injury or mortality of a captured elk will cause at least temporary suspension of capture activities to assess the cause of injury and if further injuries can be prevented. Animals having a broken leg, neck, pelvis, or other debilitating wound will be euthanized with a gunshot to the head (0.357 or larger caliber pistol) following euthanasia protocols of the Colorado Division of Wildlife Animal Care and Use Committee. The principal investigator will make decisions regarding euthanasia but all persons involved in capture will be trained to properly euthanize appropriate animals. The helicopter net-gunning crew and the handling crew will both have ready access to pistols needed for euthanasia. Euthanized animals will be processed for human consumption a"nddonated to social service agencies. Release of Animals: While still blindfolded, hobbled, and prior to release, elk will again be examined for injuries. Superficial injuries such as abrasions and small cuts will be treated with antibiotic ointment. The release sequence will be to place elk in sternal recumbency with head pointed towards direction of capture, remove hobbles, remove blindfold, physically hold elk until elk regains eyesight and orientation, at which time handlers release elk and help elk maintain its balance and upright position. Elk will then be observed for any signs of injury while moving away from handlers. Care will be taken to avoid releasing elk towards fences or unfavorable terrain. Post-Capture Monitorin~: All radioed elk will be monitored for their life/death status 2:2 times within 10 days of capture. If a mortality occurs, the carcass will be located, necropsy performed, and cause of death estimated if possible. If available, muscle tissue samples will be collected and sent to Colorado State University Veterinary Diagnostic Laboratory to detect evidence of capture myopathy. November 2000 Final �239 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 PROGRESS REPORT Stmeof, C~ol~o~ra~d~o~ _ Division of Wildlife - Mammals Research Work Package No. ---=3::..._::0'-"'0=3 _ Predatory Mammals Conservation Task No. ----'3"-- Peiod Covered: January 1,2001- _ Pilot Study - Evaluation ofGPS Technology in Measuring Chronic Wasting Disease Prevalence Among Deer Preyed upon by Puma December 31,2001 Author: C. E. Krumm, T.D.I. Beck, M. W. Miller. Personnel: C. E. Krumm, T.D.I. Beck, M. W. Miller Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT A prospectus for a pilot study to ascertain the efficacy and feasibility of using Global Position Systems (GPS) technology to measure chronic wasting disease prevalence among puma prey, as well as in other studies of puma, was developed. Objectives of the pilot study are to: 1) Evaluate the potential utility of Televilt Positioning GPS collars in studies of selective predation in puma under field conditions; and 2) Develop and assess the adequacy of field sampling techniques for studying selective predation on CWD-infected mule deer. Two adult puma are to be captured and fitted with GPS collars for the pilot study . . ! ��241 PILOT STUDY Evaluation of new GPS technology in measuring chronic wasting disease prevalence preyed upon by mountain lions among deer C. E. Krumm, T. D. I. Beck, and M. W. Miller Background As a pilot study to test a new technology in Global Positioning Systems (GPS) and its application to studies of predator-prey relationships, we plan to capture and collar two free-ranging puma (Puma concolor) in the foothills west of Ft. Collins in early April of 200 1. Our pilot study will evaluate new GPS technology, as well as the potential utility of data collected with this system in testing hypotheses about selective predation; specifically, we will evaluate the ability to compare chronic wasting disease prevalence among puma-killed deer to prevalence among harvested deer. Chronic wasting disease (CWD) is a naturally occurring spongiform encephalopathy of captive and freeranging deer and elk. CWD has become a concern in managing deer herds in northeastern Colorado. Studies conducted the past several years have provided important data on prevalence of CWD (Miller et al. 2000) and the potential effects of selective population control on affected populations (Gross and Miller 2001). It follows that processes fostering selective removal of affected individuals, like test-andslaughter or predation, should be closely evaluated in the context of disease management. New technology in GPS tracking of animals by Televilt Positioning (Lindesberg, Sweden) allows location data to be downloaded remotely without retrieval of collars. Testing the effectiveness and accuracy of these collars will benefit a suite of studies that are being planned across Colorado to examine the selectivity of puma for prey animals (specifically mule deer) of varying condition. These studies will help to answer a fundamental ecological question: Do puma selectively prey on debilitated or compromised animals rather than healthy ones? Objectives Our specific objectives are to: 1. evaluate the potential utility of Televilt Positioning GPS collars in studies of selective predation in puma under field conditions; and 2. develop and assess the adequacy of field sampling techniques for studying selective predation on CWD-infected mule deer. Study Design Because this is a pilot study, we will capture and collar only two adult puma to evaluate equipment and sampling techniques. We regard two individuals as the fewest needed to adequately assess all aspects of equipment use and performance, sampling techniques, and other logistical facets of larger prospective studies. Capture Methods and Handling We plan to capture adult puma for this study using methods described in Shaw (1979). Briefly, a tracker with experience in tracking and handling mountain lions will be hired to facilitate capture and will use trained dogs to track and tree or bay each mountain lion. Field anesthesia will be supervised by an attending veterinarian. Anesthetic drugs will be administered intramuscularly via projectile syringe using a gas-powered projector. For capture, puma will be anesthetized with ketamine (1O-11mg/kg) and xylazine HCI (1.8-2mg/kg) or ketamine (2 mg/kg) and medetomidine (0.075 mg/kg) (Shaw 1979, Kreeger 1996). We will observe darted puma for signs of sedation (salivation, unsteadiness of head and body, and a wide-eyed expression). If the puma is treed, then people and dogs will be removed from the immediate area to give the animal a chance to descend before becoming completely anesthetized. If the puma remains in the tree until almost completely anesthetized, then someone wearing climbing gear will climb to the puma and attach either a chest harness (preferred) or hind leg noose and quickly lower the animal �242 before it falls; others will hold a taut net below to break the puma's fall should it slip before a harness or rope can be secured. If signs of anesthesia are inapparent after 15 minutes, then a second full injection will be given. Upon first approach of an apparently anesthetized puma, a 4-5 foot stick will be used to gently prod the paws and muzzle of the animal; if there is no response (i.e. snarling or biting), then we will assume anesthesia is sufficient for handling. Once anesthetized, we will apply eye ointment and a blindfold to reduce visual stimuli, place gauze pads in the puma's ears to reduce auditory stimuli, and restrain its legs with nylon belts or hobbles. A GPS-Simplex collar (Televilt Positioning; maximum weight 600 g) will be fastened around the puma's neck. The leg restraints will be quickly removed, and the puma will be allowed to recover from the sedation either naturally or with the aid of an antagonist; when prescribed, yohimbine HCI (0.125 mg/kg IV) will be used to antagonize xylazine sedation and atipamezole (0.3 mglkg) will be used to antagonize medetomidine sedation. Postcapture Monitoring According to the manufacturer, the locations of collared animals can be retrieved and plotted several times a day without removing the collars. Up to 2000 satellite positions can be stored in the memory, allowing us to closely monitor the puma's movement on a daily basis. If a puma remains in one location for several hours, we will assume that it has made a kill. Based on data from studies elsewhere (e.g., Hornocker 1970, C. Anderson, personal communication), we anticipate that each collared animal will make an ungulate kill every 7 to 11 days on average. We will locate the prospective kill site using the GPS-Simplex system. We will evaluate whether using this system allows us to locate kill sites quickly enough to retrieve a suitable tissue sample to test for CWD. If the animal killed is a deer, the presence of suitable diagnostic samples (brain stem and tonsil tissues) and overall carcass condition will be noted, and tissues will be taken to test for CWD when available. To evaluate the effect of carcass sampling activities on puma behavior, we will alternate taking the entire head of the kill with sampling only the necessary tissues in the field to compare the effect on the puma's return to the kill. The animals will be monitored closely after the kill has been sampled to ensure our handling does not interfere with their return to the kill site. Generally, researchers' presence at and inspection of a kill site does not dissuade a puma from returning to that site (T. Beck, unpublished data). However, if it becomes apparent that one technique is more disruptive than the other, then we will adopt the least disruptive sampling technique for the remainder of the study. Both puma will remain collared for a period of no less than one month unless the collars appear to be adversely affecting them. We will monitor each animal for changes in behavior like decreased kill rates or mobility that may be attributed to the collars. If the collars seem to have no adverse effects on the puma, then they will remain in place until the batteries must be replaced (about 3-4 mo, depending on . final programming configuration). If the collars need to be removed for any reason, the same capture and handling methods as described above will be used for recapture. Data from this pilot study will be used in designing more comprehensive studies of puma-deer relationships in Colorado, and may be of use in other studies of predator-prey ecology. Literature Cited Gross, J. E., and M. W. Miller. 2001. Chronic wasting disease in mule deer: A model of disease dynamics, control options, and population consequences. J. Wildl. Manage. In press. Hornocker, M. G. 1970. An analysis of mountain lion predation upon mule deer and elk in the Idaho Primative Area. Wildlife Monographs 21. Kreeger, T. 1. 1996. Handbook of wildlife chemical immobilization. International Wildlife Veterinary Sciences, Inc. Laramie, Wyoming, USA. Miller, M. W., E. S. Williams, C. W. McCarty, T. R. Spraker, T. J. Kreeger, C. T. Larsen, and E. T. Thorne. 2000. Epizootiology of chronic wasting disease in free-ranging cervids in Colorado and Wyoming. Journal of Wildlife Diseases 38:676-690. Shaw, H.G. 1979. Mountain lion field guide. Fourth edition. Arizona Game and Fish, Phoenix, Arizona, USA. �243 Colorado Division of Wildlife Wildlife Research Report July 2001 and July 2002 PROGRESS REPORT State of -=C""o.o..:lo,:_:r.",a:>:_do"'-_ Work Package No. __ ----=<.3"'-'00,,_4,___ Task No. Personnel: Other Ungulate Conservation _ Period Covered: Authors: _ July 1,2000 Division of Wildlife - Mammals Research Annual Winter Count of Middle Park Pronghorn - June 30,2001 Thomas M. Pojar CDOW - T.M. Pojar, R. Firth, J.Claassen, M. Crosby, K. Holinka, T. Kroening, R. Thompson, C. Wagner. Others - C. Cesar (BLM). Volunteers - B. Kraft:, R. Nutter, D. O'Sullivan, M. Palowoda. MIDDLE PARK PRONGHORN WINTER 2000-01 COUNT Tom Pojar, February 13,2001 The annual winter count of the Middle Park pronghorn herd was conducted during February 9 through February 12,2001. The major effort was done on February 9th when several observation crews from Area 9 assisted and the largest pronghorn groups were counted. The smaller, more isolated groups were counted during subsequent days. Division of Wildlife personnel from Area 9 that participated in the count were: Jerry Claassen, Mike Crosby, Kris Holinka, Tom Kroening, Jim Liewer, Bob Thompson, and Chuck Wagner. Chuck Cesar of BLM assisted as well as the following volunteers: Ben Kraft, Ron Nutter, Dan O'Sullivan, and Marie Palowoda. This year's count was made more interesting with the infusion of animals into the population from the Blue Valley Ranch transplant. The purpose of this transplant was to expand the. range of the Middle Park population to wintering areas south of the Colorado River. Throughout the years of habitation, the pronghorn have only wintered north of the Colorado River. BVR pronghorn were released from enclosures they were held in during winter 1999-00 around June 1,2000. At this point they were free to select the summer, and subsequently, the winter range they found desirable. Of 50 BVR pronghorn radioed, 39 survived to the winter of 2000-01. Twenty-six of these are wintering south of the Colorado River; 15 west ofBVR headquarters west of the Blue River, 2 west ofJim Yust's (west of the Blue River), and 9 east of Junction Butte, which is east of the Blue River. Thirteen of the BVR radioed animals are wintering north of the Colorado River with groups of the "native" pronghorn. �244 Count North of the Colorado River AREA COUNT Back Troublesome 176 Starr Gulch 221 NE Red Mt. 138 Pinto Ranch 4 TOTAL 539 AREA COUNT Junction Butte - east 13 Blue Valley Ranch - west 28 Jim Yust's ranch - west 2 TOTAL 43 Count south of the Colorado River GRAND TOTAL = 582 The conclusion from this count is that there are at least 582 pronghorn wintering in Middle Park during winter 2000-01. A spreadsheet population model has been maintained for this herd since it was first being tracked in 1986. The projected winter population has corresponded with the actual count quite closely through the years with a mean deviate count of 17. This year, the model projects a population of 675 for the largest discrepancy ever encountered - 93 animals. The model was adjusted for the infusion of BVR animals with the fawn to doe ratio applied to all mature females in the entire Middle Park population. There are several possible scenarios to explain the apparent undercount for this year. No new radios have been deployed on the population north of the Colorado River since 1998. Population growth, radio failure, and harvested radioed animals have contributed to dilution of the proportion of radioed animals. This year about 5% of the population north of the river are carrying working radios. As this percentage decreases the probability of having a group of animals without at least one radio in it to allow detection increases. Finding pronghorn groups with winter conditions featuring a mottled background of snow and sagebrush can be very difficult. Radios are crucial to locating pronghorn groups during winter. All of the radios that were presumed to be working were located except 3. Although these radios were located earlier in the fall during the herd structure survey they may have failed since then or it is possible we missed detecting them during the winter count. The Antelope Creek, Antelope Pass, Cow Gulch, Wolford Mountain, Sulphur Gulch, and Corral Creek areas were searched and radio scanned for these 3 radios. The fact that these radios were not found does not eliminate the possibility that a group (or groups) of pronghorn were missed. Winter conditions are mild thus far this year. The winter began with a much colder than normal November and some snow. However, milder conditions prevailed during December, January, and so far in February. Snow depth where the pronghorn are wintering ranges from 4-10 inches with clear south facing slopes and adequate wind-blown ridges. In brief, the pronghorn should come through this winter in very good condition barring any severe late winter weather. �245 Colorado Division of Wildlife Wildlife Research Report July 200 I and July 2002 JOB PROGRESS REPORT State of C=o=l=o=ra=d=o'--- _ Work Package No. ~1""-A_"__ Task No. -=5'--- Mammals Research _ Multispecies Investigations _ Consulting Services for Mark-Recapture Analysis Federal Aid Project No. _-'W'-'--'-1=5..=.3-=-R=-..=2;_ _ Research and Development 1 Period Covered: July 1,2000 - June 30, 2001 Author: G C. White, Ph.D. Personnel: C. Bishop, R. B. Gill, D. C. Bowden, R. M. Bartmann, D. 1. Freddy, T. M. Shenk, M. M. Conner, M. Post Vieira, A. Dharman, B. Lubow ABSTRACT Progress towards the objectives of this job include: Consulting assistance to CDOW on harvest surveys, terrestrial inventory systems, and population modeling procedures was provided. Estimates of spring and fall turkey, spring snow goose, sharp-tailed and sage grouse, chukars, ptarmigan, Abert's squirrels, and general small game harvest were computed from survey data, and programs and harvest estimates provided to CDOW via email and CD ROM. Input on the design and analysis of the Harvest Information Program was provided on several occasions. The DEAMAN software package for the storage, summary, and analysis of big game population and harvest data was revised further as a Windows 95/98INT/2000IME program. The capability to incorporate data on radio-collared animals to estimate survival with the Kaplan-Meier estimator and display movement data was added, and distributed to terrestrial biologist via the WWW at http://www.cnr.colostate.edul~g\vhite/deal11an. A I-day workshop was conducted with NE region personnel in the use ofDEAMAN and population modeling procedures, mainly to instruct region personnel on the use of spreadsheet models for ungulate population dynamics. In addition, numerous questions were answered via meetings with biologists, and via email. A preliminary analysis of the survival rates from the mule deer monitoring data was completed. However, I have not received final data from some of the biologists, so have not been able to complete this analysis. A paper, coauthored with Bruce Lubow, was submitted for publication to the Journal of Wildlife Management on past efforts to develop a realistic mule deer population model based on data collected with current CDOW procedures. Data from the Piceance Basin were used to illustrate the modeling �246 technique. In addition, a book chapter on modeling big game populations appeared in print: White, G. C. 2000. Modeling Population Dynamics. Pages 84-107 in S. Demarais and P. R. Krausman, eds. Ecology and Management of Large Mammals in North America. Prentice-Hall, Upper Saddle River, New Jersey, USA. A paper on optimal allocation of resources to sample Colorado mule deer populations was published in the Journal of Wildlife Management: Bowden, D. c., G. C. White, and R. M. Bartmann. 2000. Optimal allocation of sampling effort for monitoring a harvested mule deer population. Journal of Wildlife Management 64: 1013-1024. A paper on trends in Colorado mule deer age and sex ratios was published in the Journal of Wildlife Management: White, G. C., D. J. Freddy, R. B. Gill, and J. H. Ellenberger. 200 l. Effect of adult sex ratio on mule deer and elk productivity in Colorado. Journal of Wildlife Management 65:436-444. Assistance in the design and analysis of candidate systems to estimate deer abundance in GMU 10 was provided. A research study to examine the impact of nutrition on the decline of mule deer fecundity during the last 20 years was initiated. I have provided input on estimation of the number of deer on the feed sites, and developed an estimator of fawn survival rates based on radio-collared does and fall and spring fawn:doe ratios. Data were collected and analyzed on spatial distribution, movement of radio-collared animals, and population sizes related to estimating the spread and impacts of chronic wasting disease in deer populations. A report summarizing these findings was provided to CDOW personnel involved with the study. A [mal report on the response of elk to lower numbers of archery licenses in the White River Data Analysis Unit was prepared and submitted to CDOW personnel involved with the project. A paper reporting results of the earlier experiment to detect elk response to the opening of archery season has been accepted for publication in the Journal of Wildlife Management: Conner, M. M., G. C. White, and D. J. Freddy. 200l. Elk movement in response to early-season hunting in Colorado. Journal of Wildlife Management 65. In Press. A graduate research project to evaluate the movements of Preble's meadow jumping mouse populations away from riparian areas was completed. A final report of this project was submitted to CDOW personnel involved with the project. . . In cooperation with CDOW personnel, I developed an analysis of survival of lynx released as part of the reintroduction program. An analysis to estimate the effort required to estimate the percent of eastern Colorado inhabited by blacktailed prairie dogs was completed and results provided to CDOW personnel involved with the effort. �247 CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSES G. C. White p, N. OBJECTIVES Design a sampling scheme to estimate the area of black-tailed prairie dog colonies in eastern Colorado. SEGMENT OBJECTIVES 1. Develop a sampling scheme to estimate the area of black-tailed prairie dog colonies in eastern Colorado. 2. Develop estimates of the cost of this sampling scheme as a function of the expected precision. RESULTS AND DISCUSSION Area of black-tailed prairie dog colonies in Wyoming, North and South Dakota, and Nebraska have been sampled successfully with aerial line intercept sampling techniques (Sidle et al. In Press). CDOW is interested in applying this technique to eastern Colorado, and obtaining estimates of the areas occupied by prairie dogs by county. However, there are concerns regarding the cost of the survey and expected precision. In the following, I present an analysis of the expected cost as a function of the precision of the estimates of area of black-tailed prairie dog colonies. To compute the expected precision as a function of the cost of the aerial survey for black-tailed prairie dogs, I went through the following steps. I assumed that the lines to be flown would be stratified by county. Because an infinite number of lines can be flown for each county, the sampling scheme can be viewed as sampling with replacement, and hence, no fmite population correction is allowed. Further, I treated each line as providing an estimate of the proportion of the county area in active prairie dog towns, and not as a ratio estimator. Sidle et al. (In Press) compared both types of estimators, and developed a composite of the 2. However, design of a new survey seemed easier to conceptualize with the approach taken. This approach allowed the use of the formulas on pages 341-342 of Thompson et al. (1998), ignoring the finite population correction. Other pertinent references are Thompson (1992) and Cochran (1997). From the area of each county and the estimated area of prairie dog towns within the county provided by the EDAW survey, I predicted the proportion of the line in each county that would intersect dog towns (r) as: r= Active Towns Area County Area -- C A From Table 1 of Sidle et al. (In Press) I computed the relationship between the standard deviation of r [SD(r)] and the value of r. To compute SD(r) from Table 1 of Sidle et al., I got the number of lines flown for each of the 8 surveys from Douglas Johnson, Northern Prairie Wildlife Research Center, USGS. A linear relationship of SDt ) = 0.0087 + 1.0804r was found to provide a decent fit to the data (Figure 1). �248 0.25 -.----,------,--------,-------,.-----, 0.2 -I---~--------~--------~--------~~-I s 0.15 Q I (/) 0.1 ..•.. __ ••_.H· , : ~ ~ -----t------------~- ····_·I 0.05 o o 0.05 0.1 r 0.15 0.2 I assumed that each county was to be estimated with some relative precision (e) such that the 95% confidence interval for each county would be ± eC, where C is the estimated acres of active towns. This approach is not the optimal for the estimate of the total active town area in the state, but would provide good estimates (i.e., estimates of quality e) for each county. For each county, the standard error of the estimate of the active prairie dog town area [SE(C)] was computed based on the SD(r) and the estimated number of lines (n) to be flown, where SEer) = SD(r)/.j;; , and SEC C) 2 = A SE(r). Given the desired level of precision, I computed the number oflines to fly in a county as: Because some counties had values of C = 0 (and hence the above equation s undefined), and others have very small values, I assumed that all counties had at least 0.5% area in active towns to compute these samples sizes, although the actual value of r was used to compute the standard deviation. The total length of the lines to be flown in the county is the square root of the county area multiplied by the number of lines to be flown. Cost of the survey for a county was figured as the length of line to be flown plus 2 times the square root of county area in miles (to account for ferry time), all divided by a flight speed of 90 mph, times $180 per hour of flight time. The total acreage of prairie dog towns (CT) is the sum of the county estimates, with the variance computed as the sum of the variances across the counties. � https://cpw.cvlcollections.org/files/original/fd347cae4851648bafc251d872eae8e5.pdf 79086bce223a1046168c8c2f08055243 PDF Text Text �����1 JOB PROGRESS REPORT Smreof ~~C~o~l~or~a~d~o _ Division of Wildlife - Mammals Research Work Package No. --"0'-"'6~62"'____· _ Preble's Meadow Jumping Mouse Conservation Task No. --'2"'-- Period Covered: Author: Personnel: _ Effects of Resource Addition on Preble's Meadow Jumping Mouse (Zapus hudsonius preblei) Movement Patterns July 1, 2002 - June 30, 2003 Anne M. Trainor. T. M. Shenk, K. Wilson, G. C. White Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT The Preble's meadow jumping mouse (Zapus hudsonius preblei; PMJM) is a federally threatened species. Improving our understanding of PMJM habitat is essential for the development of effective management strategies for conservation of the species. Thus, the objectives of our research were to compare microhabitat characteristics among low and high use areas within PMJM habitat and to determine how the addition of artificial resources influence the movement patterns of PMJM. A comparison of microhabitat characteristics from a random sample of "high-use" and "no-use" areas indicated a greater (P < 0.0001) shrub canopy cover in "high-use" areas verses "no-use" areas (47.7% ± 29.8%, 12.6% ± 14.11 %, respectively). Further, "high-use" areas had greater basal cover (P = 0.013) and bare ground (P = 0.0459) and "no-use" areas contained a greater (P = 0.0331) abundance of forb canopy cover. We conducted a manipulation experiment where we constructed patches of artificial resources (food and cover) in areas without previous PMJM activity. PMJM were radio collared and located hourly before and after the addition of food and cover. The majority of PMJM movements were not influenced by the addition of resources in 2002. These results may be due to site fidelity or lack of exploratory movement to locate the additional resources �2 Effects of Resource Addition on Preble's Meadow Jumping Mouse (Zapus hudson ius preble/) Movement Patterns Anne M. Trainor Colorado State University INTRODUCTION The U.S. Fish and Wildlife Service (USFWS) listed the Preble's meadow jumping mouse (Zapus hudson ius preblei; PMJM) as a threatened species in 1998 under the Endangered Species Act (USFWS 1999). Upon listing, little was known about the biology and habitat requirements of this subspecies within its range along the Front Range of Colorado and southeastern Wyoming. Since listing, a number of projects (e.g., long-term monitoring, surveying, and movement studies) have collected valuable information throughout Colorado (Schorr 2001, Meaney 2000, Shenk and Sivert 1999). However, information on specific habitat requirements and their relationship to the distribution, density, survival and reproduction of PMJM is still lacking. The threatened status of PMJM requires management decisions be made despite our limited knowledge. In particular, the species and its habitat are subject to habitat conservation plans (HCPs). HCPs are written for endangered and threatened species to compensate for authorized "take" through mitigation practices (Bingham and Noon 1998). HCPs require the use of the "best available" science to determine the biological needs of target species (Harding et al. 2001). Collection of reliable information for the species will improve the mitigation practices developed for HCPs. Well-designed habitat manipulation experiments provide the strongest inference to determine cause and effect relationships. Understanding of the species habitat requirements will enable the development of effective mitigation strategies. A manipulation experiment was conducted in Douglas County, Colorado (Columbine Open Space) during 2002 and 2003 to advance our understanding ofPMJM habitat requirements. We manipulated sections of the riparian habitat and adjacent grassland within the 100-year flood plain. The site was manipulated by adding patches (3 m x 2.43 m) of artificial resources (food and cover). Time limitations of only a 2-year study were inadequate for vegetation to establish and limited funding (cost of planting and sustaining vegetation) restricted this manipulation experiment to simulating habitat with temporary structures and food supplementation. The treatments were placed in areas of low use based on past monitoring studies conducted by the Colorado Division of Wildlife (CDOW) during 1998-2000. PMJM were radio tracked before and after the manipulation to determine if PMJM movements were altered through the addition of resources. We propose two primary objectives: 1) determine how the presence of resource additions influences the distribution of individual PMJM within a population, and 2) to quantify habitat characteristics of PMJM on a microhabitat scale. We want to examine if the distribution of individual PMJM can be altered in response to the addition of resources (food and cover) and to quantify relevant microhabitat characteristics where PMJM have been detected. �3 STUDY AREA The study was conducted within the riparian habitat within Columbine Open Space, owned by Douglas County Open Space managed by the CDOW and the adjacent grassland. Columbine Open Space was selected because PMJM were monitored for 3 years by the CDOW (1998-2000), providing sitespecific information on PMJM locations before this manipulation experiment.' METHODS PMJM were trapped using non-folding Sherman live traps (7.6 em x 8.9 em x 22.9 em) placed 5m apart along approximately 0.5 km transects adjacent to both sides of East Plum Creek for a minimum of 5 consecutive nights. Trapping procedures were in accordance with the guidelines published by the USFWS (1999). Species other than PMJM were recorded by trap location and immediately released. The following information was recorded for captured PMJM: unique identification, trap location, weight, sex, age, and reproductive condition. PMJM were scanned for a passive integrated transponder (PIT) tag. Newly captured individuals were marked by inserting a unique PIT-tag. Individuals ::::18grams were anesthetized with isoflurane and fitted with a l-g radio transmitter (Holohil Systems Ltd Ontario, Canada). All methods were approved by the Animal Care and Use Committee of Colorado State University (Authorization Number A3572-01). Radio telemetry was used to monitor locations of individuals for a 21-day period, the battery life of the radio transmitters. Observers attempted to stay approximately 3 m from the radio-tagged individual to avoid influencing PMJM movement. Observations taken 3 m or greater from PMJM did not influence movement (T. Shenk, CDOW personal. comm.). The following information was recorded at each relocation: individual identification, time, weather, and surrounding vegetation. All data were combined into a geographical information system (GIS) database using ArcView®3.2 (Environmental Systems Research Institute, Redlands, California, U.S.A.). The manipulation experiment consisted of 5 phases: I) selection of areas of little or no previous use by PMJM based on CDOW location data (1998-2000) collected at Columbine Open Space, 2) recording of pre-treatment location data of radio-tagged individuals for 6 nights, 3) selection of treatment plot location based on pre-treatment and CDOW location data, 4) addition of resources to treatment plots, and 5) recording of post-treatment location of radio-tagged individuals. Two sessions (June and July) of the manipulation experiment were conducted each year. A digital map with a grid cell size of 9 m x 9 m was constructed for the entire study site with ArcView®3.2 (Environmental Systems Research Institute, Redlands, California, U.S.A.) software. CDOW location data was pooled into a single coverage over the grid to establish areas > 1,000 m2 containing only low use cells «2 locations/cell based on CDOW location data) within the 100-year flood plain. Location of treatment plots was selected with a stratified random design from a set of candidate cells meeting criteria developed to describe poor PMJM habitat (sparse vegetation and little food) within 60 m of East Plum Creek, and low historical use. The artificial cover, simulating vertical complexity, was constructed with wheat straw and tree branches distributed in a patch (3 m x 2.43 m). Burlap cloth was suspended 30 em over the tree branches and straw. Food supplements composed of an equal mixture of whole wheat, dehydrated alfalfa pellets and sweet feed were placed on cardboard trays (0.16 m x 0.3 m) within the straw and branches as an attractant and a source of high protein. The dimensions of the treatments were selected to balance the manageability of construction and decrease the chance of inter and intra-species domination within a treatment. Quantification of microhabitat variables in areas of high use were examined by comparing a random sample of cells (9 m x 9 m) containing ~ 99 % of PMJM locations for each session to a random �4 sample of cells where no PMJM locations detected. Two line transects were randomly placed in each selected cell with 6 quadrat frames (50 cm x 20 em) evenly distributed per line transect (Daubenmire 1959). The variables measured in each cell included percent bare ground, shrub, grass, and forb cover and vegetation composition. The location data were analyzed using linear regression. The response variable was the number of locations detected in a cell. A suite of candidate models was developed as predictors of the response variable. Akaike's information criterion (AIC) was applied to select the best "approximating" model (Burnham and Anderson 2002). The independent habitat variables of interest for the models included distance from the center of the cell to the nearest water, area and juxtaposition of nearest shrub, and presence of wetland grasses in the cell. Additional variables -included in the models were period (pre- or post-treatment), sex, session, and year. The microhabitat data collected from the Daubenmire plots were analyzed with Proc GLM (SAS 2002) to test for differences in means among areas of high use and no use by PMJM. PRELIMINARY RESULTS A comparison of microhabitat characteristics from a random sample of "high-use" and "no-use" areas indicated a greater (P < 0.0001) shrub canopy cover in "high-use" areas verses "no-use" areas (47.7% ± 29.8%, 12.6% ± 14.11 %, respectively). Further, "high-use" areas had greater basal cover (P = 0.013) and bare ground (P = 0.0459) and "no-use" areas contained a greater (P = 0.0331) abundance of forb canopy cover. We conducted a manipulation experiment where we constructed patches of artificial resources (food and cover) in areas without previous PMJM activity. PMJM were radio collared and located hourly before and after the addition of food and cover. The majority ofPMJM movements were not influenced by the addition of resources in 2002. These results may be due to site fidelity or lack of exploratory movement to locate the additional resources LITERATURE CITED Bingham, B. B. and B. R. Noon. 1998. The use of core areas in comprehensive mitigation strategies. Conservation Biology 12:241-243. Burnham K. P. and D. R. Anderson. 2002. Model selection and multimodel inference. Second edition. Springer, New York, New York, USA. Daubenmire, R. 1959. A canopy-coverage method of vegetational analysis. Northwest Science 33:4364. Harding, E., E. Crone, B. D. Elderd, J. M. Hoekstra, A. 1. McKerrow, J. D. Perrine, 1. Regetz, L. J. Rissler, A. G. Stanley, E. L. Walters and NCEAS Habitat Conservation Plan Working Group. 2001. The scientific foundations of habitat conservation plans: a quantitative assessment. Conservation Biology 15:488-500. Meaney, C. A. 2000. Monitoring for Preble's meadow jumping mice along South Boulder Creek and Four Ditches. Boulder, Colorado, USA. Report prepared for the Colorado Division of Wildlife. SAS Institute. 2002. SAS Version 8.2. SAS Institute, Cary, North Carolina, USA. Schorr, R. 2001 Meadow jumping mice (Zapus hudsonius preblei) on the U.S. Air Force Academy, El Paso County, Colorado, USA. Shenk, T. M. and M. Sivert. 1999. Movement patterns of Preble's meadow jumping mouse (Zap us hudsonius preblei) as they very across time and space. Annual Report to the Colorado Division of Wildlife. Fort Collins, Colorado, USA. U. S. Fish and Wildlife Service. 1999. Interim Survey Guidelines for Preble's meadow jumping mouse. U.S. Fish and Wildlife Service. Denver, Colorado, USA. �5 JOB PROGRESS REPORT State of Colorado Work Package No. __ ----"-0=67.!...:0"-- Task No. Division of Wildlife - Mammals Research _ Lynx Conservation Ecology of Snowshoe Hares (Lepus 2 american us) in Colorado Period Covered: Author: Personnel: July 1, 2002 - June 30, 2003 Steven W. Buskirk and Jennifer L. Zahratka T. M. Shenk Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT How the densities of woody stems of different sizes, tree dominants, and successional stage affect densities of snowshoe hares is key to effective management of snowshoe hare habitats in the southern Rocky Mountains. Therefore, we investigated two conceptual issues relating to snowshoe hare habitat in late winter. First, how do site conditions produce woody stems of suitable diameters and heights above the snow surface for food and how do site conditions provide suitable protective cover for hares? Second, do snowshoe hares in fact attain their highest densities in these presumptive high-quality habitats? The results in this progress report are preliminary and subject to revision based upon continuing analyses of data. Still, some patterns in the data are apparent. Temperature appeared to have an effect on capture success whereas moon phase, although it has been reported to have an effect, did not. Our preliminary analysis of vegetation data suggests that canopy cover and distance to the nearest 1-7 em stem also affect capture success. A resource selection model will be generated in the next phase to determine habitat predictors of capture success. Our comparison of diameters of fecal pellets of snowshoe hares and mountain cottontails suggests a difference in size of pellets between the two sympatric lagomorphs that should be useful for identification of pellets to species in the field. �6 Ecology of Snowshoe Hares (Lepus americanus) in Colorado Steven W. Buskirk and Jennifer L. Zahratka Department of Zoology and Physiology University of Wyoming INTRODUCTION The snowshoe hare (Lepus americanus) is a widely distributed and well-studied leporid of North American boreal forests. Scientists have long been interested in the snowshoe hare, its cyclic population fluctuations at high latitudes, and its ecological relationship with the Canada lynx (Lynx canadensis). The snowshoe hare is the obligate primary prey item of the lynx, which was listed as threatened under the Endangered Species Act in 2000 (U.S Fish and Wildlife Service 2000). Data dealing with the ecology, particularly the habitat ecology, of southern snowshoe hare populations are lacking, especially in the southern Rocky Mountains. Indeed, only a single study (Dolbeer and Clark 1975) described the habitat associations of hares in the southern Rocky Mountains, but only in the most cursory fashion. The reintroduction of Canada lynx to the southern Rocky Mountains in 1999-2003 has stimulated the need for understanding the habitat requirements of snowshoe hare populations. Data from the southern Rocky Mountains are critical for managing habitats to conserve lynx and other boreal forest predators at their southernmost limits in the southern Rocky Mountains. The abundance and fitness of snowshoe hares depend on the protection afforded by plants as well as their suitability as food for hares. Although food is an obvious requirement for snowshoe hare survival, snowshoe hares rarely starve to death. Instead, predation is the overwhelming proximate cause of death for snowshoe hares (Hodges 2000a) and food shortage only predisposes them to predation. Largediameter woody structure provides horizontal and vertical protection from predators (Wolff 1980). Also, small-diameter « 5-mm) (Grigal and Moody 1980) woody stems < 45 cm from the snow surface (Bider 1961) are an important food source (Hodges 2000b). Whereas large-diameter woody stems presumably provide protection from predation, small-diameter woody stems are believed to provide nutrition, particularly in winter. Therefore, we assume that woody structure in two different size classes meets two distinct habitat needs of snowshoe hares. Winter is a critical time of year for snowshoe hare survival because fewer woody stems, large or small, are available than in other seasons, and herbaceous plants are not available. How the densities of woody stems of different sizes, tree dominants, and successional stage affect densities of snowshoe hares is key to effective management of snowshoe hare habitats in the southern Rocky Mountains. Therefore, we investigated two conceptual issues relating to snowshoe hare habitat in late winter. First, how do site conditions produce woody stems of suitable diameters and heights above the snow surface for food and how do site conditions provide suitable protective cover for hares? Second, do snowshoe hares in fact attain their highest densities in these presumptive high-quality habitats? These general questions subsumed more specific ones. 1. In order to understand the links between diet and habitat use in winter, and because diets of snowshoe hares have not been studied in the southern Rocky Mountains, we studied diets of snowshoes hares. 2. Captures of snowshoe hares and non-target leporid species allowed us to collect fecal pellets of known species origin. Because the size of leporid pellets has been used to identify their source to species in the southern Rocky Mountains (Dolbeer and Clark 1975, Bartmann and Byrne 2001) where leporid species are sympatric, we characterized the sizes of fecal pellets of sympatric leporid species, specifically of snowshoe hares and mountain cottontails (Sylvi/agus nuttalliit. 3. Because various abiotic factors (e.g. air temperature, moon phase) have been reported in the literature (Gilbert and Boutin 1991) or anecdotally to affect capture success of snowshoe hares, we �7 tested for these influences in our data, and accounted for them in our analyses of maj or treatment effects (e.g. stand type). STUDY AREA Location The study area was a broad area of southwestern Colorado on the Gunnison and Rio Grande National Forests, which we studied during January - April 2002 and January - March 2003. Within our study area, we established two study sites: one was a 1963-km2 area centered over Taylor Park Reservoir on the Gunnison National Forest (39050' N, 106034' W); the second was the Divide District (4,089 km") of the Rio Grande National Forest (370 40' N, 106040' W) centered directly north of South Fork, Colorado (Figure 1). Spruce-fir is an important habitat for snowshoe hares throughout its temperate range (Hodges 2000a) and it is the most widely distributed stand type in coniferous forests of Colorado. Approximately 48% of the coniferous forests of Colorado are dominated by spruce-fir (Buttery and Gillam 1987). In Colorado, lodgepole pine accounts for 16% of the coniferous forests (Buttery and Gillam 1987); our Gunnison study area represents the southernmost natural extent of this species. Lodgepole pine is an important habitat type for snowshoe hares in other coniferous forests of the Rocky Mountains (Koehler 1990a, b) and reintroduced lynx have been documented in the Gunnison study area. Therefore, lodgepole pine was included in our study. The Rio Grande study area, although lower in elevation, contains ponderosa pine, also widely distributed in Colorado. About 24% of coniferous forests in Colorado are dominated by ponderosa pine (Buttery and Gillam 1987). Bartmann and Byrne (2001) reported some of their highest densities of lagomorph pellets in ponderosa pine stands. Therefore, it was important for our study to examine the suitability of ponderosa pine stands for snowshoe hares. Topography Southwestern Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Elevations of our Gunnison study site ranged from 2850 m to 3480 m. The Rio Grande study site ranged in elevation from 2460 m to 2580 m. Our spruce-fir sites occurred at elevations of 3210 - 3480 m, our lodgepole pine sites occurred at 2850 - 3100 m, and our ponderosa pine sites occurred at 2460 - 2680 m. The overall aspect of each trapping grid varied (Table 1). Climate Southwestern Colorado exhibits an arid and temperate climate; strong local variation reflects elevation and aspect. The mean temperature in Gunnison, Colorado from January - April 2002 was -7°C and in South Fork, Colorado the corresponding mean was ODe. In 2003 the corresponding mean in Gunnison, Colorado was -SoC and in South Fork was -1DC(Weather Channel web site, unpublished data). Unlike northern Colorado, where more precipitation falls as winter snow than as summer rain, the monsoon season in southwestern Colorado brings most yearly precipitation in late summer. The mean monthly precipitation in Gunnison, Colorado for January - April 2002 was 1.6 cm, whereas in the monsoon months of July and August 2002 the mean was 3.8 em. In South Fork, Colorado the corresponding means were 1.5 em and 4.5 cm. �8 METHODS Trapping Grid Selection Our study area comprised the Gunnison and Rio Grande National Forests, within which trapping grids were chosen using a GIS database of national forest lands with Common Vegetation Unit (CVU) coverage using the Integrated Resource Inventory protocol (IRI) made available by each of the forests .. Two sets of criteria, applied sequentially, were used to select the site of the trapping grids. The first set of criteria was based upon the CVU coverages using GIS: 1. Stand types included were Engelmann spruce-subalpine fir, lodgepole pine, ponderosa pine and riparian (Salix spp.). 2. Structural stage was mature with canopy cover 2: 40% (SS 4b, 4c) (Buttery and Gillam 1987). 3. Vegetation polygons were considered if2: 30 m, but:S 1 Ian from a mapped road, i.e. a highway, paved, graded or gravel road, or a 4-wheel drive road. 4. Vegetation polygons were considered if2: 25 ha. 5. Vegetation polygons were considered if shaped so as to admit a 330 m x 550 m (l6.5-ha) trapping grid with a 50-m buffer between the edge of the trapping grid and the nearest edge of the polygon. 6. Fifteen of the candidate polygons were selected randomly. Within each of these random polygons a 330-m x 550-m rectangle was placed at a randomly generated orientation (0 - 180°). All potential ponderosa pine sites on the Gunnison National Forest were excluded using these criteria. All potential riparian sites on the Rio Grande were excluded using these criteria and no lodgepole pine sites were available on the Rio Grande to evaluate by CVU layers. Potential sites were visited in random order, at which time we applied the second set of criteria: 1. Forested sites were excluded if 2: 40% of the trapping grid was dominated by a cover type other than the nominal species dominant. 2. Candidate sites were excluded if inaccessible by snowmobile and snowshoes. 3. Candidate sites were excluded if they held any unmapped roads. 4. Candidate sites were excluded if logging or thinning had occurred within them. 5. Candidate sites were excluded if avalanche danger was present. 6. Candidate sites were excluded if trapping grids were < 500 m from a grid that had already been included. The first three sites from the list of candidates for each stand type to meet these criteria were included as trapping grids. Because of the availability of suitable sites, and for logistical reasons, all spruce-fir trapping grids, all lodgepole pine trapping grids and all riparian trapping grids were evaluated on the Gunnison National Forest. Only the ponderosa pine trapping grids were evaluated on the Rio Grande National Forest. After visiting 14 sites mapped as lodgepole pine on the Gunnison National Forest, three were found that met our criteria. Fifteen sites mapped as spruce-fir on the Gunnison National Forest were evaluated before three were found that met our criteria. Ten sites tentatively mapped as riparian on the Gunnison were visited, but none were found that met our criteria. Fifteen sites mapped as ponderosa pine on the Rio Grande National Forest were visited before three were found that met our criteria. Trapping and Handling All methods related to trapping and handling of animals were approved by the University of Wyoming Animal Care and Use Committee and by the Colorado Division of Wildlife Animal Care and Use Committee. Snowshoe hares were trapped using Tomahawk Model 204 live traps (18 em x 18 em x 51 �9 em) placed on trapping grids of 84 traps (7 lines of 12 traps each), with 50-m spacing for a trapping grid size of 16.5 ha (Figure 2). Three replicates for each stand type were sampled for 6 trap nights, which we assumed to be a closed population for the purposes of mark-recapture models. No reproduction occurred during our winter field season. The trapping grid size and method were developed by Scott Mills and Paul Griffin, University of Montana; we used these methods to maximize comparability between our study and theirs. Upon visiting a suitable site, the trapping grid was flagged and numbered using the UTM coordinates generated by a GPS receiver and a compass bearing (Figure 2). Traps were placed in suitable habitat within 2 m of the flagging and if necessary, covered with tree branches to provide cover for captured hares. Traps were baited with a mixture of pellets of Timothy grain, alfalfa, corn, and oats (TACO), alfalfa pellets and apples (P. Griffin, pers. commun.). Traps were checked as early as possible each morning and re-baited as needed. Once a snowshoe hare was captured, a pillowcase with a drawstring was placed over the front door of the trap. The hare was moved into the bag by gently tipping the trap, blowing on the hare, or making noise. Once the hare was in the bag it was immediately weighed using a 2500-g Pesola spring scale. The hare was then placed between the legs of a kneeling handler with the head facing towards the handler. The second handler marked the hare using a sterile passive-integrated transponder (PIT) tag. One tag was injected subcutaneously with a sterile needle between the shoulder blades. Both ears of the snowshoe hare were also marked using a permanent black marker for short-term identification. After the first day of any trapping session (i.e. on traps days 2-6) every snowshoe hare was scanned with a 125-kHz Miniportable reader to determine whether the hare was a recapture or a new capture. In the event the snowshoe hare was preyed upon and partially ingested, the earmarks were checked. Each snowshoe hare was sexed by turning the hare on its dorsal side and protruding the genitalia. The forefinger and middle finger were used to apply slight pressure to the vent area just above the anus. Snowshoe hares were then released away from handlers. Snowshoe hares that suffered severe trap or predation injuries were euthanized with a I-ml intrathoracic injection of sodium pentobarbital. Each carcass was necropsied and the liver and kidneys preserved for analysis of metals concentrations. After necropsy and tissue collection, euthanized animals were disposed of by cremation or deposited in a landfill. Any non-target species caught in traps were immediately released; whole specimens from any mortality of non-target species were donated to the Denver Museum of Nature and Science. Diet In 2003, fecal pellets were collected from the inside of each live-trap where a snowshoe hare was captured and allowed to air dry in kraft brown-paper bags. Fecal pellet samples were randomly selected for diet analyses from 24 individual snowshoe hares: four from each of the three spruce-fir grids and four from each of the three lodgepole pine grids. To reduce the possibility of finding TACO and alfalfa in the diet analyses, only first captures of snowshoe hares were used. Where < 4 snowshoe hares were captured on a trapping grid (e.g. SF 1, LP 2), fecal pellets were collected from fresh snowshoe hare tracks two days after snowfall. Fifteen fecal pellets were required for diet analyses (Bruce Davitt, Washington State University, pers. comm.). If < 15 fecal pellets were collected, a new random sample was chosen. For this reason, one sample (LP 1) was taken from a recaptured snowshoe hare three nights after the initial capture. Fifteen fecal pellets were arbitrarily chosen from each paper bag and transferred to a labeled envelope. Samples were submitted to the Wildlife Habitat and Nutrition Laboratory at Washington State University, Pullman, W A for analysis of diet. �10 Size of Fecal Pellets We measured snowshoe hare fecal pellets collected in 2002 to 0.1 mm using SPI dial calipers. Fecal pellets were also collected from every mountain cottontail incidentally captured in 2002 and 2003 and measured in the same way. Partial or damaged fecal pellets were eliminated from measurement. We measured the longest diameter for any non-spherical pellets. For snowshoe hares, 32 samples from 23 animals (n = 2374 fecal pellets) were measured. Ten samples from 10 mountain cottontails (n = 655 pellets) were measured. Vegetation Habitat attributes were estimated at two levels: at each trap site and for each trapping grid (Table 2). Within each trapping grid, vegetation was sampled from 15 trap sites, similar to the design of Scott Mills (Figure 2). Methods developed by Tanya Shenk (Colorado Division of Wildlife) to monitor habitat use by reintroduced lynx to Colorado were followed with modification (Figure 3). Accordingly, a 12-m x 12m square of25 points was placed in 5 rows of 5 (3 m apart), centered over the trap location (Figure 3). The measurements taken at each of the 25 points included: 1. Snow depth (em), as measured by a calibrated avalanche probe, from the center of each trap location. 2. Understory "hits" measured in a column of3-cm radius around an avalanche probe. a. All live or dead stems and coarse woody debris (CWO) that fall within the 3-cm radius column using the standardized four-letter genus-species code at 3 height categories (0-0.5 m, 0.51-1.0 m, 1.01 - 1.5 m) above the snow surface. b. Each of the above stems classified in 3 different diameter categories « 5 mm, 5.1 - 10 mm, 10.1 - 15 mm) measured at the point where the stem hit the avalanche probe 3. Overstory was measured using a densitometer attached to the avalanche probe. a. Species that hit the crosshairs inside the sighting tube were recorded. Multiple hits by the same species were only recorded once. 4. Every shrub within the plot along with its species and diameter at breast height was recorded (dbh). 5. Every tree within the plot along with its species and dbh was recorded. 6. Every snag within the plot along with its dbh was recorded. 7. Every sapling within the plot along with its species was counted. 8. All coarse woody debris (CWO) deemed usable by snowshoe hare for cover or food (i.e. available above the snow) was recorded along with its diameter. At all of the 84 trap sites within the trapping grid, including the 15 trap sites sampled as described above, the following data were measured: 1. Snow depth (em), as measured by a calibrated avalanche probe. 2. Species of, dbh of, and distance to the closest woody stem in two categories: ~ 1.0 em - 7.0 and ~ 7.1 em at the snow surface. 3. Canopy cover for the center of the trap site, as estimated by the use of a spherical densiometer, in the four cardinal quadrants (NW, NE, SE, SW). The following rules were used for unusual events: 1. If a point in a vegetation plot lay within a tree bole, the tree species and the dbh was written on the data form. �11 2. A snag was defined as any dead tree bole >45° from the horizontal. Dead boles <45° vertical angle were considered CWD. 3. The mid-point diameter was measured of exposed CWD partially covered by snow. 4. Ifa leaning tree fell partially outside the 12 m x 12 m sampling plot it was included if>50% of the tree lay within the sampling plot. Temperature and Moon Phase We used daily minimum temperatures recorded by the National Weather Service in Gunnison, Colorado in 2002 and 2003 for each night of trapping. This temperature was intended to represent general weather in the region rather than exact conditions at each trapping grid. We estimated the amount of moonlight for each night of trapping as the percentage of the moon's surface illuminated (Astronomical Applications Department, U.S. Naval Observatory, unpublished data). STATISTICAL ANALYSIS AND PRELIMINARY RESULTS We initially examined our preliminary data for distributional properties and homoscedasticity using SPSS 11.0. These properties are not important in predictors used in binary logistic regression, but are important in comparisons of means. Where we found substantive violations of assumptions regarding distributional properties, we used the appropriate non-parametric test. Our basic study design involved three stand types as represented by tree species dominants (spruce-fir, lodgepole pine, ponderosa pine). Other predictor variables (e.g. elevation, air temperature, habitat attributes) were highly co-linear with tree stand type and each other (Table 1). Trapping grids in spruce-fir tended to be at higher elevations, and have deeper snow and lower air temperatures (Table 1). Because air temperature (Paul Griffin, University of Montana, pers. comm.) and moon phase (Gilbert and Boutin 1991) have been reported to affect captures of snowshoe hares, we also explored these possible relationships and their relationship to other predictors We first used binary logistic regression to identify factors measured at the scale of the trapping grid (grid-night = unit of replication) that predict capture success. We included stand type (to include the covariates, elevation and snow depth), percent moon phase, temperature and year as candidate predictors of capture success. In this preliminary analysis stand type and temperature were significant in predicting capture success (Table 3). We then tested how air temperature in Gunnison was related with capture success in spruce-fir and lodgepole pine stands. Although there was no confounding variation with air temperature and stand type (AN OVA F= 98.8, d.f = 2, P = 0.19; spruce-fir = -14°C, lodgepole pine X = -l3°C, ponderosa pine = -11°C) we chose to exclude ponderosa pine from this analysis because no hares were captured on the ponderosa pine trapping grids. The relationship between air temperature and captures was significant (t = -3.9, d.f = 45, P < 0.001), with grid-nights for which captures were recorded having mean minimum temperatures of -11 °C, and those for which no captures were recorded having temperatures of -18°C. We also examined patterns of captures of snowshoe hares within trapping grids using the response variable of whether a trap location recorded a snowshoe hare capture during either 2002 or 2003. We examined patterns of independence of trap locations within a trapping grid by examining the distribution of trap locations where snowshoe hares were captured, versus those where they were not (Figure 4). We observed no obvious pattern of clumping of successful trap locations, and therefore assumed independence of individual traps as sampling units. When we used the grid-night as the unit of replication (n = 108), and included ponderosa pine trapping grids, trapping success did not differ between years (t = l.57, df = 106, P = 0.12). However, when trap-night was used as the unit of replication (n = 1512), trapping success did differ between years (t = -3.14, df = 1395, P = 0.002), with more captures in 2003 than 2002. x x �12 We used binary logistic regression to identify vegetation attributes that predicted capture success for snowshoe hares in an individual trap (trap-night = unit of replication). In this preliminary analysis we found that canopy cover was a significant predictor of capture success at trap locations (Table 5) with successful trap locations (x = 84% cover) having canopy cover 40% greater than that for unsuccessful trap locations (x = 60%, Mann-Whitney U = 14086, P < 0.001). The other significant predictor was distance to the nearest woody stem 1-7 cm in diameter, with successful trap locations (x = 2.0 m) having nearest stems only 56% as far away as unsuccessful trap locations (x = 3.6 m, M-W U= 21897, P < 0.001). We measured the mean sizes of fecal pellets of snowshoe hares (x = 8.4 mm) and mountain cottontails (x = 7.2 mm) from known species origin and found the means differed (Mann-Whitney U = 26.5, P = 0.001) and 95% confidence intervals did not overlap (Figure 5). DISCUSSION The results in this progress report are preliminary and subject to revision based upon continuing analyses of data. Still, some patterns in the data are apparent. Temperature appeared to have an effect on capture success whereas moon phase, although it has been reported to have an effect, did not. Our preliminary analysis of vegetation data suggests that canopy cover and distance to the nearest 1-7 em stem also affect capture success. A resource selection model will be generated in the next phase to determine habitat predictors of capture success. Our comparison of diameters of fecal pellets of snowshoe hares and mountain cottontails suggests a difference in size of pellets between the two sympatric lagomorphs that should be useful for identification of pellets to species in the field. �13 LITERATURE CITED Bartmann, R. M. and G. Byrne. 2001. Analysis and critique of the 1998 snowshoe hare pellet survey. Colorado Division of Wildlife, unpublished report no. 20. Bider, 1. R. 1961. An ecological study of the hare Lepus americanus. 39:81-103. Canadian Journal of Zoology Buttery, R. F. and B. C. Gillam. 1987. Managing forested lands for wildlife. Pages 43-71. Division of Wildlife, Denver, Colorado. Colorado Dolbeer, R. A. and W. R. Clark. 1975. Population ecology of snowshoe hares in the central Rocky Mountains. Journal of Wildlife Management 39:535-549. Gilbert, B. S. and S. Boutin. 1991. Effect of moonlight on winter activity of snowshoe hares. Arctic and Alpine Research. 23:61-65. Grigal, D. F. and N. R. Moody. 1980. Estimation of browse by size classes for snowshoe hare. Journal of Wildlife Management 44:34-40. Hodges, K. E. 2000a. The ecology of snowshoe hares in northern boreal forests. Pages 117-161 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and 1. R. Squires, editors. Ecology and conservation oflynx in the United States. University Press of Colorado, Boulder, Colorado. Hodges, K. E. 2000b. Ecology of snowshoe hares in southern boreal a..'1d montane forests. Pages 163206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation oflynx in the United States. University Press of Colorado, Boulder, Colorado. Hoover, R. L. and D. L. Wills. 1987. Managing forested lands for wildlife. Pages 455-477. Colorado Division of Wildlife, Eastwood Printing and Publishing, Denver, Colorado. Koehler, G. M. 1990a. Population and habitat characteristics of lynx and snowshoe hares in north-central Washington. Canadian Journal of Zoology 68:845-851. Koehler, G. M. 1990b. Snowshoe hare, Lepus americanus, use of forest successional stages and population changes during 1985-1989 in north-central Washington. Canadian Field-Naturalist 105:291-293. Lemmon, P. E. 1957. A new instrument for measuring forest overstory density. Journal of Forestry 55:667-668. U.S. Fish and Wildlife Service. 2000. Determination of threatened status for the contiguous U.S. distinct population segment of the Canada lynx and related rule; final rule. U.S. Federal Register 65: 1605116086. Wolff, J. O. 1980. The role of habitat patchiness in the population dynamics of snowshoe hares. Ecological Monographs 50: 111-130. �Table 1. Abiotic characteristics of nine trapping grids in three stand types, southwestern Colorado, late winter 2002 and 2003. Snow depth (em) is the mean (SE) measured at 84 trap locations at each trapping grid. Temperature (0C) (SE) is the mean low temperature recorded in Gunnison for each grid-night. The aspect of each trapping grid is shown in degrees in their respective order. Trapping grids Stand Type PP 1, PP 2, PP 3 Snow depth Elevation Temperature Aspect Pinus ponderosa 2 (0.4) 2600 -11 (1) 50°, 130°, 130° LP 1, LP 2, LP 3 Pinus contorta 45 (1) 3000 -13 (1) 230°, 90°, 130° SF 1, SF 2, SF 3 Picea engelmanii, Abies lasiocarpa 74 (1) 3400 -14 (1) 310°, 150°, 110° Table 2. Vegetation characteristics for nine trapping grids (see Table 1) in three stand types (n = 3 each), southwestern Colorado. Mean tree density, mean sapling density, and mean snag density (number ha") (SE) were counted at 15 trap locations on each grid, late winter 2002. Mean canopy cover (%) (SE) was measured at 84 trap locations on each grid using a densiometer , late winter 2002. The median horizontal cover (%) was measured at 15 trap locations on each grid using a horizontal profile board, late winter 2003. Stand Type Tree density Sapling density Snag density Canopy cover Horizontal cover Pinus ponderosa 187 (29) 301 (81) 273 (65) 36 (2) o Pinus contorta 1268 (138) 554 (109) 443 (67) 73 (1) 10 Picea engelmanii, Abies lasiocarpa 1418 (116) 642 (107) 287 (44) 79 (1) 65 -I::- �Table 3. Preliminary results of binary logistic regression using stand type (excluding ponderosa pine) and abiotic factors as variables to predict capture success (n = 72). Variables are described fully in the methods section. 95% C.I. Coefficient Z -- df P -- Odds Ratio Lower Upper Temperature 0.169 3.3 1 0.001 1.184 1.071 1.309 Stand type 1.794 2.7 1 0.006 6.012 NA Year -0.210 -0.3 1 0.771 0.811 NA Moonlight -0.003 -0.2 1 0.808 0.997 Constant -1.146 -0.6 1 0.541 0.318 Variable -- 0.808 0.997 NA Table 4. Preliminary results of binary logistic regression using vegetation characteristics to predict capture success at trapping locations within trapping grids (n=108). Variables are described fully in the methods section. 95% C.1. Coefficient --Z d.f P Odds Ratio Lower Upper Canopy cover 0.061 6.10 1 < 0.001 1.063 1.043 1.084 Diameter 1-7 cm -0.005 0.08 1 0.942 0.995 0.880 1.126 Distance 1-7 ern -0.002 -2.00 1 0.002 0.998 0.997 0.999 Diameter >7 em -0.014 -1.17 1 0.235 0.986 0.963 1.009 Distance >7 ern 0.001 1.00 1 0.148 1.001 0.999 1.003 Constant -6.058 -6.44 1 < 0.001 0.002 Variable NA •.....• VI �•.....• ILP2 0\ -; " ?l ~ LP3 ,,~~ , SF1 0(.- t?fl Taylor Park Ressrvoir ,, ,, , ~ ''', ~~ ~"'\, ~./cf~ V~n "-',,~ 'I; .. PP 1 "', PP 2 ~ ~ ~ PP 3 _ 1~ 1 Paved highways ------------- - I .. _, - - ~ 1 Rivers and streams -----"''''''' \\~~~/...... _,,,,/ randeR ./'" South Fork '" 0\) I RioG ~~ S.t~t($J o km N -* 10 I I I Figure 1. Location of nine trapping grids (mml), southwestern Colorado, 2002 - 2003. SF is spruce-fir, LP is lodgepole pine, and PP is ponderosa pine. Trapping grids are not to scale. �17 1# 2# 3# 4# 5# 6# 7# 8# 9* 10# 11* 12# 13* 14# 15# ,16# 17# 18# 19# 20# 21# 22# 23* 24# 25* 26# 27* 28# 29# 30# 31# 32# 33# 34# 35# 36# 37* 38# 39* 40# 41 * 42# 43# 44# 45# 46# 47# 48# 49# 50# 51* 52# 53* 54# 55* 56# 57# 58# 59# 60# 61# 62# 63# 64# 65* 66# 67* 68# 69* 70# 71# 72# 73# 74# 75# 76# 77# 78# 79# 80# 81# 82# 83# 84# Figure 2. Schematic of 300 m x 550 m trapping grid for estimating population density of snowshoe hares in southern Colorado. Asterisks (*) indicate the location of the 15 vegetation plots centered on trapping points. Pound signs (#) indicate where the point-quarter method will be used on all other trap locations. �18 trap 12m Figure 3. Schematic of 12 m x 12 m vegetation plot centered on each of the 15 trap sites (Figure 2) used in measuring habitat variables for snowshoe hares in southwestern Colorado, late winter 2002. The trap location is at the center of the vegetation plot. �19 SF 1 •0 00 • 0• 0• 00 • • • 0 0 0 0 0 • • 0 0 0 0 0 0 • 0 0 0 0 • • • 0 0 0 0 • • • 0 0 0 0 • • • 0 0 0 0 • 0 0 0 0• 0• 0 • 0 0 0 0 0 • 0 • 0 0 • • • • 0 0 0 • • • • SF2 0 0 0 0 • 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 LP 1 •0 00 00 00 00 00 00 • • n= 33 •0 00 00 00 0 0 • 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 • 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 • • 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 n= 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 n=4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 • 0 0 0 0 0 0 • • • • • LP2 n=4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 • • • • 0 0 0 0 0 0 0 0 SF 3 • 00 00 • 00 • • • 0 0 0• 0 0• • • 0 • 0 0 0 • 0• 0• 0 0 • • • 0 0 0 0 0 0 0 • 00 00 0 00 0• 0• • 0 0 • 0 0 • 0 0 0• 0 • • • • 0 0 0 0 0 0 • • 0 0 0 0 0 • LP3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 • n= 30 • • • • 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 • • • 0 0 0 0 0 0 0 0 0 • n=9 Figure 4. 12 x 7 trapping grid schematic representing snowshoe hare trap successes (.) for 6 trapping grids in two stand types, spruce-fir and lodgepole pine (snowshoe hares were absent from all pondersosa pine trapping grids), southwestern Colorado, late winter 2002 and 2003. �20 10 9 8 7 ...-... 8 8 6 '-' 1-< <I) .•....• 5 8 eli 4 <I) ;:a 3 2 O~--------------.--------------.--------------_J L. americanus S. nuttallii Figure 5. Mean diameters of fecal pellets of Lepus americanus (n = 23 animals) and Sy/vi/agus nuttallii (n = 10 animals). Error bars indicate 95% confidence interval. �21 JOB PROGRESS REPORT Smteof ~C=o=l=or=a=d=o Work Package No . .:<..06~7,-,,0,--Task No. -'I'--- Period Covered: July 1,2002 _ Division of Wildlife - Mammals Research _ Lynx Conservation _ Post-Release Monitoring of Lynx Reintroduced to Colorado - June 30, 2003 Author: Tanya M. Shenk Personnel: R. Dickman, R. Kahn, A. Keith, G. Miller, C. Wagner, S. Wait, D. Younkin Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged ABSTRACT Reproduction is critical to the success of any reintroduction effort if a self-sustaining, viable population is the ultimate goal of the conservation effort. As of winter 2002-2003, no reproduction had been documented from lynx reintroduced to Colorado beginning in winter 1999. However, the low density of lynx present in Colorado by winter 2002-2003 limited the ability to answer the question of whether Colorado is suitable to sustain a viable lynx population because either insufficient habitat or lynx at too Iowa density to achieve reproductive success could have resulted in the lack of reproduction. Following an analysis of possible management options, it was decided that an augmentation of this reintroduction effort was necessary to eliminate an ambiguous result if successful reproduction had not occurred under densities such as exist in winter 2002-03. The reintroduction effort was augmented with 33 additional animals, released within the Core Area in April 2003, to increase lynx density so that the question of whether lynx can sustain viable populations in Colorado could be more definitively addressed. Based on dispersal patterns of lynx released in 2000, the second cohort, it was hypothesized that lynx released in the Core Area would show the necessary site fidelity to increase lynx densities to enhance the probability of successful reproduction. The first lynx kittens documented to be born to lynx reintroduced to Colorado were found on May 21,2003. A total of 6 dens and 16 kittens were found in 2003. From results to date it can be concluded that CDOW has developed release protocols that ensure high initial post-release survival, and on an individual level lynx have demonstrated they can survive long-term in areas of Colorado. It had also been documented that reintroduced lynx could exhibit site fidelity, engage in breeding behavior and produce kittens. What is yet to be demonstrated is whether Colorado conditions can support the recruitment necessary to offset annual mortality for a population to sustain itself. Monitoring of reintroduced lynx will continue in an effort to document such viability. �22 Post-Release Monitoring of Lynx (Lynx canadensis) Reintroduced to Colorado Tanya M. Shenk Mammals Research Colorado Division of Wildlife INTRODUCTION The Canada lynx (Lynx canadensis) occurs throughout the boreal forests of northern North America. Colorado represents the southern-most historical distribution of lynx, where the species occupied the higher elevation, montane forests in the state. Little was known about the population dynamics or habitat use of this species in their southern distribution. Lynx were extirpated or reduced to a few animals in the state by the late 1970's. Given the isolation of Colorado to the nearest northern populations, the Colorado Division of Wildlife (CDOW) considered reintroduction as the only option to attempt to reestablish the species in the state. A key question to be asked when considering the re-establishment of any species is, "What is different now from when they disappeared?" For lynx, the causative factor(s) of their extirpation may never be known. Many of the hypothesized factors, however, have changed substantially since the early and mid-1900's. For example, widespread predator poisoning no longer occurs; conservation of wildlife habitat is now given much stronger consideration in public land management decisions; trapping and hunting are more strictly regulated and regulations enforced; and in some areas, at least, the passage of time has allowed the landscape to recover from abuses of the past, perhaps to a state that is more conducive to lynx survival. It must be acknowledged, however, that there may be other detrimental factors operating now that did not exist previously. In particular, increased human density and development have occurred in some areas and exotic diseases such as plague have been introduced in Colorado. The uncertainty surrounding the cause of the extirpation of lynx and the effects of current conditions in Colorado on lynx makes it impossible to predict with confidence whether Colorado has sufficient habitat to sustain viable population(s) of lynx. In order to perform the best test of this question the CDOW led a cooperative effort to reintroduce wild-trapped lynx from Canada and Alaska into southwestern Colorado beginning in 1999. It was hoped the effort would clarify whether or not Colorado is or is not suitable for sustaining viable lynx populations, provided the fate of the released animals could be determined. The goal of the Colorado lynx reintroduction program is to establish a viable population oflynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing if the reintroduction effort is progressing towards success. There are seven critical criteria for achieving a viable population: (1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, (2) long-term survival oflynx in Colorado, (3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, (4) reintroduced lynx must breed, (5) breeding must lead to reproduction of surviving kittens (6) lynx born in Colorado must reach breeding age and reproduce successfully, and (7) recruitment must be equal to or greater than mortality. Prior to the reintroduction, it was hypothesized that a minimum of 100 animals would need to be released for a fair evaluation of the suitable/unsuitable question. In 1999 and 2000,96 lynx (57 females, 39 males) were released into the San Juan Mountains of southwestern Colorado. The 1999 cohort of 41 individuals scattered widely, and suffered a first year mortality of 17 (41 %) lynx (Shenk 2001). The 2000 cohort of 55 animals, being released into areas already occupied (although sparsely) by the previous year's animals, were more sedentary, and experienced a first year mortality of 10 (18%) lynx. Humancaused mortalities due to vehicle collision, gunshot, and the mortalities where only a cut collar was found �23 comprise the greatest known cause of mortality for all the reintroduced lynx (31 %). Mortalities due to starvation (23%) were minimized with the improved release protocols. To date, only 2 of the 55 lynx released in 2000 died of starvation. However, the improved survival of reintroduced lynx provided only partial evidence that Colorado could sustain a viable population of the species. As of winter 2003, no successful reproduction had been documented. This lack of reproduction resulted in an increased emphasis on the question of whether or not Colorado could provide sufficient habitat to sustain a selfsustaining population of lynx. Two options existed to address the problem of answering the suitable/unsuitable question. The first was to continue to monitor the existing animals for recruitment, with the understanding that the probability of detection would decrease rapidly as radio-collars failed, and the probability of successful pairing might further decrease with lowered densities due to natural mortality. Possible outcomes include 1) the animals currently out there would eventually reproduce with sufficient success to establish a viable population of lynx, 2) the animals currently out there would reproduce although not in sufficient numbers to offset mortality or 3) the animals currently out there would fail to reproduce. The primary reasons for outcomes 2 and 3 are either that Colorado does not have sufficient habitat to support viable populations of lynx or there were too few lynx released to achieve sufficient successful reproduction. Thus, the question of whether or not Colorado can support viable population(s) of lynx would remain arguable. A second option would be to supplement the existing lynx by re-introducing additional lynx over multiple years into the Core Area to attain a density approaching that of established populations of lynx. The possible outcomes could be any of those listed for the first option. The difference, however, would be that the low-density explanation for failure to establish a viable population would be difficult to support. Thus, CDOW could more definitively address the question of the suitability of Colorado for lynx populations. An analysis of these two options was conducted to determine the best management strategy to pursue to enhance the ability to assess the outcome. An update of the post-release monitoring program was also conducted. OBJECTIVES The initial post-release monitoring of reintroduced lynx will emphasize 5 primary objectives: 1. Assess and modify release protocols to enure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival oflynx reintroduced to Colorado. 5. Estimate reproduction oflynx reintroduced to Colorado. Three additional objectives will be emphasized after lynx display site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of IY~O ervation strategies in the southern Rocky Mountains. Lastly, an analysis was conducted to evaluat tow ____----;/ management options for assessing Colorado's suitability for sustaining a viable lynx populatio . "- �24 METHODS Augmentation An analysis of two management options was conducted to determine the best management strategy to pursue to enhance the ability to assess whether Colorado provided suitable habiat for a viable, self-sustaining population of lynx. In response to the completed analysis, the current reintroduction effort was augmented with additional animals, released within the Core Area, to increase lynx density so that the question of whether lynx can sustain viable populations in Colorado could be more definitively addressed. These new releases were conducted under the protocols found to maximize survival (see Shenk 1999). Based on dispersal patterns of lynx released in 2000, the second cohort, it was hypothesized that lynx released in the Core Area would show the necessary site fidelity to increase lynx densities to enhance the probability of successful reproduction. Movement Patterns To determine general movement patterns and habitat used by reintroduced lynx, regular locations of released lynx were collected through a combination of aerial, satellite and ground radio-tracking. Locations and general habitat descriptions at each location were recorded and mapped. Frequent flights (at least 2 times per week) were critical during the initial post-release periods because of the greater likelihood of dispersal and mortality in reintroduced carnivores during this period. Every effort was made to locate all lynx each flight during this period. All lynx released in the winter and spring of 1999 were fitted with Telonics™ VHF radio-collars, equipped with a mortality switch that activates if the collar remains motionless for 4 hours or more. Fiftyone of the 55 lynx released in the spring 2000 were fitted with Sirtrack™ dual satellitelVHF radio-collars (the other 4 lynx were fitted with Telonics™ VHF collars). All 33 lynx released in 2003 were fitted with Sirtrack™ dual satellite/VHF radio-collars. These collars also had a mortality indicator switch that operated on both the satellite and VHF mode. The satellite component of each collar was programmed to be active for 12 hours per week. The 12-hour active periods were staggered throughout the week, with approximately 7 collars being active each day of the week. Signals from the collars allowed for locations of the animals to be made via Argos, NASA, and NOAA satellites. The location information was processed by ServiceArgos and distributed to the CDOW through e-mail messages. Survival and Mortality Factors When a mortality signal (75 ppm vs. 50 ppm for the Telonics™ VHF transmitters, 20 bpm vs. 40 bpm for the Sirtrack™ VHF transmitters, 0 activity for Sirtrack™ PIT) was heard during either satellite, aerial or ground surveys, the location (UTM coordinates) was recorded. Ground crews then located and retrieved the carcass as soon as possible. The immediate area was searched for evidence of other predators and the carcass photographed in place before removal. Additionally, the mortality site was described, habitat associations, and exact location were recorded. Any scat found near the dead lynx that appeared to be from the lynx was collected. All carcasses were transported immediately to the Colorado State University Veterinary Hospital for a post mortem exam to I) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, and 3) archive samples for future reference (research or forensic). The gross necropsy and histology were performed by, or under the lead and direct supervision of a board certified veterinary pathologist. At least one research personnel from the CDOW involved with the lynx program was also present. The protocol followed standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing (see Shenk �25 1999 for details). Some additional data/samples were routinely collected for research, forensics, and archiving. Other data/samples were collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). The CDOW retained all samples and carcass remains with the exception of tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, and other diagnostic samples. Reproduction Females were monitored for proximity to males during breeding season and for site fidelity to a given area during the denning period of May and June. Each female that exhibited stationary movement patterns in Mayor June 2003 was observed to look for accompanying kittens. If kittens were found at a den site they were weighed, sexed and photographed. Each kitten was uniquely marked by inserting a sterile passive integrated transponder (PIT, Biomark, Inc., Boise, Idaho, USA) tag subcutaneously between the shoulder blades. Time spent at the den was minimized to ensure the least amount of disturbance to the female and the kittens. Weight, PIT-tag number, sex and any distinguishing characteristics of each kitten was recorded. Den site location was recorded as Universal Transmercator (UTM) Coordinates. Other data to be recorded include general vegetation characteristics, elevation, weather, field personnel, time at the den, and behavioral responses of the kittens and female. RESULTS Rationale for Augmentation. Thirty-six reintroduced lynx were known to be in the Core Area in winter 2002-2003, which is approximately 10,000 mi". Thus, the lowest possible density of lynx in the Core Area was approximately 2 lynx /500 me, an area slightly larger than Rocky Mountain National Park. The highest density of reintroduced lynx in the Core Area was approximately 3 lynx /500 mi", if all the missing lynx at that time were currently there but not being detected due to faulty radio collars. If additional naturally occurring lynx were in the area these densities could have been even higher. Lynx densities reported for natural populations occurring in northern habitats range from < 13 lynx /500 mi2 during snowshoe hare lows to 104-259 lynx /500 me in years of peak hare densities in mature forests. The densities of lynx reported for populations in the north during the low in the hare cycle may not represent the lowest densities at which lynx could exist and maintain viable populations. At these lows, northern lynx still reproduce although at a much lower rate then when the hare density is higher. This low reproductive rate could be related to poor body condition, low lynx densities, or a combination of both. What can be assumed is that lynx occurring at these low densities are able to rebound and achieve higher densities. Given that reintroduced lynx in Colorado are in good body condition, CDOW may only need to increase densities to achieve reproductive rates that would sustain a viable population of lynx. Densities of lynx reported for their northern range reflect densities where lynx habitat is more uniform and consistent than in Colorado. In Colorado, although the Core Area is described as 10,000 mi", lynx are not using the Core Area uniformly but rather are dispersed in patches throughout the Core Area. Therefore the densities calculated for lynx in Colorado are not directly comparable to those estimated from the north. It is difficult, however, to estimate an appropriate correction factor for Colorado densities to make them comparable to those reported for northern populations. Therefore, the number of lynx needed to augment the current population to achieve a density of 13 lynx! 500 mi2 under several combinations of current density and percent of the Core Area that has suitable habitat was estimated (Table 1). �26 Although this analysis required numerous assumptions, an augmentation effort of at least 150 animals (no more than 50 per year) is a minimum target for achieving densities of lynx conducive to successful reproduction and recruitment. Once minimum densities have been achieved, additional releases should continue over four to five years to maintain the minimum densities considered necessary for successful reproduction. Monitoring of the lynx population throughout the augmentation will be critical and should be conducted rigorously. The target density of 13 lynx /500 rni2 is based on the lowest densities documented for northern populations. However, lynx may be able to rebound from lower densities. Thus, through monitoring CDOW should estimate at what densities reproduction occurs, and at what densities successful recruitment of animals occurs. This may happen at densities lower than low lynx densities estimated for the north. Table 1. Estimates of current densities of reintroduced lynx in the Core Area under various combinations of number of lynx and percent suitable habitat. Calculations of how many lynx would be needed under these conditions to achieve densities similar to the lowest densities reported for northern populations are presented and the number of additional lynx needed to achieve this density. Minimum Density Lynx needed to achieve additional lynx Density Assumptions lynx! 500 mi" 13 lynx! 500 m? needed' No.of lynx % Area suitable rrummum 100% 1.8 260 224 2.6 260 maximum 100% 208 2.4 195 mmrmurn 75% 159 3.5 maximum 75% 195 143 3.6 130 mmrmum 50% 94 5.2 130 maximum 50% 78 Assumes no mortality. Augmentation Based on the adoption of the augmentation management strategy, 33 lynx were released in April 2003, bringing the total number of lynx reintroduced to Colorado to 129 (Table 2). The 33 lynx reintroduced in 2003 had been captured in Quebec, Manitoba and British Columbia. These new releases were conducted under the protocols found to maximize survival (see Shenk 2001). All 33 lynx were released in the Core Area of southwestern Colorado. Each lynx was released with a dual VHF/satellite radio collar so that the lynx can be monitor for movement and mortality. Estimated age, sex and body condition were ascertained and recorded for each lynx prior to release (see Wild 1999). Specific release sites were selected based on land ownership and accessibility during times of release. Lynx were transported from the holding facility to the release site in cages (usually 1, occasionally 2 lynx per cage). Release site location was recorded in Universal Transverse Mercator (UTM) coordinates and identification of all other lynx released at the same location, on the same day, was recorded. Behavior of the lynx on release and movement away from the 'release site were documented. �27 Table 2. Colorado lynx reintroduction effort as of June 30, 2004. Females Males TOTAL Year 22 19 41 1999 35 20 55 2000 17 16 33 2003 74 55 129 TOTAL Reproduction Nine pairs oflynx were documented during the 2003 breeding season (March and April). In May and June 2003,6 dens and a total of 16 kittens were found in the lynx core research area in southwestern Colorado (Table 3). At all dens the females appeared in excellent condition, as did the kittens. The kittens weighed from 270-500 grams. Lynx kittens weigh approximately 200 grams at birth and do not open their eyes until they are 10-17 days old. Dens were found when field crews walked in on females that exhibited virtually no movement for at least 10 days from both aerial and ground telemetry. Table 3. Reproduction information for summer 2003. Kittens Date Den Female Release Year Found Females BCOOF8 2000 5/21/03 ? BCOOF19 2000 5/26/03 1 YKOOF16 2000 6/19/03 1 YK99Fl 6/10/03 1999 2 YKOOF19 2000 6/11/03 1 YKOOFI0 2000 5/31/03 2 TOTAL 7 Males ? 1 1 1 2 2 7 Total 2 2 2 3 3 4 16 The dens were scattered throughout the Core Area, with no dens found outside the Core Area. All the dens were in Engelmann spruce/subalpine fir forests in areas of extensive downfall. Elevations ranged from 3240-3557 m (10,630 - 11,670 feet). Field crews weighed, photographed, and PIT-tagged the kittens. Field crews also took hair samples from the kittens for genetic work in an attempt to confirm paternity. Kittens were processed as quickly as possible (11-32 minutes) to minimize the time the kittens were without their mother. While working with the kittens the females remained nearby, often making themselves visible to us. The females generally continued a low growling vocalization the entire time personnel were at the den. In all cases, the female returned to the den site once field crews left the area. Locations .The 2003 releases have remained in the Core Area with the exception of 2 lynx that went briefly to New Mexico but subsequently returned to Colorado. Most lynx continue to use terrain within the Core Area: New Mexico north to Gunnison, west as far as Taylor Mesa and east to Monarch Pass. There are some lynx north of Gunnison up to the 170 corridor and in the Taylor Park area. No lynx are known to be north of 170 at this time. Mortalities Of the total 129 lynx released in 1999,2000 and 2003 there are 46 known mortalities. Of these 46 mortalities, 25 are from the 1999 releases, 20 are from the 2000 releases, and 1 is from the 2003 releases. Causes of death are listed in Table 4. �28 Table 4. Causes of death for lynx released into southwestern Colorado in 1999,2000 and 2003. 2000 2000 2003 2003 1999 1999 2000 Male Female Male Female Unk Male Female Cause of Death Starvation 1 6 1 1 3 1 Hit by Vehicle 2 I 3 1 I Shot Probable Predation 1 3 Plague Unknown: Human Caused Probable Shot I 2 1 Probable Hit by Vehicle 2 Unknown: Not Starvation I 2 1 2 4 3 1 Unknown 1 12 Total Mortalities 8 17 7 1 1 Total 9 6 6 3 4 2 4 11 46 Current Status At this time, CDOW is tracking 61 of the 83 lynx still possibly alive. A lynx is listed as missing if a signal has not been heard from the animal for at least 1 year. There are 21 lynx that CDOW has not heard signals on since at least June 30, 2002 (Table 5). One of these missing lynx cannot be identified but was hit by a truck in New Mexico, thus only 20 are truly missing. Possible reasons for not locating these missing lynx include (1) long distance dispersal, beyond the areas currently being searched, (2) radio failure, or (3) destruction of the radio (e.g., run over by car). CDOW continues to search for all missing lynx during both aerial and ground searches. Expanded flights outside the research area during the summer and fall months may yield locating these missing lynx. Two of the lynx released in 2000 have probably slipped their collars. Thus, CDOW has tracked 61 individual lynx since at least June 30,2002. Table 5. Status of lynx reintroduced to Colorado as of June 30,2003. Females Males Unknown TOTALS Released 74 55 129 46 Known Dead 29 16 45 39 Possible Alive 83 7 Missing 14 21 (1 is unknown mortality) 1-2 Slipped Collar 1 I? 37 24 61 Tracking �29 DISCUSSION The low density oflynx present in Colorado in winter 2002-2003 limited the ability to answer to the question of whether Colorado has sufficient suitable habitat to sustain a viable lynx population. At that time, the lack of successful reproduction may have reflected either insufficient habitat or lynx at too Iowa density to achieve reproductive success. It was decided that an augmentation of this reintroduction effort was necessary to eliminate an ambiguous result if successful reproduction had not occurred under densities existing in winter 2002-03. In order to maintain densities equal to those in areas that have maintained breeding populations the CDOW would need to reintroduce 50 lynx per year for the next three years and augment the population with an additional 10-12 lynx for years 4 through 6. The reintroduction effort was augmented with 33 additional animals, released within the Core Area in April 2003, to increase lynx density so that the question of whether lynx can sustain viable populations in Colorado could be more definitively addressed. Based on dispersal patterns of lynx released in 2000, the second cohort, it was assumed lynx released in the Core Area would show the necessary site fidelity to increase lynx densities to enhance the probability of successful reproduction. The first lynx kittens documented to be born to lynx reintroduced to Colorado were found on May 21, 2003. A total of 6 dens and 16 kittens were found in 2003. While this is a milestone CDOW has been hoping to achieve, live births are the first step towards recruitment. Recruitment into a population would require these kittens to survive through their first year oflife and produce offspring of their own. To achieve a viable population of lynx, enough kittens need to be recruited into the population to offset the mortality that occurs in that year and hopefully even add more so that the population can grow. Although den sites will not be visited again until fall 2003, so as not to disturb the female and kittens further, the female's movement patterns will be monitored through aerial telemetry. During fall 2003, demales with kittens will be observed through walk-ins to try to count the number of kittens still with her. Alternatively, the females will be snow-tracked once there is sufficient snowfall on the ground to document the presence and number of kittens. Kittens typically stay with their mothers until they are 10 months old. The Colorado lynx reintroduction effort has overcome most obstacles encountered so far. From results to date it can be concluded that the CDOW has developed release protocols that ensure high initial post-release survival (Shenk 2001), and on an individual level lynx have demonstrated they can survive long-term in areas of Colorado. It had also been documented that reintroduced lynx could exhibit site fidelity, engage in breeding behavior and produce kittens. What is yet to be demonstrated is whether Colorado conditions can support the recruitment necessary to more-than-offset annual mortality for a population to sustain itself. Monitoring of reintroduced lynx will continue in an effort to document such viability. LITERATURE CITED Shenk, T. M. 1999. Program narrative: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Report for the Colorado Division of Wildlife. Shenk, T. M. 2001. Post-release monitoring oflynx reintroduced to Colorado. Wildlife Research Report. Colorado Division of Wildlife. Wild, M. A. 1999. Lynx veterinary services and diagnostics. Division of Wildlife. Fort Collins, Colorado. Job Progress Report for the Colorado �30 �31 JOB PROGRESS REPORT Srnreof C~ol~o=ra=d=o---- Work Package No. 0880 Task "-1 Division of Wildlife - Mammals Research Black-footed Ferret Conservation _ Disease Monitoring & Management Period Covered: July 1 2002 through June 30, 2003 Author: L. L. Wolfe and L. A. Baeten Personnel: D. Finley, P. Schnurr, K. Cramer, H. Edwards, E. Knox, C. T. Larsen, N. Mier, M. W. Miller; K. Taurman, E. S. Williams Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT We continued monitoring carnivores at proposed black-footed ferret reintroduction sites for serological evidence of select disease epidemics. Sampling at the Wolf Creek Management Area (WCMA) in August 2003 revealed little evidence of ongoing epidemics that could impede black-footed ferret restoration efforts. Serology darn from culled coyotes showed no evidence of active canine distemper or plague epidemics in the WCMA vicinity. In contrast, serologic evidence of exposure to tularemia was relatively high (-30%), consistent with previous observations in this and other monitored areas. We will continue this work as part of the ongoing Colorado-Utah black-footed ferret reintroduction protocol. �32 INTRODUCTION As part of the Colorado-Utah black-footed ferret reintroduction protocol, we continued monitoring carnivores at proposed ferret reintroduction sites for serological evidence of select disease epidemics. Originally, we monitored coyote (Canis latrans) populations at two Colorado sites: the Little Snake Management Area (LSMA) and the Wolf Creek Management Area (WCMA), Colorado. Under this program, >200 coyotes have been collected for post-mortem examination and samples collected as described in established protocols since March 1997. Monitoring has been accomplished via cooperative efforts of Colorado Division of Wildlife, USDA Wildlife Services, and Bureau of Land Management (BLM) personnel. To date, no lesions indicative of active infections with any of the select pathogens (Francisellia tularensis, Yersinia pestis, canine distemper virus [CDV]) have been noted on gross examinations of carcasses. However, relatively high proportions (31-89%) of the coyotes collected from the LSMA had positive titers to plague between March 1997 and July 1999. Although the proportion of plague-positive coyotes declined during the sampling period, evidence of continued exposure and perhaps declining prairie dog abundance led to abandonment of surveillance at LSMA after 1999. Monitoring at the WCMA has continued, and black-footed ferrets were reintroduced at this site in 2001. METHODS Coyotes were collected using a combination of calling and aerial gunning (USDA-APHIS-Wildlife Services). In light of ambiguity in results from mid-winter sampling attributable to the inability to accurately estimate ages of coyotes in the field, we began focusing on late summer sampling to monitor epidemic trends. Postmortem examination, sampling, and serological methods were as described . previously (Colorado Division of Wildlife, Disease Survey of Carnivores in the Little Snake Area, ACUC 1997-3). RESULTS AND DISCUSSION Initial sampling (February 2000) at WCMA indicated substantially lower exposure rates to select pathogens than observed at LSMA. Data from 2001 surveys indicated a relatively high proportion of adult coyotes exposed to canine distemper virus (CDV)(Figure 1): in February 2001, about 79% of the coyotes sampled had serum neutralizing titers ~1:16. Recent sampling revealed lower proportions of CDV -positive coyotes, similar to the initial sampling periods. In contrast to canine distemper, exposure to plague appears relatively rare among coyotes sampled from WCMA (Figure I). As tularemia is commonly found in rodents in Colorado, a seroprevalence of 20-40% is not surprising in WCMA Date/pathogen Figure 1. Seroprevalence of presumed tularemia, plague, and canine distemper exposure among coyotes sampled from the Wolf Creek Management Area, Colorado, during February 2000 to August 2003. �33 JOB PROGRESS REPORT Division of Wildlife - Mammals Research State of Colorado Work Package No. __ -=30-"-'0"-'1,___ Task No. Effect of Nutrition and Habitat Enhancements on Mule Deer Recruitment and Survival Rates ---'-W_,_-....Oc1=8:::._5-....OcR.=o._ _ 4 Federal Aid Project __ _ Deer Conservation Period Covered: July 1, 2002 - June 30, 2003 Authors: C. 1. Bishop, G. C. White, D. 1. Freddy, and B. E. Watkins Personnel: D. L. Baker, L. Baeten, S. K. Carroll, D. Coven, K. Crane, M. DelTonto, B. Diamond, B. deVergie, D. Gallegos, J. Garner, L. Gepfert, R. B. Gill, D. Hale, J. Grigg, R. Harthan, W. J. Lassiter, T. Mathieson, 1. McMillan, G. C. Miller, M. W. Miller, 1. Nicholson, 1. A. Padia, T. M. Pojar, J. E. Risher, C. A. Schroeder, W. G. Sinner, C. M. Solohub, J. Thayer, M. A. Thonhoff, L. Wolfe, CDOW; H. VanCampen, CSU; D. Felix, Olathe Spray Service; T. R. Stephenson, California Fish and Game; L. H. Carpenter, WMI; 1. Sazma, B. Welch, BLM. ABSTRACT To further understand the factors that caused deer numbers to decline in western Colorado during the 1990s, we designed and initiated a field experiment to measure deer population parameters in response to a nutrition enhancement treatment. During November 2000 - June 2003, we captured and radio-collared 533 individual mule deer evenly distributed among treatment and control units on the Uncompahgre Plateau in southwest Colorado. This included 216 adult females, 94 of which received vaginal implant transmitters (VITs), 160 6-month old fawns, and 157 newborn fawns born from either treatment or control adult does. We enhanced the nutrition of deer in the treatment unit by providing a safe, pelleted supplemental feed on a daily basis from December through April each winter. Early winter fawn:doe ratios were measured using helicopter and ground classification surveys the year following treatment delivery to determine whether fawn production and survival increased as a result of enhanced nutrition of adult females. We also measured overwinter fawn survival rates in response to the treatment. In 2002 and 2003, we measured pregnancy rates, fetus rates, and body condition of treatment and control adult does during late winter using ultrasonography. We also directly measured fetus survival and neonate survival by using VITs to help locate and radio-collar newborn fawns born from treatment and control does. Estimated percent body fat of adult does during late February and early March of 2002 and 2003 was significantly higher (Fl. 90 = 108.21, P < 0.001) for treatment deer (10.4%, SE = 0.48, n = 48) than control deer (4.0%, SE = 0.36, n = 46). Serum thyroid hormone concentrations (measured only in 2003) were higher in treatment does than control does as well (F4• 52 = 32.59, P < 0.001). Pregnancy and fetus rates were similar among treatment and control does. The pregnancy rate of adult does was 0.95 (SE = 0.036, n = 38) and the fetus rate was 1.80 fetuses/doe (SE = 0.10, n = 36) during 2002. Rates were similar in 2003, where we measured a pregnancy rate of 0.92 (SE = 0.034, n = 63) and a fetus rate of 1.74 fetuses/doe (SE = 0.069, n = 50) which included 5 yearlings (the fetus rate excluding yearlings was 1.82 fetuses/doe, SE = 0.066, n = 45). The fetus survival rate with treatment and control fetuses combined was 0.86 (SE = 0.073) during 2002 and 0.97 (SE = 0.024) during 2003. Based on multiple early winter age classification surveys, we concluded that the winter nutrition enhancement treatment did not cause an increase in neonatal production and survival during 2001. Neonate survival data coupled with early �34 winter age classification surveys indicated a marginal treatment effect during 2002. However, fawn production and summer-fall survival was relatively good during 2001 and 2002 for the overall population, and not representative of most years during the past decade when the population declined. During 2003, as of late September, survival of newborn treatment fawns was 0.745 (SE = 0.059) and control fawn survival was 0.614 (SE = 0.073). During 2001-02, the overwinter survival rate of fawns was significantly greater (X2} = 13.216, P < 0.001) in the treatment unit (S(t) = 0.865, SE = 0.056) than in the control unit (S(t) = 0.510, SE = 0.080). Again in 2002-03, the overwinter survival rate of fawns was significantly greater (X2} = 5.734, P = 0.017) in the treatment unit (S(t) = 0.900, SE = 0.047) than in the control unit (S(t) = 0.691, SE = 0.074). Because ofa cross-over over experimental design, the treatment unit during winter 2001-02 became the control unit during winter 2002-03, and vice versa. Thus, the overwinter survival treatment effect was replicated across each experimental unit. Combining both years of data, the best model of overwinter fawn survival (AICc = 148.63) included the treatment effect (X2} = 14.71, P < 0.001), early winter fawn mass (X21 = 16.80, P < 0.001), year (X2} = 3.53, P = 0.060), and sex (X21 = l.99, P = 0; 158). The AIC model selection analysis emphasized the importance of both the treatment effect as well as early winter mass of fawns, because any models without treatment or fawn mass were very poor. Early winter mass was not different among experimental units (FI = 0.35, P = 0.558), thus the effect of the treatment was not confounded with fawn mass. We will continue this research for 1.5 more years. The results reported here are preliminary and should be treated as such. �35 EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES C. 1. Bishop, G. C. White, D. J. Freddy, and B. E. Watkins P. N. OBJECTIVES 1. To determine experimentally whether enhancing mule deer nutrition during winter and early spring by supplemental feeding increases fetus survival, neonate survival, early winter fawn:doe ratios or overwinter fawn survival. 2. To determine experimentally to what extent habitat treatments replicate the effect of enhanced nutrition from supplemental feeding. SEGMENT OBJECTIVES l. Capture and radio-collar a target sample of adult female mule deer and 6 month-old fawns during late November through mid-December in a treatment unit and a control unit. 2. Capture a target sample of adult female mule deer in the treatment unit and the control unit to measure pregnancy rates, fetal rates, and body condition during late February to early March, and fit each adult female deer with a radio collar and vaginal implant transmitter. 3. Deliver the nutrition enhancement treatment to all deer occupying the treatment unit from early December through the end of April. 4. Capture and radio-collar a target sample of newborn fawns from treatment and control radio-collared does during June using the vaginal implant transmitters as a technique to determine the timing and location of birth. 5. Measure fetus survival, neonate survival, early winter fawn:doe ratios, overwinter fawn survival, and annual adult female survival based on radio-collared deer from the treatment and control units. INTRODUCTION Mule deer (Odocoileus hemionus) numbers apparently declined during the 1990's throughout much of the West, and have clearly decreased since the peak population levels documented in the 1940's-60's (Gill et al. 1999, Unsworth et al. 1999). Biologists and sportsmen alike have concerns as to what factors may be responsible for declining population trends. Although previous and current research indicates that multiple interacting factors are responsible, habitat and predation have received the focus of attention. A number of studies have evaluated whether predator control increases deer survival, yet results are highly variable (Connolly 1981, Ballard et al. 2001). Together, predator control studies with adequate rigor indicate that predation effects on mule deer are variable as a result of time-specific and site-specific factors. Studies which have demonstrated deer population responses to predator control treatments have failed to determine whether predation is ultimately more limiting than habitat. Numerous research studies have evaluated mule deer habitat quality, but virtually no studies have documented population responses to habitat improvements. In many areas where declining deer numbers are of concern, predation is common yet habitat quality appears to have declined. The question remains as to whether predation, habitat, or some other factor is more limiting to mule deer in these situations, and whether habitat quality �36 can be improved for the benefit of deer. It may also be that no single factor is any more or less important than another, and that a more comprehensive understanding of multi-factor interactions is paramount. We designed a field experiment to measure deer population responses to nutrition enhancement treatments, to further understand the causative factors underlying observed deer population dynamics. We are conducting the study on the Uncompahgre Plateau in southwest Colorado, where several predator species are present in abundant numbers: coyotes (Canis latrans), mountain lions (Felis concolor), and bears (Ursus americanus). In addition to predation, myriad diseases in combination proximately affect survival of the Uncompahgre deer population (Pojar 2000, B.E. Watkins, unpublished data). Predator numbers have not and will not be manipulated in any manner during the course of the study. All factors have been left constant with the exception of deer nutrition. Deer nutrition is being enhanced by providing supplemental feed to deer occupying a treatment area during the winter. If December fawn recruitment and/or overwinter fawn survival improve as a direct result of the nutrition enhancement treatment, then we can presume that deer nutrition is ultimately more limiting than predation or disease. The second phase of the field experiment, which has not yet been initiated, will incorporate habitat manipulation treatments. The treatments will consist of prescribed fire or mechanical techniques to set back succession of pinyon-juniper (Pinus edulis-Juniperus osteosperma) habitat in an effort to improve the vigor and quality of winter habitat for mule deer. Deer population responses will be measured in relation to the habitat manipulations in the same manner as the supplemental feed. Thus, the experiment allows us to determine whether nutritional quality of winter range habitat is ultimately more limiting than other factors in a late-seral pinyon-juniper/sagebrush (Artemisia spp.) landscape, and if so, whether habitat can be effectively improved for mule deer. The results will also advance our current understanding of multi-factor interactions, with direct implications for mule deer management. MATERIALS AND METHODS Experimental Approach Experimental Design and Study Area We non-randomly selected two areas within mule deer winter range on the Uncompahgre Plateau to create 2 experimental units (A-B) (Fig. 1). The following criteria were used to select experimental units: 1.) Deer densities (~50-80 deer/me): areas were selected where deer densities were sufficient to meet sample size requirements within the experimental unit, while simultaneously selecting areas that would require feeding less than ~500-600 animals during a normal winter 2.) Buffer zones: areas were selected such that experimental units would be separated by several miles of non-treatment area (buffers) to prevent deer from occupying more than one experimental unit 3.) Similarity: areas were selected that comprise relatively similar habitat complexes and deer densities that are representative of the overall area 4.) Elk populations: areas were selected to minimize the number of elk present during normal winters �37 Units A and B are receiving the nutrition enhancement treatment in a cross-over experimental design, and are being used to address P.N. Objective 1. Unit A served as the treatment unit, while Unit B served as the control, for the first 2 winters of research (2000 - 2002). Beginning November 2002, Unit B received the treatment while Unit A served as the control. Upon completion ofP.N. Objective 1, two additional winter range experimental units will be used to conduct phase 2 of the research, or P.N. Objective 2. Habitat in one unit will be manipulated to set back plant succession (treatment), while habitat in the other unit will remain unchanged (control) throughout the experiment. 2002-03 2003-04 Figure 1. Schematic representation of experimental units and nutrition enhancement treatment allocation. Units A and B are located in winter range habitat on the Uncompahgre Plateau in southwest Colorado. The nutrition enhancement cross-over design will encompass 4 years. The 2 experimental units (A and B) receiving the nutrition enhancement treatment are (Figs. 2 and 3): (1) Experimental unit A includes the Colona Tract of the Billy Creek State Wildlife Area and adjacent land, located approximately 13 km south of Montrose, CO adjacent to U.S. Hwy 550 South. The experimental unit is located within the Colona USGS 7.5 Minute Quadrangle, and roughly includes the polygon defined by the following Zone 13 UTM coordinates: (1) 254000 E, 4250200 N; (2) 252700 E, 4249400 N; (3) 254700 E, 4245600 N; and (4) 256200 E, 4246600 N. (2) Experimental unit B includes Shavano Valley and adjacent land extending west to the Dry Creek Rim. Shavano Valley is located approximately 13 km west of Montrose, CO. The experimental unit is located within the Dry Creek Basin and Montrose West Quadrangles (USGS 7.5 Minute), and roughly includes the polygon defined by the following Zone 13 UTM coordinates: (1) 238400 E, 4262600 N; (2) 232400 E, 4256700 N; (3) 235000 E, 4253600 N; and (4) 239500 E, 4258200 N. In late April and May, prior to fawning, deer from the winter range experimental units migrate to summer range. The summer range study area is defined by movements of the radio-collared deer, which encompass> 1000 mi2 covering the southern portion of the Uncompahgre Plateau and adjacent San Juan Mountains to the south and east (Fig. 2). The summer range study area extends north to the Dry Creek river drainage on the Uncompaghre Plateau, south to Mineral Creek near Silverton, CO, east to the Big Blue river drainage, and west to the San Miguel River canyon. However, a majority of the radio-collared deer summer on the Uncompahgre Plateau between Dry Creek to the north and Horsefly Peak to the south. Winter range elevations range from 1830 m (6000 ft) in Shavano Valley to 2318 m (7600 ft) adjacent to the Dry Creek Rim above Shavano Valley. Winter range habitat is dominated by pinyon-juniper with interspersed sagebrush adjacent to agricultural fields in the Shavano and Uncompahgre Valleys. Summer range elevations occupied by deer range from 1891 m (6200 ft) in the Uncompahgre Valley to 3538 m (11,600 ft) in Imogene Basin southwest of Ouray, CO. Summer range habitats are dominated by sprucefir (Picea spp.-Abies spp.), aspen (Populus tremuloides), ponderosa pine (Pinus ponderosa), Gambel oak (Quercus gambelii), and to a lesser extent, sagebrush and pinyon-juniper at lower elevations. �38 / .. .. ~. , " ,,:;::_ Gunnison County Winter Range Exp. Units Summer Ranze ·····~.f Montr~s'e, County ~..... t~' """""'" Figure 2. Location of Colona and Shavano (Units A and B) experimental units in Game Management Unit 62 on the Uncompahgre Plateau, southwest Colorado; and location of the summer range study area throughout the southern Uncompahgre Plateau and adjacent San Juan Mountains �39 Figure 3. Colona and Shavano experimental units (Units A and B), located in Game Management Unit 62 on the Uncompahgre Plateau, southwest Colorado. Polygons represent the nucleus of each experimental unit, which is where animals have been collared and the nutrition enhancement treatment delivered. �40 Response Variables The response variables are fetal and neonatal survival rates, early winter fawn:doe ratios, and overwinter fawn survival rates. The nutrition enhancement treatment is delivered to deer from December through April, fetus survival is assessed during June, neonate survival is measured from June to December, and fawn:doe ratios are measured during the following December and January (1 year after the treatment was initiated). Overwinter fawn survival is measured from December to June as a direct result of the current winter's treatment. We are measuring these response variables in each experimental unit (treatment and control) to determine whether enhanced winter nutrition of adult does increases subsequent newborn fawn production and survival, and whether enhanced winter' nutrition of 6-mo. old fawns directly increases overwinter fawn survival. Ultimately, these measurements provide an assessment of the effect of winter range habitat quality on yearling recruitment, and thus population productivity. We are also measuring overwinter and annual survival of adult does as a function of enhanced winter nutrition. Sample Size FetuslNeonate Survival: We were primarily interested in survival of newborn fawns from radio-collared does that occupy the 2 winter range experimental units. Fetus survival is also important, but difficult to measure. Fetus rates from a sample of radio-collared does can be measured in winter, but the fate of all fetuses cannot be determined the following June because oflogistical constraints. Fetus survival rates can only be measured from some unpredictable fraction of the radio-collared doe sample, making sample size calculations of limited use. Thus, our sample size calculations were based on quantifying neonate survival, not fetus survival. For neonate survival, a sample size of 40 neonates per experimental unit per year provides power of 0.81 to detect a difference of 0.15 in survival between 2 experimental units if survival among control fawns is 0.40. We assumed a control survival rate of 0.40 based on neonate survival rates measured recently for the Uncompahgre deer population (Pojar 2000) in combination with December fawn:doe ratios measured during the late 1980's and 1990's, when the Uncompahgre population declined (B. E. Watkins, unpublished data). Based on Bishop et al. (2002), we determined that 60 radio-collared does (30 treatment and 30 control) equipped with vaginal implant transmitters (VITs) would be necessary to capture a minimum of 80 newborn fawns. We also assumed that some fawns would be captured from other treatment and control radio-collared does not equipped with VITs. The 60 radio-collared does with VITs are also being used to evaluate fetus survival; however, logistical constraints limit the power of fetus survival comparisons among experimental units. Early winter fawn:doe ratios: We desired to detect an effect size, i.e., an increase in fawn:doe ratios in response to the treatments, in the range of 15 to 20 fawns per 100 does. These values were based on simple population models with overwinter fawn survival of 0.444, adult female survival of 0.853, and December fawn:doe ratios of 66 fawns per 100 does to obtain a stationary population (Unsworth et al. 1999). Based on surveys of the Uncompahgre deer population during the 1990's, the standard deviation of the fawn:doe ratio for groups with at least one adult female was 57, with a mean of 41. Using an expected standard deviation of 57, the standard error of the mean fawn:doe ratio for 40 radio-collared does is 57/(401/2) = 9.0, which is the expected standard deviation of measured fawn:doe ratios on each experimental unit. We assessed power using a two-sample t-test with a sample size of 4, representing the 4 years of the study where fawn:doe ratios are being measured in response to enhanced nutrition. Our power to detect an increase of 20 fawns per 100 does based on classification of 40 radio-collared doe groups in each experimental unit is about 0.87. A sample size of 40 fawns per experimental unit per year provides a power of 0.81 to detect a difference of 0.15 in survival between 2 experimental units if survival on the control unit is 0.40. We expected to �41 see an increase in fawn survival (effect size) ofapproxirnately 0.l5, because this was the difference measured in the density reduction experiment conducted by White and Bartmann (1998). Adult and 6-month Old Fawn Capture During November and December, adult does and 6-month old fawns were captured using baited drop nets (Ramsey 1968, Schmidt et al. 1978) and helicopter net guns (Barrett et al. 1982, van Reenen 1982). Drop nets were baited with certified weed-free alfalfa hay and apple pulp. Drop nets were used as the principle capture technique for a 3-4 week capture period; helicopter net-gunning was then used at the end of the drop-net capture to secure the remainder of deer needed to meet our target sample sizes. All deer were hobbled and blind-folded after being captured. Deer captured via drop nets were carried away from the net to an adjacent handling site using stretchers. Deer were fitted with leather radio collars equipped with mortality sensors, which cause an increase in pulse rate after remaining motionless for 4 hours. Permanent collars were placed on adult females, while temporary collars were placed on fawns. To make collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars zo months post-capture. A rectangular piece of flexible plastic (Ritchey" neck band material) engraved with a unique identifier was stitched to the side of each collar. The unique identifier consisted of2 symbols for adult females, and 1 symbol on 2 different colors of plastic for fawns. The identifiers were necessary to visually identify deer from the ground. This allowed us to effectively document use of the treatment, measure fawn:doe ratios from the ground, and assess experimental unit population size via mark-resight estimators. We recorded the weight, hind foot length and chest girth of each deer, and collected blood samples to evaluate disease prevalence. During late February and early March, an additional 30 adult female deer were captured in each experimental unit by net-gunning. Captured deer were ferried by the helicopter to a central processing location, where deer were carried by stretchers to a tent for handling. For each captured deer, we used ultrasonography to measure pregnancy status, fetal rate, and body condition. Only pregnant does were retained and radio-collared. We then inserted a vaginal implant transmitter (VIT) in each doe as a technique for locating the timing and location of her birth site the following June. We also recorded the weight, hind foot length and chest girth of each deer, and collected blood samples to evaluate disease prevalence. Body Condition and Reproductive Status We estimated body fat of treatment and control adult does during mid-late winter using an Aloka 210 (Aloka, Inc., Wallinford, Conn.) portable ultrasound unit with a 5 MHz linear transducer. We measured maximum subcutaneous fat thickness on the rump (MAXF AT) following the methodology of Stephenson et al. (1998,2002). We also measured thickness of the longissimus dorsi muscle via ultrasound (Cook et al. 2001, Stephenson et al. 2002). A small area of hair was shaved to ensure contact between the transducer and the skin. Vegetable oil was applied to the shaved area for conduction purposes and fat/muscle thickness was measured using electronic calipers. We coupled the ultrasound measurements with body condition scores (BCS) obtained from palpation of the ribs, withers, and rump (Cook 2000). MAXF AT and rump BCS measurements were combined into a condition index used to estimate percent body fat (Cook and Cook 2002): % Fat = -6.6387617 + 7.4271417x - 1.11579443x2 + 0.07733803x3 where x = rLIVINDEX = (MAXFAT - 0.15) + rump BCS (ifMAXFAT < 0.15, then rLIVINDEX = rump BCS). The rLIVINDEX and body fat regression was initially developed and validated for elk by Cook et al. (2001), and then modified by incorporating a validation ofMAXFAT for mule deer performed by Stephenson et al. (2002). �42 During mid-late winter 2003, we also evaluated differences in serum thyroid hormone concentrations between treatment and control adult does. Specifically, we measured total thyroxine (T4), free T4 (FT4), total tri-iodothyronine (T3), and free T3 (FT3) following the methodologies of Watkins et al. (1983, 1991). Blood samples were collected at the time of capture, and serum hormone analyses were performed by the Michigan State University Animal Health Diagnostic Laboratory (East Lansing, Michigan). We compared serum thyroid hormone concentrations between treatment and control adult does, and also compared hormone levels to body fat estimates derived from the ultrasonography. We quantified reproductive status (Stephenson et al. 1995, Pojar 2000) with ultrasound via transabdominal scanning using a 3 MHz linear transducer. We searched for fetuses by scanning a portion of the abdomen that was shaved caudal to the last rib and left of the midline. We systematically searched each uterine hom to identify fetal numbers ranging from 0 to 3. Whenever possible, we measured eye diameter of each fetus to approximately estimate fetal age and parturition date. Vaginal Implant Transmitters (VITs) We used VITs manufactured by Advanced Telemetry Systems, Inc. (Isanti, MN). The VIT was 76 mm long, excluding antenna length, and had 2 plastic wings with a width of 57 mm when fully spread apart. The plastic wings were used to retain the transmitter in the vagina until parturition. The VIT weighed 15 grams and contained a 10-28 lithium battery programmed to a 12-hour on/off cycle. The diameter of the transmitter/battery was 14 mm, and was encased in an impermeable, water-proof, electrical resin. The transmitter contained an embedded heat-sensor which dictated the frequency pulse rate. When the heat sensor dropped below 90°F, synonymous with transmitter expulsion from the deer, the pulse rate changed from 40 PPM to 80 PPM. VIT batteries were programmed to be active from 0430 to 1630 hrs prior to daylight savings, and thus were active from 0530 to 1730 hrs after daylight savings and during the fawning period. The VIT was inserted into deer using a vaginoscope (Jorgensen Laboratories, Inc., Loveland, CO) and alligator forceps. The vaginoscope was 6" long with a 5/8" internal diameter and had a machined end (smooth surface) to minimize trauma when inserted into the vagina. A discreet mark was placed on the applicator showing the appropriate distance it should be inserted into the deer. The length of a typical mule deer vaginal tract was obtained by taking measurements from road-killed deer and/or other fresh deer carcasses obtained in the study area. Prior to use in the field, VITs were sterilized using a Chlorhexidine solution, air-dried, and sealed in a 3" x 8" sterilization pouch. Sterilization containers with Chlorhexidine solution were used on site during capture to sterilize the vaginoscope and alligator forceps between each use. A new pair of nitrile surgical gloves was used to handle the vaginoscope and VIT for each deer. To insert a VIT, the plastic wings were folded together and placed into the end of the vaginoscope. We then liberally applied sterile KY Jelly to the scope and inserted it into the deer's vagina to the point where the mark on the applicator was reached. The alligator forceps, which extended through the vaginoscope to hold the VIT, was held firmly in place while the scope was pulled out from the vagina .. This procedure pushed the VIT out of the scope into the vagina, and the plastic wings spread apart to hold the transmitter in place. The transmitter antenna was typically flush with the vulva, but on occasion extended up to 1 cm beyond the vulva. The tip of the antenna was encapsulated in a wax bead to protect the deer. Neonate Fawn Capture During June we relocated each of the radio-collared does having a VIT each morning using aerial and ground telemetry. Flights began at 0530 hr and were usually completed by 1000 - 1100 hrs. The early flights were crucial for detecting fast signals because shed VITs could exceed 90 OFby mid-day if shed in the open, which caused them to switch back to a slow ("pre-birth") pulse. When a fast ("postpartum") �43 pulse rate was detected, we located the VIT from the ground to determine whether it was shed at the birth site. If the transmitter was located at the birth site, we identified whether any fawn(s) were stillborn. If the fawn(s) were no longer present at the birth site, or could not be found in the vicinity of the birth site, we located the radio-collared doe and searched for fawns at her location. All personnel involved wore surgical gloves to help minimize human scent when handling fawns. For each doe, we attempted to locate each of her fawns and document whether any fawns were stillborn. We attempted to account for each doe's fetuses in order to quantify in utero fetal survival from February to birth. We placed a dropoff radio-collar on each live fawn; radio collars were constructed with elastic neck-band material to facilitate expansion. Hole-punched, leather tabs extended from the end of the elastic and from the transmitter for attachment purposes. Collars were made temporary by cutting the leather tab extending from the elastic and reattaching the leather with latex tubing, which caused the collars to shed from the animal >6 months post-capture. For each fawn, mass and hind foot length were recorded, and a nasal swab sample was collected to screen for Bovine Viral Diarrhea. We then recorded basic vegetation characteristics of the birth site and promptly exited the site. We also routinely located treatment and control radio-collared does not having VITs and attempted to capture their fawns to help achieve our targeted sample size. Each of these does had been previously captured during the research, and were present on either the treatment or control experimental unit during winter. Measurement of Survival Rates and Fawn:Doe Ratios We measured survival rates by radio-monitoring collared deer from the ground and air to determine fate (live/mortality). We also attempted to determine the cause of each mortality, with a primary goal of distinguishing between predation and non-predation mortality causes. Deer were radio-monitored from the ground on a daily basis throughout the year and from the air on approximately a biweekly basis. We were able to detect signals from nearly all radio-collared deer each day during winter, which typically allowed us to arrive at mortality sites within 24 hours of the mortality event. During summer and migration periods, deer were distributed widely and thus were more difficult to radio-monitor. All radiocollared neonates were checked daily throughout the summer and fall, whereas some adult and yearling deer could not be ground-monitored on a routine basis. In result, we typically located neonate mortalities within 24 hours of death, but some adult deer mortalities were not detected for several days, or on rare occasion, for one or more weeks. Fresh, intact neonate carcasses were collected and submitted to the Colorado Division of Wildlife's Wildlife Health Laboratory or the Colorado State University Diagnostic Laboratory for necropsy and tissue analyses. Fresh, intact adult and 6-month old fawn carcasses were also submitted for laboratory necropsy when feasible. Field necropsies were performed on all other deer mortalities, and when appropriate, tissue samples were collected and submitted for analysis. Each winter we used the radio-collared does to measure fawn:doe ratios in each experimental unit. The resulting fawn:doe ratio is a measurement of the previous year's treatment effect. We measured fawn:doe ratios using 2 techniques: (1) We located the sample of radio-collared does in each experimental unit from a fixed-wing airplane, and used the set of locations to define boundaries for the experimental unit. Shortly after (i.e. 1-2 days), we used a helicopter to systematically fly the defined unit and classify all deer groups encountered. For each group, we documented whether a radio-collared doe was present. (2) We located each radio-collared doe by radio telemetry from the ground. The group of deer with the collared doe was counted and classified by age and sex. Both methods were employed to gather as much information as possible to determine whether there was a treatment effect. The "true" value cannot be measured perfectly because of the inherent biases and potential sources of error associated with each technique. Thus, by employing both techniques, we had a greater chance of fully understanding whether the treatment caused an effect. �44 Treatment Delivery Deer nutrition was enhanced in the treatment area by providing a safe, pelleted supplemental feed. The supplemental feed was developed through extensive testing with both captive and wild deer (Baker and Hobbs 1985, Baker et al. 1998), and has been safely used in both applied research and management projects. Pellets were distributed daily using 4wd pickup trucks and ATVs on primitive roads throughout the experimental unit to provide a food source for the entire deer population in the treatment unit. Each 501b. bag of pellets was carried :::;200mfrom the truckiATV and distributed by hand in approximately 2030 small piles offeed in a linear fashion. Numerous bags were distributed in successive order allowing us to create linear lines of feed that spanned most of the treatment area, which prevented animals from concentrating in any single location. This feeding technique also prevented dominant animals from restricting access to the food supply because of the large area over which pellets were distributed. We supplied pellets ad libitum such that a small residual remained when the next day's ration was provided. Collared deer were closely monitored to ensure that treatment deer remained in the experimental unit and actually consumed the feed, and to make sure that non-treatment deer remained in the control unit, which they did. The few treatment adult does that moved away from the treatment unit were withdrawn from the sample for purposes of measuring treatment effects. However, to avoid any biases, all 6-month old fawns captured in the treatment unit were included in survival analyses regardless of whether they accessed the supplement or not. This was because some fawns died shortly after capture (e.g. 2-3 weeks), before we could document whether they had access to the feed. Also, very few fawns that survived more than 2-3 weeks moved away from the treatment unit. The pelleted ration was commercially produced in the form of 2x 1xO.5-cm wafers (Baker and Hobbs 1985). Feed constituents (i.e. digestibility, protein, gross energy etc.) vastly exceeded those of typical winter range deer diets; exact constituent values are provided by Baker et al. (1998). When provided ad libitum, the feed should have allowed deer to meet or exceed nutritional requirements for growth and maintenance (Ullrey et al. 1967, Verme and Ullrey 1972, Thompson et al. 1973, Smith et al. 1975, Baker et al. 1979, Holter et al. 1979). The basis for feeding such high quality pellets was to ensure that the treatment (enhanced nutrition) was effectively delivered to the deer. Our intent was not to determine the exact level of nutrition necessary to increase fawn recruitment, but rather to determine if nutrition is a limiting factor to recruitment. If nutrition is in fact limiting, we will rely on habitat manipulation treatments to evaluate what exactly can be done via management to increase fawn survival and recruitment. Statistical Methods A preliminary fawn:doe ratio analysis was completed using PROC MIXED in SAS (SAS Institute 1997). We used a reduced model with experimental unit as the independent variable; we considered experimental unit as a fixed effect and radio-collared does within an experimental unit as random effects. Survival rates were calculated using a Kaplan-Meier survival analysis (Kaplan and Meier 1958, Pollock et al. 1989), and contrasted among experimental units and sexes using a chi-square analysis. For neonate survival analyses, we used a common entry date because a staggered entry would have biased survival rates low due to early mortalities that occurred before most of the sample was captured. We modeled overwinter fawn survival with a logistic regression model using PROC LOGISTIC in SAS (SAS Institute 1989a); model selection was performed using Akaike's Information Criterion (AlC) (Burnham and Anderson 1998). Survival was modeled as a function of the nutrition enhancement treatment, sex, year, and capture mass. We used a general linear model in PROC GLM in SAS (SAS Institute 1989b) to test for differences in estimated percent body fat between treatment and control adult does and a multivariate model to test for differences in T4, FT4, T3, and FT3 thryoid hormones between treatment and control does. We then used PROG REG (SAS Institute 1989b) to evaluate the relationship between estimated �45 percent body fat and serum thyroid hormone concentrations. We analyzed fetus survival directly with a binomial survival rate for the subset of fetuses with known fates. We also indirectly analyzed fetus survival by comparing the February fetus rate with the number oflive newborn fawns/doe observed in June using a change-in-ratio estimator (White et al. 1996). Other results in this report are presented as data summaries incorporating means and standard errors, or in some cases, raw data values. These results are incomplete and preliminary in nature, and should be treated as such. RESULTS AND DISCUSSION Deer Capture During November and December 2000-2002, we captured and radio-collared 122 adult female mule deer evenly distributed among the treatment and control units. We also captured and radio-collared 1606month old fawns during November and December 2001-2002 (40 fawns/unit/year). Due to budgeting constraints, we were unable to radio-collar 6-month old fawns during 2000. We captured an additional 94 adult females during late February and early March 2002-2003 and equipped them with radio collars and VITs. During June 2002-2003, we captured and radio-collared 157 newborn fawns from radio-collared adult females. Thus, the following results are based upon radio-monitoring of 533 individual mule deer evenly distributed among treatment and control units during November 2000-June 2003. Treatment Delivery 2000-01 From December 15,2000, through April 19, 2001, we distributed 88 tons of the pelleted ration. For most of the winter and spring, on average, we distributed 0.85 tons of feed each day throughout 22 feeding sites across the 2.3 mi2 treatment unit. Deer were fed ad libitum because there was always residual feed remaining the next day during the feeding routine. Each sack was distributed in approximately 20-30 distinct, small piles, resulting in > 1000 small piles of feed throughout the treatment unit. This effort allowed deer to effectively access the feed in small groups, and no aggression was ever observed among deer seeking access to the feed. By distributing the feed in this manner, we were able to avoid the negative aspects associated with large-scale feeding operations. Deer adapted to the pelleted supplement right away and utilized it extensively throughout the winter. We continually monitored deer use of the feed from ground observation points, where we obtained 440 visual observations of radio-collared does consuming the feed. These observations, coupled with daily radio-monitoring and periodic aerial relocations, indicate 32 of the 37 radio-collared treatment does spent the entire winter and spring within the boundaries of the treatment unit and received the supplement on a daily basis. Mark-resight population estimates from March helicopter (489 deer, SE = 62) and ground (494 deer, SE = 81) surveys, coupled with feed consumption, indicate we fed roughly 450 to 500 deer during most of the winter and spring. Feed consumption declined coincident with spring green-up, although deer continued to use the feed through mid-late April, at which point they began migrating to summer range. We also fed approximately 25 to 30 elk, but the elk did not affect deer access to the feed. Deer in the control experimental unit did not receive feed or any other treatment. Based on helicopter mark-resight surveys, . the deer density in the treatment unit in December was 120 deer/me (SE = 9), but increased shortly after and was 213 deer/mi' (SE = 27) in March. Deer densities in the control unit changed little from 83 deer/mi ' (SE = 12) in December to 101 deer/mi.' (SE = 14) in March. �46 2001-02 From December 15,2001, through April 25, 2002, we distributed 194 tons of the supplement throughout the treatment unit. For most of the winter and spring, we distributed 2.0-2.1 tons of feed each day. The dramatic increase in supplement distribution from the previous year occurred because a large number of elk descended into the Uncompahgre Valley during mid-late fall/early winter. Elk arrived in unusually large numbers throughout much of the valley prior to the onset of treatment delivery. Once feeding was initiated, approximately 300-500 elk adapted to the feed and remained in or around the 2.3 me treatment unit throughout most of the winter. Given myriad logistical and budgetary constraints, 2.1 tons was the maximum amount of feed we could routinely deliver on a daily basis. Feed was not delivered ad libitum to all deer and elk in the treatment unit throughout the winter because residual feed was rarely observed during the next day's distribution. However, daily field observations indicated most deer approached ad libitum consumption of the supplement. In contrast to the previous winter, deer were waiting for the daily supplement to arrive each morning. Deer then consumed the supplement immediately after it was distributed. Elk were rarely observed utilizing the feed until late morning or afternoon, and elk continued to forage in fields below the treatment unit, whereas deer did not. We observed numerous radio-collared deer consuming the pelleted supplement each day; not all of these observations were recorded because of time constraints with distributing the feed. Given this time limitation, we still recorded 818 observations of radio-collared deer consuming the supplemental feed (497 collared doe observations and 321 collared fawn observations). Most days, > 100 and sometimes 200-300 deer were observed utilizing the pellets during the course of distributing the supplement. These observations rarely included elk; thus, deer-elk competition was minimized because oftemporal differences in feeding, and deer clearly had first access to the feed. 2002-03 Beginning December 2002, we switched the treatment and control units consistent with the cross-over experimental design. From December 15,2002, through April 30, 2003, we distributed 97 tons of the supplement throughout the new treatment unit, which had served as the control unit the previous 2 years. The supplement was distributed daily throughout 29 sites over a larger area (-7 mi2) than the first 2 years of research because of the greater size of the experimental unit and broader distribution of radio-collared deer. Residual feed was always present throughout the winter, thus deer were fed ad libitum. Only small groups of elk periodically accessed the supplement, and did not affect deer access. We obtained 286 observations of radio-collared deer consuming the supplement, which were difficult to obtain because the supplement was spread out over a large area and only a single feed site could be observed at any given moment. We also used daily ground radio-monitoring and periodic aerial relocations to document deer access to the supplement. Body Condition Estimated percent body fat of adult does during late February and early March of 2002 and 2003 was significantly higher for treatment deer than control deer (Fl, 90 = 108.21, P < 0.001). Over both years combined, mean predicted body fat was 10.4% (SE = 0.48) for treatment adult does and 4.0% (SE = 0.36) for control does. The interaction of experimental unit x year for predicted body fat was also significant (Fl, 90 = 21.79, P < 0.001). This interaction occurred because the difference in body fat between treatment and control deer was greater during 2003 than during 2002. During 2002, mean predicted body fat was 8.2% (SE = 0.92) for treatment adult does and 5.0% (SE = 0.71) for control does, whereas during 2003, mean predicted body fat was 11.7% (SE = 0.35) for treatment does and 3.4% (SE = 0.35) for control does. The body fat estimates reported here should accurately reflect deer, but may be further refined in the �47 future as additional research provides more data on the relationship between body condition indices and estimated percent body fat. In 2003, serum thyroid hormone concentrations were higher in treatment does than control does (F4•52 = 32.59, P < 0.001). T4 was the most important thyroid hormone in describing the single canonical variable (l.78*T4 - 0.04*T3 + 0.20*FT4 - 0.27*FT3). Not surprisingly, there was a high partial correlation between T4 and FT4 (r = 0.77, P < 0.001) and between T3 and FT3 (r = 0.73, P < 0.001), which has been documented previously (Watkins et al. 1983). When treated as 4 separate ANOVAs, T4 (Fl. 55 = 127.45, P < 0.001), FT4 (F1,55= 8l.72, P < 0.001), and T3 (F1,55= 5.39, P = 0.024) were significantly higher in treatment does than control does, whereas FT3 levels were less different among treatment and control deer (Fl. 55 = 2.59, P = 0.113). Given these results, we evaluated the relationship between T4 concentrations and estimated percent body fat (derived form ultrasound and BCS indices) using a simple linear regression model (% Fat = -5.114 + O.l06*T4, r2 = 0.59, P < 0.001). Similar correlations between T4 and actual percent body fat during mid-late winter have been previously documented for white-tailed deer and elk (Watkins et al. 1991, Cook et al. 2001). Fetus Survival and Pregnancy/Fetus Rates We began measuring fetus survival in 2002 as part of our effort to capture and radio-collar newborn fawns born from radio-collared does. Similar numbers of stillborns were observed between treatment and control does during both 2002 and 2003, so all fetus survival analyses reported here represent pooled estimates. In February-March 2002,36 of38 adult does captured were pregnant, thus the pregnancy rate was 0.95 (SE = 0.036). We measured an average of l.80 fetuses/doe (SE = 0.10, n = 36), which included 1.77 fetuses/doe (SE = 0.14, n = 18) in the treatment unit and 1.83 fetuses/doe (SE = 0.15, n = 18) in the control unit. During June 2002, we determined the fate of all fetuses (live or stillborn) from only 14 of the 36 VIT does, largely because ofa high VIT battery failure rate. The survival rate of fetuses (n = 22) from these 14 does was 0.86 (SE = 0.073). We also assessed fetus survival using a change-in-ratio estimator between the fetal rate measured in February-March and the observed number of live fawns/doe postpartum in June. In June 2002, considering all does (n = 43) that we located any fawn from, whether live or stillborn, we observed 1.42 (SE = 0.11) live fawns/doe postpartum. This rate should represent a conservative estimate of live fawns/doe postpartum because we inevitably failed to locate all live fawns from each doe. In other words, this estimate would treat any unaccounted fetuses (from the February measurement) as if they were stillborns. For radio-collared does that did not have VITs, and thus we did not have a winter fetus rate measurement, singletons would infer that either the deer only had 1 fetus, or that the other fetus died. It is likely that some of these singletons had a twin that we did not locate. This equates to a conservative fetus survival rate estimate of 0.79 (SE = 0.18). In February-March 2003, 58 of 63 adult does captured were pregnant, resulting in a pregnancy rate of 0.92 (SE = 0.034). Critical personnel and equipment for measuring fetus rates were not continuously available due to capture delays associated with helicopter mechanical problems. Some of the deer fetus counts were performed by inexperienced observers without optimum ultrasound equipment. VITs worked very well, though, allowing us to determine fetus numbers at parturition for many of the deer. Thus, we determined winter fetus rates by using the greatest fetus count for each individual deer, whether obtained using ultrasound during February-March or by locating newborn fawns and stillborns at birthsites during June. We were unable to determine a fetus count for 8 treatment deer because only pregnancy was established with ultrasound and no birthsite assessments were possible in June. These 8 deer were removed from the fetus rate estimates. Of the 50 deer where a fetus count was obtained, 5 were yearlings (2 treatment yearlings, 3 control yearlings). We measured l.74 fetuses/doe (SE = 0.069, n = 50) overall including yearlings, and l.82 fetuses/doe (SE = 0.066, n = 45) excluding yearlings. Fetus rates with yearlings included were 1.77 fetuses/doe (SE = 0.091, n = 22) in the treatment unit and 1.70 �48 fetuses/doe (SE = 0.10, n = 28) in the control unit. During June 2003, we determined the fate of all fetuses (live or stillborn) from 33 of the 58 VIT does; the good success was based on VITs commonly being shed at birthsites. The survival rate of fetuses (n = 58) from these 33 does was 0.97 (SE == 0.024). In June 2003, incorporating all does (n = 71) that we located any fawn from, whether live or stillborn, we observed 1.49 (SE = 0.072) live fawns/doe postpartum. Using the change-in-ratio estimator described above, this results in an overall conservative fetus survival rate estimate of 0.86 (SE = 0.15). Neonatal Survival/Fawn: Doe Ratios 2001 In December 2000, at the beginning of the study and prior to the first year's treatment delivery, fawn:doe ratios were similar in the 2 experimental units. Pre-treatment fawn:doe ratios were 52.6 fawns: 100 does (SE = 5.3) in the treatment unit, and 51.6 fawns: 100 does (SE = 5.0) in the control unit. In late December 2001 and early January 2002, following the first year's treatment, we conducted 2 age classification helicopter surveys in the treatment and control units. On 12/23/01, we observed 52.8 fawns: 100 does (SE == 6.7) in the treatment unit, and 36.7 fawns: 100 does (SE == 3.8) in the control unit. On 1/8/02, we observed 54.7 fawns: 100 does (SE = 6.6) in the treatment unit, and 50.5 fawns: 100 does (SE = 6.0) in the control unit. During December 2001 - February 2002, we obtained fawn:doe ratio estimates from ground observations of radio-collared deer groups for both treatment and control deer. This survey resulted in 61.2 fawns: 100 does (SE = 7.8) in the treatment unit, and 74.5 fawns: 100 does (SE = 8.5) in the control unit, although the result was not statistically significant (t74 = 1.16, P = 0.249). The fawn:doe ratio results are conflicting, and clearly do not provide evidence that there was any treatment effect. In short, we concluded that the nutrition enhancement treatment did not cause an increase in neonatal production and survival during 2001. However, our results, in conjunction with a December estimate of 64 fawns: 100 does for the entire Uncompahgre deer population (B.E. Watkins, unpublished), indicate fawn production and survival was good during 2001. The observed fawn:doe ratios coupled with overwinter fawn survival and annual adult survival rates indicate the deer population was increasing. Considering the past 1-2 decades, this was an atypically good year for the Uncompahgre deer population. It would appear that whatever set of environmental conditions have led to a declining deer population were not present during 2001 in the same manner as in the past. Our main interest lies in observing the effect of the treatment on the deer population in a year where fawn:doe ratios are lower for the population as a whole, similar to what they have been much of the past 15 years. 2002 During June - December 2002, following the second year's treatment, we measured neonate survival directly using radio-collared fawns; however, sample sizes were based on a technique assessment ofVITs and were relatively small for contrasting treatment and control survival of neonates (Bishop et al. 2002). Treatment fawn survival was 0.613 (SE = 0.115, n == 29) and control fawn survival was 0.511 (SE == 0.108, n = 25). In late December 2002 and early January 2003, we once again conducted 2 age classification helicopter surveys in the treatment and control units. On 12/31/02, we observed 9l.9 fawns: 100 does (SE = 8.4) in the treatment unit, and 52.2 fawns: 100 does (SE == 6.9) in the control unit. On 1/21/03, we observed 52.6 fawns: 100 does (SE = 6.4) in the treatment unit, and 36.8 fawns: 100 does (SE = 3.9) in the control unit. The combined helicopter survey data indicated 68.1 fawns: 100 does (SE == 5.6) in the treatment unit and 42.8 fawns: 100 does (SE = 3.5) in the control unit. Oppositely, fawn:doe ratio estimates from ground classifications of doe groups during December 2002 - February 2003 were 47.7 fawns: 100 does (SE = 6.3) in the treatment unit, and 63.4 fawns: 100 does (SE == 7.5) in the control unit (t108 = l.61, P = 0.110). As in 2001, fawn:doe ratio results were conflicting. Helicopter survey data �49 varied between 2 different flights, but consistently indicated a treatment effect. Ground classification data did not indicate a treatment effect. Also, survival data combined with age ratio data indicate neonate production and survival was reasonably favorable during 2002, and not indicative of the low fawn recruitment observed during the late 1980's and 1990's. Our results from 2001 and 2002 point out the inherent difficulties and biases associated with precisely measuring fawn:doe ratios, particularly in this research study. Ratios obtained from helicopter surveys were based on 2 short-duration flights/unit/year over spatially small units. Helicopter surveys were complicated by high deer densities in heavy cover, making both deer detection and fawn:doe classifications a considerable challenge. There is a variety of potential biases that may have affected the helicopter surveys, including differential sightability of does and fawns, double classification of some deer, and incorrectly classifying yearling bucks with small antlers. Ground fawn:doe ratio observations of radio-collared doe groups were made using spotting scopes and field glasses, where we commonly studied the deer for some time. Incorrect classifications during these surveys were likely minimal. For example, small-antlered yearling bucks (e.g. 3 - 6" spikes) were detected from the ground, whereas they were undoubtedly missed on occasion during helicopter surveys. We also obtained repeated observations for some of the radio-collared doe groups from the ground. The main potential bias affecting ground fawn:doe classifications was how observations were made. Many of the ground classifications in the Shavano Valley experimental unit were made by radio-tracking does during the day. On the other hand, a majority of ground classifications in the Colona experimental unit were based on observing deer groups as they entered openings to feed during the late afternoon. Given the inherent difficulties of measuring fawn:doe ratios in the 2 experimental units, and the lack of a clear indication as to the effectiveness of the treatment, we intensified efforts in 2003 to directly measure survival of neonate fawns born from treatment and control radio-collared does. At the completion of the research, we will test whether enhanced winter nutrition of adult does improved newborn fawn survival based on a three-year model of radio-collared neonate survival data. We will continue to measure early winter fawn:doe ratios, but the data will be used cautiously to make inferences regarding treatment effects. 2003 During June 2003, we captured and radio-collared 103 newborn fawns born from treatment and control radio-collared does (55 treatment fawns, 48 control fawns). The VITs worked well; we captured fawns from 41 of the 54 does fitted with VITs. As oflate September 2003, treatment fawn survival was 0.745 (SE = 0.059) and control fawn survival was 0.614 (SE = 0.073). Neonate Mortality Causes During 2002, 11 of the 29 treatment fawns died from the following causes: 3 - coyote predation, 2 - bear predation, 1 - felid predation, 1 - predation where the predator was undetermined, 1 - disease/ malnutrition, 1 - abandonment, 1 - road-kill, and 1 - trauma/injury. Twelve of the 25 control fawns died: 6 - malnutrition/disease, 3 - coyote predation, 1 - felid predation, 1 - bear predation, and 1 predation mortality where the predator was undetermined. Thus, 13% of all radio-collared fawns died from malnutrition, 11% from coyote predation, 6% from bear predation, 4% from felid predation, 4% from predation (unknown predator), and 6% from miscellaneous causes. Currently (June - September 2003), 14 of the 55 treatment fawns have died from the following causes: 6 - disease/malnutrition/starvation, 4 - coyote predation, 3 - predation (unknown predator), and 1 - felid predation. Over the same time period, 18 of the 48 control fawns have died: 8 - coyote predation, 4 - disease/malnutrition/starvation, 3felid predation, 1 - bear predation, and 2 - unknown. Thus, as of the end of September during 2003, 12% �50 of all radio-collared fawns have died from coyote predation, 10% from disease/malnutrition/starvation, 4% from felid predation, 3% from predation (unknown predator), 1% from bear predation, and 2% from unknown causes. Overwinter Fawn Survival and Mortality Causes During winter 2001-02 (Dec 1,2001- May 31, 2002), the survival rate of fawns was significantly greater (X21 = 13.216, P < 0.001) in the treatment unit (S(t) = 0.865, SE = 0.056) than in the control unit (S(t) = 0.510, SE = 0.080). Again in 2002-03 (Dec 1, 2002 - May 31, 2003), the overwinter survival rate of fawns was significantly greater (X21 = 5.734, P = 0.017) in the treatment unit (S(t) = 0.900, SE = 0.047) than in the control unit (S(t) = 0.691, SE = 0.074) (Fig. 4). The treatment unit during winter 2001-02 became the control unit during winter 2002-03, and vice versa. Thus, the overwinter survival treatment effect was replicated across each experimental unit. Combining both years of data, the best model of overwinter fawn survival (AICc = 148.63) included treatment (X\ = 14.71, P < 0.001), early winter fawn mass (X\ = 16.80, P < 0.001), year (X21 = 3.53, P = 0.060), and sex (X\ = 1.99, P = 0.158). The AlC model selection analysis emphasizes the importance of both the treatment effect as well as early winter mass of fawns, because any models without treatment or fawn mass were very poor (Table 1). Survival of fawns receiving the nutrition enhancement treatment was 0.31 higher than survival of control fawns during two mild to average winters, and surviving fawns averaged 2.9 kg heavier than fawns that died. Early winter mass was not different among experimental units (FI = 0.35, P = 0.558), thus the effect of the treatment was not confounded with fawn mass. Fawn mass was similar between winters as well (FI = 0.45, P = 0.502). The importance of early winter fawn mass as a predictor of overwinter survival has been documented previously (White et al. 1987, Bishop 1998, White and Bartmann 1998, Unsworth et al. 1999). In summary, the nutrition enhancement treatment improved overwinter fawn survival and thus yearling recruitment, and heavier fawns in each experimental unit had higher survival probabilities. lUI· . J O·••.•. -r: , Oil ~ ·lli:-: Treatment (2001-02)J' --Control 0.5 _ .. ' ·~w . (200]··02) 'Trent:.rmmt. (2002··03) Con trot (2002-(3) -~ ..---•............... ·m ••.·••·.·.·_ -- ---- -•.•.- . -..-....• OA+----r----r---~---,----~---r---,----~---r--~----~--~ U!l nil{:i. l;2.i:H, .VJ.~ l"!.(1 Zil.4· ·3!l $11>1 ~/31 4/1..<;' 4..~ $1~ .5/:50 Figure 4. Overwinter fawn survival (Dec 1 - May 31) in a nutrition enhancement treatment unit (S(t) = 0.865, SE = 0.056, 2001-02; Set) = 0.900, SE = 0.047, 2002-03) and a control unit (S(t) = 0.510, SE = 0.080,2001-02; Set) = 0.691, SE = 0.074,2002-03), Uncompahgre Plateau, southwest Colorado. �51 Model Name -2 Log Likelih od # Param eters (K) Ale Alec I:!. Ale c Treatment + Sex + Year + Mass 143.231 5 153.231 148.626 0 Treatment + Year + Mass Treatment + Sex + Year + Trt*Year + Mass Treatment + Sex + Mass 145.286 4 153.286 149.548 0.92 143.059 6 155.059 149.615 0.99 146.898 4 154.898 151.159 2.53 Treatment + Mass 148.957 3 154.957 152.113 3.49 Sex + Year + Mass 160.345 4 168.345 164.606 15.98 Treatment 165.845 2 169.845 167.922 19.30 Sex + Year 178.195 3 184.195 181.351 32.73 Table 1. Model selection results for a logistic regression analysis of overwinter mule deer fawn survival in southwest Colorado. Enhanced nutrition (Treatment) and early winter fawn mass were the critical predictors of survival. Model selection was performed using Akaike's Information Criterion (AlC). During winter 2001-02, five fawns in the treatment unit died: 2 from malnutrition/sickness and 3 from disease. Of the 2 fawn mortalities caused by malnutrition/sickness, 1 was a result of basic malnutrition and occurred on December 31, 2001, shortly after the treatment was initiated. The other fawn died early as well and had a combination of heavy parasite loads, scours, and general poor condition. Each of the 3 fawns that died from disease had adequate fat stores. At least one of these fawns died as a result of pneumonia. In the control unit, 19 fawns died during the winter: 5 from malnutrition, 6 from mountain lionlbobcat predation, 4 from coyote/canine predation, 3 unknown predation mortalities, and 1 unknown. A majority of the fawns killed by predators had virtually no femur marrow fat remaining, indicating the predation was likely compensatory in nature. During winter 2002-03, where the initial control unit became the treatment following the cross-over, four fawns died in the treatment unit: 3 from coyote predation and 1 unknown mortality. In the control unit, 12 fawns died during the winter: 4 from coyote predation, 2 from malnutrition, 1 from mountain lion predation, 1 was road-killed, and 4 causes were unknown. As in the previous winter, these fawns had virtually no femur marrow fat remaining, indicating very poor condition. Adult Female Survival and Causes of Mortality During winter 2000-01 (Dec 1, 2000 - May 31, 2001), the adult doe survival rate in the treatment unit (S(t) == 0.968, SE == 0.032) was greater (X21 == 2.649, P == 0.104) than the survival rate in the control unit (S(t) == 0.861, SE == 0.058). However, annual adult doe survival rates (Dec 1,2000 - Nov 30,2001) were similar among the treatment and control deer (Trt: S(t) == 0.839, SE == 0.066; Control: S(t) == 0.833, SE == 0.062; X21 == 0.004, P == 0.947). We observed a similar result the following year. The 2001-02 overwinter adult doe survival rate in the treatment unit (S(t) == 0.942, SE == 0.030) was greater (X21 == 3.116, P == 0.078) than survival in the control unit (S(t) == 0.848, SE == 0.044), yet annual adult doe survival was similar among treatment and control deer (Trt: S(t) == 0.824, SE == 0.049; Control: S(t) == 0.818, SE == 0.047; X\ == 0.090, P == 0.764). Thus, mortalities of control deer occurred primarily during the winter months, while treatment does died primarily during the summer and fall months. �52 During winter 2002-03, following the treatment cross-over, overwinter adult doe survival rates were similar among treatment and control deer (Trt: S(t) = 0.945, SE = 0.024; Control: S(t) = 0.924, SE = 0.028; X:l = 0.360, P = 0.549). The main difference from the previous 2 years was that overwinter survival of adult does in the Shavano experimental unit increased in 2002-03 upon receiving the treatment. Current annual adult doe survival rates (Dec 1,2002 - Oct 7,2003) are 0.888 (SE = 0.034) for treatment does and 0.835 (SE = 0.039) for control does. The treatment has apparently had a minimal impact on annual adult doe survival, and annual survival rates measured thus far align with expected survival based on other studies (Unsworth et al. 1999, B.E. Watkins, unpublished). During 2000-02, when the Colona experimental unit received the treatment and the Shavano experimental unit was the control, 16 treatment and 16 control does died. The 16 treatment does died from the following categories: 4 - road-killed, 3 - while giving birth, 3 - predation (undetermined predator), 2non-predation unknown (intact carcasses with no evidence of predation or scavenging), 1 - disease (chronic arthritis), 1 - mountain lion predation, and 2 - unknown. Predation was not a major mortality factor for treatment does, and a majority of mortalities were independent of nutrition (does were in good condition). The 16 control doe mortalities included the following causes: 5 - mountain lion predation, 3 - malnutrition, 2 - non-predation unknown, 1 - road-killed, 1 - bear predation, 1 - injury (fence), 1 legal harvest, and 2 - unknown. Predation and malnutrition were the major mortality causes of control deer. Interestingly, during this 2-year period, we did not document any coyote predation on adult does. Thus far during 2003, with Shavano as the treatment and Colona as the control, there have been 9 treatment doe mortalities: 3 - coyote predation, 3 - disease/infection, 1 - road-killed, and 2 unknown. Two of the coyote mortalities, 2 of the disease mortalities, and the road-kill occurred on adult does in good condition. There have been 14 control doe mortalities thus far in 2003: 3 - coyote predation, 3 malnutrition/disease, 3 - non-predation unknown, 1 - mountain lion predation, 1 - road-kill, and 3 unknown. As we saw during 2000 - 2002, malnutrition and predation were the major mortality factors of control does. LITERATURE CITED Baker, D. L., and N. T. Hobbs. 1985. Emergency feeding of mule deer during winter: tests ofa supplemental ration. Journal of Wildlife Management 49:934-942. Baker, D. L., D. E. Johnson, L. H. Carpenter, O. C. Wallmo, and R. B. Gill. 1979. 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Effects of enhanced nutrition of adult female mule deer on fetal and neonatal survival rates: a pilot study to address feasibility. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R, Job Final Report. Fort Collins, Colorado, USA. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in 0. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, Nebraska, USA. Cook, J. G., and R. C. Cook. 2002. An informal training guide to condition evaluation in elk and deer. National Council for Air and Stream Improvement, Unpublished Report. Cook, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain elk. Thesis, University ofIdaho, Moscow, Idaho, USA. Cook, R. C; J. G. Cook, D. L. Murray, P. Zager, B. K. Johnson, and M. W. Gratson. 2001. Development of predictive models of nutritional condition for Rocky Mountain elk. Journal of Wildlife Management 65:973-987. Gill, R. B., T. D. I. Beck, C. J. Bishop, D. J. Freddy, N. T. Hobbs, R. H. Kahn, M. W. Miller, T. M. Pojar, and G. C. White. 1999. Declining mule deer populations in Colorado: reasons and responses. A report to the Colorado Legislature. Colorado Division of Wildlife, Denver, Colorado, USA. Holter, J. B., H. H. Hayes, and S. H. Smith. 1979. Protein requirement of yearling white-tailed deer. Journal of Wildlife Management 43:872-879. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. the American Statistical Association 53:457-481. Journal of Pojar, T. M. 2000. Investigating factors contributing to declining mule deer numbers. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R-13, Progress Report. Fort Collins, CO, USA. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. SAS Institute. 1989a. SAS/STAT® user's guide, version 6, fourth edition. Volume 1. SAS Institute, Cary, North Carolina, USA. SAS Institute. 1989b. SAS/STA~ user's guide, version 6, fourth edition. Volume 2. SAS Institute, Cary, North Carolina, USA. SAS Institute. 1997. SAS/STA~ Software: Changes and Enhancements through Release 6.12. SAS Institute, Cary, North Carolina, USA. �54 Schmidt, R L., W. H Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep- trapping techniques. Wildlife Society Bulletin 6:159-163. Smith, S. H, J. B. Holter, H H Hayes, and H. Silver. 1975. Protein requirement of white-tailed deer fawns. Journal of Wildlife Management 39:582-589. Stephenson, T. R, V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. Stephenson, T. R, K. J. Hundertmark, C. G. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76: 71 7-722. Stephenson, T. R, 1.W. Testa, G. P. Adams, R G. Sasser, C. G. Schwartz, and K. J. Hundertmark. 1995. Diagnosis of pregnancy and twinning in moose by ultrasonography and serum assay. Alces 31:167-172. Thompson, C. B., J. B. Holter, H. H. Hayes, H. Silver, and W. E. Urban, Jr. 1973. Nutrition of whitetailed deer. I. Energy requirements of fawns. Journal of Wildlife Management 37:301-311. Ullrey, D. E., W. G. Youatt, H E. Johnson, L. D. Fay, and B. L. Bradley. 1967. Protein requirement of white-tailed deer fawns. Journal of Wildlife Management 31 :679-685. Unsworth, 1. W., D. F. Pac, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. Verme, L. J., and D. E. Ullrey. 1972. Feeding and nutrition of deer. Pages 275-291 in D. C. Church, editor. Digestive physiology and nutrition of ruminants. Volume 3 - Practical Nutrition. D. C. Church, Corvallis, Oregon, USA. Watkins, B. E., D. E. Ullrey, R F. Nachreiner, and S. M. Schmitt. 1983. Effects of supplemental iodine and season on thyroid activity of white-tailed deer. Journal of Wildlife Management 47:45-58. Watkins, B. E., J. H Witham, D. E. Ullrey, D. J. Watkins, and J. M. Jones. 1991. Body composition and condition evaluation of white-tailed deer fawns. Journal of Wildlife Management 55:39-51. White, G. C., and R. M. Bartmann. 1998. Effect of density reduction on overwinter survival of freeranging mule deer fawns. Journal of Wildlife Management 62:214-225. White, G. C., R A. Garrott, R. M. Bartmann, L. H Carpenter, and A. W. Alldredge. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Management 51:852-859. White, G. c., A. F. Reeve, F. G. Lindzey, and K. P. Burnham. 1996. Estimation of mule deer winter mortality from age ratios. Journal of Wildlife Management 60:37-44. �55 JOB PROGRESS REPORT State of C"'-o""'l'""'o~ra""'d""'o'__ _ Work Package No. 3=-:0"-->0,-,,,1~ _ Task ~I Division of Wildlife - Mammals Research Deer Conservation _ Mule Deer Life Cycle - Neonatal Fawn Survival Federal Aid Project __ W-'-'--=..c18=5;_-R=-=- _ Period Covered: July 1 2002 through June 30, 2003 Author: Thomas M. Pojar Personnel: W. Andelt, R Arant, D. Baker, T. Baker, B. Banulis, T. Beck, C. Bishop, G. Bock, D. Bowden, P. Burke, T. Burke, M. Caddy, D. Coven, B. Diamond, B. Dreher, 1. Ellenberger, M. Farnsworth, 1. Foster, V. Graham, J. Griggs, D. Gustine, P. Hayden, B. Hoffner, B. Lamont, M. King, K. Larsen, M. Mclain, H. McNally, G. Miller, M. W. Miller, E. Myers, J. Olterman, M. Potter, 1. Risher, D. Schweitzer, D. Steele, 1. Skinner, T. Spraker, D. Swanson, B. Watkins, G. White, S. Znamenacek. The following is the abstract of the manuscript submitted to the Journal of Wildlife Management describing the neonatal fawn survival study on the Uncompahgre Plateau. Because of requests by reviewers or editors some aspects of the presentation and analysis may be modified. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such, and is discouraged. NEONATAL MULE DEER FAWN SURVIVAL IN WEST-CENTRAL COLORADO ABSTRACT Declining mule deer (Odocoileus hemionus) populations resulting from apparent low recruitment brought management and political focus on neonatal fawn survival. We captured mule deer fawns on the Uncompahgre Plateau (5,957 knr') in west-central Colorado, USA, at a mean age of3 days (range from newborn to 6 days), and we radiomarked them with mortality-sensing drop-offradiocollars. Two hundred thirty fawns were radiomarked with samples of 50 in 1999, 88 in 2000, and 92 in 2001. Designated neonate survival period was from capture to 14 December. Survival was different among years (X/ = 6.160, P = 0.046) with 3-year mean survival of 0.501. Cause-specific mortality ordered from highest to lowest was sick/starve, coyote, unknown, trauma, bear, and feline. Neither all predation combined (coyote, bear, and feline; P = 0.379) nor coyote predation alone (P > 0.989) differed among years. By 31 July, 74% of the sick/starve mortality and 75% of the predation mortality had taken place with 76% of mortality from all sources occurring by this date. Mean fawn weights at capture were different among years (P = 0.044). We also found a difference in hind foot length among years (P = 0.002). Weight and hind foot means were different between 2000 and 2001 (P> 0.017) with 1999 not different from either 2000 or 2001 (P < 0.017). Mean capture date was 19 June (SD = 4.83 days) and median capture date was 19 June (range = 9 Jun to 6 Jul) with 94.78% of all captures occurring between 13 and 30 'June. This implies that most does were bred during their first estrous cycle. Neonatal survival through 14 December did not completely account for observed low f.d ratios. We hypothesized fetus mortality during late pregnancy or mortality of fawns at birth (before they could be detected for capture) as potential causes of poor recruitment. �56 �57 JOB PROGRESS REPORT Srnteof ~C~o=lo=r=a=d=o Work Package No. __ -=3::..:0'-"0=2'-Task No. Federal Aid Project _ Division of Wildlife - Mammals Research Elk Conservation _ Technical Support for Elk and Vegerntion Management Environmenrnl Impact Srntement for Rocky Mountain National Park --'-W_,_-_,,_1=53=--_,,_R::....._ _ --=RMN="'--""P _ Period Covered: July 1,2002 - June 30, 2003 Authors: D. L. Baker, M. A. Wild, and M. M. Conner Personnel: M. Coffey, G. Dodd, B. Gill, T. Johnson, M. Monello, R. Monello, D. Plattner, J. Powers, J. Ritchie, R. Spowert, T. Nett, D. Hussain, R. Dunn, K. Zollers. ABSTRACT Overabundant wild ungulate populations have become a significant concern for natural resource managers in many parts of North America. Wild ungulates can do serious and lasting harm to many plant communities, and preventing such damage requires controlling the growth of their populations. In protected areas such as national parks, traditional methods of population control may not be feasible or publically acceptable. In these situations, alternative methods of population control are needed. One alternative is controlling the fertility of females. In this study, we evaluated the feasibility of using gonadotropin releasing hormone (GnRH) analog to control reproduction in free-ranging female elk in Rocky Mountain National Park. During fall of 2002, we captured, radio-collared and treated 34 adult elk. Seventeen elk were treated subcutaneously with a controlled release bio-implant containing 32.5 mg of leuprolide and seventeen elk were treated with the same formulation without leuprolide. We evaluated the effects ofleuprolide treatments on reproductive rates, body condition, behavior, and daily activity patterns of female elk during September 2002 to April 2003. Leuprolide administered as a sustained release formulation was 100% effective in preventing pregnancy in female elk. Body condition of all experimental elk declined from fall 2002 to spring 2003. Changes in loin depth and body condition score were similar (P. 0.254) for both treated and control elk, whereas overwinter loss in mean percent rump fat was greater (p. 0.057) for treated elk compared to controls. There were no differences (P = 0.36) in reproductive behavior rates during the breeding season between treated and control elk. �58 TECHNICAL SUPPORT FOR ELK AND VEGETATION MANAGEMENT ENVIRONMENTAL IMPACT STATEMENT FOR ROCKY MOUNTAIN NATIONAL PARK D. L. Baker, M. A. Wild, and M. M. Conner P. N. OBJECTIVE Conduct experiments with captive and free-ranging elk to evaluate fertility control as an management alternative for controlling elk populations in Rocky Mountain National Park (RMNP), Colorado. SEGMENT OBJECTIVES 1. Capture, radio-collar, and apply fertility control treatments to a target sample of free-ranging adult female elk in RMNP during September 2002. 2. Evaluate the effects of fertility control on reproductive rates of treated and non- treated adult female elk and the reversibility of these effects if they occur. 3. Evaluate the effects of fertility control on body condition of treated and non-treated adult female elk. 4. Evaluate the effects offertility control on reproductive behavior and daily activity patterns of and non-treated adult female elk. treated INTRODUCTION Overabundant wild ungulate populations have become a significant problem for natural resource managers in North America. Unregulated populations can cause adverse effects that are ecological, economic, or political in scope and resolving these issues often requires controlling animal abundance (Jewell and Holt 1981, Garrott et al. 1993, McCullough et a1.l997, Smith 2001). In Rocky Mountain National Park (RMNP), Colorado, the impact of herbivory by elk has emerged as a fundamentally important problem for those who manage the Park and its wildlife (Hess 1993, Zeignefuss et al. 1996). In 1968, RMNP adopted a natural-regulation policy for management of ungulates (Cole 1971, Houston 1971) with the objective of allowing density dependent processes to regulate elk numbers within park boundaries and use sport hunting to harvest as many animals as possible in areas surrounding the Park. Recently, however, Park managers have become concerned that possible unnatural concentrations of elk may be altering natural plant communities and ecosystem sustainability. Soil conditions and the status of willow and aspen plant communities have declined. Wet meadow, dry grasssiand, and alpine and subalpine sites show evidence of deterioration from overgrazing by elk (Singer et al. 1998, White et al. 1998). As a result of the decline in these vegetation types and the diversity of the animal species that are associated with them, the Park and other natural resource agencies are evaluating alternative management strategies for reducing elk densities within RMNP and the surrounding Estes Valley. One alternative being considered is controlling the fertility of female elk. Fertility control has been widely advocated as an alternative to lethal methods of population control for wildlife and considerable research �59 has been directed toward development of different contraceptive agents (see reviews by Kirkpatrick and Turner 1985, Fagerstone et al. 2001). Field and laboratory studies have evaluated the efficacy of delivery of contraceptives to ungulates (Jacobsen et al. 1995, DeNicola et al. 1997, Kirkpatrick et al. 1997) and models have been developed to represent effects of fertility control on the population dynamics of individual species and populations (Garrott and Siniff 1992, Seagle and Close 1996, Hobbs et al. 2000). To date, most contraceptive research for wild ungulates has focused on the development of immunocontraceptive vaccines and steroidal hormonal agents. However, after more than 40 years of research, the success of these approaches have been primarily limited to captive wildlife and small localized urban populations of wild ungulates. To meet this challenge, new technologies and approaches are needed if fertility control is to become practical and acceptable management tool for controlling overabundant wildlife species. A promising new non-steroidal, non-immunological approach to contraception involves potent analogs of gonadotropin-releasing hormone (GnRH). GnRH is a molecule produced in the hypothalamus of the brain. It directs specific cells in the pituitary gland to synthesize and secrete two important reproductive hormones; follicle stimulating hormone (FSH) and luteinizing hormone (LH). These latter two hormones, known as gonadotropes, control the proper functioning of the ovaries in the female and testes in the male. Chronic treatment with continuous, high doses of GnRH agonists results in temporary suppression of pituitary responsiveness and gonadotropin secretion. Resulting decreases in plasma LH and FSH in females leads to suppression of ovulation, estrous cyclicity, and gonadal steroidogenesis (Belchetz et a1.1978, Evans and Rawlings 1994). Once GnRH agonist treatments are terminated, normal pituitary function is gradually restored (Bergfeld et al. 1996). GnRH agonists have been shown to inhibit ovulation in several domestic ungulate species including sheep (McNeilly and Fraser 1987), cattle (D'Occhio et al. 1996; D'Occhio and Aspden 1999), and horses (Montovan et al. 1990). However, studies on wild ungulates are limited (Becker and Katz 1995; Brown et al. 1999) and to our knowledge, and only one study has demonstrated their effectiveness as a contraceptive agent (Baker et al. 2002 ). GnRH agonists provide a potential biotechnology for achieving a controlled, reversible suppression of fertility in both captive and free-ranging female wild ungulates. However, their practicality as a contraceptive agent is dependent on effective inhibition of reproduction without negative behavioral or physiological side-effects, and efficacious application in free-ranging elk. In previous experiments, we determined the effectiveness ofGnRH agonist (leuprolide) for controlling fertility in captive female elk and assessed the physiological and behavioral side-effects of treatment (Baker et al. 2002). Leuprolide administered as a subcutaneous, controlled release formulation was 100 % effective in preventing reproduction in elk for one breeding season. Serum LH and progesterone (P4) concentrations were reduced to baseline levels by day 30 and remained at those levels for 190-252 days posttreatment, with a return to normal fertility the following breeding season. In addition, there were no adverse physiological side-effects and behavioral effects were minimal. However, these results were obtained under controlled conditions with captive animals of known fertility and in excellent body condition. While these results provide strong inference on the potential utility ofleuprolide as a contraceptive agent, studies with wild elk are needed to evaluate whether the technique is truly feasible and practical. Thus, the goal of this study was to conduct a field experiment to examine the efficacy of leuprolide as a contraceptive agent and to contribute further understanding of its effects on reproduction and behavior in free-ranging female elk. Our specific objectives were to determine in elk: 1) the effectiveness ofleuprolide in preventing pregnancy, 2) the effects ofleuprolide on reproductive behavior, 3) the effects ofleuprolide on body condition, and 4) the reversibility ofleuprolide treatments. �60 MATERIALS AND METHODS Study Area Investigations were conducted in Rocky Mountain National Park and adjacent Estes Valley on the east slope of the Continental Divide between 2000 and 2800 m elevation. Experimental elk were selected from one of two subpopulations that historically wintered in Moraine ParklBeaver Meadows or Horseshoe Park (Bear 1989). Experimental Procedures During late summer and early fall of 2002, 34 adult female elk were immobilized by darting, from the ground, with 3.0 mg ofcarfentanil citrate (Wildlife Pharmaceuticals, Fort Collins, Colorado, USA) and 10-20 mg xylazine hydrochloride (Rompun; Bayer AG, Leverkusen, Germany). In order to insure that reproductive failure, if it occurred, was due to contraceptive effects rather than the effects of age or diminished body condition, we attempted to select only adult females of prime reproductive age and in moderate to excellent body condition. We hoped to accomplished this in 2 ways: 1) before immobilization, we made a visual assessment of the target animal using age (calf, yearling, adult) and relative fatness and body musculature (condition). Animal condition was classified as good, medium or poor (Riney 1960) and only medium or good condition females were selected, and 2) once the animal was immobilized we estimated age using tooth wear and replacement (Quimby and Gaab 1957), lactational status, and body condition using ultrasonography (Cook et al. 2001). Captured elk were fitted with frequency-specific transmitters on neck collars containing a plastic identification sleeve marked with a unique alpha-numeric code of76 mm-high black characters on a colored background (white for controls; yellow for treatment)(Freddy 1993). To meet U.S. Food and Drug Administration regulations, all immobilized animals were marked to prevent human consumption. Radio collars were marked with "Do Not Consume". Once sedated, female elk received a subcutaneous, sustained release leuprolide formulation (32.5 mg) using the ATRIGEL ® drug delivery system (Atrix Laboratories, Inc., Ft. Collins, CO, USA) (Dunn et al. 1994). We reversed the effects of the immobilizing drug with 300 mg of naltrexone HcL (Wildlife Pharmaceuticals, Fort Collins, Colorado, USA). To minimize any possibility of infection from immobilization, each darted elk also received a subcutaneous injection of long-lasting penicillin. We collected blood (20 ml) from each elk as baseline information for health parameters. Blood was archived by veterinarians with the National Park Service (NPS). Measurements Reproductive rates: We assessed the effects of leuprolide treatments on reproduction in elk using 4 methods: pregnancyspecific protein B (PSPB) (Noyes et al. 1997), serum progesterone (P4) (Willard et al. 1994), rectal palpation (Greer and Hawkins 1967) and fecal progesterone metabolites (FPM) (Garrott et al. 1998). We determined pregnancy status of all treated and untreated elk during late gestation (March- April) by relocating animals using radiotelemetry and recapturing them following the immobilization procedures previously described. Once immobilized, a trained wildlife veterinarian, rectally palpated each female and determined the presence or absence of a gravid uterus. A single blood sample (10 ml) was collected via jugular venipuncture from each animal for PSPB(BioTracking, Moscow, Idaho, USA) and P 4 (Niswender 1973) analysis. At the same time, a single fecal sample was collected for fecal Padetermination. �61 Females having fecal Pa levels < 0.9 Og/gm were considered nonpregnant and those. 1.0 Og/gm pregnant. Discrimination for samples with concentrations between 0.90-0.99 Og/gm was regarded as inconclusive. We will evaluate the reversibility of leuprolide treatments during March - April 2004 by using the . reproductive measurements described above. Reproductive behavior: We examined the effects ofleuprolide on reproductive interactions of male and female elk during 2 time periods; breeding season (defined as the period 15 September to 15 November) and postbreeding season (defined as the period 15 January to 15 March). We used focal animal sampling procedures to sample reproductive behaviors of all experimental elk (Lehner 1996). Behavioral measurements were be made by locating a breeding group containing radio collared/marked elk. Depending on the environmental conditions, topography, available cover, and elk viewing restrictions in RMNP, the observer attempted to approach the group undetected to within 150-500 m. Observations were made with the aid of binoculars and 15-60X spotting scope during morning (0500-0800) and late day (1400-1700). Time-of-day sampling periods were randomly assigned each week using a randomized block design. Each sampling period consisted of at least 2 hours of continuous observations. We combined individual behaviors into 4 general categories: male copulatory, male precopulatory, female precopulatory, and general breeding (Table 1). Our experimental unit for analyses was the individually marked female in each breeding group. Because sexual interactions were generally short duration « 30 sec) relative to sampling interval, we recorded the number of occurrences of each event rather than length oftime and calculated sexual interaction rates as behaviors per animal per hour. Body condition: Recent research has correlated measures of body condition, using ultrasonography of body fat deposits, to reproductive success in elk (Cook et al. 2001). Using these predictive models, we estimated the body condition of all female elk using body condition scoring and ultrasonography of fat and lean body mass. We classified each female as either excellent, very good, moderate, low, or very low reproductive candidates. We selected only those females that were judged to be, at least, in the moderate (10-15 % body fat; > 90% pregnancy rate) category. Elk that met this criteria were randomly assigned to either treatment or control groups; elk that did not, were rejected from the experiment. Additionally, we measured change in rump fat and lean body of females between fall capture and spring re-capture to evaluate the effects of leuprolide treatments on body condition. Statistical analysis: Reproductive rates. In previous experiments, a sample size of 5 treated and 5 control elk was sufficient to detect significant differences (P. 0.05) in pregnancy rates of captive animals (Baker et al. 2002). However, free-ranging elk are more elusive than their captive counterparts and treatment application and measurements of response variables less certain. Uncontrolled variables such as natural mortality, hunting mortality, low pregnancy rates, relocation success, and transmitter failure increase the need for larger sample sizes. We performed a sample size analysis with Fisher's Exact Test, using a software program (NCSS PASS 2000) to estimate the number of treated and control animals needed to detect treatment differences for PSPB, fecal progesterone metabolites, and calving rates (Table 2). For PSPB and fecal progesterone metabolites, we assumed the lowest reported pregnancy rate (63 %) for elk in RMNP (Johnson and Monello, unpublished data), 90 % recapture of radio collared females, and 100% accuracy ofPSPB for pregnancy determination in elk greater than 100 days of gestation (Huang et al. 2000). For estimating �62 sample sizes for calving rates, we assumed 63 % pregnancy rates and an 85 % success in confirming presence or absence of a calf Results of these analyses indicated that a sample size as low as 10 treated and 10 control females would be sufficient to detect a significant treatment effect using PSPB, and serum and fecal Pavalues. Reproductive behavior: We tested specific reproductive behavior hypotheses that mean behavior rate was not different between treatment and control groups for both breeding and postbreeding seasons using an ANOV model with repeated measures structure. Time was treated as a within subject effect using a multivariate approach to repeated measures (Morrison 1976). To test for treatment effects, we accounted for time-of- day effects, date effects, and their interactions. PROC GENMOD (SAS Institute 1993) was used to estimate and test for differences in mean behavior rate by treatment, time- of- day, and date. Means and standard errors were estimated using least squares, and hypothesis tests were be based on type III generalized estimating equations that accounted for correlation in repeated measures. Table 1. Description of elk reproductive behaviors and associated behavior categories. Behavior category Reproductive behavior Reproductive: General Breeding Male directed behavior related to establishing, maintaining, and defending a group or harem of female wapiti Male pre-copulatory Male courtship behavior directed toward an individual female to induce or detect oestrus or ovulation (e.g. urine testing, flehmen, tongue flick, lick, smell, or rub female's body, chivy) Female pte-copulatory Female courtship behavior directed toward dominant male to arouse copulatory behavior (e.g. lick and rub male, mount, lordosis, twitch hocks) Copulatory Male behavior directed toward a receptive female in oestrus (e.g. precopulatory mounts, intromission, pelvic thrust) Non-Reproductive: Feeding Head down in vegetation Idling Bedded or standing upright and not feeding Moving Ambulating �63 Table 2. Sample size estimates and power of the test for measurements of reproductive rates in female elk in RMNP. Measurement Treatment (n) Control (n) a I-P PSPB/Fecal P 1. 10 10 0.05 0.9386 2. 10 20 0.05 0.9890 3. 10 120 0.05 0.9996 1. 10 20 0.05 0.8613 2. 20 20 0.05 0.9685 3. 20 25 0.05 0.9829 4. 20 30 0.05 0.9865 Calving rates RESULTS AND DISCUSSION Fall:2002 We captured, sampled, and radio collared 34 female elk in RMNP during 24 August - 7 September, 2002. Elk were captured from 5 general locations in the RMNP : Kawuneeche Valley (7), alpine tundra areas near Trail Ridge Road (4), Hidden Valley (3), Beaver Meadows (9), and Moraine Park (11). Seventeen females were given a subcutaneous formulation containing 32.5 mg ofleuprolide and seventeen a placebo formulation without leuprolide. No capture-related mortalities were observed. Estimated ages of leuprolide-treated females ranged from 1-12 years of age -( = 6.9, SE = 0.82) and 1-10 years of age -( = 6.3, SE = 0.72) for untreated elk. Two yearling females were included in both groups. Yearling females were included as experimental animals because they met a priori body composition criteria. and because we wanted additional information on the effects ofleuprolide in this age group. Seventy percent of treated females were determined to be lactating when captured compared to 61 % of control females. Fall body condition ofleuprolide-treated and control females were similar for rump fat depth (P = 0.56), loin depth (P = 0.91), and body condition score (BCS) (P = 0.38) (Table 3). Rump fat percent of leupro Iide-treated females ranged from 8.8 - 16.3 %-( = 13.1 %, SE = 0.40) and from 10.6 - 15.9 %-( = 12.7 %, SE = 0.38) for control elk. With the exception of one animal, all females in the experiment had a rump fat percentage of greater than 10 % (> 90 % pregnancy rate). �64 Table 3. Mean fat depth, percent rump fat, body condition score, and loin depth of leuprolide-treated and control female elk sampled during Aug-Sept, 2002 and Mar-Apr, 2003, in Rocky Mountain National Park, Colorado. Leuprolide Measurements Control Mean SE Mean SE 2.13 5.43 3.53 13.10 0.18 0.12 0.12 0.40 2.00 5.41 3.38 12.73 0.11 0.10 0.11 0.38 0.37 4.84 2.36 6.90 0.04 0.08 0.12 0.04 0.72 5.00 2.48 8.20 0.12 0.11 0.13 0.49 Fall (Aug-Sept 2002): Rump fat depth (ern) Loin depth (em) Body condition score Rump fat (%) Spring (Mar-Apr 2003): Rump fat depth (ern) Loin depth (em) Body condition score Rump fat (%) Fall - Spring L\ L\ L\ L\ Rump fat depth (em) Loin depth (em) Body condition score Rump fat (%) - 1.76 - 0.59 - 1.17 - 6.20 - 1.28 - 0.41 - 0.90 - 4.50 We observed reproductive behaviors of treated and control elk in RMNP and Estes Valley during 11 September to 27 November, 2002. We recorded a total of 144, one hour observations for 16 different radio collared female elk (8 treated; 8 control). No copulatory behaviors were observed during this period, thus there was no analysis for this category. There were no differences in reproductive behavior rates (number ofbehaviorslhour) for general breeding (P = 0.36), female precopulatory (P = 0.13), or male precopulatory (P = 0.70) behaviors (Fig. 1). In general, control females showed somewhat higher rates of general breeding (25 % higher than treated females) and male precopulatory (9 % higher than treated females) behaviors, but none of these differences were statistically significant. In addition to reproductive behaviors, we evaluated the effects ofleuprolide on the daily activity patterns of treated and control female elk. These data are currently being analyzed. �65 Figure 1. Mean (± SE) reproductive behavior rates during the breeding season for control female elk (n = 8) and females treated with a sustained release implant containing 32.5 mg leuprolide formulation (n = 8), in Rocky Mountain National Park, Colorado. Columns with different lower case letters indicate significant differences between means (p. 0.05). Spring 2003 During 24 March to 30 April, 2003, we evaluated the effects of leupro lide on pregnancy rates, body condition, and reproductive behavior of treated and control female elk. Using the capture methods previously described, we recaptured 15 out of 17 treated elk and 17 out of 17 control elk. Elk were recaptured in. 3 general locations: RMNP (13), Estes Park, Colorado area (16), and Loveland, Colorado area (3). Leuprolide, administered as a sustained release formulation, prior to the breeding season, effectively prevented pregnancy in all female elk for one year. Pregnancy rates of untreated females ranged from �66 64.7 -78.5 %, depending on the method of determination. Fecal P4 analyses for pregnancy determination have not been completed. Body condition of experimental elk declined for all measures of body composition during fall 2003 and spring 2004 (Table 3). Changes in mean loin depth (P. 0.25) and body condition score (P. 0.08) were similar for both treated and control female elk, whereas, overwinter loss in mean percent rump fat was greater (P. 0.057) for elk treated with leuprolide. Post-breeding season reproductive behaviors and daily activity patterns of control and leuprolide-treated females are currently being analyzed. SUMMARY To date, we have completed or are in the process of completing 3 out of the 4 objectives originally stated for this investigation. First, we have evaluated the effects of leuprolide on pregnancy rates of female elk using rectal palpation, PSPB, and P 4 analysis and all methods support the conclusion that leuprolide is 100% effective in preventing pregnancy for at least one breeding season. The only remaining analysis for pregnancy determination is fecal P4, which will be completed during winter 2004. Second, we have evaluated the effects ofleuprolide on breeding and post-breeding reproductive behavior of elk. Although neither of these data sets have been completely analyzed, leuprolide does not appear to have deleterious effects on elk reproductive behavior or daily activity patterns. Third, we assessed the effects of leuprolide on body condition dynamics of elk. We observed only minor differences in overwinter body composition changes between treated and control elk. The only objective yet to be completed is to confirm the reversibility ofleuprolide treatments. This will be accomplished during March-April 2004 by comparing pregnancy rates of treated and control female elk. LITERATURE CITED Baker, D. L., M. A. Wild, M. M. Conner, H. B. Ravivarapu, R. L. Dunn, and T. M. Nett. 2002. Effects of GnRH agonist (leuprolide) on reproduction and behavior in female wapiti (Cervus elaphus nelsoni). Reproduction (Suppl) 60:155-167. Bear, G. D. 1989. Seasonal distribution and population characteristics of elk in the Estes Valley, Colorado. Colorado Division of Wildlife R-S-65-89, Special Report 65. Becker, S. E., and L. S. Katz. 1995. Effects of gonadotropin-releasing hormone agonist on serum LH concentrations in female white-tailed deer. Small Ruminant Research 18: 145-150. Belchetz, P. E., T. M. Plant, Y. Nakai, E. J. Keogh, and E. Knobil. 1978. Hypophysial response to continuous and intermittent delivery of hypothalamic gonadotropin-releasing hormone. Science 202: 631-633. Bergfeld E., M. J. D'Occhio, and J. E. Kinder. 1996. Pituitary function, ovarian follicular growth, and plasma concentrations of 17~-oestradiol and progesterone in prepubertal heifers during and after treatment with the luteinizing hormone-releasing hormone agonist deslorelin. Biology of Reproduction 54: 776-782. Brown, J. L., D. L. Schmitt, A. Bellem, L. H. Graham, and J. Lehnhardt. 1999. Hormone secretion in the Asian elephant (Elaphus maximus): Characterization of ovulatory and anovulatory LH surges. Biology of Reproduction 61: 1294-1299. �67 Cole, G. F. 1971. An ecological rationale for the natural or artificial regulation of native ungulates in parks. Transactions of the North American Wildlife and Natural Resources Conference 36:417426. Cook, R. c., 1. G. Cook, and D. L. Murray. 2001. Development of predictive models of nutritional condition for Rocky Mountain elk. Journal of Wildlife Management 65:973-987. D'Occhio, M. H., W. 1. Aspden, and T Whyte. 1996. Controlled reversible suppression of oestrous cycles in beef heifers and cows using agonist ofluteinizing hormone - releasing hormone. Journal of Animal Science 74:218-225. ___ M. J., and W. J. Aspden. 1999. Endocrine and reproductive responses of male and female cattle to agonist of gonadotrophin-releasing hormone. Journal of Reproduction and Fertility Supplement 54:101-114 --> DeNicola, A. 1., D. 1. Kesler, and R. K. Swihart. 1997. Remotely delivered prostaglandin F- 2 alpha implants terminate pregnancy in white-tailed deer. Wildlife Society Bulletin 25:527-531. Dunn, R. L., 1. P. English, D. R. Cowan, and D. P. Vanderbilt. 1994. Biodegradable in situ forming implants and methods of producing the same. U. S. patent no. 5,278,201. Evans, A. C. 0., and N. C. Rawlings. 1994. Effects of a long-acting gonadotrophin-releasing hormone agonist (Leuprolide) on ovarian follicular development in prepubertal heifer calves. Canadian Journal of Animal Science 74:649-656. Fagerstone, K. A, M. Coffey, P. Curtis, R. Dolbeer, G. Killian, L. A. Miller, and L.Wilmot. 2001 Wildlife contraception. Wildlife Society Technical Review. Proceedings of the Wildlife Society 8th Annual Conference, Reno, USA Freddy, D. J. 1993. Estimating survival rates of elk and developing techniques to estimate population size. Colorado Division of Wildlife Report, July. Garrott, P. 1. White, and C. A. Vanderbilt White. 1993. Overabundance: an issue for conservation biologist? Conservation Biology 7:946-949. _____ , and D. B. Siniff. 1992. Limitations of male-oriented contraception for controlling feral horse populations. Journal of Wildlife Management 56:456-464. ' ____ , S. L. Monfort, P. 1. White, K. L. Mashburn, and 1. G. Cook. 1998. One-sample pregnancy diagnosis in elk using fecal steroid metabolites. Journal of Wildlife Management 34: 126-131. Huang, F., D. C. Cockrell, T R. Stephenson, 1. H. Noyes, and R. G. Sasser. 2000. A serum pregnancy test with specific radioimmunoassay for moose and elk pregnancy specific protein B. Journal of Wildlife Management 64:492-499. Hess, K. H. 1993. Rocky Times in Rocky Mountain National Park. University of Colorado Press. Niwot Colorado, USA. Hobbs, N. T, D. C. Bowden, and D. L. Baker. 2000. Effects of fertility control on populations of ungulates: general, stage-structured models. Journal of Wildlife Management 64: 473-491. �68 Houston, D. B. 1971. Ecosystems of national parks. Science 172:648-651. Jacobsen, N. K., D. A. Jessup, and D. 1. Kesler. 1995. Contraception in captive black-tailed deer by remotely delivered norgestomet ballistic implants. Wildlife Society Bulletin 23:718-722. Jewell, P. A., and S. Holt. 1981. Problems in management of locally abundant wild animals. Academic Press. 321pp. Lehner, P. N. 1996. Handbook of Ethological Methods. Second Edition. Cambridge University Press, Cambridge, UK. Kirkpatrick, J. F., and J. W. Turner, Jr. 1985. Chemical fertility control and wildlife management. Bioscience 35 :485-491. __________ , I. K. M. Lui, R C. Fayrer Hosken, and A. T. Rutberg. 1997. Case studies in wildlife immunocontraception: wild and feral equids and white-tailed deer. Reproduction, Fertility, and Development 9: 105-11 O. McCullough, D. R, K. W. Jennings, N. B. Gates, B. G. Elliot, and J. E. Didonato. deer populations in California. Wildlife Society Bulletin 25:478-483. 1997. Overabundant McNeilly, A. S., and H. M. Fraser HM. 1987. Effect of gonadotrophin-releasing hormone agonist-induced suppression ofLH and FSH on follicle growth and corpus luteum function in the ewe. Journal of Endocrinology 115: 273-282. Montovan, S. M., P. P. Daels, J. Rivier, G. H. Hughes, G. H. Stabenfeldt, and B.L. Lasley. 1990. The effect of potent GnRH agonist on gonadal and sexual activity in the horse. Theriogenology 33:1305-1321. Morrison, D. F. 1976. Multivariate Statistical Methods. McGraw-Hill Book Co., New York, USA. Quimby, D. c., and 1. E. Gaab. 1957. Mandibular dentition as an age indicator in Rocky Mountain elk. Journal of Wildlife Management 21: 134-153. Riney, T. 1960. A field technique for assessing physical condition of some ungulates. Journal of Wildlife Management 24:92-94. SAS Institute. 1993. SAS/STAT user's guide. Release 6.03 edition. SAS Institute, Cary, North Carolina, USA. Seagle, S. W., and J. D. Close. 1996. Modeling white-tailed deer population control by contraception. Biological Conservation 76:87-91. Singer, F. 1., L. C. Zeigenfuss, R G. Cates, and D. T. Barnett. 1998. Elk, multiple factors, and persistence of willows in national parks. Wildlife Society Bulletin 26:419-428. White, C. A., C. E. Olmsted, and C. E. Kay. 1998. Aspen, elk, and fire in the Rocky Mountain national parks of North America. Wildlife Society Bulletin 26:449-462. �69 Willard, S. T., R. G. Sasser, 1. C. Gillespie, 1. T. Jaques, T. H. Welsh, Jr., and R. D. Randel. 1994. Methods for pregnancy determination and the effects of body condition on pregnancy status in Rocky Mountain elk (Cervus elaphus nelsoni). Theriogenology 42: 1095-1102. White, C. A., C. E. Olmsted, and C. E. Kay. 1998. Aspen, elk, and fire in the Rocky Mountain national parks of North America. Wildlife Society Bulletin 26:449-462. Willard, S. T., R. G. Sasser, 1. C. Gillespie, 1. T. Jaques, T. H. Welsh, Jr., and R. D. Randel. 1994. Methods for pregnancy determination and the effects of body condition on pregnancy status in Rocky Mountain elk (Cervus elaphus nelsoni). Theriogenology 42:1095-1102. Zeignefuss, L., F. 1. Singer, and D. C. Bowden. Vegetation and elk responses following release from artificial controls within Rocky Mountain National Park, 1968-1996. Report to the Superintendent, Rocky Mountain National Park. �70 �71 JOB PROGRESS REPORT Smteof ~C~o~lo~r~a~d~o _ Division of Wildlife - Mammals Research Work Package _-'3'-'0'--=0=2'-- _ Task No. _ ~3 Federal Aid Project. Elk Conservation Estimating Calf and Adult Survival Rates and Pregnancy Rates of Gunnison Basin Elk W-153-R-16 Period Covered: July 1,2002- June 30, 2003 Author: D. J. Freddy Personnel: L. Gepfert, D. Masden, R. Basagoitia, L. Spicer, B. Carochi, 1. Oulton, T. Beck, C. Mehaffey, D. Williams, J. Johnston, and R. Kahn of CD OW, Dr. G. C. White Colorado State University, and cooperators/contractors Gunnison Basin Habitat Partnership Program, M. Schuette of Mountainscape Imaging, L. Coulter of Coulter Aviation, USFS, BLM, private land owners, and elk hunters. ABSTRACT We used aerial and ground surveys to estimate survival rates and assess sources of mortality for radio-collared adult elk (Cervus elaphpus nelsonii) in the Gunnison Basin of Colorado. Between 15 December 2000 and 14 June 2003, hunting accounted for 94% and 79% of the adult, age ~12 months, female and male deaths, respectively, while natural causes were attributed to 6% and 21 % of the adult female and male deaths, respectively. During 3 winter-spring intervals, 15 December - 14 June, natural survival rates for adult females, age ~18 months, were ~ 0.98 (n = 39-86 elk, 148-168 elk-winters). During 2 summer-fall intervals, 15 June - 14 December, natural survival rates for adult females, age ~12 months, were ~0.97 (n = 37-86 elk, 98-157 elk-summers). Including hunting mortalities reduced summer-fall female survival to 0.91 ± 0.07 in 2001 (n = 77) and 0.77 ± 0.08 in 2002 (n = 112). During 2 annual intervals, 15 December to next 14 December, natural survival rates for adult females, age ~ 18 months, were ~0.97 (n = 33-61). Including hunting mortalities reduced annual female survival to 0.92 ± 0.08 in 2001 (n = 39) and 0.74 ± 0.09 in 2002 (n = 82). Natural survival rates for 2 cohorts of yearlings, age 12-23 months, were 1.00 for females (n = 59) and 0.93 ± 0.08 (n = 43) for males. Including hunting mortalities reduced cohort survival to 0.87 ± 0.08 (n = 68) for females and 0.82 ± 0.11 (n = 49) for males. During summer-fall, natural survival rate for male elk, age 24-29 months, was 1.00 (n = 14) which was reduced to 0.74 ± 0.22 (n = 19) by including hunting mortalities. During winter-spring, natural survival rate for male elk, age 30-35 months, was 1.00 (n = 13). Predation by mountain lions or black bears was suspected in 4 of the 5 adult elk natural deaths. Hunting removal rates for adult females, age ~12 months, were 0.08 ± 0.06 (n = 76) in 2001 and lower than the 0.23 ± 0.08 (n = 112) in 2002 (P = 0.006). Removal rates for yearling females, age 12-17 months, averaged 0.13 ± 0.08 (n = 68). Removal rate for yearling· males averaged 0.13 ± 0.10 (n = 48) and for legal branch-antlered males was 0.26 ± 0.22 (n = 19). Wounding loss as a percent of legal harvest was 44 for all adult females and 0 for branch-antlered males. All hunting deaths of yearling males were illegal harvest/wounding loss while removal rate for branchantlered males was unexpectedly low, likely representing a year effect on elk vulnerability. Apparent differences in survival of adult females between DAUs (P:s 0.063) likely reflected geographic differences in vulnerability of elk to hunting while differences in male survival between DAUs (P = 0.046) reflected impacts of illegal harvest/wounding loss on removal of yearling males. Adult female elk body condition suggested marginally deficient levels of seasonal nutrition in 2002. �72 Distribution and movements of radio-collared elk during 3 years of monitoring revealed that elk had a relatively high fidelity to the Gunnison Basin as defined by current DAU boundaries but elk also commonly ventured into adjoining GMUs outside the Gunnison Basin. Distribution patterns revealed minimal interchange of elk between areas north and south of U.S. Highway 50 which bisected the Gunnison Basin from east to west. Movements by adult females, young females, and young males (n = 35,48, and 76) suggested DAU elk population management boundaries might be altered to better represent elk population units. Young male and female elk tended to move greater distances and exhibit higher rates of venturing into adjoining GMUs than adult females. Patterns of dispersion suggested movement corridors that allowed for genetic linkage between Gunnison Basin and other elk populations. All information in this report is preliminary and subject to further evaluation. �73 JOB PROGRESS REPORT ESTIMATING CALF AND ADULT SURVIVAL AND PREGNANCY RATES OF GUNNISON BASIN ELK POPULATIONS DAVID 1. FREDDY P.N. OBJECTIVE Estimate survival rates of calf, adult female, and adult male elk and estimate pregnancy rates of adult female elk in Gunnison Basin elk populations for 3 years. NOTE: Prioritization of available research funding resulted in discontinuing efforts to estimate calf survival, pregnancy rates, and body condition during 2002-03 but allowed for monitoring adult elk survival through June 2003. SEGMENT OBJECTIVES 1. Estimate calf, adult female and adult male survival rates during winter, December-June. 2. Estimate adult male and female survival rates during summer-fall, June-November. 3. Estimate harvest removal rates for yearling and adult males and females. 4. Estimate pregnancy rates, fetal rates, conception dates, and body condition of female elk collected in December. 5. Summarize data in Research Progress reports and prepare peer-reviewed publications. INTRODUCTION The elk resource has many benefits but frequent social, political, and economic conflicts suggest elk can reach "social" if not "biological" carrying capacities (Freddy et al. 1993). Recent controversy surrounding elk in the Gunnison Basin (Basin) of Colorado (Roath et al. 1999) exemplifies conflicting social and biological agendas regarding appropriate numbers of elk. The core of conflict in elk management often centers on establishing management objectives for numbers of elk that are agreeable to competing interests and then monitoring elk populations to demonstrate that objectives are achieved. This type of conflict is paramount in Colorado Division of Wildlife (CDOW) elk population Data Analysis Units (DAUs) E-2S, E-41, and E-43 in the Gunnison Basin where a combination of resource carrying capacity objectives for elk on winter ranges and difficulties associated with knowingly achieving those objectives has fostered argumentative distrust among public groups and management agencies. Accomplishing management by population objective can depend on reliably estimating elk population size which is expensive and intensive (Samuel et al. 1987, Bear et al. 1989, Unsworth et al. 1990, Anderson et al. 1998, Cogan and Diefenbach 1998, Eberhardt et al. 1998, Freddy 1998). Alternatively, population size and trend can be estimated using computer models that incorporate harvest, age and sex ratios, and survival rates (White 1991, Bartholow 1999). Model outputs are extremely sensitive to estimates of survival rates such that, reliable measurements of survival can greatly enhance the quality of models (Nelson and Peek 1982). We chose to estimate survival rates of calf and adult elk during winter and adults year-around to aid in developing improved population models for elk in the Basin. The Basin in south-central Colorado encompasses the entire headwaters of the main Gunnison River and the centrally located town of Gunnison. Between 12-16,000 elk and 8-10,000 mule deer (Odocoileus hemionus) are thought to exist �74 within the Basin. Elk are managed as 3 populations representing DAUs E-25 (Game Management Units [GMU] 66, 67), E-41 (GMU 54), and E-43(GMUs 55, 551). The 3 DAUs encompass about 9,291 km2 of which 3,648 km2 are considered potential winter range for elk (CDOW unpublished WRIS database). DAUs are contiguous with few major geographic barriers separating DAUs that would absolutely prevent interchange of elk among DAUs (Freddy 2002). The Basin represents a high altitude, cold winter range for both elk and mule deer which is similar to ecosystems in North Park, Middle Park, and the San Luis Valley, Colorado. The sagebrush (Artemisia tridentata) steppe winter ranges (2,250-2,700 m elevation) can receive both extreme snow depths and cold temperatures that cause severe mortality among ungulates (Carpenter et al. 1984) while the conifer meadow and alpine summer ranges (3,000-4,200 m elevation) can be lush sources offorage subjected to periodic drought. Overall, these ranges collectively are thought to be less productive and nutritious for elk than the milder climate oakbrush-pinyon-juniper winter ranges and aspen and subalpine summer ranges of the Grand Mesa, Colorado where elk survival was measured from 1993-2000 (Freddy 2000). METHODS Capture Adult female (age 2:30 months) and calf (age 6 months) male and female elk were captured and radio-collared using helicopter net-gunning from 16-22 December, 2000 and 16-20 December 2001 (Table 1, and Freddy 2002). All radio-collars were 172-176 MHz and contained 4-6 hour mortality sensors (Lotek®, Inc.). Calf collars were expandable allowing collars to remain on elk as they matured to adults (Freddy 2002). All capture protocols were approved by the CDOW Animal Care and Use Committee. Our desired yearly sample sizes for radio-collared calves (n = 78) and adult females (n = 39, Freddy 2002) were based on detecting yearly differences of ±15% in calf survival rates and ±10% in adult female survival rates for elk throughout the entire Basin. Our statistical power was thus premised on treating elk in all 3 elk management DAUs within the Basin as 1 population of elk. If calves and adult females were captured and radioed for 3 years in each DAU, we would be able to detect differences in survival rates among DAUs by pooling survival data within each DAU over 3 years (Freddy 2002). We chose to radio-collar equal numbers of calves (26) and adult females (13) yearly among DAUs knowing that counts of elk were similar but not equal among DAUs (Freddy 2002). Prior to capturing elk, the 3 DAUs demarcating the Basin were divided into 10 geographic trap-zones (Figure 1, A-J). Within each DAU, we distributed numbers of calves and adult females captured according to observed relative proportions of elk counted in each trap-zone within each DAU resulting in radiocollared elk being distributed across the landscape relative to numbers of elk counted during early winter. Counts of elk occurred during sex and age composition surveys conducted with a helicopter during December-January post-harvest 1995-96, 1997-98, and 1999-2000 prior to initiating this study (Freddy 2002). Telemetry Monitoring During this yearly segment, we monitored life or death status of radio-collared elk at 2-4 week intervals from July 2002 through June 2003 using a Cessna 185 or 182 equipped with strut mounted 'H' antennas. Additionally, as in previous years, the Cessna 185 was equipped with a rotational belly mounted 'H' antenna to provide more directional accuracy in interpreting telemetry signals. We used a �75 Lotek® SRX400 receiver-scanner for monitoring telemetry signals. Elk survival data were compiled using the RADIOS module of the CDOW program DEAMAN® (White 1991). Mortality Assessments All suspected mortalities based on telemetry mortality signals were confirmed using ground searches. Once carcasses were located, criteria for assigning probable cause of death followed standardized written procedures that included assessment of body position and body condition, presence of bite or claw marks and sub-dermal hemorrhaging or gunshot wounds, presence of tracks or drag marks, and collection of organ, muscle, and femur marrow samples for laboratory analyses, if available (Wade and Browns 1982, Freddy 1998). Multiple photographs were taken of the carcass along with any potential evidence for assessing cause of death and when appropriate, an outside expert (T. D. I. Beck, CDOW retired) was consulted to assess evidence. Field necropsies were performed to the extent possible depending on completeness of carcass. We routinely collected muscle samples from large muscle groups in the hind- and forequarters of carcasses when available during the first winter post-capture to assess for evidence of capture myopathy (Lewis et al. 1977, Spraker 1982, Haigh and Hudson 1993). Histopathology assessments of organ and muscle samples were completed by the Colorado State University Veterinary Diagnostic Laboratory and analyses of percent femur marrow fat (FMF) on a dry-matter basis were conducted by the CDOW research laboratory. Field technicians provided a standardized written summary for each death. The principal investigator made the final assessment for probable cause of death based upon field summaries, photographs, and laboratory analyses. Potential causes of death included malnutrition, predation by black bears (Ursus americanus), mountain lions, (Felis concolor), coyotes (Canis latrans), and domestic dogs (Canis jamiliaris), legal and illegal hunter harvest, accidental trauma, plant poisoning, capture-induced, and unknown (Freddy 1997). Causes of death were broadly summarized as malnutrition, predation, suspected malnutrition, suspected predation, accident, unknown, hunter harvest, and capture-induced. Mortalities classed as malnutrition were usually nearly intact carcasses with little or no evidence of predator presence whereas mortalities classed as predation usually had evidence of bite wounds and subdermal hemorrhaging indicating bites were inflicted on a live animal. In those cases classed as suspected malnutrition or suspected predation a preponderance of collected evidence was used to assign cause of death to the most likely class. Telemetry collars that prematurely slipped-off elk causing a mortality signal to be emitted were confirmed by locating and retrieving the collar. Elk were subjected to multiple hunting seasons during fall 2002. These seasons were: archery, 31 August-29 September; muzzleloading, 14-22 September; elk-only, rifle, 12-16 October; deer-elk first combined, rifle, 19-25 October; deer-elk second combined, rifle, 2-8 November; deer-elk third combined, rifle, 9-13 November, and late antlerless elk only, 23 November - 15 December in all Basin DADs, E-25, E-41, and E-43. Harvest of males was restricted to branch-antlered males with spike-antlered males (yearlings) not legal quarry. Hunters harvesting radioed elk were asked to complete a mail-in questionnaire to provide information on radio-collars and general health condition of elk (Appendix D). Survival Rates Survival rates of radio-collared elk were calculated for this report using the binomial estimator and in final analyses will be calculated using a Kaplan-Meier estimator (White and Garrott 1990). Binomial estimates of survival rates were calculated as mean survival (s) = [Alive / Alive+Dead collared elk], with a variance of [VAR (s) = (s) x (l-s) / n collars], and 95% confidence intervals of (s) ± [t (1=0.05, n- �76 1 df x " (VAR (s»]. Survival rates were estimated for time intervals of winter-spring (15 December - 14 June), summer-fall (15 June - 14 December), and yearly (15 December - 14 December) which coincided with capturing and radio-collaring elk and thus represented a biological year. Survival rates for these seasonal intervals corresponded to time periods used for input of survival rates into standard population models constructed by CDOW. By definition, calf elk became 12-month old yearlings on 15 June and calves surviving to this date were considered to be recruited into the population. For adult elk during time intervals that included hunting seasons, we calculated survival rates inclusive of natural and hunting related mortalities, exclusive of hunting mortalities, and exclusive of natural mortalities. Excluding, or censoring hunting mortalities, provided estimates of natural survival rates, while censoring natural mortalities but including hunting mortalities provided estimates of hunting removal rates calculated as (r) = (1 - s), with (s) being survival rate with natural mortalities censored. Survival rates representing estimates averaged across multiple years or time intervals may have involved individual radioed elk that were common to multiple intervals. In these cases, years or time intervals were considered independent events, and sample sizes were expressed as elk-years or elk-winters reflecting that individual radioed elk contributed to estimates over multiple intervals. Chi-square contingency tests (X2) were used in this segment for initially comparing adult elk survival (alive or dead categories) among sexes, years, cohorts, and DAUs (White and Garrott 1990, SAS 1988 PROC FREQ). Parameter estimates were expressed as means ±95% confidence limits unless otherwise noted. Elk dying of suspected captured-induced trauma were censored from survival estimates. Deaths of calves or adults occurring within I-week of capture were likely to be classed as capture-induced deaths unless field evidence strongly suggested a natural cause of death independent of capture. Captureinduced trauma could affect animals for up to 2-4 weeks post-capture so we routinely attempted to assess whether deaths were potentially capture-induced. We also censored elk having telemetry collars that electronically failed or slipped-off the elk (White and Garrott 1990). Elk with failed or slipped collars were censored for an entire seasonal time interval for binomial survival estimates and will be censored on the date they were last known alive based on telemetry signals in Kaplan-Meier estimates of survival. Elk whose telemetry signals disappeared during hunting seasons continued to be monitored for several subsequent months over large geographic areas until such time these elk were judged to have likely been removed during hunting seasons. Radioed elk that disappeared during hunting seasons were assumed to have been legally harvested. Elk Distribution and Movements During aerial flights to monitor survival status of elk (Table 8), we interpreted telemetry signal strength and direction to judge general locations of each elk. Locations were collected at a level of accuracy deemed sufficient to assess movements of elk among DAUs and GMUs and assess general areas used by elk seasonally. However, we documented locations of elk that made large or unique movements, such as across main highways or DAU boundaries, by obtaining more precise fixes on telemetry signals such that location errors were likely of radius <500 m; elk mortalities were more precisely located to aid recovery of collars from ground surveys. Our data is limited to inferences regarding distribution of elk during daylight hours as flights were conducted between 7 AM and 7 PM Mountain Standard or Daylight Savings time. NOTE: Primary data collection was completed in June 2003 but we were able to incorporate locations of hunter harvested elk during fall 2003 and locations of live elk from December 2003 into this report. �77 We collected written descriptive generalized locations of each radio-collared elk during aerial surveys; i.e, lower Beaver Creek, upper Big Blue Creek, Home Gulch, etc., and stored information in sequentially dated archived files of the RADIOS module of the DEAMAN database (White 1991) that were later compiled for each elk We did not routinely collect refined aerial telemetry locations (Carrel et al. 1997) because oflimited available aircraft-hours and desire to avoid risks of low-level flying in mountainous terrain. To describe macro-spatial distribution of elk, we summarized information for 3 general classes of elk: males radio-collared as calves (MCA) having location observations from age 6-months to maximum age of 42 months (the only males radio-collared were calves, Tables 1,9); adult females (AF) captured as adults (age ~30 months, Tables 1, 10) and located as adults; and, those females radioed as 6-month calves (FCA) that survived until age ~12 months (Tables 4,5, 11) and located to maximum age of 42 months. The span of months an elk survived determined number of locations per elk Descriptions of estimated elk locations were manually input into ArcGIS8® to create a point-coverage shape-file with each point identified by elk radio-collar frequency, sex, age, date, season, and attributed with existing ArcGIS coverages for UTMx and UTMy coordinates (NAD 27), trap-zone, GMU, and DAD. We used locations from 100% of the males to maximize sample size because males had higher mortality rates than females primarily due to higher removal rates during hunting seasons and censoring due to slipped collars. In part to economize data input, we used locations from a random sample of adult females and those female calves surviving to adults (Tables 9, 10). We used restricted random sampling to select AF and FCA with stipulations that within each trap-zone, :::::65%of the AF and FCA would be selected with a minimum sample size of 3 AF and FCA per trap-zone and that each trap-site within a trapzone was represented by at least 1 AF and FCA provided there was a surviving elk from a trap-site. These stipulations assured that estimated distributions of elk reflected a geographically proportioned sample of radioed females among and within DAUs (Tables 9,10). These 3 sets of elk locations were used for all spatial summaries except for elk mortalities which were based on 100% of the elk mortalities (Freddy 2002). We presumed that AF would represent the most stable or habitual patterns of spatial use while MCA and FCA maturing to young adults would represent more variable patterns of dispersing . individuals or individuals establishing their home ranges. We defined seasons as: Winter - 1 December-31 March when snow on the ground was common at all elevations and forage was most restricted in availability and quality; Spring - 1 April-30 May when snow cover was receding from lower to higher elevations and herbaceous forage was progressing from cured to growing status; Summer - 1 June-30 August when forage was green and growing at all elevations; Fall- 1 September-30 November when herbaceous forage was changing from growing to cured status, snow was progressively accumulating from higher to lower elevations, and all regular hunting seasons were ongoing. We summarized locations in June for adult females (AF plus FCA of age ~ 12 months) to identify areas that could be associated with birthing and rearing of young elk calves with most of the June locations obtained during the first and third weeks of June. We recognized the importance of obtaining a random sample of radio-collared elk to reduce bias in assessing spatial use by elk in the Basin (Erickson et al. 2001, Manly et al. 2002). We consider our radio-collared elk to be a sufficiently unbiased random sample of elk in the Basin. First, elk were originally captured using a systematic system stratified to geographic trap-zones and trap-sites with numbers of elk captured in each trap-zone determined apriori to capture and proportionate to documented elk densities and, additionally, efforts were made to avoid capturing multiple elk from any single group of elk (Garton et al. 2001). Second, for female elk captured and radio-collared as calves or adults, we randomly selected a sub-sample of these females again proportioned by trap-zone strata to represent the distribution of female elk in the Basin. For males, we used 100% of the radio-collared elk and therefore �78 relied only on our capture sampling protocols to achieve a random sample. Third, our aerial flights were sufficiently spaced in time to minimize effects of temporal correlation on locations of individual elk (Otis and White 1999) and we obtained locations for nearly all elk during all flights so that each elk provided data. Arguments have been presented regarding individual elk versus elk locations as the appropriate sampling unit (Otis and White 1999, Erickson et al. 2001). To describe spatial distribution of elk, we created maps in ArcGIS8 that pooled elk locations across radio-collared elk and therefore assumed each location was an independent sample unit with inferences limited to the distribution of the population of radio-collared elk in the Basin. We estimated maximum distances and directions elk moved from their original trap-sites and their home ranges during their monitored life-span to represent patterns of spatial use based on individual elk as independent sample units, thereby representing the entire elk population in the Gunnison Basin. We used Spatial Analyst® of ArcGIS8 to calculate maximum movement vectors (MMV) and minimum convex polygon (MCP) year-around home ranges recognizing that MCP were sensitive to location outliers (Kernohan et al. 2001) . Vectors and MCP were calculated only for those elk having 2:.8locations who generally had attained an age 2:.12months. We pooled data among years and therefore presumed no year effects. We caution that location data should not be used to assign importance to elk of micro-habitat types or micro-scale geographic areas. Importantly, areas estimated to have low levels of use by elk based on spatial plots of locations should not necessarily be deemed unimportant but rather may reflect our coarseness of estimated locations. Plots of spatial locations are weighted towards areas used by elk during winter because of the relative seasonal concentration of animals, length of defined winter relative to other seasons, and number of aerial flights conducted (Table 8). RESULTS AND DISCUSSION Sampiing Distribution of Captured Radio-coiiared Elk Proportions of total elk captured and radio-collared within each trap-zone in December 2000 and 2001 generally reflected the proportions of elk counted in each trap-zone within each DAU (Table 2). Large differences in numbers of elk counted among trap-zones within a DAU were adequately reflected by proportions of elk captured in those trap-zones especially in DAUs E-43 and E-41. Limitations on capture imposed by local weather, time, logistics, and daily elk distribution prevented capturing elk in exact proportions to relative estimated numbers of elk. Requiring equal numbers of calves and adult females to be radio-collared for each DAU to meet sample size requirements did not unduly distort the distribution of radio-collared elk relative to numbers of elk counted among DAUs (Table 2). Weather Precipitation in the Basin during summer-fall 2002 was well below average while winter-spring snow depths during 2002-03 approached average for some areas at elevations >3,000 m. Although official NOAA weather data has not been summarized, severe drought conditions generally existed for the Basin and most of southwestern Colorado during 2002 and recent previous years. Large forest fires were common in many parts of Colorado during summer 2002. Based on observations made during summer-fall aerial flights, winter ranges in the Basin were parched during summer and fall 2002 due to lack of rainfall. Extremely dry summer conditions were also evident for alpine ranges where vegetation also looked parched, many high elevation snow-fields became almost non-existent, and in some cases, small alpine lakes were devoid of water. Casual ground surveys �79 at all elevations reinforced the poor production of annual vegetation and the limited sources of water in creeks, lakes, and ponds. In general, the Basin appeared driest in the southeast and east and less dry in the southwest and north-central portions. Subjectively, the summer drought in sub-alpine and alpine ranges surrounding the Basin was worst to least worst in: the La Garita Mountains, Collegiate Peaks, San Juan Mountains, West Elk Mountains, Ragged-Ruby Mountains, and Maroon Bells-Elk Mountains. Some moderation in the drought cycle occurred with rain and snow received in mid-September that may have promoted some vegetation regrowth at mid-elevations. In early November, 20-30 em of snow was received on winter ranges and more at higher elevations, but this snow slowly dissipated from lower elevation open sites as fall progressed into winter. During winter 2002-03, snow depths were generally shallow and seldom exceeded 30 em on most segments of winter range in the Basin based on observations during aerial survey flights. From December through February, many south- and west-facing slopes within sagebrush winter ranges were devoid of snow. Snow had melted from primary winter ranges by late-March to early April. Snow depths by 26 March at elevations >3,050 m, appeared lowest to highest in: the La Garita Mountains, Collegiate Mountains, San Juan Mountains, West Elk Mountains, and Ragged-Ruby-Maroon Bells-Elk Mountains. By 26 April, the snow-line varied between 2,900 and 3,300 m through out the Basin. Winter temperatures were again generally mild for the Basin with daily minimums seldom below -26 C and generally >-18 C and daily maximums often >-6 C. Collar Failures Two radio-collars were censored between 15 June 2002 and 14 June 2003. One female age 13 months (173.681/01), slipped her collar between 17 July and 22 August 2002 apparently because latex snubbers prematurely broke allowing the calf collar to expand and slip over the yearling female's head (see Freddy 2002). The collar on male 175.250/01 was plagued by white-noise frequencies that interfered with detecting the pulse signal from the first day the collar was deployed on 19 December 2001 until 7 February 2003 when the collar was last heard. This collar was considered to have failed electronically. Adult Elk Survival Deaths from hunting were the primary cause of mortalities in adult (age ~12 months) male and female radio-collared elk. Between 15 December 2000 and 14 June 2003,34 adult females died with 32 (94%) deaths attributed to hunting and 2 deaths (6%) from natural causes and, for adult males, 14 died with 11 (79%) deaths due to hunting and 3 (21 %) from natural causes (Appendix C). Hunting also accounted for >90% of the deaths of adult radio-collared elk on the Grand Mesa (Freddy 1998). Adult Female Survival. +During winter-spring intervals, natural survival rates for adult females age ~30 months were ~0.98 ± 0.03 as no mortalities occurred during 2000-01(n = 39) and 2001-02 (n = 48), and 1 mountain lion predation mortality occurred in May 2002-03 (n = 61). For all winter-spring intervals, survival rate was 0.99 ± 0.02 (n = 148 elk-winters). Similarly, natural survival rates for all adult females age ~18 months during 2 winter-spring intervals were ~0.99 ± 0.03 (n = 82, 2001-02, = 86, 200203) and 0.99 ± 0.01 for both winter-spring intervals (n = 168 elk-winters) (Table 3). During summer-fall intervals, natural survival rates for adult females age ~24 months were ~0.97 ± 0.05 in 2001 (n = 37) and 2002 (n = 61), and 0.99 ± 0.02 for both summer-fall intervals (n = 98 elksummers, hunting mortalities censored). The 1 natural death involved a female age 19 years and occurred about 1 July 2001 from unknown causes. Survival rates during summer-fall inclusive of hunting and natural mortalities were 0.92 ± 0.08 and 0.74 ± 0.09 in 2001 (n = 39) and 2002 (n = 82), respectively (Table 3). Similarly, for all adult females age ~12 months, natural survival rates were ~0.99 ± 0.03 in �80 2001 (n = 71) and 2002 (n = 86), and 0.99 ± 0.02 for both summer-fall intervals (n = 157 elk-summers, hunting mortalities censored). Survival rates during summer-fall for all adult females age ~12 months inclusive of hunting and natural deaths were 0.91 ± 0.07 in 2001 (n = 77) and 0.77 ± 0.08 in 2002 (n = 112) (Table 3). Survival rates during summer-fall, inclusive of hunting mortalities, were lower in 2002 than 2001 for adult females age ~24 months (X2 = 5.336, df= 1, P = 0.021) and age ~12 months (X2 = 6.316, df= 1, P = 0.012). Annual natural survival rates for adult females age ~30 months were ~0.97 ± 0.05 in 2000-01 (n = 37) and 2001-02 (n = 33) while survival rates including hunting and natural mortalities were 0.92 ± 0.08 (n = 39) in 2001 and 0.69 ± 0.14 (n = 48) in 2002. For adult females age ~18 months, annual natural survival rates were ~0.97 ± 0.05 in 2000-01 (n = 37) and 2001-02 (n = 61) while survival rates including hunting and natural deaths were 0.92 ± 0.08 (n = 39) in 2001 and 0.74 ± 0.09 (n = 82) in 2002 (Table 3). Annual survival rates, inclusive of hunting mortalities, were lower in 2002 than 2001 for adult females age ~30 months (X2 = 7.277, df= 1, P = 0.007) and age ~18 months (X2 = 5.336, df= 1, P = 0.021). Yearling Female Survival.--During summer-fall intervals, natural survival rates for female elk, age 12-17 months, were l.00 in 2001 (n = 34), 2002 (n = 25), and for both summer-fall intervals (n = 59) as no natural mortalities occurred. Survival rates including hunting mortalities were 0.89 ± 0.10 (n = 38) in 2001,0.83 ± 0.14 (n = 30) in 2002, and 0.87 ± 0.08 (n = 68) for both years as rates were similar between years (X2 = 0.550, df= 1, P = 0.458). During winter-spring intervals, natural survival rates for female elk, age 18-23 months, were l.00 in 2001 (n = 34),2002 (n = 25), and for both winter-spring intervals (n = 59) as no natural mortalities occurred (Tables 4, 5). Over their first year as a young adult, natural survival rates for yearling females, age 12 to 23 months, were l.00 (n = 59) as no natural deaths occurred. Survival rates including hunting mortalities were 0.89 ± 0.10 (n = 38) in 2001,0.83 ± 0.l4 (n = 30) in 2002, and 0.87 ± 0.08 (n = 68) for both years as rates were similar between years (X2 = 0.550, df= 1, P = 0.458) (Tables 4,5). Yearling Male Survival.--During summer-fall intervals, natural survival rates for male elk, age 12-17 months, were 0.90 ± 0.13 in 2001 (n = 21),1.00 in 2002 (n = 23), and 0.95 ± 0.06 for both years (n = 44) as rates were similar between years = 2.295, df= 1, P = 0.130). The two mortalities in July 2001 were from suspected black bear and mountain lion predation. Survival rates including hunting mortalities were 0.86 ± 0.15 (n = 22) in 2001,0.82 ± 0.15 (n = 28) in 2002, and 0.87 ± 0.09 (n = 60) for both years as rates were similar between years (X2 = 0.163, df= 1, P = 0.686). During winter-spring intervals, natural survival rates for male elk, age 18-23 months, were l.00 in 2001 (n = 19),0.95 ± 0.09 in 2002 (n = 22), and 0.98 ± 0.05 (n = 41) for both years as rates were similar between years (X2 = 0.885, df = 1, P = 0.347). The 1 mortality in April 2002 was from suspected mountain lion predation (Tables 4,5). (l Over their first year as a young adult, natural survival rates for yearling males, age 12 to 23 months, were 0.90 ± 0.13 (n = 21) in 2001,0.95 ± 0.09 (n = 22) in 2002, and 0.93 ± 0.08 (n = 43) for both years as rates were similar between years = 0.410, df= 1, P = 0.522). Survival rates including hunting mortalities were 0.86 ± 0.15 (n = 22) in 2001, 0.78 ± 0.17 (n = 27), and 0.82 ± 0.11 (n = 49) for both years as rates were similar between years = 0..596, df= 1, P = 0.440)(Tables 4, 5). (l (l Adult Male Survival.--During summer-fall, natural survival rate for male elk, age 24-29 months, was l.00 (n = 14) and including hunting mortalities, was 0.74 ± 0.22 (n = 19) in 2002. During winterspring, natural survival rate for male elk, age 30-35 months, was 1.00 in 2003 (n = 14) (Table 4). �81 Adult Elk Harvest Removal Male Removal. -- Removal rate (r) for adult males, age 24-29 months and assumed to be legal branch-antlered males, was 0.26 ± 0.22, or 26%, as 5 of 19 were harvested during fall 2002 (Table 4). Wounding loss was 0% of the legal harvest and 80% of the harvest occurred in the third rifle combined season. On the Grand Mesa, removal rate, inclusive of elk wounded, averaged 76% during 1995-99 with a range of 64-92% under similar harvest regulations for branch-antlered males (Freddy 2000). Removal rates for yearling males were 0.05 ± 0.10 in 2001 (n = 20, 1 killed), 0.18 ± 0.15 in 2002 (n = 28,5 killed), and 0.13 ± 0.10 for both years (n = 48) as rates were similar between years ("1..,2 = 1.763, df= 1, P = 0.184) (Tables 4,5). Five deaths were considered wounding/illegal loss and 1 was an illegal harvest because only the radio-collar was found under the ice in a main stream along a road indicating the hunter took possession of the yearling bull. In 2002, all deaths occurred during the third rifle combined season. Five of the yearling bulls had spike antlers with 4 sets of antlers still covered by velvet. On the Grand Mesa, wounding/illegal removal rates of yearling bulls averaged 11% and ranged from 3 to 17% during 1994-97 (Freddy 1997, 1998). Female Removal.-- Removal rates for adult females, age ::::24months, were 0.05 ± 0.08 (n = 38) in 2001 and 0.26 ± 0.10 (n = 82) in 2002 with rate being higher in 2002 ("1..,2 = 6.939, df= 1, P = 0.008). For adult females, age ::::12months, removal rates were 0.08 ± 0.06 (n = 76) in 2001 and 0.23 ± 0.08 (n = 112) in 2002 with rate being higher in 2002 ("1..,2 = 7.523, df= 1, P = 0.006). Removal rates for yearling females, age 12-17 months, were 0.11 ± 0.11 (n = 38) in 2001,0.17 ± 0.14 (n = 30) in 2002, and 0.13 ± 0.08 (n = 68) for both years as rates were similar between years ("1..,2 = 0.550, df= 1, P = 0.458)(Tables 3, 4,5). Wounding loss on adult females, age::::12 months, was 100% of the legal harvest in 2001 (3 harvested, 3 wounded) and 44% of the legal harvest in 2002 (18 harvested, 8 wounded). In 2002,42% of the adult female hunting mortality occurred during the late season and 27% during the third rifle combined season. Wounding losses in 2002 that occurred during all regular hunting seasons represented 36% of the legal harvest during those seasons and, similarly, losses in the late season represented 57% of the legal late season harvest. However, frequency of wounding loss was not different between regular and late seasons ("1..,2 = 0.280, df= I, P = 0.597). Wounding loss for adult females on Grand Mesa averaged between 25 and 30% over 6 years (Freddy 1998,2000). Of the 26 adult females killed in 2002, 13 or 50%, were killed in GMU 55 and the northwestern portion ofGMU 551, representing a core area ofDAU E-43 (Fig. I). This distribution of harvest likely resulted from a combination of major movements by elk coupled with timely snowfall that was advantageous to hunters. By the 31 October aerial flight (Table 8), nearly all radio-collared elk that had previously been in the upper portions of the Taylor River system (northeastern portion ofGMU 55) had moved into South Lottis, Crystal, and East Beaver creeks in the southwestern portion ofGMU 55. This mass movement of radio-collared elk to a relatively small area was not duplicated during October by , radio-collared elk in other portions of the Basin. This concentration of elk then became static and vulnerable to hunters when the large snowfall occurred on 9 November and snow depths persisted well into the late rifle season. Adult Elk Survival By DAU Comparisons in survival rates for adult females between DAUs suggested survival was highest in E-41 and lowest in E-43 for either females age ::::12months or ::::30months(Table 6). During the multi- �82 year interval 15 December 2000 through 14 June 2003, survival in E-43 was lower than E-41 for both age groupings of adult females = 3.793, df= 1, P = 0.052, age 2:12 months; X2 = 3.463, df= 1, P = 0.063, age 2:30 months). Differences in survival between E-25 and E-43 and E-25 and E-41 were not significant for either age grouping of adult females (P 2: 0.138). Differences in survival reflect the comparative impacts or relative success of hunting antlerless elk in these DAUs as there were only 2 natural mortalities of adult females among all DAUs resulting in natural survival rates of 0.92 to 1.00 (Table 6). (l Comparisons in survival rates for adult males between DAUs suggested there were marginal differences in survival, in part due to the insensitivity associated with small sample of radio-collared males (Table 7). During the multi-year interval 15 June 2001 through 14 June 2003, survival of males, age 12-35 months, was not different between all paired combinations ofDAUs E-25, E-43, and E-41 (X2 2.488, df= 1, P 2: 0.115). For males age 12-23 months, differences in survival occurred only between E43 and E-41 (X2 = 3.980, df= 1, P = 0.046). Differences between these 2 DAUs occurred primarily because all natural deaths of yearling males and nearly all illegal wounding loss of yearling males occurred in E-43 (Table 7). :s Calf Cohort to Adult Survival Survival by female and male calves to age 23 months for the year 2000 calf cohort favored females over males by l.3x (0.87 vs 0.66, X2 = 4.540, df= 1, P = 0.033), primarily because of high female calf survival (0.97) compared to males (0.78) (Table 4) whereas survival to age 23 months was nearly equal for both sexes (0.64M, 0.68F) for the 2001 calf cohort as both sexes had similar survival rates as calves (0.84M, 0.82F) and harvest removal rates as yearlings (0.18M and 0.17F) (Table 5). For the 2000 cohort, survival to age 35 months was higher for females (0.72) than males (0.48) (X2 = 4.416, M= 1, P = 0.036). A higher survival for females would be expected because of the potentially high hunting removal rate on males at age 24-29 months when males first become branch-antlered and legal quarry. In 2002,2year old males were removed at an unexpectedly low rate of 0.26 which likely reduced the differential survival between sexes in this cohort. Adult Elk Body Condition Insight into elk nutritional status during fall was obtained from estimates of FMF for recovered wounding losses of adult elk during hunting seasons. For adult females that died during October or November, FMF averaged 97.3% (n = 7) and ranged from 95.9 - 99.0%. These females were 2 -17 years old with 6 collected in 2002 and 1 in 200 l. Yearling females age 16-17 months (n = 2) had average FMF of92.6% which ranged from 85.2-95.2% with both samples from October-November 200l. Yearling males age 17-18 months (n = 4) had average FMF of89.5%which ranged from 86.3-92.2%. Male samples were collected in November (n = 3, 2002) and December (n = 1,2001) (Appendix C). These FMF values suggested elk were replenishing femur marrow fat and achieving minimally adequate body condition status (Mech and DelGiudice 1985) before entering winter. Additionally, hunters who harvested radioed elk provided further insight into elk nutritional status. Hunters (n = 16, fall 2002 only) who harvested radioed elk judged the general health condition of their elk as excellent (56%), good (38%), and fair (6%). Rump fat for adult females (n = 12) was judged plentiful in 25%, fair in 58%, and poor in 17% while adult males, age 24-29 months (n = 2), had poor rump fat (100%). Internal and mesentery fat was judged plentiful in 25 %, fair in 33%, and poor in 42% of the adult females (n = 12) and considered poor in 100% of the adult males (n = 2). These judgments followed the summer of 2002 which was extremely dry when production of forage was relatively poor. As expected, adult males were lean on fat following the rut. The judged fat condition of adult females was highly variable but 75% were rated in fair or poor fat condition. In comparison, for adult females harvested by hunters in December 2000 and 2001 following comparatively more productive forage �83 summers, measurements of kidney fat and subsequent estimates of total body fat for adult females indicated 65% were in moderate and 30% in low body condition status, with 0% rated in very good or excellent condition (Freddy 2002). Collectively, these assessments of body condition suggest that elk in the Basin were subject to marginally deficient levels of seasonal nutrition. Although FMF values were high during fall, the subcutaneous rump and internal and mesentery fat deposits are the fat stores most sensitive in reflecting nutritional condition and are the most important fat stores available to mitigate impacts of nutritional stress during winter and late stages offetal development (Riney 1955, Kistner et al. 1980, Harder and Kirkpatrick 1994, Cook et al. 2001). Few assessments of adult elk body condition during winter and spring were available because few radio-collared elk died. Femur marrow fat was 73.5% in a 22-month old male in April 2003 and 8.6% in a 4-year old female in May 2003. Both deaths likely involved predation by mountain lions (Appendix C). Elk Distribution and Movements Distribution.--Exarnining macro-movements of elk revealed few instances of elk moving north or south across U.S. Highway 50 (Hwy 50) which bisects the Basin from east to west. We therefore divided distribution maps into Gunnison-North, representing elk captured in trap-zones F-J, and Gunnison-South, representing elk captured in trap-zones A-E (see Fig. 1). Importantly, Hwy 50 divided DAU E-43 into segments north and south of this highway. Distribution and movement patterns of elk were based on 1627 elk per class of elk (MCA, AF, FCA) per Gunnison-North or Gunnison-South areas and an average of 26-32 locations per elk for each class of elk representing >3,700 total locations (Table 12). Based on locations, all classes of elk (MCA, AF, FCA) showed relatively high fidelity to areas in the Basin as defined by the collective boundaries ofDAUs E-25, E-41, and E-43 (Figs. 2-4). Exceptions were seen with some elk using areas primarily during spring, summer, and fall in adjacent GMUs 65, 63, 53, and 521 to the west and north, 48, 481, 68, and 681 to the east, and 76 and 79 to the south. Deepest penetration into adjoining GMUs occurred in GMUs 65, 63, 53, 76, and 79. A few AF, FCA, and MCA did move and use areas outside the Basin during winter in GMUs 65, 63, 521,68,681, 76 and 79 (Figs. 24). We realize the following descriptive narratives of areas used by elk cannot be referenced in detail on the maps provided (Figs. 2-27) because providing geographic names on maps was space limited. As such, the narratives will be most useful when maps with geographic references are used in conjunction with the narrative. Maps provide a UTM reference grid which should allow for specific areas of interest to be spatially referenced. Gunnison Elk-North=- AF, FCA, and MCA remained almost exclusively north ofHwy 50 during all seasons. AF leaving the Basin most commonly ventured into GMU 63 and 53 to the west (Fig. 5). FCA followed similar patterns with elk venturing into GMUs 63, 53, and GMU 521 to the west and north and additionally, to the east into 481 (Fig. 6). MCA followed similar patterns but with apparently much of the dispersed activity focused into GMUs 53 and 521 to the northwest with a few elk venturing into GMUs 63 and 411 to the west, 43, 471, and 48 to the north, and 76 and 79 to the south (Fig. 7). Areas used during winter by elk within each trap-zone were: trap-zone F, Dawson Ridge-Hom Gulch, Tomichi Dome, Greathouse Gulch-Yellowpine Ridge, Wood Gulch, lower Hot Springs Creek; trap-zone G, lower Gold to lower Alder creeks, Roundup Basin, Cabin and East Cabin creeks and Sheep Gulch, Lost Canyon, Fisher, and Tepee gulches, Beaver-East Beaver creeks, Almont Triangle, Roaring Judy Creek-Round Mountain, lower Cement Creek; trap-zone H, areas surrounding Flattop Mountain to lower Carbon Creek; trap-zone 1, lower West Antelope and Antelope creeks, Steers Gulch, lower Beaver, Steuben, and Dry creeks; trap-zone J, lower East Elk Creek, Dry Gulch, Tenderfoot Mesa, lower Red, �84 West Elk, Coal, and Soap creeks (Figs. 5-7). Areas used during spring by elk within each trap-zone were: trap-zone F, Tomichi DomeWaunita Park with suspected movement corridors to summer ranges associated with Waunita Pass-Little Baldy Mountain and Triano-Canyon creeks to upper Quartz creeks; trap-zone G, Beaver-East Beaver, Threemile, and Fivemile creeks, east of Taylor Reservoir from Willow to Illinois creek, Almont TriangleRoaring Judy Creek, lower Cement and Brush creeks, with suspected movement corridors to summer areas lying between Spring and Summerville creeks along the Taylor River canyon for elk moving north or northeast from winter ranges and a corridor passing through Crystal, South Lottis, and Lottis creeks for elk moving northeast and east; trap-zone H, western portions of Red Mountain from Willow Creek to Carbon Peak in lower Carbon Creek with a diffuse movement corridor through branches of Carbon Creek to Gibson Ridge and Mt. Axtell; trap-zone I, upper West Antelope Creek, middle elevations of Squirrel, Castle, Pass, Beaver, Steuben, and Willow creeks with a movement corridor from upper West Antelope through lower Castle Creek to Pass Creek; trap-zone J, middle elevations of Dry Creek to Red Creek, pronounced use of areas near Little and Big Soap parks in Soap Creek, and in adjoining Coal Basin in GMU 53, with a suspected movement corridor from lower West Elk and Soap creeks through Soap parks to upper West and main Soap creeks to Coal Basin and Soap Basin (Figs. 5-7). Areas used during summer by elk within each trap-zone were: trap-zone F, upper Dawson Ridge to Triano Creek, upper South and Middle Quartz creeks, Granite Mountain, Tomichi Pass, upper Chalk Creek, Waunita Pass-Little Baldy Mountain; trap-zone G, upper East Beaver and Crystal creeks, Union Park-Lottis Creek, areas east and northeast of Taylor Park Reservoir through Willow, Texas, Illinois, Pieplant, Red Mountain, Tellurium, and Pine creeks, upper Sayres Gulch of Lake Creek, Trail, South Italian, and Italian creeks and headwaters of Taylor River, upper Cement and Brush creeks, Dry Basin, Copper Creek, upper Slate River, and Oh-Be-Joyful Creek; trap-zone H, Red Mountain, upper Carbon Creek, Whetstone Mountain, Gibson Ridge, Mt. Axtell; trap-zone I, upper Pass, Castle, and branches of Beaver creeks; trap-zone J, West and upper Soap creeks and Soap Basin, with adjoining areas in Coal Basin, and Coal, Robinson, and Cliff creeks in GMU 53, and upper Curecanti, Crystal, and Dyer creeks in GMU63 (Figs. 5-7). Areas receiving use by female elkin June may be of importance to successful rearing of calves and these areas should receive further surveillance as to their importance to elk reproduction (Fig. 11). Areas of interest within each trap-zone were: trap-zone F, Waunita Park, upper South Quartz and upper Tomichi creeks; trap-zone G, upper East Beaver Creek, Union Park, east of Taylor River from Texas Creek north to Pine Creek, upper East Brush Creek; trap-zone H, western slopes of Red Mountain, Carbon Creek and Carbon Mountain; trap-zone I, confluence of North and South Castle creeks, upper Pass Creek; trap-zone J, upper East Soap and West Elk creeks, Big Soap Park, and Coal Creek to Spruce Draw within Coal Basin in adjacent GMU 53. Areas receiving focused use by elk during fall were difficult to identify because elk movements were diffuse and likely heavily affected by hunting seasons from September to December. However, some elk in trap-zones F and G appeared more prone to move to areas near winter ranges than did elk in trap-zones H-J, especially to areas near Tornichi Dome (trap-zone F) and East Beaver Creek (trap-zone G) (Figs. 5-7). Maximum movement vectors (MMV) and year-around home ranges (MCP) revealed general patterns of movement for the elk population north of Hwy 50. Directions moved by AF and FCA for each trap-zone were (Figs. 13, 14, 19,20): trap-zone F, elk moved northeast to summer ranges generally within the confines ofGMU 551 north ofHwy 50; trap-zone G, elk from southern trap-sites moved relatively long distances north-northeast into the upper Taylor River and Collegiate Peaks areas, while elk from the northern Almont trap-sites moved north-northwest with elk from both areas generally remaining within GMU 55 with the exception of an elk moving southwest across Hwy 50 into GMU 67; trap-zone H, elk moved north, west, and southwest frequenting both DAUs E-41 and E-43; trap-zone I, elk moved �85 northwest to northeast frequenting both DAUsE-41 and E-43 and leaving the Basin into GMU 53 and 521 with the exception of an elk moving southeast across Hwy 50 into GMU 551; trap-zone J, elk moved from north to west commonly leaving the Basin into GMUs 53 and 63. Directions moved by MCA were similar to AF and FCA for each trap-zone but MCA often traveled further outside the Basin into adjoining GMUs including one long-distance movement south across Hwy 50 into GMUs 76 and 79 (Figs. 15,21). From 37% to 55% of elk in each class ventured into GMUs outside the Gunnison-North area during their seasonal movements with estimated rates of dispersion similar for MMV and MCP metrics (Table 13). However, MCP documented elk moving into GMUs not detected by MMV probably because MMV were limited to one data point per elk whereas MCP incorporated multiple data points per elk. Estimated rates of movement to outside GMUs were highest for MCA and FCA. Movements were most frequent to the west and northwest into GMU 53 by AF, FCA, and MCA primarily by elk from trap-zones I and J (Figs. 13-15). MCA demonstrated a greater tendency to venture into more outside GMUs than did AF or FCA (Table 13). One elk from each of the AF, FCA, and MCA classes moved south and crossed Hwy 50 between Gunnison and Sargents, Colorado indicating up to 5% of the Gunnison-North elk may move south across Hwy 50 (Table 13). For MCA, 38% of the legal hunting harvest (6 of 16) occurred in outside GMUs, primarily in 63,53, and 521 (Fig. 27). Maximum distances (MMV) moved were similar among elk classes (F = 1.08 2.83, P = 0.342) and averaged 32.3 km for AF, 37.6 km for FCA, and 38.5 km for MCA (Table 14). Extreme distances moved were III km by MCA and 65 km for FCA. Young male and female elk, as expected, were responsible for longest movements likely reflecting aspects of dispersal or exploratory behavior and therefore, most likely to promote genetic interchange with other elk populations. Maximum distances (MMV) moved by all classes of elk occurred primarily during summer (67-70%) and fall (12-21 %) and probably reflected migrations to summer ranges and possibly, responses to hunting seasons during fall. Maximum movements that occurred during winter for FCA and MCA (6-7%) usually indicated elk moved to winter ranges distant from the original trap-site winter range which occurred more rarely for adult females (Table 15). Overall, MMV and MCP of all elk revealed a progressive interaction among spatially adjoining segments of the elk population from east to west but with little interchange between extreme eastern and western segments of elk inhabiting areas north ofHwy 50 (Figs. 13-15, 19-21). Somewhat discrete movement patterns suggested that segments of the elk population could be specifically targeted for harvest in specific geographic areas either during regular or late hunting seasons. Also, elk movements indicated corridors of interaction between Basin elk and elk populations to the east, north, and west. Notably, comparable studies of elk movements on the Grand Mesa (Freddy 1997,1998) and Gunnison Basin (this project) have documented interchange between these large elk populations involving both male and female elk that moved between populations via corridors in GMUs 53 and 521 that would allow for genetic linkage of elk in GMUs 54 and 55 (Gunnison Basin) with elk in GMU 42 (Grand Mesa) south of Rifle, Colorado. Comparisons with Previous Studies.-- From 1978 through 1981, distribution and movements of elk in the north-central portion of the Gunnison Basin were documented by 2 graduate student projects (Young 1982, Wright 1983). These graduate projects were prompted by proposals to construct a large molybdenum mine complex north of Gunnison (not constructed as of2003) and focused on elk inhabiting areas north of U.S. Highway 50 between Quartz Creek on the east and Soap Creek on the west, which equated to portions of Gunnison Elk-North or trap-zones G-J (Fig. 1) in the current elk project. Both of these projects obtained spatially precise aerial relocations of radio-collared elk which provided detailed summaries of areas and movement corridors used by elk. Information from these projects plus the current project documented patterns in elk movements that apparently have persisted for at least 20 years. Here, I briefly summarize these patterns. For reference, I summarized results of these graduate projects according to the definitions of seasons used in the current elk project: Winter - 1 December-31March; �86 Spring - 1 April-30 May; Summer - 1 June-30 August; Fall - 1 September-30 November; and, June was considered to be inclusive of calf birthing and rearing. Gunnison Elk-North 1978-1981.-- During winters 1978-79 and 1979-80, snow depths approaching 1 m on some winter. ranges along with cold temperatures prompted emergency feeding of mule deer and elk and these conditions constrained areas used by elk (Young 1982) much more so than during 2000-2003. In spite of these harsh winter conditions, areas used by elk as outlined by Young (1982:44,45) were remarkably similar to areas used by elk in winters 2000-2003, allowing for elk to be at slightly higher elevations because of comparably reduced snow depths during winters 2000-2003 (Figs. 57). Areas used during winter by elk as noted by Young (1982:39-42, 44-45) within trap-zones of the current project were: trap-zone G, lower Cabin Creek and Sewell Gulch, and the Almont Triangle; trapzone H, areas west and southwest of Flattop Mountain; trap-zone I, lower Steuben and Beaver creeks; and trap-zone J, lower Red Creek and Dillon Mesa. During spring 1979 and 1980, above average snow depths likely retarded or hindered movements of elk from winter areas to areas used during spring. However, descriptions of areas used in spring 1979 and 1980 were similar to observations in 2000-2003 (Young 1982:39-42, 51-52) (Figs. 5-7). Areas used during spring (Young 1982) within the current trap-zones were: trap-zone G, upper Cabin creeks and Lost Canyon Gulch and from the Almont Triangle to Round Mountain; trap-zone H, west and north of Flattop Mountain along with the western slopes of Red Mountain; trap-zone I, from Beaver Creek northeast through Antelope and Mill creeks; trap-zone J; areas near Red Creek. During April and May, Young (1982:32-35) found elk to make noticeable movements upward in elevation as was also observed during 2000-2003 (Freddy 2002:205). Corridors used by elk during these movements in spring towards summer areas as described by Young (1982:46-50) were similar to general movements observed during the current project. Spring movement corridors according to Young (1982) within current trap-zones were: trap-zone G, from Cabin creeks and Lost Canyon Gulch into Beaver-East Beaver creeks, from Beaver-East Beaver creeks north into upper Spring Creek, Matchless Mountain, Italian creeks, and upper Taylor River, and to areas east and northeast in Union Park and Taylor Park, and then also from Almont Triangle north to Brush Creek; trap-zone H, from Flattop Mountain north to Red Mountain and onto Mt. Axtell, Gibson Ridge and Whetstone Peak with some elk moving towards Kebler Pass; trap-zone I, from Beaver Creek north to Mill, Castle, and Pass creeks; trap-zone J, from Red Creek west and north into Soap Creek. During summer, areas used by elk as documented by Young (1982:39-42) and Wright (1983:39, 41) were similar to areas used during summers 2000-2003 (Figs. 5-7). Areas used according to Young (1982) and Wright (1983) within current trap-zones were: trap-zone G, an extensive area from Fossil Ridge to Taylor Park, to upper Taylor River and Italian creeks, and to Brush creeks near the town of Gothic; trap-zone H, from Red Mountain to Mt Axtell and Whetstone Peak and near Ohio and Kebler passes; trap-zone I, areas in upper Beaver, Mill, Castle, and Pass creeks and upper Anthracite Creek; trapzone J, upper Soap and West Elk creeks and north into Robinson, Kaufman, and Cliff (GMU 53) creeks. Most drainages on the eastern and western flanks of the West Elk Mountains were used by elk in summer according to Young (1982) and Wright (1983). Both Young (1982:30-35) and Wright (1983:31-37) documented elk at highest elevations in sub-alpine and alpine areas from late June to early August which was similar to observations in 2000-2003 (Freddy 2002:205). Areas used and associated with calving during June as noted by Young (1982:39-42) and outlined by Wright (1983:25,30) were similar to distribution of elk in June 2000-2003 (Fig. 11). Areas used by elk (Young 1982, Wright 1983) within current trap-zones were: trap-zone G, a large diffuse area inclusive of Beaver-East Beaver creeks, Fossil Ridge, Union Park, Taylor Park, Italian creeks, Brush creeks, and Spring Creek with observations in 1979 and 1980 (Young 1982) suggesting elk calved in areas near Round Mountain near Almont, Rosebud Gulch of Spring Creek, and areas near Matchless mountains possibly because melting of the snow-pack was delayed by cooler temperatures and overall greater snow-depths resulting in elk moving shorter distances in these years than in 1981 (Wright 1983) �87 or 2000-2003 (Fig. 11); trap-zone H, Red Mountain, especially the western slopes, and Mt. Axtell north to Coal Creek; trap-zone I, from upper Antelope creeks, through Mill, Castle, and Pass creeks to Swampy Pass; trap-zone J, upper West Elk Creek, areas near Big Soap Park and Soap Basin in upper Soap Creek, and north into Kaufman and Robinson creeks (GMU 53). During fall, Wright (1983) focused attention on distribution and movements of elk in relation to timing of hunting seasons. During fall 1980 and 1981(Wright 1983: 124-137), distribution of elk encompassed an extensive area including portions of summer, spring, and upper winter ranges similar to observations in 2000-2003 (Figs. 5-7). Straight-line distances traveled by elk and downward shifts in elevations used by elk were most pronounced during and following the first rifle elk season (:::::10-20 October, Wright 1983:142-147). In response to rifle seasons, areas that elk moved into (Wright 1983) within current trap-zones were: trap-zone G, from upper Taylor River and Italian creeks south into Spring Creek, Matchless mountains, and Beaver-East Beaver creek, and from Taylor and Union parks southwest into Beaver-East Beaver creeks; trap-zone H, from Mt. Axtell and Whetstone Peak south to Red and Flattop mountains; trap-zone I, from Pass and Castle creeks south into Mill, West Antelope, and Beaver creeks; trap-zone J, from Kaufman Ridge and Cliff Creek (GMU 53) south into Cow and Coal creeks of lower Soap Creek and West Elk Creek. The tendency for elk in trap-zone G to make long movements during rifle seasons to areas associated with Beaver-East Beaver creeks (Wright 1983) remained apparent in 2000-2003 (Figs. 5-7). Movement corridors used during spring and fall by elk as illustrated by Wright (1983:56,59) and noted by Young (1982) agreed with observations in 2000-2003. Within the current trap-zone G, Wright (1983:59) noted multiple movement corridors for fall movements. Elk from upper Taylor River, Italian creeks, upper East River and Brush creeks moved south via portions of Spring and Roaring Judy creeks to the Almont Triangle and Beaver-East Beaver creeks while elk from northeast and southeast of Taylor Park Reservoir moved through Matchless mountains or Lottis creeks into Crystal Creek and eventually to Beaver-East Beaver creeks and on south into Cabin creeks. Both of these corridors required elk to cross the Taylor River canyon and highway between Almont Triangle and Crystal Creek. In trap-zone H, Wright (1983:56) showed elk moving relatively short distances from Mt. Axtell, Gibson Ridge, and Whetstone Peak south to areas around Flattop Mountain which was also documented by Young (1982). In trap-zone I, elk moved from Swampy Pass and Pass Creek of upper Ohio Creek south through Castle, Mill, and Antelope creeks to reach winter ranges in lower Antelope and Beaver creeks. In trap-zone J, elk moved from Robinson and Cliff creeks (GMU 53) south through upper Soap Creek and down Soap and West Elk creeks to winter ranges associated with lower Soap, Red, and West Elk creeks. Young (1982:87) described similar corridors for both spring and fall movements of elk in trap-zones I and J as areas flanking the west and east sides of the West Elk Mountains that were often associated with aspen vegetation. Differences among Projects 1978-1981 and 2000-2003.-- Distribution and movements of elk documented by Young (1982) and Wright (1983) were primarily based on movements of adult female elk. The current study (Freddy 2002) benefited from capturing elk over a broader range of trap-sites the within Gunnison Elk-North area that were located from Tomichi Dome on the east to Soap Creek on the west (Fig. 1) and from radio-collaring 6-month old male and female calves in addition to radio-collaring adult female elk. These calves, as they became 12-18 months of age, were responsible for many of the wideranging movements that indicated Gunnison Elk-North interacted with elk in areas to the east, north, and west of the main Gunnison Basin (GMUs 56, 481, 48, 471, 43, 521, 53, 63, Table 13, Figs. 13-15, 19-21). This interchange was likely also occurring, at least to some degree, from 1978 to 1981, but Young (1982) and Wright (1983) may have been less able to document such movements because adult female elk were less likely to disperse to out-lying areas. However, as was observed in 2000-2003, Wright (1983:23) documented interchange in the upper Taylor River with elk to the north in GMUs 43 or 471 and noted movements of elk north during summer into GMU 53 (Kaufman Ridge) while Young (1982:61) noted elk moving into upper Anthracite creek (GMU 521). Neither author documented movement of elk to the west into GMU 63 as was observed in 2000-2003. �88 Gunnison Elk-South,« AF, FCA, and MCA remained exclusively south ofHwy 50 during all seasons. We did not detect movement to the north across Hwy 50 by elk from trap-zones A through E. AF and FCA leaving the Basin were detected in GMU 65 to the west; GMU 76 to the south, and GMUs 68 and 681 to the east (Figs. 8, 9). MCA generally stayed within the Basin except for some movement into adjoining GMUs 68 and 681 to the east and 76 to the south (Fig. 10). Areas used during winter by elk within each trap-zone were: trap-zone A, areas west and adjacent to the Lake Fork of the Gunnison River including Willow Mesa to upper Willow and Little Willow creeks and Round Mountain, Campbell to Narrow Grade and Elk creeks, Well Gulch to Bill Hare Gulch,with some female elk using areas in adjoining GMU 65 in the lower Cimarron River associated with the Cimarron State Wildlife Area and in Cow and Owl creeks east of Ridgway; trap-zone B, Carpenter Ridge to Kezar Basin and lower Wolf Creek with adjoining areas in lower Cebolla Creek, areas east and adjacent to the Lake Fork of the Gunnison River including Lake Gulch, Red Bridge to Dutch Gulch, and adjoining lower elevations of Indian Creek, Yeager Gulch, Trout, Skunk, Fourth of July, and Devils creeks, Sparling Gulch near Lake City, Colorado, lower Powderhorn Creek, and Calf and Rough creeks of upper Cebolla creek with disjunct activity in Shallow and Fir creeks near Creede, Colorado to the south in adjoining GMU 76; trap-zone C, mid-lower elevations from South Beaver Creek west through Pole, Sugar, Camp, and Willow creeks, and Huntsman Mesa and Willow Creek south into the Road Beaver creeks; trap-zone D, lower and upper Long Gulch including Dutch Gulch and Green Mountain, lower Bead Creek to Rock Creek, Alkali Creek to Homestead Gulch, Poison Ridge to Cold Spring and Burro parks, and Cochetopa Dome with some elk venturing east into lower Sheep, Fourmile, and branches of Luders creeks in adjoining GMUs 68 and 681; trap-zone E, areas surrounding Table Top Mountain, Camp Kettle Gulch, lower elevations of Razor Creek and adjoining northwest, west, and southwest portions of Razor Dome, and lower elevation branches of Home, Myers, Wolverine and Stag gulches (Figs. 8-10). Areas used during spring by elk within each trap-zone were: trap-zone A, areas west of the Lake Fork of the Gunnison River in upper Little Willow and Willow creeks and from Dwyer Gulch to Elk Creek, areas adjacent to Blue Mesa and lower Little Blue creeks along with lower Pine Creek, and areas near the Cimarron State Wildlife Area to the west in GMU 65 with suspected movement corridors from Elk Creek into Big Blue Creek and from Willow Mesa west towards Blue Mesa and then south towards the Alpine Plateau; trap-zone B, east of the Lake Fork of the Gunnison River from lower Indian Creek to Yeager Gulch and Trout Creek, Big Buck Creek to Fourth of July and Devils creeks, and lower Calf Creek and Fish Canyon Ridge in upper Cebolla Creek with suspected movement corridors from Fourth of July Creek to Waterdog Lake and then east to Calf Creek Plateau or south into Rambouillet Park; trapzone C, upper Sugar Creek to lower Camp Creek, Willow Creek from Soderquist Reservoir to Rock Creek Park, and Rock Creek and Summit parks; trap-zone D, Alkali Creek to Homestead Gulch, areas adjacent to Sorro and Elk Parks, Cochetopa Dome and Park; trap-zone E, areas south of Razor Dome and into Home Gulch, Razor Creek lower to upper parks, branches of Barret and Needle creeks, lower Dutchman and Hicks creeks with a suspected movement corridor from Razor Creek to Long Branch Creek (Figs. 8-10). Areas used during summer by elk within each trap-zone were: trap-zone A, Blue Mesa along with segments of lower Pine, Little Blue, and Middle Blue creeks, upper Willow, Pine, and Little and Middle Blue creeks along the Alpine Plateau, alpine and sub-alpine areas of upper Big Blue and Fall creeks, upper El Paso and Nellie creeks and Sunshine and Gravel mountains in Henson Creek, and High Mesa and Firebox Creek areas of the Little Cimarron River in adjoining GMU 65 used by some female elk; trap-zone B, upper Fourth of July and Devils creeks, upper Trout Creek, Waterdog Lake area, Cannibal Plateau, Calf Creek Plateau, Calf, Brush, and Deer creeks, and in adjoining GMU 76 in upper West Willow and Rat creeks north of Creede, Colorado, Rito Hondo and Big Buck creeks and Pole Creek Mountain in the upper northwestern portions of the Rio Grande River; trap-zone C, upper East Beaver, Deer Beaver, Monument, and South Beaver creeks, and upper Rock and Monument Rock creeks; trap- �89 zone D, Pauline Creek west through Elk and Blue parks to Los Pinos Pass and upper branches of Los Pinos Creek with some elk moving east into upper Luders and East P~ss creeks in adjoining in GMU 68; trap-zone E, upper Home Gulch-Green Mountain, areas adjacent to lower and upper Razor Creek parks, branches of upper Needle Creek, lower to upper Long Branch creek, and upper Indian and Marshall creeks (Figs. 8-10). Areas receiving use by female elk in June (Fig. 12) that should receive further surveillance as to their importance to elk reproduction were: trap-zone A, Blue Mesa and lower Big, Middle, and Little Blue creeks and adjoining Pine Creek, subalpine in upper Big Blue Creek; trap-zone B, Waterdog Lake area, mid- to upper elevations of Calf and Brush Creeks and Calf Creek Plateau; trap-zone C, upper portions of Monument, Rock, and Monument Rock creeks; trap-zone D, Sorro to Blue parks in Pauline Creek; trapzone D, areas near lower and upper Razor Creek parks. Distribution of elk in the fall was diffuse, again likely because of hunting seasons, but there were some areas of focused use: trap-zone A, lower Pine and Little Blue creeks near Blue Mesa, and upper Big Blue and Fall creeks; trap-zone B, Trout Creek and Yeager Gulch; trap-zone C, East Beaver Creek; trapzone D, Elk Park to Los Pinos Pass, upper Alkali Creek and Homestead Gulch; trap-zone E, Long Branch Creek, Razor Creek parks, and upper Home Gulch to Green Mountain with some indication that elk in this trap-zone were prone to move sooner to areas near winter ranges (Figs. 8-10). Maximum movement vectors (MMV) and MCP revealed patterns of movement for the elk population south ofHwy 50. Directions moved by AF and FCA for each trap-zone were (Figs. 16, 17, 22,23): trap-zone A, elk moved west, southwest, and east with some activity outside the Basin in adjoining GMU 65 ; trap-zone B, elk moved primarily south to west with activity into adjoining GMUs 65 and 76; trap-zone C, elk moved southeast to southwest with movements outside the Basin into adjoining GMUs 65 and 76; trap-zone D, elk moved southeast to southwest with movement into adjoining GMUs 68 and 76; trap-zone E, elk moved from east to southwest with some activity into GMUs 681 and 68. Directions moved by MCA were similar to AF and FCA for each trap-zone with MCA in trap-zone C exhibiting the widest array of directions moved (Figs. 18,24). Travel by MCA outside the Basin was east into adjoining GMUs 681 and 68 and south into GMU 76. From 25% to 62% of the elk ventured into GMUs outside of the Gunnison-South area during their seasonal movements with estimated rates of dispersion higher for MCP than MMV (Table 13). Movements to the east and west by AF, FCA, and MCA into GMUs 68 and 681, and 65, respectively, were most frequent and associated with elk from all trap-zones A-E (Figs. 16-18). MCA and FCA demonstrated a greater tendency than AF to venture into outside GMUs (Table 13). No elk were detected north ofHwy 50 indicating that :::::0%of the Gunnison-South elk move north across Hwy 50 (Table 13). Maximum distances (MMV) moved were similar among elk classes (F= 0.052 2,46, P = 0.949) and averaged 34.8 km for AF, 33.4 km for FCA, and 34.8 km for MCA (Table 14). Extreme distances moved were 62.5 km by MCA and 78.5 km for FCA. Young male and female elk were again responsible for longest movements. Maximum distances (MMV) moved by all classes of elk occurred primarily during summer (42-57%) and fall (8-25%), again reflecting migrations to summer ranges and potential responses to hunting seasons during fall. Maximum movements that occurred during winter for FCA and MCA (19-33%) usually indicated elk moved to winter ranges distant from the original trap-site winter range (Table 15). Observed elk movements indicated a mixing and continuous flow of elk from east to west among adjoining segments of the elk population within GMUs 67 and 66 (DAU E-25) and some interaction among elk in GMU 67 with elk to the east in the adjoining southern half of GMU 551 (DAU E-43) and among elk in GMU 67 with elk to the west in GMU 65 (Figs. 16-18,22-24). Elk trapped in GMU 551 south ofHwy 50 remained within the southern portion ofGMU 551 or associated with elk in GMUs 681, �90 68, and 67 rather than interacting with elk north ofHwy 50. Movements indicated interaction among elk in the Basin south ofHwy 50 with elk in GMUs 681, 68, 76, and 65. Elk Distribution and DAU Boundaries=- Distribution and movements of Gunnison Basin elk provide a basis for assessing the adequacy of current DAU boundaries. DAU boundaries reflect attempts to compartmentalize elk into populations that can be managed as relatively closed demographic units based on patterns of elk distribution and harvest while GMU boundaries serve primarily to distribute hunter numbers and hunting effort among segments of elk populations. Dividing the Basin into DAUs north and south ofHwy 50 could be considered as interchange of elk across this highway was low. Merging DAU E-43 with DAU E-41 north ofHwy 50 could be considered as there was a continuous mixing of elk from east to west across this geographic area. Additionally, the interaction with elk in GMUs 53 and 63 suggest these areas to the northwest and west of the Gunnison Basin could be incorporated into one large DAU that would merge elk in the North Fork of the Gunnison River with elk in the Gunnison Basin. Historically, Young (1982:65) and Wright (1983:23) concluded there were 3 sub-populations of elk (noted as EA, DA, WA) in the area of their studies within the Gunnison Elk-North area. These subpopulations, defined from east to west, were bounded by: from Quartz Creek west to the East and Gunnison rivers (EA) which corresponded to current trap-zone G; from the East and Gunnison rivers west to Ohio Creek (DA), which corresponded to current trap-zone H; and, from Ohio Creek west to Soap Creek (W A), which corresponded to current trap-zones I and J (see Fig. 1). Interchange of marked elk among these 3 sub-populations was low and the interchange that did occur was primarily during hunting seasons when elk were disturbed by human activity (Young 1982, Wright 1983). Wright (1983:179) recommended creating a separate GMU for the DA area (trap-zone H) to allow for more specific population management. Movements and distribution of elk during 2000-2003 tended to reinforce this general pattern of interchange among sub-population areas except that the current study documented more interchange on summer ranges in the north-central portion of the Gunnison Basin (Crested Butte to Kebler Pass) between elk trapped in trap-zone H with elk trapped in either trap-zones G or I (Figs. 13-15, 19-21). Young (1982:60) also showed some overlap during summer in the Kebler Pass area between current trap-zone H and I elk. Although some spatial separation does continue to exist among these 3 sub-populations of elk, current distribution and movements of elk north ofHwy 50 would suggest that all 3 sub-populations should be in the same meta-DAU population (Figs. 19-21). Current DAU boundaries for elk south of Hwy 50 could be modified to add GMU 551 south of Hwy 50 to E-25. Consideration should be given to adding GMU 65 or the Cimarron River portion of this unit to DAU E-25. Distribution of Elk Mortalities. --Mortalities of calves (n = 21) were scattered throughout the Basin (Fig. 25, Appendices A, B, Freddy 2002). Incidents of predation or suspected predation were often associated with mountain lions and frequently occurred within spatial proximity of each other within trapzones A, B, C, and J. Incidents of malnutrition were detected in trap-zones A, F, I, and J. Clustering of 4 mortalities in lower Soap-Coal creeks (trap-zone J) was associated with mountain lion activity. Mortalities of adult females (n = 40) were almost exclusively due to hunting (95%) and were scattered throughout the Basin (Fig. 26, Appendix C). Relative clustering of hunting mortalities occurred in southwestern portion oftrap-zone G involving Cabin, East Beaver, Lost Canyon creeks, and in trapzone F from Yellow Pine ridge to Lookout Mountain. Notable outlier deaths occurred in GMU 681 to the southeast, GMU 76 to the south, and GMU 63 to the west. The 1 incident of predation was attributed to mountain lion which occurred in proximity to lion predation on a calf (trap-zone E, Figs. 25, 26). Mortalities of adult males (n = 26) were primarily due to hunting (88%) and occurred mainly in trap-zones G through J and north ofHwy 50 (Fig. 27, Appendix C). Adult males were harvested outside �91 the Basin in adjacent northern GMUs 63, 53, and 521. Notable outlier deaths occurred in GMU 48 to the northeast, GMU 681 to the southeast, and GMU 411 to the northwest. Clustering of hunting mortalities occurred in areas near East Beaver-Cabin creeks in trap-zone G. Four of five illegal hunting incidents involving yearling male elk occurred in trap-zone G and all deaths involving suspected predation by bears or mountain lions (n = 3) occurred in trap-zone G (Fig. 27). SUMMARY Natural survival rates for adult elk in the Gunnison Basin were ?:.97% for females and ?:.90% for males for all elk ages and seasonal intervals examined between December 2000 and June 2003 with results mimicking natural survival rates estimated for elk on Grand Mesa during 7 consecutive years from 1993 to 2000. Hunting removal rates on adult females increased in 2002 over 2001 reflecting attempts to liberalize the harvest of antlerless elk. In 2002, the adult female removal rate of 23 % likely stabilized or reduced population growth for one year. The illegal harvest/wounding loss rate of 13% on yearling spikeantlered elk was similar to the 11% rate documented for yearling male elk on Grand Mesa. . Wounding loss on adult females was 44% and commensurate with the high rate of 25-30% documented on Grand Mesa. Assessments of adult female elk body condition suggested marginally deficient levels of nutrition during 2002. Distribution and movements of radio-collared elk suggested DAU population boundaries might be altered. Patterns of dispersion suggested movement corridors that would allow for genetic linkage between Gunnison Basin and other elk populations. LITERATURE CITED Anderson, e.R, Jr., D.S. Moody, B.L. Smith, F.G. Lindzey, and R. P Lanka. 1998. Development and evaluation of sightability models for summer elk surveys. Journal of Wildlife Management 62:1055-1066. Bartholow, J. 1999. POP-II system documentation Windows™ Version 1.0. Fossil Creek Software, Fort Collins, Colorado USA. Bear, G.D., G.e. White, L.H. Carpenter, RB. 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Freddy, DJ. 2002. Estimating calf and adult survival rates and pregnancy rates of Gunnison Basin elk. Colorado Division of Wildlife Research Report July: 191-222. Fort Collins, Colorado USA. Freddy, DJ., D.L. Baker, RM. Bartmann, and RC. Kufeld. 1993. Deer and elk management analysis guide, 1992-1994. Colorado Division of Wildlife Division Report 17, Fort Collins, Colorado USA. Garton, E.O., M.J. Wisdom, F.A. Leban, and B.K. Johnson. 200l. Experimental design for radiotelemtry studies. Pages 15-42 in J. J. Millspaugh andd J. M. Marzluff, editors. Radio tracking and animal populations. Academic Press, San Diego, California, USA. Haigh, J.C., and RJ. Hudson. 1993. Farming wapiti and red deer. Mosby, Saint Louis, Missouri, USA, pages 187-192. Harder, J.D., and RL. Kirkpatrick. 1994. Physiological methods in wildlife research. Pages 275-306 in T.A. Bookhout, editor. Research and management techniques for wildlife and habitats. Fifth edition. The Wildlife Society, Bethesda, Maryland, USA. Kernohan, B. J., R A. Gitzen, and J. 1. Millspaugh. 200l. Analysis of animal space use and movements. Pages 125-166 in 1. J. Millspaugh andd 1. M. Marzluff, editors. Radio tracking and animal populations. Academic Press, San Diego, California, USA. Kistner, T.P., C.E. Trainer, and N.A. Hartmann. 1980. A field technique for evaluating physical condition of deer. Wildlife Society Bulletin 8: 11-17. Lewis, R1., G.A. Chalmers, M.W. Barrett, and R Bhatnagar. 1977. Capture myopathy in elk in Alberta, Canada: a report of three cases. Journal of The American Veterinary Medical Association 171: 927-932. Manly, FJ., L.L. McDonald, D.L. Thomas, T.L. McDonald, and W.P. Erickson. 2002. Resource selection by animals, statisitical design and analysis for field studies. 2002. Kluwer Academic Publishers, Dordrecht, The Netherlands. Mech, L.D.,and G.D. DelGiudice. 1985. Limitations of the marrow-fat technique as an indicator of body condition. Wildlife Society Bulletin 13:204-206. Nelson, LJ., and J.M. Peek. 1982. Effect of survival and fecundity on rate of increase of elk. Journal of Wildlife Management 46: 535-540. Otis, D. L., and G. C. White. 1999. Auto-correlation of location estimates and the analysis of radiotracking data. Journal of Wildlife Management 63:1039-1044. Riney, T. 1955. Evaluating condition of free ranging red deer (Cervus e/aphus), with special reference to New Zealand. New Zealand Journal of Science and Technology 36:429-463. Roath, R, L. Carpenter, B. Riebsame, and D. Swift. 1999. Gunnison Basin habitat assessment projectFinal Report March 1999. Colorado State University, Department of Range Science, Fort Collins, Colorado USA. Samuel, M.D., E.O. Garton, M.W. Schlegel, and R. G. Carson. 1987. Visibility bias during aerial surveys of elk in northcentral Idaho. Journal of Wildlife Management 51: 622-630. SAS. 1988. SAS/STAT user's guide, release 6.03. SAS Institute, Inc. Cary, North Carolina USA. Spraker, T.R. 1982. An overview of the pathophysiology of capture myopathy and related conditions that occur at the time of capture of wild animals. Pages 82-118 in L. Nielsen, 1.C. Haigh, and M.E. Fowler, editors. Chemical immobilization of North American Wildlife. Wisconsin Humane Society, Inc., Milwaukee, Wisconsin, USA. Unsworth, J.W., L. Kuck, and E.O. Garton. 1990. Elk sightability model validation at the National Bison Range, Montana. Wildlife Society Bulletin 18: 113-115. Wade, D.A., and J.E. Browns. 1982. Procedures for evaluating predation on livestock and wildlife. Texas- Agricultural Experiment Station Publication B-1429. White, G.c. 1991. DEAMAN database manager and population modeling procedures; Colorado Division of Wildlife User's manual and reference. Colorado State University, Fort Collins, Colorado USA. White, G.c. and RA. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic Press, Inc., San Diego, California USA. �93 Wright, K. L. 1983. Elk movements, habitat use, and the effects of hunting activity on elk behavior near Gunnison, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Young, S. 1982. Migration patterns of the upper Gunnison River elk herd. Thesis, Colorado State University, Fort Collins, Colorado, USA. Table 1. Number of male (M) and female (F) calf and adult female elk radio-collared in each DAU and trae-zone in the Gunnison Basin, December 2000 and 2001. Calf Elk Collared 2000 DAU-(GMUs) Trapzone E-25 (66, 67) E-43 (55, 551) M Total M A- Lake Fork 4 7 11 B -Cebolla 3 4 C - Huntsman 4 D - Sawtooth 2 II E - Razor F M F Total 2000 2001 2 4 6 6 11 17 5 7 2 0 2 5 4 9 3 5 6 6 12 10 7 17 3 2: Collared 2000-01 2000 2001 6 16 7 2 5 10 4 2 5 8 14 3 2 4 6 4 5 9 2 3 5 7 II 26 12 14 26 25 27 52 II 19 39 32 2 3 5' 6 2 7 9 2 3 5 7 F - Tomichi 4 5 3 3 6 7 4 11 3 0 3 8 6 7 11 18 11 5 16 18 16 34 8 2 10 26 18 12 14 26 11 11 28 27 27 54 11 1 l2. 39 II 2 4 6 3 6 5 7 12 4 5 10 7 H - Flat Top 3 I - Beaver 4 6 10 3 4 7 7 10 17 4 0 4 14 7 J - West Elk 7 3 10 7 6 13 14 9 23 5 2 7 15 15 13 11 26 11 11 26 26 26 52 11 1 16 39 29 38 40 78 40 80 78 80 ill 39 II .ll ill 92 subtotals E-41 Totals Collared 2000-01 Total Total Elk G- Almont subtotals E-43 E-41 (54) 2001 F subtotals E-25 Adult Female Elk All Subtotals 40 Includes 2 female calves that died of capture-induced causes within 24 hours of capture for which 2 additional female calves were captured from the same area and radio-collared prior to completing capture of all elk. The net beginning sample size was therefore I I female calves for estimating survival rates in DAU E-43 in 200l. a �94 Table 2. Numbers and proportions (%) of adult female and calf elk counted within geographic trap-zones (TZ) in relation to numbers and proportions (%) of radio-collared adult female and calf elk captured within trap-zones in elk DAUs E-25, E-43, and E-41 and DAUs combined in the Gunnison Basin. Counts of elk represent total adult females and total calves counted during elk sex and age classification helicopter flights conducted post-harvest during December-January for years 1995-96, 1997-98, and 1999-2000 combined. Elk caEtured in December 2000 and 2001. DAUE-25 Elk Class TZ-A TZ-B TZ-C Adult Females-Counted 1,553 (34) 1,113 (24) 1,366 (30) Adult Females-Captured TZ-D 569 (12) DAU-Total 4,601 (100) 6 (32) 5 (26) 5 (26) 3 (16) 19 (100) Calves-Counted 660 (33) 504 (25) 647 (32) 180 (9) 1,991 (100) Calves-Captured 17 (33) 9 (17) 17 (33) 9 (17) 52(100) DAU E-43 Elk Class TZ-E TZ-F TZ-G Adult Females-Counted 634 (11) 1,133 (20) 3,860 (68) 5,627 (100) Adult Females-Captured 3 (19) 3 (19) 10 (62) 16 (100) Calves-Counted 302 (11) 633 (23) 1,847 (66) 2,782 (100) Calves-Captured 9 (17) 11 (20) 34 (63) 54 (100) DAU-Total DAUE-4l Elk Class TZ-H TZ- I TZ-J Adult Females-Counted 1,120 (21) 2,134 (40) 2,039 (39) 5,293 (100) Adult Females-Captured 5 (31) 4 (25) 7 (44) 16 (100) Calves-Counted 535 (23) 939 (40) 903 (38) 2,377 (100) Calves-Captured 12 (23) 17 (33) 23 (44) 52 (100) DAU-Total DAUs Elk Class DAUE-25 DAUE-43 DAU E-41 DAUs-Total Adult Females-Counted 4,601 (30) 5,267 (35) 5,293 (35) 15,161 (100) Adult Females-Captured 19 (37) 16(31) 16(31) 51 (100) Calves-Counted 1,991 (28) 2,782 (39) 2,377 (33) 7,150 (100) Calves-Captured 52 (33) 54 (34) 52 (33) 158 (100) �95 Table 3. Survival rates during winter-spring (WS), summer-fall (SF), and annual (Ann) seasonal intervals from 15 December 2000 to 14 June 2003 for adult female elk age :::::24months (mos.) and :::::12 months that were radio-collared in December 2000 and 2001 in the Gunnison Basin, Colorado. Survival rates include all sources of mortality. Survival rates and confidence limits calculated using binomial estimator based on n-collars that excluded censored elk. All radioed elk combined among DAUs E-25, E-4l, and E-43. Seasonal Survival Intervals and Dates FEMALES (age?: 24 mos.) Survival Rate Lower 95%CL Upper 95%CL n Collars Collars Deployed Collars Censored Died Non-hunting Deaths Hunting Deaths FEMALES (age?: 12 mos.) Survival Rate Lower 95%CL Upper 95%CL n Collars Collars Deployed Collars Censored Died Non-hunting Deaths Hunting Deaths a Includes WS SF Ann WS SF Ann WS 12/15/00 06/14/01 06/15/0112/14/01 12/15/0012/14/01 12/15/0106/14/02 06/15/0212/14/02 12/15/0112/14/02 12/15/0206/14/03 1.00 0.92 0.84 1.00 39' 39 1.00 0.74 0.65 0.84 82' 3' 0.92 0.84 1.00 39' 39 0 3' 2 2 0.69 0.55 0.82 48b 48 0 15f 0 15 0.98 0.95 1.00 61d 61 0 18 1 0 0.91 0.84 0.97 77h 77 0 7m 0.92 0.84 1.00 39' 39 0 3' 6 2 0.99 0.96 1.00 861 86 0 I" 1 0 39' 39 0 0 0 0 1.00 39' 39 0 0 0 0 o 48b 48 0 0 0 0 82 o 21f o 21 1.00 0.77 0.69 0.85 8i nz' 0.74 0.65 0.84 82k 82 0 0 0 0 113 In 26f 0 26 82 0 21f 0 21 only adult females age ~ 30 months radio-collared 16-22 December 2000 as there were no females age 18 months radio-collared at time of initial capture and radio-collaring. b Includes 12 additional adult females age ~ 30 months radio-collared 16-20 December 2001. c Includes 34 females age 24-29 months recruited from surviving radioed calves and 48 females age ~36 months. d Includes 28 females age 30-35 months recruited from surviving radioed calves and 33 females ~42 months. e Adult female deaths: 172.758/00 in early July of unknown causes, 172.030/00 archery/muzzleloading wounding loss, and 174.478/00 harvested first rifle season. f See Appendix C for listing of hunting and non-hunting mortalities for adult radio-collared elk. g Female 174.629/01 died early May from mountain lion predation. h Includes 38 females age 12-17 months recruited from surviving radioed calves and to 39 females age ~36 months. i Includes 34 females age 18-23 months recruited from surviving radioed calves and 48 females age ~ 30 months. j Includes 31 females age 12-17 months and 34 females age 24-29 months recruited from surviving radioed calves and 48 females age ~36 months. k Includes 34 females age 18-29 months recruited from surviving radioed calves and 48 females ~30 months. I Includes 25 females age 18-23 months and 28 females age 30-35 months recruited from surviving radioed calves, and 33 females age ~42 months. m Adult female deaths: 172.758/00 in early July of unknown causes, 172.030/00 archery/muzzleloading wounding loss, 174.478/00 harvested first rifle season, 172.619/00 and 174.360/00 wounding loss first and fourth rifle seasons, respectively, and 173.589/00 and 174.560/00 disappeared late and third rifle seasons, respectively. n Censored elk 173.681101 mid-July for slipped collar. �96 Table 4. Survival rates during winter-spring (WS) and summer-fall (SF) seasonal intervals from 15 December 2000 to 14 June 2003 for the cohort of 6-month old elk calves radio-collared in December Survival rates include all sources of mortality. Survival rates and 2000 in. the Gunnison Basin, Colorado. confidence limits calculated using binomial estimator based on n-collars that excluded censored elk. All radioed elk combined among DAUs E-25, E-41, and E-43. Elk Age In Months (mos.) and Seasonal Intervals and Dates 18-23 mos. 6-23 mos. 24-29 mos. 30-35 mos. 6-35 mos. SF WS All Intervals SF WS All Intervals 06/15/0112/14/01 12/15/0106/14/02 12/15/0006/14/02 06/15/0212/14/02 12/15/0206/14/03 12/15/00- 1.00 0.66 0.74 1.00 0.48 0.48 0.52 0.84 0.95 19 29 19 14 29 25 19 38 19 14 38 6' 3b 0 9 0 0 9 7 0 10 5 0 15 7' 3 2d 0 9 0 1e 0 Survival Rate 0.97 0.89 1.00 Lower 95%CL 0.92 0.79 Upper 95% CL 1.00 0.99 n Collars 39 38 Collars Deployed 40 1& 6-11 mos. 12-17 mos. WS 12/15/00 06/14/01 Survival Rate 0.78 0.86 Lower 95%CL 0.63 0.71 Upper 95%CL 0.93 1.00 n Collars 32 22 Collars Deployed 38 Collars Censored Died MALES Non-hunting Deaths Hunting Deaths 06/14/03 0.29 0.67 0 0 9 . s' 0 6 0.87 0.82 1.00 0.72 0.76 0.69 0.98 0.96 34 39 34 28 39 38 34 40 34 28 40 0 4 0 0 I 5 0 6 0 0 11 0 4h 0 0 4 0 6; FEMALES Collars Censored Died Non-hunting Deaths Hunting Deaths 1 1c 0 0 0.57 0.86 0 10 Male calves censored: for post-capture induced mortality 173.082/00 on 12/29/00; for slipped collars 173.269/00 on 4/30/01,173/170/00 on 5/7/01, 173.250/00 on 5125/01,173.151100 and 173.220/00 on 6/7/0l. b Yearling males censored: slipped collars, 173.091100, 173.3 91/00, and 173.510/00 between 6122/01 and 7/20/0 l. C See Appendix A for timing and estimated causes of calf deaths. d Males 173.330/00 and 173.340/00 died during early July of suspected mountain lion and black bear predation. e Yearling male 174.140/00 illegally wounded and died about 12/10/01 during late-season for antlerless elk. fHarvested as branch-antlered males: 172.890/00 in first rifle season, 173.358/00, 174.200/00, 174.729/00, 174.800/00 in third rifle season. g Female calf censored: for post-capture induced mortality 172.379/00 on 12/26/00. h Yearling females 172.619/00 and 174.360/00 wounded during fust and fourth rifle seasons, respectively and 174.560/00 and 173.589/00 disappeared during third rifle and late rifle seasons respectively, and assumed legally harvested. i Females harvested: 172.230/00 first rifle season, 172.450/00 third rifle season, 172.529/00 and 174.520/00 wounding losses third rifle season, 174.910/00 and 172.540/00 disappeared in third rifle and late rifle seasons, respectively, and assumed legally harvested. a �97 Table 5. Survival rates during winter-spring (WS) and summer-fall (SF) seasonal intervals from 15 December 2001 to 14 June 2003 for the cohort of 6-month old elk calves radio-collared in December 2001 in the Gunnison Basin, Colorado. Survival rates include all sources of mortality. Survival rates and confidence limits calculated using binomial estimator based on n-collars that excluded censored elk. All radioed elk combined among DADs E-25, E-41, and E-43. Elk Age In Months (mos.) and Seasonal Intervals and Dates 6-11 mos. 12-17 mos. 18-23 mos. 6-23 mos. WS SF WS All Intervals 12/15101 06/14/02 06/15102- 12/15102- 12/15101- 12/14/02 06/14/03 06/14/03 Survival Rate 0.84 0.82 0.95 0.64 Lower 95%CL 0.71 0.67 0.47 Upper 95%CL 0.96 0.97 0.86 1.00 n Collars 37 28 22 33 Collars Deployed 40 31 23 40 Collars Censored 3' 3h 1' Died 6 5 6d 0 1e 7 0 5 f 0 5 1.00 MALES Non-hunting Deaths Hunting Deaths 0.81 7 12 FEMALES Survival Rate 0.82 0.83 Lower 95%CL 0.69 0.69 Upper 95%CL 0.94 0.97 n Collars 38 30 25 37 Collars Deployed 40 25 40 Collars Censored Died 2g 7 31 1h 5 0 0 3 12 Non-hunting 7d 0 0 7 0 5i 0 5 Deaths Hunting Deaths a Male 0.68 0.52 0.83 calves censored: for post-capture induced mortality 174.720/01 on 12/19/01; for slipped-collars, 174.099/01 on 5120/02 and 175.221101 on 6/3/02. b Male yearlings censored: 173.170/01, 174.580/01, 174.690/01 for slipped-collars between 6/18 and 7/17/02. C Male censored: 175.250/01 on 217/03 possible collar failure. d See Appendix B for timing and estimated causes of calf deaths. e Male died 173.949/01 early April suspected mountain lion predation. fMale yearlings died: 173.041101, l73.082/01, l73.091/01, 173.340/01, l74.380/01; all illegal harvests during Fall hunting seasons 2002. g Female calves censored: for post-capture induced mortality 173.429/01 onI2/16/01 and 173.740/01 on 12/16/0l. h Female yearling censored: 173.681101 for slipped-collar between 7/17 and 8/21102. i Female yearlings died: 172.519/01, 172.741101, 173.210/01, 173.999/01, 174.019/01; all died during Fall 2002 hunting seasons as legal harvest. �98 Table 6. Survival rates for adult female elk age 2:30 months (mos.) and 2:12 months by DAU from 15 December 2000 to 14 June 2003. Elk assigned to a DAU based on being trapped within that DAU. Elk were radio-collared in December 2000 and 2001 in the Gunnison Basin, Colorado. Females age 2:30 months include only females originally radioed at that age and do not include recruitment of radioed calves surviving to older age classes. Females age 2:12 months include females originally radioed at age 2:30 months and recruitment of radioed calves surviving to age 2:12 months .. Survival rates include all sources of mortality. Survival rates and confidence limits calculated using binomial estimator based on n-collars that excluded censored elk. Survival Rates b}::DAU for Multi-}::ear Interval Dates FEMALES (age? 30 mos.) Survival Rate Lower 95%CL Upper 95%CL n Collars Collars Deployed Collars Censored Died Non-hunting Deaths Hunting Deaths DAU E-25 DAU E-43 DAUE-41 DAU E-25 DAU E-43 DAUE-41 12/15/00 06/14/03 12/15/00 06/14/03 12/15/00 06/14/03 12/15/00 06/14/03 12/15/00 06/14/03 12/15/00 06/14/03 0.58 0.34 0.82 19 19 0 8 0.50 0.234 0.766 16 16 0 8 0 8 0.81 0.61 1.00 16 16 0 3 0.74 0.61 0.88 43 44 I II 0.60 0.44 0.76 40 40 0 16 0 16 0.81 0.67 0.94 36 36 0 7 I 6 7 2 FEMALES (age::: 12 mos.) Survival Rate Lower 95%CL Upper 95%CL n Collars Collars Deployed Collars Censored Died Non-hunting Deaths Hunting Deaths 10 Table 7. Survival rates for adult male elk age 12-35 months (mos.) and age 12-23 months by DAU for intervals between 15 June 200 land 14 June 2003. Elk assigned to a DAU based on being trapped within that DAU. Elk were radio-collared as calves in December 2000 and 2001 in the Gunnison Basin, Colorado. Survival rates for age 12-35 months represent elk combined from 2 cohorts of yearlings of which 1 cohort advanced to age 24+ months and was subject to 1 hunting season as legal branch-antlered males. Survival rates for age 12-23 months represent elk combined from 2 cohorts of yearlings neither of were subject to hunting season as legal branch-antlered males during the time intervals summarized. Survival rates include all sources of mortality. Survival rates and confidence limits calculated using binomial estimator based on n-collars that excluded censored elk. Survival Rates by DAU for Multi-year Interval Dates Males (age 12-35 mos.) Survival Rate Lower 95%CL Upper 95%CL n Collars Collars Deployed Collars Censored Died Non-hunting Deaths Hunting Deaths DAU E-25 DAU E-43 DAU E-41 6/15/01 6/14/03 6/15/01 6/14/03 6/15101 6/14/03 0.88 0.60 1.00 8 12 4 I 0 0.57 0.35 0.78 23 24 0.77 0.55 0.98 17 20 3 4 0 4 10 3 7 DAUE-25 6/15/01&026/14/02&03 Males (age 12-23 mos.) Survival Rate Lower 95%CL Upper 95%CL n Collars Collars Deployed Collars Censored Died Non-hunting Deaths Hunting Deaths 0.88 0.60 1.00 8 12 4 0 DAUE-43 DAU E-41 6/15/01&026/14/02&03 6/15/01&026/14/02&03 0.70 0.50 0.90 23 24 0.94 0.83 1.00 18 20 2 1 0 7 3 4 �99 Table 8. Dates of aerial surveys to determine survival status and general locations of radio-collared elk in the Gunnison Basin, January 2001 - December 2003. Seasons defined as: Winter - December-March; Spring - April-May; Summer - June-August; Fall - September-November. Total Flights 9 5 6 6 26 8 7 6 3 24 4 2 2 Year 2001 2002 2003 o 8 Season Winter Spring Summer Fall All Winter Spring Summer Fall All Winter Spring Summer Fall All Flight Dates (mm/dd) 01104,01124,02/02,02116,03/02,03119,12/05,12127,12/28 04113,04/27,05110,05/18, OS/25 06/01,06/07,06/22,07113,07,20,08/21 09/08,09/25,10118, 10/30, 11108, 11116 01103,01109,01124,02/07,02/21,03/06,03/20,12/19 04/04,04/19,04/30,05/10,05115, OS/20, OS/28 06/03,06/18,06119,07117,08/08,08121 10/01, 10/31, 11/19 01107, 02/07, 03/26, 12119 04/25, 05121 06/25,06/26 Table 9. Male elk calves radio-collared in December 2000 and 2001 within each trap-zone whose estimated seasonal geographic locations were used to illustrate spatial distribution of young male elk in the Gunnison Basin, December 2000 - December 2003. Within each trap-zone, 100% of the calves were used to illustrate distribution. Maximum age of these elk in December 2003 was 42 months. Number of calves radioed does not include calves dying from capture-induced deaths. Trap-zone A B C D E F G H I J All Male Calves Radioed 6 3 10 4 2 7 18 5 7 14 76 Elk Selected To Illustrate Spatial Distribution Representing 6 3 10 4 2 7 18 5 7 14 76 Elk in DAU E-25 E-25 E-25 E-25 E-43 E-43 E-43 E-41 E-41 E-41 E-25 Total = 23 E-43 Total = 27 E-41 Total = 26 Table 10. Adult female elk within each trap-zone whose estimated seasonal geographic locations were used to illustrate spatial distribution of adult female elk in the Gunnison Basin, December 2000 December 2003. Within each trap-zone, ::::65%of the females captured as adults (age 2:30 months) were selected at random to illustrate elk distribution. Trap-zone A B C D E F G H I J All Adult Females Radioed 6 5 5 3 3 3 10 5 4 7 51 Elk Selected To Illustrate Spatial Distribution 4 3 3 3 3 3 6 3 3 4 35 Representing Elk in DAU E-25 E-25 E-25 E-25 E-43 E-43 E-43 E-41 E-41 E-41 E-25 Total = 13 E-43 Total = 12 E-41 Total = 10 �100 Table 11. Female elk calves radio-collared in December 2000 and 2001 within each trap-zone that survived to age 2::12months whose estimated seasonal geographic locations were used to illustrate spatial distribution of young female elk in the Gunnison Basin, December 2000 - December 2003. Within each trap-zone, :::::65%of surviving calves were selected at random to illustrate elk distribution: Maximum age of these elk in December 2003 was 42 months. Number of calves radioed does not include calves dying from capture-induced deaths. Female Calves Trap-zone Radioed A 11 4 B 7 C 5 D 7 E 4 F 16 G 7 H 10 I J 9 All 80 Female Calves Surviving To Age> 12 Months 10 4 6 5 5 4 15 4 9 7 69 Elk Selected To Ilustrate Spatial Distribution Representing Elk in DAU E-25 E-25 E-25 E-25 E-25 Total = 18 E-43 E-43 E-43 E-43 Total = 16 E-41 E-41 E-41 E-41 Total = 14 7 3 4 4 3 3 10 3 6 5 48 Table 12. Sample sizes for estimating seasonal distribution and movements of adult female (AF), female calf to adult (FCA) and male calfto adult (MCA) elk in the north and south portions of the Gunnison Basin based on elk locations, maximum movement vectors (MMV), and minimum convex polygon home ranges (MCP) from December 2000 through December 2003. The north Basin represented elk captured in trap-zones F-J and the south Basin represented elk captured in trap-zones A-E (see Fig. 1). Gunnison Basin North or South Elk Group Class Elk Sampled Per Data Type Locations Per Elk Locations MMV MCP Avg. Min Max North AF South AF 19 16 19 19 8 43 578 16 16 30 26 Total Locations 13 39 420 North FCA South FCA 27 27 21 27 15 12 874 21 32 29 44 21 43 608 North MCA 51 40 40 20 2 40 1,016 South MCA 25 12 12 11 3 39 264 �101 Table 13. Number and percentages (%) of radio-collared elk venturing into Game Management Units (GMUs) outside the Gunnison Basin North or South from December 2000 through December 2003 for adult females (AF), female calves to adults (FCA), and male calves to adults (MCA) based on maximum movement vectors (MMV) and home ranges (MCP). Percentages based on elk sampled for MMV and MCP (see Table 12). Gunnison Basin North or South Elk Group Class GMUs with Number and ( % ) of Elk Venturing Into Each GMU 48&481 56 68&68176&79 65 64 63 53 521 43&471 411 67 551 ABOut· North AF - MMV 1 (5) 0 (0) 0 (0) MCP 1 (5) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 5 (26) 0 (0) 0 (0) 0 (0) 1b (5) 0 (0) 7 (37) 0 (0) 0 (0) 0 (0) 1 (5) 5 (26) 0 (0) 0 (0) 0 (0) 1b (5) 0 (0) 7 (37) 2(7) 1(4) 0(0) 0(0) 0(0) 0(0) 1(4) 6(22) 2(7) 0(0) 0(0) 0(0) Ib(4) 11(41) ---"2-(75----i-(4)-----0(0)------0-(o)-----0-(0")--0-(0)---i-(4)--3(1-1)----i-(7)------0-(O)-----0-(0)--0-(O-)--16-(4)---10-C-37)-' North FCA - MMV MCP ----)-(35------1(3-)------OCO)--------1b-(3-5----0-(0-)---0-(0)---0-CO)---il-(i-S)---i-(5)------i-(5)------r-C-3)--0-(0-)--0-(0)---2"i-c-53)- North MCA - MMV MCP 4 (10) 1 (3) 1 (3) Ib (3) 0 (0) 0 (0) 4 (10) 14 (35) 2 (5) 2 (6) 1 (3) 0 (0) 0 (0) 22 (55) South AF - MMV 0(0) 0 (0) 3 (19) 0 (0) 1 (6) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 4 (25) ____ ~_~~l__?_~~~ ~i~~~ MCP South FCA - MMV 0(0) 0 (0) 0 (0) 0 (0) 0 (0) ?_i~L_~_0~? ?_~9L_~_l~L~_(?) ?_~~~ ?_i~2 9_i?? ~_~?2_ __?_~~__2_(~~~_. 1 (5) 4 (19) 2 (10) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 7 (33) ____ ~_~~1 ?_~~~ ~_i~~ ~_(~2 ~_Q~?_~__~_~~__9_i?! ~_~?) _?_~~~ ?_~~L ?_i?? ~_~?2_ __?_~~~!_~_5~~L MCP South MCA - MMV 0(0) 0 (0) 4 (33) 2 (17) 1 (8) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 7 (58) MCP 0(0) 0 (0) 4 (33) 2 (17) 1 (8) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 7 (58) Sum and percent of individual elk that moved to outside GMUs, does not double-count elk that ventured to > I outside GMU based on MCP. b Moved south across U. S. Highway 50. a Table 14. Maximum movement vector (MMV) distances (km) and confidence limits (CL) for classes of elk in the Gunnison Basin North, South, and All areas from December 2000 to December 2003. Movement Vectors (MMV) for Elk Classes in Gunnison Basin Areas Maximum Vector Statistics Adult Females North Adult Females South Calf To Adult Females North Calf To Adult Females South Calf To Adult Males North Calf To Adult Males South All Adult Females All Calf To Adult Females All Calf To Adult Males Mean(km) 32.3 34.8 37.6 33.4 38.5 35.8 37.7 15.0 15.4 11.9 15.0 11.9 6.4 Maximum Variance 56.4 57.2 57.2 78.5 125.5 111.0 350.4 62.5 105.9 65.0 175.9 15.3 78.5 13.4 34.8 6.4 33.4 Minimum 343.9 112.7 175.9 111.0 344.7 218.1 SEofMean 2.4 2.8 2.6 3.2 3.0 5.4 1.8 2.0 2.6 95% Lower CL 27.3 28.8 32.4 26.7 32.5 23.0 29.8 31.7 32.5 95% UpperCL 37.2 40.8 42.9 40.1 44.5 46.6 37.1 39.8 42.8 n = elk 19 16 27 21 40 12 35 48 52 Table 15. Number and percentages (%) of maximum movement vectors (MMV) by season of occurrence for elk classes in the Gunnison Basin North, South, and All areas from December 2000 to December 2003. Number and (%) Movement Vectors (MMV) for Elk Classes in Gunnison Basin Areas Seasons For Maximum Vectors Winter Spring Summer Fall n = elk Adult Females North Adult Females South 0(0) 2 (11) I (6) 2 (13) 13 (68) 4 (21) 19(100) Calf To Adult Females North Calf To Adult Females South Calf To Adult Males North Calf To Adult Males South All Adult Females All Calf To Adult Females All Calf To Adult Males 2 (7) 4 (19) 3 (14) 2 (6) 5 (12) 4 (33) 2 (17) I (3) 4 (11) 6 (12) 6 (12) 6 (II) 3 (11) 9 (56) 4 (25) 18 (67) 12 (57) 28 (70) 33 (65) 16 (100) 5 (12) 40 (100) 6 (12) 27 (100) 2 (10) 21(100) 22 (63) 8 (23) 30 (64) 4 (15) 5 (42) I (8) 12 (100) 35 (100) 48 (100) 6 (11) 52(100) 7 (13) �102 I es m th e Gunmson Basm, 15 D ecem ber to 14 J une, 2000-01. A~ppen dix A Rad'10-CO 11are d ca If e Ik mo rtaliti Trap- Death zone Date No ElkID Sex Mass I 173.082100 M 92 B 2 172.379/00 F 127 H 12129/00114101 12119-26/00 Recovered 5-Jan-01 3-Jan-Ol Femur Marrow Fat Tissue Samples Parasites White Creamy 38.7% White Finn YesCM nla nla nla Carcass Status Nearly Complete Scavenged 94.7% 3 173.640/00 F 82 A 211-7/01 7-Feb-01 4 172.959/00 M 125 J 2115101 15-Feb-01 Red Jelly 15.8% Watery Pink NoCM NoCM 48.7% 5 173.351100 M 52 F 3121/01 24-Mar-Ol Red Jelly NoCM 27.5% 6 173.160/00 M 94 A 3/25/01 26-Mar-01 Red Jelly Red Jelly 0.0% NoCM Red Jelly 77.66% Red Creamy NoCM NoCM 42.8% 7 173.300/00 M 112 I 3131/01 I-Apr-Ol 8 173.041/00 M 97 I 4113-14101 I5-Apr-0 I 9 173.949/00 M 107 A 4120/01 26-Apr-01 NoCM 45.27% Partially Scavenged Carcass Complete Scavenged Carcass Complete Carcass Complete Nearly Complete Scavenged Capture Related / Lion Capture Related Lion Predation Unk. -Suspect Starvation Unk. -Suspect Starvation Starvation Unk. -Suspect Starvation Unk.-Suspect Starvation Lion Predation Scavenged Bear Predation Red Jelly nla 13.15% Mass - Weight of calf (kg) at capture; CM - capture myopathy; NI - no evidence of inflamation around sarcocysts; nla ~ samples not available' Unk.s=unknown. 10 173.011100 M 113 J 4128-5/10/01 23-May-01 Moderate sarcocysts Moderate sarcocysts Normal sarcocysts Moderate sarcocystsINI Severe sarcocystsINI Severe sarcocysWNI Normal sarcocysts nla Death Location Death Cause UTMx 303163 UTMy 4253981 335406 4282773 Drainage Lake Gulch Flat Top 304608 4243376 Lake Fork 304753 4261110 Red Ck. 360867 4262422 298132 4230866 Yellow Pine Dwyer Gulch Dry Gulch 308379 4263917 320104 4270341 311827 4245467 300715 4268428 Beavear Ck. Cebolla Ck. E.Coal Ck. A\P pen dix B Radi o-co 11are d c alf e lk morta lues IIIthe Gunmson B asm, 15D ecem ber to 14 June, 2001 -02 Trap- Death Zone Date No ElkID Sex Mass I 173.429/01 F 100 E 12118/2001 20-0ec·01 2 173.740/01 F 101 E 1212112001 21-Dec-01 3 174.720/01 M 101 B 121212312001 01121212002 26-Dec-01 Recovered Femur Marrow Fat Tissue Samples Parasites Finn core,pink;87.45% Finn core. pink;66.5% Soft core, pink;88.87% nla NoCM unremarkable MildCM nla NoCM nla Low Sarcosysts nla Finn core,pink;78.50% Firm core, pink;90.71% NoCM unremarkable NoCM Low Sarcosysts 6-Feb-02 Finn, red; 68.56% nla Jelly, red: 1.57% NoCM NoCM 14-Jan-02 4 173.269/01 M 98 J 5 172.350101 F 86 H 0113-712002 8-Jan-02 6 173.852101 F 101 I 1/4-9/2002 10-Jan-02 7 175.181101 M 91 A 1/15- nla 215/2002 8 172.170/01 F 58 H 01/2021/2002 23-Jan-02 9 173.861101 F 102 J 1125- 29-Jan-02 A 2/21- 4-Mar-02 G 2812002 2125- 7-Mar-02 Finn core. pink: 94.36% Soft core, red; 5.27% nla 9-Mar-02 nla 2812002 10 II 174.770/01 172.379101 M F 92 81 nla bronchopneumonia Moderate sarcocysts Moderate sarcocysts nla nla nla NoCM 3/612002 12 173.300/01 M none J 212731612002 Finn core, pink: Moderate NoCM 83.60% sarcocysts 108 J 4/25Finn core, pink; nla nla 14 173.780/01 F 4130/2002 27.08% 100 5/1521-May-02 Red, fum core; nla nla C 15 175.240/01 M 5/2012002 60.02% 5/1522-May-02 Firm core, nla nla 95 E 16 174.180/01 M 5120/2002 pink;75.63% Mass ~ Weight ofcalf(kg) at capture; CM ~ capture myopathy; nla ~ samples not available; Unk.=unknown 13 173.632101 F 96 C 312025/2002 26-Mar-02 I-May-02 Carcass Status Death Cause Carcass Complete Carcass Complete Partially Scavenged Totally Scavenged Partially Scavenged Partially Scavenged Capture Related Fence Kill Capture Related euthanized Capture Related I Lion Unk. -suspect lion predation Bear Predation Scavenged heavily Carcass Complete Partially Scavenged Carcass Complete Totally Scavenged Not FoundSnow Partially Scavenged Totally Scavenged Totally Scavenged Totally Scavenged UTMx 351433 Death Location UTMy Drainage 4245033 Prosser Ck 353050 4250600 302744 4230958 E. Table TopMt SkunkCk. 300102 4267074 Pearson Pt. 334033 4282350 Lion predation 321888 4275810 Unk.-suspect coyote predation AccidentHaystack collapse Lion predation 297064 4231180 330243 4280937 FlatTop Min W. Antelope Ck Dwyer Gulch Redden's 299250 4267725 Pearson Pt Accident-fell, trapped Unknown 294622 4227200 ElkCk. 342715 4288645 Unknown 299323 4268454 Lion predation 322925 4232867 Unknown 306109 4267739 Almont Triangle N. Pearson Pl. Road Beaver Ck. RedCk. Unk. -suspect lion predation Unk.-suspect lion predation 325443 4235881 351363 4240438 N. Road BeaverCk. Home Gulch �103 C_ Radio-collared A INo I' IElklD I~~ 172.758100 119yrs I Sex 1;:;IF IH 1~"::wF" Inf. Inf. ~=~ I Parasites Inf. I Carcass Status I Decomposed 77.46"'" Inf. Inf. IScovmged I"'a I adult elk mortalities in the Gunnison Basin 15 December 2000 to 14 June 2003_ I~:th IR"ov=d 121-lul-<>1 es lo",thc.us< I Unknown Mortality lTlMx f32I262 '!Mv fill446T Dninage I S_Corton Mln fTIill9 ]429OID I SummervilieCk. [384766 14303460 I N. Cottonwood Ck. 1:~~i701 173.330100 t z mcs 73.340100 1'2mo. '72.030100 16yr 1M IG 1M 10 I24-lul-<>1 I:~~~I 1>6122<7/l0IU' 1'6-Aug-01 IC 119-0et-<> Infa I"'a 16 116mo. '74A7",00 174_360100 s.9yrs 7 mo. ~:~:!rol I 110113/2001 IG l74.'401oo 1'8 mo. 173.>0.,00 1'8 mos 1'0 l74.'6<>'00 z mcs lIZ .039/00 172.101100 15-9".. I ,..yrs 113 1172.201100 14 yrs 114 II> :.230100 112.411100 28mo, '-9y" 1M I~~%~mbles I"" Inf. Inf. Inf. Infa Inf. I Complet. I:~~ink.finn Inf. I"" I Scavenged I"" I"" Inf. Inf. In" I"" Infa Inf. Inf. Inf. I 24-Nov-02 Inf. Infa '"" InfO Inf. rPkntifuTFoWlC ILowF"-HQ 195;;~ I::~I IB I~:~;~~: IC IF 1127/200: 11123/2002 IB IA 10 112.4''''00 29mo, IF 112.>1>101 15mo. IF 110 112.>29100 29mo, IF 1° 119 II 72.549/00 5yrs IF IG 20 21 :.581/00 !.639/00 II. 1~:~:01 1° 5-9."., 5-9m I:: :::912002 1101141200: l7J.041101 r mcs 1M o 2> "'.00210' t mcs 1M 0 26 l7J.09110' j mcs 1M 0 27 173.20210' 7yrs 28 m.",,,,ol r recs 30 31 J2 :74.019/01 1/4.129/01 7 mo. 'yrs 33 34 3S 174.200100 174.260100 l74.38"'01 29 mo. 24m z mcs Iwhite. finn 96.13% I"" I"" 15-0ct.<J; I 26-Mu-03 I",. Inf. lril. I Swinehort Gukh [4illi64 ICowCk 134-000 1346979 i24265D 14279939 Reck Ck. I'" SaverCk. 1108573 14242145 ILalte""y,;ut-U" I"" Infa ILow Cebolla Ck. Infa Inf. IW"'''lk<-l<. rili800 IR;ne Late season Legal III 7200 illi200 14353200 IHomeGukh I~tt Ck."d>oll. [296z98 fil10388 IJj,"'''''"liU''" ="'== l3Ol8OO 1350800 illl500 14263100 INourse Ck IN" 'arton Town f340300 14283300 flliOOtl [ill9iOO I"'ay liUlen 1341303 14270882 Isn eep ocicn f347668 [42llill ILest Canyon Gulch :.,.sruont:e2'l -== == f3%30() 1140600 f146500 ffi200 i27lruO Iill8(jQ :.bin Ck Le.P' Fisher Guleh Lost Canyon ()u_lch_ ~:'E' I~!:::~'i'::.n IRifle Late season I~e:::~~~:;;~e I~:''!'~~'!.~I = ~ Inf. I"" I"" Mod_eFat-HQ Iwhite. finn 95.90% Inf. Inf. I"" 12'-Nov-02 Inf' Inf. 1<: ::1912002 dequate 13-0«-02 2·0«-02 :~::::~ed CCOni,iIer.e I"'a fii" Inf. InfO Inf. Int. bite, finn 91.34% Inf. Inf. Int. Inf. nf. Inf. iiV'I I"'::I: I~~'Ioadins ~~ nfa Mod"""iF.[:HC IComplet. '•• cason 11o," 1349206 14273981 I c••in Ck. fents <-1<. Iwhite. fum8g.11% Inf. Infa I Complete IRiflel- season 11o," 1342844 14286400 IAlmont Tnangte 21-Nov-02 I white, finn 92.19% I nf Inf. I Complete IRiflel~ season 110« 1347101 14279609 :::::912002 36 37 ::~::12002 11=002 20-0,,-02 Iwhite. finn 99.01% Inf. Inf. 1299643 14248782 Iw,llowMes. Inf. Inf. Inf. I~::;;;.ed Complete I~~,:~: 4-Nov-02 IRifl. ~:. season 110," 1349149 i 427472' ICabin Ck. rents <-1<. 20-0<,.<J2 I"'i Infi Inf. Infi Inf. Inf. Moderat F"-He nf. Legal IRifle "season Legal 194300 326100 ;4248400 14292600 PineCk. R'dg' 1~""Ck.on,o 9-0,,-02 22-Nov-02 Infi Inf. Infi Inf. Inf. Inf. Plmtiful F"-HQ ' Coli e- Under lee IRille Late season Legal I~~~. 3" season illegal 307800 322526 1270600 14290153 IW_Foo1<Red ex, 10",0 Ck. Road 12-Nov-02 21-Nov-02 Infi while. finn 97.18% Inf. Inf. Inf. 364250 364938 1263650 14268448 ILockout Mtn '0000 282200 306192 1276300 1291000 I4237g53 IEaot.t>.averCk. ISm,thFl<. Ck. IlndianCk. 174.420100 174.>20100 1M IF 1M 101l9/2oo2 346000 339255 1274500 14241223 [.0" :anyon Gulch IRockCk llf H :: :::9/l002 llI'212oo2 29mo, l7_""""".uu 174.870101 29 mo. l>" 1113/loo2 1M B ~:~:~/l002 12110/2002 42 174.9'9/00 0 7>" 8-Nov-02 3-Nov-02 20-0",-02 l wa l rva white, finn 97.57% Inf. "'. Infa Inf. Infa 12-0",-02 20-0«-02 nf. Infa while. finn 98.31% Inf. Inf. Inf. nf. 43 172.890100 za mcs iM 144 '72.>40100 18mo. IF 14> 114.91"'00 I 29 mo. Low Fat-HQ ifle4-,eason Legal ·~'':::ed LowF"-HO nfa I~~~:~~'i':~n @e "season Legal Rifle ,"s eason Legal I~c'::;;;.ed I~.::.:~;~~on .ifle-Late season Leeal I~'::':~':: nf. Inf. Infa nf. ~''::;;;'ed nf. I"" I"" Inf. Inf. I"" I"" Infa Inf. Infa I"" Inf. Inf. ::~:~12002 o 1::~:6/Q2 IG I~:~:~/Q2 1:::::3/02 146 148 :~::on I 1lI41 H ~::::912002 .'9 40 o I~~,"".~ont 22-Nov-02 21-Nov-02 ::::1912002 0 season I~~~~:~'i'::.n <11/1912002 1M rifle Inf. I"" A Rifl. I~~.:.!::~:~ Mcderate F.'-HQ IRifle -s essen <.ega! I 22-Sep.<J2 '0/l002 f4ill638 Inf. 16-Nov-02 1'9-0"'-02 fill980 [299i6f ~~'ed IPlmtifuiFit-HC IEmaciated 1912112002 0 124 110-0",-02 I:: ::1312002 1lI612oo2 I>1 ~::102 '612002 I;;~~i~;; 7-0<'-<>1 17-Nov-01 I29-0",.<JI IC Ip;;;J;;i~~ 120-0ct-<>1 1::::~6/01 18 ~;::;;;.ed I ~::::.ed fCoii'Plde Iwhile. solid 97.31% Iwa I:~~;8/UI l72.6'9I00 1;;;;;J;;i;;;; l7J.21(){O' r mcs IF Inf. Inf. 1:::::3/02 122mo, 1M 10 I>411a <412S/Q313O-Apr-03 I ~5~C;; volume Inf. Inf. l74.629/01 • yrs IF ID 1>5/7 <5/l1l03 I 22-MOJ-03 I~~wvolume Inf a Inf. I "'. = samples no' available: ,,,,~~i.-;'~~i ,I' nf. "'. : West Elk Ck. I~:.'!'~~'!.~ifle Inf. I"'· I C.bin Ck. Inf. Inf. I So.p Ck. Inf. Inf. IYellow Pine Ridge I I"'a I ~c'::;;; •• d c H 0= relative elk rot stal1J.from hunter questionn.ire information I r;:~';.;.ed Late l,easo~L eza1 I ~:"~~ l7J.949101 ;~~on i.-;':;' 13S<l54S 14280587 I East Beaver Ck. [348869 I W. Razor Dome Ip;;;J;;io~ J42ill44 �104 Appendix Gunnison D. Follow-up questionnaire mailed to hunters who harvested Basin during 2002 hunting seasons. a radio-collared elk in the Hunter Questionnaire, Gunnison Elk, Hunting Seasons Please take just a minute to complete this questionnaire and RETURN IN THE ENCLOSED SELF-ADDRESSED AND STAMPED ENVELOPE. HUNTER NAME: nrsr CIRCLE THE MOST APPROPRIATE ANSWER: 1. Did you see the radio-collar on the elk before you decided to shoot at the elk. Yes No 2. If you saw the radio-collar before shooting, did you hesitate to shoot the elk because the elk was radio-collared? Yes No 3. Had the radio-collar caused noticeable damage to the neck hair and/or caused any sores or wounds on the neck? Hair Damage: Yes No Sores: Yes No 4. In your opinion, how was the radio-collar fitting around the elk's neck: Tightly Just about Right Loosely 5. In your opinion, do you think the general health condition of the elk was: Excellent Good Fair Poor Don't Know 6. When you skinned the elk, do you recall whether the rump fat was: Plentiful Fair Amount Present Not Much At All Don't Know 7. When you eviscerated the elk, do you recall whether internal fat amongst the organs was: Plentiful Fair Amount Present 8. Comments You Would Like to Make: THANK YOU: DAVE FREDDY WILDLIFE RESEARCHER COLORADO DIVISION OF WILDLIFE 317 WEST PROSPECT ROAD FORT COLLINS, CO 80526 Not Much At All Don't Know �.Fig, 1. Game ManagementUnits(54-551)i .in the Gunniso n BEl sin in 2000 and 2001, trapzenas (A-J) and elk capture sites I Captu re Sites ..., AL. • Dec:cm.i.e r 2!IlI ••• ~. a:m b.r :iI::t1[] ""d!lilii Almo.ril ti.~kir .AT,.illm · Ca ptu re Site Year AI .• ...... I\Ik,:jl IlylI"CI'I.I ... .. onl. TY.I!!r"GiI: . D.~mb.r2!ll[]. liv.o a ••••• r Cn:i:k ~WJ\ .D CJ CO .·Cz:IllnCr.ck ·co ~ COol OUe; 11\(11"••.. Or!!.e k DC -.Dry • ·.llap I:on.~ Oi.lO. .1b ••••••-: .De•• ~u~ Qud). ·~v. 0 .idl~·cr".~. :Oy';' niy.. c r•• k. ·uPP. .. i· . ,. "" . a:;;, eo> ICz:IlhDr •• k ~u" llaITop 1,T •. N ". HQ.:. ·H.or•• Qul<h ·...... it 'R ~ H Om:e: Oudl' RMor . .' :A····.. ." KK~.Oirnp I!l: II. ou<.ti· KZ·:.· KU";;.·BaSl'l·Mw· . . . . ..... . U>'ic.nyOn · L¢. .. . , ..... OIJCt. lIP ". M'C<:I1 p·••• un .PP .• P..oIcCreck1 · ... . . . 20 Kilometers . POI'on ilJdgc Pl! .• . :~~.~ -.It~.dW~· · B~I.n: . Ii..~ Or.•••k '..11.0 • RO • Reil lie n ilal T<lJ F\v'. 'ROSi' Be 2lie'" Cr'te.k sc ~.~'p.-~~.~e-k C.~I al\.r> o.ii<.ti 9Q. l'i:U .• ~zr.orec~ Tf;' Ti;r<i.r:fOOlMe." . . .. . 1iA ~ Tenmll. ~ifi-Q '11) .• TanI<:H·Dom. 1T.'; Ta~le' 11ip 'WA:~ ,~~$fAr!':.IOP.~ .cre.~k II\(() ~ W""d' Oucn '.WL. WilSon oU.<:7> . . ~",.u:•. ~I!lo ••••d.A~5Z18hz . .. . ·WVlI··WIIOI'ICr.cK·j ·lIIIy. ItlIlmery H.""". .o yo." '(lol'lle,Guk:!> y~ • y~ II>"'plne 1\11ge ,_, o VI �260 280 300 320 ..-o Gunnison Elk 0\ Seasonal Distribution of Females Radioed as Adults December 2000 - December 2003 '. GI\IIU76 Trap Zoues (Tz) (A - J) Hydrology Game Management Unit, (GMlJ 55) DAt.: Boundaries Figure 2. Seasonal distribution from December 2000 through December 2003 of female elk radio-collared as adults at age ?:30-months and captured throughout the Gunnison Basin in trap-zones A-J. Distribution includes locations of elk captures and deaths and was based on random selection of n = 35 from N = 51 adult females. See Methods for sampling protocols and definitions of seasons. �260 Gunnison 280 300 420 320 Elk . :~'(~: ..... :3.::::.:' N A ... ;4etf. UT?I.\ Zone 13 Grid x 20.0001ll NAD27 Trap Zones (lz) (A-J) Hydrology Game Management Units (GMlJ 55) DA U Boundaries Figure 3. Seasonal distribution from December 2000 through December 2003 of female elk radio-collared as calves at age 6-months that survived to age ~12-months and captured throughout the Gunnison Basin in trap-zones A-J. Distribution includes locations of elk captures and deaths and was based on random selection of n = 48 from N = 69 female >-' o calves. See Methods for sampling protocols and definitions of seasons. -....l �260 280 420 300 •....• o Gunnison Elk Seasonal Distribution of Males Radioed as Calves at Age 6 December 2000 - December 2003 N (I A :: _.v .' Zone lJ Grid x 20,O(lOm NAD27 00 Game Management Units (GMU 55) DAlJ Boundaries Figure 4. Seasonal distribution from December 2000 through December 2003 of male elk radio-collared as calves at age 6-months and captured throughout the Gunnison Basin in trap-zones A-J. Distribution includes locations of elk captures and deaths and was based on all calves N = 76. See Methods for sampling protocols and definitions of seasons. �290 310 330 350 Gunnison Elk North Seasonal Distribution or Females Radioed as Adults December 2000 - December 2003 390 370 ,~' Winter (n = 19 Elk: 226 Locations) * Spring (11 = 19 Elk; 113 Locations) ~ + Summer (u v 19 Elk; 121 locations) Fall (n = 18 Elk; 118 Locations) 4,320 Trap Zones (Tz) (F-J) Hydrology Game Management Units (GMt: 55) 4,300 ): 4,280 :1-: .... " ',::.', *> ,', .. =; ' . .' " '- 4,260 :', G!\1DJi7" v _ ' 0 1 20 Kilometers Ul-:Vllonc 13 Grid x 20.000m NAD27 Figure 5, Seasonal distribution from December 2000 through December 2003 of female elk radio-collared as adults at age ::::30-months that were captured north of U.S. Highway 50 in trap-zones F, G, H, I, and J of the Gunnison Basin. Distribution includes locations of elk captures and deaths and was based on random selection of n == 19 from N == 29 adult females, See Methods for sampling protocols and definitions of seasons _ o \0 �290 310 330 350 390 370 ~ Gunnison Elk North ., Seasonal Distribution of Females Radioed as Calves at Age 6 Months • December 2000 - December 2003 ... .' ~ :; •.....• •.....• o \\'int.:r (n » 27 Elk; 338 Spring (n = 27 Elk: 194 Summer (n n 27 Ell" lSI + }\~I ....... (n = 27 Elk; 161 Locations)~ [Bill 1 rap Zones (lz) 4,320 (F - J) GM1J53·· ... . .-......... Hydrology --- Game Matl~~mellt Units (GMt;55) _ 4,300 .:*+.. 4,280 GMU67 4,240 Figure 6. Seasonal distribution from December 2000 through December 2003 of female elk radio-collared as calves at age 6-months that survived to age 2: I 2-months that were captured north of U.S. Highway 50 in trap-zones F, G, H, I, and J of the Gunnison Basin. Distribution includes locations of elk captures and deaths and was based on random selection of n = 27 from N = 39 female calves. See Methods for sampling protocols and definitions of seasons. �290 310 330 350 I Gunnison Elk North 390 370 d I "_,' Seasonal Distribution of Males Radioed as Calves at Age 6 Months December 2000 - December 2003 GMt: 43 ... : ..... I .··GMF4S * .-, + Winter (il ~ 51 Elk; 419 Spring (n = 45 Elk; 216 Summer (D = 43 Elk; 206 F.ll (u« 38 Elk; 175 .1- 4,320 Trnp Zono, (T'l) (p. J) Hydrology Game Management Units (GMU 55) '_", ........... .~ .*<_: .. . G1\113 5]·· 4,300 ....... )~* (;1\1-(; 5~ . 4,280 4,260 GMt 67 II) lJTlvl ZOllO 13 G,id x 20,000m 20Kilom<!er5 (~Ml:551 NAD27 Figure 7. Seasonal distribution from December 2000 through December 2003 of male elk radio-collared as calves at age 6-months that were captured north of U.S. Highway 50 in trap-zones F, G, H, I, and J of the Gunnison Basin. Distribution includes locations of elk captures and deaths and was based on all calves N = 51. See Methods for sampling ,_. protocols and definitions of seasons ::: �290 Gunnison Elk South 310 . . "' ." 330 390 370 350 •......• •......• N .. ... GMu 54 Seasonal Distribution of Females Radioed as Adults 4,260 .*". :...cj_)..+,...~.....•• ~ + .. :: .,;' .+*., 4,240 ~8 :5 *..... ",'0: '-.' , GMU65. ··G'·':.+ ,;) +: 4,220 "'=c G~~U6il 4,200 Winter (n = 16 Elk; 163 Locations) .. GNllJ 76 * :_c Spring (n= 16 Elk; 77 Locations) Summer (n ~ 16 Elk; 94 Locations) + ~~IU19 Fall (n = 16 Elk: 86 Locations) ;:::::::::1 Trap Zones (Tt) 4,180 (A·E) ....... ';:.v • •• IlliJi:::=::::J'v_ ••••• _""W.·.·M·" Hydrology --- Game Management Units (GMIJ 67i 20 Kilometers VIM Zone 13 Grid x lO,OOOmNAD2? - DAU Boundaries Figure 8. Seasonal distribution from December 2000 through December 2003 of female elk radio-collared as adults at age ::::.30-monthsthat were captured south of U.S. Highway 50 in trap-zones A, B, C, D, and E of the Gunnison Basin. Distribution includes locations of elk captures and deaths and was based on random selection of n = 16 from N = 22 adult females. See Methods for sampling protocols and definitions of seasons. �290 310 330 390 370 350 Gunnison Elk South Seasonal Distribution of Females Radioed at Age 6 Months December 2000 - December 2003 "__""';" 4,260 .. :~+:. " .. 4,240 (;MU6~ .: ._ ..... 4,220 , .. GMlJ68 4,200 Winter (n n 21 Elk: 236 Locations) <) c +':. * GNrU 76 C,:: . .'; Spring (n =21 Elk; 135 Locations) :J Summer (ll·~· 21 Elk; 136 Locations) + Fall i:: l Trap ',":";.-:'" :.....: '.."..~... , (n ~ 20 Elk; 101 Location» . Cl\.lU79·. ZOlles rr» 4,180 (A-E) A '---===-----N 0 5 lJlM Zone 10 .............. 20 Kilometers n Grid x 20,OOOm1':A027 ~. .: . . ** .~... . ,.. .. . . ...: . :~~•..;;~ em . : .. --- :. - Hydrology Game Management Units (GMU 67) DAU Boundaries Figure 9. Seasonal distribution from December 2000 through December 2003 of female elk radio-collared as calves at age 6-months that survived to age :::12-months that were captured south of U. S. Highway 50 in trap-zones A, B, C, D, and E of the Gunnison Basin. Distribution includes locations of elk captures and deaths and was based on random selection of n = 21 from N = 30 female calves. See Methods for sampling protocols and definitions of seasons. _. ,__. w �290 Gunnison Elk South 310 330 350 390 370 >-' >-' . GMUS4 ~ Seasonal Distribution of Males Radioed as Calves at Age 6 Months December 2000 - December 2003 4,260 .... : to·, "0'0,,'0,,"-""" .. "0:",,,,0,, . """"""'.0 0'.'.:._0;;:" .' ... "'0:""0' '0' .. 0 .'.0 '0"·0'''''''0,"0'-'0''''''''''''0 "0.",,'0" .. ····".0·1 ·,,·1 ~.".. ..._ 4,240 GMU65 . 4,220 ...... ..•.. : .... ,' : ,.:), .:' d~~~6i 4,200 ,*' .mIU 76 * Spring (n ~ 22 Elk: 65 Locations) ::.; Summer (n = 16 Elk; 49 Locations) + Fall :.".~ (n ~ 8 Elk; 31 Locations) Trap Zones (Tz) ;"~~~~~~~j (A - E) Hydrology N A 0 5 10 Game Management lInits (Gl'vIU 67) 20 Kilometers UTM Zon. 13 Grid x 20.000m NAD27 4,180 - DAU Boundaries Figure 10. Seasonal distribution from December 2000 through December 2003 of male elk radio-collared as calves at age 6-months that were captured south of U. S. Highway 50 in trap-zones A, B, C, D, and E of the Gunnison Basin. Distribution includes locations of elk captures and deaths and was based on all calves N = 25. See Methods for sampling protocols and definitions of seasons. �290 310 330 370 350 390 Summer (n= 46 Elk; 172 Locations) Gunnison Elk North Seasonal Distribution of Females in June All Elk Age ~12 Months December 2000 - December 2003 Trap ZOIl"" (Tz) (F· J) Hydrology Game Management Units (GMlJ 55) 4,320 4,300 4,280 4,260 , . G~1t()7·· urM Zone) 3 (Jrid x 20.000m NAD27 ....... ,'"' . Figure 11. Distribution during June 2001-2003 of radio-collared female elk whose age was > 12-months when locations were acquired. Elk were captured north of U. S. Highway ::: 50 in trap-zones F, G, H, I, and J of the Gunnison Basin and locations were based on the same females randomly selected as adults or calves that were used to describe composite VI seasonal distributions of elk where n = 46 from N = 68 females. �290 Gunnison Elk South 310 .; 330 350 ,_. ,_. 390 370 0\ ':.: ':' GMUS4. '". Seasonal Distribution of Females in June All Elk Age > 12 Months December 2000 - December 2003 4,260 .:: . .. ' 4,240 :..: . . CMU6$. -: .... 4,220 ..... ~ GMU 68. 4,200 .. G~U7~ C; :_ Gt.1:U 79·. Summer (n = 37 Elk; 127 Locations L;.,..u Tr~~:~es (Tz) 4,180 ....•..•....•.. Hydrology N A °,._5==5 •°•••••• • 1 2,0 Kilometers trIM Zone 13Grid x 20,000111 NADl7 ~ . GMF 80 --- - Game Management Units (GMU 67) DAU Boundaries Figure 12. Distribution during June 2001-2003 of radio-collared female elk whose age was :::12-months when locations were acquired. Elk were captured south of U.S. Highway 50 in trap-zones A, B, C, D, and E of the Gunnison Basin and locations were based on the same females randomly selected as adults or calves that were used to describe composite seasonal distributions of elk where n = 37 from N = 52 females. �290 310 330 350 390 370 Gunnison Elk North Maximum Movement from Trapsite Females Radioed as Adults - - •••• Trapzone F (n = 3) _ ••,- •••• Trapzone G (n ~ 6) GMU43 SI -----•...Trapzone H (n 3) GM1J"-4 = ~ Trapzone J (u « 3) _.., Trapzone J (n = 4) Trapsite 4,320 Trap Zones (Tz) (F· J) Hydrology Game Management Units (GMU 55) GMUS3 4,300 4,280 ,,_ 4,260 G,\1U67 N A 0 5 to 20 Kilometers UTM Zone 13 Grid x 20,00001 NAD27 •....• •....• Figure 13. Maximum distances and directions that adult female radio-collared elk moved from their trap-sites between December 2000 and December 2003. Elk captured as --.J adults at age ::-.30-months north of U. S. Highway 50 in trap-zones F -J of the Gunnison Basin. Movement vectors based on the same adult female elk randomly selected to describe composite seasonal distributions of elk which had ::-.8locations (n = 19). �290 3JO 330 390 370 350 •.....• •.....• Gunnison Elk North 00 Maximum Movement from Trapsite Females Radioed as Calves at Age 6 Months December 2000 - December 2003 4,320 4,300 4,280 4,260 GMlJ ~~1 Trapsites Trap Zones (Tz) (F .J) Hydrology G3Jl1e Management linit, (Glv[lJ 55) 4,240 Figure 14. Maximum distances and direchons that young temaIe radlo-coIlared elk moved from theIr trap-sItes between December 2000 and December 2003. Elk captured as calves at age 6-months north of U.S. Highway 50 in trap-zones F-J of the Gunnison Basin. Movement vectors based on the same calf female elk randomly selected to describe composite seasonal distributions of elk which had::::8 locations and generally attained an age ::::12-months (n = 27). �290 310 330 350 390 370 Gunnison Elk North - aximum Movement Irorn Trapsire Adult Males Age > 12 Months December 2000 - December 2003 - •••• 'Irapzone F (n = 5) _.,,- GMt.43 "GMU48 ••• Trapzone G (n ~ 15) I ....-•... Trapzone H (n ~ 5) ~ Trapzoue I (n = 5) •••••• Trapzone J (n = 10) Trapsites Trap Zones (Tz) (f· J) Hydrology 4,320 Gauie Management Unit> (GMU 55) 4,300 4,280 GMU.56 ... 4,260 GNW 67 N A 0 5 UT:\·! Zone 10 20 Kilometers 13 Grid x 20.000m NAD27 Figure IS. Maximum distances and directions that young male radio-collared elk moved from their trap-sites between December 2000 and December 2003. Elk captured as calves at age 6-months north of U.S. Highway 50 in trap-zones F-J of the Gunnison Basin. Movement vectors based on the same male elk used to describe composite seasonal distributions of elk which had ~8 locations and generally attained an age ~12-months (n = 40). \0 �,_. tv 290 310 330 350 o 390 370 GUID1ison Elk South Maximum Movement from Trapsite Females Radioed as Adults December 2000 - December 2003 4,260 4,240 -..... . GMU65 4,220 ·1 - -~ Trapzone A (n = 4) _ •••-.... Trapzone B (n = 3) •••••••.• TrapzoneC(tl"'3) ==-=--- Trapzone D (n 3) = C;;~1U6$ _..... • Trapzone E (u= 3) Trapsites Tr:\j) Zones (Tz) ................ 10 l'TIv1 Zone 13 Grid x 20,OOOm NAD27 4,200 (A· E) Hydrology --- Game Management Units (GMli 67) - DAD Boundaries Figure 16. Maximum distances and directions that adult female radio-collared elk moved from their trap-sites between December 2000 and December 2003. Elk captured as adults at age :::30-months south of U.S. Highway 50 in trap-zones A-E of the Gunnison Basin. Movement vectors based on the same adult female elk randomly selected to describe composite seasonal distributions of elk which had:::8 locations (n = 16). �290 Gunnison Elk South Maximum Movement from Trapsite Females Radioed at Age 6 Months December 2000 . December 310 330 390 370 350 'GMU54 .: 2003 4,260 G~1U551 :.~ .. 4,240 ' :" ..~1\.fU65 4,220 'GMU68 K~·'l .: :'1 GMU76· .' 4,200 ! :! . r . i I·· I ".i' i r ... · ~ ';." __ • -=:::5'." ••20Kilometers VIM Zone 13 Grid x 2U.ooOm NAD27 t _....... Trapzone B (n ~ 3) ._._._,.. Trapzone C (n ~ 4) ~ Trapzone D (u « 4) •••• TrapzoneE • Trapsites Wn?j (1I~3) Tr~1'loues rr» (A-E) ..•.•....•.•... Hydrology 4,180 Figure 17. Maximum distances and directions that young female radio-collared elk moved from their trap-sites between December 2000 and December 2003. Elk captured as calves at age 6-months south of U.S. Highway 50 in trap-zones A-E of the Gunnison Basin. Movement vectors based on the same calf female elk randomly selected to describe composite seasonal distributions of elk which had:::8 locations and generally attained an age :::12-months (n = 21). N •...... �290 310 ',' Gunnison Elk South 330 350 390 370 •..... N N . -. ('_,.j\1U 54 Maximum Movement from Trapsite Adult Males Age::: 12 months December 2000 - December 2003 4,260 4,240 ... .... . GMU65 4,220 4,200 - - •••• Trapzoue A (n ~ 1) _00'_ •••. Trapzoue B (n = I) (;MU 76· ....•. •••••• ~ Trapzone C (n ~ 8) ~ Trapzone D (n ee 1) .._.. Trapzouc E (11 .~. I) •j ['.:.,.•... Gl\IU7~ . Trapsites Trap Zones (I z) 4,180 (A-E) Hydrology Game Management S ~ 0 10 20Kilomotcf> '" UTM lOll< 13 C"n-idx 20,OOOm NAD27 Units (Glvl1.: 67) - DAlJ Boundaries Figure 18. Maximum distances and directions that young male radio-collared elk moved from their trap-sites between December 2000 and December 2003. Elk captured as calves at age 6-months south of U.S. Highway 50 in trap-zones A-E of the Gurmison Basin. Movement vectors based on the same male elk used to describe composite seasonal distributions of elk which had ~8 locations and generally attained an age ~12-months (n = 12). �290 310 Gunnison Elk North Minimum Convex Polygon Homerange Females Radioed as Adults 330 390 370 350 • L _ G;\1t! 43 , GMU,48 December 2000 - December 2003 Trapsites I "Trapzone F (II ~ 3) I ,.... I·"" TrapzoneG (n = 6) [:: .•.•..• ] Trapzone H (11 = 3) o Trapzone I (n = 3) CJ Trapzone J (n = 4) 4,320 Hydrology Game Management Units (GMIJ 55) . .:.:; 4,300 GMU481 4,280 G~ro,~6 , - 4,260 GMU67 ....::.;.. u _ ,10 20 Kilometers Ci\lI~)551 tJI}'1 Zone JJ (Jrid x 20.(lOOm NAD27 Figure 19. Minimum convex polygon (MCP) home ranges for adult female radio-collared elk between December 2000 and December 2003. Elk captured as adults at age ::::30months north of U. S. Highway 50 in trap-zones F -J of the Gunnison Basin. MCP based on the same adult female elk randomly selected to describe composite seasonal distributions of elk which had::::8 locations (n = 19). >-' N w �290 31.0 330 350 390 370 .....• N +>. Gunnison Elk North 'Minimum Convex Polygon Homerange Females Radioed as Calves at Age 6 Months December 2000 - December 2003 4,320 4,300 4,280 4,260 'Irapzone G (n = 10) Trapzone H (n = 3) Trapzone [ (0 ~ 6) Trapzone J {n = 3) Hydrology N A 0 J lV .0.' Game Management Units (GMU 55) 4,240 DA \J Boundaries Figure 20. Minimum convex polygon (MCP) home ranges for young female radio-collared elk between December 2000 and December 2003. Elk captured as calves at age 6months north of U.S. Highway 50 in trap-zones F-J of the Gunnison Basin. MCP based on the same calf female elk randomly selected to describe composite seasonal distributions of elk which had::::8 locations and generally attained an age ::::12-months (n = 27). �290 310 330 350 •L _ Gunnison Elk North Minimum Convex Polygon H Adult Males Age?: 12 Months December 2000 - December 2003 390 370 .... .. J '. GMU'.I3 1-11"'1 . GMU48 " 'lrapsites Trapzone F (n = 5) Trapzone G (n= .•........... L ..........; CJ Trapzonc I (n ~ 5) C] Trapzone J (n= HIlt- 4,320 Hydrology Game Menagement Units (GMU 55) 4,300 .: GMU481 GMU~~ . 4,280 4,260 GMU67 ~v••••i===~.v•••••••••• • 20Kilcmeters vI}.r Zone J3 Grid x 20,OOOm NAD27 Figure 2l. Minimum convex polygon (MCP) home ranges for young male radio-collared elk between December 2000 and December 2003. Elk captured as calves at age 6months north of U.S. Highway 50 in trap-zones F -J of the Gunnison Basin. MCP based on the same male elk used to describe composite seasonal distributions of elk which had ::::8locations and generally attained an age ::::12-months (n = 40). N VI �290 Gunnison Elk South 310 330 350 390 370 tv G:]\1D 54 0\ Minimum Convex Polygon Homerange Females Radioed as Adults December 2000 - December 2003 .... : :.. : 4,260 ", .-.F·"·7~;".-...'..'" <,..... ,... 4,240 . ;..,,"<:::;:..• -j: ....: ". '. GMU65 i . ...•. . ~~ -: ~ 4,220 \ \ ~~ . t;. .. \ . \. •- L _ I ...GJ.V1U76 :1-•••• Trapzone A (n = 4) t_lIi . . Trapzone B (n = 3) , Trapzoue C (n = 3) 0 CJ Trapzone D (n ~ 3) J •••••••••••••• . Gr.:llJ79 4,200 Trapsites f 1 Trapzone E (n = 3) I- 4,180 Hydrology Game Management N A 0 S 10 20 . I KIlometers VIM Zone 13 Grid x 20,OOOmNADZi lJnit$ (GMlJ 67) .' - DAlJ Boundaries Figure 22. Minimum convex polygon (MCP) home ranges for adult female radio-collared elk between December 2000 and December 2003. Elk captured as adults at age ::::30months south of US. Highway 50 in trap-zones A-E of the Gunnison Basin. MCP based on the same adult female elk randomly selected to describe composite seasonal distributions of elk which had 2:8 locations (n = 16). �290 Gunnison Elk South 310 : 330 " 350 390 370 " GiVlll 54·. 4,260 ••,! .'.... ,!: ···,l ".:" ..·::" :.f'''.'i.,,. 4,240 .9iVIU 6S. .:..<, T 4,220 G~6~ ~ .,. \ •....•.•...•.....• . . \ (;~HJ 79. \.: ~ "\. \ A Im1 5 10 20 , Kilometers Zone· J 3 ('",jd X 20,000lU NAD2i Trapzone A (n ~ 7) L_I '_IIi ",•..•......•.., , , ~\ 0 Trapsites a-IIII: "\: \ N 4,200 •- .. '~. GMU80 Trapzoue C (n ~ 4) CJ Trapzone D (n 4) = , Cl I --- ..\\ r Trapzonc [l (n = 3) Trapzoue E (n=3) I-- 4,180 Hydrology Game Management Vnits (GMLI 67) DAt; Boundaries Figure 23. Minimum convex polygon (MCP) home ranges for young female radio-collared elk between December 2000 and December 2003. Elk captured as calves at age 6months south of U.S. Highway 50 in trap-zones A-E of the Gunnison Basin. MCP based on the same calf female elk randomly selected to describe composite seasonal distributions of elk which had ~810cations and generally attained an age ~12-months (n = 21). ..... N -.l �290 'Gunnison Elk South 310 330 350 - 390 370 tv .:GMbs4·, 00 Minimum Convex Polygon Homerange . Adult Males Age 2::12 months December 2000 - December 2003 4,260 4,240 GMll65 . ",; 4,220 4,200 • Trapsites Trapzone A (11 ~ 1) :I••••• It• .,i Trapzone B (n « 1) C:~J Trapzone C (u= 8) ,.~IHtJ79,. ..... N A 0 ~ trIM 5 2011< 10 20 IKilometers J 3 Grid x 20,OOOm NAD27 D CJ Trapzone D (u ~ 1) Trapzonc E (n= \) 4,180 Hydrology Game Management Units (GMU 67) DAt' Boundaries Figure 24. Minimum convex polygon (MCP) home ranges for young male radio-collared elk between December 2000 and December 2003. Elk captured as calves at age 6months south of U.S. Highway 50 in trap-zones A-E of the Gunnison Basin. MCP based on the same male elk used to describe composite seasonal distributions of elk which had 2::8locations and generally attained an age 2::12-months (n = 12). �280 300 320 340 360 380 420 400 ....... Gunnison Elk 4,320 Mortality of Female and Male Calves Age 6 to 12 Months Winters 2000 - 01 and 2001 - 02 4,300 4,280 4.240 '~:' (5) Predation "*"* =:: 8 (0) Suspected Predation (0) Malnutrition (0) Suspected Malnutrition (lJ L4.220 Accident + (2) Unknown Mortality Hydrology r-"_' ...... ..1 Game Management Units (GMU 55) DAU Boundaries Trap Zones (A·J) rr» 1-4.200 ,_. Figure 25. Locations of mortalities for female (n = 8) and male (n = 13) radio-collared calf elk during winter between 15 December and 15 June, 2000-01 and 2001-02. Elk were ~ captured throughout the Gunnison Basin in trap-zones A-J and were age 6 to 12 months at time of death. �•.....• 280 300 320 340 380 w 420 400 o Gunnison Elk 4,320 Mortality of Adult Females Age ~ 12 Months 2001 - 2003 4,300 4,280 4,240 4,220 ••• Hunting Mortality (n ....38) + Unknown Mortality (n ~ 1) Hydrology Game Management Units (GMU 55) VTM Zone 13 Grid x 20,OOOm NAD27 u 4,200 DAU Boundaries Trap Zones (Tz) (A· J) Figure 26. Locations of mortalities (n = 40) for adult female radio-collared elk between January 2001 and December 2003, Elk were captured throughout the Gunnison Basin in trap-zones A-J and were age :::::12 months at time of death. �28() 300 320 340 360 380 42() 40() Gunnison Elk Mortality of Adult Males Age::: 12 Months 2001 - 2003 4.320 GMU ~21' 4,300 GMU62 4.240 '.. ~M~i~ o 4,220 .•. • GMU68 Illegal Hunting Mortality (n r. 5) Hydrology Game Management N A ° Units (GMt; 55) 4,200 OAt: Boundaries J.V ~ L!TMZoneI3Gridx20,000mNAD27 GMU 76 (Tz) EJerg Trap(1\ Zones J) •.....• VJ Figure 27, Locations of mortalities (n = 26) for adult male radio-collared elk that occurred between July 2001 and December 2003, Elk were captured throughout the Gunnison Basin in trap-zones A-J and were age:::12 months at time of death. •...... �132 �133 JOB PROGRESS REPORT State of ---'C"'-o=l:.;::o""ra=d=o'--_____ : Division of Wildlife - Mammals Research Work Package No. ___ ...=:.3-'-7--'.4-"-0 : Chronic Wasting Disease and Other Wildlife Disease Management Task ~1 : Chronic Wasting Disease in Mule Deer Monitoring & Management Period Covered: July 1 2002 through June 30, 2003 Author: Michael W. Miller and L. L. Wolfe Personnel: L. A. Baeten, T. H. Baker, M. M. Conner, K. Cramer, T. R. Davis, V. Dreitz, C. P. Hibler, N. T. Hobbs, E. Hoover, D. O. Hunter, E. Knox, C. E. Krwnm, C. T. Larsen, N. Mier, B. E. Powers, J. Rhyan, C. J. Sigurdson, T. R. Spraker, K. Taurman, E. S. Williams, D. Wroe Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT We continued conducting research on various aspects of chronic wasting disease (CWD) epidemiology and management. Here, we report progress in ongoing and recently-completed work. Studies focused on improving and expanding surveillance in free-ranging populations, understanding and modeling transmission mechanisms, identifying ecological and anthropogenic factors that may influence epidemic dynamics, and evaluating and applying alternative diagnostic and control strategies. In addition to preliminary findings reported here, eight original studies, as well as one review article, were published publication during this segment; citations are appended to the report. INTRODUCTION We continued conducting research on various aspects of chronic wasting disease (CWD) epidemiology and management. Some parts of this work were conducted in collaboration with investigators at Colorado State University, the University of Wyoming, and elsewhere. Specific projects were supported with various combinations of funds from the Colorado Division of Wildlife (CDOW), Federal Aid in Wildlife Restoration Project W-153-R, the U.S. Department of Agriculture, and National Science FoundationlNational Institutes of Health Grant DEB-0091961. �134 METHODS Our work on CWD is both multidisciplinary and multifaceted, but broadly falls under the topics of "epidemiology and management" or "pathogenesis and diagnosis". For simplicity, we describe progress under those headings below. STUDIES OF CWD EPIDEMIOLOGY & MANAGEMENT We continued or initiated studies related to surveillance, transmission mechanisms, epidemic trend forecasting, potential host range and strain variation, risk factors, and management tools and feasibility as aids to understanding and controlling CWD in free-ranging deer and elk in Colorado. Statewide surveillance: The discovery of CWD in northwestern Colorado in January 2002 created a sudden demand for both more widespread surveillance and more rapid turnaround on laboratory results. Consequently, the CDOW's CWD surveillance program was overhauled and its capacity greatly expanded over the summer of 2002 in order to meet anticipated demands for surveillance data, as well as to meet policy-based decisions to provide carcass quality assurance information for individual hunters. The most notable changes were the addition of three regional submission laboratories, streamlining of tissue sampling methods, and incorporation of a rapid screening test for CWD diagnosis. Details of overall programmatic features and changes were described on a new CWD-oriented CDOW web page (http://wildlife.state.co.us/CWD/index.asp); details of the evaluation of modified sampling and testing procedures are described below. Transmission mechanisms: We summarized findings on empirical evidence of animal-animal transmission of CWD and the relative importance of this mechanism in epidemic dynamics. We also completed an experiment comparing the relative contributions of live animals, contaminated environments, and infected carcasses to CWD transmission. In this study, 34 free-ranging mule deer from two sources distant to known endemic foci of chronic wasting disease (Rocky Mountain Arsenal National Wildlife Refuge, US Air Force Academy) were captured for use as experimental subjects during MarchMay 2002. We transported these deer to the Colorado Division of Wildlife's Foothills Wildlife Research Facility (FWRF), where they were placed in paddocks (n = 3 replicates/exposure route; n = 3 deer/paddock). Exposure treatments were: confinement in paddocks housing naturally-infected deer (1 infected deer/paddock), confinement in paddocks where infected deer previously resided, and confinement in paddocks where carcasses from CWD-infected deer have decomposed in situ (1 carcass/paddock); unexposed control paddocks are also being maintained. Entire paddock groups will be sacrificed and examined at the first sign of CWD in any subject deer within a paddock. We compared infection rates within and among treatments to examine which of these may contribute to perpetuation of CWD epidemics. Modeling epidemic dynamics in captive mule deer: Developing detailed, temporally dynamic models of CWD in wild populations is a pressing management need, but available field data are presently insufficient to clearly reveal natural trends in ongoing epidemic dynamics. Moreover, there are several plausible ways to model CWD transmission mechanisms, yet field data will likely not provide sufficient resolution for discerning the most appropriate representation. To begin understanding how to best model CWD transmission, we have undertaken a model selection exercise using a time series of data on prevalence on CWD in captive mule deer. We assembled 26 years of data (1974-2000) from CDOW's Foothills Wildlife Research Facility. These data are being used to evaluate strength of evidence for a set of candidate models involving indirect and direct transmission, as well as with and without latency �135 periods. Estimates of transmission rates derived from these models will provide an upper bound on what could be expected in wild populations and will guide construction of candidate sets for modeling those populations. Host range and strain variation: We continued a series of experimental studies in cattle, fallow deer, and mountain lions to explore potential host range of CWD after intense but natural exposure; these experiments compliment ongoing surveillance for evidence of infection in species not known to be natural hosts ofCWD, including moose, mountain lions, and cattle. We also continued work looking for evidence of strain variation in CWD agent from various deer sources using domestic ferrets as a laboratory model. Effects of land use on prevalence: Because land-use changes are likely to shape the spatial and temporal dynamics of CWD, as well as options for its management, we have been working to understand the effect ofland use on patterns of CWD prevalence in free-ranging mule deer. We conducted a study to determine whether CWD prevalence in urban areas is higher than prevalence in non-urban areas. We categorized two land use types: urban areas contained ~ I housing unit/I 0 acres and non-urban areas (e.g., ranch, state, and federal lands) contained < 1 housing unit/l0 acres. We compared CWD prevalence between land use types in 3 study areas in northern Colorado (Glacier View Meadows [GVM], Horsetooth [HT], Estes Park [EP]) in which urban and non-urban areas were juxtaposed. In each study area, we delineated urban areas surrounded by a 1-2 km buffer and non-urban areas concentric to the buffer. Deer were sampled in approximately equal numbers from the two land use categories. We used a combination of data collected from mule deer sampled via postmortem (Miller et al., 2000, 1. Wildl. Dis. 36:676-690; Miller & Williams, 2002, Vet. Rec. 151:610-612) and antemortem (Wolfe et aI., 2002, J. Wildl. Manage. 66:564-573) methods described previously; our target was 210 samples for each land-use category, which provided the ability to detect 10% differences in prevalence between categories with 90% probability at the 0.05 confidence level. We assumed sampling was normally distributed and tried to balance sampling equally among study areas. Selective predation upon infected mule deer: To test for evidence of selective predation, we began a study to compare prevalence of CWD among puma-killed mule deer to prevalence among mule deer harvested or randomly culled by humans within home ranges of collared mountain lions. Sample size calculations were based on the number of deer samples needed to detect two-fold differences in CWD prevalence: we assume that if the mountain lions are showing selectivity for deer with CWD, then the prevalence in the deer killed by mountain lions will be at least twice the prevalence of CWD in the local deer population. Telemetry-marked mountain lions are being monitored and, when available, brainstem (medulla oblongata at the level of the obex), retropharyngeallymph nodes, and tonsils are collected from pumakilled mule deer carcasses; where none of these tissues are available, we will try to locate and sample other lymphoid tissues (e.g., submandibular or mesenteric lymph nodes, Peyers patches, etc.). Representative subsamples of collected tissues will be fixed in 10% neutral buffered formalin, and the remainder stored frozen. Tissues will be evaluated for presence of PrPCWD accumulations using established immunohistochemistry (IRC) techniques; IRC-positive cases will be further evaluated with hematoxylin and eosin staining to stage the duration of CWD infection. We will compare CWD prevalence among puma-killed deer to prevalence among deer harvested by hunters in the same area. Using cumulative location data from each collared puma, home range will be estimated. Data from mule deer harvested and sampled within each home range will be extracted from our harvest survey database, preferentially using data collected during the period of predation sampling where sufficient harvest data are available for that time period. To assess differences between predation- and harvest-associated prevalence, we will calculate the CIon the difference as described above; if the CI does not include 0, then we will conclude that these rates differ. �136 Influence of trace minerals on susceptibility: To investigate the potential influence of trace minerals on CWD susceptibility, we began two independent studies. In a retrospective study, we will use archived tissues to compare tissue levels of copper (Cu), molybdenum (Mo), and manganese (Mn) in mule deer infected with CWD to levels in apparently uninfected deer from the same geographic area. We also started an experiment to examine the effect of Cu supplementation on CWD susceptibility in white-tailed deer, wherein we will compare the natural infection rate and course of CWD in captive deer receiving a sustained-release oral Cu supplement to the rate and course in unsupplemented controls residing in the same paddock. Vaccination as a preventive tool: We collaborated with investigators from Colorado State University to conduct a pilot study evaluating safety and serologic responses of mule deer to an anti-PrP vaccine. Four captive deer (2 vaccinates and 2 controls) were monitored and sampled over a 4-month period for evidence of vaccine effects on health and serum antibody levels. Evaluation of an urban CWD management strategy: Recognizing the need for alternatives to traditional strategies for controlling CWD, we initiated a pilot study to evaluate "test and cull" as an approach for managing CWD in urban habitats. Previously, models exploring probable consequences of various management strategies identified selective removal of infected individuals as a potentially effective method for reducing CWD prevalence in mule deer populations, provided that infected deer were detected early and a large (>50%) proportion of the population could be sampled annually (Gross and Miller, 2001, J. Wildl. Manage. 65:205-215). During November-December 2002, 113 free-ranging mule deer were captured, tested, and marked with timed-release radiocollars in urban areas throughout Estes Park to assess the feasibility of such a management approach. This sampling effort represented testing of about 25% of the adult mule deer residing Estes Park. In January 2003, biopsy-positive deer were culled. Dropped radiocollars were recovered in March-April 2003 for reuse in a second round of sampling planned for April-May 2003. In addition to the primary goal of assessing feasibility, data gathered in the course of this study will also be useful in improving our understanding and modeling of the influences of urban landscapes on CWD epidemiology. STUDIES OF CWD PATHOGENESIS & DIAGNOSIS We continued or initiated studies related to rapid screening test evaluation, pathogenesis in natural hosts, and live-animal diagnostic test refinement and evaluation as aids to improving approaches for CWD surveillance and diagnosis in free-ranging deer and elk in Colorado. Evaluation of a rapid screening test: In conjunction with expanded CWD surveillance in Colorado during Sep-Dec 2002, tissue samples (n = 25,050 total) from 23,256 mule deer, white-tailed deer, and Rocky Mountain elk collected statewide were examined using an ELISA developed by Bio-Rad Laboratories, Inc. (brELISA) in a two-phase study. In the validation phase of this study, a total of 4, 175 retropharyngeal lymph node (RLN) or obex (OB) tissue samples were examined independently by brELISA and immunohistochemistry (IRC). There were 137 IRC positive samples and 4,038 IRC negative samples. Optical density (OD) values from brELISA were classified as "not detected" or "suspect" based on recommended cut-off values during the validation phase. Based on the validation phase data, only RLN samples were collected for the field application phase of this study and only samples with brELISA OD values> 0.1 were examined by IRC. We estimated assay performance parameters (sensitivity, specificity, agreement) for brELISA to determine the utility of this rapid screening assay in CWD surveillance. programs. �137 Pathogenesis in natural host species: We continued our work studying the pathogenesis of CWD in whitetailed deer after oral inoculation with infectious, conspecific brain tissue. This study will complement studies documenting CWD pathogenesis in mule deer and elk that already have been completed. Evaluation of antemortem diagnostic techniques: In order to better study and manage CWD across landscapes where hunting and culling are not feasible sources of diagnostic samples, we continued working to refine and evaluate techniques for sampling live animals. Previously, we conducted a field study to evaluate tonsil biopsy immunohistochemistry (IHC) as a tool for diagnosing CWD in live, freeranging mule deer and estimating prevalence. Based on our initial success, we have applied these techniques to gather data for new studies related to effects of land use patterns on CWD prevalence and its management, as described elsewhere in this report. We also initiated a study to evaluate a prospective rapid blood test for diagnosing CWD in live deer. A total of37 samples from 21 different captive mule deer, some infected with CWD, were submitted to a private testing laboratory (GeneThera, Denver, CO) for evaluation using collection materials and instructions provided by the laboratory. In order to objectively assess reliability and repeatability of the candidate assay, the testing laboratory was blinded to the infection status and animal identification for individual samples that we submitted. RESULTS AND DISCUSSION STUDIES OF CWO EPIDEMIOLOGY & MANAGEMENT Statewide CWD surveillance: The CDOW sampled over 26,000 deer and elk harvested or culled in northeastern Colorado and other select locations. Survey results were posted on the Division's CWD web page. Prevalence data also will be used to augment an existing database that is the foundation for ongoing analyses and modeling of temporal and spatial aspects ofCWD epidemiology, as well as for evaluating responses to management. This year's data will be particularly useful in further exploring local patterns of disease prevalence related to deer movement, density, and land use patterns. Moreover, the surveillance strategy and methods first devised and implemented in Colorado recently served as a model for developing national recommendations on CWD surveillance in free-ranging populations. Transmission mechanisms: A manuscript describing our findings on the relative importance of animal-animal transmission of CWD, as compared to maternal transmission, was accepted for publication and should appear this fall. Our experiment comparing the relative contributions of live animals, contaminated environments, and infected carcasses to CWD transmission revealed that CWD can be transmitted indirectly, from environments contaminated by excreta or decomposed carcasses to susceptible animals. Under experimental conditions, mule deer became infected in 2 of 3 paddocks containing naturally infected deer, in 2 of 3 paddocks where infected deer carcasses had decomposed in situ -l.8 years earlier, and in 1 of 3 paddocks where infected deer had last resided 2.2 years earlier. Our data suggest that indirect transmission and environmental persistence of infectious prions will complicate efforts to control CWD, and perhaps other animal prion diseases. Modeling epidemic dynamics in captive mule deer:' Preliminary analyses suggest that indirect transmission models best represent epidemic data; moreover, our model selection results align well with independent empirical findings on CWD transmission mechanisms. We will continue refining candidate �138 models before making final comparisons and parameter estimations. Findings should be of use in refining epidemic models of CWD in free-ranging mule deer populations. Host range and strain variation: Cattle (n = 11) living in paddocks with naturally-infected mule deer remained healthy through 6 years of exposure; in contrast, only 1 of 12 mule deer introduced into these same paddocks in 1997 is still alive. Our results are consistent with data from cell-free conversion (Raymond et al., 2000, EMBO 19:4425-4430) and intracerebral (IC) challenge (Hamir et al., 2001, 1. Vet. Diag. Invest. 13:91-96) studies that suggest the probability of natural susceptibility to CWD in cattle is extremely low. Similarly, neither signs nor postmortem evidence of infection have been observed in fallow deer (n = 24) exposed to infected mule deer for :<:;2.5years, and mountain lions (n = 3) consuming carcasses of CWD-infected deer and elk for> 1 year also have remained healthy. No evidence of infection has been observed in moose, mountain lions, or cattle examined via ongoing surveillance. Clinical signs and postmortem findings consistent with CWD in ferrets were observed in four of five ICinoculated with tissue from infected deer, but have not been observed in the free-ranging white-tailed deer or control groups. Incidence and incubation periods were consistent among affected groups. Preliminary assessment of Western blots (WB) revealed no apparent differences in glycosylation patterns among WBpositive ferrets. In the absence of changes in status in the unaffected groups, we will terminate this study in the next 6 months and summarize our findings. Effects of land use on prevalence: Preliminary analyses revealed that CWD prevalence was higher among deer sampled from urban areas (12.5%, CI=8.4-16.8%, n=243) than among deer from juxtaposed nonurban areas (7.3%, CI=4.3-10.3%, n=288) (Fisher's exact test, P=0.04). The magnitude of difference between CWD prevalence rates associated with urban and non-urban land use (5.3%, CI=2.4-8.2%) further emphasized the apparent effect of urban land use on CWD prevalence. Although CWD prevalence varied somewhat among study sites, it did not differ (Fisher's exact test, P=0.088). Areaspecific differences may reflect greater risk or exposure among subpopulations. However, the trend of higher CWD prevalence in areas of urban land use was consistent across all three sites. Our findings suggest that urbanization is playing an undesirable role in CWD epidemic dynamics in northcentral Colorado's mule deer populations. The underlying cause of this influence on CWD prevalence remains unclear. Urban landscapes may attract or artificially congregate wild cervids. Supplemental feeding, although illegal in Colorado, occurred throughout urban areas in all 3 of our study sites. Urban areas also may provide refuge from predation. Mountain lions are likely the main predator of deer in this area, but they are reclusive and seldom hunt in urban lands. Deer may become more sedentary in urban areas - in extreme cases, urban development may even promote elimination or modification of seasonal migration patterns made by resident deer. Regardless of the reason(s), urban landscapes clearly cannot be ignored in attempts to manage CWD and perhaps other important wildlife disease problems. Selective predation upon infected mule deer: Our work continues from a pilot study conducted to evaluate available global positioning system (GPS)-based telemetry collars for use in this sampling application. We are now sampling mule deer carcasses to test for evidence ofCWD infection by monitoring collared mountain lions 1-3 times/week and locating prospective kill sites using a remotely downloadable GPS telemetry system (Lotek, Inc.; model GPS4000). We will continue refining our monitoring approach to ensure that we find kill sites quickly enough to retrieve a suitable tissue sample to test for CWD. Whether target sample sizes can be attained in the time planned for this work remains to be determined. Influence of trace minerals on susceptibility: Both studies are underway. �139 Vaccination as a preventive tool: We observed no adverse effects of vaccination on captive mule deer; serology results are pending. Evaluation of an urban CWD management strategy: Data from our December pilot trial indicate that testing and culling mule deer appears to be a viable approach for managing CWD in Estes Park. Based on the success of the first round of pilot testing, the CDOW has committed to a 5-year management experiment to evaluate the efficacy of test and cull in lowering CWD prevalence in an urban mule deer population. A manuscript describing the results of our feasibility study is in preparation. STUDIES OF CWD PATHOGENESIS & DIAGNOSIS Evaluation of a rapid screening test: In the validation phase, using IHC-positive cases as known CWDinfected individuals and assuming IHC-negative cases were uninfected, the relative sensitivity of brELISA depending on species ranged from 98.3-100% for RLN samples and 92.1-93.3% for OB samples; the relative specificity ofbrELISA depending on species ranged from 99.9-100% for RLN samples and was 100% for OB samples. Overall agreement between brELISA and IHC was ~97.6% in RLN samples and ~95.7% in OB samples of all species where values could be calculated; moreover, mean brELISA OD values were ~46x higher in IHC-positive samples than in IHC-negative samples. Discrepancies were observed only in early-stage cases ofCWD. Among 20,875 RLN samples screened with brELISA during the field application phase, 155 of 8,877 mule deer, 33 of 11,731 elk, and 9 of267 white-tailed deer samples (197 total) had OD values> 0.1 and were further evaluated by IHC to confirm evidence ofCWD infection. Of cases flagged for IHC follow-up, 143 of 155 mule deer, 29 of33 elk, and all 9 white-tailed deer were confirmed positive. Mean (± SE) OD values for IHC-positive cases detected during the field application phase were comparable to those measured in RLN tissues during the validation phase. Based on these data, brELISA was determined to be an excellent rapid test for screening large numbers of samples in surveys designed to detect CWD infections in deer and elk populations. Pathogenesis in natural host species: Although our study of CWD pathogenesis in white-tailed deer is ongoing, some white-tailed deer inoculated orally with about 2.5 g of brain tissue homogenate (containing about 15 fig PrPCWD) already developed clinical CWD and were euthanized in end-stage disease 16-30 mo postinoculation (PI). The clinical course in inoculated white-tailed deer was similar to that previously observed in mule deer inoculated with about IS fig PrPCWD from infected mule deer. Laboratory evaluations of tissues from both our white-tailed deer and mule deer pathogenesis studies are pending. Evaluation of antemortem diagnostic techniques: Tonsil biopsy is a useful tool for estimating CWD prevalence in nonhunted mule deer populations. In addition to applications in the two field studies described here, the techniques we developed are being used in at least four other field studies of CWD 'epidemiology (y{Y, NM, WI, SD). Thus far, we have been unable to assess the reliability or repeatability of the "GeneThera test". Over 6 mo have passed since blind samples were submitted, but we have been unable to obtain any test results despite repeated attempts to contact the laboratory. Until such evaluations can be completed, we cannot recommend incorporation of this candidate test into any of our ongoing CWD research or management programs. �140 APPENDIX Publications arising from ongoing CWD work: Gould, D. H., J. L. Voss, M. W. Miller, A. M. Bachand, B. A Cummings, and A A Frank. 2003. Survey of cattle in northeast Colorado for evidence of chronic wasting disease: Geographical and high risk targeted sample. Journal of Veterinary Diagnostic Investigation 15: 274-277. Hibler, C. P., K. L. Wilson, T. R Spraker, M. W. Miller, R R Zink, L. L. DeBuse, E. Andersen, D. Schweitzer, J. A Kennedy, L. A Baeten, J. F. Smeltzer, M. D. Salman, and B. E. Powers. 2003. Field validation and assessment of an enzyme-linked immunosorbent assay for detecting chronic wasting disease in mule deer (OdocoiJeus hemionus), white-tailed deer (Odocoileus virginianusi, and Rocky Mountain elk (Cervus elaphus nelsoni). Journal of Veterinary Diagnostic Investigation 15: 311-319. Race, R E., A Raines, T. G. M. Baron, M. W. Miller, A Jenny, and E. S. Williams. 2002. Comparison of abnormal prion protein glycoform patterns from transmissible spongiform encephalopathy agentinfected deer, elk, sheep, and cattle. Journal of Virology 76(23): 12365-12368. Samuel, M. D., D. O. Joly, M. A Wild, S. D. Wright, D. L. Otis, R W. Werge, and M. W. Miller. 2003. Surveillance strategies for detecting chronic wasting disease in free-ranging deer and elk. Results of a CWD surveillance workshop. USGS, BRD, National Wildlife Health Center, Madison, Wisconsin. Sigurdson, C. J., C. Barillas-Mury, M. W. Miller, B. Oesch, L. J. van Keulen, J. P. Langeveld, and E. A Hoover. 2002. PrP(CWD) lymphoid cell targets in early and advanced chronic wasting disease of mule deer. Journal of General Virology 83: 2617-2628. Spraker, T. R, K. I. O'Rourke, A Balachandran, R R Zink, B. A Cummings, M. W. Miller, and B. E. Powers. 2002a. Validation of monoclonal antibody F99/97.6.1 for immunohistochemical staining of brain and tonsil in mule deer (Odocoileus hemionus) with chronic wasting disease. Journal of Veterinary Diagnostic Investigation 14:3-7. Spraker, T. R, R R Zink, B. A Cummings, M. A Wild, M. W. Miller, and K. I. O'Rourke. 2002b. Comparison of histological lesions and immunohistochemical staining of proteinase resistant prion protein in a naturally-occurring spongiform encephalopathy of free-ranging mule deer (Odocoileus hemionus) with those of chronic wasting disease of captive mule deer. Veterinary Pathology 39: 110119. Wild, M. A, T. R Spraker, C. J. Sigurdson, K. I. O'Rourke, and M. W. Miller. 2002. Preclinical diagnosis of chronic wasting disease in captive mule deer (Odocoileus hemionus) and white-tailed deer (Odocoileus virginianus) using tonsillar biopsy. Journal of General Virology 83: 2629-2634. Williams, E. S., and M. W. Miller. 2003. Transmissible spongiform encephalopathies in non-domestic animals: origin, transmission, and risk factors. In Risk analysis ofprion diseases in animals. C. I. Lasmezas and D. B. Adams, (eds.). Revue scientifique et technique Office international des Epizooties 22: 145-156. �141 JOB PROGRESS REPORT Smreof ~C~o~lo~r~a~do~ Work Package No. 3740 Task =2 _ Division of Wildlife - Mammals Research _ Chronic Wasting Disease and Other Wildlife Disease Management. Chronic Wasting Disease Surveillance and Laboratory Support Period Covered: July 1 2002 through June 30,2003 Author: L. A. Baeten Personnel: K. Cramer, K. Green, E. Knox, C. T. Larsen, N. Mier, M. W. Miller, K. Taurman, and L. L. Wolfe Interim Report - Preliminary Results This work continues, and precise analysis of data has yet to be accomplished. Manipulation or interpretation of these data beyond that contained in this report should be labeled as such and is discouraged. ABSTRACT We established and staffed a Wildlife Health Laboratory (WHL) to facilitate expanded needs for chronic wasting disease (CWD) surveillance throughout Colorado. WHL activities supported CWO epidemiology and management work, as well as various new and ongoing CWO research projects. INTRODUCTION We established and staffed a Wildlife Health Laboratory (WHL) to facilitate expanded needs for chronic wasting disease (CWO) surveillance throughout Colorado. WHL activities supported CWD epidemiology and management work, as well as various new and ongoing CWD research projects. Key contributions are described herein. METHODS Smtewide CWD surveillance: The discovery of CWO in northwestern Colorado in January 2002 created a sudden demand for both more widespread surveillance and more rapid turnaround on laboratory results. Consequently, the CDOW's CWO surveillance program was overhauled and its capacity greatly expanded over the summer of 2002 in order to meet anticipated demands for surveillance data, as well as to meet policy-based decisions to provide carcass quality assurance information for individual hunters. The most notable changes were the addition of three regional submission laboratories, streamlining of tissue sampling methods, and incorporation of a rapid screening test for CWD diagnosis. Details of overall programmatic features and changes were described on a new CWD-oriented CDOW web page (http://wildlife.smte.co.us/CWD/index.asp); details of the evaluation of modified sampling and testing procedures are described below. Evaluation of a rapid screening test: In conjunction with expanded CWD surveillance in Colorado during Sep-Dec 2002, tissue samples (n = 25,050 total) from 23,256 mule deer, white-tailed deer, and Rocky Mountain elk collected statewide were examined using an ELISA developed by Bio-Rad Laboratories, �142 Inc. (brELISA) in a two-phase study. In the validation phase of this study, a total of 4, 175 retropharyngeal lymph node (RLN) or obex (OB) tissue samples were examined independently by brELISA and immunohistochemistry (mC). There were 137 mc positive samples and 4,038 mc negative samples. Optical density (00) values from brELISA were classified as "not detected" or "suspect" based on recommended cut-off values during the validation phase. Based on the validation phase data, only RLN samples were collected for the field application phase of this study and only samples with brELISA 00 values> 0.1 were examined by mc. We estimated assay performance parameters (sensitivity, specificity, agreement) for brELISA to determine the utility of this rapid screening assay in CWD surveillance programs. RESULTS AND DISCUSSION Statewide CWD surveillance: The CDOW sampled over 26,000 deer and elk harvested or culled in northeastern Colorado and other select locations. Survey results were posted on the Division's CWD web page. Prevalence data also will be used to augment an existing database that is the foundation for ongoing analyses and modeling of temporal and spatial aspects of CWD epidemiology, as well as for evaluating responses to management. This year's data will be particularly useful in further exploring local patterns of disease prevalence related to deer movement, density, and land use patterns. Moreover, the surveillance strategy and methods first devised and implemented in Colorado recently served as a model for developing national recommendations on CWD surveillance in free-ranging populations. Evaluation of a rapid screening test: In the validation phase, using mC-positive cases as known CWDinfected individuals and assuming mC-negative cases were uninfected, the relative sensitivity of brELISA depending on species ranged from 98.3-100% for RLN samples and 92.1-93.3% for OB samples; the relative specificity ofbrELISA depending on species ranged from 99.9-100% for RLN samples and was 100% for OB samples. Overall agreement between brELISA and mc was 2::97.6% in RLN samples and 2::95.7% in OB samples of all species where values could be calculated; moreover, mean brELISA OD values were 2::46xhigher in IHC-positive samples than in mC-negative sampies. Discrepancies were observed only in early-stage cases ofCWD. Among 20,875 RLN samples screened with brELISA during the field application phase, 155 of 8,877 mule deer, 33 of 11,731 elk, and 9 of 267 white-tailed deer samples (197 total) had OD values> 0.1 and were further evaluated by IHC to confirm evidence of CWD infection. Of cases flagged for mc follow-up, 143 of 155 mule deer, 29 of 33 elk, and all 9 white-tailed deer were confirmed positive. Mean (± SE) OD values for IHC-positive cases detected during the field application phase were comparable to those measured in RLN tissues during the validation phase. Based on these data, brELISA was determined to be an excellent rapid test for screening large numbers of samples in surveys designed to detect CWD infections in deer and elk populati ons. Publications: Hibler, CP, Wilson, KL, Spraker, TR, Miller, MW, Zink, RR, DeBuse, LL, Andersen, E, Shcweitzer, D, Kennedy, JA, Baeten, LA, Smeltzer, JF, Salman, MD, Powers, BE Field Validation and assessment of an enzyme-linked immunosorbent assay for detecting chronic wasting disease in mule deer (Odocoileus hemionus), white-tailed deer (Odocoileus virginianus), and Rocky Mountain elk (Cervus elaphus nelsoni). 2003 J. Vet Diagn Invest 15:311-319. �143 APPENDIX Publications arising from WHL contributions to ongoing CWO work: Hibler, C. P., K. L. Wilson, T. R. Spraker, M. W. Miller, R. R. Zink, L. L. DeBuse, E. Andersen, D. Schweitzer, J. A. Kennedy, L. A. Baeten, J. F. Smeltzer, M. D. Salman, and B. E. Powers. 2003. Field validation and assessment of an enzyme-linked immunosorbent assay for detecting chronic wasting disease in mule deer (Odocoileus hemionus), white-tailed deer (Odocoileus virginianusi, and Rocky Mountain elk (Cervus elaphus nelsoni). Journal of Veterinary Diagnostic Investigation 15: 311-319. Samuel, M. D., D. O. Joly, M. A. Wild, S. D. Wright, D. L. Otis, R. W. Werge, and M. W. Miller. 2003. Surveillance strategies for detecting chronic wasting disease in free-ranging deer and elk. Results of a CWD surveillance workshop. USGS, BRD, National Wildlife Health Center, Madison, Wisconsin. �144 �145 JOB PROGRESS REPORT Smteof ~C~o~lo~r~ad~o~ ~ Division of Wildlife - Mammals Research _ Chronic Wasting Disease and other Willife Disease Management Animal and Pen Support Facilities Work Package No. 8160 3740 Task No. _--=3 Period Covered: January 1,2001 - June 30, 2003. Author: TR. Davis Personnel: 2001: H. Barr, C. Budler, N. Dryer, D. Finley, J. Foster, M. Foster, J. Habel, M. Hanusack, L. Ho, B. Hotchmuth, E. Jones, S. Liss, M. Lowe, M. Miers, A. Mitchell, , T Petersburg, T Terrell, C. Weagley, 2001/2002: B. Bates, D. Biggins, E. Berrill, K. Downing, D. Finely, J. Foster, M. Foster, J. Grigg, J. Habel, M. Hanusack, J. Hatch, C. Hernandez, L. Ho, E. Jones, M. Lowe, A. Mitchell, N. Miers, A. Ray, L. Reimer, R. Rhyan, K. Sparks, T Stout, T Terrell, R. Thompson, M. Thonhoff, C. Weagley, D. Weaver, B. Williams, T Zeaman, 2002/2003: M. Anderson,B. Bates, K. Beamer, L. Dahl, J. Fenwick, D. Fox, K. Fox, J. Habel, J. Hatch, T Halasinski, M. Hanusack, G. Harvey, L. Ho, E. Jones, G. Kyriacou, M. Lowe, N. Miers, A. Mitchell, A. Northrup, R. Rutledge, K. Steffen, T Stout, D. Thompson, R. Thompson, D. Weaver, ABSTRACT The Colorado Division of Wildlife's Foothills Wildlife Research Facility (FWRF) maintained captive animals (2000/2001 annual total: 262, 200112002 annual total: 320, 200212003 annual total: 312) and facilities in support of twenty-one captive wildlife research projects. Chronic wasting disease (CWO) pathology, and etiology, in deer and potential transmission to other species was the primary focus of research during this period, however FWRF supported a number of other significant research projects including contraception and reproductive effects, pathogen immunization, foraging behavior, drug delivery systems, and evaluation of wildlife capture pharmaceuticals. Three new species; fallow deer, domestic ferrets, and mountain lions were added to support CWO research as well as additional numbers of mule deer and white-tailed deer. Chronic wasting disease was again a significant source of mortality in mule deer and white-tailed deer and is reflected by the number of CWO research projects conducted at FWRF during this period. The CWO Management Protocol was updated to incorporate new information and early detection techniques, while maintaining the philosophy of managing the disease for research purposes under heightened bio-safety guidelines and intensive herd management. Additionally, a number of other protocols were revised, and new SOP's developed to accommodate the new species, facility improvements, and expanded research. An expanded database, a 5 year facility capitol construction plan, and a draft facility fee schedule were also implemented. The quality of animal care and facility maintenance provided by temporary, work-study, personal service, intern and volunteer employees is in part reflected by the finding of compliance under the Animal Welfare Act during the annual USDA APHIS inspections of FWRF. In addition to routine maintenance, the FWRF team made significant facility improvements including new facilities to accommodate expanded CWO mule deer research, �146 partial completion of a mountain lion holding facility, and support for construction of the new Wildlife Health Lab now located within the FWRF perimeter. Animal Maintenance: Routine animal husbandry including feeding, health observations, training, weighing, and clean-up, was performed primarily by well trained temporary employees, work-study students, and volunteers. FWRF was inspected by USDA APHIS for compliance with federal animal welfare regulations on March 82001, April 122002, and April 30 2003. Table 1 summarizes the species totals reported to USDA animal welfare and includes all neonates born at the facility, transfers into and out of the facility, and all animals that died or were humanely euthanised during the respective fiscal year. Ungulate herd levels at anyone time averaged approximately 70 percent of the ungulate total and 60-65 percent of the total number of animals housed at the facility. Table 1. Species reported to USDA Animal Welfare Species Bighorn Sheep 2000/2001 Total 57 26 200112002 Total 52 22 2002/2003 Total 28 25 25 25 36 74 126 139 21 20 21 24 40 39 227 285 288 159 200 202 11 11 11 21 21 10 3 3 3 262 320 312 Elk Fallow Deer Mule Deer Pronghorn Antelope White-tailed Deer Ungulate Total Ungulate Mean Cattle Domestic Ferrets Mountain Lions Facility Total Herd Management: Three new species; domestic ferrets, fallow deer, and mountain lions were added to the facility in FY 2000/2001 and mule deer and white-tailed deer herd levels were expanded in FY 01/02, and 02/03 through herd management practices and incoming transfers. Additional adult animals were brought in to support expanding CWD, fertility control, and brucellosis vaccine research and consisted primarily of free �147 ranging and habituated mule deer obtained from various locations around the state. Captive mule deer, white-tailed deer, and pronghorn antelope were also brought in from out of state to supplement FWRF herds. The bighorn sheep herd was reduced in FY 200112002 and FY 200212003 through natural mortality and an out-going transfer of excess animals. The Fallow deer herd was allowed to expand naturally as per the study protocol in FY 2001/2002, while the cattle elk, and pronghorn herd levels remained relatively constant for the period. Commission approval was granted in 2001 to transfer excess FWRF captive wildlife, and/or orphaned neonates out of state to support collaborative and non-agency wildlife research projects. In 2001 the excess bighorn sheep were transferred to a research facility in Idaho, and in 2001, 2002, and 2003 orphaned mule deer neonates were transferred to a captive facility in Wyoming. It is important to note that the 2002 and 2003 out of state transfers were not of FWRF origin, but habituated orphaned fawns not suitable for release. Other facility transfers include several excess bighorn weanlings that went to a zoo for display, several pronghorn bucks that were borrowed from (and returned to), another captive wildlife research facility, and several free ranging bull elk brought in for breeding purposes. Breeding was planned annually to maintain optimal population sizes of the various species required to support current and future research projects. Depending on research objectives, some of the offspring from FWRF animals were hand-raised, and various species of wild orphaned neonates were accepted for hand rearing. Habituated weanlings and adult animals were also accepted whenever herd levels would allow. Hand rearing protocols for mule deer are described by Parker and Wong (1987), and by Wild and Miller (1991) for bighorn sheep, elk, pronghorn antelope, and white-tailed deer. The male cattle, domestic ferrets and mountain lions were castrated at an early age, and the male fallow deer were vasectomized in the summer of 02/03 to prevent further breeding. Table 3 summarizes the breeding and rearing practices of ungulate species for the period: �148 Table 3 Ungulate breeding and rearing practices Species FWRF Breeding 2000/2001 2000 Bighorn Sheep Bred Elk Bred 5 Cows Fallow Deer Yearlings, did not breed Bred Mule Deer Pronghorn Antelope Bred White-tailed Deer Bred 3 yearlings 200112002 Bighorn sheep FWRF Breeding 2001 Bred Elk Did not breed Fallow Deer Mule Deer Bred Bred Pronghorn Antelope White-tailed Deer Bred 2002/2003 Bighorn Sheep Pronghorn Antelope White-tailed Deer Orphans 2001 0 Hand raised 2, dam raised 2, 1 stillborn No offspring 1 weanling Hand raised 4, dam raised others Hand raised 4 , 2 still born, others Euthanized as per study protocol Dam raised 0 0 0 13 orphans FWRF Neonate Rearin_g 2002 Hand raised 5, dam raised others No offspring Orphans 0 3 orphans, 9 weanlings 1 weanling Bred Dam raised Hand raised 20, dam raised others Euthanized as per study protocol Dam raised FWRF Breeding 2002 Not bred FWRF Neonate Rearing 2003 No offspring Bred 3 cows 0 Not bred 1 hand raised, 2 dam raised No offspring Bred Dam raised 5 weanlings, Bred Hand raised 1 orphan Bred Dam raised 0 Elk Fallow Deer Mule Deer FWRF Neonate Rearing 2001 Dam raised 2002 1 orphan 1 weanling 11 orphans, 2 weanlings Orphans 2003 0 0 �149 Nutritional Maintenance: Feeding protocols for ungulates previously housed at the facility were reviewed by Wild (1997). The fallow deer were maintained on a high quality grass alfalfa mix hay and Regular Ranch-way deer and elk ration. The domestic ferrets were maintained on a commercial ferret chow, and the mountain lion kittens were initially maintained on Kitten Milk Replacer, Nurtural, and commercial kitten chow. The kittens were switched to a ground commercial feline diet at weaning, and were introduced to chunk deer and elk meat for training purposes at four months of age. A commercial carnivore supplement was added to the training meat to enhance dietary levels of calcium, and vitamins A and E, and was offered several times weekly. At five months of age, the kittens were gradually introduced to whole deer and elk carcasses and carcass portions with the GI tract removed, and are currently maintained on carcass portions, and training meat with supplement. Individuals of all species maintained reasonable body condition on available diets with the exception of some mule deer fawns, and CWD infected animals at the clinical stage of the disease. Fawn mortalities may have been associated with general poor body condition of does infected with chronic wasting disease, the presence of other etiological agents, and/or interspecies competition for space and cover in paddocks housing cattle and fallow deer. Pen Enrichment In an effort to provide cover and subsequently reduce stress, the mule deer in the cattle pens were provided with a refuge area not accessible to the cattle, and artificial refuge areas were constructed in all paddocks housing semi-wild deer and dam raised neonates. Single piece and "L" shaped hide-outs, were constructed on site, and vegetation ex-closures were added in early spring and removed later to provide seasonal natural cover. Additionally, the Fort Collins Water Treatment Plant donated rock, labor and the use of equipment to construct two rock mountains in the bighorn sheep pens to enhance the natural structure in these areas. In addition to pen structure, behavioral enrichment was offered through training. The mountain lions were trained using operant conditioning; a form of training based on a reward system, and used widely in wildlife display facilities. Using this system, the lion kittens were taught to sit, platform, kennel, and stretch up on the fence for physical exams. Hand raised ungulate neonates were treat trained using the same philosophy, and were taught to follow their human trainers and stand on the scale for physical exams and weighing. Passive training was also used to habituate animals to the scale and alley-way by feeding the animals supplement in these areas, and allowing free exploration without human interference. Health Maintenance: Animal health care was provided as required and as mandated by the preventive medicine program (Wild 1995) and chronic wasting disease protocols. Overall, captive wildlife maintained at FWRF remained healthy throughout the period. Chronic wasting disease (CWD) continues to be a significant source of mortality in captive mule deer and white-tailed deer and is reflected by the number of animals dedicated to CWD research.projects throughout this period. Dystocia was a significant source of mortality in adult pronghorn does, and was associated with a failure of the cervix to dilate at the time of parturition. The underlying cause of the pronghorn dystocia is still unknown, and the collaborative USDA RB51 brucellosis vaccine project was put on hold in FY 2002/2003 due to the resulting reduced number of adult females available. Other significant etiological agents included Epizootic hemorrhagic disease (EHD), bluetongue virus (BTy), and clostridium perfringens. �150 Standard Operating Procedures: Chronic wasting disease The CWD management protocol was again revised in FY 2002/2003 (Attachment 1). Generally, CWO continues to be managed as described by Wild (1997): to maintain CWO and maximize potential exposure for specific research objectives. The revised protocol was prepared to incorporate new information resulting from recent research findings: increasing bio-security, incorporating early detection techniques, and intensive herd management ofCWD infected animals (Wild et. a12002, Wolfe et. al 2002). All animals at FWRF were monitored closely for clinical signs of CWO, and tissues from all mortalities occurring at FWRF were examined for evidence of infection with CWO. Systems development In addition to the CWO protocol, all animal husbandry, facility security, FWRF management protocols, and veterinary supply inventories were reviewed and updated. Protocols were developed to manage the new species, and an Access database was developed to track additional information such as projects and veterinary treatments. The old paradox database and hard copies of vital records, necropsy, clinical pathology, and transfer information was integrated into the new database. Facility and animal maintenance costs were analyzed and incorporated into a draft fee schedule for use of research animals and FWRF facilities by professional collaborators, and a draft 5 year facility capitol construction plan was developed to address long term planning needs. Educational Contributions FWRF functions primarily to support wildlife research, however when possible and relevant, facility tours were provided to school, university, and professional groups. We emphasized the importance of maintaining captive wildlife to perform controlled experiments, and the contributions made by current and historic research projects conducted at FWRF. FWRF animals and facilities were also used occasionally for hands-on training of COOW employees, collaborators, and other professional groups in sampling techniques and chemical immobilization. Research Projects: Facility operations offered support for research projects conducted by COOW personnel and other collaborators that were initiated, conducted, or continued using FWRF animals and facilities. A total of twenty one research projects were supported by FWRF for the period: • • • • • • • • • • • Cattle susceptibility to chronic wasting disease. Mechanisms ofCWD transmission in mule deer. Evaluation of prospective preventative therapies for chronic wasting disease in mule deer. Validation of a potential blood test for chronic wasting disease (Gene'Ihera test). Prion peptide immunization and challenge. Molecular epidemiology of strain variations in chronic wasting disease. Susceptibility of Mountain Lions to chronic wasting disease. Susceptibility offallow deer to chronic wasting disease. Pathogenesis of chronic wasting disease in white-tailed deer. Effects ofGnRH-PAP on reproduction and behavior infemale mule deer. Evaluation ofGnRH agonist (leuprolide) as a reversible contraceptive in mule deer. �151 • • • • • • • • • • Evaluation ofGnRH agonist (Lupron) as a potential contraceptive in rocky mountain elk: Effects on pregnancy. Development of a remote delivery system for GnRH agonist (leuprolide) in female elk. Paradoxical immunosuppression in bighorn lambs as a mechanism for depressed recruitment following pastuerellosis epidemics. Biosafety and reproductive effects of RE51 (brucellosis) vaccine in pronghorn. Evaluation of drug delivery and dart trauma using collared and un-collared pneudart and daninject darts. Evaluation of A3080 (thiafentanil oxalate) and naltrexone HCLfor the immobilization and reversal of mule deer. Evaluation of A3080 (thiafentanil oxalate) and naltrexone HCLfor the immobilization and reversal of pronghorn antelope. Effects of 2% DRC-1339 treated brown rice on non-target species. Testing alternative models of herbivore foraging in heterogeneous environments. Field Immobilization Training. Facility Improvement Projects: A variety of scheduled and unscheduled maintenance and repair activities were necessary to support facility operation and ongoing research programs. Highlights include construction of the new Wildlife Health Lab (WlIl.) housing a laboratory, office space, a necropsy lab, and walk in freezer/cooler space, now located within the FWRF perimeter. This project was designed, constructed, and funded by the CDOW engineering and capitol construction team, while FWRF personnel provided support services. Additional facility modifications include twelve new paddocks, associated buildings, alleys and an access road to support the CWD transmission study, and an automatic water system for all paddocks on the east side of the facility. Other improvements included five new isolation pens, perimeter fence and gate upgrades, and construction of compost bins to hold animal waste material generated from CWD research paddocks. A new mountain lion facility including a concrete block building containing 4 indoor dens and a work space, a 50 x 60 foot outdoor pen, and shift containment system is currently under construction. A 2000 gallon vault was installed on the east side, a new pasture was also constructed on the west side, and the old house trailer was demolished. Additionally, the Soldier Canyon Filter Plant donated several culverts and constructed a detention pond on the west side of the facility to better manage natural water run-off and scheduled water releases from the plant. Facility maintenance and construction projects were prioritized based on animal welfare concerns and anticipated research needs. Table 3 summarizes the completed, current, and on-going facility construction maintenance projects for the period. �152 Table 3. Facility Improvement Projects Project Status Details and Information Replace roofs on existing pens, and add 5 additional pens with shelters Remove garage door, replace with permanent vvall, add window Automatic vvaters installed in all existing pens and nevv paddocks for transmission study. CSU provided the electric contractor, FWRF contracted out plumbing Purchase Tough Sheds, level sites, pour concrete pads for Transmission study, purchased 1 shed, other was supplied by WHL Construct 9 new pens, and split 2 pens into 4 for Transmission study, CSU provided contractor for installation Construct Feed-sheds for north and south transmission study pens Completion Year 1. Improvements to vvestrearing area 2. East lab improvements 3. Add 13 automatic vvaters, 4 shut off valves to east side Completed 4. Add pellet feed storage shed, and feed-shed to east side 5. Construct 12 new pens on east side Completed Construct feed shelters for transmission study pens Construct 400 feet of alley, 16 walkthru gates for transmission study 200112002 Completed Construct road, culvert donated by Fort Collins Water Treatment Plant 200112002 Completed Purchased all gates < 14 foot long, 14'gates donated by CDOW game damage, installed gates, added horse fence, add gate opening in D3 contracted out electric fence modifications Construction of D 1 pasture contracted out by NWRC 200112002 Install automatic vvater in D 1, and a vvater shut off valve in the west hub, contracted out plumbing and excavation Construct 1 feed shelter, and 1 200112002 Completed Completed Completed 6. Construct 2 additional feed storage sheds on east side 7. Construct 13 feed shelters on east side 8.Construct alley system and gates for new pens on east side 9. Construct access road to new alley system on east side 10. Replace all vvooden drive through gates with 7 foot metal tubing gates, add gate to south side of D3 11. Construct new pasture on west side (Dl) 12. Plumbing upgrades to west hub area Completed 13. Construct 2 Completed Completed Completed Completed Completed 200112002 200112002 200112002 200112002 200112002 200112002 200112002 200112002 200112002 �153 shelters in 01 14.East fawn rearing area improvements 15. House trailer demolition, and FWRF site clean-up 16. Construct ram pen exclosure around feed area in E3 17. Reconstruct shed on west side of west scale-room, modify scale 18. Water damage repair to ElfE2 feedshed 19. Perimeter Fence upgrades Completed Completed Completed 2002/2003 200212003 Completed Remove soil on west side, reconstruct wall, re-grade soil 200212003 Completed Replace rotten posts, add V-rnesh to lower 4 feet of perimeter fence, contracted out labor on V-mesh Replace 4 old drive thru gates with 8 foot chain link gates 2002/2003 Close off FWRF access road between the Ft. Collins Water Treatment Plant and Soldier Canyon Filter Plant, contracted out time and materials Construct compost bins, purchase bacteria, train personnel to mix and monitor, Contracted out initial bin construction, and start-up Replaced rusted metal 1000 gallon tank with a 2000 gallon concrete vault, Contracted out time and materials Rocks, equipt, and time to construct the mountains donated by the Ft. Collins Water Treatment Plant Construct pond to maintain drainage water inside our perimeter fence, time and equipt. to construct pond was donated by the Soldier Canyon Filter Plant Utilities, concrete block building, 50 x 60 foot outdoor pen, shift containment system, and 4 indoor dens, building slab, and alley concrete, concrete block building, 2002/2003 22. Compost animal waste from CWO paddocks Initial start-up is completed, composting is ongomg Completed 26. Construct mountain lion holding facility 200112002 Reconstruct shed, modify scale to accommodate access from west side Completed 24. Rock mountains constructed in upper sheep pens 25. Construct west detention pond 200112002 Completed 20. Upgrade 2 perimeter and main east and west gates 21. Add Secondary perimeter gate and 8 foot fence on south side of facility 23. Replace east side septic tank animal shelter Reconstruct roof structures, repair shelters, double fencing on N. side, add 1 alley gate Demo old trailer, clean up, organize FWRF construction materials and supplies, remove waste Purchased range panels, installed panels, added horse fence Completed Completed Completed Current project: planning, utilities, and building construction completed. finish: 2002/2003 200212003 200212003 2002/2003 2002/2003 Project began 200112002, scheduled for completion 2004/2005 I �154 outdoor pen, shift containment, indoor dens Current project: 5 completed, finish: 7 plumbing, electrical, and engineering contracted out 28. New roofs/repair structure on old feed-sheds and animal shelters. On-going project 29. Add additional animal shelters On-going project 30. Road Maintenance 31. Paint old building exteriors On-going project Approx. ~ of the old structures and roofs on the facility have been replaced in the last 2 years using treated lumber and long lasting roofing materials Construct additional shelters in pens with heavy stocking rates. (36 ungulate pens on the facility) Road grading and upkeep 32. Repair/replace latches, and broken or water damaged alley-way boards 33. Replace walk thru alley gates 34. Replace old visual barrier fencing and utility wire on metal gates On-going project 27. Reconstruct west isolation pens 35. Animal holding fence upgrades, and repairs 36. Construct artificial refuge areas inside pens for neonates and adults On-going project Demolish old pens and shelters, reconstruct with upgraded design and materials Now using CCA treated lumber, or metal siding for repairs & building replacements to reduce the amount of painting necessary in the future. Now using CCA treated lumber for all repairs Project began 200112002, scheduled for completion 2004/2005 Began 2000/2001, as needed Began 200112002, as needed As needed Old structures are on a painting schedule every 3-5 years As needed On-going project Replace old gates as necessary On-going project: most of the old material has been replaced, but this project is on-going due to animal and environmental damage On-going project: rotten posts have been replaced all over the facility, and many double fences have been constructed to comply with CWD protocols On-going project: completed for all new east side paddocks, maintain existing, construct Old snow fence and construction fence replaced and moved to the outside of the paddock fence (except interior fences), utility wire is systematically being replaced with horse-fence Began 200112002, as needed Replace old range fence and Vmesh, as well as electric fencing in pens that house deer, Construct double fences as required by CWD protocols Began 2002/2003, as needed Construct single and L-shaped, refuge areas to provide refuge and shade, construct hog panel seasonal exclosures to promote vegetation growth in the spring Began 2002/2003, as needed As needed �155 37. Add windscreen to west and south facing fence-lines 38. Mowing and weed control 39.WHL maintenance 40. Unscheduled miscellaneous emergency facility repairs new On-going project On-going project On-going project On-going project Provide additional shaded areas for animals, and maintain existing Began 2002/2003, as needed Seasonal mowing and manual, chemical noxious weed control Provide maintenance assistance to WHL, and support for initial lab construction Emergency repairs to structures, animal holding facilities, perimeter fence, automatic waters, utilities, etc ... As needed Began 200212003, as needed As Needed �156 Addendum 1. PROTOCOL FOR MANAGING CHRONIC WASTING DISEASE AT FOOTHILLS WILDLIFE RESEARCH FACILITY Draft Rev. 2003 HISTORY Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy (TSE) or prion disease of cervids (deer and elk). Other TSE's include scrapie of sheep, bovine spongiform encephalopathy (BSE), and Crutzfeld-Jacob disease of humans. The disease causes behavioral changes and loss of body condition and is invariably fatal to infected deer and elk. Despite a comprehensive program initiated in 1985 to eradicate CWD from cervids and the environment at Foothills Wildlife Research Facility (FWRF), CWD remains endemic at the facility. After the 1985 clean-up, CWD was first diagnosed in elk in 1989 and in mule deer in 1994. Natural transmission is now common in mule deer at FWRF and sporadic cases continue to occur in elk. Additionally, natural transmission rates are markedly higher and self-sustaining in paddocks housing infected animals being used in ongoing CWD research studies compared to paddock areas housing animals for other research studies. Based on these observations, guidelines established in 1985 (and revised in 1993 and again in 1997) for maintaining a CWD-free facility are largely obsolete. Here, we provide additional revisions to those guidelines that are directed at maintaining the disease for research purposes in captive deer and elk while minimizing the risk to personnel and the potential spread of CWD outside the facility. OBJECTIVES 1. 2. 3. 4. 5. 6. Prevent transmission or exposure of CWD from FWRF to animals or facilities outside FWRF. Minimize potential for exposing FWRF personnel and visitors to pathogens or potential pathogens including CWD. Maintain endemic CWD in deer at FWRF; however, animals showing end stage clinical signs of CWD will be euthanized to avoid undue suffering, unless directed otherwise by research protocol. Minimize potential spread of CWD among species of captive wildlife (deer, elk and noncervid research animals). Minimize cross contamination between CWD infected and non-targeted research animals. Prevent cross contamination between CWO research treatment groups. ASSUMPTIONS 1. 2. 3. 4. CWO is an infectious disease of deer and elk caused by an abnormally shaped protein prion. CWO is not widespread in free-ranging cervids. Where it occurs, the prevalence of disease varies greatly. Mode of transmission for CWD is not known, and may be direct, via animal/animal contact, or indirect, through contact with excreta (saliva, urine, feces); animate and inanimate objects may serve as fomites (vehicles) in transmitting CWO. Non-cervid wildlife and domestic species are not naturally susceptible to CWD. It is possible that non-cervids could be inapparent carriers of CWD; however, no data have been produced to support this possiblity. Based on patterns seen in other TSE's, it seems likely that ifCWD is transmitted to a new host species, then the likelihood of further transmission to others within that species is increased. �157 5. There is no evidence that CWD is transmissible to humans; however, it is prudent to minimize human exposure to CWD as well as animal pathogens known to be transmissible to humans (e.g, Salmonella spp., E Coli, etc.), APPROACH Overview: 1. Follow established guidelines that prevent contact of captive research animals with animals outside FWRF (wild and domestic). 2. Minimize potential spread of infectious material outside FWRF perimeter. 3. Minimize potential transmission of CWO between species of captive animals, between CWO and non-CWD research animals, between research projects, and between experimental treatment groups where necessary. This includes transmission from mule deer/cattle pens, mule deer/fallow deer pens, therapy mule deer pens, white-tailed deer, and mountain lion pens via contaminated materials or potentially contaminated, equipment, or clothing. 4. Maintain each species of animal in isolation from others, unless directed by research protocol (e.g., mule deer with cattle, mule deer with fallow deer). 5. Educate animal caretakers about CWD (hazards, protocols, and clinical signs exhibited by affected animals). Perform daily animal observations and maintain detailed records of animal health as a portion of the FWRF CWO surveillance program. Animals: 1. 2. 3. 4. 5. Exclude wild or captive cervids from CWD established areas from entering the captive herd, unless directed by a research protocol. Established areas will now include: northeastern, northcentral, and northwestern Colorado, Park, Albany, and surrounding counties in Wyoming, and the Denver Zoo. However established areas are dynamic and may change as surveillance for CWD increases. Therefore, please consult the latest CWD update for guidance. Depending on intended use, orphans, and neonates raised outside FWRF, may be accepted from areas that are CWD established, as well as areas that are not CWD established. These animals will be maintained separately to minimize potential CWD transmission to uninfected neonates that come from sources outside the established area. Raise and maintain each animal species in isolation from others, unless directed by a research protocol. To prevent transmission of CWD from FWRF to facilities where CWD is not established, noncervid species from FWRF will be transferred or donated to other facilities only if the following criteria are met: 1) the transfer location is within the CWD established area, 2) animals are scheduled for a specific research project, 3) the destination is a closed facility (no egress oflive animals), 4) animals will not be used in "tame animal trials" in non-confined environments. 5) transfer is approved by the mammal's research leader, 6) recipients will be notified of CWD risks associated with accepting animals from FWRF. Transfers of live cervids from FWRF are prohibited. Animal Maintenance: 1: House and maintain each species in isolation from other species, unless directed by a research protocol. 2. House and maintain CWD research animals separate from non-CWD research animals. 3. Maintain accurate records for all animals. This information includes (but is not limited to): birth date, origin, body weights on tractable animals, vaccinations, health problems and treatments, research projects, and movements (intra and inter facility). Additionally, a. Tag all animals for easy individual identification. �158 b. 4. 5. 6. Train FWRF personnel to recognize clinical signs ofCWD. FWRF personnel will maintain daily animal observation records describing animal status and will report abnormal observations to the facility manager. Where feasible, weigh and/or briefly examine every animal at least once monthly. Wild research animals usually cannot be handled for weighing; these will be visually examined and immobilized via a dart injection for closer examination if necessary. Follow a preventative medicine program that includes routine vaccination, anthelmintic treatment, hoof trimming; nutritional evaluation, and other measures to optimize overall health of research animals. Initiate early detection measures by conducting annual tonsil biopsies on all deer (WTO, MO) housed within the facility. CWO positive animals will be removed at the discretion of the lead project researcher from non-CWD research paddocks and 1) added to the CWD research herd, 2) held in isolation, or 3)humanely euthanized. Use of Research Animals Outside FWRF: 1. The transport of non-cervid species from FWRF to facilities or locations, outside the CWO established area is prohibited. 2. The transport of non-cervid species to facilities or locations outside FWRF but within areas where CWD occurs is prohibited unless expressly approved by the mammal's research leader. 3. The transport of cervids outside FWRF is prohibited. 4. Procedures for isolating cervids at other COOW facilities will be the same as those at FWRF. 5. Animals of any species maintained at FWRF will not be released into the wild. 6. The FWRF Manager is responsible for maintaining accurate records of animals transferred into and out of FWRF. General Facilities and Equipment: 1. Exclude free-ranging wildlife and livestock from the facility or from contact with captive animals using interior and perimeter fencing. A minimum 4 foot corridor must be maintained between interior pasture fencing and the 8 foot tall perimeter fence surrounding FWRF. The perimeter gates will remain closed at all times, the perimeter fence is inspected monthly, and necessary repairs are made top priority for facility maintenance. 2. Maintain each species of animal separately and allow no direct or fence-line contact unless directed by a research protocol. 3. Minimize runoff between pens housing different species through appropriate pen assignment and drainage control, unless directed by a research protocol. 4. Use drainage control to minimize runoff outside the facility in areas where natural and/or man made drainages occur inside CWO paddocks. 5. Minimize common use of equipment between pens housing different species, between CWO and non-CWD paddock areas, and between CWO treatment groups. When it is necessary to use the same equipment (vehicles) a 20 % chlorine, or 5 % LPH solution can be used to disinfect equipment immediately following the use of equipment inside CWD infected paddock areas. 6. All equipment, materials, organic, inorganic, materials that have been exposed to CWO pathogens must either remain on site or follow EPA treatment guidelines prior to leaving FWRF. 7. Feed and handle animals or clean pens using the following traffic pattern: Clean CWO controls (MD,WTO), non-cervids, elk, non-CWO research mule deer, CWD research mule deer, CWD infected white-tailed deer, mule deer with cattle/fallow deer. Additionally, follow specific protocols for traffic patterns between various CWO research treatment groups. 8. Clean animal pens (especially feed areas and waters) weekly. Dispose of waste from pens housing non-CWD research animals, and clean controls in the main dumpster. Waste from all �159 CWD infected paddocks must never leave the facility. Fecal material and non-palatable feed from CWD research paddocks will be reduced through on-site composting and palatable feed will be recycled to the cattle. 10. Isolation pens, digestion cages, and other areas where animals are held for extended periods, will be cleaned of organic matter and disinfected with a 20% chlorine solution, or 5% LPH solution after use. The researcher last using the area will be responsible for cleanup. Cooperative compliance will be made a condition of all study plans using FWRF ungulates and facilities. 11. Different species may be held concurrently in isolation pens if a buffer zone (empty pen) is used. 9. Feed: 1. Hay will not be accepted from areas where domestic sheep have grazed on cultivated pastures. Personnel: 1. Wash hands before and after handling each species of animal, before and after handling nonCWD and CWD research animals. 2. No eating or drinking allowed in animal areas. 3. Dedicate one pair of shoeslboots to FWRF. Change into/out of this pair of shoes when you arrive at work/when you leave. Alternately, shoes can be sprayed liberally, and/or washed thoroughly in 20% chlorine or 5% LPH solution. 4. Coveralls, boots, and gloves, are required when handling animals showing clinical signs of CWD; and face masks and eye protection are available for use if desired. 5. Coveralls and/or boots are a protocol requirement for CWD infected areas, and CWD control groups. Additionally, each set of treatment groups within a research project may require a separate set of boots and/or coveralls depending on research objectives. Please do not enter a paddock unless you know the protocol. 6. Unsupervised access to FWRF will be limited to authorized personnel. Unauthorized persons will not enter animal pens or be permitted direct contact with research animals. The facility will be locked except when attended during normal business hours. 7. Visitors will be informed that FWRF houses CWD infected animals and is within the CWD established area, and will be given the option of wearing rubber overshoes which will remain on site. 8. All researchers and collaborators and their subordinates will comply with this protocol. All personnel working at FWRF will be required to read this protocol and other appropriate literature and to sign the attached sheet of informed consent. Additional Requirements for CWD research Pens: 1. Protective clothing such as designated boots/shoe covers and/or coveralls and must be worn when entering all pens housing CWD infected animals (currently these are: mule deer/cattle pens, mule deer/fallow deer pens, mule deer therapy pens, infected WTD pens, and mountain lion pens), as well as all CWD control pens. 2. Place waste feed and manure from infected mule deer and white tailed deer pens in the storage compost pile at FWRF (NOT in the dumpster, or working compost piles). Compost will be mixed appropriately and put into composting bins by assigned personnel. Finished compost will be incinerated, or used for topsoil in CWD infected paddocks as needed. 3. Waste feed from the mountain lion pens is disposed of through incineration or sent to CSU for chemical digestion. Fecal material from the lion pens is composted along with other CWD pen waste material. 4. Dedicated (separate) equipment (wheelbarrows, rakes, shovels, water brushes, bucket scrapers, etc.) must be used for cleaning CWD infected vs. CWD control and non-CWD research �160 paddocks. Additionally, separate cleaning equipment may be required for each treatment group within specific research projects. Please ask the facility manager if you are not sure of the cleaning protocol. 5. Vehicles must be cleaned after use in all CWD paddocks. Wash organic material from tires, remove all organic material from the truck bed and disinfect with a 20 % chlorine, or 5% LPH solution. 6. Clean-up procedures following depopulation of a CWD infected paddock: disinfect feed bunks and feed pans in 5% LPH solution and rinse thoroughly, disinfect water receptacle with a 20% bleach solution and rinse thoroughly, rake out all fecal material, spray feed shelter and soil under and around shelter with a 50% bleach solution. Allow all to dry thoroughly before repopulation of paddock. Additional clean-up procedures may be required such as removing the top 6 inches soil around a feed area, soaking with bleach solution, and adding road-base. This will depend on the specific research project. 7. Keep gates to pens, hub/working area, and main east and west gates closed at all times except when passing through. 8. Animal carcasses must be enclosed with a protective cover to contain potentially infectious materials during transportation to the Wildlife Health Lab (WHL) on site, or off site to the CSU Vet Teaching Hospital (VTH) or the Wyoming State Veterinary Lab (WSVL). Alternatively, the truck/equipment could be cleaned with a 20% chlorine solution after use if transported to the necropsy lab on site. 9. Cattle will not leave the facility alive unless transferred to a biosecurity level 2 or greater facility and this requirement is part of a written change to the established research protocol. 10. Report any abnormalities or accidents immediately to facility supervisor. CWO SURVEILLANCE 1. 2. 3. 4. 5. PROGRAM Euthanize any animal showing clinical signs of CWD and examine tissues grossly and histologically. Perform complete postmortem examination and histologically examine brain tissue of any animal that dies at FWRF. Carcass disposition will be by incineration (required for cattle), chemical digestion, or appropriate burial at the Larimer County Landfill. IfCWD is diagnosed in any noncervid species at FWRF, this protocol will be immediately revised and biosecurity at FWRF further increased. The attending veterinarian, facility manager, and Research Facility Animal Care Committee (RFAC) will evaluate and amend this program as necessary. The FWRF CWD PROTOCOL WAS FIRST ESTABLISHED IN 1985 AND REVISED: 1993 1997 2003 INFORMED CONSENT I, have read the Foothills Wildlife Research Facility (FWRF) protocol concerning chronic wasting disease (CWD) and agree to follow the protocol. Although there is no evidence that CWD is transmissible to humans, I realize that I will be working with research animals and in an environment potentially infected with CWD. I understand that this protocol reflects current knowledge on measures for minimizing exposure to and spread of CWD and other potential pathogens at FWRF. Signature Date �161 LITERATURE CITED Parker, K. L., and B. Wong. 65:20-23. 1987. Raising black-tailed deer fawns at natural growth rates. Can. J. Zoo 1. Wild, M. A., and M. W. Miller 1991. Bottle raising wild ruminants in captivity. Colorado Div. Wildl. Outdoor Facts No. 114. Wild, M. A. 1995. Animal and pen support facilities for mammals research. Colorado Div. Wildl. Res. Rep., WPla, J'I, Jul1994 - Jun 1995, Fort Collins. Wild, M. A. 1997. Animal and pen support facilities for mammals research. Colorado Div. Wildl. Res. Rep., WPla, Jl, Jul 1996 - Jun 1997, Fort Collins. Wild, M. A., T. R. Spraker, C. 1. Sigurdson, K. I. O'Rourke, and M. W. Miller. 2002. Preclinical diagnosis of chronic wasting disease in captive mule deer (Odocoileus hemionus) and white-tailed deer (Odocoileus virgineanus) using tonsillar biopsy. 1. General Virol. 83:2629-2634. Wolfe, L. L., M. M. Conner, T. H. Baker, V. J. Dreitz, K. P. Burnham, E. S. Williams, N. T. Hobbs, and M. W. Miller. 2002. Evaluation of antemortem sampling to estimate chronic wasting disease prevalence in free-ranging mule deer. J. Wildl. Manage. 66:564-573 �162 �163 JOB PROGRESS REPORT Sffireof ~C~o~lo~r~a~do~ _ Division of Wildlife - Mammals Research Work Package No. _ Multispecies Investigations Task No. _ Prairie Dog Research and Wildlife Extension Period Covered: July 1,2002 - June 30, 2003 Author: W. F. Andelt, Colorado State University, Dept. Fishery and Wildlife Biology Personnel: M. Christopher, J. Dennis, L. Gepfert, E. Hollowed, BLM, S. M. Quinlivan, P. M. Schnurr, A. Seglund, Utah Division of Wildlife Resources, G. C. White, D. Younkin PRAIRIE DOG AND PREDATOR-GROUSE RESEARCH, AND WILDLIFE EXTENSION W. F. Andelt OBJECTIVES 1. Objectively assess and document the current scientific knowledge base about Gunnison's prairie dogs by 1 September 2002 via a technical review draft publication, submitted to the CDOW research peer review process. 2. Conduct on-the-ground surveys, and collect measurements of key elements of Gunnison's prairie dog colonies at 50 sites in western Colorado by September 30,2002, and provide a report, including data summaries, by October 30, 2002, to CDOW's project leader. By October 30, 2002, provide a data set that can be used by other investigators to develop a defensible, quantified Gunnison's prairie dog inventory technique. 3. Provide information specifically directed toward chronic wasting disease from DOW/DNR to the public through CSU's Extension network of 57 county Extension offices and provide intensive training to at least 4 offices and 100 employees/volunteers in key western slope counties by April 30,2003. 4. Provide general wildlife information and information regarding human-wildlife conflicts from DOW/DNR to the public through the CSU's Extension network of 57 county Extension offices and provide intensive training to at least 4 offices and 100 employees/volunteers by April 30, 2003. 5. Provide analyses of data on the possible role of predators in the sage grouse decline in northwest Colorado. �164 STATUS OF GUNNISON'S PRAIRIE DOGS IN COLORADO W. F. Andelt The Gunnison's prairie dog (Cynomys gunnisoni) occurs in Colorado, Arizona, New Mexico, and Utah. Their geographical range probably has not changed much during the past century (Knowles 2002). However, acreage of Gunnison's prairie dogs within their range likely has contracted during the past century. The extent of decline is unknown because there were no accurate accounts of the abundance of prairie dogs prior to settlement (Clark 1973, Anderson et al. 1986, Knowles 2002), and the abundance of Gunnison's prairie dogs today also is not well known. Approximately 22% of the range of Gunnison's prairie dog occurs in Colorado (Knowles 2002), where it is distributed primarily across the southwestern quarter of the state at elevations of 6,000 to 12,000 feet (Fitzgerald et al. 1994). The Gunnison's prairie dog consists of 2 subspecies (C g. gunnisoni and C g. zuniensisi. In Colorado C g. gunnisoni occurs in the Gunnison River drainage, the upper Arkansas and South Platte drainages, and in the San Luis Valley (Fitzgerald et al. 1994). In Colorado, C g. zuniensis occurs at lower elevations in Montezuma, La Plata, Dolores, San Miguel, and Montrose counties (Fitzgerald et al. 1994). Densities of Gunnison's prairie dogs range from 5 to 10 per acre (Knowles 2002). The primary threat to Gunnison's prairie dogs is plague tYersinia pestis), whereas poisoning, recreational shooting, agricultural land conversion, and urbanization are of secondary importance (Knowles 2002). Plague became apparent in Gunnison's prairie dog colonies during the late 1940s (Lechleitner et al. 1968, Cully 1993). Plague often kills >99% of Gunnison's prairie dogs (Lechleitner et al. 1968). South Park, Colorado apparently contained 913,000 acres of Gunnison's prairie dogs in 1941, but an epizootic of sylvatic plague entered this area in 1947, and by 1949 plague reduced the acreage of prairie dogs by 95% (Ecke and Johnson 1952, Fitzgerald 1969, Armstrong 1972). Plague has continued in this area during the 1950s and 1960s (Lechleitner et al. 1962, Fitzgerald and Lechleitner 1974). During the first half of the 20th century, Gunnison's prairie dogs were mostly eliminated from the major valleys in Colorado (Burnett and McCampbell 1926, Longhurst 1944) due to plague or poisoning (Knowles 2002). Recently, most wildlife biologists interviewed by Knowles (2002) felt that plague was the dominant controlling factor of prairie dogs. Recover of Gunnison's prairie dogs from plague appears to range from no recovery to a pattern where colonies are regularly lost, but new colonies appear and grow in other areas (Knowles 2002). Gunnison's prairie dogs were subject to poisoning in the higher valleys of Colorado during the 1950s (Lechleitner et al. 1968). Control of Gunnison's prairie dog continues on private land, but control of prairie dogs on Federal lands currently does not appear to be a conservation issue (Knowles 2002). The current abundance of Gunnison's prairie dog in Colorado is not well known. Some biologists (Fitzgerald 1991), environmental proponents, and other individuals have expressed concern that populations of Gunnison's prairie dogs have been reduced by epizootics of plague (Lechleitner et al. 1962, 1968; Fitzgerald 1969, 1978, 1993; Rayor 1985), and control of prairie dogs (Fitzgerald 1991) in Colorado. Speculation exists that the Gunnison's prairie dog might be petitioned for listing as threatened or endangered. Decisions to list the Gunnison's prairie dog should be based upon the most accurate and most current data. In this report, I summarize information from various sources about the status of Gunnison's prairie dog in Colorado. �165 Colorado Agricultural Statistics Service (1990) Survey Colorado Agricultural Statistics Service (1990) surveyed 9,046 farmers and ranchers and obtained nearly 3,000 surveys to estimate that 1,553,000 acres were occupied by prairie dogs in Colorado during 1989. This survey estimated acres occupied by prairie dogs in each county, but it did not differentiate between acres occupied by Gunnison's prairie dogs, black-tailed prairie dogs (Cynomys ludovicianus), and white-tailed prairie dogs (Cynomys leucurus). Thus, I used distribution maps in Fitzgerald et al. (1994) to ascertain which counties were occupied by the 3 species of prairie dogs. In counties where Gunnison's prairie dogs overlapped with 1 of the other species of prairie dogs, I estimated the relative proportion of the county that was occupied by Gunnison's prairie dogs. I multiplied that proportion by the acreage reported occupied by all prairie dogs in a county to obtain an estimate of the acreage occupied by Gunnison's prairie dogs for that county. I summed the acres of reported Gunnison's prairie dogs in each county and obtained an estimated 445,500 acres of reported Gunnison's prairie dogs in Colorado during 1989 (Table 1). Jim Fitzgerald (1991) letter to Galen Buterbaugh, U.S. Fish and Wildlife Service Fitzgerald (1991) expressed concern about the status of the gunnisoni subspecies of the Gunnison's prairie dog. He indicated that plague and poisoning have eliminated almost all populations in South Park. He also indicated populations appear to be in poor condition in the San Luis Valley, they appear to be gone from the extreme upper Arkansas River valley, and populations appear to be small and patchy in other parts of its historic range in Colorado. He believed Gunnison's prairie dogs are gone from Jefferson, Douglas, and Lake Counties in Colorado. He noted that a large complex exists on the Curecante National Recreation Area west of Gunnison, Colorado. Fitzgerald (1991) sent inquiries to all Colorado Division of Wildlife District Wildlife Managers and Wildlife Biologists and reported that a disappointing number of colonies were identified. He indicated that the low number of reports of colonies sent to him by the Colorado Division of Wildlife and his low estimates are in direct contrast to acreage of Gunnison's prairie dogs reported by Colorado Agricultural Statistics Service (1990). Robert Finley (1991) Survey of Distribution and Status of Gunnison's Prairie Dogs in Colorado Finley (1991) conducted a broad reconnaissance survey of the distribution of Gunnison's prairie dogs by driving some highways and roads and recording observations of prairie dogs. He observed 74 Gunnison's prairie dog colonies, of which 42 were active. He recorded colonies in 10 counties. He reported the largest active colonies were in the Gunnison drainage. He reported that South Park was almost devoid of prairie dogs, but he found a medium sized colony near Hartsel and a few on the periphery. He indicated that some mammalogists suspect that the spread of Wyoming ground squirrels southward through Colorado, after prairie dogs die out from plague, may be preventing prairie dogs from repopulating their former towns east of the Continental Divide and north of the Arkansas River. Finley (1991) concluded that populations of Gunnison's prairie dogs "seem to be far below those reported in the years prior to plague epizootics", "but I do not feel that the present situation is serious enough to warrant protection by Threatened status." �166 Mike Threlkeld, Chief of Rodent Control, Colorado Department of Agriculture (Personal Communication, 11 June 2002) Mike Threlkeld indicated that there are large acreages of Gunnison's prairie dogs around Cortez (perhaps 7,000 acres), Dolores, Montrose (perhaps 7,000 acres), Blue Mesa Reservoir, between Dove Creek and NuclalNaturita, west of Canyon City, north of Salida, and on the Ute Mountain Indian Reservation (perhaps over 7,000 acres). Colorado Division of Wildlife (2002) Report on Acreage of Gunnison's Prairie dogs Field personnel from the Colorado Division of Wildlife, Forest Service, and the Bureau of Land Management placed Gunnison's prairie dog colonies on 1:50,000 US Geological Survey County sheets during July and August, 2002 (Colorado Division of Wildlife 2002). The colonies were assigned as active (prairie dogs know to be present in the last 3 years) or unknown status (prairie dogs have been active but current presence in the area is unknown and requires field verification). From this exercise, the Colorado Division of Wildlife (2002) reported 85,795 acres of active and 194,777 of unknown acres of Gunnison's prairie dogs in Colorado (Table 1). In addition, 53,832 acres of active prairie dogs were identified in Delta County, where it was not know if these acres represented Gunnison's or white-tailed prairie dogs. These acreages are considered preliminary minimum estimates of the number of acres occupied by Gunnsion's prairie dogs. Craig Knowles (2002) Report on Status of White-tailed and Gunnison's Prairie Dogs Knowles (2002) primarily summarized Colorado Division of Wildlife (2002) for his assessment of the current status of Gunnison's prairie dogs in Colorado. He criticized the Colorado Agricultural Statistics Service (1990) report of acreage of prairie dogs in Colorado by stating" ...these estimates clearly greatly inflate the acreage at least in some counties." However, it is worth noting that Knowles (1998). reported that there was only 44,000 acres of black-tailed prairie dogs in Colorado during 1998, whereas the Colorado Agricultural Statistics Service (1990) estimated about 930,000 (calculated from their report). Recent aerial surveys by the Colorado Division of Wildlife (following Sidle et al. 2001) indicate that there are about 631,000 acres occupied by black-tailed prairie dogs in Colorado (F. Pusaterie, personal communication). Thus, the estimates provided by Colorado Agricultural Statistics Service (1990) were much closer than Knowles (1998) to the acreage reported by the Colorado Division of Wildlife. Knowles (2002) indicated that Gunnison's prairie dog populations in Colorado were greatly reduced by plague and poisoning during the 1900s and this decline may be continuing, or at best, the populations may be stable. Synthesis of Reports on Abundance of Gunnison's Prairie Dogs in Colorado Abundance of Gunnison's prairie dogs likely has declined in Colorado, particularly starting during the 1940s when plague became endemic. Our best estimates of the acreage of Gunnison's prairie dogs in Colorado seem to be provided by Colorado Division of Wildlife (2002) and Colorado Agricultural Statistics Service (1990). The Colorado Division of Wildlife (2002) reports a preliminary minimum of 85,700 acres of active Gunnison's prairie dogs, another 194,800 acres of Gunnison's prairie dogs where their status is unknown, and another 53,800 acres of prairie dogs in Delta County which are either Gunnison's or white-tailed prairie dogs. The Colorado Agricultural Statistics Service (1990) survey of acreage of prairie dogs in Colorado during 1989, from which I derived 445,500 acres of reported Gunnison's prairie dogs, has been criticized as biased by Knowles (1998, 2002). However, Colorado Agricultural Statistics Service (1990) and Colorado Division of Wildlife (2002) seem to concur at least to some extent. The Colorado Division of Wildlife is assessing the feasibility of aerial surveys for estimating acreage of Gunnison's prairie dogs in Colorado. Pending feasibility, these surveys are needed to provide better estimates of the acreage of Gunnison's prairie dogs in Colorado. �167 LITERATURE CITED Anderson, E. A., S. C. Forrest, T. W. Clark, and L. Richardson. 1986. Paleobiology, biogeography, and systematics of the black-footed ferret, Mustela nigripes (Audubon and Bachman), 1851. Great Basin Naturalist Memoirs 8: 11-62. Armstrong, D. M. 1972. Distribution of mammals in Colorado. Museum of Natural History, University of Kansas Monograph 3. 415pp. Burnett, W. L., and S. C. McCampbell. 1926. The Zuni prairie dog in Montezuma County, Colorado. Office of State Entomologist, Colorado Agricultural College, Fort Collins, Colorado. Circular 49, 16pp. Clark, T. W. 1973. Prairie dogs and black-footed ferrets in Wyoming. Pages 88-101 in Linder, R. L., and C. N. Hillman, editors. Proceedings of the black-footed ferret and prairie dog workshop. South Dakota State University, Brookings, South Dakota. Colorado Agricultural Statistics Service. 1990. Vertebrate rodent infestation survey. Colorado Department of Agriculture, Lakewood, Colorado. Colorado Division of Wildlife. 2002 (September). Report of acreages of active colonies for Gunnison's prairie dogs (Cynomys gunnisoni) and white-tailed prairie dogs (Cynomys leucurus). 2pp. Cully, J. F., Jr. 1993. Plague, prairie dogs, and black-footed ferrets. Pages 38-49 in J. L. Oldemeyer, D. E. Biggins, B. J. Miller, and R. Crete, editors. Proceedings of the symposium on the management of prairie dog complexes for the reintroduction of the black-footed ferret. US. Fish and Wildlife Service Biological Report No. 13. Ecke, D. H., and C. W. Johnson. 1952. Plague in Colorado. Part I. Plague in Colorado and Texas. US. Public Health Service, Public Health Monograph 6: 1-54. Finley, R. B., Jr. 1991. Survey of present distribution and status of Cvnomys gunnisoni gunnisoni in Colorado. Unpublished manuscript. 9pp. Fitzgerald, J. P. 1969. Sylvatic plague in Gunnison's prairie dog (Cynomys gunnisoni) and associated mammals in South Park, Colorado. Journal of the Colorado Wyoming Academy of Science 7:45. Fitzgerald, J. P. 1978. Plague tYersinia pestis) epizootics in introduced Gunnison's prairie dogs: implications for prairie dog management. New Mexico Academy of Science Bulletin 18:40. Fitzgerald, J. P. 1991. Letter to Galen Buterbaugh, Regional Director, US. Fish and Wildlife Service. Dated 1 April 1991. Fitzgerald, J. P. 1993. The ecology of plague in Gunnison's prairie dogs and suggestions for the recovery of black-footed ferrets. Pages 50-59 in J. L. Oldemeyer, D. E. Biggins, B. J. Miller, and R. Crete, editors. Proceedings of the symposium on the management of prairie dog complexes for the reintroduction of the black-footed ferret. US. Fish and Wildlife Service Biological Report No. 13. Fitzgerald, J. P., and R. R. Lechleitner. 1974. Observations on the biology of Gunnison's prairie dog in central Colorado. American Midland Naturalist 92:146-163. �168 Fitzgerald, J. P., C. A. Meaney, and D. M. Armstrong. Colorado, Niwot, Colorado. 488pp. 1994. Mammals of Colorado. University Press of Knowles, C. J. 1998. Status of the black-tailed prairie dog. Unpublished manuscript prepared for U.S. Fish and Wildlife Service, Pierre, South Dakota. 12pp. Knowles, C. 2002. Status of white-tailed and Gunnison's prairie dogs. National Wildlife Federation, Missoula, Montana and Environmental Defense, Washington, DC. 30pp. Lechleitner, R R, L. Kartman, M. I. Goldenberg, and B. W. Hudson. 1968. An epizootic of plague in Gunnison's prairie dogs (Cynomys gunnisoni) in south-central Colorado. Ecology 49:734-743. Lechleitner, R R, J. V. Tileston, and L. Kartman. 1962. Die-off of a Gunnison's prairie dog colony in central Colorado, I. Ecological observations and description Ofthe epizootic. Zoonoses Research 1:185-199. Longhurst, W. 1944. Observation on the ecology of the Gunnison prairie dog in Colorado. Journal of Mammalogy 25:24-36. Rayor, L. S. 1985. Dynamics of a plague outbreak in Gunnison's prairie dogs. Journal of Mammalogy 66:194-196. Sidle, J. G., D. H. Johnson, and B. R Euliss. 2001. Estimated areal extent of colonies of black-tailed prairie dogs in the northern great plains. Journal of Mammalogy 82:928-936. �169 Table 1. Acres of Gunnison's prairie dogs reported and estimated from the Colorado Agricultural Statistics Service (1990) survey during 1989 and estimated by Colorado Division of Wildlife (2002) during 2002 in Colorado. Colorado Agricultural Statistics Service survey County Alamosa Archuleta Chaffee Conejos Costilla Custer Delta Dolores Douglas EI Paso Fremont Gunnison Hinsdale Huerfano Jefferson Lake La Plata Las Animas Mineral Montezuma Montrose Ouray Park Rio Grande Saguache San Juan San Miguel Teller TOTAL: Acres of all Qrairie dogs 6,200 48,900 3,200 20,500 1,600 5,900 52,500 56,000 12,600 16,700 15,300 5,800 300 6,400 1,700 900 80,000 18,500 200 92,000 52,100 7,400 5,100 . 14,300 13,200 13,400 5,200 555,900 Proportion acres' occupied by Gunnison's Q.dogs 1.0 1.0 1.0 1.0 1.0 1.0 0.12 1.0 0.25 0.05 1.0 1.0 l.0 0.63 0.31 l.0 l.0 0.2 l.0 1.0 0.73 0.5 l.0 1.0 l.0 l.0 l.0 1.0 Acres of Colorado Division Gunnison's of Wildlife Qrairie dogs . Active acres Unknown acres 6,200 2 12,220 48,900 18,226 15,978 3,200 2,467 0 20,500 4,707 67,218 1,600 14,948 25,439 5,900 6,300 56,000 3,363 2,549 3,150 58 0 835 15,300 5,800 611 221 300 4,032 527 900 80,000 6,816 619 3,700 200 449 1,221 92,000 12,223 0 38,033 6,482 0 3,700 647 0 5,100 42 3,150 14,300 12,263 2,094 13,200 2,659 58,891 13,400 5,200 448,277 2,017 ~ 85,795 2,927 __ 0 194,777 'Obtained by estimating the proportion of a county (from Fitzgerald et al. 1994) that was occupied by Gunnison's prairie dogs, white-tailed prairie dogs, and black-tailed prairie dogs, and then dividing the proportion for Gunnison's prairie dogs by the sum of proportions for all 3 species. �170 EVALUATION OF AERIAL SURVEYS FOR ESTIMATING ACREAGE OF GUNNISON'S AND WHITE-TAILED PRAIRIE DOGS IN COLORADO AND UTAH W. F. Andelt, P. M. Schnurr, and A. Seglund During November 2002, we (Andelt and Schnurr 2002) reported our assessment of 3 survey techniques, including ground surveys, interpretation of satellite imagery (Sidle et al. 2002), and aerial surveys (Sidle et al. 2001), for obtaining a valid estimate of the distribution and acreage of Gunnison's prairie dogs (Cynomys gunnisoni) in Colorado. We concluded that ground surveys likely would be very difficult, if not impossible to implement for obtaining a valid scientific estimate of acreage of Gunnison's prairie dogs in Colorado. However, we recognized that ground surveys could be used to provide an estimate of the minimum acreage of Gunnison's prairie dogs in Colorado. We concluded that satellite imagery is very expensive ($2,000 per 36 mi2 or $2,880 per 100 m? of digital imagery [John Norman, Natural Resources Ecology Lab, CSU; personal communication]), the imagery would need to be interpreted and verified, activity of prairie dog towns would need to be ascertained on the ground, and it is unknown if the technology would be suitable in rolling terrain. Aerial surveys, using line intercept methodology, have been used to estimate area occupied by black-tailed prairie dogs (Cynomys ludovicianus) (Sidle et al. 2001, J. Dennis and F. Pusaterie, Colorado Division of Wildlife; personal communication). We concluded that the technique held promise for estimating acreage of Gunnison's prairie dogs in Colorado. In this paper, we report on our current progress in evaluating aerial surveys for estimating acreage of Gunnison's and white-tailed prairie dogs (Cynomys leucurus) in Colorado and Utah. Initially, on 13 June 2002, William Andelt accompanied Jim Dennis and Dave Younkin on an aerial survey of black-tailed prairie dogs to gain additional familiarity with the technique. On 24 June 2002, William Andelt and Larry Gepfert, CDOW, flew over the 32 active Gunnison's prairie dog colonies reported by Joe Cappodice. With the aid of a GPS unit, all colonies were located, although some of the smaller colonies were somewhat difficult to observe. We ascertained that aerial surveys appear to have potential for establishing distribution of Gunnison's prairie dogs and that further investigation of the technique was merited. However, because of some difficulty in observing some colonies, we, in collaboration with Gary White, decided that future test flights should also obtain photos of prairie dog colonies; classify colonies as being located in grassland, short shrubs, tall shrubs, or agriculture; rank the colonies as barely detectable, detectable, or highly detectible; and classify colonies as active, inactive, or unknown. Our plans were to use these data to estimate detection probabilities for the various categories of colonies. We then planned to use the detection probabilities to correct acreages of prairie dog colonies observed from the air (White 2002). Subsequently, during summer 2002, Pam Schnurr and Gary White met with Amy Seglund and Bill Bates, biologists with the Utah Division of Wildlife Resources (UDWR). Both states agreed to coordinate and cooperate to further ascertain the feasibility of aerial surveys to estimate acreage of Gunnison's and white-tailed prairie dogs, and to develop detection probabilities for both species. METHODS We entered the boundaries of known Gunnison's and white-tailed prairie dog colonies in both Colorado and Utah into GIS Arc/Info. We established 31, 17, 19, and 11 transects across these Gunnison's and white-tailed prairie dog colonies in Colorado and Utah, respectively. These transects were established across known colonies in both states along with a number of control transects (i.e. transects over areas without colonies). Beginning and ending UTM coordinates were ascertained for each transect and placed in a spreadsheet. We hired and trained a ground crew that verified the distribution of all white-tailed prairie dog colonies on the transects in Colorado. �171 Jim Dennis and Dave Younkin, CDOW, and Brad Crompton and Craig Hunt, from the Utah Division of Wildlife Resources flew all 4 sets of transects and obtained GPS coordinates for the beginning and end of prairie dog colonies on the transects. The crew from Colorado had extensive experience surveying black-tailed prairie dogs, whereas the crew from Utah had extensive experience with aerial surveys of wildlife, other than prairie dogs. The Utah and Colorado survey teams flew the transects in opposite directions. We plotted the endpoints of the prairie dog colonies that were ascertained by both aerial crews on all transects in GIS Arc/Info. We used Arc/Info to determine the lengths of each colony on each transect and then entered these data in a spreadsheet. We summed the lengths of colonies ascertained on the ground and from the air on each transect. We analyzed these data in SAS using Proc GLM to determine the effect of aerial team, rating of colony visibility, and rating of habitat type on the proportion of colonies observed on aerial versus ground surveys. We censored transects without prairie dogs known on ground surveys, and then used Spearman Correlation (Proc CORR) analyses to ascertain correlations for proportion of colonies observed, ratings of visibility, and ratings of habitat types between the 2 aerial crews. We also used Spearman Correlation analyses to ascertain correlations between ratings of visibility of colonies and proportion of colonies detected, and ratings of habitat types and proportion of colonies detected. RESULTS The Colorado and Utah teams overestimated lengths of Gunnison's prairie dog colonies on transects in Colorado and Utah (Table 1). Both teams also overestimated lengths of white-tailed prairie dog colonies on the white-tailed site in Utah. In contrast, the Colorado team underestimated lengths of colonies on the white-tailed site in Colorado. Although the Utah team closely estimated the overall average lengths of colonies on this site, we found considerable variation between total lengths of colonies on transects observed by this team versus those known on the ground. The Utah aerial team (x = 5.3; S.E. = 1.11), compared to the Colorado team (x = 2.3; S.E. = 0.36), observed a greater proportion oflengths of colonies on transects (Tables 1, 2), however both teams significantly overestimated the lengths of colonies compared to the lengths ascertained on the ground. The proportion of length of prairie dog colonies observed from the air compared to the lengths ascertained from the ground were not related to ratings of visibility nor to ratings of habitat types observed from the air (Table 2). Proportion of lengths of prairie dog colonies detected by aerial crews from Colorado and Utah were weakly correlated (Table 3). However, ratings of visibility of colonies and ratings of type of habitat found on transects of colonies were not correlated between the Colorado and Utah aerial crews. The 2 crews did not consistently report finding prairie dogs in the same areas along the same transect. This may partially explain the differences between the 2 crews in their ratings of visibility of colonies and rating of habitat types on transects. Proportions of lengths of colonies detected by aerial crews were not correlated with rating of visibility of colonies on transects (Table 4). The greatest proportions of lengths of colonies were detected by aerial crews on transects described as grasslands followed by transects described as short shrubs and then followed by transects described as tall shrubs (Table 4). The Colorado team rated prairie dogs on 76% of 51 transects as active, 12% as unknown, and 12% as a combination of active and unknown. The Utah team rated prairie dogs on 28% of 63 transects as active, 2% as inactive, 57% as unknown, and 25% as a combination of active, inactive, and unknown. �172 DISCUSSIONS AND RECOM MENDATIONS We recognize a number of goals when inventorying prairie dogs. We believe the most important goal is to obtain accurate and repeatable estimates (i.e. low variation within and among survey crews) of the acreage of Gunnison's and white-tailed prairie dogs. Low variation among survey crews is necessary so that differences between estimates of acreage are actually related to increases or decreases in acreage of prairie dogs rather than differences between crews. Another goal for inventorying prairie dogs is to establish minimum acreages of prairie dogs which we can relate to their status and decisions about listing them as threatened or endangered. Our goal has been to ascertain the feasibility of aerial surveys for estimating acreage of Gunnison's and white-tailed prairie dogs in Colorado and Utah. We envisioned this as a multi-step process. We first flew over known Gunnison's prairie dog colonies and noted that many of the colonies were visible from the air. Next, we arranged aerial surveys by crews from Colorado and Utah to estimate . the length of colonies on transects where the distribution of prairie dogs were known to us, but unknown to the crews. Accuracy of aerial surveys was not sufficient to estimate detection probabilities. We found significant variation between the 2 aerial teams in estimates of lengths of prairie dog colonies on transects, however these estimates were weakly correlated between the 2 teams. Shortly after completing the aerial flights and before data were compiled, Jim Dennis noted that his team likely could have more accurately estimated lengths of prairie dog colonies by conducting some flights followed by ground reconnaissance of the same transects to verify what they were observing from the air (see Appendix 1). We anticipate this training would enhance accuracy of estimates. We recommend that training, or other methods to improve estimates between teams, are needed before broad scale surveys are conducted. The large variation between teams in our study indicate that, without improving accuracy and consistency between teams, it would be difficult to ascertain even moderate changes in acreages of prairie dogs. The Colorado and Utah teams surveyed the Colorado white-tailed prairie dog site on 20 September and 28 August 2002, respectively. The Colorado team rated 10 of the transects as active and 2 as unknown. The Utah team rated 4 transects as active, 1 as inactive, 5 as unknown, and 4 as activeinactive or active-unknown. We surveyed part of the Colorado white-tailed site from the ground on 23 September 2002 and found very little sign of activity by prairie dogs. Thus, we recommend that ground crews verify ratings of activity on a random sample of future transects. If aerial crews are unable to accurately determine activity, a ground crew will need to verify activity on a random portion of transects on future surveys. We reviewed potential causes for why estimates of lengths of prairie dog colonies varied between ground surveys and aerial surveys, and between the 2 aerial crews. We closely surveyed the distribution of prairie dogs on the white-tailed sites in Colorado and Utah, but additional verification on the ground is needed for the 2 Gunnison's prairie dog sites to insure that accuracy of ground surveys is not a cause of error. Coordinates of prairie dog colonies were recorded on the ground and by the Utah team in the NAD27 datum. The Colorado team used the WGS84 datum when they flew the transects. The use of the WGS84 resulted in the Colorado team being 38 to 219 m off the actual transect, depending on the study area and direction of flight (east-west versus north-south). Although we initially suspected that the 38 to 219 m away from transects resulted in some errors, our review of the data suggested that accuracy appeared similar when the airplane was on the transect versus away from the transect. The Utah team strayed over 1,000 m from portions of 4 transects which likely attributed to some errors. �173 We recognize 2 general approaches (ground vs. aerial surveys) for continuing surveys of Gunnison's and white-tailed prairie dogs. To continue aerial surveys, we recommend that the distribution of prairie dogs is more accurately verified on the ground on the 2 Gunnison's prairie dog sites. If distributions are different than what is currently known, the distribution of prairie dogs on aerial and ground surveys should be compared again. Then, we recommend training aerial crews by conducting flights over short transects over some colonies and then surveying the colonies from the ground so that they can better ascertain what they are observing from the air. After this training, we recommend reflying the previous transects to ascertain if accuracy can be improved. If accuracy cannot be improved, we recommend discontinuing aerial surveys. An alternative to surveying prairie dogs from the air would be to continue Pam Schnurr's earlier work of meeting with biologists to plot known distribution of Gunnison's and white-tailed prairie dogs on maps. A ground crew should then verify a random portion of these distributions. Although this alternative likely would cost less than aerial surveys, it likely would underestimate acreage of prairie dogs and would not provide an adequate and repeatable sample for future comparisons. However, this methodology might be sufficient for considerations of listing prairie dogs as threatened or endangered. LlTURATURE CITED Andelt, W. F., and P. Schnurr. 2002. Progress report: inventorying Gunnison's prairie dogs in Colorado. Unpublished Report submitted to the Colorado Division of Wildlife, Denver, Colorado. Sidle, J. G., D. H. Johnson, and B. R. Euliss. 200l. Estimated areal extent of colonies of black-tailed prairie dogs in the northern great plains. Journal of Mammalogy 82:928-936. Sidle, J. G., D. H. Johnson, B. R. Euliss, and M. Tooze. 2002. Monitoring black-tailed prairie dog colonies with high-resolution satellite imagery. Wildlife Society Bulletin 30:405-41l. White, G. C. 2002. Memorandum to Pam Schnurr, Bill Bates, and Amy Seglund, Colorado Division of Wildlife and Utah Division of Wildlife Resources. Dated July 1, 2002. �174 Table 1. Average length (m) of Gunnison's and white-tailed prairie dog colonies, observed from the ground and reported by aerial survey crews from the Colorado Division of Wildlife and the Utah Division of Wildlife Resources, on transects surveyed in Colorado and Utah during August, September, and November 2002. Area Colorado Colorado Colorado Colorado Utah Utah Utah Utah SQecies Gunnison's Gunnison's White-tailed White-tailed Gunnison's Gunnison's White-tailed White-tailed Team Colo Utah Colo Utah Colo Utah Colo Utah Date of Transects Avg. Avg. length of colonies/transect" Proportion of colony leng1h observed" survey 9/19-20 10/1 9/20 8/28 9/23 8/28 9/24 8/26 N length 31 8,671 31 8,671 17 5,446 17 5,446 19 10,660 19 10,660 11 40,403 11 40,403 Ground 264 246 1,955 1,955 424 424 2,912 2,912 Aerial 723 1,511 1,202 1,984 1,770 3,406 9,714 5,418 N 18 18 14 14 11 11 8 8 X 2.6 8.4 0.7 l.8 3.5 7.5 2.7 l.7 S.E. 0.65 2.57 0.16 0.80 0.97 2.09 0.85 0.44 1,045 1,045 2,350 2,626 51 51 2.3 5.3 0.36 1.11 TOTAL: 78 78 Colo Utah 12,928 12,928 "Represents average length of colonies known primarily from ground reconnaissance, and estimated from aerial surveys on transects with and without prairie dog colonies. 'Represenrs proportion of length of prairie dog colonies observed from aerial surveys divided by lengths ascertained from ground reconnaissance on transects with prairie dog colonies. Table 2. Effects of aerial teams", ratings of visibility of colonies", and ratings of habitat types" on proportions of length of Gunnison's and white-tailed prairie dog colonies observed on aerial transects during August, September, and November 2002. IndeQendent variable Aerial teams Rating of visibility Rating of habitat type df 1 4 5 F 6.79 0.57 0.48 P 0.011 0.684 0.793 "Aerial team from Colorado Division of Wildlife and from Utah Division of Wildlife Resources. bBarely detectible, barely detectible-detectible, detectible. "Grassland, grassland-short detectible, detectible-highly detectible, highly shrub, short shrub, short shrub-tall shrub, tall shrub, agricultural. �175 Table 3. Correlations between aerial crews from the Colorado Division of Wildlife and the Utah Division of Wildlife Resources for proportions oflengths of prairie dog colonies detected, ratings of visibility a, and ratings of habitat types" on aerial transects of Gunnison's and white-tailed prairie dogs observed during August, September, and November 2002. . Utah team Colorado team Variable Proportion of colony length detected Rating of visibility of colony Rating of habitat type on colony X N 51 30 22 S.E. 0.36 0.11 0.12 2.3 2.4 2.2 "I = barely detectible, 1.5 = barely detectible-detectible, detectible, 3 = highly detectible. X N 51 30 22 S.E. 1.11 0.10 0.08 5.3 2.5 1.4 r~ 0.301 -0.020 -0.066 P 0.032 0.916 0.769 2 = detectible, 2.5 = detectible-highly l = grassland, 1.5 = grassland-short shrub, 2 = short shrub, 2.5 = short shrub-tall shrub, 3 = tall shrub. b Table 4. Correlations between ratings of visibility" and proportions of prairie dog colony lengths detected, and ratings of habitat types" and proportions of prairie dog colony lengths detected on transects of Gunnison's and white-tailed prairie dogs combined by aerial crews from the Colorado Division of Wildlife and the Utah Division of Wildlife Resources combined during August, September, and November 2002. VisibilitylHabitat Variable Visibility versus proportion of colony length detected Habitat versus proportion of colony length detected Proportion of colony detected r~__ P N X S.E. N X 77 2.4 0.07 77 4.5 0.76 0.038 0.742 65 1.7 0.07 65 4.3 0.88 -0.246 0.048 "I = barely detectible, 1.5 = barely detectible-detectible, detectible, 3 = highly detectible. S.E. 2 = detectible, 2.5 = detectible-highly bl = grassland, 1.5 = grassland-short shrub, 2 = short shrub, 2.5 = short shrub-tall shrub, 3 = tall shrub. �176 Appendix 1. Suggestions for Aerial Surveys (from Andelt and Schnurr 2002). Based upon our flight with Larry Gepfert and suggestions from Jim Dennis and Dave Younkin we have developed a number of suggestions for aerial surveys of Gunnison's prairie dogs and white-tailed prairie dogs: • Elevation and overall range distributions (Armstrong 1972, Fitzgerald et al. 1994) should be ascertained before aerial surveys are conducted to minimize the area that needs to be surveyed. • Flight crews should spend at least 1 day on the ground in Gunnison's prairie dog and white-tailed prairie dog towns to become more familiar with the towns before they fly transects. The crews should also gain experience by flying over known colonies. After flying over known colonies, the crew should spend some time on the ground in a colony to better ascertain what they have seen from the air. • Transects should be constructed along drainages, instead of across drainages, to minimize changes in elevation while conducting surveys. Further, transects should be flown down the drainage, instead of up drainages, to maximize aircraft maneuverability while minimizing danger. RECOMMENDED PLANS FOR FUTURE • Complete ground surveys to establish the remaining "known" boundaries for white-tailed prairie dog colony transects already flown in Colorado. Compare known and aerial estimates of the locations of prairie dog colonies to ascertain accuracy of aerial surveys. • Ascertain if a correction for detection probabilities will need to be employed. This will be primarily needed if the aerial crews were unable to observe a significant proportion of the "known" colonies. • Determine strata boundaries utilizing recent WRlS mapped activity areas and elevation limits for prairie dogs to minimize the extent of surveys. • Establish transect lines along drainages and within strata. • Determine who will conduct aerial surveys in Colorado. We suspect that we will need to contract with a commercial company. • Ascertain if prairie dog colony activity can be determined from the air. If colony activity cannot be determined from the air, a subset ground sampling technique will need to be established to determine activity. During September field trips to the white-tailed colony in Colorado, we were unable to ascertain activity of many colonies because many prairie dogs apparently entered hibernation early this year due to the drought (Dean Biggins, personal communication). �177 PRELIMINARY EVALUATION OF SURVEYS OF PLOTS FOR ESTIMATING OCCURRENCE OF WHITE-TAILED PRAIRIE DOGS IN COLORADO AND UTAH W. F. Andelt, G. C. White, P. M. Schnurr, and A. Seglund Our research (see above) indicated that aerial line-intercept surveys likely will not work for reliably estimating acreage of Gunnison's and white-tailed prairie dogs. Thus, during Spring 2003, we established a pilot project and surveyed 19 500 by 500 m plots from the ground and air to ascertain if surveys of plots can be used to ascertain trends in occurrence of white-tailed prairie dogs in Colorado and Utah. We focused on white-tailed prairie dogs because they have been petitioned for listing as a threatened or endangered species, but we also plan to expand this methodology for Gunnison's prairie dogs. METHODS We overlaid 7.5 minute topo maps (NAD27 datum) in GIS with 500 by 500 m grid lines on each of 4 study areas (WolfCreek and Grand Valley, Colorado, Coyote Basin and Cisco, Utah) where locations of prairie dogs were identified. After reviewing the maps and visiting with colleagues familiar with distributions of prairie dogs in each of the 4 study areas, we visited grids (plots) in the field and choose 6 plots in Wolf Creek and 6 plots Coyote Basin such that 2 had low, 2 had medium, and 2 had relatively high abundance of prairie dogs. Also within this classification, 1 of each of the low, medium, and high abundance grids had low visibility and the other high visibility. We also established 4 plots in the Grand Valley, near Grand Junction, and 3 plots near Cisco, Utah in areas with relatively low abundance of white-tailed prairie dogs. During June 2003, we visited the 4 corners of most study plots 3 times each to establish detection probabilities, with 1 visit during 0700-1100, another visit during 1100-1500, and another visit during 1500-1900 hrs. For each study plot, we recorded the investigator's name, date, time, UTM Zone, GPS coordinates for the lower left (SW) corner of the plot, percent cloud cover, and soil type (from a soil survey map), approximate precipitation during last 24 hours, and approximate precipitation during last 30 minutes. For the 4 corners of each plot, we recorded temperature, wind direction, approximate wind speed, percent of plot that was visible, percent of plot in sunshine, rating of visibility, rating of elevation, number of mounds observed, and groups of prairie dogs observed. On 12 June, William Andelt flew over each study plot to ascertain if prairie dogs could be reliably detected in plots from aircraft. We also hired a commercial company to photograph, with high resolution, 9 by 9 inch, color infrared film, 21 study plots to ascertain its feasibility for establishing occurrence of prairie dogs in plots. RESULTS AND DISCUSSION We are currently analyzing data from our pilot observations of white-tailed prairie dogs within 19 study plots. Initial results indicate that we should be able to reliably monitor occurrence and detect changes in occurrence of white-tailed prairie dogs by visiting plots from the ground. We plan to establish about 300 (based upon computer simulations) random plots within the range of white-tailed prairie dogs in Colorado. We plan to hire a field crew and visit these plots to ascertain occurrence of prairie dogs during spring and summer 2004. Our flight over 21 study plots indicate that an airplane might be used to establish occurrence of prairie dogs in high density plots, especially on warm days with snow cover during spring. We will evaluate aerial photographs after they are developed. We also plan to conduct a pilot study, during spring 2004, of the above methodology for ascertaining occurrence of Gunnison's prairie dogs in Colorado. We are currently writing a proposal which will detail our subsequent work. �178 CHRONIC WASTING DISEASE W. F. Andelt We established links, on my web site (http://www.coopext.colostate.edu/wildlife/ , then, go to Diseases), to 9 sites that contain information on chronic wasting disease. I informed all extension personnel, including all county extension agents, in Colorado about the availability of this information on my web site. I also informed 153 Cooperative Extension volunteers at 3 training sessions in Colorado, that information on chronic wasting disease was available on my web site. My web page on Diseases was accessed 701 times during January-June, 2003. EXTENSION'INFORMATION ON RESOLVING HUMAN-WILDLIFE CONFLICTS W. F. Andelt My Cooperative Extension activities included: Refereed Publications: Yoder, C. A, W. F. Andelt, L. A Miller, 1. 1. Johnston, and M. J. Goodall. 2003. Effectiveness of twenty, twenty-five diazacholesterol, avian gonadotropin releasing hormone, and chicken riboflavin carrier protein for inhibiting reproduction in Cotumix quail. (Submitted to Poultry Science). Refereed Publications In Preparation: Schwartz, A M., and W. F. Andelt. Effects of castration on reproduction and social structure in the black-tailed prairie dog (Cynomys ludovicianusy. (Manuscript is 95% completed, will be submitted to the Journal of Wildlife Management). Schwartz, A M., and W. F. Andelt. Effects of castration on body mass and survival in the blacktailed prairie dog (Cynomys ludovicianus). (Manuscript is 95% completed, will be submitted to the Journal of Wildlife Management). Heffernan, D. 1., W. F. Andelt, and 1. A. Shivik. Coyote exploratory behavior following removal of novel stimuli. (Manuscript is 95% completed, will be submitted to the Journal of Wildlife Management. Book Chapters: Lamb, B. L., R. P. Reading, and W. F. Andelt. 2003. Public attitudes and perceptions toward black-tailed prairie dogs. Pages _ to _ in 1. L. Hoogland, editor. Conservation and management of prairie dogs. Island Press, Washington, D.C. (Submitted 2nd draft). Andelt, W. F. 2003. Methods and economics of managing prairie dogs. Pages _ to _ in J. L. Hoogland, editor. Conservation and management of prairie dogs. Island Press, Washington, D.C. (Submitted 3rd draft). �179 Extension Publications: Andelt, W. F. 2002. Impacts of drought on wildlife. lpp. (Published at http://drought.colostate.eduD. Andelt, W. F., S.N. Hopper, and M. Cerato. 2002 (revised). Preventing woodpecker damage. Cooperative Extension Bulletin, Colorado State University, Fort Collins. 5pp. (Published at hnp-_:f!_F.lYF..&~!,y.Ql_9_i@j~,-edl!Lr!J~.siliAlRE.sLQ]JJm~1r.J}.!mJ) . Andelt, W. F. 2003. Preventing woodpecker damage to trees. The Green Scene (July, In press). Cerato, M., and W. F. Andelt. 2003 (revised). Coping with skunks. Cooperative Extension Bulletin, Colorado State University, Fort Collins. 5pp. (In press; will be published at ht!Q;LL,!{WF,_~!ftJ~_QIQ!:!1<:!!~._~g]Ji.PJ1~.S.mAIRE.Sjp-.\:!J2~~tf.,h!!!!D . Cerato, M., and W. F. Andelt. 2003 (revised). Coping with snakes. Cooperative Extension Bulletin, Colorado State University, Fort Collins. 6pp. (published at http://www.ext.colostate.eduiPUBSINATRES/pubnatr.html). Progress Reports: Andelt, W. F., and P. Schnurr. 2002. Progress report: inventorying Gunnison's prairie dogs in Colorado. Progress report submitted to Gary Miller, Colorado Division of Wildlife, 7 November 2002. 7pp. Andelt, W. F. 2003. Status of Gunnison's prairie dogs in Colorado. Progress report submitted to Gary Miller, Colorado Division of Wildlife, 13 January 2003. lOpp. Andelt, W. F., P. Schnurr, and A. Seglund. 2003. Evaluation of aerial surveys for estimating acreage of Gunnison's and white-tailed prairie dogs in Colorado and Utah. Progress report submitted to Gary Miller, Colorado Division of Wildlife, 24 February 2003. 13pp. Papers Presentation at National, Regional, and State Meetings: Andelt, W. F. 2003. Alternatives to toxicants for managing conflicts with black-tailed prairie dogs. Colorado Prairie Dog Technical Conference, Fort Collins, Colorado (Invited paper). Andelt, W. F. 2003. Behavioral modification of coyotes to reduce predation on livestock. Department of Fisheries and Wildlife, Utah State University (Invited paper). Andelt, W. F. 2003. Evaluation of aerial surveys for estimating acreage of Gunnison's and white-tailed prairie dogs in Colorado and Utah. Colorado Prairie Dog Technical Conference, Fort Collins, Colorado. Andelt, W. F. 2003. Incorporating experimental design in education on managing humanwildlife conflicts at Colorado State University. Tenth Wildlife Damage Management Conference, Hots Springs, Arkansas (Invited paper). Andelt, W. F. 2003. Managing conflicts with coyotes: aversive stimuli, novel stimuli, and livestock guarding dogs. Wyoming Student Chapter of The Wildlife Society, Laramie, Wyoming (Invited paper). �180 Andelt, W. F. 2003. Non-lethal methods for managing conflicts with prairie dogs. Colorado Prairie Dog Technical Conference, Fort Collins, Colorado (Invited paper). Jozwiak, E. A., T. N. Bailey, and W. F. Andelt. 2003. Response of wolves to changing harvest levels on the Kenai NWR, Alaska. The World Wolf Congress 2003 - Bridging Science and Community, The Banff Centre, Banff, Canada (submitted). Analyzed about 200 predator scats to help assess the role of various predators in the decline of sage grouse in northwestern Colorado. . Obtained $1,200 from the Renewable Resources Extension Act to revise Cooperative Extension fact sheets on managing conflicts with wildlife. Submitted a research proposal to study Ecology of coyotes and coyote predation on bighorn sheep in Rocky Mountain National Park, Colorado. Project was not funded. Co-coordinator and instructor at 3 2-4 hour workshops for 153 extension volunteers and 3 Colorado Division of Wildlife employees. Speaker at 3 Cooperative Extension meetings with 80 participants. Provided training for 55 biologists and other professionals including wildlife commissioners at I workshop. Presented 3 guest lectures to 107 students in Colorado State University courses on managing conflicts with wildlife. Advised an M.S. candidate that conducted research on resolving conflicts with prairie dogs, and a Ph.D. candidate that was conducted research on coyotes. Served on 2 M.S. and 1 PhD. Committees. Evaluated 27 posters for the Cooperative Extension Poster Session at the February 2003 InService training. Served on the Jefferson County Cooperative Extension Natural Resources Agent Search Committee. Served as a Mentor for Thomas Mason, Jefferson County Cooperative Extension Natural Resources County Agent. Served on the Colorado Department of Agriculture Pesticide Review Committee. Commented on impacts of pesticides on wildlife.· Provided extensive reviews of the efficacy data for the Rodex 4000 (an explosive device for killing rodents), and efficacy of 2 repellents (Deer Stopper, Deer Stopper Ready to Use) for deterring deer. Served on the Colorado State University Cooperative Extension, College of Natural Resources, Renewable Resources Extension Act Committee. Served on the Rodent Program Review Panel for the National Wildlife Research Center. �181 Updated my web site on Managing Conflicts with Wildlife at (_4np-;(l_w..w~,~Q.Qp._t;:xt~.QIQ_~@1~,_~g!!!Filg!if~DVarious pages of the web site have been accessed 227 to 3,381 times each during January-June 2003_ Provided interviews for 5 newspaper reporters at United Press International, Rocky Mountain News, Denver Post, and others. Provided interviews for 2 radio stations, Wrote 1 news release for CSU Cooperative Extension Agents. Reviewed 2 manuscripts for scientific journals and 1 manuscript for a colleague, Participated in about 75' meetings. Wrote about 50 e-mail messages about conflicts with wildlife, Answered about 50 telephone inquiries about managing conflicts with wildlife. �182 POSSIBLE ROLE OF PREDATORS IN THE SAGE GROUSE DECLINE W. F. Andelt Approximately $5,200 was received from the Moffat County Department of Natural Resources to conduct preliminary research on the possible role of predators in the sage grouse (Centrocercus urophasianus) decline in Moffat County. Red fox (Vulpes vulpes; Flinders [1999]) have been reported as one of the primary mammalian predators of sage grouse, whereas coyotes (Canis latrans; Presnall and Wood [1953]), bobcats (Felis rufus; Hartzler [1974], mink (Mustella vison; Hartzler [1974]), badgers (Taxidea laxus; Gill [1965]), and ground squirrels (Spermophilus spp.; Schroeder and Baydack [2001]) also prey on adults or nests of sage grouse. Thus, we obtained data on relative abundance of mammalian carnivores on 2 study areas (immediately northwest of Craig ["Craig"] and north of Maybell ("Maybell"). Sage grouse are scarce on the Craig study area which is fragmented habitat (sagebrush-grassland interspersed with CRP, alfalfa, and wheat), whereas they are moderately abundant on the Maybell study area which is primarily contiguous habitat (mostly sagebrush-grassland). Golden eagles (Aquila chrysaetos; Hartzler [1974]) appear to be the primary avian predator of sage grouse, particularly on leks, whereas prairie falcons (Falco mexicanus; Hartzler [1974]), red-tailed hawks (Buteo jamaicensis), Swainson's hawks (B. swainsoni), ferruginous hawks (B. regalis), northern harriers (Circus cyaneus; references in Schroeder and Baydack 2001) may occasionally kill some sage grouse. Common ravens (Corvus corax; Allred [1942], Autenrieth [1981], Alstatt [1988]) appear to be the primary avian predators of sage grouse nests or simulated nests, whereas black-billed magpies (Pica pica; Autenrieth [1981]) may prey on some nests. Consequently, we collected data on relative abundance of avian predators, and collected carnivore scats on the Craig study area, the Maybell study area, and in the Axial basin (Appendix 1), which consists primarily of contiguous habitat (mostly sagebrushgrassland) where sage grouse are moderately abundant. I also provided information to Dr. Tony Apa and colleagues on identifying which predators killed sage grouse or depredated their nests. Relative Abundance of Mammalian Predators During 5 to 10 June 2001, we (Dr. Andelt, 1 graduate student, and 1 technician) set 92 scent stations on the Craig study area and 92 scent stations on the Maybell study area to gain an assessment of general abundance of carnivores on the 2 sites. Scent stations are l-yard diameter circles of sifted earth with an attractant (fatty acid scent, small traffic cone or both) placed in the center. The scent stations were set in groups of 4 with each station 0.2 miles apart. Each group of 4 scent stations were set at least 2 miles apart to minimize visits to different groups of stations by individual carnivores. The locations for stations were mostly randomly selected from BLM maps. The stations were checked 1 day after they were set. A few of the stations were rendered inoperable by light to moderate rain. I used chi-square tests (PROC FREQ, SAS Inst. Inc. 1988) to analyze the data. Red fox visited more scent stations (XJ2 = 5.465; P = 0.0194) and more groups of stations (X/ = 5.199; P = 0.0226) on the area with few sage grouse compared to the area where grouse were fairly abundant (Table 1). We need to interpret these data with caution. First, we do not know exactly how scent station visitation rates relate to relative abundance of red fox on the 2 sites, but these data do suggest that red fox likely are more abundant on the site where grouse are rare. These data also do not indicate that red fox caused the decline of sage grouse. Surprisingly, we did not positively identify coyote tracks at any of the stations although it is possible that 1 or 2 of the stations could have been visited by coyotes. �183 Table 1. Visits by red fox to scent stations set in Moffat County, Colorado during 5 to 10 June 2001. Few grouse Grouse moderately abundant (Craig study area) (Maybell study area) 92 92 Number scent stations 78 87 Operable stations 19 21 Operable groups of stations 12 4 Stations visited by red fox 9 3 Groups of stations visited by red fox Stations visited by coyotes o 0 Raptor Surveys We established 10 l-mile long survey routes on roads on the Craig study area, 10 I-mile long survey routes on the Maybell study area, and 10 l-mile long survey routes in the Axial Basin. We counted raptors (hawks, eagles, magpies), at all distances, along these transects once per month from August 2001 through June 2002 to ascertain if the abundance of raptors differs among the 3 areas. I compared abundance of various raptors on transects with ANOVA (PROC GLM, SAS Inst. Inc. 1988). Abundance of none of the raptors varied among study areas (F2.276 = 0.15-2.82; P = 0.865-0.062, Table 2). In general, black-billed magpies were the most abundant raptor followed by American crows (Corvus brachyrhynchos; Table 2). Table 2. Average number of rap tors observed per month" on the Craig, Maybell, and Axial Basin study areas in Moffat County, Colorado from August 2001 through June 2002. Few grouse Grouse moderately abundant (Craig study area) Maybell study area) Axial Basin Golden eagle 0.7 2.2 1.6 Common raven 0.6 0.9 0.0 Black-billed magpie 7.8 7.8 6.4 Prairie falcon 0.0 0.0 0.0 Red-tailed hawk 0.3 0.8 0.5 Ferruginous hawk 0.0 0.1 0.0 Northern harrier 0.2 0.0 0.1 Bald eagle (Haliaeetus leucocephalus) 0.2 0.0 0.1 American crow 3.7 6.2 9.1 American kestrel (Falco sparverius) 0.2 0.1 0.2 Turkey vulture (Cathartes aura) 0.8 0.0 0.0 Other (unidentified) 0.2 0.0 0.0 "Ten I-mile long transects were driven once per month and all raptors observed from the vehicle were recorded from August 2001 through June 2002, except observations were not made during January and observations also were not made on the Maybell study area during February due to difficulty traversing roads. �184 Carnivore Food Habits We established 10 l-mile long survey routes on roads on the Craig study area, 10 I-mile long survey routes on roads on the Maybell study area, and 10 l-mile long survey routes on roads in Axial Basin (Appendix 1). We collected carnivore (primarily coyote and red fox) scats along these survey routes once per month from August 2001 through June 2002, except for January when travel was hindered by snow. We measured the diameters of scats with calipers and weighed them on an electronic balance. Green and Flinders (1981) reported that only 5% of red fox scats are 2:18 mm in maximum diameter and that only 4% of coyote scats were <16 mm in maximum diameter. Iextrapolated data from Weaver and Fritts (1979) and Danner and Dodd (1982) which indicated that only about 8 and 11% of coyote scats are <16 mm in maximum diameter. Thus, Iclassified scats <16 mm in diameter as red fox and those 2:18 mm in diameter as coyote. Scats that consisted of short segments were classified as bobcat (Murie 1954). We placed these scats in fine-mesh nylon bags and washed and dried them. We visually inspected the scats to determine if they contained sage grouse feathers or egg shells to help ascertain if red fox or coyotes preyed on sage grouse. When feathers were found, we ascertained if they were from sage grouse according to overall size of the feathers, presence and size of quills, presence of aftershafts, and general structure of the feather. Only birds in the order Galliformes, which includes sage grouse, have aftershafts (Elbroch and Marks 2001:235) on their feathers. A total of224 scats were collected and analyzed (Table 3). Based upon diameter and segmentation of scats, we ascertained that 26 scats were from red fox, 141 from coyotes, 4 from bobcats, and 53 scats could not be assigned to species. Although we collected scats on 10 miles of roads in each study area, the greatest numbers of scats were found on the Maybell and Axial Basin study areas, whereas the fewest scats were found on the Craig study area. Roads on the Craig study area are traveled more frequently by automobiles and are graded more frequently than roads on the other 2 study areas. These activities obliterate scats, thus relative abundance of scats likely is a poor indicator of relative abundance of carnivores on the 3 study areas. We found feathers in only 5 of 224 scats and none of the feathers appeared to be from sage grouse (Table 3). Table 3. Number carnivore scats and presence of feathers in scats found on transects on the Craig, MaybelL and Axial Basin study areas in Moffat County, Colorado from August 2001 through June 2002. Few grouse Grouse moderately abundant (Craig study area) Maybell study area) Axial Basin 18 101 105 Total scats 4 13 9 Red fox scats 110 Red fox scats with feathers 9 66 66 Coyote scats o 1 I Coyote scats with feathers o 1 3 Bobcat scats o 0 0 Bobcat scats with feathers 5 21 27 Unknown scats" Unknown scats with feathers o 1 0 "Based upon diameter and weight, we could not assign these scats to red fox, coyote, or bobcat. �185 Assistance with Determining which Predators are Responsible for Depredating Sage Grouse and their Nests: I provided Tony Apa and colleagues with information on how to determine which predators killed grouse or depredated their nests. SYNTHESIS OF RESULTS AND DISCUSSION Results of our scent station surveys suggest that red fox are more abundant on the Craig study area, where few sage grouse were present, than on the Maybell study area, where grouse were moderately abundant. The absence of sage grouse feathers in 141 scats, ascertained to be from coyotes, suggests that coyotes perhaps may not be substantial predators of sage grouse. We also did not find grouse feathers in 26 scats ascertained to be from red fox, and 4 scats ascertained to be from bobcats, however these small sample sizes do not allow for strong inferences regarding predation by red fox and bobcats on sage grouse. Even if feathers would have been found in coyote, red fox, or bobcat scats, it would still be difficult to ascertain the impact of either species on sage grouse without knowing densities of these 3 carnivores, densities of sage grouse, carnivore digestion and defecation rates, etc. However, I analyzed carnivore scats in a preliminary attempt to ascertain if either species might be frequently preying on sage grouse. Prior research has indicated that golden eagles and common ravens are the primary avian predators of sage grouse and their nests, respectively. Our raptor surveys indicated that both species were fairly common on most of our study areas. Initially, we expected that we might find more golden eagles and common ravens on the Craig study area, where sage grouse are scarce, if they are having an impact on sage grouse. However, predators are opportunists which often frequent areas of highest prey abundance. Due to these factors, and due to no significant differences in abundance of golden eagles and common raven among the 3 study areas, it is difficult to draw solid inferences from this study about the impact of these species on sage grouse. Ultimately, the best way to ascertain impacts of various predators on adult sage grouse, sage grouse chicks, and sage grouse nests is to monitor survival and causes of mortality for these life stages of sage grouse. ACKNOWLEDGMENTS I thank numerous individuals that assisted with this project. J. Comstock provided continuous encouragement and financial support for the study. G. Miller and the Colorado Division of Wildlife provided financial support while W. Andelt conducted the study. 1. Shivik and the National Wildlife Research Center provide salary support for D. Heffernan and D. Martin while they assisted with the study. T. Apa and R. Hoffman provided suggestions for the study. D. Heffernan and D. Martin assisted with scent station surveys. A. Martin and V. Dobrich conducted surveys of raptors and collected carnivore scats. C. Simpson analyzed carnivore scats to determine presence of feathers and egg shells. R. Ryder and R. Hoffman assisted with ascertaining if feathers in carnivore scats were from sage grouse. �186 LITERATURE CITED Allred, W. 1. 1942. Predation and the sage grouse. Wyoming Wild Life 71(1):3-4. Alstatt, A. 1988. Sage grouse production and mortality studies. Job performance report, Nevada Department of Wildlife, Reno, Nevada, USA. Autenrieth, R. E. 1981. Sage-grouse management in Idaho. Idaho Department of Fish and Game, Wildlife Bulletin 9, Boise, Idaho, USA. Danner, D. A., and N. Dodd. 1982. Comparison of coyote and gray fox scat diameters. Journal of Wildlife Management 46:240-24l. Elbroch, M., and E. Marks. 200l. Bird tracks & sign: a guide to North American species. Stackpole Books, Mechanicsburg, Pennsylvania, USA. Flinders, 1. T. 1999. Restoration of sage-grouse in Strawberry Valley, Utah, 1998-99. Utah Reclamation, Mitigation and Conservation Commission, Progress Report, Brigham Young University, Provo, Utah, USA. Gill, R. B. 1965. Distribution and abundance ofa population of sage grouse in North Park, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Green, J. S., and 1. T. Flinders. 1981. Diameter and pH comparisons of coyote and red fox scats. Journal of Wildlife Management 45:765-767. Hartzler, 1. E. 1974. Predation and the daily timing of sage grouse leks. The Auk 91 :532-536. Murie, O. 1. 1954. A field guide to animal tracks. The Peterson Field Guide Series. Houghton Mifflin Company, Boston, Massachusetts, USA. Presnall, C. C.; and A. Wood. 1953. Coyote predation on sage grouse. Journal of Mammalogy 34:127. SAS Institute Inc. 1988. SAS/STAT User's guide, release 6.03 edition, SAS Institute Inc., Cary, North Carolina, USA. Schroeder, M. A., and R. K. Baydack. 200l. Predation and the management of prairie grouse. Wildlife Society Bulletin 29:24-32. Weaver, 1. L., and S. W. Fritts. 1979. Comparison of coyote and wolf scat diameters. Journal of Wildlife Management 43:786-788. �187 Appendix 1. GPS coordinates for transects where carnivore scats were collected and raptors were observed (datum = WGS 84). Transect # ----------------------Scat ---------------------Start of transect End of transect X Y X Y CRAIG STUDY AREA - FRAGMENTED HABITAT 286321 4495138 286359 4496685 1 2 3 4 5 6 7 8 9 10 MAYBELL 11 12 13 14 15 16 17 18 19 20 286993 290602 283274 280846 277689 272894 277304 281065 275680 4504934 4498993 4497952 4499870 4503788 4505463 4496358 4493667 4490952 287551 289265 282630 279994 276290 271595 278798 281903 274742 AREA - UNFRAGMENTED 747333 747215 749179 745930 742374 739699 745369 743327 749357 248318 4506266 4499443 4499345 4500954 4504491 4505789 4496016 4492847 4491859 ------------------- Raptor ------------------Start of transect End of transect X y X Y 286359 286753 289265 282630 279994 276290 271595 278798 281903 274742 4496685 4503651 4499443 4499345 4500954 4504491 4505789 4496016 4492847 4491859 286417 286993 287842 281182 278429 274892 270687 279930 281766 273755 4498162 4504934 4499021 4499731 4500997 4505050 4504525 4495509 4491265 4492689 HABITAT 4497815 4502458 4508451 4508307 4510170 4510025 4514231 4521876 4520229 4517684 748923 745844 750735 744658 742575 738301 746090 744832 750726 249268 4497867 4501925 4508465 4507713 4511677 4510610 4515477 4522160 4519826 4516416 748923 745844 750735 744658 742575 738301 746090 744832 750726 249268 4497867 750446 4501925 744495 4508465 752004 4507713 744178 4511677 741688 4510610 737962 4515477? 4522160 746305 4519826 752031 4516416 249486 4498098 4501667 4509245 4508932 4511365 4511658 ? 4521754 4519026 4514902 4480100 4474342 4476843 4472106 4470006 4472271 4467748 4465355 4470302 4478294 253671 254317 257398 255153 249317 246720 252917 257542 260734 249580 4478589 4474661 4475313 4471305 4471575 4473285 4466698 4464349 4470308 4477016 253671 254317 257398 255153 249317 246720 252917 259268 260734 249580 4478589 4474661 4475313 4471305 4471575 4473285 4466698 4466465 4470308 4477016 4477122 4475609 4473907 4470304 4473119 4474390 4465499 4465355 4468956 4475569 AXIAL BASIN 21 22 23 24 25 26 27 28 29 30 253432 252975 257571 256457 249225 245513 254021 258706 262032 250505 253641 255142 257138 254046 249559 247862 251914 258706 260138 248906 �188 �189 JOB PROGRESS REPORT Smteof ~C~o~l~o~ra~d~o~ _ Mammals Research Program Work Package No. _ Multispecies Investigations T~kNo. _ Consulting Service for Mark-Recapture Analysis ~5~ Federal Aid Project No. W-153-R-2 Period Covered: July 1, 2002 - June 30, 2003 Author: G. C. White Personnel: C. Bishop, G. Miller, T. E. Remington, D. J. Freddy, T. M. Shenk, L. Stevens, J. Craig, R. Kahn, D. C. Bowden, F. Pusateri, J. Dennis, P. Schnurr, B. Andelt, A Seglund, D. Finley, A Linstrom, D. Walsh, K. Strohm. ABSTRACT Progress towards the objectives of this job include: 1. Consulting assistance to CDOW on harvest surveys, terrestrial inventory systems, and population modeling procedures was provided. Estimates of spring and fall turkey, spring snow goose, sharp-tailed and sage grouse, chukars, ptarmigan, Abert's squirrels, and general small game harvest were computed from survey data, and programs and harvest estimates provided to CDOW via email and CD ROM. Computer code written in SAS to compute these estimates and display results graphically was also provided. Computer code was also written in SAS to estimate the compliance rate of Colorado small game license holders with the Harvest Information Program. 2. The DEAMAN software package for the storage, summary, and analysis of big game population and harvest dam was revised further as a Windows 95/98INT/2000/ME/XP program. A User's Manual was provided to terrestrial biologists on CD and also distributed via the WWW at hnv_;!j_w..w..~!~!!L~_Q1Q~1g.1~_,~_g!!L::-_g~h!1~LQ~_':l:mg.Q . 3. Consultation with CDOW Terrestial Biologists in the use of DEAMAN and population modeling procedures continued. Numerous questions were answered via meetings with biologists, and via email. 4. A paper, coauthored with Marilet Zablan and Clait Braun, was published in the Journal of Wildlife Management on past efforts to estimate survival rates of sage grouse in North Park from CDOW banding records. The full citation is: Zablan, M. A, C. E. Braun, and G. C. White. 2003. Estimation of northern sage-grouse survival in North Park, Colorado. Journal of Wildlife Management 67:144-154. �190 5. A paper on the estimation of population size from correlated sampling unit estimates of the variable of interest was published in the Journal of Wildlife Management. The methodology developed in this paper is proposed for use in a joint Colorado/Utah survey of the colony area of whitetailed and Gunnison prairie dogs in western Colorado and eastern Utah. The full citation is: Bowden, D. c., G. C. White, A. B. Franklin, and J. L. Ganey. 2003. Estimating population size with correlated sampling unit estimates. Journal of Wildlife Management 67:1-10. 6. A paper on the use of lek counts to index prairie grouse populations was published in the Wildlife Society Bulletin: Walsh, D. P., G. C. White, T. E. Remington, and D. C. Bowden. 2003. Evaluation ofLek Count Index for Prairie Grouse Wildlife Society Bulletin. 32:56-68. 7. A paper on the estimation of sage grouse populations was submitted to the Journal of Wildlife Management: Walsh, D. P., G. C. White, T. E. Remington, and D. C. Bowden. 2003. Population Estimation of Greater Sage-Grouse. Journal of Wildlife Management. Submitted. 8. A paper on the effects of early season hunter numbers on elk movement was published in the Journal of Wildlife Management: Vieira, M. E. P., M. M. Conner, G. C. White, and D. J. Freddy. 2003. Relative effects of early season hunter numbers and opening date on elk movement in northwest Colorado. Journal of Wildlife Management. 67:717-728. 9. A paper on the impact of limited antlered harvest on mule deer sex and age ratios was submitted to the Wildlife Society Bulletin: Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2003. Effect oflimited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin. Submitted. 10. A paper on the survival and recruitment of peregrine falcons was published in the Journal of Wildlife Management: Craig, G. R., G. C. White, and 1. H. Enderson. 2004. Survival, recruitment, and rate of population change of the Colorado peregrine falcon population. Journal of Wildlife Management. In Press. 11. A research study to examine the impact of nutrition on the decline of mule deer fecundity during the last 20 years was continued. I have provided input on estimation of the number of deer on the feed sites, and developed an estimator of fawn survival rates based on radio-collared does and fall and spring fawn:doe ratios. 12. A graduate research project by Dan Walsh to evaluate utility oflek counts of Greater Sagegrouse in Middle Park was completed. Mark-resight methods are being used to estimate lek attendance and population size. The thesis citation is: Walsh, D. P. 2002. Population Estimation Techniques for Greater Sage-grouse. M. S. Thesis, Colorado State University, Fort Collins. USA. 158pp. 13. A graduate research project to develop a sage grouse population model, using North Park sage grouse data to develop parameter estimates, was initiated. The graduate student is Kristen Strohm. 14. An analysis to estimate the estimate the percent of eastern Colorado inhabited by black-tailed prairie dogs was completed and results provided to CDOW personnel involved with the effort. Estimates were computed in an Excel spreadsheet, and also verified through a program written in SAS to be sure that no errors in the calculations would be found when the spreadsheet is distributed to interested stakeholders. �191 15. Development of the design of a monitoring system for white-tailed prairie dogs in western Colorado and eastern Utah was started. This effort is in cooperation with Pam Schnurr, Bill Andelt, and Amy Seglund. 16. Development of the design of a monitoring system for swift fox in eastern Colorado was started. This effort is in cooperation with Francie Pusatari and Darby Finley. 17. Two new graduate students have been accepted for my supervision in the Department of Fishery and Wildlife Biology at Colorado State University. Chad Bishop will start a Ph.D. program in Fall, 2003, and Aaron Linstrom will start an M.S. program in Fall, 2003. �192 CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSES G. C. White P. N. OBJECTIVES Assess the status of Colorado swift fox population through an occupancy monitoring approach. SEGMENT OBJECTIVES 1. Develop a monitoring scheme to estimate the occupancy rate of swift fox in eastern Colorado. 2. Determine necessary sample sizes to obtain adequate statistical power to detect biologically important changes in the occupancy rate. RESULTS AND DISCUSSION Estimation of occupancy rate for Swift Foxes (Vulpes velox) in eastern Colorado was based on trapping data provided by Finley (1999). The data consist of 72 randomly selected trapping grids 4 miles by 5 miles in area, with 20 traps set at 1 mile intervals. METHODS The occupancy model of MacKenzie et al. (2002) was fit to the 72 trapping grids using Program MARK (White and Burnham 1999). The model fit included 8 detection probabilities (P) for the 8 trapping occasions plus the probability of occupancy (If/"). Detection probabilities were predicted with the month that a grid was trapped. Month was modeled with trigometric functions; sin(Monthx2w'12) and cos(Monthx2w'12), and powers of these functions. By using these sin and cosine functions, I can make the capture probability continuous across the December to January interval. Trend models were also used to model capture probabilities across occasions, forcing a linear trend on a logit scale in the capture probabilities. The percentage of each trapping grid comprised of short grass prairie was used as an additional covariate to predict both detection probability and probability of occupancy on a logit scale. Model selection was performed with AICc (Burnham and Anderson 1999). RESULTS Model selection results (Table l)suggest that month is an important predictor of the probability of detecting foxes on a grid. In addition, the top-ranked AICc includes a positive trend effect in the detection probabilities across the occasions, consistent with the results from the population estimation models. Model selection results also suggest that short grass prairie vegetation affects both the detection probability as well as the probability of occupancy. Detection probability is affected by the density of animals on the grid, and the percentage of short grass prairie on a trapping grid correlates (r = 0.375) with estimated population sizes provided in Table 5 of my September 23rd memo. �193 Table 1. Model selection results from fitting the occupancy estimation model of MacKenzie et al. (2002). AICc ~AICc AICcNum Weights Par. {p(T +coslvlonth+coslvlonth=Z) psi(SGPProp)} 318.6146 0.0000 031440 6 305.3223 {p(T +cosMonth+cosMonthI\2+SGPProp) psi(SGPProp) } 319.0596 0.4450 0.25168 7 303.3096 320.1094 l.4948 0.14890 6 306.8171 {p(coslvlonth+coslvlonth=Z) psi(SGPProp)} 32l.2674 2.6528 0.08345 5 310.3583 {p(cosMonth+cosMonthI\2+SGPProp) psi(SGPProp) } 32l.3341 2.7195 0.08071 6 308.0418 {p(T+coslvlonth+coslvlonth=Z) psi} 322.6843 4.0697 0.04109 5 31l.7753· 322.7973 4.1827 0.03884 5 31l.8882 {p(cosMonth) psi(SGPProp)} 323.6307 5.0161 0.02560 4 315.0337 {p(coslvlonth+coslvlonth=Z) psi} 325.5083 6.8937 0.01001 4 316.9113 {p(cosMonth) psi} 328.1180 9.5034 0.00272 3 321.7651 329.1845 10.5699 0.00159 4 320.5875 {ptt+coslvlonth+coslvlonth=Z) psi} 330.1385 11.5239 0.00099 11 303.7385 {p(.) psi} 340.3683 2l.7537 0.00001 2 336.1944 {p(sinMonth) psi} 342.5446 23.9300 0 3 336.1917 {p(t) psi} 343.2296 24.6150 0 9 322.3264 Model {p(T +cosMonth+cosMonthI\2+SGPProp) {p(cosMonth+cosMonthI\2+cosMonthI\3) {p(cosMonth+sinMonth) psi} psi} psi} Deviance Parameter values for the top-ranked AICc model (Table 2) demonstrate the increasing detection probability with occasion. In addition, the estimate of If/' of 0.821 suggests that 59.1 of the 72 grids trapped contained foxes, in contrast to the 51 grids that were observed to have foxes. �194 Table 2. Parameter estimates for the month of March from the top-ranked AICc occupancy model {P(T + cos(Month) + cos'(Month) psi(SGP Proportion)}, where month was set to March (3), and the short grass prairie habitat proportion for the trapping grid was set to 66.9%, the mean of the grids trapped. Parameter Estimate SE LCI VCI PI 0.611647 0.083074 0.442448 0.757627 P2 0.675704 0.066681 0.534363 0.790928 P3 0.733793 0.060627 0.600043 0.835107 P4 0.784792 0.061708 0.640538 0.881835 P5 0.828306 0.064248 0.665567 0.921227 P6 0.864541 0.065008 0.682552 0.949861 P7 0.894106 0.063204 0.695294 0.968985 P8 0.917831 0.059218 0.705628 0.981150 'V 0.820811 0.065876 0.655653 0.916806 The effect of month in the top-ranked AlCc model (Figure 1) is significant, and somewhat consistent with the results obtained with the population estimation models that included the variable month (reported in the memo of September 23). That is, the lowest detection probabilities are during summer. However, the occupancy model results suggest that September through March have the highest detection probabilities. The impact of the percentage of short grass prairie habitat on the estimates of occupancy is strong (Figure 2), with the probability of occupancy estimated at 34% for trapping grids with no short grass prairie habitat up to 93% for grids consisting of 100% short grass prairie. �195 0.9 0.8 >~ 0.7 :c 0.6 C'CS ..c .:::(':::" ./ .. 0 s... 0.5 ~------------------~. a. c: 0.4 -j------------------iIIIIl>~-.:: .-::--------------:::::-0: ..... :/:::::::::. 0 +0 (.) Q) 0.3 ·,·····:·······cosine quadratic --Trend+cosine quadratic c 0.2 0.1 Q) 0 1 2 3 4 5 7 6 8 9 10 11 12 Month Figure l. Effect of month in the 3 of the models of occupancy considered for detection probability: {P(cosMonth+cosMonthI\2+cosMonthI\3) psi}=cosine cubic, {P(cosMonth+cosMonthI\2) psi}=cosine quadratic, and {peT + cos(Month) + cos'(Month) psi }=Trend+cosine quadratic. The values shown for {peT + cos (Month) + cos/(Month) psi} are for PI, so estimates for P2 through P8 increase monotonically from this value. >. 1 0.8 g[ 0.9 ..•.·.w~ ..•. ·''''N' ''''.·~·.w~~'''''''''""''' ..•..• _,,",,,~ __,..•. ·.·.·.'.~ ... N" •.-- .•••.•""N'N"'N t===============================::::::;~~~~::::::~~========~ ~~,.~.·.W.·.·N"'N"""'--"""''''''''''''N.WN'W.·.,"",~",,,,,,,,,~~ ••• W.-- .••.••.••.••••-.~ ••''''( ~ § 0.7 +-----------------~----=---=---------------------------------~ o 0.6+---------~--~~~--------------------------------~ o 0.5 +----~----~P=------------------------------------------------~ ~ 0.4 +__.",_---=.--=''-------------------------------------------------------------'! ~ 0.3 +----------------------------------------------------------~ ~ 0.2 +-----------------------------------------------------------------~ 0.1 +-----------------------------------------------------------------~ e ~ a +----------r--------~----------~--------_r--------_,--------~ a 20 40 60 80 100 Short Grass Prairie (%) Figure 2. Effect of the percentage of the grid consisting of short grass prairie habitat on the probability of occupancy for the top-ranked Alec model {peT + cos/Month) + cos/(Month) psi(SGP Proportion) }. 120 �196 DISCUSSION The high detection probabilities during the September through March period suggests that swift fox monitoring should take place during this period. The increasing detection probability with trapping occasion also suggests that increasing the number of occasions will result in higher detection probabilities on each succeeding occasion. However, this trend effect is relatively minor. That is, the probability of not detecting foxes on a grid with 2 occasions trapped during March with the trend model estimates is (1 - 0.610297)0(1 0.6749937) = 0.126656. With the cosine quadratic model that does not include a trend across occasions, the probability of not detecting foxes is 0.085212. With 3 trapping occasions in March, the corresponding probabilities are 0.041164 and 0.024874, respectively. The strong relationship between the probability of occupancy and the short grass prairie habitat variable suggests that the design of an occupancy monitoring scheme should include this covariate. In particular, a ratio estimator can be developed that predicts the probability of occupancy based on the relationship in Figure 2. FURTHER WORK A reasonable estimate of the number of swift foxes in eastern Colorado can be obtained from the grid trapping scheme analyzed here. The population estimate for each trapping grid within a strata can be used to obtain a naive estimate of population density that will be biased high. However, through the use of radio collars, the proportion of time that marked animals spend on the trapping grid where they were initially captured can be used to correct these naive estimates. That is, the naive estimate multiplied by the proportion of radio locations on the trapping grid gives an unbiased estimate of density. Such a procedure has been used by White and Shenk (2001) to estimate population sizes for Preble's Meadow Jumping Mice, and details are provided in that article. Thus, to obtain an unbiased population estimate, radio-collared animals would be required. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical information-theoretic approach. Springer-Verlag, New York, New York, USA. 353 pp. Finley, D. J. 1999. Distribution of the swift fox (Vulpes velox) on the eastern plains of Colorado. M. S. Thesis, University of Northern Colorado, Greeley, USA. 96pp. MacKenzie, D. I., J. D. Nichols, G. B. Lachman, S. Droege, J. A. Royle, and C. A. Langtimm. 2002. Estimating site occupancy when detection probabilities are less than one. Ecology 83:2248-2255. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement: 120-138. White, G. C., and T. M. Shenk. 2001. Population estimation with radio-marked animals. Pages 329-350 in J. J. Millspaugh and J. M. Marzluff, editors. Design and Analysis of Wildlife Radiotelemetry Studies. Academic Press, San Diego, California, USA. �197 JOB PROGRESS REPORT Smreof ~C=0=10=r=a=do~ Work Package No.___,_7.=2-=-10-=-Task No. -"'I _ Division of Wildlife - Mammals Research Research support / Administrative Services _ _ Customer Services - Library Services Period Covered: July 1,2002 - June 30,2003 Author: Jacqueline A. Boss Personnel: Jacqueline A. Boss ABSTRACT During the Segment, the following were accomplished: 1,024 publications acquired by the Research Center Library for the use of Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public. These publications include books, interlibrary loan materials, periodicals, and newsletters. 1,941 items of information delivered to Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public, resulting from requests and literature searches. 585 items of information cataloged into the electronic and card catalogues, which including duplicates and additional volumes, expanded the Research Center Library inventory to 22,995 items. 1,131 items of information entered into the electronic catalogue for the maintenance of the circulation system of the Research Center Library. 1,316 items checked-out by Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public indicating satisfaction oflibrary services. 1,590 items of information delivered that are produced by the Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public. These items include: 1) publications - 951 [from time to time duplicated books donated to our Library are also given to CDOWemployees and are included in this number], 2) research articles by CDOW personnel- 344, and 3) CDOW federal aid reports - 295. �198 COLORADO DIV. OF WILDLIFE RESEARCH LIBRARY SERVICES Jacqueline A. Boss SEGMENT OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public. SUMMARY OF SERVICES Maintain Electronic and Card Catalogues of all Research Library Holdings 585 is the total number of items cataloged during this period. This includes not only new acquisitions, but also older materials from the Library collection being entered into the electronic catalog for the first time. Among the new acquisitions are Federal Aid: Job Progress Reports and manuscripts written by Colorado Div. of Wildlife Researchers and other employees. 1,131 is the total number of items of information added to the electronic circulation system during this period. This includes not only the above mentioned newly cataloged items, but also newly acquired serials, volumes, additional copies, and other items being assigned scanning numbers for the electronic circulation system for the first time. $178,625.90 is the "known value" of the 22,995 items in the Research Center Library collection as of June 30,2003. The project to determine the value of the library collection began in May 2000. As time permits, the value of books already in the collection is determined, and added to the already "known value." Each month's addition of values of older materials, plus the new materials, increases the value of the Library collection. Not included in the "known value" of the Library collection are all of the periodicals, older materials, and government documents, which continue to be a large part of the collection, thus the "known value" of the Library collection continues to grow month by month Some of the Publications Acquired in the Research Center Library Bailey, R. G. 2002. Ecoregion-based design for sustainability. New York: Springer-Verlag. Banks, A. J. 2002. A history of the avifauna and vegetation of the Mile High Wetlands. Rocky Mountain Bird Observatory. 17 leaves. Banks, A. J. 2002. A report of migrating birds at the Mile High Wetlands in 200l. Rocky Mountain Bird Observatory. 22 leaves. 222pp. Brighton, CO : Brighton, CO : Bartholomew, J. L. and J. C. Wilson, eds. 2002. Whirling disease: reviews and current topics. Bethesda, MD: Am. Fish. Soc. American Fisheries Society Symposium; 29. 247pp. Baumann, R. W. 2002. Monographs of the western North American naturalist. Young Univ. 115pp. Provo, UT : Brigham �199 Behnke, R. 1. 2002. Trout and salmon of North America. New York: Free Press. Illus. By 1. R. Tomelleri. 359pp. Belanger, D. O. and A. Kinnane. 2002. Managing American wildlife: a history of the International Association ofFish and Wildlife Agencies. Rockville, MD : Montrose Press. Centennial edition. 334pp. Boisvert, J. H. 2002. Ecology of Columbian sharp-tailed grouse associated with Conservation Reserve Program and reclaimed surface mine lands in northwestern Colorado. M.S. Thesis, Moscow, ID : Univ.ofIdaho. 184 leaves. Bristow, K. D. and R. A. Ockenfels. 2000. Effects of human activity and habitat conditions on Mearns' quail populations. Phoenix, AZ : Ariz. Game and Fish Dept. Technical guidance bulletin; no. 4. 27pp. Brouder, M. 1., D. D. Rogers, and L. D. Avenetti. 2000. Life history and ecology of the roundtail chub, Gila robusta, from two streams in the Verde River basin. Phoenix, AZ : Ariz. Game and Fish Dept. Technical guidance bulletin; no. 3. 16pp. Brown, J. K., R. W. Mutch, and C. W. Spoon, eds. 1995. Proceedings: Symposium on Fire in Wilderness and Park Management: Missoula, MT : March 30 - Aprill, 1993. Ogden, UT : U.S. Forest Servo Intermountain Research Station. General technical report; INT-320. 283pp. Brown, R. L. 1994. Effects of timber management practices on elk : a final report. Phoenix, AZ : Ariz. Game and Fish Dept. Technical report; no. 10 (revised). 70pp. Brown, R. L. 1994. Elk seasonal ranges and migrations in Arizona: a final report. Phoenix, AZ : Ariz. Game and Fish Dept. Technical report; no. 15. 122pp. Browne, D. 2002. Significant wildlife habitat maps: Adams, Arapahoe and Denver Counties, Colorado. [Fort Collins, CO] : Colo. Div. of Wild 1. u.p. Browne, D. 2002. Significant wildlife habitat maps: Boulder & Broomfield Counties, Colorado. [Fort Collins, CO] : Colo. Div. of Wild 1. u.p. Browne, D. 2002. Significant wildlife habitat maps: Clear Creek & Gilpin Counties, Colorado. [Fort Collins, CO] : Colo. Div. of Wild 1. u.p. Browne, D. 2002. Significant wildlife habitat maps: Douglas County, Colorado. Colo. Div. of Wild 1. u.p. Browne, D. 2002. Significant wildlife habitat maps: Elbert County, Colorado. Colo. Div. of Wild 1. u.p. [Fort Collins, CO] : [Fort Collins, CO] : Browne, D. 2002. Significant wildlife habitat maps: Jefferson County, Colorado. Colo. Div. of Wild 1. u.p. [Fort Collins, CO] : Browne, D. 2002. Significant wildlife habitat maps: Larimer County, Colorado. [Fort Collins, CO] : Colo. Div. of Wild 1. u.p. �200 Browne, D. 2002. Significant wildlife habitat maps: Logan County, Colorado. [Fort Collins, CO] : Colo. Div. ofWildl. u.p. Browne, D. 2002. Significant wildlife habitat maps: Morgan County, Colorado. [Fort Collins, CO] : Colo. Div. ofWildl. u.p. Browne, D. 2002. Significant wildlife habitat maps: Park County, Colorado. [Fort Collins, CO] : Colo. Div. ofWildl. u.p. Browne, D. 2002. Significant wildlife habitat maps: Phillips County, Colorado. [Fort Collins, CO] : Colo. Div. ofWildl. u.p. Browne, D. 2002. Significant wildlife habitat maps: Sedgwick County, Colorado. [Fort Collins, CO] : Colo. Div. ofWildl. u.p. Browne, D. 2002. Significant wildlife habitat maps: Washington County, Colorado. [Fort Collins, CO] : Colo. Div. ofWildl. u.p. Browne, D. 2002. Significant wildlife habitat maps: Weld County, Colorado. [Fort Collins, CO] : Colo. Div. ofWildl. u.p. Browne, D. 2002. Significant wildlife habitat maps: Yuma County, Colorado. [Fort Collins, CO] : Colo. Div. ofWildl. u.p. Byelich, B. R. and D. A. Gasseling. [2002]. Plantings for wild turkeys: guidelines for establishment and management in the Black Hills, eastern Montana, eastern Wyoming, western Nebraska, and the Colorado Front Range. S.l.: US. Natural Resources Conservation Service. 8pp. Chafin, D. T. 2002. Evaluation of trends in pH in the Yampa River, northwestern Colorado, 1950-2000. 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In: The Wildlife Society: 9th annual conference: September 24-28,2002: Bismarck, North Dakota. Bethesda, MD : The Wildl Soc. pp.63-64 (abstract) Bain, M. R and T. M. Shenk. 2002. Nests of Preble's meadow jumping mouse (Zapus hudson ius preblei) in Douglas County, Colorado. Southwest. Nat. 47(4):630-633 Baker, D. L., M. A. Wild, M. M. Conner, H. B. Ravivarapu, R L. Dunn, and T. M. Nett. 2002. Effects ofGnRH agonist (leuprolide) on reproduction and behaviour in female wapiti (Cervus elaphus nelsoni). Reprod. Suppl. 60: 155-167 Bergersen, E. P. and P. J. Martinez. 2003. The use of a pattern recognition model to assess fish habitat in two Colorado reservoirs. Lake Reserv. Manage. 19(1):55-63 Bissell, S. J. 2002. Book review: The evolution of national wildlife law by M. J. Bean and M. J. Rowland. 1997. Westport, CT : Praeger Publishers. 3rdedition. 586pp. Hum. Dim. Wildl. 7(2): 145-146 Braun, C. E. 2001. Conservation and management of lesser prairie-chickens: the need for a coordinated approach. Prairie Grouse Technical Council: Meeting; 24:26-27 (abstract) �210 Braun, C. E. 2002. Federal land management and prairie grouse. In: The Wildlife Society: 9th annual conference: September 24-28,2002: Bismarck, North Dakota. Bethesda, MD : The Wildl. Soc. p.80 (abstract) Braun, C. E., R. J. Delpiccolo, R. W. Hoffman, and T. E. Remington. 2003. First specimen records for ruffed grouse in Colorado. West. N. Am. Natural. 63(1): 105-107 Braun, C. E. and K. Martin. 2001. Unusual summer plumage of white-tailed ptarmigan. 113(4):373-377 Wilson Bull. Braun, C. E., O. O. Oedekoven, and C. L. Aldridge. 2002. Oil and gas development in western North America: effects on sagebrush steppe avifauna. In: Transactions of the sixty-seventh North American Wildlife and Natural Resource Conference 67:337-349 Colorado Div. of Wildlife. 2002. 2002 hunting guide: a special edition of Colorado Outdoors. Denver, CO : Colo. Div. of Wildlife. Hunting guide to Colorado 2002; no. 11. 40pp Dreitz, V. J., N. T. Hobbs, M. W. Miller, K. P. Burnham, and M. M. Conner. 2002. Effects of chronic wasting disease on growth rates of Colorado mule deer populations. In: The Wildlife Society: 9th annual conference: September 24-28,2002: Bismarck, North Dakota. Bethesda, MD : The Wildl. Soc. pp.l 04-1 05 (abstract) Fischer, J., V. Nettles, R. Gerhold, E. S. Williams, M. W. Miller, and L. Creekmore. 2002. National chronic wasting disease surveillance: accomplishments and needs. In: Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7, 2002. Fort Collins, CO : Colo. Div. of Wild 1. Addendum (abstract) Gammonley, J. H. and M. K. Laubhan. 2002. Patterns of food abundance for breeding waterbirds in the San Luis Valley of Colorado. Wetlands 22(3):499-508 Gill, R. Bruce. 2002. Build an experience and they will come: managing the biology of wildlife viewing for benefits to people and wildlife. In: Wildlife viewing: a management handbook by M. J. Manfredo, ed. Corvallis, OR: Oreg. State Univ. Press. pp.218-253 Gould, D. H., J. L. Voss, M. W. Miller, A. M. Bachand, B. A Cummings, and A A Frank. 2003. Survey of cattle in northeast Colorado for evidence of chronic wasting disease : geographical and high-risk targeted sample. J. Vet. Diagn. Invest. 15(3):274-277 Guiming, W., N. T. Hobbs, H. Galbraith, and K. M. Giesen. 2002. Signatures of large-scale and local climates on the demography of white-tailed ptarmigan in Rocky Mountain National Park, Colorado, USA Int. J. Biometeorol. 46(4):197-201 Guiming, W., N. T. Hobbs, K. M. Giesen, H. Galbraith, D. S. Ojima, and C. E. Braun. 2002. Relationships between climate and population dynamics of white-tailed ptarmigan Lagopus leucurus in Rocky Mountain National Park. Climate Research 23(1):81-87 Hagen, C. A, B. E. Jamison, K. M. Giesen, and T. Z. Riley. 2002. Guidelines for management oflesser prairie chicken populations and their habitats. In: The Wildlife Society: 9th annual conference: September 24-28, 2002 : Bismarck, North Dakota. Bethesda, MD : The Wildl. Soc. p.129 (abstract) �211 Hoover, E. A., C. J. Sigurdson, C. K. Mathiason, M. W. Miller, M. R. Perrott, G. A. Eliason, T. R. Spraker, and J. C. Bartz. 2002. Experimental CWD infection and bioassay in the ferret. In: Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7, 2002. Fort Collins, CO : Colo. Div. of Wild I. p.13 (ebstract) Kahn, R. H., coordinator. 2002. Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7, 2002. Fort Collins, CO : Colo. Div. of Wild I. 31pp Kahn, R. H, 2002. Policies and strategies for managing chronic wasting disease in Colorado. In: Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7,2002. Fort Collins, CO : Colo. Div. of Wild I. p.18 (zbstract) McNeil, H. J., P. E. Shewen, R. Y. C. Lo, J. A. Conlon, and M. W. Miller. 2002. Mannheimia haemolytica serotype 1 and Pasteurella trehalosi serotype 10 culture supernatants contain fibrinogen-binding proteins. Vet. Immunol. Immunop. 90(1-2): 107-110 Miller, M. W. 2002. Chronic wasting disease surveillance and monitoring strategies: an overview. In: Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7, 2002. Fort Collins, CO : Colo. Div. of Wild I. p.6 (ebstract) Miller, M. W. 2002. Distribution and occurrence of chronic wasting disease in Colorado. In: Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7,2002. Fort Collins, CO: Colo. Div. of Wildl. pp.6-7 (ebstract) Miller, M. W. 2002. Temporal and spatial dynamics of chronic wasting disease epidemics. In: Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7,2002. Fort Collins, CO : Colo. Div. of Wild I. p.9 (ebstract) Miller, M. W. and E. S. Williams. 2002. Detection of PrPCWD in mule deer by immunohistochemistry lymphoid tissues. Vet. Record. 151(20):610-612 of Navo, K. W. and J. A. Gore. 200l. Distribution of the big free-tailed bat (Nyctinomops macrotis) in Colorado. Southwest. Nat. 46(3):370-376 Nehring, R. B., K. G. Thompson, K. A. Taurman, and D. L. Shuler. 2002. Laboratory studies indicating that living brown trout Salmo trutta expel viable Myxobolus cerebralis myxospores. Am. Fish. Soc. Symp; 29: 125-134 Parmenter, R. P., T. L. Yates, D. R. Anderson, K. P. Burnham, J. L. Dunnum, A. B. Franklin, M. T. Friggens, B. C. Lubow, M. W. Miller, G. S. Olson, C. A. Parmenter, J. Pollard, E. Rexstad, T. M. Shenk, T. R. Stanley, and G. C. White. 2003. Small-mammal density estimation: a field comparison of grid-based vs. web-based density estimators. Ecolo. Mono. 73(1): 1-26 Race, R. E., A. Raines, T. G. M. Baron, M. W. Miller, A. Jenny, and E. S. Williams. 2002. Comparison of abnormal prion protein glycoform patterns from transmissible spongiform encephalopathy agent-infected deer, elk, sheep, and cattle. J. Virol. 76(23): 12365-12368 Rosenstock, S. S., D. R. Anderson, K. M. Giesen, T. Leukering, and M. F. Carter. 2002. Landbird counting techniques: current practices and an alternative. Auk 119(1):46-53 �212 Schisler, G. 1. 2002. Influences of habitat, water quality, and other physical parameters on the severity of whirling disease : a summary of current knowledge and implications to salmonid populations in Colorado. Fort Collins, CO : Colo. Div. ofWildl. Aquat. Wildl. Resear. Sect. 14pp. Schisler, G. 1. and E. P. Bergersen. 2002. Evaluation of risk of high elevation Colorado waters to the establishment ofMyxobolus cerebralis. Am. Fish. Soc. Symp; 29:33-41 Schroeder, M. A, K. M. Giesen, and J. W. Connelly. 2002. Changes in distribution, abundance, and status of prairie grouse. In: The Wildlife Society: 9th annual conference: September 24-28,2002 : Bismarck, North Dakota. Bethesda, MD : The Wildl. Soc. p.219 (abstract) Sigurdson, C. 1., C. Barillas-Mury, M. W. Miller, B. Oesch, L. 1. M. van Keulen, 1. P. M. Langeveld, and E. A Hoover. 2002. PrPCWD lymphoid cell targets in early and advanced chronic wasting disease of mule deer. 1. Gen. Viol. 83(10):2617-2628 Spraker, T. R, R R Zink, B. A Cummings, C. J. Sigurdson, M. W. Miller, and K. I. O'Rouke. 2002. Distribution of protease-resistant prion protein and spongiform encephalopathy in free-ranging mule deer (Odocoileus hemionus) with chronic wasting disease. Vet. Pathol. 39(5):546-556 Spraker, T. R, R R Zink, B. A Cummings, M. A Wild, M. W. Miller, and K. I. O'Rouke. 2002. Comparison of histological lesions and immunohistochemical staining of proteinase-resistant prion protein in a naturally occurring spongiform encephalopathy of free-ranging mule deer (Odocoileus hemionus) with those of chronic wasting disease of captive mule deer. Vet. Path. 39:110-119 Spraker, T. R, R R Zink, B. A Cummings, M. A Wild, C. J. Sigurdson, M. W. Miller, and K. I. O'Rouke. 2002. Comparison oflesions in free-ranging mule deer with naturally-occurring spongiform encephalopathy with those of chronic wasting disease in captive mule deer and distribution patterns of Prpres in brain and palatine tonsil of non-clinical mule deer with chronic wasting disease. In: Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7, 2002. Fort Collins, CO: Colo. Div. ofWildl. p.12 (abstract) Spraker, T. R, K. I. O'Rouke, A Balachandran, R R Zink, B. A. Cummings; M. W. Miller, and B. E. Powers. 2002. Validation of monoclonal antibody F99/97.6.1 for immunohistochemical staining of brain and tonsil in mule deer (Odocoileus hemionus) with chronic wasting disease. 1. Vet. Diagn. Invest. 14(3):3-7 Wild, M. A., T. R Spraker, C. 1. Sigurdson, K. I. O'Rourke and M. W. Miller. 2002. Preclinical diagnosis of chronic wasting disease in captive mule deer (Odocoileus hemionus) and whitetailed deer (Odocoileus virginianus) using tonsillar biopsy. 1. Gen. Viral. 83(10):2629-2634 Williams, E. S. and M. W. Miller. 2002. Chronic wasting disease in deer and elk in North America. Revue Scientifique et Technique de l'Office International des Epizooties 21(2):305-316 Williams, E. S. and M. W. Miller. 2003. Transmissible spongiform encephalopathies in non-domestic animals: origin, transmission and risk factors. Revue Scientifique et Technique de l'Office International des Epizooties 22(1):145-156 Williams, E. S., M. W. Miller, T. J. Kreeger, R H. Kahn, and E. T. Thorne. 2002. Chronic wasting disease of deer and elk: a review with recommendations for management. 1. Wildl. Manage. 66(3):551-563 �213 Williams, E. S., M. W. Miller, and E. T. Thorne. 2002. Chronic wasting disease: implications and challenges for wildlife managers. In: Transactions of the sixty-seventh North American Wildlife and Natural Resource Conference 67:87-103 Wolfe, L. L. 2002. Detecting chronic wasting disease infections in live animals. In: Chronic Wasting Disease Symposium: Denver, Colorado: August 6 & 7, 2002. Fort Collins, CO : Colo. Div. of Wildl. p.11 (sbstract) Wolfe, L. L., M. M. Conner, T. H. Baker, V. J. Dreitz, K. P. Burnham, E. S. Williams, N. T. Hobbs, and M. W. Miller. 2002. Evaluation of antemortem sampling to estimate chronic wasting disease prevalence in free-ranging mule deer. J. Wildl. Manage. 66(3):564-573 Zablan, M. A., C. E. Braun, and G. C. White. 2003. Estimation of greater sage-grouse survival in North Park, Colorado. J. Wildl. Manage. 67(1):144-154 Prepared by -.,.Jacqueline A. Boss Librarian _ � https://cpw.cvlcollections.org/files/original/2444d331fda046677787c48c6cf3275a.pdf 38ae254adc7acf83f5042a729c2ed2f0 PDF Text Text MAMMALS - JULY 2004 ��WILDLIFE RESEARCH REPORT JULY 2003 – JUNE 2004 MAMMALS PROGRAM COLORADO DIVISION OF WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Job Progress Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author. �STATE OF COLORADO Bill Owens, Governor DEPARTMENT OF NATURAL RESOURCES Russell George, Executive Director WILDLIFE COMMISSION Rick Enstrom, Chair ……………………………………………………………………….…..… Denver Phillip J. James, Vice Chair ………………………………….…………...………….….....…Fort Collins Claire O’Neal, Secretary ……………………………………...…………….……………..……. Holyoke Bernard Black, Jr…………………………………………………..............................................…Denver Tom Burke………………………………………………………………….………….….Grand Junction Jeffrey A. Crawford …………………………………………………………………..….………. Denver Brad Phelps ……………………………………………………..…………….………..……..…Gunnison Robert T. Shoemaker…………………………………………………………….……….…….Canon City Ken Torres ………………………………………………………………………………...........…Weston Don Ament, Dept. of Ag, Ex-officio…………………………………………………….….…..…Denver Russell George, Executive Director, Ex-officio……………………………………………………Denver DIVISION OF WILDLIFE LEADERSHIP TEAM Bruce McCloskey, Director Steve Cassin, Planning/Budgeting Jeff Ver Steeg, Wildlife Programs Scott Hoover, Acting Public Services Marilyn Salazar, Support Services MAMMALS RESEARCH STAFF Gary C. Miller, Mammals Research Leader Dan L. Baker, Wildlife Researcher Eric Bergman, Wildlife Researcher Chad Bishop, Wildlife Researcher Tracy Davis, Technician, FWR Facility Supervisor David J. Freddy, Wildlife Researcher Ken Logan, Wildlife Researcher Michael W. Miller, Wildlife Researcher Veterinarian Tanya Shenk, Wildlife Researcher Lisa Wolfe, Staff Veterinarian Wildlife Health Lab Laurie Baeten, Supervisor, Veterinarian Kate Larsen, Technician Karen Griffin, Technician Jennifer Hall, Technician Ivy LeVan, Technician Jackie Boss, Librarian Margie Michaels, Administrative Assistant ii �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 TABLE OF CONTENTS MAMMALS RESEARCH PROGRESS REPORTS PREBLE’S MEADOW JUMPING MOUSE CONSERVATION WP 0662 EFFECTS OF RESOURCE ADDITION ON PREBLE’S MEADOW JUMPING MOUSE (Zapus hudsonius preblei) MOVEMENT PATTERNS by T. Shenk…………..1 LYNX CONSERVATION WP 0670 POST-RELEASE MONITORING OF LYNX REINTRODUCED TO COLORADO by T. Shenk…………………………….………………………….………………..……..5 WP 0670 ECOLOGY OF SNOWSHOE HARES IN COLORADO by J. Zahratkal………………15 BLACK-FOOTED FERRET WP 0880 DISEASE MONITORING AND MANAGEMENT by L. Wolfe.……….……………..17 DEER CONSERVATION WP 3001 EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES by C. Bishop…………………….21 ELK CONSERVATION WP 3002 TECHNICAL SUPPORT FOR ELK AND VEGETATION MANAGEMENT ENIRONMENTAL IMPACT STATEMENT FOR ROCKY MOUNTAIN NATIONAL PARK by D. Baker…..……………………………….…………………...45 WP 3002 ESTIMATING CALF AND ADULT SURVIVAL RATES AND PREGNANCY RATES OF GUNNISON BASIN ELK by D. Freddy……………….…57 PUMA CONSERVATION WP 3003 COLORADO PUMA RESEARCH AND MANAGEMENT PROGRAM by K. Logan……………………………………………………………..……………….61 OTHER UNGULATES CONSERVATION WP 3004 POTENTIAL RESEARCH PROJECT ASSESSMENT by E. Bergman…………...….89 iii �WILDLIFE DISEASES WP 3740 CHRONIC WASTING DISEASE IN MULE DEER – RESEARCH AND DEVELOPMENT by M. Miller and L. Wolfe.………………………………….…..…103 WP 3740 WILDLIFE DISEASE SURVEILLANCE TECHNICAL AND LABORATORY SUPPORT by L. Baeten……………………………….…………………………….....113 WP 3740 PILOT EVALUATION OF GPS TECHNOLOGY IN CHRONIC WASTING DISEASE PREVALENCE AND MANAGEMENT AT ARTIFICIAL FEEDING SITES IN URBAN AREAS by E. Bergman, M. Miller, and L. Wolfe…………...……119 WP 3740 VETERINARY SERVICES – MEDICAL SUPPORT by L. L. Wolfe……………..…123 WP 3740 ANIMAL AND PEN SUPPORT FACILITIES FOR MAMMALS RESEARCH by T. Davis……………………………………..……………………………….………139 MULTISPECIES INVESTIGATIONS WP 3001 CONSULTING SERVICES FOR JOB MARK-RECAPTURE ANALYSIS by G. White…………………………………..………………………………….…..….151 RESEARCH SUPPORT / ADMINISTRATIVE SERVICES WP 7210 LIBRARY SERVICES by J. Boss…………………..………………………………….163 iv �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Colorado Task No. 2 : Cost Center 3430 : Mammals Research : Preble’s Meadow Jumping Mouse Conservation Effects of Resource Addition on Preble’s Meadow Jumping Mouse (Zapus hudsonius : preblei) Movement Patterns 0662 Federal Aid Project: N/A : Period Covered: July 1, 2003 - June 30, 2004 Author: Anne M. Trainor. Personnel: T. M. Shenk, K. R. Wilson, G. C. White All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A thesis, entitled ‘Influence of resource supplementation on movements of Preble’s meadow jumping mouse (Zapus hudsonius preblei) and habitat use characteristics,’ was completed and submitted to Colorado State University in partial fulfillment of a Master of Science degree. The thesis is available from The Colorado Division of Wildlife Library or the Colorado State University Library. Included in this report is an abstract of the thesis. 1 �JOB PROGRESS REPORT INFLUENCE OF RESOURCE SUPPLEMENTATION ON MOVEMENTS OF PREBLE’S MEADOW JUMPING MOUSE (Zapus hudsonius preblei) AND HABITAT USE CHARACTERISTICS Anne M. Trainor ABSTRACT Riparian wetlands are complex ecosystems containing great species diversity that may easily be affected by anthropogenic disturbances. Preble’s meadow jumping mouse (Zapus hudsonius preblei) is a federally threatened species dependent upon riparian wetlands. It has been the subject of habitat management and conservation efforts involving restoration and mitigation projects along the eastern Front Range of Colorado and southeastern Wyoming. Although habitat improvements for Z. h. preblei are designed for multiple spatial scales, most knowledge about the species’ habitat requirements has been described at a broad landscape scale. In addition, few projects have directly evaluated the mouse’s response to restoration and mitigation projects. The first objective of this study was to determine how supplementation using artificial resources influences the spatial movement patterns of a Z. h. preblei population. Previous studies described Z. h. preblei use areas through live trapping. This study more precisely evaluated Z. h. preblei spatial use by applying radio telemetry within a riparian ecosystem. I conducted an experiment by constructing treatment plots of artificial resources (food and cover) in areas with no previous detections of Z. h. preblei during 3 prior years (1998-2000) of intensive monitoring. Z. h. preblei were radio collared and then located hourly during nightly activity periods before and after the addition of food and cover. The second objective of this study was to improve understanding about micro-habitat characteristics that Z. h. preblei use. During the resource supplementation experiment, Z. h. preblei response to treatment plots varied by year with only 1 of 13 radio-tagged individuals using supplemental resources during 2002 and 6 of 8 in 2003. The lower use in 2002 may have been due to drought conditions, which decreased available herbaceous cover and thus protection from predators. While treatment plot use increased in 2003, the overall use was relatively low when compared to natural, high-use areas. The mean proportion of treatment plot use in 2003 was = 5.9% (SE =1.4%, range = 0% to 12%). Limited use of treatment plots may have been due to site fidelity and minimal exploratory movements by Z. h. preblei or to elevated predation risk. A comparison of micro-habitat characteristics from random samples of high-use and no-use areas indicated that areas used intensely by Z. h. preblei were closer to the center of the creek bed and positively associated with shrub, grass, and woody debris cover. Distance to center of the creek bed, percent shrub cover, and grass cover had the greatest relative importance of the habitat variables modeled in describing high-use areas. High-use areas contained three times the percent of grass cover as forb cover. There was a greater proportion of wetland shrub and grass cover in high-use versus no-use cells. However, proportion of cover type (shrub or grass) did not vary greatly between high-use and no use cells. Within riparian wetlands, the identification of key micro-habitat components that are intensively used by Z. h. preblei could improve conservation and management programs. In addition, results from the resource supplementation experiment suggest that TP pˆ mitigation and restoration may not ensure use of areas by threatened and endangered species. Therefore, understanding how species respond to changes in 2 �areas where they currently live will require development of more efficient and effective mitigation projects, and monitoring by conservation biologists and wildlife managers will be essential. Prepared by _______________________ Anne M. Trainor, Colorado State University 3 �4 �Colorado Division of Wildlife Wildlife Research Report July 2003- June 2004 JOB PROGRESS REPORT State of Colorado Project No. Work Package No. 0670 Task No. 1 : : : : Federal Aid Project: : N/A Cost Center 3430 Mammals Research Lynx Conservation Post-Release Monitoring of Lynx Reintroduced to Colorado Period Covered: July 1, 2003 - June 30, 2004 Author: Tanya M. Shenk Personnel: R. Dickman, L. Gepfert, R. Kahn, A. Keith, G. Merrill, G. Miller, C. Wagner, S. Wait, S. Waters, L. Wolfe, D. Younkin All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to establish a viable population of lynx (Lynx canadensis) in Colorado, a reintroduction effort was initiated in 1999. The reintroduction effort was augmented with the release of 37 additional animals in April 2004, bringing the total to 166 lynx reintroduced to southwestern Colorado. Each lynx is released with dual satellite and VHF radio transmitters to allow intensive monitoring of animals after release. Through documentation of lynx mortalities and causes of death, human-caused mortality factors such as gunshot and vehicle collision are currently the highest source of mortality for reintroduced lynx. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns. Most lynx remain in the southwestern quarter of Colorado. Reproduction was first documented during the 2003 reproduction season. A second successful breeding season was documented in 2004 with 11 dens and 30 kittens found as of June 30, 2004. Snow-tracking results indicate the primary winter prey species are snowshoe hare (Lepus americanus) and red squirrel (Tamiasciurus hudsonicus), with other mammals and birds forming a minor part of the winter diet. Site-scale habitat data collected from snowtracking efforts indicate Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) are the most common forest stands used by lynx in southwestern Colorado. From results to date it can be concluded that CDOW has developed release protocols that ensure high initial post-release survival, and on an individual level lynx have demonstrated they can survive long-term in areas of Colorado. It has also been documented that reintroduced lynx could exhibit site fidelity, engage in breeding behavior and produce kittens. What is yet to be demonstrated is whether Colorado conditions can support the recruitment necessary to offset annual mortality for a population to sustain itself. Monitoring of reintroduced lynx will continue in an effort to document such viability. 5 �JOB PROGRESS REPORT POST-RELEASE MONITORING OF LYNX (Lynx canadensis) REINTRODUCED TO COLORADO Tanya M. Shenk SEGMENT OBJECTIVES The initial post-release monitoring of reintroduced lynx will emphasize 5 primary objectives: 1. Assess and modify release protocols to ensure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival of lynx reintroduced to Colorado. 5. Estimate reproduction of lynx reintroduced to Colorado. Three additional objectives will be emphasized after lynx display site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of lynx conservation strategies in the southern Rocky Mountains. INTRODUCTION The Canada lynx occurs throughout the boreal forests of northern North America. Colorado represents the southern-most historical distribution of lynx, where the species occupied the higher elevation, montane forests in the state. Little was known about the population dynamics or habitat use of this species in their southern distribution. Lynx were extirpated or reduced to a few animals in the state by the late 1970’s. Given the isolation of Colorado to the nearest northern populations, the Colorado Division of Wildlife (CDOW) considered reintroduction as the only option to attempt to reestablish the species in the state. A reintroduction effort was begun in 1999. To date, 166 wild-caught lynx from Alaska and Canada have been released in southwestern Colorado. The goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of lynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing if the reintroduction effort is progressing towards success. There are seven critical criteria for achieving a viable population: (1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, (2) long-term survival of lynx in Colorado, (3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, (4) reintroduced lynx must breed, (5) breeding must lead to reproduction of surviving kittens (6) lynx born in Colorado must reach breeding age and reproduce successfully, and (7) recruitment must be equal to or greater than mortality. The post-release monitoring program for the reintroduced lynx has 2 primary goals. The first goal is to determine how many lynx remain in Colorado and their locations relative to each other. Given this information and knowing the sex of each individual, we can assess whether these lynx can form a breeding core from which a viable population might be established. From these data we can also describe general movement patterns and habitats used. The second primary goal of the monitoring program is to 6 �estimate survival of the reintroduced lynx and, where possible, determine cause of mortality of reintroduced lynx. Such information will help in assessing and modifying release protocols and management of lynx once they have been released. Additional goals of the post-release monitoring program for lynx reintroduced to the southern Rocky Mountains include refining descriptions of habitat use and movement patterns, determining hunting habits, and obtaining information on reproduction. When the lynx establish home ranges that encompass their preferred habitat, more emphasis will be placed on refining descriptions of movement patterns and habitat use. Lynx is listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.)(U. S. Fish and Wildlife Service 2000). As a listed species, an additional objective of the post-release monitoring program is to develop conservation strategies relevant to lynx in Colorado. Therefore, information specific to the ecology of the lynx in its southern Rocky Mountain range such as habitats used, movement patterns, mortality factors, survival, and reproduction in Colorado is needed. METHODS Reintroduction Effort All 2004 lynx releases were conducted under the protocols found to maximize survival (see Shenk 2001). Estimated age, sex and body condition were ascertained and recorded for each lynx prior to release (see Wild 1999). Specific release sites were selected based on land ownership and accessibility during times of release. Lynx were transported from the holding facility to the release site in individual cages. Release site location was recorded in Universal Transverse Mercator (UTM) coordinates and identification of all lynx released at the same location, on the same day, was recorded. Behavior of the lynx on release and movement away from the release site were documented. Movement Patterns All lynx released in spring 2004 were fitted with SirtrackTM dual satellite/VHF radio-collars. These collars have a mortality indicator switch that operated on both the satellite and VHF mode. The satellite component of each collar was programmed to be active for 12 hours per week. The 12-hour active periods were staggered throughout the week. Signals from the collars allowed for locations of the animals to be made via Argos, NASA, and NOAA satellites. The location information was processed by ServiceArgos and distributed to the CDOW through e-mail messages. To determine general movement patterns of reintroduced lynx, regular locations of released lynx were collected through a combination of aerial, satellite and ground radio-tracking. Locations and general habitat descriptions at each location were recorded and mapped. Survival and Mortality Factors When a mortality signal (75 ppm vs. 50 ppm for the Telonics™ VHF transmitters, 20 bpm vs. 40 bpm for the Sirtrack™ VHF transmitters, 0 activity for Sirtrack™ PTT) was heard during either satellite, aerial or ground surveys, the location (UTM coordinates) was recorded. Ground crews then located and retrieved the carcass as soon as possible. The immediate area was searched for evidence of other predators and the carcass photographed in place before removal. Additionally, the mortality site was described and habitat associations and exact location were recorded. Any scat found near the dead lynx that appeared to be from the lynx was collected. All carcasses were transported immediately to the Colorado State University Veterinary Hospital for a post mortem exam to 1) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, and 3) archive samples for future reference (research or 7 �forensic). The gross necropsy and histology were performed by, or under the lead and direct supervision of a board certified veterinary pathologist. At least one research personnel from the CDOW involved with the lynx program was also present. The protocol followed standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing (see Shenk 1999 for details). Some additional data/samples were routinely collected for research, forensics, and archiving. Other data/samples were collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). The CDOW retained all samples and carcass remains with the exception of tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, and other diagnostic samples. Reproduction Females were monitored for proximity to males during breeding season and for site fidelity to a given area during the denning period of May and June. Each female that exhibited stationary movement patterns in May or June 2004 was observed to look for accompanying kittens. Kittens found at den sites were weighed, sexed and photographed. Each kitten was uniquely marked by inserting a sterile passive integrated transponder (PIT, Biomark, Inc., Boise, Idaho, USA) tag subcutaneously between the shoulder blades. Time spent at the den was minimized to ensure the least amount of disturbance to the female and the kittens. Weight, PIT-tag number, sex and any distinguishing characteristics of each kitten was also recorded. Den site location was recorded as UTM coordinates. General vegetation characteristics, elevation, weather, field personnel, time at the den, and behavioral responses of the kittens and female were also recorded. Diet Winter diet of reintroduced lynx was estimated by documenting successful kills through snowtracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. Scat samples were collected wherever found and labeled with location and individual lynx identification. Only part of the scat was collected; the remainder was left in place in the event that the scat was being used by the animal as a territory mark. RESULTS Reintroduction Effort Based on the adoption of the approved augmentation management strategy (Shenk 2003), 37 lynx (17 females and 20 males) were released in April 2004, bringing the total number of lynx reintroduced to Colorado to 166 (Table 1). Lynx for the 2004 augmentation were captured in Quebec and British Columbia. All 37 lynx were released at previously used release sites in southwestern Colorado. Table 1. Colorado lynx reintroduction effort as of June 30, 2004. Year Females Males TOTAL 1999 22 19 41 2000 35 20 55 2003 17 16 33 2004 17 20 37 TOTAL 91 75 166 8 �Movement Patterns Most of the lynx released in 2004 have remained in the southwestern quarter of Colorado, with the exception of 2 lynx that went briefly to New Mexico but subsequently returned to Colorado. The majority of surviving lynx from the entire reintroduction effort continue to use areas from New Mexico north to Gunnison, west as far as Taylor Mesa and east to Monarch Pass. There are some lynx north of Gunnison up to the I70 corridor and in the Taylor Park area. No lynx are known to be north of I70 at this time. Mortalities Of the total 166 adult lynx released in 1999, 2000, 2003 and 2004 we have 56 known mortalities. Of these 56 mortalities, 25 are from the 1999 releases, 23 are from the 2000 releases, 4 are from the 2003 releases, and 4 are from the 2004 releases. Causes of death are listed in Table 2. Of the 16 kittens known to have been born in Colorado in 2003, we have 7 confirmed mortalities and 3 possible mortalities. Table 2. Causes of death for adult lynx released into southwestern Colorado in 1999, 2000, 2003 and 2004. 1999 Total Cause of death 2000 2003 2004 M F M F U M F M F Starvation 1 Hit by Vehicle Shot 6 1 2 3 Probable Predation 1 1 3 1 9 1 1 1 1 7 7 1 1 Plague 4 4 Unknown: Human Caused 1 1 Probable Shot 1 Probable Hit by Vehicle 2 1 4 2 Unknown: Not Starvation 1 2 Unknown 2 1 2 1 4 1 4 2 1 Human Caused Total 1 14 1 8 17 7 15 1 3 1 6 2 1 2 56 As of June 30, 2004, CDOW was actively tracking 85 of the 110 lynx still possibly alive (Table 3). Of the remaining 25 remaining lynx possibly alive, 24 were ‘missing’ as of June 30, 2004 (Table 3). A lynx was listed as missing if a signal has not been heard from the animal for at least 1 year. One of these missing lynx is the unknown mortality, thus only 23 are truly missing. Possible reasons for not locating these missing lynx include (1) long distance dispersal, beyond the areas currently being searched, (2) radio failure, or (3) destruction of the radio (e.g., run over by car). CDOW continues to search for all missing lynx during both aerial and ground searches. Two of the lynx released in 2000 are thought to have slipped their collars. Thus, CDOW tracked 85 individual lynx since at least June 30, 2003. 9 �Table 3. Status of adult lynx reintroduced to Colorado as of June 30, 2004. Females Males Unknown TOTALS Released 91 75 Known Dead 35 20 Possible Alive 56 55 110 Missing 9 15 23 (1 is unknown mortality) Slipped Collar 1 1? 1-2 Tracking 46 39 85 166 1 56 Reproduction Of the 6 females that had kittens in 2003, 1 died and 2 had collars that shut off prior to denning season in 2004. Of the 3 that could be monitored during the 2004 denning season, 1 had a litter of 2 kittens (YK00F10), 1 did not have kittens (BC00F08) and it is highly probable the third female (YK99F1) has kittens with her based on her movement patterns. We are still trying to document her status. The 2004 dens were scattered throughout Colorado and 1 den was found in southern Wyoming. Most of the dens were in Engelmann spruce/subalpine fir forests in areas of extensive downfall. Elevations at the den sites ranged from 2652-3560 m (8701 - 11,680 feet). We weighed, photographed, and PIT-tagged the kittens and recorded sex. We also took hair samples from the kittens for genetic work in an attempt to confirm paternity. We processed the kittens as quickly as possible (15-35 minutes) to minimize the time the kittens were without their mother. Four of the females would not leave the den until we reached out to pick up a kitten. While we were working with the kittens the females remained nearby, often remaining visible to us. The females generally continued a low growling vocalization the entire time we were at the den. In all cases, the female returned to the den site once we left the area. Four of the 6 females that we know had kittens in summer 2003 were still with kittens at the end of April 2004. Two of those females still had 2 kittens with them at that time. Visual observations in February 2004 of one female with 2 kittens indicated all 3 were in good body condition. Snow-trackers documented at least 1 snowshoe hare kill by a kitten in winter 2003-04. The mortality of the female YK00F16 and her 1 kitten from plague was not due to poor habitat or prey conditions, and thus we might assume she would have raised the 1 kitten to this stage as well. Three probable kitten deaths from female YK00F19 were from 1 litter that most likely failed very early. Through snow-tracking an unknown female (no radio frequency heard in the area of the tracks) we also documented 1-2 additional kittens born spring 2003 and still alive in winter 2004. Of the 16 kittens we found in summer 2003, we documented the following by April 2004: 6 confirmed alive, 7 confirmed dead, and 3 some evidence dead (Table 4). Although we tried, we were not able to capture any of the 6 surviving kittens to fit them with radio collars. Unless we capture or find any of these kittens from other methods we will not know their fate beyond this 10 months of survival. 10 �Table 4. Known reproduction for summer 2003 and subsequent kitten fates by April 2004. Kittens Known Dead in April 2004 1 Female Release Year Date Den Found Females Males Total BC00F8 2000 5/21/2003 ? ? 2 Kittens Known Alive in April 2004 1 BC00F19 2000 5/26/2003 1 1 2 1 1 YK00F16 2000 6/19/2003 1 1 2 0 2 YK99F1 1999 6/10/2003 2 1 3 2 1 YK00F19 2000 6/11/2003 1 2 3 ? 3? YK00F10 2000 5/31/2003 2 2 4 2 2 16 6 7, 3? Kittens Born TOTAL In spring 2004 we had 26 females from the releases in 1999, 2000 and 2003 that had active radio collars. We documented 18 possible mating pairs of lynx during breeding season. We defined a possible mating pair as any male and female documented within at least 1 km of each other in breeding season through either flight data or snow-tracking data. All 4 of the females that had kittens with them through winter 2003-04 bred again this spring, 2 with the same male they successfully bred with last spring. During May-June 2004 we found 11 dens and a total of 30 kittens (Table 5). Dens were found when we walked in on females that exhibited virtually no movement for at least 10 days from both aerial and ground telemetry. At all dens the females appeared in excellent condition, as did the kittens. The kittens weighed from 250-770 grams. Lynx kittens weigh approximately 200 grams at birth and do not open their eyes until they are 10-17 days old. Three of the 11 females with kittens were from the 2003 releases (Table 5). Table 5. Lynx reproduction documented in 2004. Kittens Born Female Release Year Date Den Found Females Males Total YK00F2 2000 5/28/2004 3 1 4 AK00F2 2000 5/31/2004 2 1 3 YK00F1 2000 6/1/2004 3 YK00F15 2000 6/4/2004 1 2 3 BC00F14 2000 6/7/2004 1 2 3 BC00F18 2000 6/10/2004 4 YK00F10 2000 6/17/2004 1 BC03F02 2003 6/25/2004 BC03F10 2003 6/26/2004 BC03F09 2003 YK00F7 2000 TOTAL 3 4 1 2 2 2 1 1 2 6/29/2004 1 1 2 6/30/2004 1 1 2 18 12 30 11 �Diet Winter diet of lynx was documented through detection of kills found through snow-tracking. In each winter, the most common prey item was snowshoe hare (Lepus americanus), followed by red squirrel (Tamiasciurus hudsonicus) (Table 6). Table 6. Number of kills found each winter field season through snow-tracking of lynx and percent composition of kills of the three primary prey species. Field Season 1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 n 9 81 88 54 65 37 Snowshoe Hare 55.56 67.46 67.41 90.74 90.77 67.56 Prey (%) Red Squirrel Cottontail 22.22 0 19.27 1.20 19.10 8.99 5.56 0 6.15 0 27.03 2.70 Other 22.22 12.05 4.49 3.70 3.08 2.70 DISCUSSION In an effort to establish a viable population of lynx in Colorado, a reintroduction effort was initiated in 1999. The reintroduction effort was augmented with the release of 37 additional animals in April 2004, bringing the total to 166 lynx reintroduced to southwestern Colorado. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns and to detect mortalities. Most lynx remain in the southwestern quarter of Colorado. Humancaused mortality factors such as gunshot and vehicle collision are currently the highest causes of death. Reproduction was first documented from the 2003 reproduction season. A second successful breeding season was documented in 2004 with 11 dens and 30 kittens found as of June 30, 2004. Live births are the first step towards recruitment. Recruitment into a population would require these kittens to survive through their first year of life and produce offspring of their own. To achieve a viable population of lynx, enough kittens need to be recruited into the population to offset the mortality that occurs in that year and hopefully even add more so that the population can grow. Snow-tracking of released lynx provided preliminary information on hunting behavior by documenting location of kills, food caches, chases, and diet composition estimated through scat analysis. Snow-tracking results indicate the primary winter prey species are snowshoe hare and red squirrel, with other mammals and birds forming a minor part of the winter diet. Site-scale habitat data collected from snow-tracking efforts indicate Engelmann spruce and subalpine fir are the most common forest stands used by lynx in southwestern Colorado. From results to date it can be concluded that CDOW has developed release protocols that ensure high initial post-release survival, and on an individual level lynx have demonstrated they can survive long-term in areas of Colorado. It has also been documented that reintroduced lynx could exhibit site fidelity, engage in breeding behavior and produce kittens. What is yet to be demonstrated is whether Colorado conditions can support the recruitment necessary to offset annual mortality for a population to sustain itself. Monitoring of reintroduced lynx will continue in an effort to document such viability. 12 �LITURATURE CITED Shenk, T. M. 1999. Program narrative: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. __________ 2001. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. __________ 2003. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. Wild, M. A. 1999. Lynx veterinary services and diagnostics. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. Prepared by _______________________________ Tanya M. Shenk, Wildlife Researcher 13 �14 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Colorado : : Cost Center 3430 Mammals Research Work Package No. Task No. 0670 2 : Lynx Conservation : Ecology of Snowshoe Hares (Lepus americanus) in Colorado Federal Aid Project: N/A : Period Covered: July 1, 2003 – June 30, 2004 Author: Jennifer L. Zahratka Personnel: S. W. Buskirk , T. M. Shenk All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A thesis, entitled ‘The population and habitat ecology of snowshoe hares (Lepus americanus) in the southern Rocky Mountains’ was completed and submitted to the University of Wyoming in partial fulfillment of a Master of Science degree. The thesis is available from The Colorado Division of Wildlife Library or the University of Wyoming Library. Included in this report is an abstract of the thesis. 15 �JOB PROGRESS REPORT THE POPULATION AND HABITAT ECOLOGY OF SNOWSHOE HARES (Lepus americanus) IN THE SOUTHERN ROCKY MOUNTAINS Jennifer L. Zahratka ABSTRACT To better understand the population ecology and habitat associations of snowshoe hares (Lepus americanus), I studied snowshoe hares in southwestern Colorado in winters 2002 and 2003. I estimated densities from mark-recapture data and compared vegetative attributes in the mature structural stage (SS 4) among three stand types: Engelmann spruce (Picea engelmannii)–subalpine fir (Abies lasiocarpa), lodgepole pine (Pinus contorta), and ponderosa pine (Pinus ponderosa). I used three methods to calculate a boundary strip width (W) to estimate the effective area trapped Â(Ŵ) in order to illustrate the effect of different methods of estimating Â(Ŵ) on estimates of density. Density estimates [ D̂ = N̂ / Â(Ŵ)] in mature spruce-fir ranged from 0.1 ± 0.03 (SE) hares/ha to 0.9 ± 0.1 hares/ha in 2002 and 0.3 ± 0.05 to 1.0 ± 0.1 hares/ha in 2003. I report only minimum number alive (MNA) in lodgepole pine due to too few captures to estimate density. No snowshoe hares were captured in mature ponderosa pine stands. Model selection based upon the corrected Akaike’s Information Criterion (AICc) showed a strong relationship between MNA and understory cover, density of woody stems 1-7 cm in diameter, and the availability of suitable woody stems for food among the mature stand types I studied (R = 0.91, df = 8, P = 0.008). My empirical data support the assumption that snowshoe hares select habitat with protection from predation. However, the availability of suitable woody stems for food is also an important vegetative attribute for hare habitat. Snowshoe hares selected for spruce-fir among the mature stand types I studied. Mature spruce-fir provided more understory, greater density of woody stems 1-7 cm in diameter, and more woody stems (<1.5 cm) for food. In my study, the winter diet of snowshoe hares was overwhelmingly gymnosperms. Extremely low temperatures affected capture success, but moon phase did not. Counts of fecal pellets are an attractive tool to estimate densities of snowshoe hares because they are less costly and less labor-intensive than conventional mark-recapture techniques. In the southern Rocky Mountains, snowshoe hares and mountain cottontails (Sylvilagus nuttallii) are syntopic. Indeed, I captured two mountain cottontails in two traps in which I captured snowshoe hares. Therefore, distinguishing between fecal pellets is necessary for making inferences specific to these species. Methods to distinguish between the two leporid species have been developed based upon the assumption that the larger snowshoe hare produces larger fecal pellets than the smaller mountain cottontail. In this study, I measured 655 fecal pellets from 10 individual mountain cottontails and 2,374 fecal pellets from 23 individual snowshoe hares: I found no apparent relationship between the body weight of mountain cottontails or snowshoe hares and the size of their fecal pellets (mountain cottontails: r = 0.04, F = 0.01, P = 0.91; snowshoe hares: r = 0.48, F = 9.3, P = 0.005). Although the two species differed in the size of their fecal pellets, the difference (1.2 mm) would be indistinguishable without measuring equipment and is only applicable to adults. While fecal pellet counts may be accurately used to estimate densities of snowshoe hares in the boreal forests of Canada, in the southern Rocky Mountains where leporid species are potentially syntopic, this method may yield misleading results. 16 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Colorado 0880 Task Federal Aid Project : : : : N/A Cost Center 3430 Mammals Research Black-Footed Ferret Conservation Black-Footed Ferret Recovery Program Disease Monitoring & Management : Period Covered: July 1 2003 through June 30, 2004 Author: L. L. Wolfe Personnel: L. A. Baeten, H. Edwards, C. T. Larsen, M. W. Miller, K. Taurman, E. S. Williams All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We continued monitoring carnivores at proposed black-footed ferret reintroduction sites for serological evidence of select disease epidemics. Sampling at the Wolf Creek Management Area (WCMA) in August 2004 revealed little evidence of ongoing epidemics that could impede black-footed ferret restoration efforts. Serology data from culled coyotes showed no evidence of active canine distemper or plague epidemics in the WCMA vicinity. In contrast, serologic evidence of exposure to tularemia continues to be relatively high (~30%), consistent with previous observations in this and other monitored areas. We will continue this work as part of the ongoing Colorado−Utah black-footed ferret reintroduction protocol. 17 �JOB PROGRESS REPORT BLACK-FOOTED FERRET RECOVERY PROGRAM DISEASE MONITORING & MANAGEMENT LISA L. WOLFE INTRODUCTION As part of the Colorado−Utah black-footed ferret reintroduction protocol, we continued monitoring carnivores at proposed ferret reintroduction sites for serological evidence of select disease epidemics. Originally, we monitored coyote (Canis latrans) populations at two Colorado sites: the Little Snake Management Area (LSMA) and the Wolf Creek Management Area (WCMA), Colorado. Under this program, >200 coyotes have been collected for post-mortem examination and samples collected as described in established protocols since March 1997. Monitoring has been accomplished via cooperative efforts of Colorado Division of Wildlife, USDA Wildlife Services, and Bureau of Land Management (BLM) personnel. To date, no lesions indicative of active infections with any of the select pathogens (Francisellia tularensis, Yersinia pestis, canine distemper virus [CDV]) have been noted on gross examinations of carcasses. However, relatively high proportions (31-89%) of the coyotes collected from the LSMA had positive titers to plague between March 1997 and July 1999. Although the proportion of plague-positive coyotes declined during the sampling period, evidence of continued exposure and perhaps declining prairie dog abundance led to abandonment of surveillance at LSMA after 1999. Monitoring at the WCMA has continued, and black-footed ferrets were reintroduced at this site in 2001. RESULTS AND DISCUSSION Disease surveillance As part of the Colorado-Utah black-footed ferret reintroduction protocol, we monitored serological evidence of exposure to select infectious diseases in coyotes at Wolf Creek Management Area (WCMA), Colorado; our strategy was to use exposed coyotes as sentinels for detecting epidemics at restoration and prospective release sites. Over 350 coyotes (Canis latrans) have been collected for postmortem examination and samples collected as described in established protocols since March 1997 via cooperative efforts of Colorado Division of Wildlife, USDA Wildlife Services, and Bureau of Land Management (BLM) personnel. Coyotes were collected using a combination of calling and aerial gunning. In 2004, 20 coyotes were sampled (5 pups, 6 juvenile, 6 adult, 3 not aged) in late July. (Because data from juveniles are most useful in detecting evidence of recent epidemics, we discontinued mid-winter sampling in 2002.) No lesions indicative of active infections with select pathogens (Francisellia tularensis, Yersinia pestis, canine distemper virus [CDV]) were noted on gross examinations of carcasses through 2002; in the absence of meaningful necropsy findings, we discontinued gross examinations of carcasses in 2003. Initial sampling (February 2000) at WCMA indicated substantially lower exposure rates to select pathogens than observed at another site (Little Snake Management Area) monitored in earlier years of this survey. Initial sampling demonstrated 24 percent of the coyotes surveyed with antibody titers suggestive of exposure to CDV. Although seroprevalence increased slightly in 2001, sampling since 2002 revealed much lower proportions of CDV-positive coyotes (Figure 1). There was no serologic evidence of CDV exposure in 2002, and only 1 case each in 2003 and 2004. Exposure to plague still appears relatively rare among coyotes sampled from WCMA (Figure 1). In 2004 one juvenile, out of 21 coyotes sampled, was 18 �“moderately positive” antibody titer to plague. The most significant pathogen exposure noted by seroprevalence is for tularemia. As tularemia is commonly found in rodents in Colorado, seroprevalence of 20–40% is not surprising in carnivores, and very little change in tularemia seroprevalence has been seen over the 5-year sampling period. Prepared by ________________________ Lisa L. Wolfe, Veterinarian 100% 80% 60% 40% 20% Y. pestsis F. tularensis CDV Date/pathogen 08/04 (n=20) 08/03 (n=11) 07/02 (n=13) 07/01 (n=16) 07/00 (n=20) 08/04 (n=20) 08/03 (n=11) 07/02 (n=13) 07/01 (n=16) 07/00 (n=20) 08/04 (n=20) 08/03 (n=11) 07/02 (n=13) 07/01 (n=16) 07/00 (n=20) 0% Positive Negative Figure 1. Seroprevalence of presumed tularemia (F. tularensis), plague (Y. pestis), and canine distemper virus (CDV) exposure among coyotes sampled from the Wolf Creek Management Area, Colorado, during summer sampling 2000−2004. 19 �20 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Task No. Colorado : : : 3001 4 : Federal Aid Project: W-185-R Cost Center 3430 Mammals Research Deer Conservation Effect of Nutrition and Habitat Enhancements on Mule Deer Recruitment and Survival Rates : Period Covered: July 1, 2003 - June 30, 2004 Authors: C. J. Bishop, G. C. White, D. J. Freddy, and B. E. Watkins Personnel: D. L. Baker, L. Baeten, T. Banulis, E. J. Bergman, S. K. Carroll, D. Coven, K. Crane, M. DelTonto, B. Diamond, B. deVergie, D. Gallegos, J. Garner, L. Gepfert, R. B. Gill, D. Hale, J. Grigg, H. Halbritter, R. Harthan, M. Johnston, W. J. Lassiter, T. Mathieson, J. McMillan, G. C. Miller, M. W. Miller, J. Nicholson, J. A. Padia, T. M. Pojar, R. Powers, J. E. Risher, C. A. Schroeder, W. G. Sinner, C. M. Solohub, J. Thayer, M. A. Thonhoff, R. Wertsbaugh, L. Wolfe, CDOW; H. VanCampen, CSU; D. Felix, Olathe Spray Service; T. R. Stephenson, California Fish and Game; L. H. Carpenter, WMI; J. Sazma, B. Welch, BLM. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT To further understand the factors that caused deer numbers to decline in western Colorado during the 1990s, we designed and initiated a field experiment to measure deer population parameters in response to a nutrition enhancement treatment. During November 2000 – June 2004, we captured and radio-collared 810 individual mule deer evenly distributed among treatment and control units on the Uncompahgre Plateau in southwest Colorado. This included 293 adult females, 154 of which received vaginal implant transmitters (VITs), 241 6-month old fawns, and 276 newborn fawns born from either treatment or control adult does. We enhanced the nutrition of deer in the treatment unit by providing a safe, pelleted supplemental feed on a daily basis from December through April each winter. Early winter fawn:doe ratios were measured using helicopter and ground classification surveys the year following treatment delivery to determine whether fawn production and survival increased as a result of enhanced nutrition of adult females. We also measured overwinter fawn survival rates in response to the treatment. During 2002 – 2004, we measured pregnancy rates, fetus rates, and body condition of treatment and control adult does during late winter using ultrasonography. We also directly measured fetus survival and neonate survival by using VITs to help locate and radio-collar newborn fawns born from treatment and control does. Estimated percent body fat of adult does during late February and early March, 2002-04, 21 �was significantly higher (F1, 148 = 153.41, P < 0.001) for treatment deer (9.8%, SE = 0.36, n = 78) than control deer (4.3%, SE = 0.26, n = 76). Serum thyroid hormone concentrations, measured only in 2003 and 2004, were higher in treatment does than control does (F4, 108 = 46.59, P < 0.001). Pregnancy and fetus rates were similar among treatment and control does. The pregnancy rate of adult does was 0.95 (SE = 0.036, n = 38) and the fetus rate was 1.80 fetuses/doe (SE = 0.10, n = 36) during 2002. Rates were similar in 2003, where we measured a pregnancy rate of 0.92 (SE = 0.034, n = 63) and a fetus rate of 1.74 fetuses/doe (SE = 0.069, n = 50) which included 5 yearlings (the fetus rate excluding yearlings was 1.82 fetuses/doe, SE = 0.066, n = 45). In 2004, we measured a pregnancy rate of 0.94 (SE = 0.029, n = 66) and the fetus rate was 1.97 fetuses/doe (SE = 0.053, n = 60), which included 4 yearlings (the fetus rate excluding yearlings was 2.00 fetuses/doe, SE = 0.051, n = 56). The fetus survival rate with treatment and control fetuses combined was 0.86 (SE = 0.073) during 2002, 0.97 (SE = 0.024) during 2003, and 0.90 (SE = 0.040) during 2004. Fetus survival was similar among treatment and control deer during 2002 – 2003, but not 2004, where treatment fetus survival was 1.00 (SE = 0.000, n = 33) and control fetus survival was 0.76 (SE = 0.085, n = 25). Based on multiple early winter age classification surveys, we concluded the winter nutrition enhancement treatment did not cause an increase in neonatal production and survival during 2001. However, fawn production and summer-fall survival was relatively good for the overall population, and not representative of most years during the past decade when the population declined. During June – December, 2002−2003, survival of newborn treatment fawns was 0.620 (SE = 0.067) and control fawn survival was 0.493 (SE = 0.070). Survival data coupled with early winter age classification surveys provided evidence the nutrition enhancement treatment increased December fawn recruitment during 2002 and 2003. During December – June, 2001−2004, the overwinter survival rate of fawns was significantly greater (χ21 = 18.781, P < 0.001) in the treatment unit (S(t) = 0.895, SE = 0.029) than in the control unit (S(t) = 0.655, SE = 0.044). Because of a cross-over experimental design, the treatment unit during winter 2001-02 became the control unit during winters 2002-04, and vice versa. Thus, the treatment effect was replicated across each experimental unit. Combining all years of data, the best model of overwinter fawn survival (AICc = 207.65) included the nutrition enhancement treatment (χ21 = 19.04, P < 0.001), early winter fawn mass (χ21 = 23.27, P < 0.001), and year (χ21 = 6.20, P = 0.045). The AIC model selection analysis emphasized the importance of both the treatment effect as well as early winter mass of fawns, because any models without treatment or fawn mass were poor. Early winter mass of control fawns was slightly higher than that of treatment fawns (F1, 231 = 3.00, P = 0.085); thus the effect of the treatment was not confounded with fawn mass. Data collection will not be completed until January 2005. The results reported here are preliminary and should be treated as such. 22 �JOB PROGRESS REPORT EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES C. J. Bishop, G. C. White, D. J. Freddy, and B. E. Watkins P. N. OBJECTIVES 1. To determine experimentally whether enhancing mule deer nutrition during winter and early spring by supplemental feeding increases fetus survival, neonate survival, early winter fawn:doe ratios or overwinter fawn survival. 2. To determine experimentally to what extent habitat treatments replicate the effect of enhanced nutrition from supplemental feeding. SEGMENT OBJECTIVES 1. Capture and radio-collar a target sample of adult female mule deer and 6 month-old fawns during late November through mid-December in a treatment unit and a control unit. 2. Capture a target sample of adult female mule deer in the treatment unit and the control unit to measure pregnancy rates, fetal rates, and body condition during late February to early March, and fit each adult female deer with a radio collar and vaginal implant transmitter. 3. Deliver the nutrition enhancement treatment to all deer occupying the treatment unit from early December through the end of April. 4. Capture and radio-collar a target sample of newborn fawns from treatment and control radio-collared does during June using the vaginal implant transmitters as a technique to determine the timing and location of birth. 5. Measure fetus survival, neonate survival, early winter fawn:doe ratios, overwinter fawn survival, and annual adult female survival based on radio-collared deer from the treatment and control units. INTRODUCTION Mule deer (Odocoileus hemionus) numbers apparently declined during the 1990’s throughout much of the West, and have clearly decreased since the peak population levels documented in the 1940’s60’s (Unsworth et al. 1999, Gill et al. 2001). Biologists and sportsmen alike have concerns as to what factors may be responsible for declining population trends. Although previous and current research indicates multiple interacting factors are responsible, habitat and predation have received the focus of attention. A number of studies have evaluated whether predator control increases deer survival, yet results are highly variable (Connolly 1981, Ballard et al. 2001). Together, predator control studies with adequate rigor indicate predation effects on mule deer are variable as a result of time-specific and sitespecific factors. Studies which have demonstrated deer population responses to predator control treatments have failed to determine whether predation is ultimately more limiting than habitat. Numerous research studies have evaluated mule deer habitat quality, but virtually no studies have documented population responses to habitat improvements. In many areas where declining deer numbers are of concern, predation is common yet habitat quality appears to have declined. The question remains as to whether predation, habitat, or some other factor is more limiting to mule deer in these situations, and whether habitat quality can be improved for the benefit of deer. It may also be that no single factor is any more or less important than others, and a more comprehensive understanding of multi-factor interactions is needed. We designed a field experiment to measure deer population responses to nutrition enhancement treatments, to further understand the causative factors underlying observed deer population dynamics. We 23 �are conducting the study on the Uncompahgre Plateau in southwest Colorado, where several predator species are present in abundant numbers: coyotes (Canis latrans), mountain lions (Felis concolor), and bears (Ursus americanus). In addition to predation, myriad diseases in combination proximately affect survival of the Uncompahgre deer population (Pojar and Bowden 2004, B.E. Watkins, unpublished data). Predator numbers have not and will not be manipulated in any manner during the course of the study. All factors have been left constant with the exception of deer nutrition. Deer nutrition is being enhanced by providing supplemental feed to deer occupying a treatment area during the winter. If December fawn recruitment and/or overwinter fawn survival improve as a direct result of the nutrition enhancement treatment, then we can presume that deer nutrition is ultimately more limiting than predation or disease. The second phase of the field experiment, which has not yet been initiated, will incorporate habitat manipulation treatments. The treatments will consist of prescribed fire or mechanical techniques to set back succession of pinyon-juniper (Pinus edulis-Juniperus osteosperma) habitat in an effort to improve the vigor and quality of winter habitat for mule deer. Deer population responses will be measured in relation to the habitat manipulations in the same manner as the supplemental feed. Thus, the experiment will evaluate whether nutritional quality of winter range habitat is ultimately more limiting than other factors in a late-seral pinyon-juniper/sagebrush (Artemisia spp.) landscape, and if so, whether habitat can be effectively improved for mule deer. The results will also advance our current understanding of multifactor interactions, with direct implications for mule deer management. MATERIALS AND METHODS Experimental Approach Experimental Design and Study Area We non-randomly selected two areas within mule deer winter range on the Uncompahgre Plateau to create 2 experimental units (A-B) (Fig. 1). The following criteria were used to select experimental units: 1.) Deer densities (~50-80 deer/mi2): areas were selected where deer densities were sufficient to meet sample size requirements within the experimental unit, while simultaneously selecting areas that would require feeding less than ~500-600 animals during a normal winter 2.) Buffer zones: areas were selected such that experimental units would be separated by several miles of non-treatment area (buffers) to prevent deer from occupying more than one experimental unit 3.) Similarity: areas were selected that comprise relatively similar habitat complexes and deer densities that are representative of the overall area 4.) Elk populations: areas were selected to minimize the number of elk present during normal winters Units A and B are receiving the nutrition enhancement treatment in a cross-over experimental design, and are being used to address P.N. Objective 1. Unit A served as the treatment unit, while Unit B served as the control, for the first 2 winters of research (2000 – 2002). Beginning November 2002, Unit B received the treatment while Unit A served as the control. Upon completion of P.N. Objective 1, two additional winter range experimental units will be used to conduct phase 2 of the research, or P.N. Objective 2. Habitat in one unit will be manipulated to set back plant succession (treatment), while habitat in the other unit will remain unchanged (control) throughout the experiment. 24 �Year 2000-01 Unit A Treatment Unit B Control 2001-02 Control 2002-03 Treatment Control Treatment 2003-04 Control Treatment Figure 1. Schematic representation of experimental units and nutrition enhancement treatment allocation. Units A and B are located in winter range habitat on the Uncompahgre Plateau in southwest Colorado. The nutrition enhancement cross-over design will encompass 4 years. The 2 experimental units (A and B) receiving the nutrition enhancement treatment are (Figs. 2 and 3): (1) Experimental unit A includes the Colona Tract of the Billy Creek State Wildlife Area and adjacent land, located approximately 13 km south of Montrose, CO adjacent to U.S. Hwy 550 South. The experimental unit is located within the Colona USGS 7.5 Minute Quadrangle, and roughly includes the polygon defined by the following Zone 13 UTM coordinates: (1) 254000 E, 4250200 N; (2) 252700 E, 4249400 N; (3) 254700 E, 4245600 N; and (4) 256200 E, 4246600 N. (2) Experimental unit B includes Shavano Valley and adjacent land extending west to the Dry Creek Rim. Shavano Valley is located approximately 13 km west of Montrose, CO. The experimental unit is located within the Dry Creek Basin and Montrose West Quadrangles (USGS 7.5 Minute), and roughly includes the polygon defined by the following Zone 13 UTM coordinates: (1) 238400 E, 4262600 N; (2) 232400 E, 4256700 N; (3) 235000 E, 4253600 N; and (4) 239500 E, 4258200 N. In late April and May, prior to fawning, deer from the winter range experimental units migrate to summer range. The summer range study area is defined by movements of the radio-collared deer, which encompass >1000 mi2 covering the southern portion of the Uncompahgre Plateau and adjacent San Juan Mountains to the south and east (Fig. 2). The summer range study area extends north to the Dry Creek river drainage on the Uncompaghre Plateau, south to Mineral Creek near Silverton, CO, east to the Big Blue river drainage, and west to the San Miguel River canyon. However, a majority of the radio-collared deer summer on the Uncompahgre Plateau between Dry Creek to the north and Highway 62 to the south. Winter range elevations range from 1830 m (6000 ft) in Shavano Valley to 2318 m (7600 ft) adjacent to the Dry Creek Rim above Shavano Valley. Winter range habitat is dominated by pinyonjuniper with interspersed sagebrush adjacent to agricultural fields in the Shavano and Uncompahgre Valleys. Summer range elevations occupied by deer range from 1891 m (6200 ft) in the Uncompahgre Valley to 3538 m (11,600 ft) in Imogene Basin southwest of Ouray, CO. Summer range habitats are dominated by spruce-fir (Picea spp.-Abies spp.), aspen (Populus tremuloides), ponderosa pine (Pinus ponderosa), Gambel oak (Quercus gambelii), and to a lesser extent, sagebrush and pinyon-juniper at lower elevations. 25 �Uncompahgre Plateau Mesa County GRAND JUNCTION Delta County U om nc GMU 62 r hg pa e u ea at Pl Montrose County GMU 61 DELTA Shavano E.U. MONTROSE Colona Montrose County E.U. Gunnison County Winter Range Exp. Units Summer Range Ouray County Sanmiguel County Figure 2. Location of Colona and Shavano (Units A and B) experimental units in Game Management Unit 62 on the Uncompahgre Plateau, southwest Colorado; and location of the summer range study area throughout the southern Uncompahgre Plateau and adjacent San Juan Mountains. 26 �Hwy 550 Uncompahgre Valley Colona Exp. Unit Shavano Valley Shavano Exp. Unit Figure 3. Colona and Shavano experimental units (Units A and B), located in Game Management Unit 62 on the Uncompahgre Plateau, southwest Colorado. 27 �Response Variables The response variables are fetal and neonatal survival rates, early winter fawn:doe ratios, and overwinter fawn survival rates. The nutrition enhancement treatment is delivered to deer from December through April, fetus survival is assessed during June, neonate survival is measured from June to December, and fawn:doe ratios are measured during the following December and January (1 year after the treatment was initiated). Overwinter fawn survival is measured from December to June as a direct result of the current winter’s treatment. We are measuring these response variables in each experimental unit (treatment and control) to determine whether enhanced winter nutrition of adult does increases subsequent newborn fawn production and survival, and whether enhanced winter nutrition of 6-mo. old fawns directly increases overwinter fawn survival. Ultimately, these measurements provide an assessment of the effect of winter range habitat quality on yearling recruitment, and thus population productivity. We are also measuring overwinter and annual survival of adult does as a function of enhanced winter nutrition. Sample Size Fetus/Neonate Survival: We were primarily interested in survival of newborn fawns from radiocollared does that occupy the 2 winter range experimental units. Fetus survival is also important, but difficult to measure. Fetus rates from a sample of radio-collared does can be measured in winter, but the fate of all fetuses cannot be determined the following June because of logistical constraints. Fetus survival rates can only be measured from some unpredictable fraction of the radio-collared doe sample, making sample size calculations of limited use. Thus, our sample size calculations were based on quantifying neonate survival, not fetus survival. For neonate survival, a sample size of 40 neonates per experimental unit per year provides power of 0.81 to detect a difference of 0.15 in survival between 2 experimental units if survival among control fawns is 0.40. We assumed a control survival rate of 0.40 based on neonate survival rates measured recently for the Uncompahgre deer population (Pojar and Bowden 2004) in combination with December fawn:doe ratios measured during the late 1980’s and 1990’s, when the Uncompahgre population declined (B. E. Watkins, unpublished data). Based on Bishop et al. (2002), we determined that 60 radio-collared does (30 treatment and 30 control) equipped with vaginal implant transmitters (VITs) would be necessary to capture a minimum of 80 newborn fawns. We also assumed that some fawns would be captured from other treatment and control radio-collared does not equipped with VITs. The 60 radio-collared does with VITs are also being used to evaluate fetus survival; however, logistical constraints limit the power of fetus survival comparisons among experimental units. Early winter fawn:doe ratios: We desired to detect an effect size, i.e., an increase in fawn:doe ratios in response to the treatments, in the range of 15 to 20 fawns per 100 does. These values were based on simple population models with overwinter fawn survival of 0.444, adult female survival of 0.853, and December fawn:doe ratios of 66 fawns per 100 does to obtain a stationary population (Unsworth et al. 1999). Based on surveys of the Uncompahgre deer population during the 1990’s, the standard deviation of the fawn:doe ratio for groups with at least one adult female was 57, with a mean of 41. Using an expected standard deviation of 57, the standard error of the mean fawn:doe ratio for 40 radio-collared does is 57/(401/2) = 9.0, which is the expected standard deviation of measured fawn:doe ratios on each experimental unit. We assessed power using a two-sample t-test with a sample size of 4, representing the 4 years of the study where fawn:doe ratios are being measured in response to enhanced nutrition. Our power to detect an increase of 20 fawns per 100 does based on classification of 40 radio-collared doe groups in each experimental unit is about 0.87. A sample size of 40 fawns per experimental unit per year provides a power of 0.81 to detect a difference of 0.15 in survival between 2 experimental units if survival on the control unit is 0.40. We expected to see an increase in fawn survival (effect size) of approximately 0.15, because this was the difference measured in the density reduction experiment conducted by White and Bartmann (1998). 28 �Adult and 6-month Old Fawn Capture During November and December, adult does and 6-month old fawns were captured using baited drop nets (Ramsey 1968, Schmidt et al. 1978) and helicopter net guns (Barrett et al. 1982, van Reenen 1982). Drop nets were baited with certified weed-free alfalfa hay and apple pulp. Drop nets were used as the principle capture technique for a 3-4 week capture period; helicopter net-gunning was then used at the end of the drop-net capture to secure the remainder of deer needed to meet our target sample sizes. All deer were hobbled and blind-folded after being captured. Deer captured via drop nets were carried away from the net to an adjacent handling site using stretchers. Deer were fitted with leather radio collars equipped with mortality sensors, which cause an increase in pulse rate after remaining motionless for 4 hours. Permanent collars were placed on adult females, while temporary collars were placed on fawns. To make collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars ≥6 months post-capture. A rectangular piece of flexible plastic (Ritchey® neck band material) engraved with a unique identifier was stitched to the side of each collar. The unique identifier consisted of 2 symbols for adult females, and 1 symbol on 2 different colors of plastic for fawns. The identifiers were necessary to visually identify deer from the ground. This allowed us to effectively document use of the treatment, measure fawn:doe ratios from the ground, and assess experimental unit population size via mark-resight estimators. We recorded the weight, hind foot length and chest girth of each deer, and collected blood samples to evaluate disease prevalence. During late February and early March, an additional 30 adult female deer were captured in each experimental unit by net-gunning. Captured deer were ferried by the helicopter to a central processing location, where deer were carried by stretchers to a tent for handling. For each captured deer, we used ultrasonography to measure pregnancy status, fetal rate, and body condition. Only pregnant does were retained and radio-collared. We then inserted a vaginal implant transmitter (VIT) in each doe as a technique for locating the timing and location of her birth site the following June. We also recorded the weight, hind foot length and chest girth of each deer, and collected blood samples to evaluate disease prevalence. Body Condition and Reproductive Status We estimated body fat of treatment and control adult does during mid-late winter using an Aloka 210 (Aloka, Inc., Wallinford, Conn.) or SonoVet 2000 (Universal Medical Systems, Bedford Hills, NY) portable ultrasound unit with a 5 MHz linear transducer. We measured maximum subcutaneous fat thickness on the rump (MAXFAT) following the methodology of Stephenson et al. (1998, 2002). We also measured thickness of the longissimus dorsi muscle via ultrasound (Cook et al. 2001, Stephenson et al. 2002). A small area of hair was shaved to ensure contact between the transducer and the skin. Vegetable oil was applied to the shaved area for conduction purposes and fat/muscle thickness was measured using electronic calipers. We coupled the ultrasound measurements with body condition scores (BCS) obtained from palpation of the ribs, withers, and rump (Cook 2000). MAXFAT and rump BCS measurements were combined into a condition index used to estimate percent body fat (Cook and Cook 2002): % Fat = -6.6387617 + 7.4271417x – 1.11579443x2 + 0.07733803x3 where x = rLIVINDEX = (MAXFAT – 0.15) + rump BCS (if MAXFAT < 0.15, then rLIVINDEX = rump BCS). The rLIVINDEX and body fat regression was initially developed and validated for elk by Cook et al. (2001), and then modified by incorporating a validation of MAXFAT for mule deer performed by Stephenson et al. (2002). During mid-late winter, we also evaluated differences in serum thyroid hormone concentrations between treatment and control adult does. Specifically, we measured total thyroxine (T4), free T4 (FT4), total tri-iodothyronine (T3), and free T3 (FT3) following the methodologies of Watkins et al. (1983, 1991). Blood samples were collected at the time of capture, and serum hormone analyses were performed by the Michigan State University Animal Health Diagnostic Laboratory (East Lansing, Michigan). We 29 �compared serum thyroid hormone concentrations between treatment and control adult does, and also compared hormone levels to body fat estimates derived from the ultrasonography. We quantified reproductive status (Stephenson et al. 1995, Andelt et al. 2004) with ultrasound via transabdominal scanning using a 3 MHz linear transducer. We searched for fetuses by scanning a portion of the abdomen that was shaved caudal to the last rib and left of the midline. We systematically searched each uterine horn to identify fetal numbers ranging from 0 to 3. Whenever possible, we measured eye diameter of each fetus to approximately estimate fetal age and parturition date. Vaginal Implant Transmitters (VITs) We used VITs manufactured by Advanced Telemetry Systems, Inc. (Isanti, MN). The VIT was 76 mm long, excluding antenna length, and had 2 plastic wings with a width of 57 mm when fully spread apart. The plastic wings were used to retain the transmitter in the vagina until parturition. The VIT weighed 15 grams and contained a 10-28 lithium battery programmed to a 12-hour on/off cycle. The diameter of the transmitter/battery was 14 mm, and was encased in an impermeable, water-proof, electrical resin. The transmitter contained an embedded heat-sensor which dictated the frequency pulse rate. When the heat sensor dropped below 90°F, synonymous with transmitter expulsion from the deer, the pulse rate changed from 40 PPM to 80 PPM. VIT batteries were programmed to be active from 0430 to 1630 hrs prior to daylight savings, and thus were active from 0530 to 1730 hrs after daylight savings and during the fawning period. The VIT was inserted into deer using a vaginoscope (Jorgensen Laboratories, Inc., Loveland, CO) and alligator forceps. The vaginoscope was 6” long with a 5/8” internal diameter and had a machined end (smooth surface) to minimize trauma when inserted into the vagina. A discreet mark was placed on the applicator showing the appropriate distance it should be inserted into the deer. The length of a typical mule deer vaginal tract was obtained by taking measurements from road-killed deer and/or other fresh deer carcasses obtained in the study area. Prior to use in the field, VITs were sterilized using a Chlorhexidine solution, air-dried, and sealed in a 3” x 8” sterilization pouch. Sterilization containers with Chlorhexidine solution were used on site during capture to sterilize the vaginoscope and alligator forceps between each use. A new pair of nitrile surgical gloves was used to handle the vaginoscope and VIT for each deer. To insert a VIT, the plastic wings were folded together and placed into the end of the vaginoscope. We then liberally applied sterile KY Jelly to the scope and inserted it into the deer’s vagina to the point where the mark on the applicator was reached. The alligator forceps, which extended through the vaginoscope to hold the VIT, was held firmly in place while the scope was pulled out from the vagina. This procedure pushed the VIT out of the scope into the vagina, and the plastic wings spread apart to hold the transmitter in place. The transmitter antenna was typically flush with the vulva, but on occasion extended up to 1 cm beyond the vulva. The tip of the antenna was encapsulated in a wax bead to protect the deer. Neonate Fawn Capture During June we relocated each of the radio-collared does having a VIT each morning using aerial and ground telemetry. Flights began at 0530 hr and were usually completed by 1000 – 1100 hrs. The early flights were crucial for detecting fast signals because shed VITs could exceed 90 °F by mid-day if shed in the open, which caused them to switch back to a slow (“pre-birth”) pulse. When a fast (“postpartum”) pulse rate was detected, we located the VIT from the ground to determine whether it was shed at the birth site. If the transmitter was located at the birth site, we identified whether any fawn(s) were stillborn. If the fawn(s) were no longer present at the birth site, or could not be found in the vicinity of the birth site, we located the radio-collared doe and searched for fawns at her location. All personnel involved wore surgical gloves to help minimize human scent when handling fawns. For each doe, we attempted to locate each of her fawns and document whether any fawns were stillborn. We attempted to account for each doe’s fetuses in order to quantify in utero fetal survival from February to birth. We placed a drop-off radio-collar on each live fawn; radio collars were constructed with elastic neck-band 30 �material to facilitate expansion. Hole-punched, leather tabs extended from the end of the elastic and from the transmitter for attachment purposes. Collars were made temporary by cutting the leather tab extending from the elastic and reattaching the leather with latex tubing, which caused the collars to shed from the animal >6 months post-capture. For each fawn, mass and hind foot length were recorded, and a nasal swab sample was collected to screen for Bovine Viral Diarrhea. We then recorded basic vegetation characteristics of the birth site and promptly exited the site. We also routinely located and attempted to capture fawns from treatment and control radiocollared does not having VITs to help achieve our targeted sample size. Each of these does had been previously captured during the research, and were present on either the treatment or control experimental unit during winter. Measurement of Survival Rates and Fawn:Doe Ratios We measured survival rates by radio-monitoring collared deer from the ground and air to determine fate (live/mortality). We also attempted to determine the cause of each mortality, with a primary goal of distinguishing between predation and non-predation mortality causes. Deer were radiomonitored from the ground on a daily basis throughout the year and from the air on approximately a biweekly basis. We were able to detect signals from nearly all radio-collared deer each day during winter, which typically allowed us to arrive at mortality sites within 24 hours of the mortality event. During summer and migration periods, deer were distributed widely and thus were more difficult to radiomonitor. All radio-collared neonates were checked daily throughout the summer and fall, whereas some adult and yearling deer could not be ground-monitored on a routine basis. In result, we typically located neonate mortalities within 24 hours of death, but some adult deer mortalities were not detected for several days, or on rare occasion, for one or more weeks. Fresh, intact neonate carcasses were collected and submitted to the Colorado Division of Wildlife’s Wildlife Health Laboratory or the Colorado State University Diagnostic Laboratory for necropsy and tissue analyses. Fresh, intact adult and 6-month old fawn carcasses were also submitted for laboratory necropsy when feasible. Field necropsies were performed on all other deer mortalities, and when appropriate, tissue samples were collected and submitted for analysis. Each winter we used the radio-collared does to measure fawn:doe ratios in each experimental unit. The resulting fawn:doe ratio is a measurement of the previous year’s treatment effect. We measured fawn:doe ratios using 2 techniques: (1) We located the sample of radio-collared does in each experimental unit from a fixed-wing airplane, and used the set of locations to define boundaries for the experimental unit. Shortly after (i.e. 1-2 days), we used a helicopter to systematically fly the defined unit and classify all deer groups encountered. For each group, we documented whether a radio-collared doe was present. (2) We located each radio-collared doe by radio telemetry from the ground. The group of deer with the collared doe was counted and classified by age and sex. Both methods were employed to gather as much information as possible to determine whether there was a treatment effect. The “true” value cannot be measured perfectly because of the inherent biases and potential sources of error associated with each technique. Thus, by employing both techniques, we had a greater chance of fully understanding whether the treatment caused an effect. Treatment Delivery Deer nutrition was enhanced in the treatment area by providing a safe, pelleted supplemental feed. The supplemental feed was developed through extensive testing with both captive and wild deer (Baker and Hobbs 1985, Baker et al. 1998), and has been safely used in both applied research and management projects. Pellets were distributed daily using 4wd pickup trucks, ATVs, and snowmobiles on primitive roads throughout the experimental unit to provide a food source for the entire deer population in the treatment unit. Each 50lb. bag of pellets was carried ≤200m from the vehicle and distributed by hand in approximately 20-30 small piles of feed in a linear fashion. Numerous bags were 31 �distributed in successive order allowing us to create linear lines of feed that spanned most of the treatment area, which prevented animals from concentrating in any single location. This feeding technique also prevented dominant animals from restricting access to the food supply because of the large area over which pellets were distributed. We supplied pellets ad libitum where a small residual remained when the next day’s ration was provided. Collared deer were closely monitored to ensure that treatment deer remained in the experimental unit and actually consumed the feed, and to make sure that non-treatment deer remained in the control unit, which they did. The few treatment adult does that moved away from the treatment unit were withdrawn from the sample for purposes of measuring treatment effects. However, to avoid any biases, all 6-month old fawns captured in the treatment unit were included in survival analyses regardless of whether they accessed the supplement or not. This was because some fawns died shortly after capture (e.g. 2-3 weeks), before we could document whether they had access to the feed. Also, very few fawns that survived more than 2-3 weeks moved away from the treatment unit. The pelleted ration was commercially produced in the form of 2×1×0.5-cm wafers (Baker and Hobbs 1985). Feed constituents (i.e. digestibility, protein, gross energy etc.) vastly exceeded those of typical winter range deer diets; exact constituent values are provided by Baker et al. (1998). When provided ad libitum, the feed should have allowed deer to meet or exceed nutritional requirements for growth and maintenance (Ullrey et al. 1967, Verme and Ullrey 1972, Thompson et al. 1973, Smith et al. 1975, Baker et al. 1979, Holter et al. 1979). The basis for feeding such high quality pellets was to ensure that the treatment (enhanced nutrition) was effectively delivered to the deer. Our intent was not to determine the exact level of nutrition necessary to increase fawn recruitment, but rather to determine if nutrition is a limiting factor to recruitment. If nutrition is in fact limiting, we will rely on habitat manipulation treatments to evaluate what exactly can be done via management to increase fawn survival and recruitment. Statistical Methods A preliminary fawn:doe ratio analysis was completed using PROC MIXED in SAS (SAS Institute 1997). We used a reduced model with experimental unit as the independent variable; we considered experimental unit as a fixed effect and radio-collared does within an experimental unit as random effects. Survival rates were calculated using a Kaplan-Meier survival analysis (Kaplan and Meier 1958, Pollock et al. 1989), and contrasted among experimental units and sexes using a chi-square analysis. For neonate survival analyses, we used a common entry date because a staggered entry would have biased survival rates low due to early mortalities that occurred before most of the sample was captured. We modeled overwinter fawn survival with a logistic regression model using PROC LOGISTIC in SAS (SAS Institute 1989a); model selection was performed using Akaike’s Information Criterion (AIC) (Burnham and Anderson 1998). Survival was modeled as a function of the nutrition enhancement treatment, sex, year, and capture mass. We used a general linear model in PROC GLM in SAS (SAS Institute 1989b) to test for differences in estimated percent body fat between treatment and control adult does and a multivariate model to test for differences in T4, FT4, T3, and FT3 thryoid hormones between treatment and control does. We then used PROG REG (SAS Institute 1989b) to evaluate the relationship between estimated percent body fat and serum thyroid hormone concentrations. We analyzed fetus survival directly with a binomial survival rate for the subset of fetuses with known fates. We also indirectly analyzed fetus survival by comparing the February fetus rate with the number of live newborn fawns/doe observed in June using a change-in-ratio estimator (White et al. 1996). Other results in this report are presented as data summaries incorporating means and standard errors, or in some cases, raw data values. These results are incomplete and preliminary, and should be treated as such. 32 �RESULTS AND DISCUSSION Deer Capture During November and December 2000-2003, we captured and radio-collared 139 adult female mule deer evenly distributed among the treatment and control units. We also captured and radio-collared 241 6-month-old fawns during November and December 2001-2003 (40 fawns/unit/year). Due to budgeting constraints, we were unable to radio-collar 6-month old fawns during 2000. We captured an additional 154 adult females during late February and early March 2002-2004 and equipped them with radio collars and VITs. During June 2002-2004, we captured and radio-collared 276 newborn fawns from radio-collared adult females. Thus, the following results are based upon radio-monitoring of 810 individual mule deer evenly distributed among treatment and control units during November 2000-June 2004. Treatment Delivery 2000-01 From December 15, 2000, through April 19, 2001, we distributed 88 tons of the pelleted ration. For most of the winter and spring, on average, we distributed 0.85 tons of feed each day throughout 22 feeding sites across the 2.3 mi2 treatment unit. Deer were fed ad libitum because there was always residual feed remaining the next day during the feeding routine. Each sack was distributed in approximately 20-30 distinct, small piles, resulting in >1000 small piles of feed throughout the treatment unit. This effort allowed deer to effectively access the feed in small groups, and no aggression was ever observed among deer seeking access to the feed. By distributing the feed in this manner, we were able to avoid the negative aspects associated with large-scale feeding operations. Deer adapted to the pelleted supplement right away and utilized it extensively throughout the winter. We continually monitored deer use of the feed from ground observation points, where we obtained 440 visual observations of radiocollared does consuming the feed. These observations, coupled with daily radio-monitoring and periodic aerial relocations, indicate 32 of the 37 radio-collared treatment does spent the entire winter and spring within the boundaries of the treatment unit and received the supplement on a daily basis. Mark-resight population estimates from March helicopter (489 deer, SE = 62) and ground (494 deer, SE = 81) surveys, coupled with feed consumption, indicate we fed roughly 450 to 500 deer during most of the winter and spring. Feed consumption declined coincident with spring green-up, although deer continued to use the feed through mid-late April, at which point they began migrating to summer range. We also fed approximately 25 to 30 elk, but the elk did not affect deer access to the feed. Deer in the control experimental unit did not receive feed or any other treatment. Based on helicopter mark-resight surveys, the deer density in the treatment unit in December was 120 deer/mi2 (SE = 9), but increased shortly after and was 213 deer/mi2 (SE = 27) in March. Deer densities in the control unit changed little from 83 deer/mi2 (SE = 12) in December to 101 deer/mi2 (SE = 14) in March. 2001-02 From December 15, 2001, through April 25, 2002, we distributed 194 tons of the supplement throughout the treatment unit. For most of the winter and spring, we distributed 2.0-2.1 tons of feed each day. The dramatic increase in supplement distribution from the previous year occurred because a large number of elk descended into the Uncompahgre Valley during mid-late fall/early winter. Elk arrived in unusually large numbers throughout much of the valley prior to the onset of treatment delivery. Once feeding was initiated, approximately 300-500 elk adapted to the feed and remained in or around the 2.3 mi2 treatment unit throughout most of the winter. Given myriad logistical and budgetary constraints, 2.1 tons was the maximum amount of feed we could routinely deliver on a daily basis. Feed was not delivered ad libitum to all deer and elk in the treatment unit throughout the winter because residual feed was rarely observed during the next day’s 33 �distribution. However, daily field observations indicated most deer approached ad libitum consumption of the supplement. In contrast to the previous winter, deer were waiting for the daily supplement to arrive each morning. Deer then consumed the supplement immediately after it was distributed. Elk were rarely observed utilizing the feed until late morning or afternoon, and elk continued to forage in fields below the treatment unit, whereas deer did not. We observed numerous radio-collared deer consuming the pelleted supplement each day; not all of these observations were recorded because of time constraints with distributing the feed. Given this time limitation, we still recorded 818 observations of radio-collared deer consuming the supplemental feed (497 collared doe observations and 321 collared fawn observations). Most days, >100 and sometimes 200-300 deer were observed utilizing the pellets during the course of distributing the supplement. These observations rarely included elk; thus, deer-elk competition was minimized because of temporal differences in feeding, and deer clearly had first access to the feed. 2002-03 Beginning December 2002, we switched the treatment and control units consistent with the crossover experimental design. From December 15, 2002, through April 30, 2003, we distributed 97 tons of the supplement throughout the new treatment unit, which had served as the control unit the previous 2 years. The supplement was distributed daily throughout 29 sites over a larger area (~7 mi2) than the first 2 years of research because of the greater size of the experimental unit and broader distribution of radiocollared deer. Residual feed was always present throughout the winter, thus deer were fed ad libitum. Only small groups of elk periodically accessed the supplement, and did not affect deer access. We obtained 286 observations of radio-collared deer consuming the supplement, which were difficult to obtain because the supplement was spread out over a large area and only a single feed site could be observed at any given moment. We also used daily ground radio-monitoring and periodic aerial relocations to document deer access to the supplement. 2003-04 From December 10, 2003, through April 30, 2004, we distributed 197 tons of the supplement throughout the treatment unit. The increase in supplement distribution occurred because of an increase in elk on the upper portion of the experimental unit. However, unlike winter 2001-02, residual feed was present throughout the winter and deer were fed ad libitum. By targeting a portion of the daily feed distribution to elk, we restricted elk to the upper extent of the deer winter range for most of the winter. Thus, elk had a minimal affect on deer access to the supplement. We obtained 413 observations of radiocollared deer consuming the supplement. As before, we also used daily ground radio-monitoring and periodic aerial relocations to document deer access to the supplement. Body Condition Estimated percent body fat of adult does during late February and early March, 2002–2004, was significantly higher for treatment deer than control deer (F1, 148 = 153.41, P < 0.001). Over all years combined, mean predicted body fat was 9.8% (SE = 0.36) for treatment adult does and 4.3% (SE = 0.26) for control does. The interaction of experimental unit × year for predicted body fat was also significant (F2, 148 = 14.39, P < 0.001). This interaction occurred because the difference in body fat between treatment and control deer was greater during 2003 than during 2002 or 2004. Mean predicted body fat was 8.2% (SE = 0.92) for treatment adult does and 5.0% (SE = 0.71) for control does during 2002, and 9.0% (SE = 0.53) for treatment does and 4.7% (SE = 0.36) for control does during 2004. The difference was greater during 2003, where mean predicted body fat was 11.7% (SE = 0.35) for treatment does and 3.4% (SE = 0.35) for control does. The body fat estimates reported here should accurately reflect deer, but may be further refined in the future as additional research provides more data on the relationship between body condition indices and estimated percent body fat. Serum thyroid hormone concentrations, measured during 2003 and 2004, were higher in treatment does than control does (F4, 108 = 46.59, P < 0.001) (Table 1). Hormone concentrations also 34 �varied between years (F4, 108 = 14.21, P < 0.001), but the experimental unit × year interaction was not significant (F4, 108 = 1.68, P = 0.160). Thus, each year thyroid hormone concentrations were higher in treatment does than control does. T4 was the most important thyroid hormone in describing the canonical variable for differences between treatment and control does (1.04*T4 − 0.02*T3 + 0.77*FT4 – 0.17*FT3). As expected, there was a high partial correlation between T4 and FT4 (r = 0.67, P < 0.001) and between T3 and FT3 (r = 0.60, P < 0.001), which has been documented previously (Watkins et al. 1983). When treated as 4 separate ANOVAs, T4 (F1, 111 = 165.97, P < 0.001), FT4 (F1, 111 = 144.37, P < 0.001), T3 (F1, 111 = 13.84, P < 0.001), and FT3 (F1, 111 = 8.26, P = 0.005) were significantly higher in treatment does than control does. Given these results, we evaluated the relationship between T4 concentrations and estimated percent body fat (derived from ultrasound and BCS indices) using a simple linear regression model (% Fat = −3.122 + 0.090*T4, r2 = 0.52, P < 0.001). Similar correlations between T4 and actual percent body fat during mid-late winter have been previously documented for white-tailed deer and elk (Watkins et al. 1991, Cook et al. 2001). Table 1. Total thyroxine (T4) and total tri-iodothyronine (T3) concentrations (nmol/l), and free T4 (FT4) and free T3 (FT3) concentrations (pmol/l), measured during late February in adult female mule deer occupying a nutrition enhancement treatment unit and a control unit on the Uncompahgre Plateau in southwest Colorado, 2003-04. Thyroid Hormone T3 (SE) FT3 (SE) 146.6 (3.53) FT4 (SE) 30.0 (1.27) 1.65 (0.058) 4.10 (0.130) Control 92.3 (3.56) 17.1 (0.65) 1.42 (0.080) 3.71 (0.210) Treatment 131.9 (4.48) 24.8 (1.39) 2.08 (0.075) 4.21 (0.154) Control 90.0 (3.54) 12.5 (0.59) 1.70 (0.104) 3.60 (0.188) Year Exp. Unit T4 (SE) 2003 Treatment 2004 Fetus Survival and Pregnancy/Fetus Rates We began measuring fetus survival in 2002 as part of our effort to capture and radio-collar newborn fawns born from radio-collared does. Similar numbers of stillborns were observed between treatment and control does during both 2002 and 2003, so fetus survival estimates for those years are not differentiated by experimental unit. In February-March 2002, 36 of 38 adult does captured were pregnant, thus the pregnancy rate was 0.95 (SE = 0.036). We measured an average of 1.80 fetuses/doe (SE = 0.10, n = 36), which included 1.77 fetuses/doe (SE = 0.14, n = 18) in the treatment unit and 1.83 fetuses/doe (SE = 0.15, n = 18) in the control unit. During June 2002, we determined the fate of all fetuses (live or stillborn) from only 14 of the 36 VIT does, largely because of a high VIT battery failure rate. The survival rate of fetuses (n = 22) from these 14 does was 0.86 (SE = 0.073). We also assessed fetus survival using a change-in-ratio estimator between the fetal rate measured in February-March and the observed number of live fawns/doe postpartum in June. In June 2002, considering all does (n = 43) that we located any fawn from, whether live or stillborn, we observed 1.42 (SE = 0.11) live fawns/doe postpartum. This rate should represent a conservative estimate of live fawns/doe postpartum because we inevitably failed to locate all live fawns from each doe. In other words, this estimate would treat any unaccounted fetuses (from the February measurement) as if they were stillborns. For radio-collared does that did not have VITs, and thus we did not have a winter fetus rate measurement, singletons would infer that either the deer only had 1 fetus, or that the other fetus died. It is likely that some of these singletons had a twin that we did not locate. This equates to a conservative fetus survival rate estimate of 0.79 (SE = 0.18). 35 �In February-March 2003, 58 of 63 adult does captured were pregnant, resulting in a pregnancy rate of 0.92 (SE = 0.034). Critical personnel and equipment for measuring fetus rates were not continuously available due to capture delays associated with helicopter mechanical problems. Some of the deer fetus counts were performed by inexperienced observers without optimum ultrasound equipment. VITs worked very well, though, allowing us to determine fetus numbers at parturition for many of the deer. Thus, we determined winter fetus rates by using the greatest fetus count for each individual deer, whether obtained using ultrasound during February-March or by locating newborn fawns and stillborns at birthsites during June. We were unable to determine a fetus count for 8 treatment deer because only pregnancy was established with ultrasound and no birthsite assessments were possible in June. These 8 deer were removed from the fetus rate estimates. Of the 50 deer where a fetus count was obtained, 5 were yearlings (2 treatment yearlings, 3 control yearlings). We measured 1.74 fetuses/doe (SE = 0.069, n = 50) overall including yearlings, and 1.82 fetuses/doe (SE = 0.066, n = 45) excluding yearlings. Fetus rates with yearlings included were 1.77 fetuses/doe (SE = 0.091, n = 22) in the treatment unit and 1.70 fetuses/doe (SE = 0.10, n = 28) in the control unit. During June 2003, we determined the fate of all fetuses (live or stillborn) from 33 of the 58 VIT does; the good success was based on VITs commonly being shed at birthsites. The survival rate of fetuses (n = 58) from these 33 does was 0.97 (SE = 0.024). In June 2003, incorporating all does (n = 71) that we located any fawn from, whether live or stillborn, we observed 1.49 (SE = 0.072) live fawns/doe postpartum. Using the change-in-ratio estimator described above, this results in an overall conservative fetus survival rate estimate of 0.86 (SE = 0.15). In February 2004, the overall pregnancy rate was 0.94 (SE = 0.029, n = 66) and the fetus rate was 1.97 fetuses/doe (SE = 0.053, n = 60), which included 4 yearlings. Excluding yearlings, the fetus rate was 2.00 fetuses/doe (SE = 0.051, n = 56). Fetus rates were 1.90 fetuses/doe (SE = 0.074, n = 30) in the treatment unit and 2.03 fetuses/doe (SE = 0.076, n = 30) in the control unit with yearlings included, and 1.93 (SE = 0.069, n = 29) in the treatment unit and 2.07 (SE = 0.074, n = 27) in the control unit with yearlings excluded. We determined the fate of all fetuses (live or stillborn) from 31 of the 60 VIT does. The overall fetus survival rate was 0.90 (SE = 0.040, n = 58). Different from 2002 or 2003, each of these stillborns were from control does. The survival rate of control fetuses was 0.76 (SE = 0.085, n = 25) as compared to a survival rate of 1.00 (n = 33) for treatment fetuses. Using data from all does (n = 82) in which we located any fawn, the conservative change-in-ratio fetus survival estimate was 0.79 (SE = 0.13) overall, 0.88 (SE = 0.17) for treatment deer, and 0.69 (SE = 0.14) for control deer. Neonatal Survival/Fawn:Doe Ratios 2001 In December 2000, at the beginning of the study and prior to the first year’s treatment delivery, fawn:doe ratios were similar in the 2 experimental units. Pre-treatment fawn:doe ratios were 52.6 fawns:100 does (SE = 5.3) in the treatment unit, and 51.6 fawns:100 does (SE = 5.0) in the control unit. In late December 2001 and early January 2002, following the first year’s treatment, we conducted 2 age classification helicopter surveys in the treatment and control units. On 12/23/01, we observed 52.8 fawns:100 does (SE = 6.7) in the treatment unit, and 36.7 fawns:100 does (SE = 3.8) in the control unit. On 1/8/02, we observed 54.7 fawns:100 does (SE = 6.6) in the treatment unit, and 50.5 fawns:100 does (SE = 6.0) in the control unit. During December 2001 – February 2002, we obtained fawn:doe ratio estimates from ground observations of radio-collared deer groups for both treatment and control deer. This survey resulted in 61.2 fawns:100 does (SE = 7.8) in the treatment unit, and 74.5 fawns:100 does (SE = 8.5) in the control unit, although the result was not statistically significant (t74 = 1.16, P = 0.249). The fawn:doe ratio results are conflicting, and clearly do not provide evidence that there was any treatment effect. In short, we concluded that the nutrition enhancement treatment did not cause an increase in neonatal production and survival during 2001. However, our results, in conjunction with a December estimate of 64 fawns:100 does for the entire Uncompahgre deer population (B.E. Watkins, 36 �unpublished), indicate fawn production and survival was good during 2001. The observed fawn:doe ratios coupled with overwinter fawn survival and annual adult survival rates indicate the deer population was increasing. Considering the past 1-2 decades, this was an atypically good year for the Uncompahgre deer population. 2002 During June – December 2002, following the second year’s treatment, we measured neonate survival directly using radio-collared fawns; however, sample sizes were based on a technique assessment of VITs and were relatively small for contrasting treatment and control survival of neonates (Bishop et al. 2002). Treatment fawn survival was 0.613 (SE = 0.115, n = 29) and control fawn survival was 0.511 (SE = 0.108, n = 25). In late December 2002 and early January 2003, we once again conducted 2 age classification helicopter surveys in the treatment and control units. On 12/31/02, we observed 91.9 fawns:100 does (SE = 8.4) in the treatment unit, and 52.2 fawns:100 does (SE = 6.9) in the control unit. On 1/21/03, we observed 52.6 fawns:100 does (SE = 6.4) in the treatment unit, and 36.8 fawns:100 does (SE = 3.9) in the control unit. The combined helicopter survey data indicated 68.1 fawns:100 does (SE = 5.6) in the treatment unit and 42.8 fawns:100 does (SE = 3.5) in the control unit. Oppositely, fawn:doe ratio estimates from ground classifications of doe groups during December 2002 – February 2003 were 47.7 fawns:100 does (SE = 6.3) in the treatment unit, and 63.4 fawns:100 does (SE = 7.5) in the control unit (t108 = 1.61, P = 0.110). As in 2001, fawn:doe ratio results were conflicting. Helicopter survey data varied between 2 different flights, but consistently indicated a treatment effect. Ground classification data did not indicate a treatment effect. Also, survival data combined with age ratio data indicate neonate production and survival was reasonably favorable during 2002, and not indicative of the low fawn recruitment observed during the late 1980’s and 1990’s. 2003 During June 2003, we captured and radio-collared 103 newborn fawns born from treatment and control radio-collared does (55 treatment fawns, 48 control fawns). The VITs worked well; we captured fawns from 41 of the 54 does fitted with VITs. Treatment fawn survival (June – Dec) was 0.624 (SE = 0.082) and control fawn survival was 0.483 (SE = 0.093). Final standard errors were larger than expected because a number of fawns shed collars prematurely when crossing fences during fall migration. Using helicopter surveys, we measured 62.4 fawns:100 does (SE = 5.3) in the treatment unit and 50.0 fawns:100 does (SE = 4.9) in the control unit. Estimates from ground classifications of doe groups were 68.0 fawns:100 does (SE = 7.6) in the treatment unit and 62.1 fawns:100 does (SE = 7.6) in the control unit. Age ratio estimates from the helicopter and the ground were more consistent during 2003 than in past years. Overall, observed fawn:doe ratios were consistent with treatment and control fawn survival rates measured from June to December. 2002-03 Survival rate point estimates were very similar during 2002 and 2003. Combined over both years, treatment survival (S(t) = 0.620, SE = 0.067) was higher (P = 0.189) than control survival (S(t) = 0.493, SE = 0.070). The high censor rate due to shed collars during fall affected the p-value. Neonate survival through July 15, 2002 and 2003, was significantly higher (P = 0.006) for treatment fawns (S(t) = 0.833, SE = 0.041) than control fawns (S(t) = 0.634, SE = 0.057). We are currently measuring 2004 neonate survival rates, which will be necessary for final interpretations as to the effectiveness of the treatment. Our results from 2001 and 2002 emphasize the inherent difficulties and biases associated with precisely measuring fawn:doe ratios, particularly in this research study. Ratios obtained from helicopter surveys were based on 2 short-duration flights/unit/year over spatially small units. Helicopter surveys were complicated by high deer densities in heavy cover, making both deer detection and fawn:doe classifications a considerable challenge. There is a variety of potential biases that may have affected the 37 �helicopter surveys, including differential sightability of does and fawns, double classification of some deer, and incorrectly classifying yearling bucks with small antlers. Ground fawn:doe ratio observations of radio-collared doe groups were made using spotting scopes and field glasses, where we commonly studied the deer for some time. Incorrect classifications during these surveys were likely minimal. For example, small-antlered yearling bucks (e.g. 3 – 6” spikes) were detected from the ground, whereas they were undoubtedly missed on occasion during helicopter surveys. We also obtained repeated observations for some of the radio-collared doe groups from the ground. The main potential bias affecting ground fawn:doe classifications was how observations were made. Many of the ground classifications in the Shavano Valley experimental unit were made by radio-tracking does during the day. On the other hand, a majority of ground classifications in the Colona experimental unit were based on observing deer groups as they entered openings to feed during the late afternoon. Our age ratio results were more consistent during 2003. Deer were not as concentrated during helicopter surveys, and unlike previous years, almost all of the ground classification data for the Colona experimental unit was obtained by radio-tracking does during the day. Given the inherent difficulties of measuring fawn:doe ratios in the 2 experimental units, and the lack of a clear indication as to the effectiveness of the treatment, we will only cautiously use fawn:doe ratios to make inferences regarding treatment effects. At the completion of the research, we will test whether enhanced winter nutrition of adult does improved newborn fawn survival based on a three-year model of the radio-collared neonate survival data. Neonate Mortality Causes During June − December of 2002 and 2003, 32 of 84 treatment fawns died: 8 – coyote predation, 2 – bear predation, 2 – felid predation, 3 – predation where the predator was undetermined, 9 – disease/starvation/ malnutrition, 1 – abandonment, 2 – trauma/injury, 1 – road-kill, 2 – unknown, and 2 – poached. The two poached fawns were censored from analyses evaluating the effect of the treatment. Converted to mortality rates based on the Kaplan-Meier survival analysis, 11.4% of all treatment fawns died from disease/starvation/malnutrition, 10.1% from coyote predation, 3.8% from predation where the predator was undetermined, 2.5% each from bear predation, felid predation, injury/trauma, and unknown causes, and 1.3% each from abandonment and road-kill. Simplified, 18.9% of all treatment fawns died from predation, 11.4% died from disease/starvation/malnutrition, and 7.6% died from other or unknown causes. During June – December of 2002 and 2003, 35 of 72 control fawns died: 12 – coyote predation, 4 – felid predation, 2 – bear predation, 1 – predation where the predator was undetermined, 11 – disease/starvation/ malnutrition, 1 – trauma/injury, and 4 – unknown. Converted to mortality rates based on the Kaplan-Meier survival analysis, 17.4% of all control fawns died from coyote predation, 15.9% died from disease/starvation/malnutrition, 5.8% each from felid predation and unknown causes, 2.9% from bear predation, and 1.4% each from trauma/injury and predation where the predator was undetermined. Simplified, 27.5% of all control fawns died from predation, 15.9% from disease/starvation/malnutrition, and 7.2% from other or unknown causes. In summary, mortality rates due to predation and disease/starvation/malnutrition were lower for treatment fawns than control fawns. Overwinter Fawn Survival and Mortality Causes During winter 2001-02 (Dec 10, 2001 – June 15, 2002), the survival rate of fawns was significantly greater (χ21 = 13.216, P < 0.001) in the treatment unit (S(t) = 0.865, SE = 0.056) than in the control unit (S(t) = 0.510, SE = 0.080). Similarly, in 2002-03 (Dec 10, 2002 – June 15, 2003), the overwinter survival rate of fawns was significantly greater (χ21 = 5.734, P = 0.017) in the treatment unit (S(t) = 0.900, SE = 0.047) than in the control unit (S(t) = 0.691, SE = 0.074). Again in 2003-04 (Dec 10, 2003 – June 15, 2004), the overwinter survival rate of fawns was significantly greater (χ21 = 3.852, P = 0.050) in the treatment unit (S(t) = 0.920, SE = 0.045) than in the control unit (S(t) = 0.756, SE = 0.067). Combining survival data across all 3 winters, treatment fawn survival (S(t) = 0.895, SE = 0.029) was 38 �higher (χ21 = 18.781, P < 0.001) than control fawn survival (S(t) = 0.655, SE = 0.044) (Fig. 4). The treatment unit during winter 2001-02 became the control unit during winters 2002-03 and 2003-04, and vice versa. Thus, the overwinter survival treatment effect was replicated across each experimental unit. Combining all years of data, the best model of overwinter fawn survival (AICc = 207.65) included treatment (χ21 = 19.04, P < 0.001), early winter fawn mass (χ21 = 23.27, P < 0.001), and year (χ21 = 6.20, P = 0.045). The AIC model selection analysis emphasizes the importance of both the treatment effect as well as early winter mass of fawns, because any models without treatment or fawn mass were very poor (Table 2). Survival of fawns receiving the nutrition enhancement treatment was 0.24 higher than survival of control fawns during three mild to average winters, and surviving fawns averaged 3.5 kg heavier than fawns that died. Early winter mass of control fawns was slightly higher than that of treatment fawns (F1, 231 = 3.00, P = 0.085); thus the effect of the treatment was not confounded with fawn mass. Fawn mass was similar between winters as well (F2, 231 = 1.31, P = 0.273). The importance of early winter fawn mass as a predictor of overwinter survival has been documented previously (White et al. 1987, Bishop 1998, White and Bartmann 1998, Unsworth et al. 1999). In summary, the nutrition enhancement treatment improved overwinter fawn survival and thus yearling recruitment, and heavier fawns in each experimental unit had higher survival probabilities. Figure 4. Overwinter fawn survival (Dec 10 – June 15, 2001 – 2004) in a nutrition enhancement treatment unit (S(t) = 0.895, SE = 0.029) and a control unit (S(t) = 0.655, SE = 0.044) on the Uncompahgre Plateau, southwest Colorado. 39 �Table 2. Model selection results for a logistic regression analysis of overwinter mule deer fawn survival in southwest Colorado, 2001− 2004. Enhanced nutrition (Treatment) and early winter fawn mass were the critical predictors of survival. Model selection was performed using Akaike’s Information Criterion (AIC). # -2 Log Param ∆ Likelih eters AIC Model Name od (K) AIC AICc c Treatment + Year + Mass Treatment + Sex + Year + Mass Treatment + Sex + Year + Trt*Year + Mass Treatment + Sex + Mass 202.254 5 212.254 207.649 0 201.227 6 213.227 207.783 0.13 201.060 8 217.060 210.026 2.38 207.179 4 215.179 211.440 3.79 Treatment + Mass 208.556 3 214.556 211.712 4.06 Sex + Year + Mass 223.598 5 233.598 228.993 21.34 Treatment 235.739 2 239.739 237.816 30.17 Sex + Year 248.878 4 256.878 253.139 45.49 During winters 2001-04, 12 of 115 treatment fawns died: 5 from coyote predation, 3 from disease/illness, 2 from malnutrition, 1 from trauma/injury, and 1 unknown. Each of the 3 fawns that died from disease had adequate fat stores. At least one of these fawns died as a result of pneumonia. Converted to mortality rates based on the Kaplan-Meier survival analysis, 4.3% of all treatment fawns died from coyote predation, 2.6% from disease/illness, 1.7% from malnutrition, 0.9% from trauma/injury, and 0.9% from unknown causes. Simplified, 4.3% of all treatment fawns died from predation, 4.3% from disease/malnutrition, and 1.8% from other or unknown causes. During winters 2001-04, 41 of 120 control fawns died: 13 from coyote predation, 8 from mountain lion predation, 8 from malnutrition, 6 from unknown causes, 3 from predation where the predator was undetermined, 2 were road-killed, and 1 from trauma/injury. Converted to mortality rates based on the Kaplan-Meier survival analysis, 10.9% of all control fawns died from coyote predation, 6.7% from mountain lion predation, 6.7% from malnutrition, 5.0% from unknown causes, 2.5% from predation where the predator was undetermined, 1.7% from road-kill, and 0.8% from trauma/injury. Simplified, 20.1% of all control fawns died from predation, 6.7% from malnutrition, and 7.5% from other or unknown causes. Most fawns killed by predators had little or no femur marrow fat remaining, indicating the predation was likely compensatory in nature. Adult Female Survival and Causes of Mortality During winter 2000-01 (Dec 1, 2000 – May 31, 2001), the adult doe survival rate in the treatment unit (S(t) = 0.968, SE = 0.032) was greater (χ21 = 2.649, P = 0.104) than the survival rate in the control unit (S(t) = 0.861, SE = 0.058). However, annual adult doe survival rates (Dec 1, 2000 – Nov 30, 2001) were similar among the treatment and control deer (Trt: S(t) = 0.839, SE = 0.066; Control: S(t) = 0.833, SE = 0.062; χ21 = 0.004, P = 0.947). We observed a similar result the following year. The 2001-02 overwinter adult doe survival rate in the treatment unit (S(t) = 0.942, SE = 0.030) was greater (χ21 = 3.116, P = 0.078) than survival in the control unit (S(t) = 0.848, SE = 0.044), yet annual adult doe survival was similar among treatment and control deer (Trt: S(t) = 0.824, SE = 0.049; Control: S(t) = 0.818, SE = 0.047; χ21 = 0.090, P = 0.764). Thus, mortalities of control deer occurred primarily during the winter months, while treatment does died primarily during the summer and fall months. 40 �During winter 2002-03, following the treatment cross-over, overwinter adult doe survival rates were similar among treatment and control deer (Trt: S(t) = 0.945, SE = 0.024; Control: S(t) = 0.924, SE = 0.028; χ21 = 0.360, P = 0.549). The main difference from the previous 2 years was that overwinter survival of adult does in the Shavano experimental unit increased in 2002-03 upon receiving the treatment. However, annual adult doe survival rates (Dec 1, 2002 – Nov 30, 2003) were higher (χ21 = 2.016, P = 0.156) for treatment does 0.888 (SE = 0.034) than control does 0.813 (SE = 0.041). The main difference from the previous 2 years was overwinter survival of adult does in the Shavano experimental unit increased in 2002-03 upon receiving the treatment. Summer-fall survival was similar in that Colona adult does had higher mortality rates than Shavano adult does. Thus, in 2002-03, there was no difference between survival rates of treatment and control adult does during winter but there was evidence of higher annual survival of treatment adult does. During winter 2003-04, overwinter adult doe survival rates were higher (χ21 = 3.843, P = 0.050) among treatment does (S(t) = 0.979, SE = 0.014) than control does (S(t) = 0.915, SE = 0.027). Thus far in 2004, annual adult doe survival rates (Dec 1, 2003 – 8/31, 2004) are 0.951 (SE = 0.021) for treatment does and 0.896 (SE = 0.029) for control does. Considering all years, the treatment has improved overwinter adult doe survival but had a relatively minor affect on annual survival. Considering only the past 2 years, there is evidence the treatment has had a positive affect on annual survival. Annual survival rates measured in this study align with expected survival based on other studies (Unsworth et al. 1999, B.E. Watkins, unpublished). During 2000-02, when the Colona experimental unit received the treatment and the Shavano experimental unit was the control, 16 treatment and 16 control does died. The 16 treatment does died from the following categories: 4 – road-killed, 3 – while giving birth, 3 – predation (undetermined predator), 2 – non-predation unknown (intact carcasses with no evidence of predation or scavenging), 1 – disease (chronic arthritis), 1 – mountain lion predation, and 2 – unknown. Predation was not a major mortality factor for treatment does, and a majority of mortalities were independent of nutrition (does were in good condition). The 16 control doe mortalities included the following causes: 5 – mountain lion predation, 3 – malnutrition, 2 – non-predation unknown, 1 – road-killed, 1 – bear predation, 1 – injury (fence), 1 – legal harvest, and 2 – unknown. Predation and malnutrition were the major mortality causes of control deer. Interestingly, during this 2-year period, we did not document any coyote predation on adult does. During Dec 2002 – August 2004, with Shavano as the treatment and Colona as the control, there have been 14 treatment doe mortalities: 5 – disease/infection, 5 unknown causes, 3 – coyote predation, and 1 – road-killed. As we saw during 2000-02, predation was not a major mortality factor for treatment does, and a majority of mortalities were independent of nutrition. There have been 26 control adult doe mortalities during this same time period: 7 – malnutrition/disease, 5 – road-kill, 4 – coyote predation, 4 – unknown causes, 3 – mountain lion predation, and 3 – non-predation unknown. Malnutrition, predation, and road-kill were the major mortality factors of control does during 2002-04. SUMMARY We successfully enhanced nutrition of deer occupying the treatment units. There was no evidence the treatment positively influenced fetus survival until 2004, when virtually all stillborn fetuses were from control adult does. We currently have evidence the treatment caused an increase in neonate survival; however, data collection is incomplete. The treatment caused a significant increase in overwinter fawn survival, which is where the greatest differences occurred between treatment and control deer. Overwinter adult doe survival increased as a result of the treatment, but annual survival was more similar among treatment and control adult does. Results reported here are based on preliminary analyses, and in some cases, incomplete data sets. Final analyses will be conducted once data collection is complete. 41 �LITERATURE CITED Andelt, W. F., T. M. Pojar, and L. W. Johnson. 2004. Long-term trends in mule deer pregnancy and fetal rates in Colorado. Journal of Wildlife Management 68:542-549. Baker, D. L., and N. T. Hobbs. 1985. Emergency feeding of mule deer during winter: tests of a supplemental ration. Journal of Wildlife Management 49:934-942. Baker, D. L., D. E. Johnson, L. H. Carpenter, O. C. Wallmo, and R. B. Gill. 1979. Energy requirements of mule deer fawns in winter. Journal of Wildlife Management 43:162-169. Baker, D. L., G. W. Stout, and M. W. Miller. 1998. A diet supplement for captive wild ruminants. Journal of Zoo and Wildlife Medicine 29:150-156. Ballard, W. B, D. Lutz, T. W. Keegan, L. H. Carpenter, and J. C. deVos, Jr. 2001. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin 29:99-115. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bishop, C. J. 1998. Mule deer fawn mortality and habitat use, and the nutritional quality of bitterbrush and cheatgrass in southwest Idaho. Thesis, University of Idaho, Moscow, Idaho, USA. Bishop, C. J., D. J. Freddy, and G. C. White. 2002. Effects of enhanced nutrition of adult female mule deer on fetal and neonatal survival rates: a pilot study to address feasibility. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R, Job Final Report. Fort Collins, Colorado, USA. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, Nebraska, USA. Cook, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain elk. Thesis, University of Idaho, Moscow, Idaho, USA. Cook, R. C., and J. G. Cook. 2002. An informal training guide to condition evaluation in elk and deer. National Council for Air and Stream Improvement, Unpublished Report. Cook, R. C., J. G. Cook, D. L. Murray, P. Zager, B. K. Johnson, and M. W. Gratson. 2001. Development of predictive models of nutritional condition for Rocky Mountain elk. Journal of Wildlife Management 65:973-987. Gill, R. B., T. D. I. Beck, C. J. Bishop, D. J. Freddy, N. T. Hobbs, R. H. Kahn, M. W. Miller, T. M. Pojar, and G. C. White. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Denver, Colorado, USA. Holter, J. B., H. H. Hayes, and S. H. Smith. 1979. Protein requirement of yearling white-tailed deer. Journal of Wildlife Management 43:872-879. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 53:457-481. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. SAS Institute. 1989a. SAS/STAT® user’s guide, version 6, fourth edition. Volume 1. SAS Institute, Cary, North Carolina, USA. SAS Institute. 1989b. SAS/STAT® user’s guide, version 6, fourth edition. Volume 2. SAS Institute, Cary, North Carolina, USA. SAS Institute. 1997. SAS/STAT® Software: Changes and Enhancements through Release 6.12. SAS Institute, Cary, North Carolina, USA. 42 �Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep- trapping techniques. Wildlife Society Bulletin 6:159-163. Smith, S. H., J. B. Holter, H. H. Hayes, and H. Silver. 1975. Protein requirement of white-tailed deer fawns. Journal of Wildlife Management 39:582-589. Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. Stephenson, T. R., K. J. Hundertmark, C. G. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717-722. Stephenson, T. R., J. W. Testa, G. P. Adams, R. G. Sasser, C. G. Schwartz, and K. J. Hundertmark. 1995. Diagnosis of pregnancy and twinning in moose by ultrasonography and serum assay. Alces 31:167-172. Thompson, C. B., J. B. Holter, H. H. Hayes, H. Silver, and W. E. Urban, Jr. 1973. Nutrition of whitetailed deer. I. Energy requirements of fawns. Journal of Wildlife Management 37:301-311. Ullrey, D. E., W. G. Youatt, H. E. Johnson, L. D. Fay, and B. L. Bradley. 1967. Protein requirement of white-tailed deer fawns. Journal of Wildlife Management 31:679-685. Unsworth, J. W., D. F. Pac, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. Verme, L. J., and D. E. Ullrey. 1972. Feeding and nutrition of deer. Pages 275-291 in D. C. Church, editor. Digestive physiology and nutrition of ruminants. Volume 3 – Practical Nutrition. D. C. Church, Corvallis, Oregon, USA. Watkins, B. E., D. E. Ullrey, R. F. Nachreiner, and S. M. Schmitt. 1983. Effects of supplemental iodine and season on thyroid activity of white-tailed deer. Journal of Wildlife Management 47:45-58. Watkins, B. E., J. H. Witham, D. E. Ullrey, D. J. Watkins, and J. M. Jones. 1991. Body composition and condition evaluation of white-tailed deer fawns. Journal of Wildlife Management 55:39-51. White, G. C., and R. M. Bartmann. 1998. Effect of density reduction on overwinter survival of freeranging mule deer fawns. Journal of Wildlife Management 62:214-225. White, G. C., R. A. Garrott, R. M. Bartmann, L. H. Carpenter, and A. W. Alldredge. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Management 51:852-859. White, G. C., A. F. Reeve, F. G. Lindzey, and K. P. Burnham. 1996. Estimation of mule deer winter mortality from age ratios. Journal of Wildlife Management 60:37-44. Prepared by _______________________ Chad J. Bishop, Wildlife Researcher 43 �44 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Task No. Colorado W-153-R 3002 RMNP Federal Aid Project: : : : : : Cost Center 3430 Mammals Research Elk Conservation Technical Support for Elk and Vegetation Management Environmental Impact Statement for Rocky Mountain National Park Period Covered : July 1, 2003 - June 30, 2004 Authors : D. L. Baker, M. A. Wild, M. D. Hussain, R. L. Dunn, T. M. Nett Personnel: E. Jones, J. Ritchie, A. Mitchell, X. Sha, M. Allen, J. Powers. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Practical application of fertility control technology in free-ranging wild ungulates requires remote delivery of a safe and efficacious contraceptive agent. The objective of this investigation was to evaluate the potential of a remotely delivered, sustained release, biodegradable implant formulation of leuprolide acetate, to achieve reversible suppression of ovulation and fertility in female elk (Cervus elaphus nelsoni). Fifteen, captive adult female elk were randomly allocated to one of three experimental groups. Six elk were injected intramuscularly with a dart containing the implant formulation of leuprolide, and the remaining nine elk received the same formulation without leuprolide. We measured pregnancy rates, suppression of luteinizing hormone (LH) and progesterone concentrations, and reversibility of leuprolide treatments during 1 August 2002 to 3 September 2003. The sustained release implant formulation, remotely administered by dart, resulted in decreased concentrations of LH and progesterone, temporary suppression of ovulation and steroidogenesis, and effective contraception (100%) for one breeding season. These results extend the potential for practical application of the leuprolide implant as contraceptive agent in female elk, where in the absence of such technology, wild elk must first be captured and restrained prior to treatment. 45 �JOB PROGRESS REPORT TECHNICAL SUPPORT FOR ELK AND VEGETATION MANAGEMENT ENVIRONMENTAL IMPACT STATEMENT FOR ROCKY MOUNTAIN NATIONAL PARK D. L. Baker, M. A. Wild, M. D. Hussain, R. L. Dunn, and T. M. Nett P. N. OBJECTIVE Conduct experiments with captive and free-ranging elk to evaluate fertility control as an management alternative for controlling elk populations in Rocky Mountain National Park (RMNP), Colorado. SEGMENT OBJECTIVES 1. 2. 3. Determine the effectiveness of a remotely delivered intramuscular leuprolide implant in preventing pregnancy in captive female elk. Determine the duration of effectiveness of remotely delivered leuprolide implant (if any) on luteinizing hormone (LH) and progesterone secretion in captive female elk. Determine the reversibility of remotely delivered leuprolide implant on infertility (if achieved) in captive female elk. INTRODUCTION Fundamental to practical application of contraceptives to wildlife, is a safe and effective antifertility agent that can be remotely delivered to the target species. To attain this goal, considerable research has focused on the development and testing of ballistic systems and controlled drug release formulations that can remotely administer contraceptive agents to wild ungulates (Kreeger, 1997). Contraceptive agents have been delivered via projectile dart or biodegradable implant to a variety of wild ungulate species including deer (Odocoileus spp.) (Turner et al., 1992; Jacobsen et al., 1995; DeNicola et al., 1997), elk (Cervus elaphus nannodes) (Shideler et al., 2002), wild horses (Equus caballus) (Kirkpatrick et al.,1990), burros (Equus asinus) (Turner et al., 1996), and elephants (Loxodonta africana) (Delsink et al., 2002). However, to date, no contraceptive agent that possess all of the desired attributes (Fagerstone et al., 2002) has been developed for remote delivery. The use of GnRH agonist implants to suppress short-term ovarian follicular growth and ovulation are well documented for a number of species including cattle (McLeod et al., 1991, D’Occhio et al., 1996), sheep (McNeilly and Fraser,1987), monkeys (Fraser et al., 1987), and humans (Broekmans et al., 1996). However, few studies have established the efficacy of these agents for long-term suppression of ovarian activity and contraception (Trigg et al., 2001; Baker et al., 2002, 2004; D’Occhio et al., 2002) and to our knowledge, none have previously demonstrated effective contraception by dart delivery of the implant. In previous research, we administered gonadotropin releasing hormone (GnRH) agonist leuprolide acetate by hand injection to captive female elk (Cervus elaphus nelsoni) (Baker et al., 2002), and mule deer (Odocoileus hemionus hemionus) (Baker et al. 2004), as a sustained release injectable implant, and achieved 100 % infertility for one breeding season. The implant formulation consisted of 45 % w/w 75/25 poly (DL-lactide-co-glycolide) (PLG) polymer having an intrinsic viscosity of 0.20 dL/g dissolved in N-methyl-2-pyrrolidone (NMP) and containing 6 % w/w leuprolide in the polymer solution. This formulation was designed to release the drug for a period of 3 to 4 months after subcutaneous injection (Ravivarapu et al., 2000). 46 �In these previous studies, the leuprolide formulation was demonstrated to be highly effective when delivered subcutaneously, however, it’s not known if similar effectiveness can be achieved when administered as an intramuscular (IM) injection via dart. Differences in drug pharmacokinetics and metabolism between muscle and subcutaneous tissues could affect release dynamics of the implant and possibly decrease the antifertility properties of leuprolide. Therefore, the objectives of this experiment were to determine in captive female elk (1) the effectiveness of this remotely delivered intramuscular leuprolide implant in preventing pregnancy, (2) the duration of effects (if any) on luteinizing hormone (LH) and progesterone secretion, and (3) the reversibility of infertility (if achieved). MATERIALS AND METHODS Experimental animals During 1 August 2002 to 3 September 2003, we evaluated the effects of remotely delivered leuprolide formulation on pregnancy rates, luteinizing hormone (LH), and progesterone secretion in captive female elk. Controlled experiments were conducted with 15 adult females (2-14 years of age; 220 - 275 kg BW), two intact adult male elk (3 years of age; 350-400 kg BW), and one epididymectomized adult male elk (3 years of age; 340-375 kg BW) at the Colorado Division of Wildlife’s Foothills Wildlife Research Facility in Fort Collins, Colorado, USA. Captive elk used in this experiment were permanently maintained at this facility and were trained to repeated handling, weighing, blood sampling techniques, and isolation pens. When not involved in the periodic intensive sampling procedures required by this study, elk were maintained in fenced pastures (5 ha) containing native vegetation and fed a diet consisting of ad libitum quantities of grass-alfalfa hay, grain supplement, trace mineral block, and water. In an effort to induce normal cyclic ovulatory responses and synchronize estrus, we released an epididymectomized male elk with 15 seasonally anovulatory female elk on 20 July 2002 (McComb, 1987). Four weeks later (21 August) and prior to assigning elk to experimental treatments, we assessed the reproductive status of each female by: 1) manual rectal palpation of the reproductive tract to diagnose ovarian status and identify any abnormalities, and 2) measuring the responsiveness of pituitary gonadotropes to an exogenous dose of GnRH analog. Females showing evidence of reproductive tract abnormalities or suppressed gonadotrope function were excluded from the experiment. Experimental design Fifteen female elk were randomly assigned to one of three experimental groups. Six elk (group A) were injected with a dart containing the polymeric matrix formulation of leuprolide acetate (D-Leu6GnRH-Pro9-ethylamide). Four elk (group B) were designated as pregnant controls. They received the polymer solution without leuprolide and were used to compare the effects of leuprolide formulation on pregnancy rates between treated and untreated elk. These two groups of elk were maintained together in the same pastures with two intact, adult male elk from 13 September 2002 to 10 April 2003. The remaining five elk (group C) served as non-pregnant controls and were placed in a separate pasture (2 ha) without direct contact with male elk. We compared concentrations of LH and progesterone of these females to those treated with leuprolide formulation (group A). Non-pregnant control females (group C) provided a more representative comparison to treated elk for evaluating treatment-induced hormonal responses than potentially pregnant elk, thus the need for two separate control groups. Treatments Leuprolide implant formulation. The polymer, 85/15 poly (DL-lactide-co-glycolide) (PLG) with intrinsic viscosity 0.31 dL/g (Absorbable Polymer Technologies, Pelham, Alabama, USA) and N-methyl2-pyrrolidone (NMP, International Speciality Products, Wayne, New Jersey, USA) were mixed in a ratio of 50:50 in a vial until the polymer was completely dissolved. The polymer solution was sterilized by γirradiation at a dose of approximately 25Gy (Isomedix, Morton Grove, Illinois, USA) and an appropriate amount of the sterilized polymer solution was filled into 1.2 luer-lock female syringes. For the leuprolide 47 �part of the system, calculated volume of filtered aqueous solution of leuprolide acetate (Mallinkrodt, St. Louis, Missouri, USA) was filled in 1-mL male syringe barrels (Becton-Dickenson, Franklin Lakes, New Jersey, USA) and lyophilized. This formulation was designed to deliver a 32.5 mg dose of leuprolide at a controlled rate over a 180-day therapeutic period. A similar formulation was previously shown to suppress ovulation and pregnancy for one breeding season in captive elk when delivered subcutaneously by hand-injection (Baker et al., 2002). Treatment application. On the day before treatment application (6 September 2002), experimental elk were moved from holding paddocks to individual isolation pens (5 m x 10 m), weighed (± 0.5 kg), sedated with xylazine hydrochloride (Rompun; Bayer AG, Leverkusen; 25-200 mg/animal, IM) and fitted nonsurgically with indwelling jugular catheters. The next day, and just prior to injection, separate syringes containing the polymer and the leuprolide were connected and the contents mixed with 60 back and forth mixing cycles. The resulting homogenous dispersion was drawn into the male syringe, and the formulation was transferred into single use, 1 ml, 13-mm-diameter, barb-less darts equipped with gel-collared 32-mm-long needles (Pneu-dart, Williamsport, Pennsylvania, USA). The final concentration of leuprolide was 12 % in the homogenous mixture of polymer solution and leuprolide acetate after mixing and was designed to deliver approximately 32.5 mg of leuprolide acetate to the elk. Control elk received only the polymer solution processed the same way but without leuprolide. Prior to darting, individual elk were placed in a handling chute and lightly sedated with intravenous (IV) xylazine hydrochloride (15-20 mg/animal). This dose allowed animals to remain standing in the chute and minimized excitation associated with discharge of the dart gun. All elk were remotely injected with a dart fired from a CO2-powered pistol (DanInject™ , Wildlife Pharmaceuticals, Fort Collins, Colorado, USA). In order to accurately determine the precise dose of leuprolide formulation delivered to each elk, darts were weighed before and after injection. With the exception of two animals, one dart per animal was fired from approximately 3 meters into the area of the biceps femoris muscle of the standing elk. In two animals, the dart failed to discharge or only partially injected the prescribed dose. In these cases, we re-weighed and fired additional darts until the complete dose was delivered to each animal. Once all elk had been treated, sedation was reversed with yohimbine (30 mg, IV) (Antagonil®, Wildlife Laboratories, Fort Collins, Colorado, USA) and animals were returned to individual isolation pens. Measurements 24 h LH response to leuprolide treatment. Immediately following application of treatments to groups A and group C, we determined the amount of LH released during the initial 24 h of the treatment period. Blood samples (5 ml) were collected via jugular catheters at 0, 120, 180, 240, 300, 360, 480, 600, 960, and 1440 min after drug injection. Catheters were flushed after each collection with sterile saline solution. After the last blood collection, catheters were removed and animals were returned to holding paddocks. Eight days later, two intact male elk were placed into the same pasture with these females. Duration of LH and progesterone response to leuprolide treatment. The effect of leuprolide formulation on the duration of suppression of LH and progesterone was determined by periodically conducting pituitary stimulation trials. These trials were performed prior to treatment application as an aid in the selection of animals for this experiment and periodically during 29 October 2002 to 3 September 2003 to determine pituitary responsiveness to an exogenous dose of GnRH analog (D-Ala6-GnRH-Pro9ethylamide; Sigma Chemical Company, St. Louis, Missouri, USA). Pituitary stimulation trials were conducted with elk in groups A and C elk at 50, 100, 150, 185, 215, and 361 days post-treatment. The final stimulation trial (3 September 2003) provided hormonal evidence of the reversibility of leuprolide treatment. Stimulation trials were conducted according to the 48 �following procedures: On the day of testing, elk from groups A and C were moved from 5 ha pastures to individual isolation pens, weighed, sedated (as previously described), and fitted nonsurgically with indwelling jugular catheters. A bolus dose of GnRH analog (1 g/50 kg body weight) was administered through the cannula and blood samples (5 ml) were collected at 0, 60, 120, 180, 240, 300, 360, and 480 min post-administration. After collections, blood was stored at 4 C for 24 h until serum was obtained by centrifugation (1500 RCF for 15 min). Serum for progesterone analysis was obtained from the 0 h blood sample for each animal on each of the trial days. Serum was stored at -20 C until analyzed for LH and progesterone. Following the last blood collection, catheters were removed, and elk were returned to holding pastures. Reproductive response to leuprolide treatment - The effect of leuprolide formulation on reproduction in groups A and B was determined in two ways : (1) by measuring pregnancy rates using the presence or absence of pregnancy specific protein B (PSPB) (BioTracking, Moscow, Idaho, USA) in serum collected at approximately 100 and 215 days of gestation (Huang et al., 2000), and (2) by observing the presence or absence of calves the following summer. Analyses Serum concentrations of LH were quantified by means of an ovine oLH radioimmunoassay (Niswender et al., 1969). Elk serum was demonstrated to inhibit binding of 125 I-labeled oLH to LH antiserum in a manner that paralleled the standard (NIH- oLH-S24). Similarly, when different quantities of oLH standard were added to elk serum and samples were subjected to radioimmunoassay, the values obtained were increased by the quantity of oLH added (r2 = 0.99, slope = 0.92, β1 = 0.22, P = 0.002). These data indicated that the radioimmunoassay provided a quantitative assessment of LH in elk serum. The limit of sensitivity of the LH assay was 0.02 ng /ml. Serum concentrations of progesterone were also determined by radioimmunoassay (Niswender, 1973). Sensitivity of the progesterone assay was 0.12 ng /ml. Intra-and-inter assay coefficients of variation for each of these assays were < 10 %. Hormone concentrations are reported as untransformed arithmetic means (± SE). Responsiveness of the pituitary gland to GnRH analog stimulation was determined by the total amount of LH secreted (ng /ml/ min) which was estimated by calculating the area under the LH response curve (Abramowitz and Stegun, 1968). Differences among hormone concentrations were tested using least squares ANOVA for general linear models (SAS Institute, 1997). Responses to treatment were analyzed with one-way ANOVA for a randomized complete block design with repeated measures. Treatment effects were determined using the total animal-within-treatment variances as the error term. Time was treated as a within-subject effect, using a multivariate approach to repeated measures (Morrison et al., 1976). A “protected” least significant difference test (Milliken and Johnson, 1984) was used to separate means when the overall F- test indicated significant treatment effects (P < 0.05). RESULTS Intramuscular injection of leuprolide formulation via dart, was 100 % effective in suppressing ovulation and preventing pregnancy in captive female elk for one breeding season. All leuprolide treated females (group A) tested negative and untreated controls (group B) positive for PSPB at approximately 100 and 215 days of gestation. No calves were born to treated elk, whereas the calving rate of untreated elk was 100 %. The amount of leuprolide acetate delivered to each elk ranged from 22. 6 to 38.1 mg ( = 33.1, SE = 2.4). We did not observe any unusual bleeding, swelling or trauma at the injection site nor did any of the elk show evidence of impaired mobility or post-treatment tissue necrosis or abscesses related to dart delivery of the bioimplant. Of particular interest was that the lowest individual dose delivered (22.6 mg) was equally as effective as higher doses in suppressing hormone concentrations 49 �and pregnancy, suggesting that the minimum effective dose in elk could be substantially lower than the estimated dose (32.5 mg) used in this experiment. Mean serum concentrations of LH increased (P = 0.015) in treated elk (group A) within 2 h of drug injection, peaked at 63.12 ± 10.8 ng/ml (mean ± SE) 4.3 ± 0.65 h (mean ± SE) later, then gradually declined to baseline levels by 16 h post-treatment (Fig. 1). Levels of LH in group A were greater (P = 0.032) than those of untreated controls (group C) for 2- 10 h post-treatment, after which, values decreased to baseline levels and were similar (P = 0.285) for both groups. Results of periodic GnRH challenges revealed that the leuprolide formulation reduced pituitary content of LH to basal concentrations for at least 215 days post-treatment, which was 35 days longer than the expected 180-day delivery period (Fig. 2). Concentrations of GnRH analog-induced LH secretion were lower (P = 0.022) in leuprolide - treated elk (group A) compared to non-pregnant controls (group C) at days 50, 150, 185, and 215 days after treatment. Chronic suppression of LH in treated females was followed by a return to pretreatment levels, indicative of estrus, prior to the subsequent breeding season (September 2003, Fig. 3). In contrast to leuprolide-treated elk, pituitary responsiveness of untreated elk (group C) to GnRH analog were elevated and relatively similar (P = 0.64) in magnitude during the first 185 days of the experiment, after which, these levels declined (P = 0.087), presumably with the onset of seasonal anestrus (March). Similar (P = 0.582) to treated elk, pituitary responsiveness in control elk (group C) returned to pretreatment levels in September 20003. Serum concentrations of progesterone in leuprolide - treated females (group A) followed a parallel pattern to that observed for serum LH (Fig. 3). The suppressive effects of leuprolide on corpus luteum formation and steroidogenesis was readily apparent by its effects on serum progesterone concentrations in treated elk compared to controls (group C). Progesterone levels in treated elk declined (P = 0.017) to limits of detection by 50 days post-treatment and remained at those levels for the duration of the breeding period. For untreated elk (group C), serum progesterone was more variable and consistently higher (P = 0.043) than that for treated elk at 50, 100, 150, 185, and 215 days post-treatment. As evidence of normal estrous cycles and contraceptive reversibility, progesterone concentrations in both treated and untreated elk (group C) returned to pretreatment levels (P = 0.435) at the onset of the following breeding season. DISCUSSION In the present experiment, we evaluated the effectiveness of projectile dart delivery of the GnRH agonist, leuprolide, as a potential antifertility agent in female elk. The sustained release polymeric implant formulation of leuprolide acetate, remotely delivered in a projectile dart, resulted in decreased LH and progesterone secretion, presumably suppression of ovulation and steroidogenesis, and effective contraception (100 %) without adverse effects for one breeding season. The contraceptive effects of leuprolide formulation followed a two-phase process. The first phase was characterized by an acute, transient rise in serum LH which gradually declined to basal concentrations about 16 h post-treatment. The second phase was defined by chronic inhibition of LH and progesterone secretion for the duration of the seasonal breeding period. Subsequently, normal ovarian function and fertility were re-established prior to next breeding season. We conclude from these patterns of LH and progesterone in serum that gonadotropes in female elk are down-regulated during treatment with GnRH agonist. As a consequence, long-term exposure to GnRH agonist resulted in reduction in GnRH receptors on gonadotropes (Clayton, 1989), depletion of pituitary LH and FSH content (Aspden et al., 1996), and elimination of the preovulatory LH surge (Gong et al., 1995; D’Occhio et al., 1996). These responses have been shown to result in ovulation failure and infertility which persists as long as the GnRH agonist is present in circulation at therapeutic levels (Melson et al., 1986; D’Occhio et al., 2000). 50 �Our findings here are consistent with previous observations of acute and chronic responses of sheep (Dobson, 1985), cattle (D’Occhio et al., 1989; Gong et al., 1996), horses (Montovan et al., 1990), deer (Becker and Katz, 1995), and elk (Baker et al.,2002) treated with GnRH agonist. Effective contraception in polyestrous, seasonal breeders is dependent on suppression of ovulation from the beginning of the breeding season to the onset of seasonal anestrous, a period of approximately 200 d in elk. Therefore, the timing of treatment application is an important consideration in successful contraception. Because of the acute rise in LH concentrations that occurs following GnRH agonist treatments, ovulation of growing follicles can be induced (Macmillan and Thatcher, 1991, D’Occhio and Aspden, 1999). Therefore, to ensure effective contraception in female elk, leuprolide treatments should be applied prior to the initiation of seasonal estrus. In the present study, leuprolide inhibited LH secretion and ovulation for at least 215 days which is in close agreement with previous research, in which a subcutaneous dose of leuprolide suppressed LH levels for 190-250 days (Baker et al., 2002). In other studies, implants containing GnRH agonist have been shown to suppress ovarian activity for a minimum of 150 days in mule deer and (Baker et al., 2004) and almost 400 days in cattle (D’Occhio et al., 2002). Persistent suppression of ovarian function, beyond the formulated delivery period of the implant, has been reported for a number of different species. Leuprolide suppressed LH and progesterone levels in elk in this experiment for at least 35 days longer (19 %) than the expected six month effective duration and 30 -110 days longer in deer and elk in previous studies (Baker et al., 2002, 2004). Similar observations of extended gonadotrope suppression were reported previously in cattle (Bergfeld et al., 1996; D’Occhio et al., 1996), monkeys (Fraser et al., 1987), men (Hall et al., 1999), and women (Broekmans et al., 1996). The underlying mechanism for this effect is not completely understood, but it is thought to be a associated with prolonged dysfunction of gonadotrope cells rather than direct action on the ovaries (D’Occhio et al., 2000; Aspden et al., 2003). Regardless of the mechanism involved, the extended suppression of ovarian function, as a consequence of GnRH agonist treatment, is fundamentally essential to effective contraception in deer and elk. In conclusion, intramuscular delivery of the sustained release biodegradable polymeric implant formulation of leuprolide via dart resulted in effective suppression of ovarian function and fertility in female elk for one breeding season with a return to normal reproductive function the following year. These results are particularly important for wildlife applications where, in the absence of such technology, animals must first be captured and restrained prior to treatment. LITERATURE CITED Abramowitz, M., and I. A. Stegun. 1968. Handbook of mathematical functions. Dover Publishing, Inc., New York, New York, 343 pp. Aspden, W. J., A. Rao, P. T. Scott, I. J. Clark, T. E. Trigg, J. Walsh, and M. J. D’Occhio. 1996. Direct actions of the luteinizing hormone -releasing hormone agonist, deslorelin, on anterior pituitary contents of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), LH and FSH subunit messenger ribonucleic acid, and plasma concentrations of LH and FSH in castrated male cattle. Biology of Reproduction 55:386-392. __________ , A. Jackson, T. E. Trigg, and M. J. D’occhio. 2003. Pituitary expression of LHβ-and FSHβsubunit mRNA, cellular distribution of Lhβsubunit mRNA and LH and FSH synthesis during and after treatment with a gonadotrophin-releasing hormone agonist in heifers. Reproduction, Fertility and Development 15:149-156. 51 �Baker, D. L., M. A. Wild, M. M. Conner, H. B. Ravivarapu, R. L. Dunn, and T. M. Nett. 2002. Effects of GnRH agonist (leuprolide) on reproduction and behavior in female wapiti (Cervus elaphus nelsoni). Reproduction (Suppl.) 60: 155-167. ___________ , ___________ , ___________ , __________ , _____________ , _________ . 2004. Gonadotropin releasing hormone agonist: a new approach to reversible contraception in female deer. Journal of Wildlife Diseases 40: (in press). Becker, S. E., and L. S. Katz. 1995. Effects of gonadotropin-releasing hormone agonist on serum LH concentrations in female white-tailed deer. Small Ruminant Research 18:145-150. Bergfeld E. G. M., M. J. D’occhio, and J. E. Kinder. 1996. Continued desensitization of the pituitary gland in young bulls after treatment with the luteinizing hormone-releasing hormone agonist deslorelin. Biology of Reproduction 54:769-775. Broekmans, F. J., P. G. Hompes, C. B. Lambalk, E. Broeders, and J. Schoemaker. 1996. Short-term desensitization: effects of different doses of gonadotrophin-releasing hormone agonist triptorelin. Human Reproduction 11:55-60. Clayton, R. N. 1989. Gonadotropin-releasing hormone: its actions and receptors. Journal of Endocrinology 120:11-19. Delsink, A. K., J. J. van Altena, J. J. Kirkpatrick , and R. A. Fayrer-Hosken. 2002. Field application of immunocontraception in African elephants (Loxodonta africana). Reproduction (Suppl.) 60:117124. DeNicola, A. J., D. J. Kesler, and R. K. Swihart. 1997. Remotely delivered prostaglandin F2 implants terminate pregnancy in white-tailed deer. Wildlife Society Bulletin 25: 527-531. Dobson, H. 1985. Effects of chronic treatment with a GnRH agonist on oestrous behavior and on the secretion of LH and progesterone in the ewe. Theriogenology 24: 1-11. D’occhio, M. J., D. R. Gifford, C. R. Earl, T. Weatherly, and W. Von Rechengerg. 1989. Pituitary and ovarian responses of post-partum acyclic beef cows to continuous long-term GnRH and GnRH agonist treatment. Journal of Reproduction and Fertility 85:495-502. ____________, W. J. Aspden, and T. R. Whyte. 1996. Controlled, reversible suppression of estrous cycles in beef heifers and cows using agonist of gonadotropin-releasing hormone. Journal of Animal Science 74:218-225. ____________, and Aspden, W. J. 1999. Endocrine and reproductive responses of male and female cattle to agonist of gonadotrophin-releasing hormone. Journal of Reproduction and Fertility 54 (Suppl.):101-114. ____________ , G. Fordyce, T. R. Whyte, W. J. Aspden, and T. E. Trigg. 2000. Reproductive responses of cattle GnRH agonist. Animal Reproduction Science 60-61: 433-442. ______________ , _____________ , ____________ , L. A. Fitzpatrick, N. J. Cooper, W. J. Aspden, M. J. Bolam, and T. E. Trigg. 2002. Use of GnRH agonist implants for long-term suppression of fertility in extensively managed heifers and cows. Animal Reproduction Science 74: 151-162. Fagerstone, K. A., M. A. Coffey, P. D. Curtis, R. A. Dolbeer, G. J. Killian, L. A. Miller, and D. L. Wilmot. 2002. Wildlife fertility control. Wildlife Society Technical Review 02-02. The Wildlife Society, Bethesda, Maryland, USA. Fraser, H. M, J. Sandow, H. R. Seidel, W. Von Rechenberg. 1987. An implant of gonadotropin releasing hormone agonist (buserelin) which suppresses ovarian function in the macaque for 3-5 months. Acta Endocrinology 121:841-853. Gong, J. G., T. A. Bramley, C. G. Gutierrez, A. R. Peters, R. Webb. 1995. Effects of chronic treatment with gonadotrophin-releasing hormone agonist on peripheral concentrations of FSH and LH, and ovarian function in heifers. Journal of Reproduction and Fertility 105: 263-270. ___________ , B. K. Campbell, T. A. Bramley, C. G. Gutierrez, A. R. Peters, and D R. Webb. 1996. Suppression in the secretion of follicle-stimulating hormone and luteinizing hormone, and ovarian follicle development in heifers continuously infused with a gonadotropin- releasing hormone agonist. Biology of Reproduction 55: 68-74. 52 �Hall, M. C., R. J. Fritzsch, A. I. Sagalowsky, A. Ahrens, B. Petty, and C. G. Roehrborn. 1999. Prospective determination of the hormonal response after cessation of luteinizing hormonereleasing hormone agonist treatment in patients with prostate cancer. Urology 53:898-902. Huang, F., D. C. Cockrell, T. R. Stephenson, J. H. Noyes, and R. G. Sasser. 2000. A serum pregnancy test with a specific radioimmunoassay for moose and elk pregnancy specific protein B. Journal of Wildlife Management 64: 492-499. Jacobson, N. K., D. A. Jessup, and D. J. Kesler. 1995. Contraception in black-tailed deer by remotely delivered norgestomet ballistic implants. Wildlife Society Bulletin 23: 718-722. Kreeger, T. J. 1997. Overview of delivery systems for the administration of contraceptives to wildlife. In Contraception in wildlife management. T. J. Kreeger, (ed.) USDA-APHIS Technical Bulletin 1853, Washington, D. C., pp 29-48. Kirkpatrick, J. F., I. K. M. Liu, and J. W. Turner. 1990. Remotely-delivered immunocontraception in feral horses. Wildlife Society Bulletin 18: 326-330. Macmillan, K. L., and D W. W. Thatcher. 1991. Effects of gonadotrophin-releasing hormone on ovarian follicles in cattle. Biology of Reproduction 45:883-889. McComb, K. 1987. Roaring by red deer stags advances the date of oestrus in hinds. Nature 330:648-649. McCleod, B. J., S. E. Dodson, A. R. Peters, and G. E. Lamming. 1991. Effects of a GnRH agonist (Buserelin) on LH secretion in post-partum beef cows. Animal Reproduction Science 24:1-11. McNeilly, A. S., and H. M. Fraser. 1987. Effect of gonadotrophin-releasing hormone agonist-induced suppression of LH and FSH on follicle growth and corpus luteum function in the ewe. Journal of Endocrinology 115:273-282. Melson, B. E., J. L. Brown, H. M. Schoeneman, G. K. Tarnavsky, and J. J. Reeves. 1986. Elevation of serum testosterone during chronic LHRH agonist treatment in the bull. Journal of Animal Science 62:199-207. Milliken, G. A., and D. E. Johnson. 1984. Analysis of messy data. Volume 1.Designed experiments. Lifetime Learning Publications, Belmont, California, 399 pp. Montovan, S. M., P. P. Daels, J. River, J. P. Hughes, G. H. Stabenfeldt, and B. L. Lasley. 1990. The effect of potent GnRH agonist on gonadal and sexual activity in the horse. Theriogenology 33:1305-1321. Morrison, J. A., C. E. Trainer, and D P. L. Wright. 1976. Multivariate statistical methods. McGraw-Hill, New York, New York, 432 pp. Niswender, G. D, Reichert, L. E., JR., A. R. Midgley, and A.V. Nalbandov. 1969. Radioimmunoassay for bovine and ovine luteinizing hormone. Endocrinology 84:1166-1173. ___________ . 1973. Influence of the site of conjugation on the specificity of antibodies in progesterone. Steriods 22: 413-424. Ravivarapu, H. B., K. L. Moyer, and D. R. Dunn. 2000. Sustained activity and release of leuprolide acetate from an in situ forming polymeric implant. American Association of Pharmaceutical Scientist 1:1-12. SAS Institute. 1997. SAS/STAT ® user’s guide 6.03 edition. SAS Institute Incorporated, Cary, North Carolina, USA. Shideler, S. E., M. A. Stoops, N. A. Gee, J. A. Howell, and D B. L. Lasley. 2002. Use of porcine zona pellucida (PZP) vaccine as a contraceptive agent in free-ranging tule elk (Cervus elaphus nannodes). Reproduction (Suppl) 60: 169-176. Trigg, G. G, T. E., P. J. Wright, A. F. Armout, P. E. Williamson, A. Jundaidi, G. B. Martine, A. G. Doyle, and D. J. Walsh. 2001. Use of GnRH analogue implant to produce reversible long-term suppression of reproductive function in male and female domestic dogs. Journal of Reproduction and Fertility 57:255-261. Turner, J. W., JR., I. K. M. Liu, and J. F. Kirkpatrick. 1992. Remotely delivered immunocontraception in white-tailed deer. Journal of Wildlife Management 56: 154-157. ___________ , ____________ , ____________ . 1996. Remotely delivered 53 �immunocontraception in free-roaming feral burros. Journal of Reproduction and Fertility 107: 31-35. Prepared by ___________________________ Dan L. Baker, Wildlife Researcher Figure 1. Twenty-four hour serum LH concentrations (ng/ml, mean ± SE) for untreated female elk (", n = 5) and female elk (!, n = 6) treated with a 180-day sustained release implant formulation, containing approximately 32.5 mg of leuprolide acetate, remotely delivered via projectile dart. 54 �Figure 2. Total serum LH concentrations (ng/ml/min, mean ± SE) for GnRH analog-induced release of LH for untreated female elk (", n = 5), and female elk (!, n = 6) treated with a 180 -day sustained release implant formulation, containing approximately 32.5 mg of leuprolide acetate, remotely delivered via projectile dart. Different lower case letters indicate significant differences between means (P 0.05). Figure 3. Serum profiles of mean progesterone concentrations (ng/ml, mean ± SE) for untreated female elk (", n = 5) and female elk (!, n = 6) treated with a 180-day sustained release implant formulation, containing approximately 32.5 mg of leuprolide acetate, remotely delivered via projectile dart. Different lower case letters indicate significant differences between means. (P 0.05). 55 �56 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Task No. Colorado 3002 3 : : : : Federal Aid Project: N/A : Cost Center 3430 Mammals Research Elk Conservation Estimating Calf and Adult Survival Rates and Pregnancy Rates of Gunnison Basin Elk Period Covered: July 1, 2003- June 30, 2004 Author: D. J. Freddy Personnel: D. Masden, R. Basagoitia, L. Spicer, B. Diamond of CDOW, Dr. G. C. White Colorado State University, and cooperators/contractors Gunnison Basin Habitat Partnership Program, M. Schuette of MountainScape Imaging, private land owners, and elk hunters. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT During this segment, the transition of monitoring the remaining 119 radio-collared adult elk from research to management biologists was facilitated by providing databases, telemetry equipment, and other guidance as needed. Progress reports were completed, peer-reviewed publications on elk survival rates were initiated, and publications were accepted by peer-reviewed journals. 57 �JOB PROGRESS REPORT ESTIMATING CALF AND ADULT SURVIVAL AND PREGNANCY RATES OF GUNNISON BASIN ELK POPULATIONS DAVID J. FREDDY P. N. OBJECTIVE Estimate survival rates of calf, adult female, and adult male elk and estimate pregnancy rates of adult female elk in Gunnison Basin elk populations for 3 years. NOTE: Prioritization of available research funding resulted in discontinuing efforts to estimate calf survival, pregnancy rates and body condition during 2002-03 but allowed for monitoring adult elk survival through June 2003. SEGMENT OBJECTIVES 1. 2. Facilitate the transition of monitoring the remaining 119 radio-collared adult elk from research to management biologists by providing databases, telemetry equipment, and other guidance as needed. Summarize and analyze data and publish information as Progress Reports, peer-reviewed manuscripts for appropriate scientific journals, or Colorado Division of Wildlife (CDOW) technical publications. SUMMARY Progress reports were completed for the Gunnison Basin elk project (Freddy 2002, Freddy 2003) and can be obtained through the CDOW Research Center library in Fort Collins, Colorado. Publications incorporating calf and adult elk survival rates measured in the Gunnison Basin and Grand Mesa, Colorado were initiated. Two publications were accepted by the Wildlife Society Bulletin for publication during this segment with authors and abstracts provided here for reference. How many mule deer are there? Challenges of credibility in Colorado David J. Freddy, Colorado Division of Wildlife, 317 West Prospect Road, Fort Collins, CO 80526, USA, dave.freddy@state.co.us Gary C. White, Department of Fishery and Wildlife Biology, Colorado State University, Fort Collins, CO 80523, USA Mary C. Kneeland, Colorado Division of Wildlife, 317 West Prospect Road, Fort Collins, CO 80526, USA Richard H. Kahn, Colorado Division of Wildlife, 317 West Prospect Road, Fort Collins, CO 80526, USA James W. Unsworth, Idaho Department of Fish and Game, P.O. Box 25, Boise, ID 83707, USA William J. deVergie, Colorado Division of Wildlife, 2300 South Townsend Avenue, Montrose, CO 81401, USA Van K. Graham, Colorado Division of Wildlife, 711 Independent Avenue, Grand Junction, CO 81505, USA John H. Ellenberger, Colorado Division of Wildlife, 711 Independent Avenue, Grand Junction, CO 81505, USA 58 �Charles H. Wagner, Colorado Division of Wildlife, 222 South Road 1 East, Monte Vista, CO 81144, USA Abstract: Conflict resolution between stakeholder groups and management agencies is a problem in wildlife management. We evaluated our success in resolving a conflict between sportsmen and the Colorado Division of Wildlife (CDOW). Sportsmen challenged the credibility of methods used to estimate numbers of mule deer (Odocoileus hemionus) in Colorado and demanded validating surveys to verify numbers of deer. Sportsmen, other interested wildlife stakeholders, and CDOW engaged in a conflict resolution process and designed and implemented an aerial survey to estimate numbers of deer in a specific population whose previous estimated size had been contested by sportsmen. We used helicopters to count mule deer on randomly selected sample units distributed on deer winter range in March 2001. Estimated population size was 6,782 ± 2,497 (90% CL) using stratified random sample estimators and 11,052 ± 3,503 (90% CL) when counts of deer were adjusted using the Idaho mule deer sightability model. Both aerial survey estimates supported computer modeled population estimates of 7,000 to 7,300 deer that had been contested by sportsmen and all estimates were greater than the sportsmen’s estimate of 1,750 deer which was determined from their casual observations. After the survey, sportsmen did not accept survey estimates despite their involvement in design, analysis, and interpretation of the validation survey. By failing to support results of a validation survey they had demanded, the credibility of sportsmen plummeted among other stakeholders, the Colorado Wildlife Commission, and outside public entities while credibility of CDOW managers rose. We contend that CDOW successfully met challenges of sportsmen because the aerial survey systems used to validate deer numbers were founded on credible science and applied within a resolution process that elicited trust from most stakeholders. We caution other agencies facing similar challenges to use tested methods that can withstand public scrutiny, allow ample time for planning and implementing, carefully assess technical and political risks associated with potential outcomes, and engage multiple stakeholders in planning efforts to gain trust of participants. Cost of this resolution process was about 100,000 $US. Key words: Colorado, conflict resolution, credibility, helicopter surveys, human dimensions, mule deer, Odocoileus hemionus, population estimates, sightability Wildlife Society Bulletin 32 (3):00-00. Effect of limited antlered harvest on mule deer sex and age ratios Chad J. Bishop, Colorado Division of Wildlife, 2300 South Townsend Avenue, Montrose, CO 81401, USA, chad.bishop@state.co.us Gary C. White, Department of Fishery and Wildlife Biology, Colorado State University, Fort Collins, CO 80523, USA David J. Freddy, Colorado Division of Wildlife, 317 West Prospect Road, Fort Collins, CO 80526, USA Bruce E. Watkins, Colorado Division of Wildlife, 2300 South Townsend Avenue, Montrose, CO 81401, USA Abstract: During the 1990s, in response to apparent declining mule deer (Odocoileus hemionus) numbers in Colorado, high buck harvest rates were identified as one of several factors that could be negatively affecting population productivity. Some wildlife managers and sportsmen hypothesized that increasing buck:doe ratios by limiting buck harvest would cause an increase in fawn:doe ratios, and hence, population productivity. We evaluated this hypothesis using data collected by the Colorado Division of Wildlife (CDOW) from 1983 to 1998. Beginning in 1991, CDOW reduced buck harvest in 4 deer management units to provide quality hunting opportunities while maintaining high harvests in other management units. We examined effects of limited harvest on December ratios of bucks:100 does and fawns:100 does using data obtained from helicopter surveys in limited and unlimited harvest units. 59 �Annual buck harvest was reduced by 359 bucks (SE = 133) as a result of limiting licenses in the 4 limited harvest units. Fawn:doe ratios declined by 7.51 fawns:100 does (SE = 2.50), total buck:doe ratios increased by 4.52 bucks:100 does (SE = 1.40), and adult buck:doe ratios increased by 3.37 bucks:100 does (SE = 1.04) in response to limited harvest. Evidence suggested that factors other than buck harvest were regulating population productivity with density dependence being a plausible explanation of declining fawn:doe ratios. Limiting buck harvest to enhance fawn recruitment is not justified in Colorado based on our analysis. Management for limited buck harvest should be largely framed as an issue of quality hunting opportunity rather than an issue of deer productivity. Key words: age ratio, buck:doe ratio, Colorado, fawn:doe ratio, limited harvest, mule deer, Odocoileus hemionus, productivity, quality hunting, sex ratio Wildlife Society Bulletin 33 (0):00-00. LITERATURE CITED Freddy, D.J. 2002. Estimating calf and adult survival rates and pregnancy rates of Gunnison Basin elk. Colorado Division of Wildlife Wildlife Research Report July: 191-222. Fort Collins, Colorado, USA. Freddy, D.J. 2003. Estimating calf and adult survival rates and pregnancy rates of Gunnison Basin elk. Colorado Division of Wildlife Wildlife Research Report July: In Press. Fort Collins, Colorado, USA. Prepared by _______________________________ David J. Freddy, Wildlife Researcher 60 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Colorado Project No. 1 Work Package No. 3003 Task No. 1 : : : : Federal Aid Project: : N/A Cost Center 3430 Mammals Research Predatory Mammals Conservation Colorado Puma Research & Management Program Period Covered: July 1, 2003― June 30, 2004 Author: K. A. Logan Personnel: J.Apker, J. Kindler, Colorado Division of Wildlife; L. Mundy-Four Corners Houndsmen’s Association; and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Puma Research and Management Program started in July 2003. The goal is to improve the scientific foundation of puma management by the Colorado Division of Wildlife. The program was developed with inputs of Division researchers, managers, and biologists, and Colorado citizens interested in wildlife management, hunting, and the environment. Puma population research is scheduled to begin in November 2004. Associated projects to improve puma management in Colorado, also initiated this year include: the Colorado puma data map, prospective work for Front Range pumahuman interaction research, puma technical workshops, and Data Analysis Unit management plans and puma-human conflict guidelines. 61 �JOB PROGRESS REPORT COLORADO PUMA RESEARCH AND MANAGEMENT PROGRAM Kenneth A. Logan INTRODUCTION The Colorado Puma Research and Management Program started in July 2003. The goal is to improve the scientific foundation of puma management in Colorado. A Prospectus was developed with inputs of Division researchers, managers, and biologists, and Colorado citizens interested in wildlife management, hunting, and the environment. The major part of the program is the puma research project in the prospectus, scheduled to begin in November 2004. The initial design of the research will be clarified in a study plan in September 2004 which will pertain to the puma population research on the Uncompahgre Plateau study area. Other work associated with the development of the research program included: visiting with affected publics (private landowners, ranchers, hunters, guides and outfitters) and agency cooperators, surveying potential study areas, and two public meetings for information on the proposed puma research. Associated projects to improve puma management in Colorado included: the Colorado puma data map, puma workshops, technical advice on puma Data Analysis Unit management plans, and puma-human conflict guidelines. COLORADO PUMA DATA MAP The objective of this project is to map and quantify puma data that exists in records of the Colorado Division of Wildlife. This is the first step for Division staff to examine historical and current situations regarding puma management actions and puma mortality patterns state-wide and within management units. The map is intended to be an evolving instrument that allows comparisons with puma data gathered in the future to examine potential effects of changing puma management prescriptions, habitat, ungulate populations, and human developments. Interpretations of the map could be clarified from information on puma populations, movement patterns, habitat use, habitat characteristics, pumaungulate interactions, and hunter access to occupied puma habitat. Reliable interpretations of such maps would be useful to managers. Number and distribution of puma mortality locations and absence of mortality locations may indicate relative puma abundance or hunting pressure. High mortality areas, influenced principally by sport-hunting pressure, may indicate potential areas of high puma densities, puma population sinks (defined as areas where the average population growth rate is negative), areas of facilitated puma hunting conditions (e.g., high road density, consistent snow coverage), and liberal puma harvest objectives. Low puma mortality areas and blank areas on the map may indicate potential puma habitat with puma source populations (defined as areas where mean population growth rate is positive, and which serve as net exporters of dispersing animals), areas where few if any puma live, or areas with low hunter access or good hunting conditions. RESULTS Desired products are maps and associated tabulated data on geographical distribution and intensity of puma mortality. Puma mortality data (including sport-harvest, depredation control, public safety management, and accidental deaths) recorded by the Division on mandatory check forms since 1997 were mapped, state-wide and by Data Analysis Units and Game Management Units, and stratified by year and puma sex and age class (e.g., adult, subadult, cub). This entails about 2,423 data points statewide, from 1997―2002 (2003 data have not been entered, yet). Of that, over 90% of the mortality locations are due to sport-harvest. The remainder is due to depredation or public safety control kills, roadkills, and other recorded deaths. Maps are currently in a preliminary development stage. Mortality 62 �locations of puma will be buffered by average puma home range sizes for adult puma in western North America (195 km2 for females; 357 km2 for males) and overlaid by mule deer, elk, and bighorn sheep winter ranges. In addition, the identity of DAUs with the management objective of a stable or increasing puma population and DAUs with the management objective of a suppressed population also need to be mapped for managers to consider the number, distribution and effects of potential source and sink populations. Other map overlays that may facilitate interpretation of the puma data include: road distribution (i.e., paved, all-weather, dirt), vegetation cover types, elevation, and human developments and density. Puma mortality characteristics (i.e., location, density) might be modeled by using an analytical approach that uses habitat and biological features (e.g., ungulate distribution and relative density, elevation, roads, vegetation, terrain ruggedness) as variables. Another approach might be to distribute puma mortality maps to Division field personnel and to knowledgeable puma hunters to record their explanations about geographical puma distributions, relative densities, mortality patterns, and effects of habitat characteristics (e.g., landownership, snow conditions, access). COLORADO PUMA-HUMAN INTERACTIONS RESULTS Meetings involving Division staff, and individuals from the U.S. Geological Survey Ft. Collins Research Center and Colorado State University were held to discuss potentials for puma-human interaction research on the Colorado Front Range. Meetings were held in conjunction with field trips to explore potential study areas west Ft. Collins on October 6, 2003; west of Boulder on January 28 and February 6, 2004; and west of Colorado Springs on February 5, 2004. Division staff from the southeast and northeast expressed a great deal of interest in developing puma-human interaction of research in the next 1―2 years, and discussions indicated the need to develop a reliable funding base and connections with potential cooperators. The Division of Wildlife and Four Corners Houndsmen’s Association co-hosted four workshops in 2004 to inform hunters and other interested citizens about puma in Colorado. Workshops were held in Grand Junction (July 19), Alamosa (July 17), Denver (July 22), and Canon City (August 14). In all, the workshops were attended by about 60 people. Workshop agenda topics included: puma population characteristics, vital rates, reproductive biology, behavior, prey selection, female and cub vulnerability to hunting, gender identification in the field, aging techniques, Colorado puma data map, puma management, Data Analysis Unit plans, quota setting process, proposed puma research, and puma-human conflict management. A PowerPoint presentation was developed as the main source of information on these topics. Some attendees suggested that such workshops should be held periodically for puma hunters and other people interested in puma. Associated with this effort to bring reliable information on puma to hunters, we also produced printed guidelines for sexing puma in the wild. This information is available on the Division’s webpage: http://wildlife.state.co.us/hunt/BigGame/pdf/MtLionGender.pdf and in APPENDIX I of this progress report. Drafts of guidelines developed by Division managers for addressing incidents when puma conflict with people were discussed and reviewed and a final draft was created for review by Division staff: Draft—Human Mountain-Lion Incidents. 63 �PUMA RESEARCH AND MANAGEMENT PROSPECTUS PROBLEM STATEMENT Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the Division objective of actively managing puma while “achieving healthy, self-sustaining populations”(Colorado Div. of Wildlife 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Members of the Division’s Mammals Research staff met with Division wildlife managers and biologists from the Northwest, Southwest, Southeast, and Northeast Regions regarding puma management issues and the resultant research needs. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other Division employees. In general, Division staff in western Colorado conveyed concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, (perhaps because of results from recent research findings in western Colorado), they expressed interest in puma-prey interactions. Division managers on the Rocky Mountain’s Front Range placed greater emphasis on puma-human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Specific management needs and lines of inquiry identified by Division staff and public stakeholders are categorized as follows: Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates). ● Methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance puma. ● Effects of aversive conditioning on puma. Past Puma Research in Colorado Data from past puma research in Colorado that address the topics above are limited. Currier et al. (1977:8) studied 29 captured puma on 2 tracts― one 900 km2, and one 1,950 km2― in Fremont and Custer Counties during 1974―1977. The puma population under study was subject to sport-hunting. Hunters killed a total of 31 puma in 3 winters. Non-systematic puma track counts were used to estimate 64 �the minimum puma population at 11 on the 900 km2 tract (density = 1.2/100 km2) and 25―28 on the 1,950 km2 tract (density = 1.3―1.4/100 km2. The Petersen mark-recapture method was used to estimate 95 puma (95% CI = 35, 155; density = 4.8/100 km2) during 1977―1978; however, researchers probably did not meet 4 of the 6 assumptions needed for valid estimates of puma numbers (Anderson 1983:61, 63). Vital rate data were limited to mean litter size of 2.1 (range = 1―5, n = 14). An effort to estimate puma population density in Game Management Units (GMU) 33 (Garfield and Rio Blanco Counties) and 40 (Mesa County) was made during 1980―1983 (Brent 1981, 1982, 1983). A total of 38 puma were captured: 21 were marked and released; 8 were released unmarked; 9 were killed for livestock depredation control (8) or during handling (1). Twelve puma were captured in GMU 33 and 26 were captured in GMU 40. Crude adult puma density estimates for GMU 33 ranged from 2.7―3.1 puma/100 km2. GMU 40 crude adult puma density estimates ranged from 1.2―3.7 puma/100 km2. Anderson et al. (1992) studied 57 captured puma on 3,426 km2 of the eastern slope of Uncompahgre Plateau in Mesa, Delta, Montrose, and Ouray counties during 1981―1988. Puma density was estimated only for 1987; the minimum density (mean ± SE) of residents was 1.1 ± 0.15 pumas/100 km2. Male to female sex ratios for 26 captured puma 1―12 months old was 1:1; for 19 captured puma ≥24 months old, it was 1:1.4. Age structure in that sample was 66.7% <24 months old and 33.3% ≥24 months old (the class most likely comprised of breeding adults). Vital rates included, mean (± SD) litter size of 2.4 ± 0.80 (n = 17), birth interval of 12 months (n = 2 intervals for 1 female), estimated annual survival rate for 42 puma of both sexes of 88.0 % (90% CI = 83.1, 91.4). Humans caused 18 of 21 deaths in radio-collared puma even though the study population was supposed to be protected from human offtake. Anderson et al. (1992) examined aerial locations of 7 radio-collared puma and subjective estimates of relative deer and elk density categories and could not identify consistent relationships probably because of the small non-random sample of puma, the subjective nature of the ungulate density categories, and other non-quantified factors. Mean annual home range sizes ranged from 436―732 km2 for 3 males and 190―463 km2 for 7 females. All of 9 radio-collared subadult male puma dispersed from natal areas. Two of 6 radio-collared subadult females did not disperse. Means and extremes of dispersal distances were 86.2 km (23―151) for 8 males that were 10―13 months old and 37.0 km (17―54) for 4 females that were 11―31 months old. Data on puma―human interactions were from 17 responses to 40 questionnaires submitted to residents in the housing development on the southeastern extreme of the study area. Seven of 17 respondents reported 25 puma sightings during about 260 months of residence. Ten respondents did not observe puma in about 476 months of residence. Koloski (2002) studied 19 captured puma on the 2,758 km2 Southern Ute Indian Reservation in La Plata, Archuleta, and Montezuma Counties during 1999―2001. The puma population was not subject to sport-hunting at the time. Transect intercept probability sampling was used in 2001 to estimate the puma population at 55 (90% CI = 9.0, 114.4) and a density of independent puma at 2.7/100 km2. Male to female ratio of the captured sample of 14 independent puma was 1:2.8. Of 16 captured pumas that were aged, 31% were <24 months old and 69% ≥24 months old. Vital rates included: litter size (mean ± SD) of 2.5 ± 0.58 (n = 4), birth interval of 16 months (n = 1), annual survival rate for radio-collared males (mean ± SD) of 0.89 ± 0.19 (n = 3) and radio-collared females of 0.72 ± 0.19 (n = 8); earliest age for female reproduction at 2―3 years; annual reproductive rate for resident females (mean ± SD) of 42% ± 12%. Mean home range sizes were 252.4 km2 for 3 radio-collared males and 182.4 km2 for 8 radio-collared females. Road density within puma home ranges and core areas was lower than that on the landscape where pumas occurred (P ≤ 0.002). Distance from puma locations to nearest roads was lower than distance from random points to nearest roads (P = 0.002). 65 �Current Puma Research in Colorado Presently, researchers with the Colorado Division of Wildlife (Mike Miller, Ph.D., DVM) and Colorado State University (Caroline Krumm, Graduate Student and Dr. N. Thompson Hobbs, Advisor) are conducting puma research in Larimer County. The research goal is to test for selective puma predation on mule deer infected with chronic wasting disease (CWD) by comparing CWD prevalence in puma-killed deer to prevalence in harvested deer. The research protocol calls for 6 or more puma fitted with global positioning system (GPS) collars. RESEARCHABLE OBJECTIVES The management issues listed previously in the PROBLEM STATEMENT may be translated into a number of researchable objectives, requiring descriptive studies and field experiments (Fig 1). Our goal is to provide managers with reliable information on puma biology and ecology and to develop and test tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. Researchable objectives address managers’ main needs. We propose that the Division begin to address objectives that focus on puma population dynamics, effects of harvest, and estimating puma population abundance with an intensive puma population study on the West Slope. Those objectives include: 1. Describe and quantify puma population characteristics, including: density, sex and age structure. 2. Describe and quantify puma population vital rates, including: birth rates, age or stage-specific survival rates, emigration rates, immigration rates. 3. Describe and quantify agent-specific mortality rates and vulnerability of different classes of puma to hunter harvest and quantify agent-specific mortality rates. 4. Develop and test puma population models using metrics from objectives 1―3. 5. Develop and test indices to puma abundance calibrated on an estimated puma population (i.e., puma track counts, catch per unit effort, DNA genotyping). In addition, other objectives could be partially addressed during the intensive puma population research effort (i.e., objectives 1―5). Those include: 6. Describe and quantify relationships of puma to people and human facilities on the study area. 7. Describe and quantify puma use of habitats and landscape linkages. 8. Describe and quantify relationships of puma to mule deer, elk, and other prey. 9. Describe and quantify responses of puma to aversive conditioning. 10. Describe and quantify behavior and survival of translocated puma. Data collection for primary objectives 1―5 will often have applicability to objectives 6―10. For example, GPS-collared puma will enable us to quantify puma predation rates on ungulate prey, puma use of habitats and landscape linkages, puma-human interactions, and behavior and survival of translocated puma (if puma are removed from a study area as part of an experimental manipulation). However, we cautioned that such opportunistic data gathering likely will not yield the power or confidence levels of studies specifically designed to meet those objectives. Yet, such efforts could function as pilot studies. Additional research efforts can be phased in later in the puma research program. And some, (e.g., puma relationships to people, puma use of habitats and landscape linkages) can be conducted in different areas of Colorado. 66 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Density, Sex & Age, Vital Rates, Growth Rates Vulnerability to Harvest Puma Habitat Human Development Habitat Use Effects of Translocation Indices of Abundance for Monitoring Deer, Elk, Other Natural Prey & Species of Concern Domestic Animals PumaHuman Relationships Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Models for Habitat Models for Populations Puma Prey Map Habitat Model PumaPrey Relationships Fig. 1. Conceptual model of the Colorado Puma Research & Management Program. 67 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with the main objectives can be structured to test assumptions, information, and methods that may guide puma management in Colorado. 1. Lacking Colorado-specific information, managers might assume that puma population densities in Colorado are within the range of those quantified in other populations studied in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992), and New Mexico (Logan and Sweanor 2001). The Division has used density ranges of 2.0―4.6 puma/100 km2 to extrapolate to Data Analysis Units to estimate a range of 3,000―7,000 puma in Colorado and to guide the quota-setting process. Likewise, managers may assume that the population sex and age structure is similar to puma populations described in the above-mentioned studies. Using capture, mark-recapture (or resight) techniques, a descriptive study will test H1a: The puma population density on the study area will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations in Wyoming, Idaho, Alberta, and New Mexico. Yet, an experimental study that allows puma population growth to approach carrying capacity in high quality puma habitat can test if a puma population in Colorado might exceed published density estimates. H1b: Puma population density in high quality puma habitat in Colorado exceeds the high range of 4.6 puma/100 km2. 2. Background material that guides puma management in Colorado assumes a moderate rate of growth of 15% for the adult puma population. Theoretically, consideration of management changes would occur if hunter kill exceeds 15% of the low end adult puma population estimate. A field experiment, involving an increase population growth phase, is required to test H2: The estimated average annual adult puma population growth rate in high quality puma habitat in Colorado (during an increase phase) will match or exceed the hypothetical r = 0.15. 3. The same background material assumes “that when female” puma “comprise greater than 50% of the hunter harvest it is an indicator that hunting may be acting to suppress the population.” An experimental study with a decline puma population growth phase will test H3: The population of harvest-age puma (i.e., adults, subadults) will decline only when 50% or more of the harvest is comprised of harvest-age female puma (i.e., independent subadults ≈≥12―24 mo. old and adults ≥24 mo. old). 4. Colorado puma Data Analysis Units (DAUs) or other management units may behave as a demographic source-sink metapopulation structure where the puma population of a region is comprised of subpopulations each of which may have dynamics that are not necessarily correlated with other subpopulations. Source-sink metapopulation dynamics function as a result of variable puma habitat quality and management practices (e.g., prey population dynamics, harvest pressure). Sources are increasing or stable populations where recruitment via local reproduction and immigration equal or outpace mortality. These source populations produce emigrating progeny that immigrate into other subpopulations, augmenting them numerically and genetically. Comparatively, sink populations are those where mortality exceeds recruitment, and puma numbers are declining or suppressed to a relatively low density. Sink populations contribute few emigrating progeny as potential recruits for other subpopulations. Sink populations are augmented by immigrants from source populations (Sweanor et al. 2000, Logan and Sweanor 2001). This project will examine H4: The study population will exhibit characteristics of a subpopulation in a demographic source-sink metapopulation structure. The following predictions must come true to support this hypothesis. 68 �a. The majority (i.e., >50%) of male recruits in the adult segment of the population on the study area will be immigrants (Logan and Sweanor 2001). Immigrants will not be offspring of puma on the study area as determined by genetic parentage analysis. b. Up to one-third of female recruits will be immigrants (Logan and Sweanor 2001). c. Male and female immigrant recruits will produce viable young. d. The majority of male progeny from the study area will emigrate (Logan and Sweanor 2001). e. About one-third of female progeny from the study area will emigrate (Logan and Sweanor 2001). f. Movements of male and female emigrants will be large enough to carry them to other Data Analysis Units with differing management objectives (i.e., population reduction, population stability). g. Male and female emigrants will establish adult home ranges in other puma habitats in Colorado. H4A: Recruits born in the local population are the largest contributor (i.e., >80%) to the maintenance of the puma population on the study area. 5. In southern Utah, Van Sickle and Lindzey (1992) found a positive relationship (r2 = 0.73) between the number of radio-collared puma known to have home ranges overlapping dirt roads (response variable) and track-finding frequency (explanatory variable). Similarly, researchers in Montana are finding a positive relationship between the number of puma home ranges overlapping search routes and puma track density (DeSimone et al. 2002). This relationship should reflect changes in puma numbers on the survey area, and thus may be useful as an index to relative abundance. A field experiment requiring both increase and decrease puma population growth phases is required to test H5a: Puma track-finding frequency (response variable) is positively correlated to number of puma with home ranges overlapping snow-covered search routes (explanatory variable). H5b: Puma track-finding frequency (response variable) is positively correlated to the density of independent puma (explanatory variable). 6. Theoretically, the amount of effort (i.e., hunting days) that hunters spend in pursuit of finding harvest-age puma (i.e., adults and subadults) should be proportionate to the abundance of puma (Lancia et al. 1996). A relationship should exist between changes in catch (or encounter)-perunit-effort and population changes. A field experiment, involving manipulation of the study population (i.e., increase phase, decline phase), is required to test H6a: Catch-per-unit effort of the research team in the increase phase, teams in the capture-recapture occasions during the increase and decline phases, and puma hunters during the decline phase will reflect the trend in the puma population. There will be an inverse (i.e., negative) correlation between the mean number of days per capture (response variable) and the number of independent puma in the population (explanatory variable) during the increase phase and the decline phase. H6b: During the increase phase, there will be a positive correlation between the mean number of days per capture of unmarked puma (response variable) and the number of marked puma “removed” from the unmarked population per year (explanatory variable). In the decline phase, there will be an inverse correlation between the mean number of days per capture (response variable) and the number of puma killed by hunters per year (explanatory variable). 7. Relative vulnerability of puma to hunters is limited to information from 2 studies on the same area in southern Utah (Van Dyke et al. 1986, Barnhurst 1986). Van Dyke et al. (1986) quantified effort to locate 4 classes of puma by looking for their tracks on dirt roads, a method that hunters use to find puma. He found that cubs and adult females required the least effort, followed by independent subadults and adult males. In contrast, Barnhurst (1986) assessed vulnerability based on the relative road crossing frequencies of radio-collared puma in each of 7 classes that were relocated once per week. He found that the most vulnerable puma were subadult males, followed 69 �by adult resident males, subadult females, and adult females (in 4 classes― females with 0 cubs, females with cubs 0-6 mo. old, females with cubs 7-12 mo. old, females with cubs 13-18 mo. old). Mothers with 0―6 month-old cubs had the lowest road-crossing frequency of all classes. Cubs in this age class are most vulnerable to death if their mothers die (K. Logan, unpublished data). A descriptive study will test H7: Relative vulnerability of GPS-collared puma on the study area, based on road-crossing frequency per day, will reflect the results of Van Dyke et al. (1986). H7A: Relative vulnerability of GPS-collared puma on the study area, based on road-crossing frequency per day, will reflect results of Barnhurst (1986). 8. Studies on the effectiveness of puma translocation, and the behavior, survival, and agent-specific mortality of translocated puma in western North America are limited to 2 studies. Ruth et al. (1998) reported on 14 puma translocated from 338―510 km in New Mexico, and Ross and Jalkotzy (1995) reported on 3 puma that were translocated 51―94 km in Alberta. The New Mexico research found that translocation was most successful for puma that were 12―27 months old, the age at which puma naturally attempt to disperse and search for a home range or establish a home range if they are philopatric. Older adult puma attempt to move back to their original home ranges. They found that mortality rates for translocated puma were significantly higher than mortality rates of non-translocated puma in a reference population. If translocation is used to experimentally reduce the population, this research would test H8: Translocation of puma will exhibit similar characteristics to the New Mexico results. For this hypothesis to be supported, the following predictions must be true. a. Mortality rates of translocated puma will be significantly higher than mortality rates of non-translocated puma. b. Independent puma 12 to about 30 months old will establish home ranges in or near release areas and have relatively greater survival rates than older adult translocated puma. c. Adult puma about 3 years old and older will tend to move back toward their original home ranges. DESIRED OUTCOMES AND MANAGEMENT APPLICATIONS 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population model(s) useful for estimates of puma population abundance and trends, evaluation of management alternatives, and effects of management prescriptions. 2. Indices to puma abundance or trends of known reliability will allow managers to “ground truth” modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives. 3. Testing assumptions about puma populations, currently used by Division managers, will help those managers adapt puma management based on Colorado-specific estimated characteristics and dynamics of puma populations. 4. An understanding of relative vulnerability of the various puma sex and age classes to harvest could enable managers to better structure harvest data collection and interpretation, and to develop novel prescriptions to meet management objectives. 5. Functional relationships between population vital rates and population density could be examined. Puma life history traits in Colorado may be used to test generalized hypotheses regarding puma life history strategies in the literature, and inform managers to structure successful management strategies. 70 �6. Determining whether or not the puma population in Colorado has a source-sink demographic sourcesink structure is important to evaluating the current Game Management Unit and Data Analysis Unit structure of puma management and potential effects of the juxtaposition of puma sub-populations in Colorado managed for stability, suppression, or that may function as refugia. 7. Knowledge of the relationships of puma to deer, elk, and species of special concern would allow managers to realistically consider potential effects of puma predation on those prey in the development of management strategies and policy. In addition, such information would enable the testing of scientific hypotheses on relationships of puma to their prey. 8. In the study areas currently being contemplated, some puma home ranges will probably contain human habitations and other facilities. GPS-collared and VHF-collared puma will generate quantitative information on puma behavior in relation to human activity and assist managers to better inform people about ways of reducing potential conflicts between people and puma, and to structure puma conflict policy. 9. Habitat use data gathered during the course of this research could be used to quantify puma habitat characteristics on the study area, as well as habitats and landscape linkages used by dispersing puma. Such information could be used to structure more extensive investigations of puma habitat that contribute to habitat modeling efforts that may help identify puma habitat in Colorado. This would allow a more realistic conceptual inventory of puma habitat in the state. 10. This information could be disseminated to public stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREAS Three potential study areas were evaluated and are under consideration: the Plateau Creek-toSouth Canyon area (in Garfield, Mesa, Gunnison, and Pitkin counties), the lower Dolores River-toDisappointment Creek area (in Dolores and Montezuma counties), the South Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties) (Table 1). These areas appear to have attributes conducive to an intensive puma research effort, including sufficient area (400―500 mi.2 = 1,036―1,295 km2) of puma habitat and suitable road access. Preferably, there should be a 300―400 mi.2 buffer zone around the study area to reduce the effect of puma harvest. 71 �Table 1. Potential puma study area locations and characteristics. Location Dolores River-toDisappointment Creek (GMUs 71 & 711) Area ~840 mi.2 = 2,176 km2 Junction of Interstate 70 & State Route 6 northeast to South Canyon (GMU 42) ~400 mi.2 = 1,036 km2 Area can be expanded ~155 mi.2 (~401 km2) by adding northern portion of GMU 421 (north of state routes 6 & 330, the north slope of the Plateau Creek drainage. South Uncompahgre Plateau (southern halves of GMUs 61 & 62) ~870 mi.2 = 2,253 km2 Other Attributes Large enough for core study area and buffer. Ratio of public:private land (mi.2) ~4:1. Town of Dolores is at the south end of this area. Substantial number of people live on the plateau. Domestic sheep and cattle use the area. Puma hunting pressure is moderate. Puma predation on domestic animals is low. Minimum study area size. Ratio of public:private land (mi.2) ~2:1. Substantial number of people live along the I-70 corridor and in lower Mamm, Hollow, Divide, and Battlement Creeks, and on Grass Mesa. Recent research on elk seasonal movements, survival and causespecific mortality rates (Freddy). An unknown number of cattle and horses use the area, but there are no domestic sheep. Gas exploration and development is occurring on the area. Puma hunting pressure is moderate. Puma predation on domestic animals is low. Large enough for core study area and buffer. Ratio of public:private land (mi.2) ~3:1. Ongoing mule deer research (Bishop et al. 2003), substantial “pre-treatment” data on mule deer productivity, survival, and cause-specific mortality (Pojar, Watkins, Bishop). Historical puma research (Anderson et al. 1992). Substantial number of people live in the eastern foothills and along the eastern, western, and southern edges of the plateau. Domestic sheep (~6 operators), cattle, and horses use the area. Puma hunting pressure is moderate. Puma predation on domestic animals is low. Puma can be captured year-round using 4 basic methods: trained dogs, cage traps, foot-hold snares, and hands (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when snow facilitates searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, and walking. When puma tracks ≤1 day old are detected, trained dogs will be released to trail puma. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 3.3 mg/kg estimated body mass (Wildlife Restraint Handbook, 1996, California Dep. of Fish and Game, Wildlife Investigation Laboratory, Sacramento). Immobilizing agent will be delivered in a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its 72 �legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ≈ 70―80 bpm, respiration ≈ 20 bpm, capillary refill time ≤2 sec., rectal temperature ≈ 101oF average, range = 95―106oF.) (Wildlife Restraint Handbook, 1996, California Dep. of Fish and Game, Wildlife Investigation Laboratory, Sacramento). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2004). Efficiency of the trap will be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Windham, NH). Researchers will monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected with a pole syringe. Immobilized puma will be restrained and monitored as described above. Foot-hold snares will be used to capture adults, subadults, and large cubs as described by Logan et al. (1999). Puma will be immobilized with Telazol injected with a pole syringe and their vital signs monitored during the handling procedures. Efficiency of snares will also be enhanced with the use of an automated digital call box. Small cubs (≤10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ≈100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to nurseries (Logan and Sweanor 2001). All captured puma will be examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tag ), blood (30 ml from the saphenous or cephalic veins), and hair (from various body regions) for genotyping individuals, parentage analysis and disease screening; fecal for diet analyses. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Marking, Global Positioning System and Radio-telemetry- Objectives 1―9 Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture and marking of individual puma is essential to a number of program objectives. Adult and subadult puma will be marked 3 ways: radio-collar, ear-tag, and tattoo. The identification number tattooed in one pinna is permanent and cannot be lost unless the pinna is severed. A colored, numbered 25 mm diameter ear-tag will be inserted into the other pinna to facilitate individual identification during recaptures and in photos taken by field cameras (see capture-recapture methods below). Adult and subadult puma will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) programmed to fix and store puma locations at least 4 times per day at 6-hours intervals to sample daytime, nighttime, and crepuscular locations. Each collar will have a color-coded identification number on each side also to facilitate identification during physical recaptures and photographic resightings. GPS locations for puma will provide precise, quantitative data for estimating 73 �puma home ranges, habitat use, quantifying road crossings (an index to vulnerability to hunting), finding ungulate kills (at location clusters), and estimating kill rates on ungulate prey (i.e., days per kill). VHF radio transmitters on GPS collars will enable researchers to find those puma on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters will have a mortality mode set to alert researchers when puma have been immobile for at least 4 hours so that dead puma can be found to quantify survival rates and agentspecific mortality rates by gender and age. At least one cub of each sex in each litter will be fitted with small VHF transmitter mounted on an expandable collar (≈100g, MOD 210, Telonics, Inc., Mesa, Arizona). Simultaneous locations of mothers and radioed cubs enable researchers to quantify the frequency that mothers are away from cubs to assess the potential risk of orphaning by hunters and other mortality factors, and quantification of survival rates and agent-specific mortality rates. Attrition of cubs in the remainder of the litter can be estimated by periodic visual checks for other siblings by homing on radioed cubs (Logan and Sweanor 2001). Locations of GPS- and VHF-collared puma will be fixed at least once per week from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using ArcGIS 8 software. Puma Abundance― Objectives 1, 4 &5 Capture-recapture estimates 1. Capture-recapture models will be used to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of puma present in the survey area) and puma density (i.e., number of puma/100 km2) each winter― Dec. through Mar.― when snow facilitates detection and capture of puma, provided that we meet model assumptions. The Dec.―Mar. period also corresponds with Colorado’s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma of legal harvest age. Furthermore, adults comprise the breeding segment of the population and subadults comprise potential recruits into the adult population in ≤1 year. Thus, the sampling unit is the individual independent puma (≈≥1 yr. old). General assumptions for capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). Marked puma will make it possible to acquire most of the basic statistics needed for capture-recapture models. Those include: nj (number of individually identified puma caught and released on occasion j), mj (number of previously marked puma recaptured in occasion j), uj (number of new unmarked puma captured in occasion j) (Otis et al. 1978, White et al. 1982). Attribute data of captured puma, such as age and sex, will be recorded to stratify the population in case separate analysis of different strata is necessary (if sample size allows) to meet certain assumptions of capture-recapture models (Pollock et al. 1990). Precise estimates of puma population size may also allow analyses of functional relationships between population vital rates and population size. 74 �We anticipate it may take 2 years to capture and mark the large majority of puma in the population. Our operational objective will be to have ≥90% of the independent puma marked before capture-recapture occasions commence. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during the capture-recapture occasions, therefore, we will capture and mark puma prior to performing capture-recapture occasions. In addition, by marking puma before capture-recapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked during the winter. After cubs are weaned, the mothers’ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Our year-round capture efforts using trained dogs, foot-hold snares, and cage traps should help to reduce biases in capture probabilities attributed to any individual capture method (Miller et al. 1997). Thus, capture-recapture occasions may not begin until the end of the second winter. Capture-recapture occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, biases in field methods (relative to GPS data on collared puma), and precision of capturerecapture models used to estimate the puma population. Data gathered directly from GPS-collared puma and knowledge of the study area acquired by the research team in years 1―2 will allow us to assess if capture-recapture methods are appropriate (i.e., if basic assumptions can be met), and if they are, facilitate the exact design of the mark-recapture schemes for population and density estimates. Movements of GPS-collared puma in and out of the study area during capture occasions will also allow us to estimate corrections for such movements (White 1996). A composite range (i.e., minimum convex polygon) of all the GPS-collared puma home ranges (i.e., using locations from each of the collared puma) will be estimated and mapped to define the search area (i.e., the area inhabited by the estimated population) and allow mapping of search routes for a thorough systematic search of the area to detect puma for capture (i.e., any individual puma should not have a negligible probability of detection). Density estimates using the generated population estimates will be based on the search area (i.e., N/Area) (Miller et al. 1997). A grid will be constructed on the same search area with cells equal to the minimum home range size. There will be a minimum of 4 search routes per cell, each chosen to sample a quarter of each cell. Any spaces in habitat on the search area not occupied by collared puma will also be sampled. Capture occasions will be repeated 3―6 times each winter (i.e., t1, t2, t3,...t6) to resample the population. Unmarked puma will be marked and returned to the population to increase the precision of population estimates. Teams of trained houndsmen (4―6 teams of at least 2 persons each) will by used to systematically and thoroughly search the study area each occasion. Capture occasions will be about 1―2 weeks apart. Capture occasions will commence 1―2 days following fresh snowfall that covers the study area and last 3―5 days (i.e., this is how long it may take teams to thoroughly search the study area). But if fresh snowfall is lacking, we will attempt capture efforts anyway (although this could increase variation in capture probabilities). At puma captures, the puma identification number, sex, age, and location (U.T.M. coordinate) will be the minimum information recorded. If the same individual puma is caught more than once in the same occasion, each capture will be recorded, but only the first capture will be used for data analysis. All capture-recapture occasions will be conducted within a 2―3 month span in winter to minimize the chance of population changes (i.e., deaths, immigration, emigration). Once capture history data on puma are gathered, estimates of the number of independent puma in the population in winter can be made by using capture-recapture models that deal with variation in capture probability and closed or open populations (Otis et al. 1978, White 75 �et al. 1982, Pollock et al. 1990). In order for closed models to be valid, the population of independent puma cannot change (as a result of death, emigration, or immigration) during the 2―3 month span that contain the capture-recapture occasions. Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of about 0.6 (for 3 occasions) and 0.4 (for 6 occasions) to yield capture probabilities ≥0.9 for individual puma in the population each winter (Trolle and Kery 2003). Theoretically, capture probabilities within this range (i.e., 0.4―0.6) would tend to reduce the coefficient of variation of the estimate to about 0.20 (i.e., increase the precision of the estimate) in small populations where individuals have a survival probability of about 0.90 in 5 samples (Pollock et al. 1990:72), which is realistic for puma. In addition, behavior, movements, and survival rates of GPS-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models may be used (Pollock et al. 1990). GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information as well. This will allow us to determine the number of marked puma present in the search area each capturerecapture occasion and the probability that unmarked puma move in and out of the search area during each occasion. 2. Photographic captures and recaptures (i.e., camera traps) could be assessed in a 3-year pilot study (e.g., years 2―4) as an independent method for estimating puma numbers and density on the study area (Mace et al. 1994, Karanth 1995, Karanth and Nichols 1998, Karanth and Nichols 2001, Trolle and Kery 2003). The pilot study could be carried out by a graduate student and begin in the second winter, at which time we may begin estimating the puma population using capturerecapture methods (described above). 3. Genotype captures and recaptures could be assessed in coordination with the physical and photographic capture methods described above (1 and 2). This could also be initiated as a 3-year pilot study (e.g., years 2―4) done by a graduate student. Genotypes can be used to estimate minimum population size directly (Kohn et al. 1999) and in capture-recapture models (e.g., Otis et al. 1978, Boulanger et al. 2002). However, genotyping errors should be estimated and considered in population estimates (Creel et al. 2003). This project could be another independent non-invasive method for estimating puma numbers and density on the study area. Moreover, this method may be useful to monitor puma populations in Colorado (see Indices to Puma Abundance below). Vulnerability of Puma to Hunters― Objective 3 Puma hunting in Colorado normally involves hunters searching for puma tracks while driving snow-covered roads with four-wheel drive vehicles or snowmobiles. Thus, vulnerability of puma to hunters is associated with the frequency that puma cross roads (Murphy 1983, Van Dyke et al. 1986, Barnhurst 1986). Hunters active on snow may successfully catch puma >85% of the time that they release dogs on tracks, and road access influences puma hunting distribution (Murphy 1983). 76 �Road crossing frequencies of GPS-collared puma will be used to assess relative vulnerability of various sex, age, and reproductive classes of puma to detection by puma hunters. Density of roads (i.e., km/100 km2) will be estimated within each GPS-collared puma home range (i.e., 100% minimum convex polygon), each quadrat in the sampling frame, and the entire study area. Road crossings per puma per 24hour periods will be quantified (GPS collars programmed for 4 locations per day, each 6 hours apart). Comparisons will be made between road crossing frequencies of puma classes and road densities in home ranges for puma classes. Puma classes will be: adult females (≥2 yr. old) with no cubs; adult females with cubs ≤2 months old (i.e., nursling cubs), adult females with cubs 3―12 months old (i.e., weaned, carnivorous cubs), subadult females (i.e., independent females <2 yr. old), adult males (i.e., ≥2 years old), and subadult males (i.e., independent males <2 years old) (Logan and Sweanor 2001). Vulnerability will also be quantified using road crossing frequencies of different classes of puma (female, male, divided into adult and subadult age classes if individuals are known) during the track index discussed below. In addition, actual capture rates of those puma will be quantified during capturerecapture occasions (no. of captures per puma class/no. of puma in each class). Frequency of capturing known puma mothers with and without their cubs will also be tallied to quantify vulnerability of puma mothers to legal harvest (i.e., known mothers without cubs by their side). During the puma population decline (i.e., reduction) phase (years 6―10), hunters can be used to kill puma. Relative vulnerability to and selection by hunters will be quantified during hunting seasons by having hunters report number of hunter-days, number of tracks encountered and locations (fixed by GPS), number of times dogs were released on tracks, number of captures, characteristics of killed or captured puma (i.e., hunters may capture puma and release them). At the same time, researchers will have quantitative knowledge of puma available for harvest on the study area (as a result of ongoing capture and marking procedures and GPS data) to estimate capture rate per puma class. The hunter-kill will also allow a direct assessment of puma mothers in the harvest and a comparison of the fates of potential orphaned cubs with cubs in intact families. Indices to Puma Abundance― Objective 5 This project will develop and test both the efficacy and feasibility, including costs and other management considerations, of using indices to monitor changes in puma abundance. Two such indices are track counts and catch-per-unit-effort. These indices will be calibrated with the estimated puma population. Track Counts An index to puma abundance using counts and classification of puma tracks on snow-covered routes will be developed and tested. This will be done simultaneous with obtaining estimates of puma population size using capture-recapture occasions with houndsmen teams (above) and spatial analysis of home ranges of GPS-collared puma. A 3-year pilot study for this index may be started in year 2 and could be conducted by a graduate student. Information on puma gathered during years 1―2 will facilitate the exact research design. Experimental manipulation of the puma population resulting in a 5-year increase phase and a 5-year decline phase will allow testing the index through known puma population changes and assessment of the sensitivity of the index with the parameter in question― puma population size― by analyzing the statistical power of the method to detect population change (up or down) (Kendall et al. 1992, Beier and Cunningham 1996). The main operating assumption is that the frequency of finding puma tracks on snow-covered routes is related to puma numbers. We will examine the number of individual puma track sets/km (differentiated by size and direction of travel) and presence of puma tracks/km of search route to see 77 �which metric better detects actual population change (Kendall et al. 1992). In addition, we will examine how frequency of different classes of tracks (male, female, females with cubs) may relate to the known puma population changes. The most direct relationship will be a linear one between puma numbers and frequency of encountering puma tracks. Snow-tracking conditions (e.g., powder, crusted, slush, continuous, patchy) will be categorized each search day. Tracking teams, different than houndsmen teams used in capture-recapture occasions, will be used to make the puma track surveys 3 to 6 times per winter. Track surveys will be run on 4-wheel drive vehicles or snowmobiles 1―2 days following snowfall that covers the study area. Effort and costs will be quantified. Catch-Per-Unit-Effort The main operating assumption is that the amount of effort to capture puma is related to puma numbers (Lancia et al. 1996). The puma research team(s) will quantify the number of days required to capture individually identified puma with dogs during each year in the population increase phase. We will also quantify the number of days required to capture unmarked puma with dogs each year, and treat marked puma as though they have been removed from the unmarked population. Number of days per capture will also be quantified by capture teams involved in the capture-recapture occasions each winter. During the decline phase, puma hunters used to reduce the puma population will quantify the number of hunt days per puma captured each winter. Theoretically, the number of days per puma capture should increase as the puma population is reduced by 20% increments in years 6 and 7, and in possible further reductions in years 8―10. Hunters will also be asked to record (i.e., GPS location, date) the total number of tracks of independently-traveling puma (classified as male and female), and the number of tracks of female puma and cubs they encounter during their hunting periods. Male and female track categories will be distinguished by the width of the hind foot plantar pads. Hind foot plantar pad widths that are >52 mm will be classed as male; hind foot plantar pad widths ≤52 mm will be classes as female. We will explore functional relationships of these efforts to the estimated puma population on the study area. Quantifying Puma Diet and Ungulate Kill Rates― Objective 8 Data collected on puma diet and ungulate kills are not directly pertinent to a puma population study. However, they would be basic to an integrated study that involves effects of puma predation on mule deer and elk. Location clusters where puma are located for ≥2 nights will be investigated to estimate puma kill rates of ungulate prey (i.e., days/ungulate kill type/puma class) (Anderson and Lindzey 2003). Sex of animals will be determined by secondary sex characteristics and ages will be estimated from tooth eruption patterns (Quimby and Gaab 1952, Robinette et al. 1957, Dimmick and Pelton 1996) and cementum annuli of incisors (Low and Cowan 1963). Necropsies will be performed on all ungulate prey recovered in the field (Roffe et al. 1996), whether killed by puma or not, and data will be recorded on standard forms. If disease is suspected, whole carcasses or vital organ tissues will be collected and preserved by standard procedures (Roffe et al. 1996) and submitted for analysis to the Colorado Division of Wildlife’s Wildlife Health Laboratory or the Colorado State University Diagonostic Laboratory. An index to physical condition of ungulates prior to death will be estimated from percent marrow fat in femurs or metatarsi (depending on presence; femurs are preferred) (Neiland 1970, Mech and DelGiudice 1985, Fuller et al. 1986, Husseman et. al. 2003). Puma feces will be collected opportunistically year-round and stored by either freezing or oven drying (80-85oC, then stored in paper bags with a fumigant) for later macroscopic diet analysis (Big Sky Laboratory, Florence MT) to estimate frequency of occurrence of prey species (Litvaitis et al. 1996). This research component could also be carried out by a graduate student. 78 �Behavior of Puma Subject to Aversive Conditioning― Objective 9 Information on responses of puma to aversive conditioning is lacking. Individual puma with activities in residential areas on the study area might be research subjects on effectiveness of aversive conditioning. GPS collars on puma would be the primary source of behavioral response data before, during, and after aversive conditioning treatments. Behavior and Survival of Translocated Puma― Objective 10 If translocation is chosen as the method of reducing the puma population during the decline phase (years 6―10), then researchers will remove puma at rates needed to test research hypotheses. Prior to translocation, potential puma habitat areas for the release of the puma will need to be identified which are: 1) relatively remote, 2) large enough to accommodate exploratory movements up to 84 km away from release areas, and 3) not near human residential areas, domestic animal operations, or desert bighorn sheep populations (Ruth et al. 1998, Logan and Sweanor 2001). Puma will be captured alive on the study area, fit with new GPS collars, transported in wooden crates, provided food and water, and translocated by truck a minimum of 120 airline km (75 mi.) for females and 220 airline km (137 mi.) for males (Ruth et al. 1998). GPS collar locations will allow researchers to map movements of translocated puma. The VHF transmitters will allow researchers to quantify survival rates and agent-specific mortality rates. This research could also be carried out by a graduate student. ANALYTICAL Puma class survival rates and agent-specific mortality rates will be estimated by using KaplanMeier (Pollock et al. 1989a, b) and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will also be plotted with survival rate on age in months (Logan and Sweanor 2001:119). To analyze capture-recapture, photographic, and genetic capture-recapture data, closed population capture-recapture models are available in program CAPTURE obtainable at www.mbrpwrc.usgs.gov/software.html and program MARK obtainable at www.cnr.colostate.edu/~gwhite.). Closed population model selection can be achieved with the algorithm based on goodness-of-fit tests and between model tests in program CAPTURE (Otis et al. 1978). For open populations, programs JOLLY (for 1 age class), and JOLLYAGE (handles 2 age classes) are available at www.mbr-pwrc.usgs.gov/software.html. Programs JOLLY and JOLLYAGE contain chi-square goodness-of-fit tests of model assumptions and between model tests that enable researchers to choose the most appropriate model for the data (Pollock et al. 1990). NOREMARK (White 1996), also available at www.cnr.colostate.edu/~gwhite, has an extension that accommodates immigration and emigration; thus, it does not assume geographic closure (but demographic closure is still assumed). Finite rates of increase (Nt+1/Nt) between consecutive years and average annual rates of increase (r) for 3- to 5-year periods will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. Graphical methods will be used to examine relationships of track counts and catch-per-unit effort (i.e., indices to puma abundance) to changes in the population of independent puma. Linear regression procedures and coefficients of determination will be used to assess functional relationships of track counts and catch-per-unit effort to changes in the population of independent puma if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). We will also consider non-parametric correlation methods, such as Spearman’s rank correlation coefficient, to test for a monotonic relationship between the index of abundance and the change in the puma population (Conover 1999). 79 �Statistical analyses will be performed using SYSTAT 10.2 and SAS 6.11. The risk of committing a type I error (i.e., concluding that a population change occurred when it did not) will be controlled at alpha = 0.10 because we will normally have small sample or population sizes (typical of large-carnivore studies). The higher alpha level will increase the probability of detecting a change and reduce the risk of a type II error (i.e., failing to reject a null hypothesis that is false). For managers, the risk of a type II error is probably more important. ArcView 8 geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frame. PRELIMINARY SCHEDULE Years 1―5 (2005―2009) will be the puma population increase phase. Protecting the puma population from sport-hunting will be vital to allowing the puma population to increase within the bounds of the ecological carrying capacity of the study area. This will allow researchers to quantify baseline demographic data on the puma population and test indices to puma abundance during an increase phase. In this phase, capture-recapture occasions, track counts (for index to abundance), and photographic and genetic capture-recapture efforts will begin in about year 2 (2006). Years 6―10 (2010―2014) will be the puma population decline phase. Puma hunters (or translocation) will be used to experimentally reduce the puma population. The portion of independent puma (i.e., adults and subadults) in the population will be reduced by 20% in year 6 and 20% more in year 7 (i.e., a 40% reduction from year 5). Additional reductions may be made to test the indices to abundance or other hypotheses that may be developed and related to effects of harvest or puma predation on mule deer and elk. Those decisions can be made later in project development and as late as years 8―10. REGULATORY NEEDS Puma on the study area that may be involved in depredation of livestock or human safety incidences will not be treated any differently than other puma in Colorado, whether they are marked or not. Thus, they may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). The increase phase in years 1―5 will require a temporary interruption of puma sport-hunting on the study area and protection of radio-collared puma that range off the study area. In years 6―10, regulated puma sport-hunting will resume. POTENTIAL COOPERATORS The Colorado Division of Wildlife will be the principal research and regulating agency in this program. The Bureau of Land Management and the Forest Service will be cooperators because the majority of the study area may be on lands under their management jurisdiction. U. S. D. A., A. P. H. I. S. Wildlife Services may provide puma capture assistance. Private landowners on the study area will be asked to cooperate with this effort. Colorado State University and other universities may cooperate by providing graduate research assistants and professors to carry out specific projects of the research program. Private individuals interested in the puma research may be asked to cooperate in puma capture and monitoring operations. 80 �Table 2. Preliminary puma research schedule. Phase Objectives: 1. 2. 3. 4. 5. 6. 7. 8. 9. Increase (Years 1―5) Decline (Years 6―10) Methods & Data: Initial capture & mark efforts of ≥90% of Capture-recapture estimates (yrs. 6―10) using independent puma (yrs. 1―2). data from physical and photographic & Capture-recapture estimates (yrs. 2―5; 3 genotype captures (if reliable). yr. minimum required for trend) using Reduce puma population using hunting or physical, photographic & genotype translocation. Reduce by 20% increments in captures. Quantify puma population sex & years 6 & 7. Puma hunting will continue, and age structure, density, & population there may be additional population reductions growth rate. in subsequent years. Quantify structure of hunter-kill. Quantify puma population vital rates as Quantify puma population vital rates as population increases. population declines. Quantify agent-specific mortality & puma Quantify agent-specific mortality & road-crossing frequency. vulnerability and selectivity of puma to hunters. Develop and test puma population models Develop and test puma population simulation validated by observed increase phase models validated by observed decrease phase puma population. puma population. Use track counts, catch-per-unit effort, & Use track counts, catch-per-unit effort, & genotype capture-recapture methods as genotype capture-recapture methods (if indices to puma abundance (yrs. 2―5). reliable) as indices to puma abundance. Use GPS data to quantify puma activity in Use GPS data to quantify puma activity in relation to people and human facilities on relation to people and human facilities on the the study area. study area. Use GPS data to quantify puma use of Use GPS data to quantify puma use of habitats habitats and landscape linkages. and landscape linkages. Estimate puma kill rates on mule deer and Estimate puma kill rates on mule deer and elk elk using GPS data. Quantify puma diet using GPS data. Quantify puma diet from from feces. feces. Describe & quantify behavior & survival of translocated puma if translocation is used to reduce the puma population. Begin final data analysis & report year 10. POTENTIAL IMPEDIMENTS Because of the relatively low densities of puma, difficulty of capture and research, obtaining needed sample sizes is expensive. Furthermore, multiple years of study are requisite to fulfill objectives. 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Capturing pumas with foot-hold snares. Wildlife Society Bulletin 27:201-208. _____, and L. L. Sweanor. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. Mace, R. D., S. C. Minta, T. L. Manley, and K. E. Aune. 1994. Estimating grizzly bear opulation size using camera sightings. Wildlife Society Bulletin 22:74-83. McDaniel, G. W., K. S. McKelvey, J. R. Squires, and L. F. Ruggiero. 2000. Efficacy of lures and hair snares to detect lynx. Wildlife Society Bulletin 28:119-123. Mech, L. D., and G. D. DelGuidice. 1985. Limitations of the marrow fat technique as an indicator of body condition. Wildlife Society Bulletin 13:204-206. Miller, S. D., G. C. White, R. A. Sellers, H. V. Reynolds, J. W. Schoen, K. Titus, V. G. Barnes, Jr., R. B. Smith, R. R. Nelson, W. B. Ballard, and C. C. Schwartz. 1997. Brown and black bear density estimation in Alaska using radiotelemetry and replicated mark-resight techniques. Wildlife Monographs 133:1-55. Murphy, K. M. 1983. Relationships between a mountain lion population and hunting pressure in western Montana. Final Report, Federal Aid in Wildlife Restoration, Project W-120-R13 and 14. Montana Department of Fish, Wildlife, and Parks, Helena. Otis, D. L., K. P. Burnham, G. C. White, and D. R. Anderson. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. Ott, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. Pojar, T. M. 2000. Investigating factors contributing to declining mule deer numbers. Colorado Division of Wildlife, Wildlife Research Report, Federal Aid in Wildlife Restoration Project W-153-R-13, Progress Report. Fort Collins, Colorado, U.S.A. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989a. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. _____, S. R. Winterstein, and M. J. Conroy. 1989b. Estimation and analysis of survival distributions for radio tagged animals. Biometrics 45:99-109. _____, J. D. Nichols, C. Brownie, and J. E. Hines. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs 107:1-97. 83 �Quimby, D. C., and J. E. Gaab. 1952. Preliminary report on a study of elk dentition as a means of determining age classes. Proceedings Western Association of State Game and Fish Commissions. 32:225-227. Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134-153. Ruth, Tik, K. A. Logan, L. L. Sweanor, M. G. Hornocker, and L. L. Temple (1998) Evaluating cougor translocation in New Mexico. Journal of Wildlife Management 62:1264-1275. Sweanor, L. L., K. A. Logan, and M. G. Hornocker. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. _____, K. Logan, J. Bauer, and W. Boyce. 2004. Puma and humans in and around Cuyamaca Rancho State Park, San Diego County, California. School of Veterinary Medicine, University of California, Davis. Trolle, M., and M. Kery. 2003. Estimation of ocelot density in the pantanal using capture-recapture analysis of camera-trapping data. Journal of Mammalogy 84:607-614. Van Ballenberghe, V. 1983. Rate of increase of white-tailed deer on the George Reserve: a re-evaluation. Journal of Wildlife Management 47:1245-1247. Van Dyke, F. G., R. H. Brocke, and H. G. Shaw. 1986. Use of road track counts as indices of mountain lion presence. Journal of Wildlife Management 50:102-109. Van Sickle, W. D., and F. G. Lindzey. 1992. Evaluation of road track surveys for cougars (Felis concolor). Great Basin Naturalist 52:232-236. White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. _____. 1996. NOREMARK: population estimation from mark-resighting surveys. Wildlife Society Bulletin 24:50-52. Prepared by ______________________ Kenneth A. Logan, Wildlife Researcher 84 �Table 3. Estimated project costs for years 1―5 only. Budget Item Personnel: -DOW Researcher -Houndsman -Project Technician -Temporary Technician Volunteers Support: Lodging, food, fuel for 8―12 Vehicles: -4x4 Trucks (2) -all terrain vehicles (3) -snowmobiles (1)a -utility trailers (1)a -dog sled & trailer Gasoline Vehicle Maintenance GPS- & Radio-telemetry: -GPS-collars -VHF-collars (cub) -cub collar material -command unit (1) -receivers, type (2) -H-antennae (3) -omni antennae (3) -coaxial cables (2) -coaxial cables (2) -antenna switch-box (2) -intercom system (1) -head sets (2) Capture Equipment: -drugs -cage trap -snares -call box -miscellaneous (darts, vials, syringes, needles, envelopes, gloves, tapes, calipers, thermometers, ear-tags, tattoos, etc...) Dog Care: -veterinary -food Aerial Support: Work tack: -backpacks, climbing gear, nets, ropes, office materials, etc... Laboratory: -genetics -carcass or tissue analysis -fecal analysis Photographic: -trail cameras (~40) -film (~200) Total a Year 1 Year 2 Year 3 Year 4 Year 5 K. Logan’s support not incl. 12,500 ($2,500/mo.*5 mo.) 35,000 33,000 12,500 35,000 33,000 13,125 35,000 33,000 13,125 35,000 33,000 13,781 35,000 33,000 0 15,000 15,000 15,000 15,000 50,000 (2*$25,000) 18,600 (3*$6,200) 5,300 1,900 1,000 4,800 (2*$2,400) 3,000 0 0 0 0 0 4,800 3,000 0 0 0 0 0 4,800 3,000 60,000 0 0 0 0 4,800 3,000 0 0 0 0 0 4,800 3,000 114,750 (25*$4,590) 3,192 (12*$266) 100 4,500 5,390 (2*$2,695) 636 (3*$212) 234 (3*$78) 56 (2*$28) 29 (2*$14.50) 112 (2*$56) 285 300 (2*150) 0 0 0 0 0 0 0 0 0 0 0 0 22,950 1,596 50 0 0 0 0 0 29 0 0 0 22,950 0 0 0 0 0 78 56 0 56 0 0 22,950 1,596 50 0 0 0 0 0 29 0 0 0 650 (25*$26/bottle Telazol) 2,000 (2*$1,000) 1,000 850 1,000 650 0 0 0 1,000 650 0 0 0 1,000 650 0 0 0 1,000 650 0 0 0 1,000 2,000 600 (120/mo.*5 mo.) 40,000 ($200/hr x 4 hr x 50) 2,000 600 40,000 2,000 600 40,000 2,000 600 40,000 2,000 600 40,000 2,000 1,000 1,000 1,000 1,000 4,650 (25*$186) 600 4,650 4,650 600 4,650 4,650 600 4,650 4,650 600 4,650 4,650 600 4,650 0 (40*$430) 0 (250*$6) 354,684 17,200 1,500 177,150 4,300 1,500 189,500 0 1,500 243,715 0 1,500 185,856 Two snowmobiles and 1 trailer are already available for the project. 85 �APPENDIX I Sex Determination of Mountain Lions Bayed in Trees With little effort the sex can be determined for a mountain lion bayed in a tree. Refer to the photos of the different lions, 4 males (A―D) 2 females (E, F), attached to these tips. Male adult and subadult lions have a conspicuous black spot of hair, about 1 inch diameter, surrounding the opening to the penis sheath behind the hind legs and about 4 to 5 inches below the anus. In between the black spot and the anus is the scrotum, which is usually covered with silver, light brown, and white hair. Therefore, look for the black spot and scrotum. The anus is usually hidden below the base of the tail. Female adult and subadult lions do not have the black spot or scrotum behind the hind legs and below the base of the tail. There is just white hair there. The anus is directly below the base of the tail, and the vulva is directly below the anus. The anus and vulva are usually hidden by the base of the tail. Teats of females are usually inconspicuous, even of mothers with weaned cubs or mothers that have just finished nursing cubs. So teats are usually not a good indicator of sex in treed lions. Sometimes sex determination of lions can be done with the naked eye. But use a pair of binoculars to make sexing lions easier. If a lion’s position in a tree obscures your view, you can get the lion to move around for a better look. Pick up a baseball-bat-size branch and bang on the trunk of the tree. If there is snow on the ground, throw a few snow balls at the lion. You can even climb the tree toward the lion. These actions usually get the lion to move. When it does, be ready to sex the lion. Also, sometimes the lion urinates when bayed by dogs or when a person climbs the tree toward it. Look for the origin of the urine stream. If the urine stream comes from behind the hind legs about 4 to 5 inches below the anus, then the lion is probably a male. If the urine stream comes from under the base of the tail, then it’s probably a female. Tracks may also be indicative of sex. Adult and large subadult male lions usually have hind foot plantar (“heel”) pad widths that exceed 2 1/16 inches (52 mm). Adult and subadult female lions usually have hind foot plantar pad widths less than or equal to 2 1/16 inches. Carry a small ruler or wind-up metal tape in your pocket to make measurements 86 �Male Mountain Lions (A―D) Penis Spot, Scrotum, Anus. Penis (black) spot ~1 inch dia. is ~4-5 inches below anus. A B K. Logan photo K. Logan photo D K. Logan photo Female Mountain Lions (E, F) Vulva directly below anus, both usually hidden by base of tail. No “black spot” 4-5 inches below anus C E K. Logan photo K. Logan photo F 87 K. Logan photo �88 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Task 2 Colorado Federal Aid Project: N/A : : : : 3004 Cost Center 3430 Mammals Research Other Ungulate Conservation Potential Research Project Assessment : Period Covered: July 1, 2003 through June 30, 2004 Author: Eric J. Bergman and Gary C. Miller Personnel: D. Freddy, C. Bishop, B. Watkins, J. Madison, J. Broderick All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT As part of the research planning process, general assessments were made for the potential to conduct research projects on 3 main topics identified by Colorado Division of Wildlife field management personnel. These topics were: impacts of mule deer/elk interactions on mule deer population performance; improving success of bighorn sheep reintroductions and translocations; and, impacts of natural gas and oil extraction on mule deer. All 3 topics present challenges to conducting successful research endeavors with deer-elk interaction studies potentially providing the most predictable research and funding situations. 89 �JOB PROGRESS REPORT POTENTIAL RESEARCH PROJECT ASSESSMENT Eric J. Bergman INTRODUCTION The Colorado Division of Wildlife is charged with protecting, preserving and enhancing Colorado's ungulate populations for the use, benefit, and enjoyment of the people. The management principles guiding managers in this mission include: wildlife conservation, use and enjoyment, maintaining healthy, diverse and abundant populations and maintaining/conserving habitat quality/quantity through science-based decision making (Colorado Div. of Wildlife 2002-2007 Strategic Plan:9). The objective of ungulate research is to provide information to facilitate the making of these science-based decisions. METHODS Members of the Division’s Mammals Research staff met with wildlife managers and biologists from the Northwest and Southwest Regions to consult on ungulate management issues and research needs. The following topics were identified as the primary statewide issues of concern: ● Negative impacts of deer/elk interactions on deer population performance. ● Variable success of bighorn sheep reintroduction/translocation efforts. ● Impacts of natural gas and oil extraction on deer. In general, research topics identified by wildlife managers favored issues occurring in their respective areas and regions. Topics identified by biologists emphasized need for broad-scale research efforts to address issues that exist throughout the state. The objective of research project selection is to successfully merge these two viewpoints into a study that: 1) Provides clear results through control/treatment experiments. 2) Addresses issues of local and statewide concern. 3) Allows inference to wide spatial/temporal boundaries. RESULTS AND DISCUSSION Impacts of Deer/Elk Interactions on Deer Population Performance A general long-term trend of mule deer population declines has existed both in Colorado and throughout the Western U.S. since the late 1950s (Unsworth et al. 1999, Gill 2001). While insular deer herds have functioned outside of this trend and others have experienced pulses of population growth nested within this long-term decline, declines of as much as 50% have been reported (Colorado Division of Wildlife, unpublished data). Along with these overall population declines, depressed fawn:doe ratios have been simultaneously measured (Gill 2001, White et al. 2001). In an attempt to address concerns over these declines and to develop working hypotheses as to the underlying causes, CDOW hosted a conference for employees of CDOW, CSU, federal agencies, invited publics and deer experts in 1998. A result of this conference was the identification of five potential sources of mule deer population depression: A) habitat deterioration, B) predation, C) competition with elk, D) disease, and E) weather (Fig. 1). Based on a coupling of the ideas from this conference with existing knowledge of mule deer/coyote predation dynamics (Bartmann et al. 1992), CDOW entered a collaborative mule deer 90 �research program with Idaho Fish and Game. Two studies were simultaneously developed. Idaho began a mule deer predation study that is currently assessing the impacts of predator control (both puma and coyote) on mule deer survival. The Division of Wildlife began a nutrition study to simulate and quantify the demographic impacts of habitat enhancement on mule deer fawn survival (Bishop 2003). Through a treatment/control, cross-over study design, CDOW is providing supplemental forage as a mechanism to test the effects of an immediate, short-term enhancement of mule deer habitat (Bishop 2003). Preliminary results of this ongoing research indicate that by enhancing the nutritional value of mule deer diets, overwinter fawn survival can be increased (Bishop 2003). While the methods employed through this research are not an acceptable management strategy to the Division, the pending conclusions exemplify the need for landscape level treatments to enhance mule deer habitat (discussed below). As such, through a series of reductionist experiments, it has been demonstrated that mule deer population performance is directly related to habitat quality, yet functions somewhat independently of coyote predation. However, a confounding factor in these conclusions stems from the fact that concurrent with mule deer declines in Colorado, there has been a dramatic increase in the distribution, number and density of elk. Accordingly, while enhancing the quality of habitat should improve mule deer survival, the ultimate causes of habitat degredation have not been tested. It remains unclear whether interference/exploitation by elk has further reduced carrying capacity for mule deer in late seral stage pinyon-juniper ecosystems. Based on past research, there is variable evidence that competition between mule deer and elk exists. Both interference and exploitation competition have been reported for deer and elk (Singer and Norland 1994, Kirchoff and Larsen 1998, Stewart et al. 2003). However, due to logistical constraints, these studies have been observational and are highly dependent on the specific conditions at which the data was collected. Thus, strong inference is not possible. In order to accurately quantify the impacts of deer/elk competition, a study would need tight control over ungulate densities. Under ideal conditions, this would be done in a controlled setting (i.e. large enclosures). Due to financial constraints and disease potential, this is not possible in Colorado. Additionally, enclosures with controlled densities of deer and elk remove much of the natural variation that exists in nature. Elk are highly mobile animals with weak site fidelity. Thus, while deer may encounter high elk densities one week, they could very easily encounter no elk the following week. Enclosures with static deer and elk densities would remove this variability and subsequent results would be of limited utility. Elk mobility is also the primary reason that density reduction treatments cannot be applied in field settings. A dramatic harvest treatment to reduce local elk density could be erased as elk immigrate into the treatment area once harvest is finished. Given these constraints, the possibility of studying the interactions between deer and elk still exists. Currently, the potential to do this is presenting itself on the Uncompahgre Plateau. The proposed follow-up to the short-term deer nutrition research is the implementation of large scale deer habitat enhancement treatments. However, there is concern that elk will monopolize treatment areas and will either displace deer or deprive deer of receiving the intended treatment. As such, regardless if elk are being studied, mitigation efforts will have to be employed to insure the delivery of treatments to deer. Due to the baseline knowledge on deer in the Uncompahgre system (C. Bishop, unpublished data, B. Watkins, unpublished data), the existing capital investment and given the fact that elk treatments would be an integral part of any deer habitat enhancement study, many of the financial and logistic hurdles to starting a complimentary elk research program would be minimized. 91 �Declining Mule Deer Habitat Quality Bishop Phase I Enhanced nutrition study showing increased fawn survival NO Collaborative deer/elk research Deer/Elk Interactions Problems: -Will elk displace deer in treatment areas? -Can we successfully apply treatments on large temporal & spatial scales? MULE DEER ISSUES -Low Populations -Poor population parameters Ongoing CWD Research No Evidence To Date Is disease depressing deer populations statewide? Have drought conditions negatively impacted deer? NO No clear Evidence Disease Bishop study, 5 statewide study areas Puma Research & Mgmt. Measure species/sex/age class of puma kills using deer & elk radio collars (K. Logan) Do coyotes force poor population performance? Miller, Wolfe, Baeten, Etc. Monitoring of deer mortalities for disease Has elk population expansion: -displaced deer? -put deer at an exploitation disadvantage? Can we enhance nutrition through habitat treatments? Are late seral stage pinon/juniper communities conducive to quality deer production? Do puma force poor population performance? Compensatory mortality in a Colorado mule deer population Weather Predation Bartmann et al. (1992) Figure 1. Conceptual model concerning mule deer population declines in Colorado with an emphasis on the relationships between sources of population depression (light gray boxes), current and past research (dark gray boxes) and potential research (dashed lines). A final benefit to conducting a study on the interactions between elk and mule deer on the Uncompahgre Plateau pertains to ecosystem level understanding. As the likelihood of puma research being conducted on the Uncompahgre Plateau increases, the addition of elk research would allow for integrated, broad scale understanding of deer, elk and puma management. Over the past 25 years, wildlife ecologists have strived to understand ecosystem level interactions (Sinclair and Norton-Griffiths 1979, Houston 1982, Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001). However, a fundamental feature of these studies is that they were conducted in systems that were managed for species conservation (i.e. no hunting), limiting the utility and applicability in systems where species are managed as a consumptive resource. All elements will likely be in place to do ecosystem level research in a system that is managed with a multi-use strategy. The level of interest within the CDOW and other western state agencies in studying deer/elk interactions is high (D. Freddy, unpublished study plan, 1998). Additionally, based on high priority achievements H-1.2 and H-1.3 of the Colorado Division of Wildlife Strategic Plan (2002-2007), research on these issues are highlighted as guiding principles of Division activities. This interest is being echoed by external conservation groups. Over the past decade, the Uncompahgre Project of southwest Colorado has actively pursued habitat enhancement on the Uncompahgre Plateau. This group has expressed interest in coordinating their proposed habitat manipulations with wildlife research, potentially relieving the Division of the financial burden of conducting landscape level treatments (R. Sherman, personal communication). Additionally, it is believed that groups such as the Mule Deer Foundation and the Rocky Mountain Elk Foundation would be willing to invest in research that further explains the impacts of deer/elk interactions as well as the effectiveness of habitat enhancement for these species. 92 �Variable success of Bighorn Sheep Reintroduction/Translocation Efforts During the late 1800's and early 1900's, the rocky-mountain west experienced dramatic declines in bighorn sheep populations (Singer et al. 2000a). Due to the role that bighorns play in ecosystems and their value as both a watched and hunted species, recovery is a high priority. Approximately 55%-58% of the existing populations are a result of reintroduction efforts (Singer et al. 2000b). However, reintroduction efforts have been variable in success (success rates fall between 40% and 58%) (Singer et al. 2000a, Singer et al. 2000b). While these trends and statistics are for the west as a whole, most are indicative of bighorn management efforts within Colorado (Bailey 1990). There are many parameters that influence the success of bighorn sheep reintroduction efforts. Among these, survival, density, metapopulation characteristics, habitat quality/quantity, disease and predation have all been identified as potential limiting factors (Fig. 2). However, due to the lack of experimental manipulation, the relative importance of any single parameter is largely unknown. Bighorn population characteristics are poorly understood, yet are likely important for planning and implementing successful recovery efforts. Many recovery efforts appear to be typified by brief periods of very high population growth, followed shortly by stabilization and population crash (Singer et al. 2000c). In the absence of disease, adult survival is typically high. However, lamb survival can be impacted by density as well as weather (McCarty and Miller 1998, Holl et al. 2004). In the absence of dispersal corridors, and due to potential growth rates as high as λ = 1.30 (Singer et al. 2000c), many recovering bighorn populations suffer from sedentariness. Because bighorns can quickly reach the local carrying capacity of a patch, and due to high adult survival, the instigation of senescence at approximately 7-9 years of age, and low dispersal, it is possible that recovery efforts fail simply because no new individuals are entering the population. A manipulative, research approach to addressing this question is to emulate dispersal through the selective removal of senescent individuals, thereby reducing density and forage pressure such that lamb survival can increase. Bighorn sheep are thought to have traditionally functioned as a metapopulation, with a single population being characterized as a discrete group with limited movement of individuals between groups. While limited in overall quantity, the role of immigration and emigration is vital in metapopulation stability. Dispersal typically occurs in the form of animals leaving one population to join another existing population (i.e. into contiguous, occupied habitat) (Singer et al. 2000a). While providing relief for dense populations, dispersal also provides other populations with new genetic stock. Unfortunately, most recolonization efforts have focused on filling insular habitat patches with a single population and dispersal is not considered. By taking a multi-patch view of the landscape and populating several patches with animals, a metapopulation could be established. Bighorn sheep habitat is typified by open vegetation structures with high visibility and rough terrain to avoid predation (Singer et al. 2000a). Additionally, typical bighorn sheep habitat is composed of climax (late-seral stage) plant communities. These habitats occur naturally (as well as through human influence) in a fragmented fashion across the landscape, further explaining the metapopulation structure. Movement between habitat patches is easily arrested by physical barriers such as rivers and roads (Singer et al. 2000b). Absence of these key habitat characteristics and presence of barriers are all factors that potentially have a negative impact on recovery efforts. Unfortunately, experimental research has not been conducted to determine the actual importance of any single parameter. Disease has also been identified as a potential arresting factor in recolonizing bighorn populations. Epizootic breakouts can reduce bighorn sheep populations by >20%/year (McCarty and Miller 1998). Typically epizootic breakouts are in the form of Pasturella haemolytica, however, parainfluenza-3 and other Mycoplasma outbreaks have also been documented (Singer et al. 2000c). In Colorado, lungworm (Protostrongylus spp.) has also been prevalent. Diseases such as bacterial 93 �pneumonia are often introduced to bighorn populations via exposure to domestic sheep (Goodson 1982). In a massive reintroduction program throughout the west during the 1990’s, a 16km buffer between wild and domestic sheep populations was deemed necessary for habitat to be classified as suitable for bighorn reintroductions (Singer et al. 2000a). Precautionary vaccination programs have been instituted, but reported results have not indicated that such approaches greatly enhance bighorn population recovery (Miller et al. 2000). Inoculation Experiment: Harvest Experiment: Can reintroduced animals be immunized to reduce susceptibility? Can population growth be slowed via limited harvest? Density Does initial population growth exceed carrying capacity at release sites, instituting density dependent limitations prior to initiation of dispersal events? Habitat Can disease vectors be removed? Disease - Does disease limit growth? - Can disease be eliminated? -Is habitat quality/quantity at reintroduction sites conducive to desired population growth? Puma Mgmt. Habitat Experiment: -Can we improve habitat by reducing fragmentation and providing dispersal corridors? Livestock Removal Experiment: Bighorn Issues -Variable success of reintroduction efforts (See Logan’s Program Narrative) Predator Control Experiment: -Does blanket lion removal facilitate re-establishment of bighorn populations? - Is selective removal of offending cats less effective than blanket removal? Metapopulation -Do reintroduction efforts establish metapopulations that function outside of immigration and are thus extremely susceptible to devastational stochastic events Reintroduction Experiment: -Does a multi-stage, long-term release strategy that emulates immigration increase reintroduction success? Predation - Do lions limit population growth in reintroduced populations? Figure 2. Conceptual model concerning the variable success of bighorn sheep reintroduction efforts with emphasis on the relationships between limiting factors (gray boxes) and research possibilities (dashed lines). The role of puma predation on bighorn sheep populations is heavily debated in the literature, but in some circumstances is thought to be the limiting factor in bighorn population growth (Wehausen 1996, Hayes et al. 2000, Holl et al. 2004). In Colorado, the impacts of puma predation on desert bighorn sheep are an issue of concern. For instance, it is believed that recent desert bighorn recovery efforts in the Dolores canyon were unsuccessful due to puma predation. Of the 12 radio-collared animals in this population, 11 have died. Nearly 100% of these deaths were due to predation (those not classified as predation were classified as unknown) (B. Watkins, unpublished data). Due to this preliminary evidence, an experimental research project that addresses the impact of puma predation on desert bighorns would likely be beneficial to future desert bighorn recovery efforts. In summary, there are many management-driven experiments that could be designed to elucidate the effectiveness of different management approaches to the recolonization of bighorn sheep. In fact, many of the potential treatments have been conducted in a non-experimental fashion (see Bailey 1990 for a review). On the western slope of Colorado, the number of potential study sites for bighorn sheep research is high. The Dolores Canyon (west of Durango) has had several failed reintroduction efforts, 94 �despite being classified as viable bighorn habitat. The Escalante, Dominguez and Roubideau canyons east of the Uncompahgre Plateau all have bighorn sheep. However, this population is currently suffering from a Pasturella outbreak (B. Watkins, personal communication). Finally, Colorado National Monument and Debeque Canyon are potential study sites. Because many of these issues take place at the population level, any study would be long-term and broad in scale. Although not explicitly detailed, conservation of bighorn sheep (especially desert bighorn sheep) is loosely prioritized in section S-2 of the CDOW strategic plan (conservation of native species). External funding for this type of research would be difficult to secure. While private groups are interested in bighorn restoration, the level of support needed to address these questions is likely greater than that which they can provide. In terms of logistical support, based on conversations with Division employees from local through the regional levels, interest and support for this research is high. Impacts of Natural Gas and Oil Extraction on Deer and Elk. The impact of natural gas and oil development on deer populations in Colorado appears to be a cyclical issue driven by economics, political policy and current world affairs. Of the impacts that resource extraction can have on deer populations, the two of most immediate concern are space use patterns and population performance (Fig. 3). In terms of space use, deer behavior can shift on broad scales, fine scales or both. For instance, a broad scale shift might manifest itself in the form of animals vacating any area where development is occurring. A fine scale shift might manifest itself in the form of avoiding habitat types, but not abandoning areas of development. Little information for this type of impact has been published. In face of the sparse literature pertaining to the impacts of development on deer and elk, there is information available that pertains to the impacts of development on caribou. Behavioral adaptations similar to those mentioned above have been documented for caribou in response to resource extraction in the arctic (Cameron et al. 1992, Nellemann and Cameron 1998, Dyer et al. 2001, Nellemann et al. 2003). Despite documented shifts in caribou distribution and density, there has been no documentation of negative population level impacts caused by resource extraction. In fact, the number of caribou in the Central Arctic caribou herd increased from 5,000 to 20,000 during oil-field development (between 19751997, Cronin et al. 2000). Similarly, while calving caribou and cow/calf pairs have been observed to avoid roads, a depression of calf survival was not reported (Nelleman and Cameron 1998). While space use behaviors are important, the DOW is primarily concerned about mule deer population performance. Of the population parameters that could potentially be impacted, fawn survival is the most sensitive to disturbance and is subsequently the key parameter for monitoring. Of additional note, measuring changes in the proximate physiological factors that lead to depressed fawn survival may be an avenue for exploring the impacts of resource extraction if monitoring fawn survival is unrealistic. Within the history of Colorado, the impacts of natural resource extraction on wildlife is a subject that has not been ignored. During the 1980's, the U.S. Department of Energy funded research on deer survival on the CA and CB tracts of the Naval Oil Shale Reserve in northwestern Colorado. This research was to be extended to include the impacts of oil-shale development. However, due to financial limitations in the extraction process, development never progressed beyond the initial phase (G. White, personal communication). A pilot study addressing the impacts of natural gas drilling on deer space-use is currently underway in southern Colorado (S. Wait, personal communication). Based on what is known about the current distribution of development, there are essentially two potential study areas in Colorado. There is interest in studying these impacts along the I-70 corridor where gas pad density approaches 1 per 20 acres. Development for natural gas extraction is also either occurring or proposed for the Roan plateau, as well as the Mamm and Divide Creek basins. Unfortunately, the current density of extraction platforms in the Mamm and Divide Creek basins is too high for a controlled experiment. The feasibility of conducting research on the Roan Plateau is unknown. Based on public sentiment reflected in the news media, development on the Roan Plateau is hotly contested. In order for this study to be accomplished, 95 �the Division would likely be placed at odds with this public sentiment due to the need for intense development as a treatment effect. Away from the I-70 corridor, development is also underway in southwestern Colorado (east of Durango, see above). This area likely offers the greatest possibility for advanced research on this issue due to the ongoing dialogue between management agencies, and the advanced stages of research activity. Additionally, because development is progressing at a slower rate in this region, and because much of the proposed development is on the Southern Ute Indian Reservation, there is potential for conducting experimental research. Fawn Survival Is fawn survival negatively impacted by development? Adult Survival Is adult survival negatively impacted by development? Population Performance Pregnancy Rates What are the population level impacts of development/? Will pregnancy rates be reduced due to stress and/or nutrition? Impacts of Natural Gas and Oil Development on deer and elk populations Temporal Response Are the impacts of development permanent, or will deer and elk become accustomed to the change and adapt accordingly? Spatial Response Do deer and elk respond to development by changing space-use patterns? Resource Selection Do deer and elk respond to development by changing selection patterns? Figure 3. Conceptual model concerning the impacts of oil and gas development on deer and elk populations, with emphasis on potential impacts (gray boxes) and research possibilities (dashed lines). From a greatly simplified viewpoint, natural resource extraction can be broken into two phases. Phase one is primarily composed of the building of infrastructure (i.e. road building, pipeline building, drill pad leveling, pump installation, etc.). The subsequent phase two is composed of steady state resource extraction (Fig. 4). In terms of impacts on deer, phase one is likely to have a strong, negative impact that is relatively short-lived. Infrastructure construction is typically high intensity and may be accompanied by a shift in space use behavior of deer (the longevity of this shift is open to debate). Phase two is typified by the physical extraction of the resource, a highly mechanized process that could require very little human presence on a daily basis. Due to the longevity of phase two, it is likely to have the longest lasting impact on deer (though the impact itself may be more subtle). However, the above described progression of development is an oversimplified scenario of how events could take place. Numerous uncertainties affect the rate of development, many of which are tightly linked to current governing policy and the overall state of the economy. For instance, it is possible that due to economic hardship or due to inefficiencies in the resource refining process, development would be aborted before the completion of phase one (Fig. 5). This sequence of events are similar to those that took place during the 1980's on the CA and CB tracts of the Naval Oil Shale Reserve (G. White, personal communication). 96 �Conversely, it is also possible that regulatory policy could be relaxed during phase one of development. Thus, instead of progressing into phase two, phase one would be closely followed by a period of even more intense development (Fig. 6). The most likely scenario for the rate of development over the next 10-15 years, however, is a merger of both of these last two possibilities (i.e. development that is marked by peaks and valleys driven by the policy and economic events of the time, Fig. 7). As such, any study would have to accommodate a highly unpredictable and sporadic development pattern (Fig. 8). As mentioned above, published experimental research on the impacts of resource extraction has been scarce. The reasons for this can largely be condensed to three primary problems: 1) the lack of experimental control, 2) the necessity for long-term commitment, and 3) cost and logistics. For experimental research to occur, the needed approach would be a treatment/control study design. Due to the fact that the natural process variation of mule deer fawn survival ranges between 0.04 and 0.81 (Unsworth et al. 1999) and to the longevity of this study, a pre/post experimental design would not provide meaningful results. However, through a treatment/control design, the confounding effects of this annual variation would be eliminated. Thus, the issue turns to maintaining clean control/treatment study areas and clean treatment affects. The criteria for a control study area include: 1) quality deer winter range similar to the treatment area (i.e. similar geographic, topographic and botanical composition), 2) close proximity to the treatment study area, such that annual weather patterns are shared between the treatment and control areas, 3) being located far enough from the treatment study area that development activities do not influence deer on the control site, 4) having no pre-existing development, and 5) remaining free of on site and nearby resource extraction/exploration during the 10-15 years covering the experiment. The criteria for an adequate treatment study area are equally complex. In addition to the underlying criteria for a control site, a treatment study area would need: 1) an absence of any pre-existing development, 2) a "phase one" development schedule that is not subject to change (regardless of political, social or economic factors), and 3) a "phase two" period of steady-state extraction and maintenance that is also void of further mining and exploration. Despite great efforts, these criteria would be difficult to meet. Mining companies cannot afford to slow the extraction process if the allowable rate increases, and likewise, they cannot afford to continue pumping if it isn't economically feasible. These economic and social factors that drive production are outside the control of DOW, DNR, high level political officials and the mining companies themselves. Long term commitment is a factor that plagues all long term research programs. However, a failed commitment to see an experiment on oil/gas development to completion would provide very little in terms of knowledge. For many long term research projects the delivery of a treatment occurs in the early stages, only to be monitored in the later years. The treatment in a study concerning oil/gas development would be two-fold, i.e. the treatment (or lack thereof) would be applied every year for 10-15 years. Willingness to maintain this program would need to persist in light of the political and economic changes that will inherently occur. Policy regulating natural resource extraction could become more stringent or more relaxed (discussed above). If the economic potential of development is not realized, long term commitment is not feasible. 97 �Phase Two Phase One LEVEL OF DISTURBANCE HIGH NONE Figure 4. A conceptual diagram showing the ideal separation between phases of natural resource extraction and subsequent development. Phase one is typified by high intensity, infrastructure construction. Phase two is typified by lower intensity, higher longevity, extraction processes. Phase Two Phase One LEVEL OF DISTURBANCE HIGH NONE Figure 5. A conceptual diagram showing potential separation between phases of natural resource extraction and subsequent development. As opposed to ideal conditions, phase one could be cut short due to changes in the economy or changes in regulatory policy. Phase Two Phase One LEVEL OF DISTURBANCE HIGH NONE Figure 6. A conceptual diagram showing potential separation between phases of natural resource extraction and subsequent development. As opposed to ideal conditions, phase one could be followed immediately by further development, a result of economic incentives or relaxation in regulatory policy. 98 �Phase Two Phase One LEVEL OF DISTURBANCE HIGH NONE Figure 7. A conceptual diagram showing likely separation between phases of natural resource extraction and subsequent development. As opposed to ideal conditions, phase one will probably be followed by highly fluctuating stages of further development and extraction. The peaks and valleys of this scenario would be driven by normal economic variation and changes in regulatory policy. Phase Two Phase One LEVEL OF DISTURBANCE HIGH NONE Figure 8. A diagram showing the potential development patterns that could be encountered during experimental research on the impacts of resource extraction. The variability shown in phase two is an uncontrollable product of changing economic patterns and changing regulatory policy. The lack of control highlighted by this figure demonstrates the underlying reason that experimental research on this issue is impossible. Cost, the third factor, is also an obstacle encountered during any study. Based on power calculations from other mule deer fawn survival studies, a sample size of 40 marked fawns per study area was deemed necessary to detect a 15% change in fawn survival (Bishop 2000). However, in this example, experimental design increased the power of detecting this difference in excess of 80% because annual results could be pooled over consecutive years. A compiling of consecutive years is not possible when studying the impacts of resource extraction because a carry over effect is present and the impact of development compounds each year. Thus, reductions in fawn survival would need to be captured on a yearly basis. A preliminary power analysis (α=.05, β=.20) using estimates of fawn survival of µ=.444 and SD=.217 (Unsworth et al. 1999) indicated that 60 marked fawns per study area would be needed to have an 80% chance of detecting a 15% change in survival. However, a 15% change in survival is unrealistic in the face of published literature. A more likely expectation is in the realm of a 5%-10% decrease. Thus, more appropriate sample size estimates are between 125 (to detect a 10% change) and 480 (to detect a 5% change) for each of 2 study areas (annual sample sizes would thus range from 250-960 individuals). 99 �Due to a lack of dialogue with personnel from natural gas and oil companies, the DOE, the Colorado Oil and Gas Conservation Commission and the Southern Ute Indian Reservation, the possibility of external funding for this type of research is unknown. Based on past efforts of these entities, it is believed that some level of financial support is possible. The issue of development is addressed by high priority achievement H-1.3 of the CDOW Strategic Plan (2002-2007). While the impacts of natural gas and oil extraction development, per se, are not addressed, they do qualify as a developmental issue of concern. SUMMARY Mule deer/elk interactions, bighorn sheep translocation, and impacts of natural gas and oil extraction are all topics that present suitable and needed research investigations. At this time, moving forward on mule deer/elk interactions appears to be the most reasonable course of action. Cooperative commitments between industry and the State of Colorado appear needed before research could be initiated to meaningfully assess the impacts of natural gas extraction on mule deer populations LITURATURE CITED Bailey, J.A. 1990. Mangement of rocky mountain bighorn sheep herds in Colorado. Colorado Division of Wildlife: Special Report No. 66. Bartmann, R.M., White, G.C. and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs No. 121. Bishop, C.J. 2000. Effects of habitat enrichment on mule deer recruitment and survival rates. Program Narrative, Colorado Division of Wildlife. Bishop, C.J. 2003. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife: Job Progress Report. Cameron, R.D., Reed, D.J., Dau, J.R., and W.T. Smith. 1992. Redistribution of calving caribou in response to oil field development on the arctic slope of Alaska. Arctic, 45: 338-342. Cronin, M.A., Whitlaw, H.A., and W.B. Ballard. 2000. Northern Alaska oil fields and caribou. Wildlife Society Bulletin, 28: 919-922. Dyer, S.J., O'Neill, J.P., Wasel, S.M. and S. Boutin. 2001. Avoidance of industrial development by woodland caribou. Journal of Wildlife Management, 65: 531-542. Gill, R.B. 2001. Declining mule deer populations in Colorado: Reasons and Responses. Colorado Division of Wildlife: Special Report No. 77. Goodson, N.J. 1982. Effects of domestic sheep grazing on bighorn sheep populations: a review. Proceedings of the biennial symposium of the Northern Wild Sheep and Goat Council 3:287-313. Hayes, C.L., Rubin, E.S., Jorgensen, M.C., Botta, R.A. and W.M. Boyce. 2000. Mountain lion predation of bighorn sheep in the Peninsular Ranges, California. Journal of Wildlife Management 64:954959. Holl, S.A., Bleich, V.C. and S.G. Torres. 2004. Population dynamics of bighorn sheep in the San Gabriel Mountains, California, 1967-2002. Wildlife Society Bulletin 32:412-426. Houston, D.B. 1982. The northern Yellowstone elk herd: ecology and management. Macmillan Publishing Co., New York, New York, USA. Jedrzejewska, B. and W. Jedrzejeswki. 1998. Predation in vertebrate communities: the Bialowieza Primeval Forest as a case study. Springer-Verlag, New York, New York, USA. Kirchoff, M.D. and D.N. Larsen. 1998. Dietary overlap between native Sitka black-tailed deer and introduced elk in southeast Alaska. Journal of Wildlife Management 62:236-242. Krebs, C.J., S. Boutin and R. Boonstra. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, Oxford, England. McCarty, C.W. and M.W. Miller. 1998. Modeling the population dynamics of bighorn sheep: a synthesis of literature. Colorado Division of Wildlife: Special Report No. 73. 100 �Miller, M.W., J.E. Vayhinger, D.C. Bowden, S.P. Roush, T.E. Verry, A.N. Torres and V.D. Jurgens. 2000. Drug treatment for lungworm in bighorn sheep: Reevaluation of a 20-year-old management prescription. Journal of Wildlife Management 64:505-512. Nellemann, C. and R.D. Cameron. 1998. Cumulative impacts of an evolving oil-field complex on the distribution of calving caribou. Canadian Journal of Zoology, 76: 1425-1430. Nellemann, C., Vistnes, I., Jordhøy, P., Strand, O., and A. Newton. 2003. Progressive impact of piecemeal infrastructure development on wild reindeer. Biological Conservation, 113: 307-317. Sinclair, A.R.E., and M. Norton-Griffiths. 1979. Serengeti: dynamics of an ecosystem. University of Chicago Press, Chicago, IL, USA. Singer, F.J., Bleich, V.C. and M.A. Gudorf. 2000a. Restoration of bighorn sheep metapopulations in and near western national parks. Restoration Ecology 8(4 special supplement):14-24. Singer, F.J., Moses, M.E., Bellew, S. and W. Sloan. 2000b. Correlates to colonizations of new patches by translocated populations of bighorn sheep. Restoration Ecology 8(4 special supplement):66-74. Singer, F.J. and J.E. Norland. 1994. Niche relationships within a guild of ungulate species in Yellowstone National Park, Wyoming, following release from artificial controls. Canadian Journal of Zoology 72:1383-1394. Singer, F.J., Williams, E., M.W. Miller and L.C. Zeigenfull. 2000c. Population growth, fecundity, and survivorship in recovering populations of bighorn sheep. Restoration Ecology 8(4 special supplement):75-84. Stewart, K.M, Bowyer, R.T., Kie, J.G., Dick, B.L. and M. Ben-David. 2003. Niche partitioning among mule deer, elk, and cattle: Do stable isotopes reflect dietary niche? Ecoscience 10:297-302. Unsworth, J.W., Pac, D.F., White, G.C. and R.M. Bartmann. 1999. Mule deer survival in Colorado, Idaho and Montana. Journal of Wildlife Management 63:315-326. Wehausen, J.D. 1996. Effects of mountain lion predation on bighorn sheep in the Sierra Nevada and Granite Mountains of California. Wildlife Society Bulletin 24:471-479. White, G.C., D.J. Freddy, R.B. Gill and J.H. Ellenberger. 2001. Effect of adult sex ratio on mule deer and elk productivity in Colorado. Journal of Wildlife Management 65:543-551. Prepared by ______________________ Eric J. Bergman, Wildlife Researcher 101 �102 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Task 1 Colorado Federal Aid Project: N/A : : : : 3740 Cost Center 3430 Mammals Research Wildlife Diseases Chronic Wasting Disease in Mule Deer Research and Development : Period Covered: July 1 2003 through June 30, 2004 Author: Michael W. Miller and L. L. Wolfe Personnel: L. A. Baeten, S. Bender, M. M. Conner, K. Cramer, T. R. Davis, M. Farnsworth, K. Griffin, C. P. Hibler, N. T. Hobbs, D. O. Hunter, J. E. Jewell, E. Knox, C. E. Krumm, C. T. Larsen, B. E. Powers, J. Rhyan, M. Sirochman, T. Sirochman, T. R. Spraker, M. K. Watry, E. S. Williams, D. Wroe All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We continued conducting research on various aspects of chronic wasting disease (CWD) epidemiology and management. Here, we report progress in ongoing and recently-completed work. Studies focused on improving and expanding surveillance in free-ranging populations, understanding and modeling transmission mechanisms, identifying ecological and anthropogenic factors that may influence epidemic dynamics, and evaluating and applying alternative diagnostic and control strategies. In addition to preliminary findings reported here, 12 original studies and review articles were published during this segment; citations are appended to the report. 103 �JOB PROGRESS REPORT CHRONIC WASTING DISEASE IN MULE DEER RESEARCH AND DEVELOPMENT Michael W. Miller and L. L. Wolfe INTRODUCTION We continued conducting research on various aspects of chronic wasting disease (CWD) epidemiology and management. Some parts of this work were conducted in collaboration with investigators at Colorado State University, the University of Wyoming, and elsewhere. Specific projects were supported with various combinations of funds from the Colorado Division of Wildlife (CDOW), Federal Aid in Wildlife Restoration Project W-153-R, the U.S. Department of Agriculture (APHIS/VS, the U.S. Department of Interior (USGS/BRD), and National Science Foundation/National Institutes of Health (NIH) Grant DEB-0091961. METHODS Our work on CWD is both multidisciplinary and multifaceted, but broadly falls under the topics of “epidemiology and management” or “pathogenesis and diagnosis”. For simplicity, we describe progress under those headings below. STUDIES OF CWD EPIDEMIOLOGY & MANAGEMENT We continued or initiated studies related to surveillance, transmission mechanisms, epidemic trend forecasting, potential host range and strain variation, risk factors, and management tools and feasibility as aids to understanding and controlling CWD in free-ranging deer and elk in Colorado. Statewide surveillance: Surveillance for CWD continued throughout Colorado to determine the extent of distribution, to estimate prevalence in affected areas, and to monitor prevalence trends. Surveillance methods were as described elsewhere (Miller et al., 2000, J. Wildl. Dis. 36:676–690; Miller & Williams, 2002, Vet. Rec. 151:610–612; Hibler et al., 2003, J. Vet. Diag. Invest. 15:311−319). In addition to reporting of annual survey findings, we also analyzed cumulative surveillance data to examine the potential influences of demographic, spatial, and temporal factors on observed prevalence patterns. We also began exploring ways of improving the efficiency of our CWD surveillance program. Since 1996, tissue samples have been collected from deer killed in vehicle collisions throughout Colorado as part of our monitoring program for detecting CWD in free-ranging populations. We estimated CWD prevalence among vehicle-killed mule deer statewide and compared this to estimated CWD prevalence among mule deer sampled in the vicinity of these collision sites to determine if CWD-infected individuals were more vulnerable to vehicle collisions than otherwise healthy deer. Transmission mechanisms: We summarized findings on empirical evidence of direct and indirect CWD transmission and the relative importance of these mechanisms in epidemic dynamics. Modeling epidemic dynamics in captive mule deer: We continued analyses of 26 years of data (1974−2000) from CWD epidemics at CDOW’s Foothills Wildlife Research Facility to evaluate strength of evidence for a set of candidate models involving indirect and/or direct transmission, with and without latency periods. Estimates of transmission rates derived from these models will provide an upper bound 104 �on what could be expected in wild populations and will guide construction of candidate sets for modeling those populations. Host range and strain variation: We continued a series of experimental studies in cattle, fallow deer, and mountain lions to explore potential host range of CWD after intense but natural exposure; these experiments compliment ongoing surveillance for evidence of infection in species not known to be natural hosts of CWD, including moose and mountain lions. We also completed work looking for evidence of strain variation in CWD agent from various deer sources using domestic ferrets as a laboratory model. Effects of land use on prevalence: We summarized findings on the apparent effects of urban vs. nonurban land use patterns on CWD prevalence in mule deer. Selective predation upon infected mule deer: We continued a study comparing prevalence of CWD among puma-killed mule deer to prevalence among mule deer harvested or randomly culled by humans within home ranges of collared mountain lions to assess whether predation is selective for CWDinfected mule deer. Methods were as described previously (Miller and Wolfe, 2003, Work Package 3430, Task 7410, Progress Report, Colorado Division of Wildlife, Ft. Collins). A total of eight adult mountain lions have been collared, resulting in 39 collared cat months between February 2001 and May 2004. Sampling of predator-killed deer is ongoing. Influence of trace minerals on susceptibility: We continued two independent studies to investigate the potential influence of trace minerals on CWD susceptibility. In a retrospective study, we completed analyses of archived tissues to compare tissue levels of copper (Cu), molybdenum (Mo), and manganese (Mn) in mule deer infected with CWD to levels in apparently uninfected deer from the same geographic area. We also continued an experiment to examine the effect of Cu supplementation on CWD susceptibility in white-tailed deer, wherein we are comparing the natural infection rate and course of CWD in captive deer receiving a sustained-release oral Cu supplement to the rate and course in unsupplemented controls residing in the same paddock. Genetic influences on susceptibility: We continued collaborating with investigators from the University of Wyoming (UWYO) in studies of genetic influence on CWD susceptibility in mule deer. The main objective of ongoing UWYO research has been to search the DNA sequence of the PrP encoding region in exon 3 of the Prnp gene of mule deer for genetic variations that may influence occurrence of naturally acquired CWD. Recent analyses included samples from 529 free-ranging mule deer from four Colorado DAUs (326 from D-10, 63 from D-19, 71 from D-9, and 69 from D-7). Total genomic DNA was extracted from each sample and the PrP coding region from each deer genome was amplified by polymerase chain reaction (PCR). Genotyping was done using commercial sequencing or a simple restriction enzyme digestion (J. E. Jewell, unpublished data) of the PCR amplified PrP gene. Preventive therapies: We collaborated with investigators from the Rocky Mountain Laboratories, NIH, to conduct a pilot study evaluating safety and efficacy of three prospective therapies for preventing CWD in mule deer. Twenty hand-raised mule deer were randomly divided into groups of 5 and assigned to receive a candidate therapy (coded PP, TA, or TC) or no therapy (control). We administered therapies continuously or 3× daily depending on the drug used; administration began 14 days before inoculation, and continued for 14 days after challenge. All groups received pelleted feed and alfalfa hay from the 105 �same source. We used a novel oral inoculation method (M. W. Miller & L. L. Wolfe, unpublished data) for experimental challenge. We collected tonsil biopsies (Wolfe et al., 2002, J. Wildl. Manage. 66:564– 573) from controls about 4 mo post inoculation (PI) and principals about 5 mo PI to assess efficacy of respective therapies in preventing CWD in mule deer. Evaluation of an urban CWD management strategy: We completed an assessment of the feasibility of “test and cull” as an approach for managing CWD in urban habitats, and continued a 5-year study to evaluate the efficacy of this approach in reducing CWD prevalence among urban mule deer. During October 2003−May 2004, we again captured and tested free-ranging mule deer, and marked them with timed-release radiocollars in urban areas throughout Estes Park; our work was complimented by a parallel, coordinated effort by the US National Park Service (NPS) to capture and test deer inside Rocky Mountain National Park (RMNP). The collective annual goal was to test ≥50% of the adult mule deer residing the Estes Park population unit (Conner and Miller, 2004, Ecol. App. in press); target sample sizes (52 adult males and 153 adult females) were estimated based on a mark-resight inventory conducted in December 2003. Field methods were as previously described (Wolfe et al., 2004, Wildl. Soc. Bull. in press). In addition to the primary goal of assessing the efficacy of test and cull as a management strategy, data gathered in the course of this study will also be useful in improving our understanding and modeling of the influences of urban landscapes on CWD epidemiology. STUDIES OF CWD PATHOGENESIS & DIAGNOSIS We continued or initiated studies related to pathogenesis in natural hosts and live-animal diagnostic test refinement and evaluation as aids to improving approaches for CWD surveillance and diagnosis in free-ranging deer and elk in Colorado. Pathogenesis in natural host species: We completed our work studying the pathogenesis of CWD in white-tailed deer after oral inoculation with infectious, conspecific brain tissue. This study will complement studies documenting CWD pathogenesis in mule deer and elk that already have been completed. Evaluation of antemortem diagnostic techniques: We continued working to refine and evaluate tonsil biopsy techniques for diagnosing CWD in live animals. In light of our continued success in applying established techniques (Wolfe et al., 2002, J. Wildl. Manage. 66:564–573), we have continued using tonsil biopsy to gather data for field studies and epidemiological investigations. We also began using tonsil biopsy IHC as diagnostic benchmark for evaluating other candidate tests for diagnosing CWD in live animals. In conjunction with ongoing studies on CWD transmission, we evaluated a candidate rapid test developed by Prion Developmental Laboratories, Inc. (PDL), modified for potential use under field laboratory conditions (J. E. Jewell, unpubl. data). Initial evaluation of this test on biopsy-sized pieces of tonsil tissue collected postmortem from culled mule deer revealed that sensitivity (about 80%) was near the lower limit of acceptability for field use. Modifications to improve sensitivity were made, and subsequently we evaluated sensitivity of the PDL test under conditions simulating those anticipated in field applications using tonsil biopsies collected from captive mule deer naturally infected with CWD. Tissue samples collected via tonsilar biopsy (Wolfe et al., 2002, J. Wildl. Manage. 66:564–573) were examined within 10 min of collection via the candidate PDL test; details of laboratory techniques were proprietary. Laboratory equipment and conditions simulated those that we anticipated would be available at a field site. Paired biopsies were collected from infected and uninfected deer (n = 16); we randomly assigned one of each pair to PDL and the other to immunohistochemistry (IHC) evaluation. Biopsies were processed, test reactions evaluated, and deer categorized as CWD-positive or -negative based on observed reactions; laboratory personnel were unaware of the infection status of sampled deer. Time 106 �from sample collection to reporting of test result was recorded for each biopsied deer. Sensitivity (estimate, 95% CI) of the PDL test was calculated, using IHC as the reference standard. We compared the proportion of positive deer detected by the PDL test to results from IHC using a one-sided Fishers exact test; we used α = 0.1 for all analyses. In addition, the mean reporting time and range of reporting times was calculated for use in assessing the utility of the PDL test under anticipated field conditions. In conjunction with ongoing studies on CWD prevention, we also reevaluated nictitating membrane (also called the “third eyelid”) biopsy as an approach for detecting CWD in live mule deer. We used a modified technique devised for domestic sheep (S. Bender, unpublished data) to identify lymphoid tissue on the nictitating membrane and adjacent conjunctiva, then collected biopsies using established techniques (O’Rourke et al., 1998, Vet. Rec. 142:489-491). We sampled both eyes of 11 mule deer experimentally infected with CWD and known to be tonsil biopsy positive. Nictitating membrane biopsies were evaluated by IHC using published methods (O’Rourke et al., 1998, Vet. Rec. 142:489-491; O’Rourke et al., 2002, Clin. Diag. Lab. Immunol. 9:966-971). We calculated the proportion (± 95% CI) of usable nictitating membrane biopsies, as well as the sensitivity (± 95% CI) of nictitating membrane biopsy IHC for CWD diagnosis using tonsil biopsy IHC as the reference; criteria for regarding this nictitating membrane biopsy technique as potentially useful in diagnosing CWD in mule deer were ≥ 90% of samples containing usable lymphoid tissue and estimated sensitivity ≥ 95%. We also collaborated in a second study to evaluate a prospective rapid blood test (GeneThera, Denver, CO) for diagnosing CWD in live deer. A total of 10 blood samples from tonsil biopsy-positive, captive mule deer were collected by GeneThera representatives using collection materials and protocols provided by the laboratory; samples were immediately taken to their laboratory for evaluation. By previous agreement, the status of sampled animals was known to GeneThera personnel prior to blood collections. RESULTS AND DISCUSSION STUDIES OF CWD EPIDEMIOLOGY & MANAGEMENT Statewide CWD surveillance: The CDOW sampled over 15,000 deer and elk harvested or culled in northern Colorado and other select locations, as well as smaller numbers of deer and elk submitted as clinical suspects. Surveillance revealed two previously undetected CWD foci in mule deer, one on the Grand Mesa (DAU D-51) and the other in Colorado Springs (DAU D-16). Survey results will be posted on the Division’s CWD web page (). Surveillance data also will be used to augment an existing database that is the foundation for ongoing analyses and modeling of temporal and spatial aspects of CWD epidemiology, as well as for evaluating responses to management. In addition to reaffirming the spatial heterogeneity among wintering mule deer subpopulations observed previously (Miller et al., 2000, J. Wildl. Dis., 36:676–690; Conner & Miller, 2004, Ecol. App., in press), our analyses revealed marked differences in CWD prevalence by sex and age groups, as well as clear local trends of increasing prevalence over a 7-yr period. CWD prevalence differed (P < 0.0001) by age (yearling vs. adult), sex, and geographic area at two different spatial scales (game management unit [GMU] or population unit winter range), and increased over time at both geographic scales (GMU: β = 0.064, 95% CI = 0.009−0.119, P = 0.0219; population unit: β = 0.263, 95% CI = 0.134−0.399, P < 0.0001). Disease status (positive or negative) was not independent of age for males (n = 947, df = 3, χ2 = 459, P < 0.0001) or females (n = 549, df = 4, χ2 = 71, P < 0.0001). For both sexes, prevalence peaked in the 4−6-yr old age class, with the largest increase occurring between the 2−3-yr-old and 4−6-yr-old age classes. This differential was larger for males: prevalence rose from 5.9% (95% CI = 4.9−6.8) among 2−3-yr-olds to 19.4% (95% CI =12.1−26.7) among 4−6-yr-olds (P = 0.0002); for the 4−6 yr age class, prevalence among males (19.4%) was 2.7× greater (P = 0.0006) than among females (7.2%). 107 �Demographic, spatial, and temporal factors all appear to contribute to the marked heterogeneity in CWD prevalence in endemic portions of northcentral Colorado. These factors likely combine in various ways to influence epidemic dynamics on both local and broad geographic scales. A manuscript describing our findings is in review for publication in the Journal of Wildlife Diseases. Sampling of vehicle-killed mule deer may be exploited in increasing the efficiency of surveillance programs designed to detect new foci of CWD infection and direct management actions; however, this differential vulnerability also may bias prevalence estimates in natural populations when data from vehicle-killed deer are included in calculating such estimates. Overall CWD prevalence was 1.66× higher in vehicle-killed deer; prevalence among vehicle-killed deer was 0.101 (95% confidence interval [CI] = 0.064−0.139) compared to 0.061 (95% CI = 0.051−0.072) prevalence among mule deer harvested, culled, or biopsied within 3 km of collision sites. The probability of detecting a CWDinfected, vehicle-killed deer, given that at least one other CWD-infected deer had been detected within a 3 km radius of the vehicle-kill site, was 16.7%. Our data suggest increased susceptibility of CWD-infected individuals to vehicle collisions. Evidence of increased susceptibility to vehicle collisions also may aid in understanding vulnerability of CWD-infected individuals to other forms of death, particularly predation. A manuscript describing our findings is in review for publication in the Journal of Wildlife Diseases. Transmission mechanisms: Manuscripts describing our findings on the relative importance of animal−animal transmission of CWD and on the relative contributions of live animals, contaminated environments, and infected carcasses to CWD transmission were accepted for publication and subsequently published in peer-reviewed journals (see Appendix for citations). Modeling epidemic dynamics in captive mule deer: Preliminary analyses suggest that indirect transmission models best represent epidemic data; moreover, our model selection results align well with independent empirical findings on CWD transmission mechanisms (Miller et al., 2004, Emerg. Inf. Dis. 10:1003−1006). We will continue refining candidate models before making final comparisons and parameter estimations. Findings should be of use in refining epidemic models of CWD in free-ranging mule deer populations. Host range and strain variation: Cattle (n = 11) living in paddocks with naturally-infected mule deer remained healthy through 7 years of exposure; in contrast, only 1 of 12 mule deer introduced into these same paddocks in 1997 is still alive. Our results are consistent with data from cell-free conversion (Raymond et al., 2000, EMBO 19:4425-4430) and intracerebral (IC) challenge (Hamir et al., 2001, J. Vet. Diag. Invest. 13:91–96) studies that suggest the probability of natural susceptibility to CWD in cattle is extremely low. Similarly, neither signs nor postmortem evidence of infection have been observed in fallow deer (n = 24) exposed to infected mule deer for ≤3.5 years, and mountain lions (n = 3) consuming carcasses of CWD-infected deer and elk for >2 years also have remained healthy. No evidence of infection has been observed in moose, mountain lions, or cattle examined via ongoing surveillance. Clinical signs and postmortem findings consistent with CWD in ferrets were observed in four of five IC-inoculated with tissue from infected deer, but were not observed in the free-ranging white-tailed deer or control groups. Incidence and incubation periods were consistent among affected groups. Preliminary assessment of Western blots (WB) revealed no apparent differences in glycosylation patterns among WB-positive ferrets, and no evidence of infection in the unaffected white-tailed deer or control groups. Effects of land use on prevalence: Urban land use appears to affect CWD prevalence: rates were higher in developed areas and among male mule deer, suggesting anthropogenic influences on the 108 �occurrence of CWD. We also observed relatively high variation in prevalence across three study sites (Estes Park, Horsetooth Mountain, Glacier View Meadows), suggesting that spatial patterns may be influenced by other factors operating at a broader, landscape scale. Our results suggest that multiple factors, including changes in land use, differences in exposure risk between sexes, and landscape-scaled heterogeneity, are associated with CWD prevalence in north-central Colorado. A manuscript describing these findings in currently “in press” (see Appendix for citation). Selective predation upon infected mule deer: Our work continues from a pilot study conducted to evaluate available global positioning system (GPS)-based telemetry collars for use in this sampling application. Three collar styles have been deployed, and we are continuing to test and evaluate this new technology; aside from our main objective of data gathering related to CWD ecology, evaluation of this technology should be a substantial contribution to future studies of predator-prey relationships. We have detected and examined over 85 kill sites from radio-collared mountain lions and successfully sampled tissues from 28 sites where adult mule deer carcasses were present; we also have collected 17 samples opportunistically from mule deer killed by mountain lions that were not radio-collared. We will continue capturing mountain lions to reach the objective of six to nine collared cat years, and will continue sampling carcasses of lion-killed mule deer to reach our target sample size (n = 157). We also will continue refining our monitoring approach to ensure that we find kill sites quickly enough to retrieve a suitable tissue sample to test for CWD. Whether target sample sizes can be attained in the time planned for this work remains to be determined. Influence of trace minerals on susceptibility: Both studies are well underway. Laboratory analyses of retrospective samples are complete, and data analysis is underway. Experimentally- treated and control deer are being sampled on a regular schedule, but laboratory analyses are incomplete. Genetic influences on susceptibility: Only four codons in the open reading frame of the Pnrp gene exhibit variation in mule deer, and only one of the four results in a change in the final version of PrP (Brayton et al., 2004, Gene 326:167−173; J. E. Jewell, unpublished data) -- this is a change from the amino acid serine (S), the high frequency allele, to phenylalanine (F) at codon 225. Preliminary results showed that estimated frequency of F allele occurrence in gene pools was similar in Colorado DAUs with (D-10: 0.095; n=652) and without endemic CWD (D-19: 0.111; n=126). However, F225 was not detected in the genomes of CWD-infected deer from D-10 (n = 50), and the F225 gene frequency was lower than in uninfected D-10 deer (0.1; χ c2 = 4.6, P < 0.05). We observed a similar pattern of low F225 gene frequency among mule deer infected with CWD after experimental exposure via direct and indirect routes (Miller et al., 2004, Emerg. Inf. Dis. 10:1003−1006). Whether F225 affects truly affects CWD susceptibility or transmission in mule deer remains to be determined, and is the subject of continued investigation. Preventive therapies: All 4 control deer that survived to 4 mo PI showed evidence of PrPCWD accumulation in tonsil biopsies collected ~4 mo PI. Unfortunately, all but 2 of the 15 treated deer also showed PrPCWD accumulation in tonsil biopsies collected ~5 mo PI; the 2 apparently uninfected deer were both from the same treatment group (PP), but overall infection rate did not differ (P = 0.28) from control. We will continue following these deer to examine potential differences in post-exposure survival that could be attributable to therapies, and to further document the outcomes of the alternative inoculation method used. We also plan to continue this work if other candidate therapies become available. Evaluation of an urban CWD management strategy: Data from the 2002−2003 field season indicated that testing and culling mule deer in Estes Park could be done at rates needed to evaluate the efficacy of this approach in reducing CWD prevalence. A manuscript describing the results of our feasibility study is in preparation is “in press” for publication in the Wildlife Society Bulletin. 109 �Males Females 0.3 Prevalence Because we were successful in reaching objectives for population-level testing, the 2002−2003 field season became year 1 of a 5-year study to evaluate the efficacy of “test and cull” as a CWD control strategy. In year 2 (2003−2004 field season), we captured and tested 44 adult (≥1.3 yr old) male and 119 adult female mule deer in Estes Park. CWD prevalence was about 13.6% among males and 5% among females tested in 0.2 0.1 0 2002 2003 Year Estes Park (Fig. 1); although no clear evidence of a Figure 2. Chronic wasting disease (CWD) prevalence among male (teal bar) and female (plum treatment effect has emerged (Fig. 1), it is probably bar) mule deer tested in Estes Park, Colorado, unrealistic to expect measurable changes in prevalence after 2002−2004. Prevalence between years did not only 1 year of test and cull management. The combined differ (Fisher exact test P≥0.4). Vertical lines are upper 95% confidence limits on estimated efforts of CDOW and RMNP programs resulted in an prevalence. overall testing rate of 63% of the deer wintering in the Estes Park vicinity, including about 90% of the estimated 103 male and 55% of the estimated 306 female deer in this population unit. STUDIES OF CWD PATHOGENESIS & DIAGNOSIS Pathogenesis in natural host species: White-tailed deer inoculated orally with about 2.5 g of brain tissue homogenate (containing about 15 µg PrPCWD) developed clinical CWD and were euthanized in endstage disease 16−30 mo postinoculation (PI). The clinical course in inoculated white-tailed deer was similar to that previously observed in mule deer inoculated with about 15 µg PrPCWD from infected mule deer. Laboratory evaluations of tissues from both our white-tailed deer and mule deer pathogenesis studies are pending. Evaluation of antemortem diagnostic techniques: Tonsil biopsy is a useful tool for estimating CWD prevalence in nonhunted mule deer populations. In addition to applications in the two field studies described here, the techniques we developed are being used in at least six other field studies of CWD epidemiology (WY, NM, WI, SD, NE, CO). Although the PDL test showed considerable promise as a potential field test, assay performance will need to be improved before it can be incorporated into ongoing CWD research or management programs. We observed good assay sensitivity (1.0; 6/6), but relatively low specificity (0.7; 7/10); overall agreement with IHC was 0.64 (95% CI = 0.29−0.98). There appeared to be an unacceptably high number of “false positive” tests -- application in a low prevalence population (e.g., Estes Park) would likely lead to unnecessary culling of numerous healthy deer, and could erode public support for our field study. Consequently, the PDL test was not incorporated into the 2003−2004 field study in Estes Park. The nictitating membrane biopsy technique provided a high proportion of usable samples: all 22 samples contained at least 1 lymphoid follicle and 12−16/22 (55−73%) samples contained ≥ 9 follicles. Unfortunately, IHC of nictitating membrane biopsies detected PrPCWD accumulation in only 2/22 biopsies, both from the same deer. Because estimated sensitivity (0.09; 95% CI 0.01−0.29) is inadequate, we cannot recommend incorporation of nictitating membrane biopsy IHC into any of our ongoing CWD research or management programs. We remain unable to assess the reliability or repeatability of the “GeneThera test”. No test results were provided on the 10 blood samples from positive mule deer; instead, a company representative indicated that extractions from samples were unsuccessful, and that consequently tests could not be run. 110 �This is our second unsuccessful attempt to obtain results from blood samples submitted to GeneThera for CWD testing. Until an evaluation of their test can be completed, we cannot recommend its incorporation into any of our ongoing CWD research or management programs. APPENDIX Publications arising from ongoing CWD work: Belay, E. D., R. A. Maddox, E. S. Williams, M. W. Miller, P. Gambetti, and L. B. Schonberger. 2004. Chronic wasting disease and potential transmission to humans. Emerging Infectious Diseases 10:977−984. Brayton, K. A., K. I. O’Rourke, A. K. Lyda, M. W. Miller, and D. P. Knowles, Jr. 2004. A processed pseudogene contributes to apparent mule deer prion gene heterogeneity. Gene 326:167−173. Miller, M. W. and M. A. Wild. 2004. Epidemiology of chronic wasting disease in captive white-tailed and mule deer. Journal of Wildlife Diseases 40: 320−327. Miller, M. W., and E. S. Williams. 2003. Horizontal prion transmission in mule deer. Nature 425: 35−36. Miller, M. W., and E. S. Williams. 2003. Chronic wasting disease of cervids. In Mad cow disease and related spongiform encephalopathies. D. A. Harris, (Ed.). Current Topics in Microbiology 284:193−214. Miller, M. W., E. S. Williams, N. T. Hobbs, and L. L. Wolfe. 2004. Environmental sources of prion transmission in mule deer. Emerging Infectious Diseases 10: 1003−1006. Miller, M. W., E. S. Williams, B. E. Powers, L. A. Baeten, L. L. Wolfe, and K. L. Green. 2004. Epidemiology and management of chronic wasting disease in free-ranging cervids. In Proceedings of the One Hundred and Seventh Annual Meeting of the United States Animal Health Association, pp. 60−63. O’Rourke, K. I., D. Zhuang, A. Lyda, G. Gomez, E. S. Williams, W. Tuo, and M. W. Miller. 2003. Abundant PrPCWD in tonsil from mule deer with preclinical chronic wasting disease. Journal of Veterinary Diagnostic Investigation 15: 320−323. Powers, B. E., C. P. Hibler, T. R. Spraker, and M. W. Miller. 2004. Large-scale surveillance for chronic wasting disease: The Colorado laboratory experience. In Proceedings of the One Hundred and Seventh Annual Meeting of the United States Animal Health Association, pp. 64. Sigurdson, C. J., and M. W. Miller. 2003. Other animal prion diseases. In Prions for physicians. C. Weissmann, A. Aguzzi, D. Dormont, and N. Hunter, (Eds.). British Medical Bulletin 66: 199−212. Williams, E., and M. Miller. 2003. Prions in the wild: CWD in deer and elk. Microbiology Today 30: 172−173. Wolfe, L. L., W. R. Lance, and M. W. Miller. 2004. Immobilization of mule deer with thiafentanil (A3080) or thiafentanil plus xylazine. Journal of Wildlife Diseases 40: 282−287. Prepared by ____________________________ Michael W. Miller, Veterinarian 111 �112 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Task Colorado : : : : 3740 Federal Aid Project Cost Center 3440 Wildlife Health Program Wildlife Diseases Wildlife Disease Surveillance Technical and Laboratory Support : Period Covered: July 1 2003 through June 30, 2004 Author: L. A. Baeten Personnel: K. Cramer, K. Green, K.A. Griffin, E. Knox, C. T. Larsen, M. W. Miller, L. L. Wolfe and D. Wroe All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Wildlife Health Laboratory (WHL) was initially created in 2002 to meet expanded needs for chronic wasting disease (CWD) surveillance throughout Colorado. WHL activities supported CWD epidemiology and management work, as well as various new and ongoing CWD research projects. In addition, the WHL has been able to meet demands for diagnostic and laboratory services related to other wildlife diseases that have come to the forefront of concern in the management of Colorado’s wildlife resources. 113 �JOB PROGRESS REPORT WILDLIFE DISEASE SURVEILLANCE TECHNICAL AND LABORATORY SUPPORT L. A. BAETEN INTRODUCTION The Wildlife Health Laboratory (WHL) was created in 2002 in response to the H-1.1 objective of the Division’s Strategic Plan. The purpose delineated in this objective is to “aggressively research, identify, detect, contain and eliminate, where possible, diseases in free-ranging wildlife and captive wildlife that could negatively impact wildlife populations”. The WHL was developed to meet the expanded needs for chronic wasting disease (CWD) surveillance throughout Colorado. WHL activities supported CWD epidemiology, harvest testing and management work, as well as various new and ongoing CWD research projects. In addition, the WHL has been able to meet demands for monitoring, detection, and diagnostic laboratory services related to other wildlife diseases that have come to the forefront of concern in the management of Colorado’s wildlife resources (i.e. West Nile virus, plague, Pasteurellosis, etc.). SUMMARY Statewide CWD surveillance: The discovery of CWD in northwestern Colorado in January 2002 created a sudden demand for both more widespread surveillance and more rapid turnaround on laboratory results. The CDOW’s CWD surveillance program was modified in 2002-2003 to decrease turnaround time (from initial submission to acquisition and posting of results), improve data collection and quality control. The notable changes in 2003-2004 were the addition of an electronic data collection system that was used statewide for collection of field and laboratory data. The WHL staff was instrumental in helping to delineate system mechanics, provide testing and troubleshooting capabilities and assist with training efforts. Details of overall programmatic features and changes were described on the CWDoriented CDOW web page (http://wildlife.state.co.us/CWD/index.asp); details of the efficiencies in the sampling and testing procedures are described below. Numerous state agencies have request demonstrations of this new system for possible implementation in their CWD surveillance programs. During 2003-2004, the CDOW sampled 17,268 deer, elk and moose harvested or culled in northeastern Colorado and other select locations. Survey results were posted on the Division’s CWD web page (http://wildlife.state.co.us/CWD/index.asp). The data generated provided annual CWD survey results. These data were added to the cumulative surveillance data that is the foundation for ongoing analysis and modeling of temporal and spatial aspects of CWD epidemiology, examining potential influences of demographics, as well as evaluating responses to management. In an effort to improve surveillance efficiencies, tissue samples were collected from deer killed from vehicle collisions throughout the state. Prevalence data from this group were analyzed to determine if CWD-infected individuals were more vulnerable than otherwise healthy animals. Moreover, the surveillance strategy and methods first devised and implemented in Colorado continue to serve as a model for developing national recommendations on CWD surveillance in freeranging populations. 114 �CWD tissue handling and disposal: The WHL staff prepared documents summarizing published literature on appropriate disposal methods for CWD infected tissues (incineration and chemical). These documents were used extensively for public information during the review process for the incinerator proposal for Wellington. The WHL supervisor worked with EPA and national veterinary diagnostic laboratory representatives to develop “Best Management Practices” when handling CWD infected materials. Research projects The WHL lab staff provided technical and diagnostic support for the ongoing DOW research projects listed below. Major accomplishments and contributions for the WHL this fiscal year include: completion of the experimental phase of the “Molecular epidemiology of strain variations in CWD”; evaluation of antemortem diagnostics (described below); the addition of DNA extractions to the list of diagnostic capabilities (supporting the “Genetic influences study and several species conservation projects); initiation of the pilot study on biosolids and wastewater; preliminary results from studies looking at prion inactivation are ready for presentation; and extensive sample collections for the studies of prions in biological excretions and environmental samples. 1. Molecular epidemiology of strain variations in chronic wasting disease (CWD) 2. CWD host range studies 3. Selective predation upon CWD-infected mule deer 4. Trace mineral influences on CWD susceptibility 5. Genetic influences on CWD susceptibility 6. Evaluation of preventative therapies for CWD 7. Evaluation of antemortem diagnostic techniques for CWD 8. Detection of prions in environmental samples 9. Detection of prions in biosolids and waste water 10. Chemical inactivation of prions 11. Detection of prions in biological excretions 12. West Nile virus in black-tailed prairie dogs 13. Prevalence of CWD in ungulates killed via vehicle collisions 14. Evaluation of a recombinant plague vaccine in lynx 15. Invertebrate role in CWD transmission 16. Evaluation of FWRF diarrhea outbreaks 17. Uncompaghre fawn mortality Evaluation of antemortem diagnostic technique for CWD: In a pilot study, the WHL evaluated the use of a lateral flow strip test (Prion Developmental Laboratories, Inc.) to determine its applicability for “live animal testing” in the field. Approximately 40 tonsil samples were used to assess the applicability of this diagnostic test under field conditions. The test kit procedures were manipulated to determine if modifications to the lymph node procedures could be used to accommodate tonsil tissue (and tonsil biopsy sized tissues). It was determined that the assay could be modified to work under field 115 �conditions (i.e. roving lab). However, despite efforts to modify the test parameters, the sensitivity was not acceptable to pursue further field trials with this new diagnostic test system. In addition, the WHL staff provide technical assistance to collaborators interested in archived tissues for ongoing research projects listed in the table below. The WHL staff accomplished this via additional sample collections from hunter harvest, culls and other DOW submissions. These samples are archived then aliquoted and shipped to the collaborators according to specific tissue requests. Collaborative Agreements IND/HPF/USCF USDA/ARS NYSIBR PDL CSU USDA/ARS NIH/RML CWRU NYSIBR CSU IDEXX USU RMNP GeneThera Brain Brain Brain Lymph nodes Multiple tissues Eyelids, blood Multiple tissues Brain, lymph nodes Urine Brain Lymph nodes DNA extracts (blood) DNA extracts (blood) Blood Transgenic mouse development/ host range studies Strain typing, comparison to other TSE strains Transgenic mouse strains Lateral flow strip test Experimental transmission (ante and post mortem collection CWD assay evaluations Evaluate strain variations Transgenic mouse host strain study, cellular prion transport CWD assay evaluations Effects of composting on prion inactivation Validation of diagnostic assay Epidemiology studies Epidemiology studies Antemortem assay evaluation Wildlife Disease Surveillance: The WHL performed necropsies to assist state wildlife managers and biologists in determining the cause of death for wildlife species including: deer, elk, bighorn sheep, mountain goats, bear, various avian species and rodents (See Table 1). This necropsy effort included support for two species conservation projects. The WHL provided technical and diagnostic support for the field projects listed below. This effort included biological sample collection, data collection, sample processing, diagnostic testing, archiving and/or distribution of samples. 1. Evaluation of diagnostic techniques for avian translocations 2. Disease surveillance for Prairie grouse restoration 3. Disease surveillance for Turkey translocation 3. Bighorn sheep translocations: Identification of Pasturella spp. strains 4. Identification of Johne’s disease in BHS and RMG 5. Identification of lungworm larvae in BHS feces 6. Black-footed ferret restoration: carnivore sampling 7. Lynx restoration 8. Winter deer capture: mule deer survival monitoring 9. Elk Fertility control 10. Test and cull evaluation 11. CWD management culling 12. Foot hills wildlife research facility 116 �West Nile Virus: The WHL established in-house testing for West Nile virus (WNV). Fifty-four carcasses were submitted as suspects for necropsy and testing during this fiscal year. Thirteen positives were identified. In conjunction with the DOW WNV testing performed at the WHL, tissue samples collected during necropsies were provided to CDC (Komar) for their use in experimental trials developing a new post mortem assay for WNV. Avian Translocations: The WHL investigated alternative diagnostic testing for avian translocation projects. An in-house assay for Mycoplasma (synoviae, gallisepticum, meleagridis) was determined to be optimal for testing individual birds being translocated. The use of the ELISA assay for these serological tests minimized the cross reactivity effects that were experienced with diagnostic tests used previously. With the use of the ELISA, next-day releases were possible, therefore, decreasing individual stress levels and increasing survivability for birds moved in translocation efforts. The WHL staff provided technical and diagnostic support for three avian translocation projects during this project year (sharp-tailed grouse, turkey and ring-necked pheasant). In combination with the diagnostic necropsy support, the WHL established a database to allow electronic review of these data over time. All historical diagnostic records were incorporated into the database during this fiscal year. To date, this database contains approximately 400 records. From the diagnostic reports database, the WHL prepared wildlife disease summaries for statewide distribution. The wildlife disease summaries for years 2002 and 2003 delineate animal mortality data by species, quarter and region. This data will assist wildlife veterinarians, managers and biologists in future wildlife disease events. During this fiscal year, the WHL established an archive database which includes all of the historical samples collected since the initial establishment of the WHL in the 1990’s. This database allows WHL staff to determine what tissues are available for use in research projects, delineates physical locations where various tissue samples can be found, tracks distribution of tissue samples and contains appropriate animal identification and specifications. At the end of the fiscal year, there were a total of 4,850 entries with approximately 300 of those added for the year. Table 1: Diagnostic Support Species Necropsies Diagnostic Samples (collected, processed, archived) Carnivore 3 40 Deer 30 385 Elk 10 4 Lynx 0 106 Other avian species (WNV) 36 36 Other ungulate 18 107 Prairie grouse 7 22 Small game 10 50 Small mammals 15 35 Total 126 745 117 �Training sessions: The WHL has provided multiple training session for CWD sample collection. The attendees included CDOW employees as well as federal employees from the Rocky Mountain region. In addition, the WHL staff assisted with training sessions for DWM trainees in necropsy techniques, darting and sample collections. Presentations: The WHL staff made various presentations on wildlife disease to various groups including the Wildlife Society, USFWS, CDOW staff, black-footed ferret subcommittee, Colorado Wildlife Federation. The titles of the presentations were: 1. West Nile Surveillance in Colorado 2003 2. The impact of West Nile virus on wildlife populations 3. The significance of West Nile virus in prairie dogs 4. Common diseases in wildlife populations of Colorado APPENDIX Publications arising from WHL contributions to ongoing CWD work: Brayton KA, O’Rourke KI, Lyda AK, Miller MW, Knowles Jr. DP. A processed pseudogene contributes to apparent mule deer gene heterogeneity. Gene 326: 167-173. Miller MW; Williams ES. Horizontal prion transmission in mule deer. Nature 2003 425: 35-36 _________: __________, Hobbs NT; Wolfe LL. Environmental Sources of Prion Transmission in Mule Deer. Emerging Infectious Diseases 2004 10(6): 1003-1007 _________; Wild MA. Epidemiology of Chronic Wasting Disease in Captive White-tailed and Mule deer. J Wildlife Dis 2004 40(2): 320-327 O’Rourke KI; Zhuang D; Lyda A; Gomez G; Williams ES; Tuo W; Miller MW. Abundant PrPCWD in tonsil from mule deer with preclinical chronic wasting disease. J Vet Diagn Invest 2003 13: 320-323 Powers BE, Hibler CP, Spraker TR, Miller MW. Large scale surveillance for chronic wasting disease: The Colorado laboratory experience. Annual proceedings USAHA 2004 pg 64. Prepared by _________________________ Laurie A. Baeten, Veterinarian 118 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Task Colorado Federal Aid Project: N/A 3740 : : : : Cost Center 3430 Mammals Research Wildlife Diseases Pilot evaluation of GPS technology in chronic wasting disease prevalence and management at artificial feeding sites in urban areas. : Period Covered: April 1 2003 through July 31, 2004 Author: Eric J. Bergman, Michael W. Miller and L. L. Wolfe Personnel: M. Sirochman All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A pilot study for assessing the utility of GPS technology in the evaluation of CWD prevalence and management in urban areas was designed is being implemented. Objectives of this pilot study are to: 1) Evaluate the utility of GPS radio collar technology in identifying artificial feed sites in urban settings, 2) Evaluate if there is evidence that artificial feed sites reduce the size of deer home ranges, 3) Evaluate if deer density is elevated at artificial feed sites, and 4) Evaluate if CWD prevalence is higher at artificial feed sites . 119 �JOB PROGRESS REPORT PILOT EVALUATION OF GPS TECHNOLOGY IN CHRONIC WASTING DISEASE PREVALENCE AND MANAGEMENT AT ARTIFICIAL FEEDING SITES IN URBAN AREAS Eric J. Bergman, Michael W. Miller and L. L. Wolfe INTRODUCTION Analyses of data from recent field studies and from culling have revealed areas of relatively high CWD prevalence associated with urban areas along the northern Front Range (Wolfe et al. 2002, 2004; Conner and Miller 2004; Farnsworth et al. 2004). Within these, artificial and illegal feeding sites may be particularly important because they appear to congregate deer in one location, thereby increasing local deer density and exposure to contaminated environments (Miller et al. 2004). Although the nature of the relationship between disease prevalence and mule deer density has not been definitively identified, it seems likely (Barlow 1996) that CWD prevalence is being indirectly elevated through artificial feeding. The development of global positioning system (GPS) technology and its incorporation into radio collars for wildlife research presents a tool for better understanding CWD in urban areas. We have initiated a pilot field study to: 1) evaluate the effectiveness of different GPS collars in identifying illegal feed sites in urban settings, and 2) develop and evaluate a strategy for utilizing GPS technology in studying and managing CWD in urban mule deer populations. METHODS The study area for this work is located within two subdivisions in Estes Park, Colorado. The subdivisions, separated by approximately 1.6 km, were identified as treatment and control sites based on the presence and absence of known feeding sites (Fig.1, Wolfe et al. 2004). Between five and eight adult (>1 yr old) female deer from each subdivision were captured and collared with one of two different brands of GPS collars (HABIT Research, British Columbia, Canada and LOTEK Wireless, Ontario, Canada). Collars from each company will be evenly distributed between sites. Capture will occur as part of an ongoing "test and cull" research project (Wolfe et al. 2004) during April 2004 and from August to October of 2004 as needed. Deer will be recaptured and collars will be removed prior to battery failure (~220 days service) in order to retrieve GPS data. No specific hypotheses are being tested in this pilot study; rather, we are attempting to determine if GPS radio collar technology is adequate for use as a tool in refining CWD epidemiology and management. We will record and report on the performance of GPS collars, and calculate costs (mean, range per animal tested) associated with our artificial feed site identification strategy as implemented in this pilot study. However, we will compare home range sizes of deer from each site to determine if artificial feeding reduces home range size of deer. We will also incorporate ground survey data (Wolfe et al. 2004) to estimate and compare mule deer density and ultimately CWD prevalence from sampled deer at each site. CWD prevalence will be compared between sites as well as to previous estimates from the greater Estes Park area (Wolfe et al. 2004) to explore future research potential. 120 �RESULTS AND DISCUSSION GPS Collar Comparison A total of 16 GPS collars (10 LOTEK, 6 HABIT) were available for testing in this study. Prior to initiation of this study no HABIT collars were on hand for deployment, rather, all 6 had to be built to specification and delivered. GPS collars from HABIT Research, ~$1,800/unit, were programmed to: collect GPS locations every 2 hours, to transmit GPS data (via VHF signal) over two day intervals every two weeks and to transmit the most recent GPS location (via VHF signal) at the start of each minute. Due to delays in the manufacturing process, no HABIT collars were received in time for spring deployment (≥2 weeks pre-fawning). Additionally, due to programming errors, 0 of 6 HABIT collars were ready for deployment after initial testing. Upon servicing by HABIT Research (~3.5 weeks), 3 of 6 collars appear to be ready for deployment in late summer 2004. The remaining HABIT collars (3 of 6) will be serviced and deployed upon satisfactory performance. All LOTEK collars were on hand prior to initiation of this study. Eight of 10 collars were deployed in spring of 2004, with 1 of 10 needing service. GPS collars from LOTEK Wireless, ~$3,500/unit, were also programmed to collect GPS locations every 2 hours, but did not offer remote download capabilities. All GPS locations collected by LOTEK collars will be acquired upon retrieval of the collar. GPS Collar Performance Data from LOTEK GPS collars continues to be collected and HABIT GPS collars will be deployed between August-September 2004. LITERATURE CITED Barlow, N.D. 1996. The ecology of wildlife disease control: simple models revisited. Journal of Applied Ecology 33:303-314. Conner, M.M., and M.W. Miller. 2004. Spatial epidemiology in natural populations: a case study of movement and prion disease prevalence relationships among mule deer population units. Ecological Applications (in press). Farnsworth, M.L., L.L. Wolfe, N.T. Hobbs, K.P. Burnham, D.M. Theobald, and M.W. Miller. 2004. Human land use influences chronic wasting disease prevalence in mule deer. Ecological Applications: in review. Miller, M.W., E.S. Williams, N.T. Hobbs, and L.L. Wolfe. 2004. Environmental sources of prion transmission in mule deer. Emerging Infectious Diseases: in press. Wolfe, L.L., M.M. Conner, T.H. Baker, V.J. Dreitz, K.P. Burnham, E.S. Williams, N.T. Hobbs, and M.W. Miller. 2002. Evaluation of antemortem sampling to estimate chronic wasting disease prevalence in free-ranging mule deer. Journal of Wildlife Mangement 66:564-573. _________, M.W. Miller, and E.S. Williams. 2004. Feasibility of "'test-and-cull" for managing chronic wasting disease in urban deer. Wildlife Society Bulletin 32:500-505. Prepared by ____________________________ Eric J. Bergman, Wildlife Researcher 121 �122 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Project No. Work Package No. Task Federal Aid Project Colorado 3740 : : : : N/A Cost Center 3430 Mammals Research Mammals Support Services Veterinary Services – Medical Support : Period Covered: July 1 2003 through June 30, 2004 Author: L. L. Wolfe Personnel: M. W. Miller, L. A. Baeten, M. M. Conner, K. Cramer, T. R. Davis, K. Griffin, D. O. Hunter, J. E. Jewell, E. Knox, C. E. Krumm, C. T. Larsen, J. Rhyan, M. Sirochman, T. Sirochman, E. S. Williams, D. Wroe All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. 123 �JOB PROGRESS REPORT VETERINARY SERVICES – MEDICAL SUPPORT L.L. Wolfe INTRODUCTION Veterinary services are provided as support for a variety of wildlife research projects, transplants and reintroductions conducted by the Colorado Division of Wildlife (CDOW) and its collaborators throughout the year. The following overviews and summarizes key wildlife veterinary medical support services provided during 2003−2004. VETERINARY MEDICAL SUPPORT Location of services & primary investigator CDOW Foothills Wildlife Research Facility (FWRF), Tracy Davis and researchers Rocky Mountain Arsenal, Sherry Skipper Species mule deer, white-tailed deer, elk, bighorn sheep, pronghorn, puma, others mule deer, white-tailed deer Uncompahgre Plateau, Chad Bishop mule deer Pinion Canyon maneuver site, Elizabeth Joyce swift fox Colorado Springs, Brian Dreher mule deer CDOW FWRF, Department of Defense contract in cooperation with Elizabeth Williams mule deer, white-tailed deer Type of medical support Preventive, routine, and emergency medical care for all research animals housed at FWRF for use in ongoing CDOW and research. Chemical immobilization of adult does for survival study and CWD surveillance. Does were ultrasounded, tonsil biopsied, blood was collected, and vaginal implant transmitters (VITs) were inserted. Medical care of injured animals, assisted with ultrasound, VIT, and blood collection for viral serosurvey and thyroid study. Swift fox kits were anesthetized and abodminal radiotransmitters were surgically inserted and blood was collection. Adult deer were captured and radiocollared for CWD surveillance. We tonsil biopsied deer, collected blood, and provided area training for future efforts Provided medical care for hand raised deer fawns, including diarrhea outbreak management and treatment of injured fawns. TRAINING Capture and Sampling A capture and handling training class was provided for the district wildlife manager trainees. A second class was held for researchers and biologists. Capture classes included lectures on drug use regulations and recordkeeping, pharmacology of select capture drugs, dosing, safety and types of equipment. These classes also included “hands on” capture and handling of animals at FWRF. This last year, we also devised and administered a written and practical exam for the DWM trainees. As needed, spaces in these classes also provide opportunities for graduate students and technicians to learn sample collection techniques. 124 �TONSIL BIOPSY Tonsil biopsy training sessions were provided for staff from Wyoming Game and Fish Department and the Wisconsin Department of Natural Resources. In addition, CDOW personnel from the Colorado Springs area were trained on-site in capture and sampling techniques. Tonsil biopsy training sessions included lectures on sampling techniques and recognizing signs of CWD. The training also involves “hands on” time in the necropsy lab for sampling techniques. We also provide hands on training, as scheduling allows, on research animals. TARGETED CWD SURVEILLANCE A training module was developed and used to instruct USFWS and tribal biologists in recognizing signs of CWD as a tool in developing targeted surveillance programs on national wildlife refuges and tribal lands. This training included a lecture and PowerPoint tutorial illustrating clinical signs of CWD, as well as first-hand observation of captive mule deer showing signs of CWD. The tutorial file was subsequently modified and made available to other state and federal agencies as a self-teaching tool to aid in respective CWD management programs. TRANSLOCATION During transplant and translocation operations, we provide emergency medical care or humane euthanasia to injured animals. We also provide blood sampling, health exams, health certificates, vaccinations, anthelmintics, and antibiotics as needed to assure safe transport and improve survival in translocated wildlife. Species BHS swift fox black-footed ferrets Lynx Services Provided Vaccination, anthelmintics, antibiotics, pharyngeal swabs Health exams and health certificates Health exams and health certificates Entry and release exams, medical care for capture injuries Comments Transplanted within Colorado Released in South Dakota Released in Utah Reintroduction project* *Lynx reintroduction: Thirty eight lynx were received for the 2004 release. Most of the lynx were in good condition on arrival at the lynx holding facility in Del Norte. Three lynx required digit amputation due to trapping injuries, but all three healed without complications. One female was euthanized due to a compound fracture of the radius-ulna. In 2003/2004, the anesthetic protocol for transported lynx was changed from 2.0-2.5 mg/kg Telazol delivered intramuscularly (IM) to 20-40 mg (0.02 -0.05 mg/kg) ketamine and 0.6-0.8 mg (0.050.11 mg/kg) medetomidine given IM. No adverse anesthetic reactions were seen. Lynx were given the ketamine/medetomidine by IM injection while held in a squeeze cage. Induction time averaged 5.1 minutes (S.E. 0.4). Anesthetic time (induction to reversal) averaged 24.5 minutes (S.E. 0.9). Lynx were given atipamazole (0.25−0.55 mg/kg) in equal volume to medetomidine by IM injection. Lynx were recovered with minimal stimulation in their den boxes. Recovery time (time from reversal to standing with coordination) averaged 48.5 minutes (S.E. 2.5). There were no poor recoveries or anesthetic reactions. This new drug combination offered substantial reduction in processing and recovery times for lynx being handled at different points in the reintroduction process. ® DRUG DISTRIBUTION Since 2002, there has been extensive reorganization of drug distribution procedures and recordkeeping for chemical capture of wildlife. Overall, there has been a dramatic improvement in drug tracking and accountability. This has resulted in a reduction in wasted expired drugs and improvement in field logs. 125 �Telazol summary 800 700 Total bottles Telazol bottles 600 bottles prescribed 500 bottles "out" unknown 400 field use logged 300 unreported field logs 200 bottles returned expired 100 bottles in FW RF safe 0 2000 2001 2002 2003 2004 year CLINICAL TRIALS The following table summarizes the clinical trials from 2003. These trials were designed and conducted to improve veterinary medical care associated with various research and management programs conducted by CDOW. More complete reports of these trials are in the appendices. Clinical Trial Investigators Clostridium perfringens type A vaccine trial Plague vaccine in Canada lynx Wolfe, Miller, Davis, Ellis BHS, MD A Wolfe, Shenk, Baeten, Miller, Roke Wolfe, Miller lynx B mountain lions, MD, WTD C Wolfe, Miller, Lance MD Published Baker, Wolfe, MD Wolfe, Ryan, Miller fallow deer See progress report for Dan Baker D Chemical immobilization field trial with medetomidine and ketamine combination Chemical immobilization with A-3080 in mule deer Chemosterilization with GnRH toxin in mule deer Comparison of dart injection quality between 2 brands of collared and uncollared darts in fallow deer 126 Species Appendix �APPENDIX A EXPERIMENTAL EVALUATION OF A VACCINE FOR CLOSTRIDIUM PERFRENGENS TYPE A IN CAPTIVE BIGHORN SHEEP (Ovis canadensis) AND CAPTIVE MULE DEER (Odocoileus hemionus) L. L. Wolfe, R. P. Ellis, K. Fox, T. Davis, and M. W. Miller INTRODUCTION Clostridium perfringens is found naturally in the intestines of animals and in the environment. This bacterium possesses the ability to produce heat-resistant endospores and potent extracellular toxins. Isolates of C. perfringens can be subdivided into types based on the production of these exotoxins. The four major toxins implicated in disease are α, β, ε, and ι. Of these four major toxins, type A produces α toxin only, type B produces α, β, and ε, type C produces α and β, type D produces α and ε, and type E produces α and ι toxins. Other minor toxins also exist within the five types of C. perfringens, although they are not used to identify the specific type due to overlap between types. These toxins include δ (found in types B and C), θ (found in all five types), κ (found in all five types), λ (found in types B, D, and E), µ (found in types A, B, C, and D) ν (found in all five types), and neuraminidase or sialidase (found in all five types). In addition, C. perfringens enterotoxin (CPE) is often produced. CPE is most often found occurring with type A, although it has also been documented with all five types of C. perfringens. Many toxins produced by C. perfringens organisms are hydrolytic enzymes, necessary for life as a saprobe found naturally in the soil. Type A, the focus of this study, also possesses enzymes with hydrolytic properties, including phospholipase C and sphingomyelinase activities (from the α toxin). (Petit et al. 1999) Clostridium perfingens type A has recently been implicated as a cause of enterotoxemia in a variety of species including lambs and goats. Tympany, hemorrhagic enteritis and abomasitis, and abomasal ulceration in calves characterize the disease. Lesions include necrotic enteritis in domestic chickens; necrotizing enterocolitis and villous atrophy in suckling and feeder pigs; and hemorrhagic gastroenteritis in dogs. (Bueschel et al. 1998). Other reports of enteric disease associated with C. perfringens type A include enterotoxemia in minks, muskrats, and racing camels, acute toxemia in water buffaloes (Songer, 1996), gastroenteritis in black-footed ferrets (Schulman et al., 1993) and dairy cattle (Dennison et al., 2002). The α toxin in type A C. perfringens acts by way of phospholipase C activity and sphingomyelinase activity, breaking down phosphatidylcholine and sphingomyelin found in the membranes of erythrocytes, platelets, leukocytes and endothelial and muscle cells. By way of this action, α toxin is thought to be responsible for the cytotoxicity, necrosis, and hemolysis observed with type A C perfringens. There is evidence suggesting that minor differences in the amino acid sequence of α toxins exist, creating two strains with different pathways of infection. One strain has an increased resistance to chymotrypsin, allowing survival and multiplication in the gut, followed by entry into circulation. This strain is believed to be the primary cause of type A related enterotoxemia. The other strain, lacking a resistance to chymotrypsin, is believed to have a higher affinity for invasion of muscle tissue, and perhaps the cause of type A related gas gangrene (Songer, 1996). Clinical signs of animals suffering from type A C. perfringens vary from species to species, but consistently include depression, anorexia, diarrhea, bloating in non-avian species, and death. Postmortem findings from these cases varies from species to species and between specific cases, but consistently tend to include gram positive bacilli surrounding necrotic tissue, necrosis, particularly in the small intestine, 127 �and hemorrhage and ulceration, again in the small intestine; in ruminants, abomasitis, tympany, and abomasal hemorrhage and ulceration are also common findings. Infection by type A C. perfringens is believed to occur in a variety of ways. One theory, especially in neonatal ruminant cases, is that engorgement on milk or esophageal groove dysfunction allows milk to spill over into the rumen, providing a substrate for growth of the bacterium, as well as an anaerobic environment in which to proliferate. Another suggested scenario, as found in cattle herds in Nebraska and Wyoming is that bacterial infection is secondary to copper deficiency. The findings of this study indicated that low copper concentrations may have weakened the abomasal mucosa and compromised immune function (Roeder et al., 1988). Environmental contamination may play a role in the acquisition of C. perfringens type A because these toxins are known to exist in the soil and many ruminant species ingest soil in attempts to acquire essential minerals. In addition, α toxin can be detected in the feces of birds with necrotic enteritis (Bueschel et al., 1998), and thus avian vectors may provide an additional method of toxin movement. The presence of C. perfringens type A at the Foothills Wildlife Research Facility (FWRF) in Ft. Collins, Colorado appears to be relatively recent, with the first case identified in 1997. Since then, the number of cases has increased exponentially, approximately doubling each year. A total of 29 cases had been attributed to C. perfringens type A since the first case was diagnosed in 1997. At the FWRF, the disease has affected primarily bighorn sheep and mule deer; these 2 species account for 25 of the 29 cases. In adult animals, bighorn sheep have been the primary species affected (6 out of 10 cases), and sudden death has been common. These animals often exhibited bloating and diarrhea shortly before death, and showed signs of hemorrhage such as bleeding from the mouth or anus. Necropsies of these animals consistently included large amounts of rod-shaped bacteria, especially in the small intestines. Other lesions included necrosis and hemorrhage, particularly in the heart and small intestine as well as intestinal and abomasal ulcers. In neonatal and juvenile animals (<1 yr old), mule deer have been the primary species affected (14 of 19 cases), and chronic symptoms have been most common. These animals consistently exhibited chronic bloating, emaciation, depression, and soft brown diarrhea that was sometimes chronic, usually present early on in the animal’s life, and often never alleviated despite various treatment attempts. Therapies included a barrage of antibiotics (benzathine penicillin and florfenicol appeared most effective), subcutaneous fluids, transfaunation, kaolin pectin with lactobacillus granules, probios powder, electrolytes, and medicated “Deccox” feed distributed by Ranchway Feeds. Despite therapy, most of these cases ended in death -- those that survived exhibited symptoms that were short-lived and often only exhibited a single case of bloating and/or diarrhea. Necropsies of affected animals consistently included: abomasitis; hemorrhage and ulcers in the intestine, abomasum, and lungs; fluid and gas throughout the intestines; watery to frothy green fluid in the rumen, and sometimes extending into other stomachs; necrosis; and rod-shaped bacteria in the abomasum and/or small intestine. Of the 19 neonatal cases, 5 occurred in bighorn sheep, and it is noteworthy that these cases were primarily in lambs born late in the spring, after the majority of lambing had already occurred. These cases were similar to those occurring in mule deer neonates. Mortality caused by C. perfringens type A is a growing impact on FWRF operations and ongoing research: it is the leading cause of death in captive bighorns and second only to chronic wasting disease (CWD) as cause of death in mule deer. Moreover, because infections occur primarily in juvenile animals, many long-term studies (e.g., CWD and fertility control) have been hampered by lack of available animals for planed experiments. Here, we proposed to develop and evaluate efficacy of a vaccine to prevent C. perfringens type A morbidity and mortality in captive bighorn sheep and mule deer. 128 �METHODS Initial vaccine development was pursued in Dr. Robert Ellis’ laboratory in the Department of Microbiology, Immunology, and Pathology at Colorado State University. We used captive Rocky Mountain bighorn sheep (O. canadensis canadensis) and mule deer (Odocoileus hemionus) in this experiment. All animals were housed at the CDOW's Foothills Wildlife Research Facility (FWRF) throughout the study and resided in 3-7 ha pastures. In addition to natural forage, grass/alfalfa hay mix and a pelleted high-energy supplement was provided as prescribed under FWRF feeding protocols for bighorn sheep and mule deer in respective age/sex classes throughout the study; fresh water and mineralized salt blocks was provided ad libitum. The general health of all animals was evaluated immediately after vaccination, as well as daily thereafter, and observations recorded throughout our experiment. Injection sites were also examined weekly for 4 weeks after vaccine administration to assess local reactions to vaccine. Bighorn sheep (n = 19) and Mule deer (n = 10) were randomly assigned to vaccinated or unvaccinated groups. The vaccinated group was injected IM with the C. perfringens vaccine in the right hind leg on day 0 and in the left hind leg 4 weeks later (booster). Blood was collected prevaccination, at the booster injection and 4 weeks after the final booster. The control group was weighed and blood was drawn at the time of the vaccine group’s booster and 4 weeks after the final booster. Serum was separated and stored frozen until it was submitted to Colorado State Diagnostic Lab for antibody titer using enzyme-linked immunosorbent assay (ELISA). As necessary deer were sedated with xylazine HCl (5-20 mg IV or 25-100 mg IM) or immobilized with a cocktail of thiafentanil HCl (8-10 mg), or ketamine HCl (100 mg), and xylazine HCl (20 mg), delivered IM by projectile syringe, to facilitate collections; narcotic effects were be reversed with naltrexone HCl (150 mg SC + 50 mg IV). RESULTS There were no vaccine site reactions or adverse effects from vaccination observed. No serum neutralizing antibody titers to C. perfringens were seen in either the BHS or MD. On follow up evaluation of the vaccine by Colorado State Diagnostic Lab, there was no type A antigen in the vaccine. DISCUSSION The vaccine in this study failed due to lack of quality control by the manufacturer, however, we anticipate that a safe and effective vaccine can be readily developed, and that its incorporation into FWRF’s preventive animal health program will reduce morbidity and mortality associated with C. perfringens type A infection. Managing clostridial enteritis is essential to improving success of preventative health programs at the FWRF and minimizing impacts on planned and ongoing research. 129 �LITERATURE CITED Bueschel, D., R. Walker, L. Woods, J. Kokai-Kun, B. McClane, J. G. Songer. 1998. Enterotoxigenic Clostridium perfringens type A necrotic enteritis in a foal. J. Am. Vet. Med. Assoc. 213(9) 1305—1307. Dennison, A. C., D. C. VanMetre, R. J. Callan, P. Dinsmore, G. L. Mason, R. P. Ellis. 2002. Hemorrhagic bowel syndrome in dairy cattle: 22 cases (1997—2000). J. Am. Vet. Med. Assoc. 221 (5) 686—689. L. Petit, M. Gibert and M. R. Popoff. 1999. Clostridium perfinrgens: toxinotype and genotype. Trends in Microbiology. 7 (3) 104—110. Roeder, M. M. Chengappa, T. G. Nagaraha, T. B. Avery, G. A. Kennedy. 1988. Experimental induction of adominal typany, abomasitis, and abomasal ulceration of intraruminal inoculation of Clostridium perfringens type A in neonatal calves. Am. J. Vet. Res. 49 (2) 201—207. Songer, J. Glenn. 1996. Clostridial enteric diseases of domestic animals. Clinical Microbiology Reviews. 9 (2) 216—234. Tillotson, K., J. Traub-Dargatz, C. E. Dickinson, R. P. Ellis, P. S. Morley, D. R. Hyatt, R. J. Magnuson, W. T. Riddle, M. D. Salman. 2002. Population-based study of fecal shedding of Clostridium perfringens in broodmares and foals. J. Am. Vet. Med. Assoc. 220 (3) 342—348. 130 �APPENDIX B SAFETY AND EFFICACY OF RECOMBINANT F1-V FUSION PROTEIN VACCINE TO PROTECT LYNX FROM PLAGUE L. L. Wolfe1, T. E. Rocke2, S. M. Dieterich3, T. M. Shenk1, A. M. Friedlander4, and M. W. Miller1 1 Colorado Division of Wildlife, Wildlife Research Center, 317 West Prospect Road, Fort Collins, Colorado 80526-2097, USA; 2U.S. Geological Survey, Biological Resources Division, National Wildlife Health Laboratory, 6006 Schroeder Road, Madison, Wisconsin 53711, USA; 3Frisco Creek Wildlife Rehabilitation Center, POB 488, Del Norte, Colorado 81132-0002, USA; 4U.S. Army Medical Research Institute of Infectious Diseases, Bacteriology Division, Fort Detrick, Frederick, Maryland 21702, USA. INTRODUCTION Plague, caused by Yersinia pestis, was introduced into the North American continent in the early 1900s, and its impacts on some native wildlife species since that time have been substantial (Cully 1993, Wuerthner 1997, Gasper and Watson 2001). Epidemics in prairie ecosystems have been well documented, and probably contributed to the marked declines observed in both prairie dogs (Cynomys spp.) and black-footed ferrets (Mustela nigripes) over the last century (Cully 1993). Although less extensively studied, it seems likely that sylvatic plague has impacted other wildlife species as well (Gasper and Watson 2001). Canada lynx (Lynx lynx) resided in Colorado historically (Fitzgerald et al. 1994), but apparently were extirpated by the late 1970s. Whether plague played any role in the disappearance of lynx from Colorado is not known. Regardless of plague’s role in the historical decline, this disease now appears to be an obstacle to ongoing efforts to reestablish lynx in southwestern Colorado. To date, Y. pestis infections have been confirmed in 6 Colorado lynx. Plague was the primary cause of death in 27% (4/15) of the known natural deaths and possibly contributed to 1 of the 6 known hit-by-vehicle deaths in adult lynx released in Colorado since 1999 (Wild 2000, Shenk 2003; T. M. Shenk, Colorado Division of Wildlife, unpublished data). Plague also killed at least 1 kitten born in the wild during the first year of documented natural reproduction in Colorado’s reintroduced lynx population (T. M. Shenk, Colorado Division of Wildlife, unpublished data). Practical tools for preventing plague in reintroduced lynx could benefit species recovery efforts in Colorado and perhaps elsewhere. Effective vaccines for preventing plague in mammalian species, including felids, have been developed only recently (Heath et al. 1998, Gasper and Watson 2001, Creekmore et al. 2002). Of these, a recombinant capsular F1-V fusion protein vaccine (Heath et al. 1998) has shown a promising combination of safety and efficacy in black-footed ferrets (Rocke et al. in press), and could be useful in lynx restoration as well. Here, we propose to (1) evaluate F1-V vaccine in captive lynx being held in southwestern Colorado prior to release as part of an ongoing restoration program and (2) compare number of lynx mortalities caused or complicated by plague in vaccinated and unvaccinated lynx released in Colorado. METHODS Our study was conducted in conjunction with the 2004 release program. All lynx were captured, transported, held, cared for, and handled as described in established protocols for Colorado’s restoration program (Wild 2000). Lynx were held at the Frisco Creek Wildlife Rehabilitation Center (FCWRC) prior to and throughout the study until release. Whenever possible, vaccination and sampling was done in 131 �conjunction with other handling activities to minimize stress that could arise from repeated handling of captive lynx. We initially evaluated safety and efficacy of F1-V vaccine (U.S. Army Medical Research Institute of Infectious Diseases, Fort Detrick, Frederick, MD) in 10 adult lynx; 10 age- and originmatched lynx will remain unvaccinated as controls. Blocks will consist of age and origin: age will be either ≤ 5 years old or ≥ 6 years old; origin will be either British Columbia (where prior exposure to plague is possible) or Manitoba/Quebec (where prior exposure is unlikely). We estimated ages based on tooth wear; animals ≤1 year old were excluded. Within each block (age and origin) of lynx, half were selected at random to receive the vaccine while the remainder will serve as controls. Vaccine was be diluted and combined with Alhydrogel adjuvant (United Vaccines, Madison, WI) as described by Rocke et al. (in press). We administered vaccine via subcutaneous (SQ) injection in the hindquarter on day 0 and a second dose was given 21 days later. Initial vaccine doses were delivered by hand-held syringe when lynx are examined upon entry into FCWRC; booster doses were delivered via hand-held syringe while the lynx was restrained in a squeeze cage. Vaccinated lynx were observed immediately after vaccination, immediately upon recovery from anesthesia (when applicable), and daily thereafter for evidence of adverse effects. To evaluate serological responses of vaccinated lynx as an index of efficacy, we will collected blood (~6 ml) from all captive lynx at each handling during the 2004 season regardless of vaccination status. For the 10 principal vaccinates and controls, at minimum blood will be collected on day 0 and again 42 days later (21 days after the booster vaccination). Serum was harvested and stored frozen until assayed. We will measure antibody titers against F1 and V antigens with phytohemagglutinaiton assay (PHA) at the Center for Disease Control and an enzyme-linked immunosorbent assay (ELISA) using methods of Rocke et al. (in press). For the 10 principal vaccinates and controls, we compared changes in log10 anti-F1 and anti-V antibody titers-1 .. Mortality of vaccinated lynx due to or complicated by plague will be compared to mortality due to or complicated by plague of unvaccinated lynx from previous releases. A suite of models developed a priori will be evaluated through AICc model selection (Burnham and Anderson 2002) to investigate the possible effects of vaccination status, age, location of birth, and time to death on mortality of lynx due to or complicated by plague. RESULTS All PHA prevaccination titers were negative. All vaccinated lynx showed seroconversion on the PHA assay at the after the first and second booster (figure 1.). ELISA results are pending. There were no vaccine site reactions and no adverse side effects were seen. 132 �Vaccine Response PHA antibody titer 10000 pre post 1st dose post 2nd dose 1000 100 10 1 QF2 QF3 QF4 QF6 QF7 BF1 animal id BF2 BF3 BF4 BF6 Figure 1. PHA antibody titer for individual lynx. All pre titers were negative. All lynx showed seroconversion following vaccination. DISCUSSION Lynx were examined on entry and 5 females from Quebec and 5 females from British Columbia were randomly chosen for vaccination with F1-V fusion protein plague vaccine. All pre vaccine PHA titers were negative. All vaccinates showed seroconversion but the quantitative titer assays are still pending. The vaccine appears to be safe in lynx; there were no vaccine site reactions or adverse systemic reactions. LITERATURE CITED Burnham, K. P. and D. R. Anderson. 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. Second edition. Springer-Verlag. New York. Cully, J. F. 1993. Plague, prairie dogs, and black-footed ferrets. In Management of prairie dog complexes for the reintroduction of the black-footed ferret, J. L. Oldemeyer, D. E. Biggins, B. J. Miller, and R. Crete (eds.). U.S. Fish and Wildlife Service, Biological Report 13, Washington, D.C., pp. 38– 49. Creekmore, T. E., T. E. Rocke, and J. Hurley. 2002. A baiting system for delivery of an oral plague vaccine to black-tailed prairie dogs. Journal of Wildlife Diseases 38: 32–39. Fitzgerald, J. P., C. A. Meaney, and D. M. Armstrong. 1994. Mammals of Colorado. Denver Museum of Natural History and University Press of Colorado, Denver, Colorado, pp. 368–371. Gasper, P. W., and R. P. Watson. 2001. Plague and yersiniosis. In Infectious diseases of wild mammals, 3rd edition, E. S. Williams and I. K. Barker (eds.). Iowa State University Press, Ames, Iowa, pp. 313–329. Heath, D. G., G. W. Anderson, Jr., J. M. Mauro, S. L. Welkos, G. P. Andrews, J. Adamovicz, and A. M. Friedlander. 1998. Protection against experimental bubonic and pneumonic plague by a recombinant capsular F1-V antigen fusion protein vaccine. Vaccine 16: 1131–1137. 133 �Rocke, T. E., J. Mencher, S. R. Smith, A. M. Friedlander, G. P. Andrews, and L. A. Baeten. Recombinant F1-V fusion protein vaccine protects black-footed ferrets (Mustela nigripes) avainst virulent Yersinia pestis infection. Journal of Zoo and Wildlife Medicine, in press.Shenk, T. 2003. Species conservation: Colorado’s lynx. Lynx Home Page, Colorado Division of Wildlife, Denver, Colorado. Accessed 23 October 2003 at http://wildlife.state.co.us/species_cons/lynx.asp. Wild, M. A. 2000. Lynx veterinary services and diagnostics. Federal Aid: Wildlife Research Report for the Colorado Division of Wildlife, pp 47-62. Wuerthner, G. 1997. Viewpoint: The black-tailed prairie dog ⎯ headed for extinction? Journal of Range Management 50: 459–466 APPENDIX C EFFICACY OF KETAMINE MEDETOMIDINE COMBINATION IN MOUTAIN LIONS (Puma concolor) , MULE DEER (Odocoileus hemionus) AND WHITE-TAILED DEER (Odocoileus verginianus) FOR CHEMICAL IMMOBILIZATION IN THE FIELD L. L. Wolfe, W. R. Lance and M. W. Miller In cooperation with Wildlife Pharmaceuticals, Inc. (Fort Collins, CO) we are using ketamine (200mg/ml) and medetomidine (20 mg/ml) compounded at a higher concentration than commercially available. By concentrating the drugs we are able to use an effective dose in a 1 cc dart for mountain lions and a 2 cc dart for deer. To date over 200 deer have been captured and 5 mountain lions using this combination. No adverse side effects have been seen. Evaluation of this drug combination for field capture is ongoing. 134 �APPENDIX D EVALUATION OF COLLARED AND UNCOLLARED DANINJECT AND PNEUDARTS L. L. Wolfe, D. M. Okeson, W. R. Lance, J. Rhyan, and M. W. Miller INTRODUCTION Remote delivery systems, powered by compressed CO2 or blank charge, are an important tool for wildlife immobilization. Darts used with these remote delivery systems are barbed, collared or have uncollared needles. The purpose of the barbs and collars are to hold darts in place long enough to ensure complete drug delivery. However, barbed darts can only be used to deliver anesthetics, thus allowing for dart retrieval. Collared darts and uncollared darts will fall out on their own, but drug delivery may be incomplete. Drugs are delivered from the darts with a powder charge (Pneu-dartTM, Williamsport, PA) or pressurized air (DaninjectTM, Wildlife Pharmaceuticals, Fort Collins, CO). Some level of trauma is inherent, and varies greatly with the type of dart used (Valenburg et al. 1999, Kreeger 2002). Powder charged darts deliver drug rapidly, but are potentially more traumatic than the air pressurized darts; consequently, induction times vary when these darts are used to deliver anesthetic drugs. In this study we compared drug delivery between collared and uncollared darts. We compared dart trauma between collared and uncollared darts and we comopared Daninject darts with Pneu-darts. METHODS This study was conducted in conjunction with a previously-approved terminal study testing fallow deer susceptibility to chronic wasting disease (CWD) (CDOW ACUC 12-2000). Because these animals were already slated for euthanasia, we opportunistically evaluate and compare trauma and drug delivery associated with the respective dart types immediately prior to euthanasia. Deeply anesthetized fallow deer were placed on a stand to facilitate darting the hindquarters. Each animal was darted in the hindquarter with a collared Daninject dart and Pneu-dart dart on one side and uncollared Dainject dart and Pneu-dart dart on the opposite side. Darts were loaded with 2 cc India ink. The animals were then be euthanized by intravenous injection of Euthansol (8.8 mg/kg). Each dart site was evaluated for amount of India ink leakage at dart site, degree of trauma (recorded on a scale of 03. (0= none, 3 = extensive hemorrhage and tissue disruption) and ink injection pattern. All fallow deer were be captured with thiafentanil oxalate (0.1 mg/kg) delivered intramuscularly (IM) via projectile syringe using an adjustable air-powered rifle and xylazine hydrochloride. Anesthetic drugs were delivered to the shoulder and neck to avoid confounding subsequent assessment of dart effects. RESULTS On necropsy the ink pattern at the injection site was evaluated. A common ink pattern noted at necropsy was a “T”shaped pattern. The superficial area of ink (top of T) averaged 20-25 mm in diameter (recorded on line #4- spread of ink in muscle). Note that this refers only to the most superficial spread (horizontally) of the ink in the muscle; ink forming the top part of the T was typically only 2 mm thick. Ink then typically followed the needle track 20-30 mm into muscle. The pattern of “focal” was often recorded, but would probably be more correctly stated as “along needle track” as these 20-30 mm deep tracks were typically only 2 mm wide (roughly the diameter of a needle). 135 �Most injection sites had minimal hemorrhage or trauma this was recorded on a scale of 0-3. (0= none, 3 = extensive hemorrhage and tissue disruption) Overall, most dart sites were rated a “0” (12 of 32 darts) or a “1” (7 of 32 darts). Uncollared PneuDarts Eight of 8 uncollared PneuDarts bounced off the animal immediately after impact. However, ink was delivered into the animals, in all but one case. In 5 cases darts bounced, but no ink was noted on the hair of the animal or was observed spraying from the bounced dart. At necropsy, ink was noted in muscle in all of these cases, indicating that the bounced darts did deliver ink prior to ejecting from animal. One dart that bounced was noted to have sprayed a large amount of ink. However on necropsy, ink was found in muscle, indicating that dart did deliver at least some of the ink into the muscle. One dart bounced was noted as “did inject”, but some ink was noted on hair around injection site. At necropsy, ink was found in muscle, indicating that dart did deliver at least some of the ink into the muscle. One dart bounced was noted as “did inject”, but there was ink running down from the injection site. At necropsy, it was hard to distinguish any ink from bruising, so this dart may have not injected any ink into the muscle. There were 2 of 8 animals scored as “3” (extensive hemorrhage and tissue disruption). However there were also 3 of 8 animals scored as a “0” (no hemorrhage and tissue disruption.). In addition 2 of 8 were NR (not recorded). It is difficult to draw a conclusion as to whether or not there is a tendency for this type of dart to cause more tissue damage. Fallow deer dart study 4/16/03 - Results for smooth Pneudart (symbol +) Deer # Dart stayed Ink on in muscle? hair 1102 N 1 202 N NR 302 N 3 2002 N 1 1002 N 1 Depth of ink in muscle 5 mm Pattern of ink in muscle Superficial spread of ink on muscle Hemorrhage/ trauma 25 mm NR ? 2 unknown 0 ? 3 N 0 N NR Unable to distinguish ink from hemorrhage/bruising. Did dart inject? 20 mm located 20 mm deep 5 mm deep, focal 20 mm 15 mm focal spot located 20 mm deep dissecting on tendon sheaths 1802 N 0 2502 N 0 < 2 mm only superficially delivered 1202 N 1 20 mm NR spot located 20 mm deep focal, but no needle track 5 mm 60 mm superficial spot plus spot located 20 mm deep into muscle with a 20 mm diameter 20 mm Fits typical T pattern of ink spread? 3 Y 0 N NR ? Collared PneuDarts All 8 collared PneuDarts stayed in the animal after impact. In 3 of 8 cases the darts delivered ink only very superficially (not deep in muscle). Overall the collared darts caused very little trauma. There were 2 of 8 animals with a rating of “0”, and 2 of 8 with a rating of “1”. Only 1 of 8 animals had a rating of either “2” or “3”. Not recorded = 2 of 8. 136 �Fallow deer dart study 4/16/03 - Results for collared Pneudarts (symbol #) Deer # Dart stayed Ink on in muscle? hair Depth of ink in muscle Pattern of ink in muscle Superficial spread of ink on muscle Hemorrhage/ trauma only superficially delivered 20 mm 2 5 mm 3 Not sure of pattern 0 N; Ink only superficially delivered with spread along superficial fascial planes 1102 Y 0 "very superficial" (?<2mm) 202 Y 0 20 mm deep, focal 70 mm Fits typical T pattern of ink spread? N; Ink only superficially delivered, minimal muscle penetration of ink. 302 Y 0 < 2mm 70 mm superficial "splotch", dissects along fascial planes 2002 Y 0 20 mm focal 20 mm 1 Y 1002 Y 0 30 mm focal 5 mm NR Y 1802 Y 0 35 mm focal 5 mm 1 Y 2502 Y 0 < 2mm only superficially delivered 60 mm 0 N; Ink only superficially delivered, minimal muscle penetration of ink. 1202 Y 0 15 mm NR 20 mm NR ? Uncollared Dan-Inject Darts Seven of 8 uncollared Dan-Inject darts stayed in the animal’s muscle after impact. The result of one uncollared Dan-Inject dart was not recorded. Overall, the uncollared Dan-inject darts caused very little hemorrhage or trauma. Four of 8 animals had a rating of “0” hemorrage/trauma rating and 2 scored 1 and 1 scored 2. Fallow deer dart study 4/16/03 - Results for smooth DanInject darts (symbol *) Deer # Dart stayed Ink on Depth of ink Pattern of ink in muscle? hair in muscle in muscle 1102 Y 0 < 2mm 202 Y 0 0 Superficial spread of ink on muscle very superficial no ink injected into muscle Hemorrhage/ Fits typical T pattern trauma of ink spread? 15 mm 1 2 smooth Daninjects hit animal. 1st "penetrated leg, injection out back side of leg". 2nd dart also recorded as Yes stayed in muscle & 0 ink on hair; but not sure if depth, pattern, and spread info is for 1st or 2nd dart. ??? 0 0 N; dart went deep into limb but injected ink out medial aspect 302 Y 0 30 mm deep, focal 20 mm 1 Y 2002 Y 0 50 mm deep, focal 5 mm 0 Y 1002 NR 0 15 mm focal 5 mm 0 Y 1802 Y 0 50 mm NR (not recorded) 20 mm 0 Y? 2502 Y 3 75 mm 1202 Y 0 0 NR 10 mm 2 1st smooth Daninject dart went through leg, injected some out caudal aspect (3 for ink on hair refers to ink on back of limb from 1st dart). 2nd dart recorded as - stayed in muscle, no ink on hair; but not sure if 75 mm & 10 mm is for 2nd dart or 1st dart??? only superficially delivered 20 mm NR N; Ink only superficially delivered, no muscle penetration of ink. Collared Dan-Inject Darts Seven of 8 collared Dan-Inject darts stayed in the animal’s muscle after impact. The result of one collared Dan-Inject dart was not recorded. These darts shows a tendency to cause little to no tissue damage. There were 6 of 8 animals with a rating of either “0” or “1”. These darts show a tendency to cause little to no tissue damage. There were 3 of 8 animals with a rating of “0”, and 3 of 8 with a rating of “1”. Only 1 of 8 animals had a rating of “3”. 137 �Fallow deer dart study 4/16/03 - Results for DanInject collared darts (symbol @) Deer # Dart stayed Ink on in muscle? hair Depth of ink Pattern of ink in muscle in muscle Superficial spread of ink on muscle Hemorrhage/ Fits typical T pattern trauma of ink spread? 1102 Y 0 5 mm focal 15 mm 1 Y 202 Y 0 2 mm deep, focal 10 mm 0 N, basically round superficial, spot 302 Y 0 20 mm diffuse ~15 mm 10 mm "deep" (?) 1 ? Not sure of pattern 2002 Y 0 5 mm 3 ? Not sure of pattern 1002 NR 1 25 mm deep, focal 25 mm 1 ? Not sure of pattern 1802 Y 0 40 mm deep, focal 5 mm 0 Y? may be 5 mm wide all the way down 2502 Y 0 10 mm deep, focal 25 mm 0 Y 1202 Y 0 35 mm NR (= not recorded) 35 mm NR ?; Note 0.5 mL of ink left in dart deep 15 mm dissects btw muscle masses DISCUSSION All of the collared darts stayed in the muscle (did not bounce). All of the Daninject uncollared darts also stayed in the muscle. Only the uncollared pneudarts bounced out of the muscle. There was no inject sprayed on the hair of animals darted with collared pneudarts. Only one animal in each group of animals darted with daninjects had ink sprayed on the hair. Five of the animals darted with uncollared pneudarts had ink sprayed on the hair. LITERATURE CITED Kreeger, T. J. 2002. Analyses of immobilizing dart characteristics. Wildlife Society Bulletin. 30(3) 968−970. Valkenburg, P., R. W. Tobey, and D. Kirk. 1999. Velocity of tranquilizer darts and capture mortality of caribou calves. Wildlife Society Bulletin. 27(4) 894−896. Prepared by _______________________________ Lisa L. Wolfe, Veterinarian 138 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Colorado Project No. Work Package No. 3740 Task No. 3 : : : : Cost Center 3430 Mammals Research Mammals Support Services Animal and Pen Support Facilities for Mammals Research Period Covered: July 1, 2003 – June 30, 2004. Author: T.R. Davis Personnel: M. Anderson, K. Beamer, T. Bogardus, E. Crawford, E. Donegan, M. Dupire, K. Fagerstone, J. Faue, E. Featherman, K. Fox, T. Halasinski, L. Ho, M. Hanusack, G. Harvey, E. Jones, K. Kanapeckas, J. Kint, G. Kyriacou, I. Levan, T. McCollum, A. Mitchell, A. Northrup, M. Paulek, A. Phillips, R. Rhyan, T. Sanders, J. Sirochman, T. Sirochman, J. Stout, T. Stout, D. Thompson, R. Thompson, D. Weaver, A. Wilson All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife's Foothills Wildlife Research Facility (FWRF) maintained captive animals (2003/2004 annual total: 360) and facilities in support of seventeen captive wildlife research projects. The primary focus of research during this period was chronic wasting disease (CWD) pathology, epidemiology, preventative therapies, sources of transmission in deer and potential transmission to other species. FWRF supported a number of other significant research projects including contraception and reproductive effects, pathogen immunization, evaluation of wildlife capture pharmaceuticals and personnel training in ante mortem sampling and field immobilization. The quality of animal care and facility maintenance provided by temporary, work-study, personal service, intern and volunteer employees is in part reflected by the finding of compliance under the Animal Welfare Act during the annual USDA inspection of FWRF. Herd management practices allowed pronghorn antelope and bighorn sheep herd levels to decline through natural mortality and the remaining domestic ferrets were removed as per study protocols. Alternatively, herd levels of mule deer and white-tailed deer were managed for maximum growth to support on going CWD research. Chronic wasting disease was again a significant source of mortality in mule deer and white-tailed deer and is reflected by the number of CWD research projects conducted during this period. We continue to manage CWD with the philosophy of managing the disease for research purposes under heightened bio-safety guidelines and intensive herd management. Fawn mortalities were higher than expected during the 2004 rearing season however a number of disease causing agents and contributing factors were identified through various diagnostic tests and evaluations. Neonate training was intensified for hand raised animals and training SOP’s developed to accommodate CWD epidemiology research. Administrative actions include compiling a summary of all current and historic FWRF published research, an animal husbandry change order request was 139 �implemented, and the FWRF tour policy revised. New SOP’s were implemented for routine equipment maintenance, seasonal winterizing, tree/shrub care, and the construction maintenance work request forms were revised and reinstated. In addition to routine maintenance, the FWRF team made significant facility improvements including new facilities to accommodate CWD epidemiology research, completion of the mountain lion holding facility, and installation of a perimeter fence around the Wildlife Health Lab. The capitol construction team allocated funds for a new hay barn which is scheduled for replacement in the summer of 2005, and engineering assisted in the development of electronic facility site maps. In addition, the FWRF landowner; Colorado State University approved an easement for the Northern Colorado Water Conservation District to install a 68 inch water pipeline through the center of the facility (north to south). The installation process partially disrupted FWRF management activities for a six week period, but resulted in an upgraded road system, and replacement of existing windrows with five gallon potted trees and shrubs. 140 �JOB PROGRESS REPORT ANIMAL AND PEN SUPPORT FACILITIES FOR MAMMALS RESEARCH T.R. Davis Animal Maintenance: Routine animal husbandry including feeding, health observations, training, weighing, and cleanup, was performed primarily by well trained temporary employees, work-study students, and volunteers. FWRF was inspected by USDA APHIS for compliance with federal animal welfare regulations on July 28, 2004. Table 1 summarizes the number of animals by species reported to USDA animal welfare for the period of October 1, 2003 – September 30, 2004. Table 1. Total number of animals by species reported to USDA Animal Welfare Species Bighorn Sheep Number of animals held, not dedicated to research 11 16 Number of animals dedicated to research 2003/2004 Total 16 15 27 31 0 28 28 75 84 159 19 0 19 1 0 1 45 25 70 0 11 11 167 179 346 201 0 10 10 1 0 1 0 3 3 168 192 360 Elk Fallow Deer Mule Deer Pronghorn Antelope Sika Deer White-tailed Deer Cattle Ungulate Total Ungulate Mean Domestic Ferrets Prairie Dog Mountain Lions Facility Total 141 �The number of animals held but not dedicated to research includes all animals being bred, conditioned, or held for use in research, but not yet used for such purposes. This group consists primarily of breeding animals, and young animals. The relatively high number of ungulates not dedicated to research during this period is the result of a large influx of young animals (born at FWRF, and orphaned neonates) dedicated to the CWD epidemiology study scheduled to begin data collections in the fall of 2004. The total number of animals dedicated to research includes all animals used in experiments at any time during the period. Experiments include those involving no pain, distress, or use of pain relieving drugs, and experiments where pain relieving drugs were necessary to minimize stress on the animal. No animals at FWRF were used in experiments involving pain, without the use of anesthetic, analgesic or tranquilizing drugs. The species total includes all adult animals housed at the facility, neonates born at the facility, transfers into and out of the facility, and all animals that died or were humanely euthanized during the respective fiscal year. It is important to note that ungulate herd levels at any one time averaged approximately 60 percent of the ungulate total and 55% percent of the total number of animals housed at the facility for the entire period. Herd Management: One habituated sika deer and one habituated prairie dog were brought into the facility to support division law enforcement efforts. Mule deer, white-tailed deer, and elk herd levels were expanded through herd management practices and incoming transfers to support CWD and fertility control research. Incoming transfers consisted primarily of habituated adult animals and orphaned neonates obtained from various locations around the state, as well as Wyoming, Nebraska, Iowa, and Kansas. The bighorn sheep and pronghorn antelope herds were reduced through natural mortality and out going transfers as the experiments these animals were dedicated to, reached a stage of completion. Eight fallow deer and the remaining domestic ferrets were removed through planned euthanasia as per the study protocols, while mountain lion and cattle numbers remained constant for the period. Commission approval was granted in 2001 to transfer excess FWRF captive wildlife, and/or orphaned neonates out of state to support collaborative and non-agency wildlife research projects. In 2004 eight pronghorn antelope neonates were transferred to the National Wildlife Research Center (NWRC) in Fort Collins. Two of these animals were orphaned neonates, and six were excess animals of FWRF origin. Other facility transfers include a pronghorn buck that was borrowed from, and returned to, the Sybille Wildlife Research Unit in Wyoming. FWRF herd management practices include planned breeding to maintain optimal population sizes of the various species required to support current and future research projects. Depending on research objectives, some of the offspring from FWRF animals are hand-raised, and various species of wild orphaned neonates are accepted for hand rearing. Habituated weanlings and adult animals are also accepted whenever herd levels will allow. Hand rearing protocols for mule deer are described by Parker and Wong (1987), and by Wild and Miller (1991) for bighorn sheep, elk, pronghorn antelope, and whitetailed deer. Table 3 summarizes the breeding and rearing practices of ungulate species for the period: 142 �Table 3. FWRF Ungulate breeding and rearing practices FWRF Breeding FWRF Neonate Orphan/Transferred 2003 Rearing 2004 Neonates 2004 Hand raised 2 Dam Bighorn Sheep Bred 7 Ewes raised 3 0 Species 2003/2004 Elk Bred 3 Cows Mule Deer Pronghorn Antelope White-tailed Deer Bred 17 Does Bred 4 does Bred 9 does Dam raised 3 Hand raised 16 Dam raised 11 Transferred to NWRC 6 Hand raised 6 Dam raised 7 1 32 0 24 Table 3 does not include three orphan mule deer fawns euthanized on arrival due to severe injuries, or very poor body condition, and five animals (3 mule deer, 2 white-tailed deer) which were still born or died shortly after birth due to parturition complications. The mountain lions, domestic ferrets, and fallow deer are also not included in the above table, as the mountain lions and domestic ferrets were neutered at an early age and the male fallow deer were vasectomies prior to the 2003 breeding season and therefore no breeding occurred in these species. Nutritional Maintenance: Feeding protocols for ungulates previously housed at the facility were reviewed by Wild (1997), and feeding protocols for the fallow deer and mountain lions were described by Davis (2003). The sika deer was maintained on a high quality grass alfalfa mix hay and Regular Ranch-way deer and elk ration. The prairie dog was maintained on Mazuri ADF # 25 herbivore diet, grass/alfalfa mix hay, and fresh vegetables. Individuals of all species maintained reasonable body condition on available diets with the exception of some hand raised neonates (primarily mule deer fawns), and CWD infected animals at the clinical stage of the disease. Fawn mortalities may have been associated with general poor body condition of does infected with chronic wasting disease, the presence of other etiological agents identified (see health maintenance below), and/or interspecies competition for space and cover in paddocks housing cattle and fallow deer. Pen Enrichment: In an effort to provide cover and subsequently reduce stress, additional artificial refuge areas were constructed in paddocks housing semi-wild deer and dam raised neonates. “Y” shaped hide-outs, were constructed on site, vegetation ex-closures were added in early spring and removed later to enhance natural cover, and creep areas with natural cover were provided for dam raised fawns. All pen structure enrichments were readily accepted and utilized by the animals. In addition to pen structure, behavioral enrichment was offered through training. Expanding on the operant conditioning system for mountain lions described by Davis (2003) hand raised ungulate neonates were "treat" trained using the same philosophy. Bighorn sheep, mule deer and white-tailed deer were taught to follow their human trainers and stand on the scale for physical exams, injections, treatments and weighing. Additionally, mule deer and white-tailed deer were gradually conditioned to the metabolic cages in preparation for CWD epidemiology sample collections. Passive training was used in conjunction with the above techniques to habituate animals to the scale and alley-way through supplemental feeding to encourage free exploration without human interference, in these areas. 143 �Health Maintenance: Animal health care was provided as required and as mandated by the preventive medicine program (Wild 1995) and chronic wasting disease protocols. Overall, captive wildlife maintained at FWRF remained healthy throughout the period. Chronic wasting disease (CWD) continues to be a significant source of mortality in captive mule deer and white-tailed deer and is reflected by the number of animals dedicated to CWD research projects throughout this period. Mortality of an adult pronghorn doe was attributed to dystocia, and as described in previous years (Davis 2003) was associated with a failure of the cervix to dilate at the time of parturition. Several cases of dystocia with variable presentations were also observed in mule deer (n=2) and white-tailed deer (n=1). Epizootic hemorrhagic disease (EHD) and bluetongue virus (BTV) were not significant etiological agents during this period and may be associated with a management effort to reduce the quantity of free standing water on the facility, coinciding with the time of documented seasonal peaks of the disease. Mortality rates and disease were higher than expected in hand raised mule deer fawns. Hand raised fawn mortalities were primarily associated with two types of illness: 1.) Intestinal disease resulting in diarrhea, bloating, and/or dehydration accompanied by a general lack of appetite and failure to thrive, and 2.) Respiratory disease (acute bacterial pneumonia) resulting in nasal discharge, coughing, labored breathing, and in some cases, no preliminary signs and acute death. Post mortem sampling and fecal isolation, revealed clostridium perfringens, salmonella, Escherichia coli, and rotovirus. Nasal cultures and post mortem sampling of lung tissue revealed mixed bacterial infections including, Alcaligenes species, Pasteurella species, Pseudomonas aeruginosa, however Arcanobacterium pyogenes was consistently diagnosed and is likely responsible for those cases resulting in acute death. In addition to the etiological agents identified, several management and natural conditions may have contributed to fawn mortalities: 1) Inadequate hospital facilities, and clean isolation areas to separate sick animals (facility carrying capacity), 2) Higher than normal precipitation levels contributing to viable pathogens surviving in the soil for longer periods, and greater exposure to damp/cool conditions, 3) immuno-compromised animals to start with, as FWRF born fawns are exposed to a very pathogen rich environment at birth, and, a high percentage of the hand raised animals were orphans who are often in poor body condition and/or ill when they arrive. Due to animal welfare concerns, management recommends construction of adequate animal holding and hospital facilities prior to hand raising mule deer in the future, as well as a review of the neonate nutrition, health maintenance, and fawn rearing programs. Chronic Wasting Disease: Following the recent revision of the CWD protocol (Davis 2003), we continue to manage CWD with the philosophy of managing the disease for research purposes under heightened bio-safety guidelines and intensive herd management. Intensive herd management is accomplished using the early detection techniques described by Wild et. al (2002) and Wolfe et. al (2002). All animals at FWRF were monitored closely for clinical signs of CWD, and tissues from all mortalities occurring at FWRF were examined for evidence of infection with CWD. Systems Development: Administrative actions include compiling a summary of published articles generated from FWRF research. Hard copies of the 100 + articles filed by date of publication are available at FWRF and the research library. Currently, we are compiling an Access database of the articles to facilitate searches by author, subject, date, etc. In addition, an animal husbandry change order request was implemented as suggested by the Mammals research leader. The change order, modeled after the construction/maintenance work request, was designed to track the origin and justification of facility changes in herd stocking levels, species needs, and basic husbandry techniques including animal care, breeding, rearing, and training practices. 144 �Other administrative actions include the development of new standard operating procedures for routine equipment maintenance, seasonal winterizing, and tree/shrub care. The SOP’s are designed to put all FWRF equipment on a routine maintenance and winterizing schedule, and the schedule is specific to what level of maintenance is necessary at each interval. In the same fashion an SOP was developed for soil moisture testing and watering of tree and shrub windrows. Due to the increasing demands for unscheduled (but necessary and often emergency) construction and maintenance needs, the work request forms were revised and reinstated. The forms were designed to assist in prioritizing and assigning tasks, as well as provide a format for information transfer (an accurate description of the need), and to track labor costs associated with specific projects, routine and emergency maintenance. Educational Contributions: The FWRF tour policy was also revised. The revised policy allows for use of FWRF animals and facilities for hands on training of CDOW employees, collaborators, and other professional groups in sampling techniques and chemical immobilization when pre-approved by the Mammals research leader and/or the Animal Care and Use Committee (ACUC). FWRF functions primarily to support wildlife research, but will no longer function secondarily as an educational facility due to the overwhelming demand for this service. Protecting the integrity of the research, facility management, and increasing animal welfare concerns were sufficient justifications for the policy change. Research Projects: Facility operations offered support for research projects conducted by CDOW personnel and other collaborators that were initiated, conducted, or continued using FWRF animals and facilities. A total of twenty one research projects were supported by FWRF for the period: • • • • • • • • • • • • • • • • • Cattle susceptibility to chronic wasting disease. Susceptibility of fallow deer to chronic wasting disease. Susceptibility of Mountain Lions to chronic wasting disease. Mechanisms of CWD transmission in mule deer. Evaluation of prospective preventative therapies for chronic wasting disease in mule deer. Validation of a potential blood test for chronic wasting disease (GeneThera test). Molecular epidemiology of strain variations in chronic wasting disease. Pathogenesis of chronic wasting disease in white-tailed deer. Effect of copper pathogenesis of CWD in white-tailed deer. Epidemiology of chronic wasting disease: detection of PrPres, shedding, and environmental contamination. Evaluation of third eyelid biopsy for detection of chronic wasting disease infection in mule deer. Survey for chronic wasting disease in cottontail rabbit populations. Leuprolide as a contraceptive agent in female elk: determination of effective minimum dose. Evaluation of GnRH-PAP as a chemosterilant in captive mule deer. I. Effects on animal health. Experimental evaluation of a vaccine for clostridium perfringens type A in captive bighorn sheep (Ovis canadensis) and captive mule deer (Odocoileus hemionus). Training personnel for tonsil biopsy for chronic wasting disease in mule deer. Field Immobilization Training. Facility Improvement Projects: A variety of scheduled and unscheduled maintenance and repair activities were necessary to support facility operation and ongoing research programs. Highlights include construction of new animal holding facilities and restoration of the metabolic cages to accommodate CWD epidemiology research. The mountain lion holding facility was also completed with the exception of the scale and squeeze/treatment area, as we are still in the design phase on this portion of the project. Additional 145 �funding assistance from the Wildlife Health Laboratory (WHL) permitted installation of a separate perimeter fence around WHL. The new fence will allow easier access to the laboratory, while controlling traffic into and out of the animal holding facility. Additional facility modifications include allocation of funding from the capitol construction team to replace the main hay barn. The barn is scheduled for replacement in the summer of 2005, and will be relocated to a central site with better access. The engineering office assisted with the development of electronic site maps of the facility. The site maps show exact locations for buildings and animal holding facilities, as well as locations for all known utilities. The maps will be updated periodically as facility construction and modifications occur. In addition, the FWRF landowner; Colorado State University approved an easement for the Northern Colorado Water Conservation District (NCWCD) to install a 68 inch water pipeline through the center of the facility (north to south). The easement was approved by the CDOW legal staff and included stipulations to maintain the perimeter fence, vehicle access, and keep all excavated soil within the perimeter of FWRF. The installation process partially disrupted FWRF management activities for a six week period, but resulted in an upgraded road system, and replacement of existing windrows with 200 five gallon potted trees and shrubs. NCWCD donated three culverts, built up the road system with excavated dirt, and added road-base which will allow for better water run-off, and should reduce road maintenance costs in the future. Facility maintenance and construction projects were prioritized based on animal welfare concerns and anticipated research needs. Table 3 summarizes the completed, current, and on-going facility construction maintenance projects for the period. 146 �Table 3. Facility Improvement Projects Project 1. CWD Therapy Pens 2. Travel Installation Status Completed Trailer Completed 3. WHL and FWRF Completed Parking Area Improvements 4. D3-6 Feed Area Completed Exclosures /catch areas 5. Electrical Upgrades 6. New Tool Equipment Shed Completed and Completed 7. E4 Site Clean-up Completed 8. Lion Facility Walk-in Completed, Freezer /Cooler Engineering request approved 9. Road Improvements Completed 10. FWRF Electronic Site Maps Completed 11. WHL Water Shut- Completed off Valve 12. Office Septic Pipe Completed Repair 13. WHL Perimeter Completed Fence Completion Details Year Split 2 pens into 4, Construct 3 new 2003/2004 shelters, add 1 automatic water (2 others included in east side plumbing upgrades above) Prepare 3 sites, winterize, hook into 2003/2004 electric, water, septic, and purchase propane tank for one, electric and water hook-up for the others, electrical and furnace repair for the third, and misc. repairs for housing, office, and lab space Add road base, gravel, landscaping 2003/2004 timbers to expand and improve parking areas Re-set poles, replace range wire and 2003/2004 snow fence with Hog panels in MD feed areas and catch areas Increased power needed for expanding 2003/2004 facilities- East and West sides, West side upgrades provided by WSVL Provided by NCWCD to replace shed 2003/2004 demolished for water pipeline construction Remove 6 top inches of soil, saturate 2003/2004 with 20% bleach soln., add 2 inches of road-base to lambing area Add a 10 x 10 cooler, and 10 x 10 2003/2004 freezer unit to the mountain lion complex The road system was built-up with extra 2003/2004 dirt to enhance water run-off, 4 new culverts, time and equipt. to build up road system and install culverts were donated by NCWCD Generated electronic site maps from an 2003/2004 aerial photo, with all utilities, animal holding facilities, and structures Valve was added to allow shut off the 2003/2004 pen and necropsy lab water, while still providing water to the lab Emergency repairs to a cracked septic 2003/2004 pipe Construct a new perimeter fence around 2003/2004 the lab to allow access to the lab without compromising the animal holding facility perimeter fence 147 �Project Status 14. Emergency Fawn Completed Rearing Shelters 15. Equipment storage Completed slab 16. DOD study Completed Facilities 17. Trailer Water Shut- Completed Off Valve Replacement 18. Mountain Lion Completed Facility 19. New roofs/repair On-going project structure on old feedsheds and animal shelters. 20. Add additional On-going project animal shelters 21. Road Maintenance On-going project 22. Paint old building On-going project exteriors 23. Repair/replace On-going project latches, and broken or water damaged alleyway boards 24. Replace walk thru On-going project alley gates Details Dairy calf shelters purchased and installed in waterfowl pen, fences modified to accommodate fawns Pour a concrete slab to store tractor and bobcat attachments out of the mud Convert E7 into 4 pens, add 6 automatic waters, construct 2 alleys, repair N. alley and Dig. Cage ramps, add drainage ditch, double fencing, refurbish the metabolic cages Some materials and labor donated by WSVL Replace leaking water shut-off valve to FWRF travel trailer Utilities, concrete block building, 50 x 60 foot outdoor pen, shift containment system, and 4 indoor dens Approx. ¼ of the old structures and roofs on the facility have been replaced in the last 2 years using treated lumber and long lasting roofing materials Construct additional shelters in pens with heavy stocking rates. (36 ungulate pens on the facility) Road grading and upkeep Now using CCA treated lumber or metal siding for repairs & building replacements to reduce the amount of painting necessary in the future. Now using CCA treated lumber for all repairs Replace old gates as necessary Completion Year 2003/2004 2004/2005 2004/2005 2004/2005 2004/2005 Began 2000/2001, as needed Began 2001/2002, as needed As needed Old structures are on a painting schedule every 3-5 years As needed As needed 25. Replace old visual barrier fencing and utility wire on metal gates On-going project: most of the old material has been replaced, but this project is ongoing due to animal and environmental damage Old snow fence and construction fence Began replaced and moved to the outside of 2001/2002, the paddock fence (except interior as needed fences), utility wire is systematically being replaced with horse-fence 26. Animal holding fence upgrades, and repairs On-going project: rotten posts have been replaced, double fences constructed Replace old range fence and V-mesh, as Began well as electric fencing in pens that 2002/2003, house deer, Construct double fences as As needed required by CWD protocols 148 �Project Status 27. Construct artificial On-going project: refuge areas inside pens completed for all for neonates and adults new east side paddocks, maintain existing, construct new 28. Add windscreen to On-going project west and south facing fence-lines 29. Mowing and weed On-going project control 30.WHL maintenance On-going project 31. Unscheduled On-going project miscellaneous emergency facility repairs Completion Details Year Construct single and L-shaped, refuge Began areas to provide refuge and shade, 2002/2003, construct hog panel seasonal exclosures As needed to promote vegetation growth in the spring Provide additional shaded areas for Began animals, and maintain existing 2002/2003, As needed Seasonal mowing and manual, chemical As needed noxious weed control Provide maintenance assistance to Began WHL, and support for initial lab 2002/2003, construction As needed Emergency repairs to structures, animal As Needed holding facilities, perimeter fence, automatic waters, utilities, etc… LITERATURE CITED Davis, T. R., 2003. Animal and pen support facilities for mammals research. Colorado Div. Wildl. Res. Rep., Jan. 2001 – Jun. 2003, Fort Collins. Parker, K. L., and B. Wong. 1987. Raising black-tailed deer fawns at natural growth rates. Can. J. Zool. 65:20-23. Wild, M. A., and M. W. Miller 1991. Bottle raising wild ruminants in captivity. Colorado Div. Wildl. Outdoor Facts No. 114. Wild, M. A. 1997. Animal and pen support facilities for mammals research. Colorado Div. Wildl. Res. Rep., WP1a, J1, Jul 1996 - Jun 1997, Fort Collins. Wild, M. A., T. R. Spraker, C. J. Sigurdson, K. I. O’Rourke, and M. W. Miller. 2002. Preclinical diagnosis of chronic wasting disease in captive mule deer (Odocoileus hemionus) and white-tailed deer (Odocoileus virgineanus) using tonsillar biopsy. J. General Virol. 83:2629-2634. Wolfe, L. L., M. M. Conner, T. H. Baker, V. J. Dreitz, K. P. Burnham, E. S. Williams, N. T. Hobbs, and M. W. Miller. 2002. Evaluation of antemortem sampling to estimate chronic wasting disease prevalence in free-ranging mule deer. J. Wildl. Manage. 66:564-573 Prepared by ________________________________ Tracy R. Davis, Wildlife Technician 149 �150 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Colorado Project No. Work Package No. Task No. 5 Federal Aid Project: 3001 W-185-R : : : : Cost Center: 3430 Mammals Research Multispecies Investigations Consulting Services for Mark-Recapture Analysis : Period Covered: July 1, 2003 - June 30, 2004 Author: G. C. White Personnel: C. Bishop, G. Miller, T. E. Remington, D. J. Freddy, T. M. Shenk, L. Stevens, J. Craig, R. Kahn, D. C. Bowden, F. Pusateri, J. Dennis, P. Schnurr, B. Andelt, A. Seglund, D. Finley, A. Linstrom, K. Strohm, P. Conn. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Progress towards the objectives of this job include: 1. 2. 3. 4. 5. Consulting assistance to CDOW on harvest surveys, terrestrial inventory systems, and population modeling procedures was provided. Estimates of spring and fall turkey, spring snow goose, sharp-tailed and sage grouse, chukars, ptarmigan, Abert’s squirrels, and general small game harvest were computed from survey data, and programs and harvest estimates provided to CDOW via email and CD ROM. Computer code written in SAS to compute these estimates and display results graphically was also provided. Computer code was also written in SAS to estimate the compliance rate of Colorado small game license holders with the Harvest Information Program. The DEAMAN software package for the storage, summary, and analysis of big game population and harvest data was revised further as a Windows 95/98/NT/2000/ME/XP program. A User’s Manual was provided to terrestrial biologists on CD and also distributed via the WWW at http://www.cnr.colostate.edu/~gwhite/deaman. Consultation with CDOW Terrestrial Biologists in the use of DEAMAN and population modeling procedures continued. Numerous questions were answered via meetings with biologists, and via email. A paper on the use of lek counts to index prairie grouse populations was published in the Wildlife Society Bulletin: Walsh, D. P., G. C. White, T. E. Remington, and D. C. Bowden. 2004. Evaluation of the lek count index for greater sage-grouse. Wildlife Society Bulletin 32: 56-68. A paper on the effects of early season hunter numbers on elk movement was published in the Journal of Wildlife Management: Vieira, M. E. P., M. M. Conner, G. C. White, and D. J. 151 �6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. Freddy. 2003. Effects of archery hunter numbers and opening dates on elk movement. Journal of Wildlife Management. 67:717-728. A paper discussing the implications of the GMU 10 special mule deer surveys was accepted for publication in the Wildlife Society Bulletin: Freddy, D. J., G. C. White, M. C. Kneeland, R. H. Kahn, J. W. Unsworth, W. J. deVergie, V. K. Grahm, J. H. Ellenberger, and C. H. Wagner. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin. In Press. A paper on the impact of limited antlered harvest on mule deer sex and age ratios was accepted for publication in the Wildlife Society Bulletin: Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2004. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin. In Press. A paper on the survival and recruitment of peregrine falcons was accepted for publication in the Journal of Wildlife Management: Craig, G. R., G. C. White, and J. H. Enderson. 2004. Survival, recruitment, and rate of population change of the Colorado peregrine falcon population. Journal of Wildlife Management. In Press. A paper on the estimation of the area of black-tailed prairie dog colonies in eastern Colorado was submitted to the Wildlife Society Bulletin: White, G. C., J. R. Dennis, and F. M. Pusateri. 2004. Area of black-tailed prairie dog colonies in eastern Colorado. Wildlife Society Bulletin. Submitted. A paper on methodologies to obtain more rigorous population monitoring data was submitted to Wildlife Research: White, G. C. 2004. Correcting counts: techniques to de-index. Wildlife Research. Submitted. A paper evaluating methods of estimating the impact of harvest on survival rates was submitted to Animal Diversity and Conservation: Otis, D. L., and G. C. White. 2004. Evaluation of ultrastructure and random effects band recovery models for estimating relationships between survival and harvest rates in exploited populations. Animal Biodiversity and Conservation. Submitted. A paper on the procedures to monitor swift fox populations in eastern Colorado was submitted to the Journal of Wildlife Management: Finley, D. J., G. C. White and J. P. Fitzgerald. 2004. Estimation of swift fox population size and occupancy rates in eastern Colorado. Journal of Wildlife Management. Submitted. A research study to examine the impact of nutrition on the decline of mule deer fecundity during the last 20 years was continued in cooperation with Chad Bishop. Portions of this work will serve as his doctoral dissertation. A graduate research project (M. S.) to develop a sage grouse population model, using North Park sage grouse data to develop parameter estimates, was continued. The graduate student is Kristen Strohm. A graduate research project (M. S.) To evaluate line transect methodology for estimating pronghorn populations in eastern Colorado was initiated. The graduate student is Aaron Linstrom, and the project is in addition to his full-time duties as a terrestrial biologist with CDOW. A graduate research project (Ph. D.) to develop statistical models to monitor puma and black bear populations in Colorado based on checks of harvested animals and DNA and/or radiotracking data was initiated. The graduate student is Paul Conn. Development of the design of a monitoring system for white-tailed prairie dogs in western Colorado and eastern Utah was continued. This effort is in cooperation with Pam Schnurr, Bill Andelt, and Amy Seglund. Development of the design of a monitoring system for swift fox in eastern Colorado was continued. This effort is in cooperation with Francie Pusatari and Darby Finley. 152 �19. A workshop on use of the DEAMAN software for data entry, data summaries, and population modeling was presented to CDOW Terrestrial Biologists on May 20, 2004. A revised edition of the DEAMAN User’s Manual was provided on a CD. 153 �JOB PROGRESS REPORT CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSES G. C. White P. N. OBJECTIVES Extend existing methods to better provide rigorous population monitoring systems. SEGMENT OBJECTIVES 1. 2. Extend a mark-recapture monitoring scheme to estimate population sizes with inadequate data per site to estimate encounter probabilities. Contrast line transect distance sampling approaches with mark-recapture approaches for monitoring populations with inadequate data per site to estimate encounter probabilities. ABSTRACT One of the most pervasive uses of indices of wildlife populations is uncorrected counts of animals. Two examples are the minimum number known alive from capture and release studies, and aerial surveys where the detection probability is not estimated from a sightability model, marked animals, or distance sampling. Both the mark-recapture and distance sampling estimators are techniques to estimate the probability of detection of an individual animal (or cluster of animals), which is then used to correct a count of animals. However, often the number of animals in a survey is inadequate to compute an estimate of the detection probability, and hence correct the count. Modern methods allow sophisticated modeling to estimate the detection probability, including incorporating covariates to provide additional information about the detection probability. Examples from both distance and mark-recapture sampling are presented to demonstrate the approach. RESULTS AND DISCUSSION The practice of using raw counts of animals as an index of the population size is one of the most pervasive uses of indices in wildlife management (Anderson 2003; Engeman 2003; Anderson 2001). Two examples include aerial surveys where no probability of detection is used to correct the count of observed animals, and the use of the minimum number known alive (MNKA) in animal (particularly small mammal) trapping studies (Slade and Blair 2000; McKelvey and Pearson 2001). These counts are known to be biased estimates of population size, and when used as an index, are assumed to be proportional to population size. These uses of uncorrected counts are some of the most perilous uses of an index in the practice of wildlife management because this assumption of proportionality is seldom verified, and is often false. Nichols (1992) appealed to researchers to incorporate capture-recapture estimators into small mammal studies. However, various reasons are given to explain why indices are used in place of more rigorous capture-recapture estimators. The most common reasons (Slade and Blair 2000) include fear of violating assumptions basic to mark-recapture models (Nichols and Pollack 1983), failure to recognize that some of these models are relatively robust to heterogeneity of capture probability and trap response (Carothers 1979), mistaken belief that MNKA suffers less than other models from problems of differential probabilities of capture and survival when capture probabilities are high (Nichols and Pollack 1983; Montgomery 1987), and prevalence of protocols involving fewer than the 5 to 7 trapping occasions recommended for model selection and population estimation (Otis et al. 1978). 154 �McKelvey and Pearson (2001) found that 98% of the samples collected in studies published from 1996 through 2000 they reviewed were too small for reliable selection among models of population estimation. However, their results do not take into account improved model selection methodologies, and new software and estimators that allow combining data across multiple studies and/or sites to provide more reliable model selection and estimation of the nuisance parameters. Their results mainly reflect the capabilities of CAPTURE (Otis et al. 1978; White et al. 1982), a software package developed in the late 1970's. More recent developments are available. The purpose of this presentation is to present the advantages of modern methods of analysis that allow combining data from multiple studies into a type of meta-analysis. Although resulting estimates of population size may not be completely unbiased, these estimates will certainly have less bias than MNKA. As discussed by Eberhardt et al. (1999), status of endangered large-mammal populations may have to depend on indices of population trend, and such indices may be improved by using auxiliary variables. However, in this paper, I go beyond just trying to standardize the counts with auxiliary information, as done by Eberhardt et al. (1999), and present methods incorporating auxiliary covariates that provide estimates of the population size. Modern Methods Correcting counts to produce estimates of population size. Estimators of population size based on counts of animals share a common form. A count, C is corrected for the detection probability, p, to give the population size. Because the detection probability must be estimated as p̂ (or otherwise N would be known), the result is an estimate of population size C Nˆ = (Nichols 1992). The standard methods used in wildlife studies to estimate p are markˆ p encounter methods and distance sampling. Both these seemingly diverse methodologies perform the same function: to correct a count of animals by the probability of detecting an animal. To illustrate, consider the simple Lincoln-Petersen estimator: Nˆ = n1n 2 n n = 2 = 2 , m2 ˆ m2 p n1 where n1 and n2 are the numbers of animals captured on occasions 1 and 2, and m2 is the number of animals marked on occasion 1 that are recaptured on occasion 2. Thus, m2 is an estimate of the capture n1 probability on the second occasion (Nichols 1992), because we know that n1 animals are available for capture on the second occasion, of which m2 were captured. For distance sampling, the estimate of density (Buckland et al. 1993) is: nfˆ(0) n n A, Dˆ = = = ˆ 2LW ˆ p p 2LW where n is the count of animals, 2LW is the area surveyed (both sides of the transect line of length L out to ˆ(0) is equivalent to 1/ p̂ . So, the right-hand side of the equation is just the a strip width W), and f ⎛ corrected count ⎜⎜ Nˆ = ⎝ n⎞ ⎟ divided by the area counted to give density. The sightability correction ˆ ⎟⎠ p models of Samuel et al. (1987) also use an equivalent approach. The probability of sighting an animal is computed for each of the groups of animals sighted, and then the number of animals in the group is divided by the estimated sighting probability to estimate the number of animals under the observed conditions that were missed. When these estimates are summed across all groups, an overall estimate of population size is obtained. Although at first glance this estimator appears to be different than the forms shown above, in fact, it is exactly the same idea. Counts are corrected by an estimate of sightability. 155 �However, because the sightability models of Samuel et al. (1987) and their extensions require first developing a model that is then applied to multiple surveys, the protocol deviates from what is the focus of this paper. That is, this paper centers on the idea of combining a number of sparse datasets into one analysis to achieve better inferences. Therefore, sightability models do not particularly fit into this approach, and so will not be discussed further here. The take-home message of this section is that counts are corrected by some probability to achieve an estimate of population size. If this correction is the same when comparing results from two surveys, then comparing just the counts will result in the same proportional change. However, without verification of the assumption that the correction is the same for both surveys, erroneous results may ensue (Nichols 1992). Consider two counts of C1 = C2 = 100, but p̂1 = 0.5 and p̂ 2 = 0.25, resulting in N̂ 1 = 200 and N̂ 2 = 400. Without knowledge of the detection probabilities, the erroneous conclusion that the population had not changed would have been made. Of course, the opposite situation can also occur. Suppose C1 = 200 and C2 = 100, with p̂1 = 0.5 and p̂ 2 = 0.25, resulting in both N̂ 1 = N̂ 2 = 400. Just comparing the counts results in the erroneous conclusion that the population has changed, when in fact, only the detection probability has changed. Thus, comparing counts is dangerous without knowledge of the underlying detection probabilities. In the next section, more advanced approaches to estimation of the detection probability are presented. Improved modeling of data to produce estimates. Earlier approaches to estimation of the size of a closed population only used the information available from the data at hand, e.g., Otis et al. (1978). Program CAPTURE (White et al. 1982) produced separate analyses for each species, sex- and age-class, and trapping grid. However, newer software packages, such as Program MARK (White and Burnham 1999) allow the user to model parameters in user-defined models. As a result, the detection probability for a population estimator can be modeled with group-specific, time-specific, and even individual-specific covariates. These covariates provide additional information with which to improve the estimates of the detection parameters. With this kind of model building capability, multiple sparse (but related) datasets can be combined into models to generate more precise estimates of p. These estimates of detection parameters and population size do not necessarily have to be the same for each of the datasets included in the analysis. For example, suppose capture probabilities are related to habitat quality, with animals in high quality habitat having smaller home ranges, and hence less probability of encountering traps. The approach advocated here is to build a model of detection probabilities by combining the data from multiple study areas and using the information about habitat quality in the model. For example, ˆ) = β 0 + β1Habitat Quality , logit(p ⎛ p ⎞ ⎟⎟ ]. The result is a model predicting ⎝1 − p ⎠ where logit is the logit transformation [logit(p) = log⎜⎜ capture probability as a function of habitat quality, where the parameters β 0 and β1 are estimated from the data and the habitat quality values provided by the user. Instead of estimating a separate value of p for each of the study areas, and likely encountering problems with too small of sample sizes, the researcher obtains an estimate of p specific to each study area based on habitat quality. Besides incorporating covariates into the model, less parameter-rich models that are still biologically realistic can be fitted to the observed data. A more extensive example is provided in White (2001), where models are combined across day- and night-time trapping occasions, gender and age-class. That example demonstrates the capability of additive models, where additive effects in the model (e.g., an effect representing the difference between day and night capture probabilities) provide differences, yet maintain a parallelism between the estimates across time or other categories. Additive models provide a useful alternative to the full multiplicative model. For example, suppose there are 5 trapping grids, each 156 �trapped for 5 nights. The full multiplicative time-specific model would have 5 × 5 = 25 parameters. In contrast, the additive model would still have 5 time parameters, but with only 4 additional parameters to represent the differences between study areas, resulting in only 9 parameters being estimated from the data. Hence, at the expense of possible bias, much improved precision of the estimates will be obtained. Finally, modern approaches provide much more flexibility in exploring alternative models. With CAPTURE, it was all or none. Only 8 models from the Mtbh set were defined, and these were cast in concrete. Only 7 models of this set had estimators (with only 5 estimators in the original program). However, with Program MARK (White and Burnham 1999), all the likelihood models from CAPTURE can be reproduced, plus many additional possibilities are provided by variations of the original 8 models. Included in MARK are the mixture models of Pledger (2000) for modeling individual heterogeneity, and Huggins (1989, 1991) and Alho (1990) versions of the closed capture estimators that allow individual covariates to be used to model initial and recapture probabilities. Thus, approaches available in MARK provide 3 areas of improvement to handle sparse markrecapture datasets. First, covariates can be incorporated into the analysis, bring additional information. Second, flexible modeling structures can provide biologically reasonable models to combine sparse datasets. Third, more flexibility is provided to construct capture-recapture models of individual datasets. Program DISTANCE 3.5 (Thomas et al. 1998; Buckland et al. 2001), and now updated to DISTANCE 4.1, provides similar capabilities for distance sampling data as does MARK for markencounter data. Data are presented to the program in strata, with stratum-specific estimates of density provided from detection probabilities estimated across strata. Although not as flexible at this time in terms of building complex models that incorporate covariates, these capabilities are forthcoming in newer versions of the program. The essence of the approach advocated here is currently available in DISTANCE – multiple datasets can be combined to estimate the sightability parameter, yet stratumspecific estimates of density are achieved. Model selection methods. Another feature of modern methods is that the estimate from a single model is not accepted as the best estimate available from the data. Burnham and Anderson (2002) describe information-theoretic model selection methods, leading to model averaging, where estimates from multiple models are combined to obtain an estimate that is an improvement over estimates from single models. The traditional approach was to find the “best” model, and use that model to make inferences from the data. However, the process of sorting through the available models carries some baggage – multiple decisions are required to decide which model is most appropriate. As a result, a source of variation in the data analysis process is ignored – model selection uncertainty. Simulations have shown that the estimates and their confidence intervals from the “best” model do not perform as hoped (Burnham et al. 1995). In particular, confidence intervals do not cover the parameter value for the expected 95% with α = 0.05. Rather than accept the poor performance because of ignoring model selection uncertainty from using the “best” model, the model-averaging methodology provided by Burnham and Anderson (2002) incorporates the model-selection uncertainty into the estimates and associated confidence intervals. Further, the approach is more biologically satisfying. For example, who really believes that the “best” model for making inferences from a capture-recapture study is something simple like Mt? Rather, we would all suspect some individual heterogeneity to be present, as in Mh. Yet, with the traditional approach of just making inferences from the “best” model, the individual heterogeneity aspect would be completely ignored if Mt was determined to be the “best” model. With model averaging, we incorporate information from all the models that have weight associated with them, with the information provided by each model proportional to its weight. The result is an estimate that reflects more accurately what we know from the data, and that a single model is inadequate for making inferences from the data. 157 �A key part of model averaging is estimating the weight to be associated with each model. The information-theoretic approach presented by Burnham and Anderson (2002) is based on Akaike’s Information Criterion (AIC). Without going into the mathematics (details are presented in Burnham and Anderson 2001; Burnham and Anderson 2002), the general idea behind AIC model selection is to rank models based on the trade-off between bias versus precision of the estimates (Figure 1). Simple models, i.e., models with small numbers of parameters, produce more precise estimates at the expense of potentially biased estimates. In contrast, complex models, i.e., models with large numbers of parameters, will produce generally unbiased estimates, but at the cost of poor precision. That is, the sampling variance of the parameter estimates from complex models will be large compared to simple model. From the AIC value for each model, a weight is computed for each model. These weights are standardized to sum to 1, so that the weight of a model reflects the likelihood of the model. From these weights, the model-averaged estimate of the parameter across all the models considered is computed. Program MARK includes information-theoretic (i.e., AIC) model selection criteria (White and Burnham 1999) and the capability for model averaging population estimates (White et al. 2001). Although DISTANCE includes AIC model selection, the capability to model average is not presently available. However, the calculations for model averaging are simple, and can be easily performed in a spreadsheet given the estimates, standard errors, and AIC values. So what’s the price for using the approach advocated here? For the user, likely a fairly steep learning curve must be climbed. More statistical and computer expertise is required to conduct the analyses described than with traditional approaches. Although likely an excuse, competent scientists will not let this reason keep them from applying better methodology to more fully interpret their data. Data are hard to come by, and deserve full treatment once acquired. Quadrat sampling example I now present an example of estimating the population size of the Mexican spotted owl in the Upper Gila Mountains Recovery Unit. Twenty-five quadrats 50–75 km2 were sampled for owls with a 4pass removal sampling scheme (Ganey et al. 1999). When an owl was detected through night-time calling, it was located the next day and leg banded to individually identify it. Recaptures were obtained when a marked owl was located during a latter pass. These capture-recapture data from banded owls on the 11 quadrats where owls had been banded and subsequently resighted were used to estimate p, the probability of capture on a given trapping occasion (Huggins 1989). To estimate p, a closed capturerecapture modeling procedure developed by Huggins (1989, 1991) that was implemented in Program MARK (White and Burnham 1999) was used. The goal was to estimate p as precisely as possible because the sampling variances of the p’s contribute to the sampling variances of the estimated N’s. In addition to p, the probability of recapture (c) can also be estimated, adding an additional parameter to be modeled. In standard closed capture-recapture models, maximum likelihood estimation is used to estimate both p and N, simultaneously (Otis et al. 1978), i.e., the resulting estimates from standard closed capture-recapture models represent the joint maximum likelihood estimates. The Huggins models differ from the standard models in that only p and c are modeled with N being estimated as a derived parameter (i.e., N is computed algebraically from p). Thus, our initial efforts centered about modeling the capturerecapture data to obtain parsimonious estimates of p. The key point relevant to this paper is that no one quadrat had adequate data to estimate p and/or c. Data were pooled across quadrats to obtain these estimates of detection probabilities, and then used to generate an estimate of N for each of the quadrats. To estimate p, 26 closed-capture models were run in program MARK. The notation used to describe these models follows Lebreton et al. (1992). In this set of models, the effects on p were modeled by sex, road access to the quadrat, occasion-specificity, and behavioral response to initial capture (i.e., inclusion of the recapture parameter c in the model). A bias-corrected version of Akaike’s Information 158 �Criteria, AICc (Burnham and Anderson 2002) was used to rank models with the best model having the lowest AICc. The best model was p = cT+roadless+sex, which constrained p’s equal to c’s, and had a linear occasion effect (T), an effect of roadless quadrats versus non-roadless quadrats and a sex effect on the p’s. The linear occasion, roadless and sex effects were all negative and different from zero (βT = -0.350, 95% CI = -0.637, -0.063; βroadless = -1.614, 95% CI = -2.742, -0.486; βsex = -0.983, 95% CI = -1.764, -0.203). This model indicated that capture probabilities declined over occasions in a linear fashion, roadless quadrats had lower capture probabilities than roaded quadrats, and that females had lower capture probabilities than males. Rather than using the p’s solely from this model, Akaike weights were estimated for each model (Buckland et al. 1997; Burnham and Anderson 2002) which represented the likelihood of a specific model as the best model to explain this particular data set, relative to the other models examined in our set of models. Akaike weights were then used to derive a weighted mean estimate of capture probabilities (pi) (i.e., the pi were “model averaged”) for each occasion for each sex and within roaded and unroaded quadrats across all models (see Stanley 1998a, 1998b). These weighted estimates of pi had estimated standard errors that included a variance component due to model selection uncertainty, i.e., which model was best for providing an adequate structure on the p’s (Buckland et al. 1997; Burnham and Anderson 2002). Thus, we ended up with 16 estimates of p, one for each of four occasions times two types of quadrats (roaded versus unroaded) and for each sex. Based on these estimates of p, a population estimate for the recovery unit was 2173 with SE 520. Had just the raw counts been used, the estimate would have been 1564 with SE 222. This example illustrates an extreme case where each trapping grid (quadrat) contained so little information about detection probabilities that by individual quadrat, the researcher is left with no choice but to use the MNKA value. However, by combining these sparse data, useful estimates were obtained that corrected for the bias of MNKA. CONCLUSIONS Sparse data need not be an impediment to correcting counts of populations to less biased estimates of population size. Modern methods incorporate information from auxiliary variables, build models from multiple sources of information, and build biologically reasonable models with fewer parameters than older approaches. Thus, past justifications of using counts as indices to population levels because of sparse data are no longer defensible. 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Symposia of the Zoological Society of London 58, 25-57. Nichols, J. D. (1992). Capture-recapture models: using marked animals to study population dynamics. Bioscience 42, 94-102. Nichols, J. D., and Pollock, K. H. (1983). Estimation methodology in contemporary small mammal capture-recapture studies. Journal of Mammalogy 64, 253-260. McKelvey, K. S., and Pearson, D. E. (2001). Population estimation with sparse data: the role of estimators versus indices revisited. Canadian Journal of Zoology 79, 1754-1765. Otis, D. L., Burnham, K. P., White, G. C., and Anderson, D. R. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monographs 62, 1-135. Pledger, S. (2000). Unified maximum likelihood estimates for closed capture-recapture models using mixtures. Biometrics 56, 434-442. Samuel, M. D., Garton, E. O., Schlegel, M. W., and Carson, R. G. (1987). Visibility bias during aerial surveys of elk in northcentral Idaho. Journal of Wildlife Management 51, 622-630. 160 �Slade, N. A., and Blair, S. M. (2000). An empirical test of using counts of individuals captured as indices of population size. Journal of Mammalogy 81, 1035-1045. Stanley, T. R., and Burnham, K. P. (1998a). Estimator selection for closed-population capture-recapture. Journal of Agricultural, Biological, and Environmental Statistics 3, 131-150. Stanley, T. R., and Burnham, K. P. (1998b). Information-theoretic model selection and model averaging for closed-population capture-recapture studies. Biometrical Journal 40, 475-494. Thomas, L., Laake, J. L. , Derry, J. F., Buckland, S. T., Borchers, D. L., Anderson, D. R., Burnham, K. P., Strindberg, S., Hedley, S. L., Burt, M. L., Marques, F. F. C., Pollard, J. H., and Fewster, R. M. (1998). Distance 3.5. Research Unit for Wildlife Population Assessment, University of St. Andrews, United Kingdom. http://www.ruwpa.st-and.ac.uk/distance/. White, G. C. (2001). Statistical models: keys to understanding the natural world. In ‘Modeling in Natural Resource Management.’ (Ed. T. M. Shenk and A. B. Franklin). pp 35-56. (Island Press: Washington, D. C.) White, G. C., Burnham, K. P., and Anderson, D. R. (2001). Advanced features of Program Mark. In ‘Wildlife, land, and people: priorities for the 21st century. Proceedings of the Second International Wildlife Management Congress.’ (Ed. R. Field, R. J. Warren, H. Okarma, and P. R. Sievert). pp 368-377. (The Wildlife Society: Bethesda, Maryland) White, G. C., and Burnham, K. P. (1999). Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement, 120-138. White, G. C., Anderson, D. R., Burnham, K. P., and Otis, D. L. (1982). Capture-recapture and removal methods for sampling closed populations. LA-8787-NERP, Los Alamos National Laboratory, Los Alamos, New Mexico, USA. 235 pp. _________________________ Gary C. White, CSU Professor Variance Bias Squared Prepared by: Few Number of Parameters Many Figure 1. The trade-off between bias2 and variance as a function of the number of parameters (from Burnham and Anderson 2002; 2001). Models with few parameters produce precise estimates that are biased, whereas models with many parameters produce less biased estimates, but imprecise. 161 �162 �Colorado Division of Wildlife Wildlife Research Report July 2003 – June 2004 JOB PROGRESS REPORT State of Colorado Project No. Work Package No. 7210 Task No. : : : : Federal Aid Project: : N/A Cost Center 3430 Mammals Research Research Support / Administrative Services Library Services Period Covered: July 1, 2003 – June 30, 2004 Author: Jacqueline A. Boss Personnel: Jacqueline A. Boss All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT During the Segment, the following were accomplished: 868 Publications acquired by the Research Center Library for the use of Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public. These publications include books, interlibrary loan materials, periodicals, and newsletters. 1,922 Items of information delivered to Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public, resulting from requests and literature searches. 308 Items of information cataloged into the electronic and card catalogues, which including duplicates and additional volumes, expanded the Research Center Library inventory to 23,781 items. 726 Items of information entered into the electronic catalogue for the maintenance of the circulation system of the Research Center Library. 1,706 Items checked-out by Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public indicating satisfaction of library services. 1,430 Items of information delivered that are produced by the Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public. These items include publications (1,430 – From time to time duplicated books donated to our Library are also given to CDOW employees and are included in this number), research articles by CDOW personnel (650), and CDOW federal aid reports (183). 163 �JOB PROGRESS REPORT COLORADO DIV. OF WILDLIFE RESEARCH LIBRARY SERVICES Jacqueline A. Boss SEGMENT OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Div. of Wildlife employees, cooperators, wildlife educators, and the public. SUMMARY OF SERVICES Maintain Electronic and Card Catalogues of all Research Library Holdings 308 is the total number of items cataloged during this period of time. This includes not only new acquisitions, but also older materials from the library collection being entered into the electronic catalog for the first time. Among the new acquisitions are Federal Aid : Job Progress Reports and manuscripts written by Colorado Div. of Wildlife Researchers and other employees. 726 is the total number of items of information added to the electronic circulation system during this period. This includes not only the above mentioned newly cataloged items, but also newly acquired serials, volumes, additional copies, and other items being assigned scanning numbers for the electronic circulation system for the first time. $211,167.94 is the “known value” of the 23,577 items in the Research Center Library collection as of June 30, 2004. The project to determine the value of the library collection began in May 2000. As time permits, the value of books already in the collection is determined, and added to the already “known value.” Each month’s addition of values of older materials, plus the new materials, increases the value of the Library collection. Not included in the “known value” of the Library collection are all of the periodicals, older materials, and government documents, which continue to be a large part of the collection, thus the “known value” of the Library collection continues to grow month by month Some of the Publications Acquired in the Research Center Library Abegglen, J. S. [2004]. Proceedings of the 20th Biennial Pronghorn Workshop : 2002 : Kearney Nebraska. [Chardon, NE : U.S. Forest Service. Nebr. Nat’l Forest]. 177pp. Adams, R. 2003. Bats of the Rocky Mountain west : natural history, ecology, and conservation. Boulder, CO : Univ. Press of Colorado. 289pp. Aiken, R. and G. P. La Rouche. 2003. Net economic values for wildlife-related recreation in 2001 : addendum to the 2001 National Survey of Fishing, Hunting and Wildlife-Associated Recreation. Washington, DC : U.S. Fish & Wildlife Service. Div. of Federal Aid. Report; 2001-3. 24pp. Allan, J. D. 1995. Stream ecology : structure and function of running waters. New York : Chapman & Hall. 1st ed. 388pp. Baird, R. 2003. Fishing Colorado. Guilford, CT : Falcon. A Falcon guide. 204pp. Barlow, C. C. 2000. The ghosts of evolution : nonsensical fruit, missing partners, and other ecological anachronisms. New York : Basic Books. 1st ed., pbk. 291pp. Beaty, B. J. and W. C. Marquardt, eds. 1996. The biology of disease vectors. Niwot, CO : Univ. Press of Colorado. 632pp. Benson, D. E. 1992. Advanced hunter education and shooting sports responsibility. Fort Collins, CO : Colo. State Univ. University Cooperative Extension. Bulletin; 555A. 266pp. 164 �Benson, D. E. and J. Manning. [1991]. Learning objectives for shooting sports instruction : using measurable criteria to evaluate performance. Fort Collins, CO : Colo. State Univ. University Cooperative Extension. Bulletin; 554A. 24pp. Best, A. K. 2003. Production fly typing : a collection of ideas, notions, hints, & variations on the techniques of fly tying Boitani, L. and T. K. Fuller, eds. 2000. Research techniques in animal ecology : controversies and consequences. New York : Columbia Univ. Press. Methods and cases in conservation science. 442pp. Bowyer, R. T., G. M. Blundell, M. Ben-David, S. C. Jewett, T. A. Dean, and L. K. Duffy. 2003. Effects of the Exxon Valdez oil spill on river otters : injury and recovery of a sentinel species. Bethesda, MD : The Wildl. Soc. Wildlife monograph; no. 153. 53pp. Boyce, M. S., B. M. Blanchard, R. R. Knight, and C. Servheen. 2001. Population viability for grizzly bears: a critical review. Yellowstone National Park, WY : International Assoc. for Bear Research & Management. Monograph series; 4. 39pp. Brown, M. S. 2003. Expanding teacher understanding of Wisconsin’s prairie chickens. M. S. Thesis, Univ. of Wisc. – Stevens Point. 174pp. Burnham, K, P. and D. R. Anderson. 2002. Model selection and multimodel inference : a practical information - theoretic approach. New York : Springer. 2nd ed. 488pp. Callenbach, E. 200. Bring back the buffalo! : a sustainable future for America’s Great Plains. Berkeley : Univ. of Calif. Press. 1st paperback printing. 303pp. Caswell, H. 2001. Matrix population models : construction, analysis, and interpretation. Sunderland, MA : Sinauer Associates. 2nd ed. 722pp. Caudill, J. 2003. 2001 national and state economic impacts of wildlife watching: addendum to the 2001 National Survey of Fishing, Hunting and Wildlife-Associated Recreation. Arlington, VA : U.S. Fish & Wildlife Service. Div. of Economics. Report; 2001-2. 16pp. Cockerell, T. D. A. 1927. Zoology of Colorado. Boulder, CO : Univ. of Colo. 262pp. Colorado Agricultural Statistics Service. 2003. Colorado agricultural statistics : 2003. Lakewood, CO : Colo. Ag. Stat. Serv. 146pp. Cypher, B. L. and D. J. Germano, eds. [2004]. Transactions of the Western Section of The Wildlife Society : 2002/2003 – Volume 38/39. Rancho Cordova, CA : Wildlife Society. Western Section. 40pp. Darling, S. R., ed. [1996]. Proceedings : 13th Eastern Black Bear Workshop : Stratton, Vermont : April 28 - May 1, 1996. S.l.: Vermont Fish and Wildlife Dept. 166pp. Davies, P. H., S. F. Brinkman, D. Hansen, R. B. Nehring, and G. Policky. 2002. Arkansas River research study : 2001 : annual progress report. [Fort Collins, CO] : Colo. Div. of Wildlife. 316pp. Dawkins, R. 1989. The selfish gene. New York : Oxford Univ. Press. New ed. 352pp. DeLorme Mapping Company. 2001. Wyoming atlas & gazetteer : detailed topographic maps, … back roads, BLM, state lands, GPS grids. Yarmouth, ME : DeLorme. 3rd ed. 72pp. Demarais, S., R. W. DeYoung, L. J. Lyon, E. S. Williams, S. J. Williamson, and G. J. Wolfe. 2002. Biological and social issues related to confinement of wild ungulates. Bethesda, MD : The Wildlife Society. Technical review; 02-3. 29pp. Deutsch, C. J., J. P. Reid, R. K. Bonde, D. E. Easton, H. I. Kochman, and t. J. O’Shea. 2003. Seasonal movements, migratory behavior, and site fidelity of West Indian manatees along the Atlantic Coast of the United States. Bethesda, MD : The Wildl. Soc. Wildlife monograph; no. 151. 77pp. Devine, R. 1998. Alien invasion : America’s battle with non-native plants and animals. Washington, D. C. : National Geographic Society. 280pp. deVos, Jr., J. C., M. R. Conover, and N. E. Headrick. 2003. Mule deer conservation : issues and management strategies. Logan, UT : Berryman Institute Press. 240pp. Eversole, A. G. [2003]. Proceedings of the fifty-fifth annual conference : Southeastern Association of Fish & Wildlife Agencies: Oct. 13-17, 2001 : Louisville, KY. S.l : Assoc. of Fish & Wildl. Agencies. 5629pp. 165 �Fagerstone, K. A., M. A. Coffey, P. D. Curtis, R. A. Dolbeer, G. J. Killian, L. A. Miller, and L. M. Wilmot. 2002. Wildlife fertility control. Bethesda, MD : The Wildlife Society. Technical review; 02-2. 30pp. Fertig, W. and S. Markow. 2001. Guide to the willows of Shoshone National Forest. Ogden, UT : U.S. Forest Service. Rocky Mountain Research Station. General technical report; RMRS-GTR-83. 79pp. Gillihan, S. W. 2000. Bird conservation on golf courses : a design and management manual. Chelsea, MI : Ann Arbor Press. 335pp. Graham, R. T. [2003]. Hayman fire case study. Fort Collins, CO : U.S. Forest Service. Rocky Mountain Research Station. General technical report RMRS; GTR-114. 396pp. Grosz, T. 2003. No safe refuge : man as predator in the world of wildlife. Boulder, CO : Johnson Books. 266pp. Gutzwiller, K., ed. 2002. Applying landscape ecology in biological conservation. New York : Springer. 518pp. Hanophy, W. and H. Teitelbaum. [2003]. Wild Colorado : crossroads of biodiversity. Denver, CO : Colo. Div. of Wildl. 68pp. Harris, R. B., ed. 2002. Ursus: an official publication of the International Association for Bear Research and Management. Yellowstone National Park, WY : International Assoc. for Bear Research & Management. Vol. 13 (2002). 391pp. Haufler, J. B., R. K. Baydack, H. Campa, III, B. J. Kernohan, C. Miller, L. J. O’Neil, and L. Waits. 2002. Performance measures for ecosystem management and ecological sustainability. Bethesda, MD : The Wildlife Society. Technical review; 02-1. 22pp. Hayes, R. D., R. Farnell, R. M. P. Ward, J. Carey, M. Dehn, G. W. Kuzyk, A. M. Baer, C. L. Gardner, and M. O’Donoghue. 2003. Experimental reduction of wolves in the Yukon : ungulate responses and management implications. Bethesda, MD : The Wildl. Soc. Wildlife monograph; no. 152. 35pp. Henjum, M. G., J. R. Karr, D. L. Bottom, D. A. Perry, J. C. Bednarz, S. G. Wright, S. A. Beckwitt, and E. Beckwitt. 1994. Interim protection for late-successional forests, fisheries, and watersheds : national forests east of the Cascade crest, Oregon and Washington. Bethesda, MD : The Wildlife Society. Technical review; 94-2. 245pp. Hermann, F. J. 1970. Manual of the carices of the Rocky Mountains and Colorado basin. Washington, DC : U.S. Gov. Print. Off. U.S. Dept. of Agriculture. Agriculture handbook; no. 374. 397pp. Honess, R. F. and N. M. Frost. 1942. A Wyoming bighorn sheep study. [Cheyenne, WY : Wyoming Game and Fish Dept. Bulletin; no. 1 127pp. Houston, K. E., w. J. Hartung, and C. J. Hartung. 2001. A field guide for forest indicator plants, sensitive plants, and noxious weeds of the Shoshone National Forest, Wyoming. Ogden, UT : U.S. Forest Service. Rocky Mountain Research Station. General technical report; RMRS-GTR84. 184 leaves Jedrzejewska, B. and W. Jedrzejewski. 1998. Predation in vertebrate communities : the Bailowieza Primeval Forest as a case study. New York : Springer-Verlag. 450pp. Julien, P. Y. 1995. Erosion and sedimentation. New York : Cambridge Univ. Press. 280pp. Knight, R. L. and P. B. Landres. 1998. Stewardship across boundaries. Washington, D.C. : Island Press. 371pp. Koch, D. 2000. The Colorado pass book : a guide to Colorado’s backroad mountain passes. Boulder, CO : Pruett Pub. 3rd ed. 225pp. Krebs, C. J., S. Boutin, and R. Boonstra, eds. 2001. Ecosystem dynamics of the Boreal Forest : the Kluane project. New York : Oxford Univ. Press. 544pp. La Rouche, G. P. 2003. Birding in the United States : a demographic and economic analysis : addendum to the 2001 National Survey of Fishing, Hunting and Wildlife-Associated Recreation. Washington, DC : U.S. Fish & Wildlife Service. Div. of Federal Aid. Report; 2001-1. 20pp. 166 �Loomis, J. B. 2002. Integrated public lands management : principles and applications to national forests, parks, wildlife refuges, and BLM lands. New York : Columbia Univ. Press. 2nd ed. 594pp. Manly, B. F. J., L. L. McDonald, D. L. Thomas, T. L. McDonald, and W. P. Erickson. 2002. Resource selection by animals : statistical design and analysis for field studies. Boston : Kluwer Academic Publishers. 2nd ed. 221pp. McGrath, M. T., S. DeStefano, R. A. Riggs, L. L. Irwin, and G. J. Roloff. 2003. Spatially explicit influences on northern goshawk nesting habitat in the interior Pacific Northwest. Bethesda, MD : The Wildlife Society. Wildlife monographs; no. 154. 63pp. Mech, D. L. and L. Boitani, eds. 2003. Wolves : behavior, ecology, and conservation. Chicago : Univ. of Chicago Press. 448pp. Midwest Association of Fish and Wildlife Agencies. [2003]. Midwest Association of Fish and Wildlife Agencies : 70th Annual Directors Meeting : Proceedings : July 12-15, 2003 : Omaha, Nebraska. S.l : s.n. hosted by Nebraska Game and Parks Commission. 332 leaves Mitchum, D. L. 1995. Parasites of fishes in Wyoming. Cheyenne, WY : Wyo. Game & Fish Dept. 304pp. National Wild Turkey Federation. [2003]. National Wild Turkey Federation : annual report 2003. Edgefield, SC : National Wild Turkey Federation. 40pp. Nelson, T. and R. Powell. 2000. A guide to elk hunting in Colorado. Evergreen, CO : Elk Mountain Guidebooks. 4th edition with 2000 update. var. pagination Noel, T. J. with R. D. Sladek. 2002. Fort Collins & Larimer County : an illustrated history. Carlsbad, CA : Heritage Media Corp. 260pp. Orff, E. P., ed. 1993. Proceedings : 11th Eastern Black Bear Workshop : Waterville Valley, N.H. : April 1 – April 3, 1992. S.l.: New Hampshire Fish and Game Dept. 240pp. Pettingil, O. S., Jr. 1981. A guide to bird finding west of the Mississippi. New York : Oxford Univ. Press. 2nd ed. 783pp. Ploger, B. J., ed. 2003. Exploring animal behavior in laboratory and field : an hypothesis-testing approach to the development, causation, function, and evolution of animal behavior. Boston, MA : Academic Press. 472pp. Posewitz, J. 1999. Inherit the hunt : journey into the heart of American hunting. Guilford, CT : Glove Pequot Press. 121pp. Richardson, P. 2002. Bats. Washington, DC : Smithsonian Institution Press. 112pp. Rosenbauer, T. 2003. The Orvis pocket guide to dry fly fishing : a detailed field guide to casting, strategies, fly selection, and presentation. Guilford, CT : Lyons. Illus. by R. Walinchus. A Chanticleer Press ed. 150pp. Schoen, A. M. 2001. Kindred spirits : how the remarkable bond between humans and animals can change the way we live. New York : Broadway Books. 1st ed., pbk. 280pp. Schuett, G. W., M. Hoggren, M. E. Douglas, and H. W. Greene, eds. 2002. Biology of the vipers. Eagle Mountain, UT : Eagle Mountain Pub. Biology of the Vipers Conference … Marielund, Sweden … was held from 17 – 19 May 2000. 580pp. Schultz, R. A., D. A. Pedrotti, and S. C. Reneau. 1999. Putting sheep on the mountain : the Foundation for North American Wild Sheep : twenty-five years dedicated to wild sheep, 1974 to 1999. Cody, WY : Found. for N. Am. Wild Sheep. 1st ed. 698pp. Sibly, R. M., J. Hone, and T. H. Clutton-Brock, eds. 2003. Wildlife population growth rates. New York : Cambridge Univ. Press. 362pp. Sigler, W. F. 1995. Wildlife law enforcement. Dubuque, IA : Wm. C. Brown. 4th ed. 342pp. Smith, D. W., D. R. Stahler, and D. S. Guernsey. 2003. Yellowstone wolf project : annual report. Yellowstone National Park, WY : U.S. National Park Service. YCR-NR-2003-04. 18pp. Southwick Associates. 2003. The 2001 economic benefits of Watchable wildlife recreation in Colorado. Fernandina Beach, FL : Southwick Assoc., Inc. 21 leaves 167 �Sovada, M. A. and L. Carbyn, eds. 2003. The swift fox : ecology and conservation of swift foxes in a changing world. Regina, Saskatchewan : Univ. of Regina. Canadian plains proceedings; 34. 250pp. Trauger, D. L., B. Czech, J. D. Erickson, P. R. Garrettson, B. J. Kernohan, and C. A. Miller. 2003. The relationship of economic growth to wildlife conservation. Bethesda, MD : The Wildlife Society. Technical review; 03-1. 22pp. Uresk, D. W., K. E. Severson, and J. Javersak. 2003. Detecting swift fox : smoked-plate scent stations versus spotlighting. Fort Collins, CO : U.S. Forest Service, Rocky Mtn. Research Stn. Research paper; RMRS-RP-39. 5pp. Uresk, D. W., K. E. Severson, and J. Javersak. 2003. Vegetative characteristics of swift fox denning and foraging sites in southwestern South Dakota. Fort Collins, CO : U.S. Forest Service, Rocky Mtn. Research Stn. Research paper; RMRS-RP-38. 4pp. Vaughan, M. R., T. K. Fuller, and R. B. Harris, eds. 2001. Ursus: an official publication of the International Association for Bear Research and Management. Yellowstone National Park, WY : International Assoc. for Bear Research & Management. Vol. 12 (2001). 246pp. Walker, D. N. and W. J. Adrian. 2003. Wildlife forensic field manual. [Lincoln, NE] : Assoc. of Midwest Fish & Game Law Enforcement Officers. 3rd ed. 254 leaves Walsh, D. P. 2002. Population estimation techniques for greater sage-grouse. M.S. Thesis, Fort Collins, CO : Colo. State Univ. 139pp. Waters, C. V., ed. [2001]. Proceedings : 16th Eastern Black Bear Workshop : March 25-28, 2001 : Clemson, SC. [S.l.: Georgia Dept. of Natural Resources. Wildlife Resources Div. & South Carolina Dept. of Natural Resources] 129pp. Videos Acquired in the Research Center Library U.S. Fish and Wildlife Service. 2003. Status of waterfowl 2003 : 2003 report on North America’s waterfowl populations and habitat conditions. S.l. : Stefan Dobert Productions, Inc. 25:30 min. Theses, Documents and Books Obtained on Interlibrary Loan Literature Searches and Information Delivered Abart, E. M., N. L. Nelson, S. M. Nelson, R. A. Roline, and J. Yahnke. 1996. Improvements to the upper Arkansas River attributable to operation of the Leadville Mine Drainage Tunnel treatment plant. Denver, CO : U.S. Bureau of Reclamation. Technical Service Center. R-96-06. 46pp. Abart, E. M., R. J. Eisenhauer, S. Hunt, H. T. Jong, F. B. Leitz, S. M. Nelson, and R. A. Roline. 1995. Leadville Mine Drainage Tunnel effluent effects on the Arkansas River, 1965-92. Denver, CO : U.S. Bureau of Reclamation. Technical Service Center. R-95-10. 60pp. Armour, M. A. 1991. Hazardous laboratory chemical disposal guide. Boca Raton : CRC Press. 464pp. Baker, M. B., Jr., P. F. Ffolliott, L.F. DeBano, and D. G. Neary. eds., 2004. Riparian areas of the southwestern United States : hydrology, ecology, and management. New York : Lewis Publishers. 408pp. Bennett, R. A., ed. 2000. Soft-tissue surgery. Veterinary clinics of North America : exotic animal practice; 3(3):563-798 Black, M. and H. W. Pritchard, eds. 2002. Desiccation and survival in plants : drying without dying. New York : CABI Publishing. 412pp. Bowyer, R. T. 1985. Correlates in group living of southern mule deer. Ph.D. Dissertation, Ann Arbor, MI, Univ. of Michigan. 89pp. Brobst, D. A. and W. P. Pratt, eds. 1973. United States mineral resources. Washington, DC : U.S. Geological Survey. Geological survey professional paper; no. 820. 722pp. 168 �Burgess, L. M. 2003. Impacts of mowing, burning, and climate on germination and seedling recruitment of Colorado butterfly plant (Gaura neomexicana ssp. Coloradensis) M.S. Thesis, Laramie, WY, Univ. of Wyoming. 68pp. Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation. Sunderland, Mass. : Sinauer Assoc. 2nd ed. 722pp. Committee on Methods for Toxicity Tests with Aquatic Organisms. 1975. Methods for acute toxicity tests with fish, macroinvertebrates, and amphibians. Corvallis, OR : U.S. Environmental Protection Agency. 61pp. Crispens, C. G., Jr. 1955. An evaluation of the adoption method of ring-necked pheasant propagation using prolactin to induce broodiness M.S. Thesis, Columbus, OH, Ohio State Univ. 49pp. Dash, R. G. and R. F. Ortiz. 1996. Water-quality data for the Arkansas River Basin, southeastern Colorado, 1990-93. Denver, CO : U.S. Geological Survey. Open-file report; 95-464 Fowler, M. E. and R. E. Miller, eds. 1999. Zoo and wild animal medicine. Philadelphia : W.B. Saunders. 4th ed. 747pp. Fromm, P. O. 1970. Toxic action of water soluble pollutants on freshwater fish. Washington, D.C. : Environmental Protection Agency. Water Quality Office. Grant No. 18050 DST. 56pp. Fronefield, S. A., ed. 2000. Therapeutics. Veterinary clinics of North America : exotic animal practice; 3(1):1-370 Hammer, D. A., ed. 1989. Constructed wetlands for wastewater treatment : municipal, industrial, and agricultural. Chelsea, MI : Lewis Publisher, Inc. Proceedings from the First International Conference on Constructed Wetlands for Wastewater Treatment held in Chattanooga, Tennessee on June 13-17, 1988. 831pp. Harrahy, E. A. 2000. Ecotoxicological and genetic effects of a mixture of heavy metals on selected aquatic macroinvertebrates. Ph.D. Dissertation, Fort Collins, CO, Colorado State Univ. 196pp. Hart, C. M., O. S. Lee, and J. B. Low. 1950. The sharp-tailed grouse in Utah : its life history, status, and management. [Salt Lake City, UT] :Utah State Dept. of Fish & Game. Publication; no. 3. 79pp. Honess, R. F. and G. Post. 1968. History of an epizootic in sage grouse. Laramie, WY : Wyoming Agricultural Experiment Station. Science monograph; no. 14, 33pp. Hull, A. C., Jr., C. W. Doran, C. H. Wasser, and D. F. Hervey. 1950. Reseeding sagebrush lands of western Colorado. Fort Collins, CO : Colorado A & M College. Colorado Agricultural Experiment Station. Bulletin; 413-A. 23pp. Jenkins, J. R., ed. 1999. Husbandry and nutrition. Veterinary clinics of North America : exotic animal practice; 2(1):1-246 Lakin, H. W. and H. G. Byers. 1948. Selenium occurrence in certain soils in the United States, with a discussion of related topics : seventh report. Washington, DC : U.S. Dept. of Ag. Technical bulletin; no. 950. 36pp. Lorbiecki, M. 1996. Aldo Leopold : a fierce green fire. Helena, MT : Falcon Publishing Co. 212pp. Loye, J. E. and M. Zuk, eds. 1991. Bird-parasite interactions : ecology, evolution, and behaviour. New York : Oxford Univ. Press. Oxford ornithology series; 2. 406pp. MacArthur, R. H. 1972. Geographical ecology : patterns in the distribution of species. New York : Harper & Row Pub. 269pp. Mander, U. and P. Jenssen, eds. 2003. Constructed wetlands for wastewater treatment in cold climates. Boston : WIT Press. 325pp. Mealor, B. A. 2003. Intraspecific variation in four native grasses exposed to long-term invasions of Russian knapweed (Centaurea repens) and hoary cress (Cardaria draba). M.S. Thesis, Laramie, WY, Univ. of Wyoming. 56pp. Moshiri, G. A., ed. 1993. Constructed wetlands for water quality improvement. Boca Raton : Lewis Publishers. 632pp. National Research Council (U.S.). Committee on Management of Wolf and Bear Populations in Alaska. 1997. Wolves, bears, and their prey in Alaska : biological and social challenges in wildlife management. 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Dean, S. E. Campana, eds. 1995. Recent developments in fish otolith research. Columbia, SC : Univ. of South Carolina Press. International Symposium on Fish Otoliths: Research and Application (1st : 1993 : Hilton Head, S.C.) The Belle W. Baruch Library in Marine Science; no. 19. 735pp. Spraker, T. R. 1979. The pathogenesis of pulmonary protostrongylosis in bighorn lambs. Ph.D. Dissertation, Fort Collins, CO, Colo. State Univ. 233pp. Stevenson, D. K. and S. E. Campana, eds. 1992. Otolith microstructure examination and analysis. Ottawa, Ont. : Canada. Dept. of Fisheries & Oceans. Canadian special publication of fisheries and aquatic sciences; 117. 126pp. Tisdale, E. W. and M. Hironaka. 1981. The sagebrush-grass region : a review of the ecological literature. Moscow, ID : Univ. of Idaho. College of Forestry, Wildlife and Range Sciences. Bulletin; no. 33. 31pp. U.S. Environmental Protection Agency. Office of Water Enforcement and Permits. Office of Water Regulations and Standards. 1991. 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Human Dimensions of Wildlife 8(3):231-233 171 �Vieira, M. E. P., M. M. Conner, G. C. White, and D. J. Freddy. 2003. Effects of archery hunter numbers and opening dates on elk movement. Journal of Wildlife Management 67(4):717-728 Williams, E. S. and M. W. Miller. Prions in the wild : CWD in deer and elk. Microbiology Today 30(4):172-173 Prepared by ___________________________ Jacqueline A. Boss, Librarian 172 � https://cpw.cvlcollections.org/files/original/5eefc9df5189c8e627f7376f3fe42dcd.pdf 95970f2678c781b5f9445ee9060291ca PDF Text Text MAMMALS - JULY 2005 ��WILDLIFE RESEARCH REPORTS JULY 2004 – JUNE 2005 MAMMALS PROGRAM COLORADO DIVISION OF WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author. �STATE OF COLORADO Bill Owens, Governor DEPARTMENT OF NATURAL RESOURCES Russell George, Executive Director WILDLIFE COMMISSION Jeffrey Crawford, Chair …………………………………………………………………….…..… Denver Tom Burke, Vice Chair ………………………………….…………...………….…........…Grand Junction Ken Torres, Secretary ……………………………………...…………….……………..……….... Weston Robert Bray………………………………………………….......................................................…Redvale Rick Enstrom………………………………………………………………….………….……...Lakewood Philip James …………………………………………………………………..….………….…Fort Collins Claire M. O’Neal………………………………………………..…………….………..…………..Holyoke Richard Ray ………………………………………………………………………………...Pagosa Springs Robert T. Shoemaker…………………………………………………………….………..…….Canon City Don Ament, Dept. of Ag, Ex-officio…………………………………………………….…….....Lakewood Russell George, Executive Director, Ex-officio……………………………………………..………Denver DIRECTOR’S STAFF Bruce McCloskey, Director Mark Konishi, Deputy Director-Education and Public Affairs Steve Cassin, Chief Financial Officer Jeff Ver Steeg, Assistant Director-Wildlife Programs John Bredehoft, Assistant Director-Field Operations Marilyn Salazar, Assistant Director-Support Services MAMMALS RESEARCH STAFF David Freddy, Mammals Research Leader Dan Baker, Wildlife Researcher Eric Bergman, Wildlife Researcher Chad Bishop, Wildlife Researcher Ken Logan, Wildlife Researcher Tanya Shenk, Wildlife Researcher Jackie Boss, Librarian Margie Michaels, Program Assistant ii �Colorado Division of Wildlife July 2004 – June 2005 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS LYNX CONSERVATION WP 0670 POST-RELEASE MONITORING OF LYNX REINTRODUCED TO COLORADO by T. Shenk………………………………………………………………………….…….1 DEER CONSERVATION WP 3001 PILOT EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON MULE DEER FAWN OVER-WINTER SURVIVAL by E. Bergman………..……23 WP 3001 EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATE by C. Bishop……………………...37 WP 3001 MULTISPECIES INVESTIGATIONS CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSIS by G. White………………………………………67 ELK CONSERVATION WP 3002 EVALUATION OF GnRH VACCINE AS LONG-TERM CONTRACEPTIVE AGENT IN FEMALE ELK: EFFECT ON REPRODUCTION AND BEHAVIOR by D. Baker…..……………………………….………………………………………….77 PREDATORY MAMMALS CONSERVATION WP 3003 PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO by K. Logan…………………………105 SUPPORT SERVICES WP 7210 LIBRARY SERVICES by J. Boss…………………..…………………………………127 iii �iv �Colorado Division of Wildlife July 2004 – June 2005 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Federal Aid Project: Colorado 3430 0670 1 : : : : N/A : Division of Wildlife Mammals Research Lynx Conservation Post-Release Monitoring of Lynx Reintroduced to Colorado Period Covered: July 1, 2004- June 30, 2005 Author: T. M. Shenk Personnel: L. Baeten, B. Diamond, R. Dickman, S. Dieterich, D. Freddy, L. Gepfert, R. Kahn, A. Keith, G. Merrill, G. Miller, J. Stewart, C. Wagner, S. Wait, S. Waters, L. Wolfe, D. Younkin All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to establish a viable population of lynx (Lynx canadensis) in Colorado, the Colorado Division of Wildlife (CDOW) initiated a reintroduction effort in 1997 with the first lynx released in February 1999. A total of 166 lynx were released from 1999-2004 and an augmentation of 38 additional animals (20 males:18 females) was completed in 2005 resulting in a total of 204 lynx reintroduced to southwestern Colorado. Each lynx was released with dual satellite and VHF radio transmitters to allow intensive monitoring of animals after release. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns. Most lynx remain in the southwestern quarter of Colorado. Through documentation of lynx mortalities and causes of death, human-caused mortality factors, such as gunshot and vehicle collision, are currently the highest source of mortality for reintroduced lynx. Reproduction was first documented during the 2003 reproduction season with 6 dens and 16 kittens found. A second successful breeding season was documented in 2004 with 30 kittens found at 11 dens and an addition 9 kittens found after denning season. In 2005, 46 kittens were found at 16 dens with an additional den located but not visited for safety reasons. Data collected from snowtracking indicate the primary winter prey species are snowshoe hare (Lepus americanus) and red squirrel (Tamiasciurus hudsonicus), with other mammals and birds forming a minor part of the winter diet. Sitescale habitat data collected from snow-tracking efforts indicate Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) are the most common forest stands used by lynx in southwestern Colorado. Results to date have demonstrated that CDOW has developed release protocols that ensure high initial post-release survival, and on an individual level, lynx have demonstrated an ability to survive long-term in areas of Colorado. Reintroduced lynx have also exhibited site fidelity, engaged in breeding behavior and produced kittens. What is yet to be demonstrated is whether conditions in Colorado can support the recruitment necessary to offset annual mortality for a population to remain viable for several generations of lynx. Monitoring of reintroduced lynx will continue in an effort to document such viability. 1 �WILDLIFE RESEARCH REPORT POST RELEASE MONITORING OF LYNX (LYNX CANADENSIS) REINTRODUCED TO COLORADO TANYA M. SHENK P. N. OBJECTIVE The initial post-release monitoring of lynx reintroduced into Colorado will emphasize 5 primary objectives: 1. Assess and modify release protocols to ensure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival of lynx reintroduced to Colorado. 5. Estimate reproduction of lynx reintroduced to Colorado. Three additional objectives will be emphasized after lynx display site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of lynx conservation strategies in the southern Rocky Mountains. SEGMENT OBJECTIVES 1. Release additional adult lynx captured in Canada in southwestern Colorado during spring 2005. 2. Complete winter 2004-05 field data collection on lynx habitat use, hunting behavior, diet, mortalities, and movement patterns. 3. Complete winter 2004-05 lynx trapping field season to collar Colorado born lynx and re-collar adult lynx. 4. Complete spring 2005 field data on lynx reproduction. 5. Summarize and analyze data and publish information as Progress Reports, peer-reviewed manuscripts for appropriate scientific journals, or CDOW technical publications. INTRODUCTION The Canada lynx occurs throughout the boreal forests of northern North America. Colorado represents the southern-most historical distribution of lynx, where the species occupied the higher elevation, montane forests in the state. Little was known about the population dynamics or habitat use of this species in their southern distribution. Lynx were extirpated or reduced to a few animals in the state by the late 1970’s due, most likely, to predator control efforts such as poisoning and trapping. Given the isolation of Colorado to the nearest northern populations, the CDOW considered reintroduction as the only option to attempt to reestablish the species in the state. A reintroduction effort was begun in 1997, with the first lynx released in Colorado in 1999. To date, 204 wild-caught lynx from Alaska and Canada have been released in southwestern Colorado. The goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of 2 �lynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing if the reintroduction effort is progressing towards success. There are 7 critical criteria for achieving a viable population: 1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, 2) long-term survival of lynx in Colorado, 3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, 4) reintroduced lynx must breed, 5) breeding must lead to reproduction of surviving kittens 6) lynx born in Colorado must reach breeding age and reproduce successfully, and 7) recruitment must be equal to or greater than mortality. The post-release monitoring program for the reintroduced lynx has 2 primary goals. The first goal is to determine how many lynx remain in Colorado and their locations relative to each other. Given this information and knowing the sex of each individual, we can assess whether these lynx can form a breeding core from which a viable population might be established. From these data we can also describe general movement patterns and habitat use. The second primary goal of the monitoring program is to estimate survival of the reintroduced lynx and, where possible, determine causes of mortality for reintroduced lynx. Such information will help in assessing and modifying release protocols and management of lynx once they have been released to ensure their highest probability of survival. Additional goals of the post-release monitoring program for lynx reintroduced to the southern Rocky Mountains included refining descriptions of habitat use and movement patterns and describing successful hunting habitat once lynx established home ranges that encompassed their preferred habitat. Specific objectives for the site-scale habitat data collection include: 1) describe and quantify site-scale habitat use by lynx reintroduced to Colorado, 2) compare site-scale habitat use among types of sites (e.g., kills vs. long-duration beds), and 3) compare habitat features at successful and unsuccessful snowshoe hare chases. The program will also investigate the ecology of snowshoe hare in Colorado. Documenting reproduction is critical to the success of the program and lynx are monitored intensively to document breeding, births, survival and recruitment of lynx born in Colorado. Site-scale habitat descriptions of den sites are also collected and compared to other sites used by lynx. Lynx is listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.)(U. S. Fish and Wildlife Service 2000). Colorado is included in the federal listing as lynx habitat. Thus, an additional objective of the post-release monitoring program is to develop conservation strategies relevant to lynx in Colorado. To develop these conservation strategies, information specific to the ecology of the lynx in its southern Rocky Mountain range, such as habitat use, movement patterns, mortality factors, survival, and reproduction in Colorado is needed. STUDY AREA Southwestern Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce-subalpine fir is the most widely distributed coniferous forest type at elevations most typically used by lynx. The Core Research Area is defined as areas bounded by the New Mexico state line to the south, Taylor Mesa to the west and Monarch Pass on the north and east and > 2900 meters in elevation. METHODS REINTRODUCTION Effort All 2005 lynx releases were conducted under the protocols found to maximize survival (see Shenk 2001). Estimated age, sex and body condition were ascertained and recorded for each lynx prior to 3 �release (see Wild 1999). Specific release sites were those used in earlier years of the project and were selected based on land ownership and accessibility during times of release (Byrne 1998). Lynx were transported from the Frisco Creek Wildlife Rehabilitation Center, where they were held from their time of arrival in Colorado, to their release site in individual cages. Release site location was recorded in Universal Transverse Mercator (UTM) coordinates and identification of all lynx released at the same location, on the same day, was recorded. Behavior of the lynx on release and movement away from the release site were documented. Distribution and Movement Patterns All lynx released in 1999 were fitted with TelonicsTM radio-collars. All lynx released since 1999, with the exception of 5 males released in spring 2000, were fitted with SirtrackTM dual satellite/VHF radio-collars. These collars have a mortality indicator switch that operated on both the satellite and VHF mode. The satellite component of each collar was programmed to be active for 12 hours per week. The 12-hour active periods for individual collars were staggered throughout the week. Signals from the collars allowed for locations of the animals to be made via Argos, NASA, and NOAA satellites. The location information was processed by ServiceArgos and distributed to the CDOW through e-mail messages. To determine general movement patterns of reintroduced lynx, regular locations of released lynx were collected through a combination of aerial, satellite and ground radio-tracking. Locations were recorded in UTM coordinates and general habitat descriptions for each ground and aerial location were recorded. Survival and Mortality Factors When a mortality signal (75 beats per minute [bpm] vs. 50 bpm for the Telonics™ VHF transmitters, 20 bpm vs. 40 bpm for the Sirtrack™ VHF transmitters, 0 activity for Sirtrack™ PTT) was heard during either satellite, aerial or ground surveys, the location (UTM coordinates) was recorded. Ground crews then located and retrieved the carcass as soon as possible. The immediate area was searched for evidence of other predators and the carcass photographed in place before removal. Additionally, the mortality site was described and habitat associations and exact location were recorded. Any scat found near the dead lynx that appeared to be from the lynx was collected. All carcasses were transported to the Colorado State University Veterinary Teaching Hospital (CSUVTH) for a post mortem exam to 1) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, and 3) archive samples for future reference (research or forensic). The gross necropsy and histology were performed by, or under the lead and direct supervision of a board certified veterinary pathologist. At least one research personnel from the CDOW involved with the lynx program was also present. The protocol followed standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing (see Shenk 1999 for details). Some additional data/samples were routinely collected for research, forensics, and archiving. Other data/samples were collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). From 1999–2004 the CDOW retained all samples and carcass remains with the exception of tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, and other diagnostic samples. Since 2005 carcasses are disposed of at the CSUVTH with the exception of the lower canine, fecal samples, stomach content samples and tissue or bone marrow samples to be delivered by CDOW to the Center for Disease control for plague testing. The lower canine is sent to Matson Labs (Missoula, Montana) for aging and the fecal and stomach content samples are evaluated for diet. 4 �Reproduction Females were monitored for proximity to males during each breeding season. We defined a possible mating pair as any male and female documented within at least 1 km of each other in breeding season through either flight data or snow-tracking data. Females were then monitored for site fidelity to a given area during each denning period of May and June. Each female that exhibited stationary movement patterns in May or June were closely monitored to locate possible dens. Dens were found when field crews walked in on females that exhibited virtually no movement for at least 10 days from both aerial and ground telemetry. Kittens found at den sites were weighed, sexed and photographed. Each kitten was uniquely marked by inserting a sterile passive integrated transponder (PIT, Biomark, Inc., Boise, Idaho, USA) tag subcutaneously between the shoulder blades. Time spent at the den was minimized to ensure the least amount of disturbance to the female and the kittens. Weight, PIT-tag number, sex and any distinguishing characteristics of each kitten was also recorded. Beginning in 2005, blood and saliva samples were collected for genetic identification. During the den site visits, den site location was recorded as UTM coordinates. General vegetation characteristics, elevation, weather, field personnel, time at the den, and behavioral responses of the kittens and female were also recorded. Once the females moved the kittens from the natal den area, den sites were visited again and site-specific habitat data were collected (see Habitat Use section below). Recaptures Recaptures were attempted for either lynx that were in poor body condition or lynx that needed to have their radio-collars replaced due to failed or failing batteries or to radio-collar kittens born in Colorado once they reached at least 10-months of age when they were nearly adult size. Methods of recapture included 1) trapping using a Tomahawk™ live trap baited with a rabbit and visual and scent lures, 2) calling in and darting lynx using a Dan-Inject CO2 rifle, 3) custom box-traps modified from those designed by other lynx researchers (Kolbe et al. 2003) and 4) hounds trained to pursue felids were also used to tree lynx and then the lynx was darted while treed. Lynx were immobilized either with Telazol (3 mg/kg; modified from Poole et al. 1993 as recommended by M. Wild, DVM) or medetomidine (0.09mg/kg) and ketamine (3 mg/kg; as recommended by L. Wolfe, DVM)) administered intramuscularly (IM) with either an extendible pole-syringe or a pressurized syringe-dart fired from a Dan-Inject air rifle. Immobilized lynx were monitored continuously for decreased respiration or hypothermia. If a lynx exhibited decreased respiration 2mg/kg of Dopram was administered under the tongue; if respiration was severely decreased, the animal was ventilated with a resuscitation bag. If medetomidine/ketamine were the immobilization drugs, the antagonist Atipamezole hydrochloride (Antisedan) was administered. Hypothermic (body temperature < 95o F) animals were warmed with hand warmers and blankets. While immobilized, lynx were fitted with replacement SirtrackTM VHF/satellite collar and blood and hair samples were collected. Once an animal was processed, recovery was expedited by injecting the equivalent amount of the antagonist Antisedan IM as the amount of medetomidine given, if medetomodine/ketemine was used for immobilization. Lynx were then monitored while confined in the box-trap until they were sufficiently recovered to move safely on their own. No antagonist is available for Telezol so lynx anesthetized with this drug were monitored until the animal recovered on its own in the box-trap and then released. If captured and in poor body condition lynx were anesthetized with Telezol (2 mg/kg) and returned to the Frisco Creek Wildlife Rehabilitation Center for treatment. HABITAT USE Gross habitat use was documented by recording canopy vegetation at aerial locations. More refined descriptions of habitat use by reintroduced lynx were obtained through following lynx tracks in 5 �the snow (i.e., snow-tracking) and site-scale habitat data collection conducted at sites found through this method to be used by lynx. Snow-tracking Locations from aerial- and satellite-tracking were used to help ground-trackers locate lynx tracks in snow. Snowmobiles, where permitted, were used to gain the closest possible access to the lynx tracks without disturbing the animal. From that point, the tracking team used snowshoes to access tracks. Once tracks were found, the ground crew back- or forward-tracked the animal if it was far enough away not to be disturbed. Back-tracking generally avoided the possibility of disturbing the lynx by moving away from the animal rather than towards the animal. However, monitoring of the lynx through radio-telemetry was used to assure that the ground crew was staying a sufficient distance away from the lynx in the event the lynx might double back on its tracks. Radio-telemetry was also used in forward-tracking to make sure the team did not disturb the animal. If it appeared the lynx began to move in response to the observers, the observers stopped following the tracks. If the lynx began to move and the movement did not appear to be a response to the observers, the ground crew continued following the track. An attempt was made in Season 1 (February-May 1999) and Season 2 (December 1999-April 2000) to snow-track each lynx. In Season 3 (December 2000-April 2001), we attempted to snow-track all lynx within the Core Research Area. In tracking Season 4 (December 2001-April 2002), Season 5 (December 2002-April 2003), Season 6 (December 2003-April 2004) and Season 7 (December 2004April 2005) we attempted to track all accessible lynx in the Core Research Area and some lynx north of the Core Research Area. Ground crews were instructed to track lynx only where it was safe to travel. Restrictions to safe travel included avalanche danger and extremely rugged terrain. Ground crews worked in pairs and were fully equipped for winter back-country survival. Data Collection For each day of tracking the date, lynx being tracked, slope, aspect, UTM coordinates, elevation, general habitat description, and summary of the days tracking were recorded. Aspect was defined as the direction of 'downhill' or 'fall line' on a slope. This is the direction along the ground in a dihedral angle between the horizontal and the plane of the ground surface. Units were compass degrees. Slope was defined as the dihedral angle between the horizontal and the plane of the ground surface (e.g., 45"). Once a track was located there were 2 types of 'sites' that were encountered. Site I areas needed documentation but either did not reflect areas lynx selected for specific habitat features, or were sites that occurred too frequently to measure each in detail. These sites included the start and end of the track being followed, the location of scat, and short-duration beds defined as being small in size (approximating an area a lynx would crouch), and with little ice formed in the bed indicating little time spent there. Site II areas included areas that might reflect specific habitat features lynx selected for and included locations where the following were found: kills, start of chases, territory marks (e.g., spray sites, buried scat, scat placed on prominent locations), long-duration beds (encompasses an area where a lynx would have lain for an extended period, iced bottom), and road crossing (both sides of road). In addition, habitat plots were conducted along lynx travel routes if no other sites sampled in last hour. At each of the 2 types of sites the date, lynx tracked, slope, aspect, forest structure class, UTM coordinates, and elevation were recorded. Forest structure classes included grass/forb, shrub/seedling, sapling/pole, mature, and old growth as defined in Table 1. For Site I areas, the only additional data that was collected was identification of what the site was used for (e.g., short-duration bed), and a brief description of the site. Habitat plots (see below) were conducted at Site II areas. 6 �Description of the Habitat Plot The habitat plot consisted of a 12 m x 12 m square defined by a series of 25 points placed in 5 rows of 5 with the center point being on the object that defined the site (e.g., a kill)(Figure 1). Each point was 3 m apart. The 12 m x 12 m sampling square exceeded the minimum requirement of 0.01 ha. recommended by Curtis (1959) for sampling trees. Measurements taken at each of the 25 points included: 1. Snow depth - measured vertically by an avalanche probe marked in cm. 2. Understory - measured from top of snow to 150 cm above snow in a column of 3-cm radius around the avalanche probe. Because understory measurements were influenced by vegetation outside the perimeter of the 25 sampling points (12 m x 12 m) the area used for estimating undersory cover was 15 m by 15 m. At each point, crews recorded all shrubs, trees and coarse woody debris (CWD) that fell within this column and was visible above the snow. Crews also recorded number of branches of each species that fell within the column at 3 different height categories (0-0.5 m, 0.51-1.0 m, 1.01-1.5 m). 3. Overstory: measured at 150 cm above snow with a sighting tube. The tube was made of PVC pipe, with a curved viewing end and a crosshair made of wire on the opposite end. The sighting tube was attached to the avalanche probe used to measure snow depth. Species that hit the crosshair were recorded at each of the 25 points in the vegetation plot. Ganey and Block (1994) found this method of measuring canopy cover (with 20 sample points per plot; Laymon 1988) provided greater precision among observers. 4. Species composition: all the different species of tree or shrub that hit the crosshair of the sighting tube at each of the 25 points were recorded. 5. Tree composition of the vegetation plot was recorded by species and diameter at breast height (DBH). Snow depth was used in conjunction with this recorded DBH to estimate true DBH. Within the 12 m x 12 m square all conifers and deciduous trees were recorded by DBH size class (A = 0-6 in, B = 6.1-12 in, C = 12.1 -18 in, D = 18.1-24 in, E = > 24 in). Area for the tree composition analysis was 12 m x 12 m. Understory was estimated as: 1) percent occurrence within the vegetation plot (number of points with understory/total number of points surveyed) and 2) mean percent occurrence and variance by species and height category over the total points sampled within the vegetation plot. Overstory was estimated as percent occurrence over the vegetation plot (number of points with overstory/total number of points surveyed). DIET AND HUNTING BEHAVIOR Winter diet of reintroduced lynx was estimated by documenting successful kills through snowtracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. Scat samples were collected wherever found and labeled with location and individual lynx identification. Only part of the scat was collected (approximately 75%); the remainder was left in place in the event that the scat was being used by the animal as a territory mark. Site-scale habitat data collected for successful and unsuccessful snowshoe hare kills were compared. RESULTS REINTRODUCTION Effort From 1999 through 2004 166 lynx were reintroduced into southwestern Colorado. An additional 37 lynx were released in April 2005 (17 females and 20 males), one female was released in June 2005. This brings the total number of lynx released in Colorado to 204 (Table 2). These lynx released in 2005 were captured in Quebec, British Columbia and Manitoba. All lynx were released in the Core Research 7 �Area of southwestern Colorado at or near previously used release sites in southwestern Colorado. Lynx were released with dual VHF/satellite radio collars so they can be monitored for movement and mortality. The CDOW plans to release up to 15 lynx annually from 2006-2008. Distribution and Movement Patterns A total of 7421 aerial VHF locations for all 204 reintroduced lynx have been collected to date. An additional 14,788 satellite locations have been collected. Most lynx released remained in the southwestern quarter of Colorado. The majority of surviving lynx from the entire reintroduction effort continue to use areas from New Mexico north to Gunnison, west as far as Taylor Mesa and east to Monarch Pass. Most movements away from the Core Research Area were to the north. Numerous travel corridors have been used repeatedly by more than one lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-SilvertonLizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast through the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. Such movement patterns have also been documented by native lynx in Wyoming and Montana (Squires and Laurion 1999). Survival and Mortality Factors Of the total 204 adult lynx released from 1999-2005 there are 66 known mortalities. Of these 66 mortalities, 26 are from the 1999 releases, 24 are from the 2000 releases, 5 are from the 2003 releases, 8 are from the 2004 releases, and 3 are from the 2005 releases. Causes of death are listed in Table 3. Starvation was a significant cause of mortality in the first year of releases only. Mortalities occurred throughout the areas through which lynx moved. As of June 30, 2005, CDOW was actively tracking 110 of the 138 lynx still possibly alive. There are 29 lynx that we have not heard signals on since at least June 30, 2004 and these animals are classified as ‘missing’ (Table 4). One of these missing lynx is a mortality of unknown identity, thus only 28 are truly missing. Possible reasons for not locating these missing lynx include 1) long distance dispersal, beyond the areas currently being searched, 2) radio failure, or 3) destruction of the radio (e.g., run over by car). CDOW continues to search for all missing lynx during both aerial and ground searches. Two of the missing lynx released in 2000 are thought to have slipped their collars. Reproduction 2003.-- Nine pairs of lynx were documented during the 2003 breeding season (March and April). In May and June, 6 dens and a total of 16 kittens were found in the lynx Core Research Area in southwestern Colorado (Table 5). At all dens the females appeared in excellent condition, as did the kittens. The kittens weighed from 270-500 grams. Lynx kittens weigh approximately 200 grams at birth and do not open their eyes until they are 10-17 days old. The dens were scattered throughout the Core Research Area, with no dens found outside the core area. All the dens were in Engelmann spruce/subalpine fir forests in areas of extensive downfall. Elevations ranged from 3240-3557 m. Field crews weighed, photographed, PIT-tagged the kittens and . took hair samples from the kittens for genetic work in an attempt to confirm paternity. Kittens were processed as quickly as possible (11-32 minutes) to minimize the time the kittens were without their mother. While working with the kittens the females remained nearby, often making themselves visible to the field crews. The females generally continued a low growling vocalization the entire time personnel were at the den. In all cases, the female returned to the den site once field crews left the area. 8 �Four of the 6 females that we know had kittens in summer 2003 were still with kittens at the end of April 2004. Two of those females still had 2 kittens with them at that time. Visual observations in February 2004 of one female with 2 kittens indicated all 3 were in good body condition. The mortality of female YK00F16 and her 1 kitten in October 2003 from plague was not due to poor habitat or prey conditions, and thus we might assume she would have raised the 1 kitten to this stage as well. Three probable kitten deaths from female YK00F19 were from 1 litter that most likely failed very early. Through snow-tracking in winter 2003-04 an unknown female (no radio frequency heard in the area of the tracks) we also documented 1-2 additional kittens born spring 2003 and still alive in winter 2004. Of the 16 kittens we found in summer 2003, we documented the following by April 2004: 6 confirmed alive, 7 confirmed dead, and 3 some evidence dead. Although we tried, we were not able to capture any of the 6 surviving kittens to fit them with radio-collars. 2004.-- In Spring 2004, 26 females from the releases in 1999, 2000 and 2003 had active radiocollars. Of these, we documented 18 possible mating pairs of lynx during breeding season. All 4 of the females that had kittens with them through winter 2003-04 bred again spring 2004, 2 with the same male they successfully bred with spring 2003. During May-June 2004 we found 11 dens and a total of 30 kittens (Table 6). At all dens the females appeared in excellent condition, as did the kittens. The kittens weighed from 250-770 grams. Three of the 11 females with kittens were from the 2003 releases (Table 6). Three additional litters were documented after denning season through either observation of a female lynx with kittens or snow-tracking females with kittens that were not one of the 11 females found on dens. From the size of the kittens they would have been born during the normal denning season in May or June. Nine additional kittens were observed from these litters for a total of 39 known kittens born in 2004. Two of these additional litters were documented from direct follow-ups to sighting made by the public and reported to CDOW. Two females that had kittens in 2003 and reared at least part of their litters through March 2004, bred and had kittens again in 2004. Two of the litters documented by direct observation or snow-tracking are from females whose collars no longer work. Seven kittens born in 2004 were captured at 10-months of age and fitted with dual satellite/VHF collars. All 7 are alive and currently being monitored. 2005.-- In spring 2005 we had 34 females from the releases in 1999, 2000, 2003 and 2004 that had active radio-collars. We documented 23 possible mating pairs of lynx during breeding season. During May-June 2005 we visited 16 dens and found a total of 46 kittens (Table 7). At all dens the females appeared in excellent condition, as did the kittens. An additional female had a den we were not able to get to during May or June due to high water. Female BC03F03 was hit and killed on I70 on 5/19/2005. She had 2 fetuses in her uterus, so would have contributed to reproduction this year had she lived. We weighed, photographed, PIT-tagged the kittens and recorded sex. We also took blood samples from the kittens for genetic work in an attempt to confirm paternity. While we were working with the kittens the females remained nearby, often remaining visible to us. The females generally continued a low growling vocalization the entire time we were at the den. In all cases, the female returned to the den site once we left the area. All of the 2005 dens were scattered throughout the high elevation areas of Colorado, south of Interstate 70. Most of the dens were in Engelmann spruce/subalpine fir forests in areas of extensive downfall. Elevations ranged from 3117-3586 m. We weighed, photographed, and PIT-tagged the kittens, recorded sex and took hair samples from the kittens for genetic work in an attempt to confirm paternity. Four of the females would not leave the den until we reached out to pick up a kitten. While we were working with the kittens the females remained nearby, often remaining visible to us. The females 9 �generally continued a low growling vocalization the entire time we were at the den. In all cases, the female returned to the den site once we left the area. One female, YK00F10 has had litters 3 years in a row. In 2003 she had 4 kittens and raised 2 through the winter. In 2004 she had 2 kittens and raised both through the winter, this year she had 4 kittens again. She has had all 3 litters in the same general area and has had the same mate for 3 years. Eight additional females had a second litter in Colorado this year. Three females from the 2004 releases had litters in 2005. This is the second year in a row we had females released the prior spring, find a territory and a mate within a year and produced live young. In reproduction season 2004 we had 3 females released in spring 2003 that did the same thing. Of those 3, 2 successfully raised at least part of their litters through winter 2005. Den Sites.--A total of 33 dens have been found. All of the dens except one have been scattered throughout the high elevation areas of Colorado, south of I-70. One den was found in southeastern Wyoming, near the Colorado border. Dens were located on steep ( x slope = 29o), north-facing, high elevation ( x = 3347 m) slopes (Figure 2). The dens were typically in Engelmann spruce/subalpine fir forests in areas of extensive downfall (Figures 3, 4, 5). Recaptures Two adult lynx were captured in 2001 for collar replacement. One lynx was captured in a tomahawk live-trap, the other was treed by hounds and then anesthetized using a jab pole. Five adult lynx were captured in 2002; 3 were treed by hounds and 2 were captured in padded leghold traps. In 2004, 1 lynx was captured with a Belisle snare and 6 other adult lynx were captured in box-traps. Trapping effort was substantially increased in winter and spring 2005 and 12 adult lynx were captured and re-collared. In addition, 7 kittens born in Colorado in 2004 were also captured and collared. All lynx captured in 2005 were caught in box-traps. All captured lynx were fitted with new Sirtrack TM dual VHF/satellite collars. Six adult lynx were captured from March 1999-June 30, 2005 because they were in poor body condition. Five of these lynx were successfully treated at the Frisco Creek Rehabilitation Center and rereleased in the Core Research Area. One lynx, BC00F7, died from starvation and hypothermia. Two lynx were captured because they were in atypical habitat outside the state of Colorado. They were held at Frisco Creek Rehabilitation Center for a minimum of 3 weeks and re-released in the Core Research Area in Colorado. Prior to release these lynx were fitted with new Sirtrack TM dual VHF/satellite collars. HABITAT USE Landscape-scale daytime habitat use was documented from 7421 aerial locations of lynx collected from February 1999-June 30, 2005. Throughout the year Engelmann spruce / subalpine fir was the dominant cover used by lynx. A mix of Engelmann spruce, subalpine fir and aspen (Populus tremuloides) was the second most common cover type used throughout the year. Various riparian and riparian-mix areas were the third most common cover type where lynx were found during the daytime flights. Use of Engelmann spruce-subalpine fir forests and Engelmann spruce-subalpine fir-aspen forests was similar throughout the year. There was a trend in increased use of riparian areas beginning in July, peaking in November, and dropping off December through June. Site-scale habitat data collected from snow-tracking efforts indicate Engelmann spruce and subalpine fir were also the most common forest stands used by lynx for all activities during winter in southwestern Colorado. Comparisons were made among sites used for long beds, dens, travel and where they made kills. Little difference in aspect, mean slope and mean elevation were detected for 3 of the 4 site types including long beds, travel and kills where lynx typically use gentler slopes ( x = 15.7o ) at an mean elevation of 3173 m, and varying aspects with a slight preference for north-facing slopes (Figure 2). 10 �Den sites however, were located at higher elevations ( x = 3347 m), steeper slopes ( x = 29o) and more commonly on north-facing slopes (Figure 2). Mean percent total overstory was higher for long bed and kill sites than travel or den sites (Figure 3). Engelmann spruce provided a mean of 35.87% overstory for kills and long beds, with travel sites averaging 28% and den sites having the lowest mean percent overstory of 23% (Figure 3). Mean percent subalpine fir or aspen overstory did not vary across use sites (Figure 3). Willow overstory was highly variable and no dens were located in willow overstory. A total of 1841 site-scale habitat plots were completed in winter from December 2002 through April 2005. The most common understory species at all 3 height categories above the snow (low = 00.5m, medium = 0.51 - 1.0 m, high = 1.1 - 1.5 m) was Engelmann spruce, subalpine fir, willow (Salix spp.) and aspen (Figure 4). Various other species such as Ponderosa pine (Pinus ponderosa), lodgepole pine (Pinus contorta), cottonwood (Populus sargentii), birch (Betula spp.) and others were also found in less than 5% of the habitat plots. If present, willow provided the greatest percent cover within a plot followed by Engelmann spruce, subalpine fir, aspen and coarse woody debris for long beds, kills and travel sites. Areas documented in willow used by lynx are typically on the edge of willow thickets as tracks are quickly lost within the thicket. Den sites had significantly higher percent understory cover for all three height categories. Understory at den sites was primarily made up of coarse woody debris (Figure 3). The most common tree species documented in the site-scale habitat plots was Engelmann spruce Figure 5). Subalpine fir and aspen were also present in >35% of the plots. Most habitat plots were vegetated with trees of DBH < 6" (Figure 5). As DBH increased, percent occurrence decreased within the plot. Although decreasing in abundance as size increased, most lynx use sites had trees in each of the DBH categories, indicating mature forest stands except for dens. Den sites had a broad spectrum of Engelmann spruce tree sizes, including > 18” but no large subalpine fir or aspen trees. While Engelmann spruce and subalpine fir occurred in similar densities for kills, long beds and travel sites, den sites had twice the density of subalpine firs found at all other sites (Figure 5). DIET AND HUNTING BEHAVIOR Winter diet of lynx was documented through detection of kills found through snow-tracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. A total of 400 kills were located from February 1999-April 2005. We collected 671 scat samples from February 1999-April 2004 that will be analyzed for content. In each winter, the most common prey item was snowshoe hare, followed by red squirrel (Table 8). A comparison of percent overstory for successful and unsuccessful snowshoe hare chases indicated lynx were more successful at sites with slightly higher percent overstory, if the overstory species were Englemann spruce, subalpine fir or willow. Lynx were slightly less successful in areas of greater aspen overstory (Figure 6). This trend was repeated for percent understory at all 3 height categories (Figure 7) except that higher aspen understory improved hunting success. Higher density of Engelmann spruce and subalpine fir increased hunting success while increased aspen density decreased hunting success (Figure 8). DISCUSSION In an effort to establish a viable population of lynx in Colorado, CDOW initiated a reintroduction effort in 1997 with the first lynx released in winter 1999. From 1999 through spring 2004, 166 lynx were released in the Core Research Area. The reintroduction effort was augmented with the release of 37 11 �additional animals in April 2005 and 1 in June 2005, bringing the total to 204 lynx reintroduced to southwestern Colorado. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns and to detect mortalities. Most lynx remain in the southwestern quarter of Colorado. Dispersal movement patterns for lynx released in 2000 and subsequent years were similar to those of lynx released in 1999. However, more animals released in 2000 and subsequent years remained within the Core Research Area than those released in 1999. This increased site fidelity may have been due to the presence of con-specifics in the area on release. Numerous travel corridors have been used repeatedly by more than 1 lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-Silverton-Lizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast to the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. Most lynx currently being tracked are within the Core Research Area. During the summer months, lynx were documented to make extensive movements away from their winter use areas. Extensive summer movements away from areas used throughout the rest of the year have been documented in native lynx in Wyoming and Montana (Squires and Laurion 1999). Human-caused mortality factors such as gunshot and vehicle collision are currently the highest causes of death. Reproduction is critical to achieving a self-sustaining viable population of lynx in Colorado. Reproduction was first documented from the 2003 reproduction season and again in 2004 and 2005. Additional reproduction is likely to have occurred in females we are no longer tracking, and from Colorado born lynx that have not been collared. The dens we find are more representative of the minimum number of litters and kittens in a reproduction season. Live-births and over-winter survival of kittens are the first steps towards recruitment into the breeding population defined as when these Colorado-born lynx will produce offspring of their own. To achieve a viable population of lynx, enough kittens need to be recruited into the population to offset the mortality that occurs in that year and hopefully even exceed the mortality rate for an increasing population. Mowat et al. (1999) suggest lynx and snowshoe hare select similar habitats except that hares select more dense stands than lynx. Very dense understory limits hunting success of the lynx and provides refugia for hares. Given the high proportion of snowshoe hare in the lynx diet in Colorado, we might then assume the habitats used by reintroduced lynx also depict areas where snowshoes hare are abundant and available for capture by lynx in Colorado. From both aerial locations taken throughout the year and from the site-scale habitat data collected in winter, the most common areas used by lynx are in stands of Engelmann spruce and subalpine fir. This is in contrast to adjacent areas of Ponderosa pine, pinyon juniper, aspen and oakbrush. The lack of lodgepole pine in the areas used by the lynx may be more reflective of the limited amount of lodgepole pine in southwestern Colorado, the Core Research Area, rather than avoidance of this tree species. Hodges (1999) summarized habitats used by snowshoe hare from 15 studies as areas of dense understory cover from shrubs, stands that are densely stocked, and stands at ages where branches have more lateral cover. Species composition and stand age appears to be less correlated with hare habitat use than is understory structure (Hodges 1999). The stands need to be old enough to provide dense cover and browse for the hares and cover for the lynx. In winter, the cover/browse needs to be tall enough to still provide browse and cover in average snow depths. Hares also use riparian areas and mature forests with understory. Site-scale habitat use documented for lynx in Colorado indicate lynx are most commonly using areas with Engelmann spruce understory present from the snow line to at least 1.5 m above the snow. The mean percent understory cover within the habitat plots is typically less than 15% regardless of understory species. However, if the understory species is willow, percent understory cover is typically 12 �double that, with mean number of shrubs per plot approximately 80, far greater than for any other understory species. In winter, hares browse on small diameter woody stems (<0.25"), bark and needles. In summer, hares shift their diet to include forbs, grasses, and other succulents as well as continuing to browse on woody stems. This shift in diet may express itself in seasonal shifts in habitat use, using more or denser coniferous cover in winter than in summer. The increased use of riparian areas by lynx in Colorado from July to November may reflect a seasonal shift in hare habitat use in Colorado. Major (1989) suggested lynx hunted the edge of dense riparian willow stands. The use of these edge habitats may allow lynx to hunt hares that live in habitats normally too dense to hunt effectively. The use of riparian areas and riparian-Engelmann spruce-subalpine fir and riparian-aspen mixes documented in Colorado may stem from a similar hunting strategy. However, too little is known about habitat use by hares in Colorado to test this hypothesis at this time. Lynx also require sufficient denning habitat. Denning habitat has been described by Koehler (1990) and Mowat et al. (1999) as areas having dense downed trees, roots, or dense live vegetation. We found this to be in true in Colorado as well. In addition, the dens used by reintroduced lynx were at high elevation, steep north-facing slopes. All females that were documented with kittens denned in areas within their winter-use area. Snow-tracking of released lynx provided information on hunting behavior and diet through documentation of kills, food caches, chases, and diet composition estimated through prey remains. Snowtracking results indicate the primary winter prey species are snowshoe hare and red squirrel, with other mammals and birds forming a minor part of the winter diet. In winter, lynx reintroduced to Colorado appear to be feeding on their preferred prey species, snowshoe hare and red squirrel in similar proportions as those reported for northern lynx during lows in the snowshoe hare cycle (Aubry et al., 1999). Caution must be used in interpreting the proportion of identified kills. Such a proportion ignores other food items that are consumed in their entirety and thus are biased towards larger prey and may not accurately represent the proportion of smaller prey items, such as microtines, in lynx winter diet. Through snowtracking we have evidence that lynx are mousing and several of the fresh carcasses have yielded small mammals in the gut on necropsy. The summer diet of lynx has been documented to include less snowshoe hare and more alternative prey than in winter (Mowat et al., 1999). All evidence suggests reintroduced lynx are finding adequate food resources. SUMMARY From results to date it can be concluded that CDOW has developed release protocols that ensure high initial post-release survival, and on an individual level lynx have demonstrated they can survive long-term in areas of Colorado. It has also been documented that reintroduced lynx could exhibit site fidelity, engage in breeding behavior and produce kittens. What is yet to be demonstrated is whether current conditions in Colorado can support the recruitment necessary to offset annual mortality for a population to sustain itself. Monitoring of reintroduced lynx will continue in an effort to document such viability. 13 �ACKNOWLEDGEMENTS The lynx reintroduction program involves the efforts of literally hundreds of people across North America, in Canada and the U. S. Any attempt to properly acknowledge all the people who played a role in this effort is at risk of missing many people. The following list should be considered to be incomplete. CDOW CLAWS Team (1998-2001): Bill Andree, Tom Beck, Gene Byrne, Bruce Gill, Mike Grode, Rick Kahn (Program Leader), Dave Kenvin, Todd Malmsbury, Jim Olterman, Dale Reed, John Seidel, Scott Wait, Margaret Wild. CDOW: John Mumma (Director 1996-2000), Conrad Albert, Jerry Apker, Laurie Baeten, Cary Carron, Don Crane, Larry DeClaire, Phil Ehrlich, Lee Flores, Delana Friedrich, Dave Gallegos, Juanita Garcia, Drayton Harrison, Jon Kindler, Ann Mangusso, Jerrie McKee, Melody Miller, Mike Miller, Kirk Navo, Robin Olterman, Jerry Pacheo, Mike Reid, Ellen Salem, Eric Schaller, Mike Sherman, Jennie Slater, Steve Steinert, Kip Stransky, Suzanne Tracey, Anne Trainor, Brad Weinmeister, Nancy Wild, Perry Will, Lisa Wolfe, Brent Woodward, Kelly Woods, Kevin Wright. Lynx Advisory Team (1998-2001): Steve Buskirk, Jeff Copeland, Dave Kenny, John Krebs, Brian Miller (Co-leader), Mike Phillips, Kim Poole, Rich Reading (Co-leader), Rob Ramey, John Weaver. U. S. Forest Service: Kit Buell, Joan Friedlander, Dale Gomez, Jerry Mastel, John Squires, Fred Wahl, Nancy Warren. U. S. Fish and Wildlife Service: Lee Carlson, Gary Patton (1998-2000), Kurt Broderdorp. State Agencies: Gary Koehler (Washington). National Park Service: Steve King. Colorado State University: Alan B. Franklin, Gary C. White. Colorado Natural Heritage Program: Rob Schorr, Mike Wunder. Alaska: ADF&G: Cathie Harms, Mark Mcnay, Dan Reed (Regional Manager), Wayne Reglin (Director), Ken Taylor (Assist. Director), Ken Whitten, Randy Zarnke, Other:Ron Perkins (trapper), Dr. Cort Zachel (veterinarian). British Columbia: Dr. Gary Armstrong (veterinarian), Mike Badry (government), Paul Blackwell (trapper coordinator), Trappers: Dennis Brown, Ken Graham, Tom Sbo, Terry Stocks, Ron Teppema, Matt Ounpuu. Yukon: Government: Arthur Hoole (Director), Harvey Jessup, Brian Pelchat, Helen Slama, Trappers: Roger Alfred, Ron Chamber, Raymond Craft, Lance Goodwin, Jerry Kruse, Elizabeth Hofer, Jurg Hofer, Guenther Mueller (YK Trapper’s Association), Ken Reeder, Rene Rivard (Trapper coordinator), Russ Rose, Gilbert Tulk, Dave Young. Alberta: Al Cook. Northwest Territories: Albert Bourque, Robert Mulders (Furbearer Biologist), Doug Steward (Director NWT Renewable Res.), Fort Providence Native People. Quebec: Luc Farrell, Pierre Fornier. Colorado Holding Facility: Herman and Susan Dieterich, Loree Harvey, Rachel Riling. Pilots: Dell Dhabolt, Larry Gepfert, Al Keith, Jim Olterman, Matt Secor, Whitey Wannamaker, Steve Waters, Dave Younkin. Field Crews (1999-2005): Steve Abele, Brandon Barr, Bryce Bateman, Todd Bayless, Ryan Besser, Mandi Brandt, Brad Buckley. Patrick Burke, Paula Capece, Stacey Ciancone, Doug Clark, John DePue, Shana Dunkley, Tim Hanks, Matt Holmes, Andy Jennings, Susan Johnson, Paul Keenlance, Tony Lavictoire, Clay Miller, Denny Morris, Kieran O’Donovan, Gene Orth, Chris Parmater, Jake Powell, Jeremy Rockweit, Josh Smith, Adam Strong, Dave Unger, David Waltz, Andy Wastell, Lyle Willmarth, Leslie Witter, Kei Yasuda, Jennifer Zahratka. Research Associates: Bob Dickman, Grant Merrill. Data Analysts: Karin Eichhoff, Joanne Stewart, Anne Trainor. Data Entry: Charlie Blackburn, Patrick Burke, Rebecca Grote, Angela Hill, Mindy Paulek. Photographs: Tom Beck, Bruce Gill, Mary Lloyd, Rich Reading, Rick Thompson. Funding: CDOW, Great Outdoors Colorado (GOCO), Turner Foundation, U.S.D.A. Forest Service, Vail Associates. 14 �LITERATURE CITED AUBRY, K. B., G. M. KOEHLER, J. R. SQUIRES. 1999. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. BYRNE, G. 1998. Core area release site selection and considerations for a Canada lynx reintroduction in Colorado. Report for the Colorado Division of Wildlife. CURTIS, J. T. 1959. The vegetation of Wisconsin. University of Wisconsin Pres, Madison. GANEY, J. L. AND W. M. BLOCK. 1994. A comparison of two techniques for measuring canopy closure. Western Journal of Applied Forestry 9:1: 21-23. HODGES, K. E. 1999. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. KOEHLER, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. KOLBE, J. A,, J. R. SQUIRES, T. W. PARKER. 2003. An effective box trap for capturing lynx. Journal of Wildlife Management 31:980-985. LAYMON, S. A. 1988. The ecology of the spotted owl in the central Sierra Nevada, California. PhD Dissertation University of California, Berkeley, California. MAJOR, A. R. 1989. Lynx, Lynx canadensis canadensis (Kerr) predation patterns and habitat use in the Yukon Territory, Canada. M. S. Thesis, State University of New York, Syracuse. MOWAT, G., K. G. POOLE, AND M. O’DONOGHUE. 1999. Ecology of lynx in northern Canada and Alaska. Pages 265-306 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. POOLE, K. G., G. MOWAT, AND B. G. SLOUGH. 1993. Chemical immobilization of lynx. Wildlife Society Bulletin 21:136-140. SHENK, T. M. 1999. Program narrative: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Report for the Colorado Division of Wildlife. __________. 2001. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. SQUIRES, J. R. AND T. LAURION. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. U. S. FISH AND WILDLIFE SERVICE. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. WILD, M. A. 1999. Lynx veterinary services and diagnostics. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. Prepared by _______________________________ Tanya M. Shenk, Wildlife Researcher 15 �Table 1. Definitions of forest structure classes used to describe habitat sites (Thomas 1979). Forest Structure Class Definition Grass/forb The grass/forb stage is created naturally by a catastrophic event, such as wildfire, and is typified by the near complete absence of snags, litter or down material in the aspen and ponderosa pine types, or vice versa in the lodgepole or subalpine forest types. Shrub/seedling The shrub/seedling stage occurs when tree seedlings or shrubs grow up to 2.5 cm at diameter breast height (DBH), either naturally or artificially through planting. Sapling/pole The sapling/pole stage is a young stage where tree DBH's range from 2.5-17.5 cm with tree heights ranging 1.8-13.5 m. These trees are 5-100 years of age, depending on species and site condition. Mature The mature stage occurs when tree diameters reach a relatively large size (25-50 cm) and the trees are usually 90 or more years old. Forest stands begin to experience accelerated mortality from disease and insects. Old-growth The old-growth stage occurs when a mature stand is at advanced age (100 years for aspen or 200 years for spruce), is very slow growing, and has advanced degrees of disease, insects, snags, and down, dead material. An exception to this occurs in ponderosa pine and aspen types where these old-growth stands typically experience low densities of down dead material or snags. Table 2. Lynx released in Colorado from February 1999 through June 30, 2005. Year Females Males TOTAL 1999 22 19 41 2000 35 20 55 2003 17 16 33 2004 17 20 37 2005 18 20 38 TOTAL 109 95 204 16 �Table 3. Causes of death for adult lynx released into southwestern Colorado in 1999-2005 as of June30, 2005. Number of Mortalities Cause of Death Unknown 22 9 Starvation Hit by Vehicle 9 Shot 8 Probable Shot 6 Plague 4 Probable Predation 2 2 Probable Hit by Vehicle Other Human Caused 2 Illness 1 Territorial Dispute 1 Total Mortalities 66 Table 4. Status of adult lynx reintroduced to Colorado as of June 30, 2005. Females Males Unknown Released 109 95 Known Dead 40 25 1 Possible Alive 69 70 Missing 16 13 Tracking 53 57 a 1 is unknown mortality TOTALS 204 66 138 28a 110 Table 5. Lynx reproduction documented in 2003. Female BC00F8 BC00F19 YK00F16 YK99F1 YK00F19 YK00F10 Release Year 2000 2000 2000 1999 2000 2000 Date Den Found 5/21/03 5/26/03 6/19/03 6/10/03 6/11/03 5/31/03 TOTAL Females ? 1 1 2 1 2 7 17 Number of Kittens Males ? 2 1 2 1 2 1 3 2 3 2 4 7 16 Total �Table 6. Lynx reproduction documented in 2004. Female ID YK00F2 AK00F2 YK00F1 YK00F15 BC00F14 BC00F18 YK00F10 BC03F02 BC03F10 BC03F09 YK00F7 YK99F1 Unknown Unknown TOTAL Release Year 2000 2000 2000 2000 2000 2000 2000 2003 2003 2003 2000 1999 Previous Litter Date Den Found 5/28/2004 5/31/2004 6/1/2004 6/4/2004 6/7/2004 6/10/2004 6/17/2004 6/25/2004 6/26/2004 6/29/2004 6/30/2004 Date Kittens Found Dec 2004 Sept 2004 Feb 2005 Number of Kittens Females Males Total 3 1 4 2 1 3 3 3 1 2 3 1 2 3 4 4 1 1 2 2 2 2 2 1 1 2 1 1 2 2 4 3 19 11 39 Table 7. Lynx reproduction documented in 2005. Female ID AK00F02 YK00F15 YK00F10 YK00F11 YK00F01 YK00F07 BC00F18 BC03F02 BC03F01 QU03F06 QU03F04 QU03F07 BC03F09 BC03F10 BC04F01 BC04F03 BC04F05 TOTAL Release year 2000 2000 2000 2000 2000 2000 2000 2003 2003 2003 2003 2003 2003 2003 2004 2004 2004 Previous Litters 2004 2004 2003, 2004 2004 2004 2004 2004 2004 2004 Date Den Found 5/21/2005 5/28/2005 6/1/2005 6/9/2005 6/10/2005 6/14/2005 6/24/2005 5/25/2005 5/27/2005 6/5/2005 6/14/2005 6/16/2005 6/27/2005 6/11/2005 6/19/2005 6/23/2005 Total 3 2 4 2 3 3 2 2 4 3 3 4 2 ? 3 3 3 46 Number of Kittens Males Females 2 1 1 1 2 2 2 2 1 1 2 1 1 1 1 2 2 3 1 2 3 1 1 1 2 3 25 1 3 21 Table 8. Number of kills found each winter field season through snow-tracking of lynx and percent composition of kills of the three primary prey species. Field Season 1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 n 9 83 89 54 65 37 78 Snowshoe Hare 55.56 67.47 67.42 90.74 90.77 67.57 83.33 Prey (%) Red Squirrel Cottontail 22.22 0 19.28 1.20 19.10 8.99 5.56 0 6.15 0 27.03 2.70 10.26 0 18 Other 22.22 12.05 4.49 3.70 3.08 2.70 6.41 �Figure 1. Design of site-scale habitat plot sampling plot. Each of the 25 points are 3 meters apart (the first 6 points are labeled 1-6). The object that triggered a habitat plot (e.g., kill ) is the center point, depicted by the hollow circle. The actual pints encompass a 12 m x 12 m square but the understory and overstory data collected are influenced by vegetation occurring within a 15 m x 15 m square. Figure 2. Frequency of aspect, mean elevation and SE and mean slope and SE for 4 lynx use sites; dens, long beds, kills and travel. 19 �Figure 3. Mean percent overstory by tree species Engelmann spruce (ES), subalpine fir (SF), aspen (AS), willow (WI) and total cover for 4 different lynx use sites: long beds, kill sites, travel and den sites. Confidence intervals (95%) are depicted by error bars. Figure 4. Mean percent understory by tree species Engelmann spruce (ES), subalpine fir (SF), coarse woody debris (CWD), aspen (AS), willow (WI) and total cover for 4 different lynx use sites: long beds, kill sites, travel and den sites. 20 �Figure 5. Mean tree density by species Engelmann spruce (ES), subalpine fir (SF) and aspen (AS) and dbh size class for 4 different lynx use sites. Figure 6. Mean percent overstory by tree species Engelmann spruce (ES), subalpine fir (SF), aspen (AS), willow (WI) and total cover for successful and unsuccessful snowshoe hare chases. Confidence intervals (95%) are depicted by error bars. 21 �Figure 7. Mean percent understory by tree species Engelmann spruce (ES), subalpine fir (SF), aspen (AS), willow (WI) and total cover for 3 different understory height categories for successful and unsuccessful snowshoe hare chases. Confidence intervals (95%) are depicted by error bars. Figure 8. Mean tree density by species Engelmann spruce (ES), subalpine fir (SF) and aspen (AS) and 5 DBH size classes for successful chases (SC) and unsuccessful chases (UC) of snowshoe hare. 22 �Colorado Division of Wildlife July 2004 – June 2005 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 2 : : : : Federal Aid Project W-185-R : Division of Wildlife Mammals Research Deer Conservation Pilot Evaluation of Winter Range Habitat Treatments on Mule Deer Fawn Over- Winter Survival Period Covered: July 1, 2004 - June 30, 2005 Author: E.J. Bergman, C.J. Bishop, D.J. Freddy and G.C. White Personnel: D. Baker, B. Banulis, M. Catanese, M. Cowardin, K. Crane, B. deVergie, K. Duckett, D. Hale, C. Harty, J. McMillan, R. Swygman, C. Tucker, S. Waters, B. Watkins, M. Zeaman, CDOW; L. Carpenter, WMI; and, project support provided by Federal Aid in Wildlife Restoration and the Mule Deer Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A pilot study Program Narrative (Appendix I) study plan was developed to test the effects of winter range habitat treatments on mule deer fawn survival rates on the Uncompahgre Plateau in southwest Colorado. Data were collected in order to confirm logistical feasibility and to establish baseline estimates for survival and process variation of survival. Overwinter fawn survival in our study areas was very high, (BCSWA Ŝ = 0.84 (SE = .075), Sowbelly Ŝ = 0.96 (SE = .039), combined Ŝ = 0.90 (SE = .042). Data collected during this pilot study proved to be very informative and are useful in the development of a full research project study plan. Our initial objectives of assessing the logistical/financial feasibility of conducting field work in our chosen study areas were adequately addressed. Based on these results, we found that each method of capture was appropriate for the respective study areas. While helicopter netgunning was not minimized due to unfavorable ground-based capture conditions, financial limitations in terms of captures costs were not broached. Despite remote location, monitoring of survival in one of our study areas was also adequately accomplished. Survival rate estimation from this study will also serve as baseline data for the estimation of process variation in survival during a full research project. 23 �WILDLIFE RESEARCH REPORT PILOT EVALUATION OF WINTER RANGE HABITAT TREATEMENTS ON OVER-WINTER MULE DEER FAWN SURVIVAL. E.J. BERGMAN, C.J. BISHOP, D.J. FREDDY AND G.C. WHITE P.N. OBJECTIVE 1. To conduct a one-year pilot study to assess the logistical feasibility of the proposed study herein and to gather preliminary data to improve a full research project's efficiency and experimental design. SEGMENT OBJECTIVES 1. Prepare a pilot study Program Narrative and complete field work accordingly. 2. To collect survival data in 2 study areas to measure baseline survival rates and to learn about differences between study areas. 3. To establish baseline collection of survival data in order to produce reliable estimates of annual process variation necessitated by the longevity of a proposed full research project. 4. Begin work on a full research project Program narrative study plan. 5. Acquire necessary field equipment (radio collars, receivers and antennas) and additional funding for implementation of full research project. INTRODUCTION As with many wildlife species, mule deer populations tend to fluctuate such that there are noticeable differences between highs and lows. Several dramatic fluctuations have been observed since the turn of the 19th century (Connolly 1981, Gill 2001), with the most recent decline taking place during the 1990's (Unsworth et al. 1999). Wildlife managers' challenges are thus two-fold: understanding the underlying causes of population fluctuations and managing populations to dampen the effects of these fluctuations. Recent research conducted by the Colorado Division of Wildlife has assessed the role of forage quality and quantity on over-winter fawn survival (Bishop et al. 2004). Using a treatment/control crossover design, the impact of ad libitum pelleted food supplements as a surrogate for habitat improvement, was measured. The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e., if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the limiting factor on population performance. As such, preliminary evidence suggests that nutrition enhancement treatments have increased fawn survival by as much as 20% (C.J. Bishop, personal communication). However, while this research elucidated some of the underlying processes in mule deer population regulation, it did not test the effectiveness of an acceptable management technique. Due to the undesirable effects of feeding wildlife (i.e. artificially elevating density, increased potential for disease transmission, cost and manpower), a more appropriate technique for delivering a high quality nutrition enhancement needs to be assessed. The reasons for conducting this work as a pilot study were two-fold. First, we wished to determine if the capture and monitoring of deer in our chosen study areas was logistically feasible. One 24 �study area (Sowbelly/Tatum - see below) was known to have low deer densities and to be located in an area that was too remote to allow for ground based capture efforts. It was unknown if deer capture in this area, via helicopter net-gunning, would be economically feasible. The second study area (Billy Creek State Wildlife Area - see below) had high ungulate densities and was easily accessible from roads. Baited drop nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) were the preferred method of capture in this area, however, the feasibility of using drop nets in this area needed to be evaluated in light of high elk densities. Drop netting in areas with large numbers of elk is not ideal because elk presence under a net, despite the number of deer, limits capture opportunities. The second primary reason for conducting a 1-year pilot study was to gather data and information to improve the design of future experimental research on the same topic. These data will allow us to improve our estimate of process variance in fawn survival, because fawn survival has been shown to vary significantly among areas and years (Unsworth et al. 1999, Bishop et al. 2005). STUDY AREA This pilot study was conducted on the Uncompahgre Plateau and in an adjacent valley in southwestern Colorado. The first study area, preliminarily identified as a high quality area, was located on Billy Creek State Wildlife Area (BCSWA - approximately 20km south of Montrose, CO). Over the past 15-30 years this area has received several habitat treatments that were intended to benefit mule deer. Additionally, BCSWA was in close proximity to agricultural lands that provided high quality, succulent forage immediately preceding the onset of winter and immediately following spring melt. The second study area, preliminarily identified as a low quality area, was located on Sowbelly and Tatum draws (Sowbelly - approximately 15km west of Delta, CO). This area was located in a segment of winter range that had not received any habitat treatments, was not in close proximity to agricultural lands and was in an advanced stage of pinyon-juniper succession (i.e. old growth trees, poor or non-existent understory and poor quality of shrub component). METHODS Twenty-five mule deer fawns were captured and radio-collared in each of the 2 study areas. At BCSWA we captured fawns with baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) and via helicopter net-gunning (Barrett et al. 1982, van Reenen 1982). At Sowbelly all fawns were captured via helicopter net-gunning. All captures occurred during December 2004. All capture and handling protocols were approved by CDOW ACUC committee (project number 09-2004). On a daily basis, from December through May, we attempted to monitor the radioed fawns in order to document live/death status. Due to the remote location of Sowbelly, we found it necessary to supplement ground tracking with weekly aerial fixed-wing flights. Combined, these methods allowed us to calculate weekly survival rates and to accurately estimate the date and proximate causes of death. All fawns were located, via aerial telemetry, one time per month. RESULTS AND DISCUSSION Ground based capture efforts during this pilot study took place on 14 days between 7 December and 30 December. During this time, 36 nets were monitored and 9 drops were made, resulting in the capture of 12 individual fawns. No injuries or capture related mortalities occurred and 1 non-target animal (adult male elk) was captured and released without injury. Helicopter net-gunning took place on 3 consecutive days between 31 December and 2 January. Capture related injuries during net-gunning were limited to 1 animal, which was later euthanized. 25 �Based on these results, we found that each method of capture was appropriate for the respective study areas. However, ground based capture efforts (confined to BCSWA) were not as efficient as originally hoped. We attribute this to mild winter conditions and the abundance of available native vegetation, as well as intermittent patches of green exotic forage. We suspect that under typical winter conditions (i.e. complete snow coverage of the study area) our efforts to bait deer into capture sites would have been more effective. Despite our poor efficiency, ground based capture efforts saved approximately $6,000. Our initial concern in regards to the cost of helicopter net-gunning in low density areas was not realized. The minimum sample size requirement of 25 fawns was met in 1.5 days of capture effort and all capture occurred at the per animal rate. Direct capture related injury was low (injury occurred in 1 of 52 animals, <2%). No post hoc capture related injury or mortality was observed in either study area, indicating that potential bias resulting from multiple capture methods was not detectable. However, potential bias does exist due to the fact that the period of time needed to capture animals in two areas via multiple methods was quite long. In order to compare survival rates between the two areas, rates couldn't be calculated until minimum sample size requirements had been met in each area. As expected based on deer density, differences in the size of winter range between the 2 study areas was very dramatic. The observed winter range size for radio marked deer on BCSWA was ~8.7km2. The observed winter range size for radio marked deer on Sowbelly was 140 km2. Despite these differences, overwinter fawn survival in both study areas was very high. The measured survival rate for BCSWA, the lowest for both areas, was Ŝ = 0.84 (SE = .075) (Table 1 and Fig. 1a). Survival at Sowbelly, hypothesized to be an area that experiences lower survival, was Ŝ = 0.96 (SE = .039) (Table 1 and Fig. 1b). Across the Uncompahgre Plateau, survival rates (Ŝ = 0.90, SE = .042) (Fig. 1c) were much higher than rates reported in the literature (B. Banulis, personal communication, Unsworth et al. 1999). SUMMARY Data collected during this pilot study proved to be very informative and are useful in the development of a full research project study plan. Our initial objectives of assessing the logistical/financial feasibility of conducting field work in our chosen study areas were adequately addressed. While ground based capture efforts in BCSWA were not as efficient as initially hoped, we found that the more pressing concern of high elk density was not a limiting factor. To further reduce potential conflict concerning elk in and around deer drop nets, starting capture operations at an earlier date, prior to elk movement down onto BCSWA, would be prudent. Helicopter net-gunning efficiency in Sowbelly was also assessed. Capture was completed after 1.5 days of effort, demonstrating that despite low densities, utilization of this area in further research efforts is warranted. Despite remote location, monitoring of survival in Sowbelly was also adequately accomplished. Weekly survival rates were measured and it is believed that the addition of future study areas in the general proximity of Sowbelly during a full research project would not prove to be cost or logistically prohibitive. Survival rate estimation from this study will also serve as baseline data for the estimation of process variation in survival during a full research project. 26 �LITERATURE CITED BARRETT, M. W., J. W. NOLAN, AND L.D. ROY. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. BARTMANN, R.M., G.C. WHITE, AND L. H. CARPENTER. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. BISHOP, C. J., J. W. UNSWORTH, AND E. O. GARTON. 2005. Mule deer survival among adjacent populations in southwest Idaho. Journal of Wildlife Management 69:311-321. BISHOP, C. J., G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2004. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. CONNOLLY, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. GILL, R. B. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Denver, USA. RAMSEY, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. SCHMIDT, R. L., W. H. RUTHERFORD, AND F. M. BODENHAM. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. UNSWORTH, J. W., D. F. PAC, G. C. WHITE, AND R. M. BARTMANN. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. VAN REENEN, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Prepared by Eric J. Bergman, Wildlife Researcher 27 �Table 1. Causes of over-winter mortality for mule deer fawns from two pilot study areas on the Uncompahgre Plateau, southwest Colorado. Study Area BCSWA Sowbelly Cause of Death Canid Sick/Starve 1 0 0 0 Felid 4 0 Unk 0 1 Figure 1. Estimated overwinter mule deer fawn survival curves, with 95% confidence intervals, for pilot research conducted on Billy Creek State Wildlife Area (1a), Sowbelly and Tatum draws on the Uncompahgre Plateau (1b) and combined for the two areas (1c). Survival estimates (solid lines) and confidence intervals (dashed lines) were measured between late-December and mid-June. Survival Estimate 1a 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1 3 5 7 9 11 13 Week 28 15 17 19 21 23 �Survival Estimate 1b 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1 3 5 7 9 11 13 15 17 19 21 23 15 17 19 21 23 Week 1c 1 Survival Estimate 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1 3 5 7 9 11 13 Week 29 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH PILOT EVALUATION OF WINTER RANGE HABITAT TREATEMENTS ON OVER-WINTER MULE DEER FAWN SURVIVAL. A pilot study proposal submitted by: E.J. Bergman, Colorado Division of Wildlife C.J. Bishop, Colorado Division of Wildlife G.C. White, Colorado State University D.J. Freddy, Colorado Division of Wildlife A. Need As with many wildlife species, mule deer populations tend to fluctuate such that there are noticeable differences between highs and lows. Several dramatic fluctuations have been observed since the turn of the 19th century (Connolly1981, Gill 2001), with the most recent decline taking place during the 1990's (Unsworth et al. 1999). Wildlife managers' challenges are thus two-fold: understanding the underlying causes of population fluctuations and managing populations to dampen the effects of these fluctuations. As a result of these objectives and challenges, considerable energy and money has been invested in assessing the role of habitat quality on mule deer population performance. Recent research conducted by the Colorado Division of Wildlife has assessed the role of forage quality and quantity on over-winter fawn survival (Bishop et al. 2004). Using a treatment/control crossover design, the impact of ad libitum pelleted food supplements as a surrogate for habitat improvement, was measured. The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e., if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the limiting factor on population performance. As such, preliminary evidence suggests that nutrition enhancement treatments have increased fawn survival by as much as 20% (C.J. Bishop, personal communication). However, while this research effectively elucidated some of the underlying processes in mule deer population regulation, it did not test the effectiveness of an acceptable management technique. Due to the undesirable effects of feeding wildlife (i.e. artificially elevating density, increased potential for disease transmission, cost and manpower), a more appropriate technique for delivering a high quality nutrition enhancement needs to be assessed. Over the past 40 years land management agencies (BLM and USFS) have conducted habitat treatments, many of which have been driven by the desire to improve mule deer habitat. During the next five winters, we plan to quantify the impact of these treatments on mule deer population performance. We are proposing to measure fawn survival on a series of randomly selected study areas 30 �1 0.9 0.8 0.7 Power 0.6 0.5 0.4 0.3 12 Areas 0.2 14 Areas 0.1 16 Areas 0 0 10 20 30 40 50 60 70 80 Number of Fawns Figure 1. Expected power, based on simulation, of detecting a 20% (d = 0.20) difference in fawn survival across study areas at an α-level of 0.10. Year Unit A Unit B Unit C Unit D Unit E Pilot Control L Control H 1 Control L Random 1 Random 2 Random 3 Control H 2 Control L Random 4 Random 5 Random 6 Control H 3 Control L Random 7 Random 8 Random 9 Control H 4 Control L Random 10 Random 11 Random 12 Control H Figure 2. Schematic representation of study units and their allocation across years. The pilot study will consist of measuring fawn survival in a low quality control (Control L) and a high quality control (Control H). During subsequent years, fawn survival will continue to be measured on each of the controls to provide an estimate of the temporal process variance, and to adjust survival rates measured on the randomly selected sites for winter-to-winter differences. that cover a range of habitat treatment quality from low to high. Power analyses (α = 0.10, β = 0.80) indicate that to detect a 20% change (d = 0.20) in survival, 25 fawns will need to be marked in each of 16 study areas (Fig. 1). Due to the logistical infeasibility of accomplishing this during one winter, we are proposing to measure fawn survival over 5 winters. However, spreading the design over multiple years confounds winter-to-winter variation in fawn survival with habitat effects. Therefore, we will measure fawn survival on 2 control areas during all years of the study to adjust for winter-to-winter effects. We propose measuring over-winter fawn survival in 2 control areas (2004 – 2008) and 3 randomly selected areas of variable habitat quality each year (2005 – 2008) (Fig. 2). We will measure fawn survival only in 31 �the control areas during the first winter as a pilot effort to obtain baseline data and gain experience with the logistics of this experiment. The reasons for conducting the first winter of data collection as a pilot study are three-fold: 1) One of the control study areas is located in a low quality area (see Methods), an area that has never received habitat treatments and is not close in proximity to agricultural lands. We do not know if deer densities are high enough to capture a sample of 25 fawns in the area. Due to the remote location of this control area, helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) is the only feasible capture technique. Helicopter net-gunning can become cost prohibitive in low density areas, emphasizing the need to test this approach prior to committing to four additional years. The high quality control area is defined by extensive exposure to habitat treatments as well as close proximity to agricultural fields (hay, alfalfa and/or grass), resulting in high densities of both deer and elk from these beneficial conditions. Because the high quality control area is easily accessible from roads and has high densities of deer, baited drop nets are the preferred method of capture. However, the feasibility and efficiency of drop nets need to be evaluated in light of high elk densities. Drop netting in areas with large numbers of elk is not ideal because elk presence under a net, despite the number of deer, limits capture opportunities. By assessing these potential problems through a pilot study, we will improve the efficiency and design of the full research study in later years. 2) We wish to collect one year of data in our control areas before instituting a monitoring program in the treatment areas in order to improve our estimate of process variance in fawn survival. 3) We will gain insight as to how much fawn survival varies between extremes in habitat quality. The final reason for conducting a pilot study prior to instituting a full study pertains to our ability to assess habitat quality as it relates to habitat improvements and mule deer winter range. From the perspective of this study, there are three primary components to habitat quality: 1) availability of native forage, 2) availability of agriculturally based forage, and 3) overall structure of habitat. By conducting the initial year of data collection as a pilot, we will be able to identify and rank study areas according to these criteria. While detailed methodologies have not been developed, the general approach will be to: 1) grossly quantify the total biomass of native forage using existing information on mule deer forage selection (Bartmann 1983), 2) compute the total amount and proximity of land devoted to agricultural practices, per study area, based on existing GIS data, and 3) rely on a panel of mule deer experts to provide a ranking of study areas based on vegetation complex, availability of cover and overall habitat structure. Information collected through these three steps will be merged, allowing a general ranking of each study area into habitat quality. Rankings will serve no purpose within the study other than to provide an efficient mechanism for stratifying sampling, such that a gradient of poor to high quality study areas can be sampled each year. B. Objective The specific objectives for our pilot study are: 1) determine if deer density is high enough in our low quality control study area to allow for the capture of 25 mule deer fawns, 2) determine if elk density in the high quality control study area (and if elk affinity for bait under drop nets) is too high to efficiently capture 25 mule deer fawns with baited drop nets, and 3) design and implement habitat assessment techniques that will allow us to segregate randomly selected study areas based on habitat quality, the impact of previous habitat treatments, and the proximity to agricultural lands. C. Expected Results We wish to determine if our proposed capture techniques are appropriate for the conditions under which we will be working. The null hypothesis for this research project is that fawn survival does not vary between study areas and therefore habitat treatment/improvement efforts do not enhance over-winter fawn survival. The alternative hypothesis is that habitat treatments improve survival and a general 32 �increase in fawn survival should be observed as habitat quality increases. This pilot study is designed to measure fawn survival under optimal and poor habitat conditions. The pilot study will provide preliminary estimates of the difference in fawn survival between high and low quality habitat. Alternative approaches for quantifying the effectiveness of habitat treatments on fawn survival, including a treatment/control design which experimentally tests this question, have been discussed. However, due to numerous logistical limitations, a feasible field experiment incorporating random selection and replication of treatment and control areas isn't achievable. A quasi-experiment incorporating a single treatment and control area where fawn survival would be measured in each area before and after administration of a treatment in the treatment area was designed and evaluated. While this study may have been logistically feasible, lack of replication would have limited inference, and the study would have been subject to the various problems associated with having only one treatment and control area (e.g. an unplanned fire in the control area would nullify study results). Further, a time frame of >5 years would be required to fully evaluate the impact of the imposed habitat treatment. We concluded that the design described in this study plan is the most effective approach to evaluate the effects of habitat treatments across a large landscape given the inherent logistical constraints of adequate replication and duration of the study. D. Approach 1. Procedures A. Capture and Handling Methods: Twenty-five mule deer fawns will be captured and radio-collared in each of the 2 control study areas. In the high quality control, we will attempt to capture all fawns with baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992). If needed, helicopter netgunning will be used to complete the necessary sample in the high quality control. In the low quality control, all fawns will be captured via helicopter net-gunning (Barrett et al. 1982, van Reenen 1982). The confounding of area and capture methods should not be a problem, because White and Bartmann (1994) found no significant difference in survival of fawns 2 and 4 weeks after capture by these 2 methods for samples of 86 and 79 fawns. Captures will occur in December 2004. B. Survival Monitoring: On a daily basis, from December through May, we will monitor the radioed fawns in order to document live/death status. This will allow us to determine accurately the date of death and estimate the proximate cause of death. 2. Use of Pilot Results We will use the data collected during this research to evaluate preliminarily the expected magnitude of difference in fawn survival between areas with high quality habitat improvements and low quality areas with no habitat improvements. Power analyses (α = 0.10, β = 0.80) indicate that similar measurements will be needed from 12 additional study areas during the next 4 winters in order to detect whether or not a 0.20 difference in fawn survival exists between low and high quality areas. Pilot data will be used to determine if such a study design is useful and feasible, and will provide evidence of whether our proposed capture methods will achieve the necessary sample sizes during the next four winters. E. Location of Work This pilot study will be conducted on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado. The proposed high quality control area is located on Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). This area has received and continues to receive 33 �habitat treatments that are intended to benefit mule deer. Additionally, the high qualtiy control is in relatively close proximity to agricultural lands that provide high quality, succulent forage immediately preceding the onset of winter and immediately following spring melt. The proposed low quality control area is located on Sowbelly and Tatum draws (approximately 15km west of Delta, CO). This area is located in a segment of winter range that has not received any habitat treatments, is not in close proximity to agricultural lands and is in an advanced stage of pinyon-juniper succession (i.e. old growth trees, poor or non-existent understory and low frequency of shrub component). F. Schedule and Work Assigned To December 2004.....................................................Capture and deploy 25 VHF (172-174 MHZ frequency band) radio collars, fitted with growth/time deteriorating release mechanism, on fawns in each of two control study areas December 2004 - May 2005..................................Monitor fawns for survival and retrieve collars as necessary April 2005 - July 2005..........................................Conduct habitat quality assessments on random study areas July 2005 - August 2005.......................................Produce preliminary results on the effectiveness of capture techniques and use pilot data to refine full-scale study plan as warranted. October 2005.........................................................Retrieve collars that have dropped off fawns G. Resource Requirements Salaries of permanent and temporary employees, as well as other logistical costs (vehicles and flights) will be covered by existing game cash funds in the CDOW mule deer research and other CDOW programs. Expenditures specific to this study will include: $11,200.................................................................50 radio collars $15,000.................................................................Approximate costs for helicopter net-gunning 25 mule deer fawns $800......................................................................Radio telemetry receivers $300......................................................................Miscellaneous drop net equipment $100......................................................................Bait for drop netting $27,400......................................................................Total 34 �H. Literature Cited BARRETT, M. W., J. W. NOLAN, AND L. D. ROY. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. BARTMANN, R. M. 1983. Composition and quality of mule deer diets on pinyon-juniper winter range, Colorado. Journal of Range Management 36:534-541. —————, G. C. WHITE, AND L . H. CARPENTER. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. BISHOP, C. J., G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2004. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado, USA. CONNOLLY, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, Nebraska, USA. GILL, R. B. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Denver, Colorado, USA. RAMSEY, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. SCHMIDT, R. L., W. H. RUTHERFORD, AND F. M. BODENHAM. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. UNSWORTH, J. W., D. F. PAC, G. C. WHITE AND R. M. BARTMANN. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. VAN REENEN, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. WHITE, G. C., AND R. M. BARTMANN. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. 35 �36 �Colorado Division of Wildlife July 2004 – June 2005 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 4 : : : : Federal Aid Project: W-185-R : Division of Wildlife Mammals Research Deer Conservation Effect of Nutrition and Habitat Enhancements on Mule Deer Recruitment and Survival Rate Period Covered: July 1, 2004 - June 30, 2005 Authors: C. J. Bishop, G. C. White, D. J. Freddy, and B. E. Watkins Personnel: D. L. Baker, L. Baeten, T. M. Banulis, E. J. Bergman, S. K. Carroll, M. J. Catanese, D. L. Coven, K. Crane, M. L. DelTonto, B. Diamond, B. deVergie, P. Ehrlich, D. Gallegos, J. Garner, L. Gepfert, R. B. Gill, D. Hale, J. L. Grigg, H. J. Halbritter, R. Harthan, M. D. Johnston, W. J. Lassiter, C. T. Larsen, T. Mathieson, J. W. McMillan, G. C. Miller, M. W. Miller, J. D. Nicholson, J. A. Padia, T. M. Pojar, R. M. Powers, J. E. Risher, C. A. Schroeder, W. G. Sinner, C. M. Solohub, M. H. Swan, K. Taurman, J. A. Thayer, M. A. Thonhoff, C. E. Tucker, R. M. Wertsbaugh, L. L. Wolfe, CDOW; H. VanCampen, CSU; D. Felix, Olathe Spray Service; T. R. Stephenson, California Fish and Game; L. H. Carpenter, WMI; J. Sazma, B. Welch, BLM. Project support received from Federal Aid in Wildlife Restoration, Mule Deer Foundation, and Colorado Habitat Partnership Program. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We measured mule deer (Odocoileus hemionus) population parameters in response to a nutrition enhancement treatment to evaluate the relative importance of habitat quality as a limiting factor of mule deer in western Colorado. During November 2000 – June 2004, we captured and radio-collared 810 individual mule deer evenly distributed among treatment and control units on the Uncompahgre Plateau in southwest Colorado. Our sample included 293 adult females, 154 of which received vaginal implant transmitters (VITs), 241 6-month-old fawns, and 276 newborn fawns born from either treatment or control adult does. We enhanced the nutrition of deer in the treatment unit by providing a safe, pelleted supplemental feed on a daily basis from December through April each winter. The treatment unit during winters 2000−01 and 2001−02 became the control unit during winters 2002−03 and 2003−04, and vice versa. Thus, the treatment effect was replicated across each experimental unit. Early winter fawn:doe ratios were measured using helicopter and ground classification surveys the year following treatment delivery to determine whether fawn production and survival increased as a result of enhanced nutrition of adult females. During winters 2001–02 through 2003−04, we measured pregnancy rates, fetus rates, and body condition of treatment and control adult does using ultrasonography. We measured fetus survival and neonate survival by using VITs to help locate and radio-collar newborn fawns born from treatment 37 �and control does. We also measured overwinter fawn survival rates in response to the treatment. Estimated percent body fat of adult does during late February and early March, 2002−04, was higher (F1, 148 = 153.41, P < 0.001) for treatment deer (9.8%, SE = 0.36, n = 78) than control deer (4.3%, SE = 0.26, n = 76). Serum thyroid hormone concentrations, measured only in 2003 and 2004, were higher in treatment does than control does (F4, 108 = 46.59, P < 0.001). Pregnancy and fetus rates were similar among treatment and control does. The pregnancy rate of adult does was 0.95 (SE = 0.036, n = 38) and the fetus rate was 1.80 fetuses/doe (SE = 0.10, n = 36) during 2002. Rates were similar in 2003, where we measured a pregnancy rate of 0.92 (SE = 0.034, n = 63) and a fetus rate of 1.74 fetuses/doe (SE = 0.069, n = 50) which included 5 yearlings (the fetus rate excluding yearlings was 1.82 fetuses/doe, SE = 0.066, n = 45). In 2004, pregnancy rate was 0.94 (SE = 0.029, n = 66) and fetus rate was 1.97 fetuses/doe (SE = 0.053, n = 60), which included 4 yearlings (fetus rate excluding yearlings was 2.00 fetuses/doe, SE = 0.051, n = 56). Based on multiple early winter age classification surveys, we lacked evidence to determine whether the winter nutrition enhancement treatment had any effect on neonatal production and survival during 2001, which provided additional incentive to directly measure fetus and neonate survival. During 2002−2004, fetus-neonate survival from 1 March−15 December was higher (χ21 = 3.846, P = 0.050) for treatment fawns (S(t) = 0.528, SE = 0.027) than control fawns (S(t) = 0.401, SE = 0.025). Survival data coupled with early winter age classification surveys provided evidence the nutrition enhancement treatment increased December fawn recruitment during 2002−2004. During 15 December– 15 June, 2001−2004, the overwinter survival rate of fawns was greater (χ21 = 18.781, P < 0.001) in the treatment unit (S(t) = 0.895, SE = 0.029) than in the control unit (S(t) = 0.655, SE = 0.044). Using a staggered entry survival process with data combined over years, survival of treatment fetuses to 1 year of age (S(t) = 0.458, SE = 0.031) was 0.18 higher (χ21 = 13.20, P < 0.001) than survival of control fetuses to 1 year of age (S(t) = 0.276, SE = 0.026). The finite rate of population increase, λ, based on our measurements of treatment population parameters was 1.20, which would cause the deer population to double in approximately 4 years. The finite rate of increase calculated from control deer was 1.04, indicating a stable or slightly increasing population. The nutrition enhancement treatment therefore had a dramatic effect on deer population performance, indicating habitat quality was ultimately limiting the population. Our results provide a foundation for focusing deer management efforts on improving habitat quality in western Colorado pinyon-juniper (Pinus edulis-Juniperus osteosperma) ecosystems with corresponding research efforts to quantify the effects of habitat manipulations on deer performance. 38 �WILDLIFE RESEARCH REPORT EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES CHAD J. BISHOP, GARY C. WHITE, DAVID J. FREDDY, AND BRUCE E. WATKINS P. N. OBJECTIVES 1. To determine experimentally whether enhancing mule deer nutrition during winter and early spring via supplementation increases fetus survival, neonate survival, overwinter fawn survival, or ultimately, population productivity. 2. To determine experimentally to what extent habitat treatments replicate the effect of enhanced nutrition from supplemental feeding. SEGMENT OBJECTIVES 1. Radio-monitor and measure survival of the sample of radio-collared mule deer adult does and fawns. 2. Measure early winter fawn:doe ratios using both aerial helicopter surveys and ground classifications of deer groups associated with radio-collared adult does. 3. Summarize and analyze data and publish information in an annual Job Progress Report. 4. Complete a peer-reviewed manuscript for publication in a scientific journal pertaining to the effectiveness of vaginal implant transmitters for capturing mule deer neonates exclusively from radiomarked adult does (Appendix I). INTRODUCTION Mule deer (Odocoileus hemionus) numbers apparently declined during the 1990s throughout much of the West, and have clearly decreased since the peak population levels documented during the 1940s−1960s (Unsworth et al. 1999, Gill et al. 2001). Biologists and sportsmen alike have concerns as to what factors may be responsible for declining population trends. Although previous and current research indicates multiple interacting factors are responsible, habitat and predation have received the focus of attention. A number of studies have evaluated whether predator control increases deer survival, yet results are highly variable (Connolly 1981, Ballard et al. 2001). Together, predator control studies with adequate rigor and statistical power indicate predation effects on mule deer are variable as a result of time-specific and site-specific factors. Studies which have demonstrated deer population responses to predator control treatments have failed to determine whether predation is ultimately more limiting than habitat when considering long term population changes. Numerous research studies have evaluated mule deer habitat quality, but virtually no studies have documented population responses to habitat improvements. In many areas where declining deer numbers are of concern, predation is common yet habitat quality appears to have declined. The question remains as to whether predation, habitat, or some other factor is more limiting to mule deer in these situations, and whether habitat quality can be improved for the benefit of deer. It may also be that no single factor is responsible for observed deer declines, and a more comprehensive understanding of multi-factor interactions is needed. We designed and implemented a field experiment where we measured deer population responses to a nutrition enhancement treatment to further understand the causative factors underlying observed deer population dynamics. We conducted the study on the Uncompahgre Plateau in southwest Colorado, where several predator species were present in abundant numbers: coyotes (Canis latrans), mountain lions (Felis concolor), and bears (Ursus americanus). In addition to predation, myriad diseases in combination have proximately affected survival of the Uncompahgre deer population (Pojar and Bowden 39 �2004, B. E. Watkins, Colorado Division of Wildlife, unpublished data). Predator numbers were not manipulated in any manner during the course of the study. All factors were left constant with the exception of deer nutrition. Deer nutrition was enhanced by providing supplemental feed to deer occupying a treatment area during winter. We measured December fawn recruitment and overwinter fawn survival in response to the treatment to determine whether deer nutrition was ultimately more limiting than predation or disease. The second phase of the research will incorporate habitat manipulation treatments. The treatments will consist of prescribed fire or mechanical techniques to set back succession of pinyon-juniper (Pinus edulis-Juniperus osteosperma) habitat in an effort to improve the vigor and quality of winter habitat for mule deer. Deer population responses will be measured in relation to the habitat manipulations in the same manner as the supplemental feed. Thus, the experiment evaluates whether nutritional quality of winter range habitat is ultimately more limiting than other factors in a lateseral pinyon-juniper and sagebrush (Artemisia spp.) landscape, and if so, whether habitat can be effectively improved for mule deer. The results advance our understanding of multi-factor interactions, with direct implications for mule deer management. STUDY AREA We non-randomly selected two experimental units (A−B) within mule deer winter range on the Uncompahgre Plateau (Figure 1) to facilitate a cross-over experimental design for evaluating the effects of enhanced deer nutrition during winter on annual population performance. We used the following criteria to select experimental units: 1.) Deer densities (≥80 deer/mi2): we selected areas where deer densities were sufficient to meet sample size requirements within the experimental unit, while simultaneously selecting areas that would require feeding no more than 600−800 animals during a normal winter; 2.) Buffer zones: we selected areas such that experimental units would be separated by several miles of non-treatment area (buffers) to prevent deer from occupying more than one experimental unit; 3.) Similarity: we selected areas that comprised relatively similar habitat complexes and deer densities that were representative of the overall area; 4.) Elk populations: we selected areas in an effort to minimize the number of elk present during normal winters. Units A and B received the nutrition enhancement treatment in a cross-over experimental design to address P.N. Objective 1. Unit A served as the treatment unit, while Unit B served as the control, for the first 2 winters of research (2000 – 2002). During winters 2002−03 and 2003−04, Unit B received the treatment while Unit A served as the control. Upon completion of P.N. Objective 1, additional winter range experimental units will be used to conduct phase 2 of the research, or P.N. Objective 2. Habitat in treatment units will be manipulated to set back plant succession, while habitat in control units will remain unchanged throughout the experiment. Experimental units A and B were defined as follows (Figures 2 and 3): (1) Experimental unit A included the Colona Tract of the Billy Creek State Wildlife Area and adjacent land, located approximately 13 km south of Montrose, CO adjacent to U.S. Hwy 550 South. The experimental unit was located within the Colona USGS 7.5 Minute Quadrangle, and roughly included the polygon defined by the following Zone 13 UTM coordinates: (1) 254000 E, 4250200 N; (2) 252700 E, 4249400 N; (3) 254700 E, 4245600 N; and (4) 256200 E, 4246600 N. (2) Experimental unit B included Shavano Valley and adjacent land extending west to the Dry Creek Rim. Shavano Valley is located approximately 13 km west of Montrose, CO. The experimental unit was located within the Dry Creek Basin and Montrose West Quadrangles (USGS 7.5 Minute), and 40 �roughly included the polygon defined by the following Zone 13 UTM coordinates: (1) 238400 E, 4262600 N; (2) 232400 E, 4256700 N; (3) 235000 E, 4253600 N; and (4) 239500 E, 4258200 N. In late April and May, prior to fawning, deer from the winter range experimental units migrated to summer range. We defined the summer range study area by movements of the radio-collared deer captured on winter range; summer range encompassed >1000 mi2 covering the southern portion of the Uncompahgre Plateau and adjacent San Juan Mountains (Figure 2). The summer range study area extended north to the Dry Creek river drainage on the Uncompaghre Plateau, south to Mineral Creek near Silverton, CO, east to the Big Blue River drainage, and west to the San Miguel River canyon. However, a majority of the radio-collared deer summered on the Uncompahgre Plateau between Dry Creek to the north and Highway 62 to the south. Winter range elevations ranged from 1830 m (6000 ft) in Shavano Valley to 2318 m (7600 ft) adjacent to the Dry Creek Rim above Shavano Valley. Winter range habitat was dominated by pinyonjuniper with interspersed sagebrush adjacent to agricultural fields in the Shavano and Uncompahgre Valleys. Summer range elevations occupied by deer ranged from 1891 m (6200 ft) in the Uncompahgre Valley to 3538 m (11,600 ft) in Imogene Basin southwest of Ouray, CO. Summer range habitats were dominated by spruce-subalpine fir (Picea spp.-Abies lasiocarpa), aspen (Populus tremuloides), sagebrush, ponderosa pine (Pinus ponderosa), Gambel oak (Quercus gambelii), and to a lesser extent, pinyon-juniper at lower elevations. METHODS Response Variables We measured fetal and neonatal survival rates, early winter fawn:doe ratios, and overwinter fawn survival rates of deer occupying the treatment and control units. We delivered the nutrition enhancement treatment to deer from December through April, assessed fetus survival during June, measured neonate survival from June to December, and fawn:doe ratios during December−February (1 year after the treatment was initiated). We measured overwinter fawn survival from December to June in direct response to the current winter’s treatment. Our measurements determined whether enhanced winter nutrition of adult does increased subsequent newborn fawn production and survival, and whether enhanced winter nutrition of 6−12-month old fawns increased overwinter fawn survival. Ultimately, these measurements provided an assessment of the effect of winter range habitat quality on yearling recruitment, and thus population productivity. We also measured overwinter and annual survival of adult does as a function of enhanced winter nutrition. Sample Size Fetus/Neonate Survival: Fetus and neonate sample sizes were not independent of one another because each resulted from the sample size of radio-collared does. We therefore needed a target sample size of either fetuses or neonates to generate our adult doe sample size. We based our sample size calculations on quantifying neonate survival because it was our highest priority and we could generate reliable estimates. Target fetus sample sizes were difficult to estimate because of uncertainty identifying fetus fates. That is, many fetuses measured in utero during winter were not accounted for as live or dead at parturition. Fetus survival rates could only be measured from some unpredictable fraction of the radiocollared doe sample, making sample size calculations of limited use. For neonate survival, a sample size of 40 neonates per experimental unit per year would provide power of 0.81 to detect a difference of 0.15 in survival between the 2 experimental units if survival among control fawns was 0.40. We assumed a control survival rate of 0.40 based on previous neonate survival rates measured on the Uncompahgre (Pojar and Bowden 2004) in combination with December fawn:doe ratios measured during the late 1980s and 1990s, when the Uncompahgre population declined (B. E. Watkins, Colorado Division of Wildlife, 41 �unpublished data). We considered 40 neonates per experimental unit per year a minimum sample size because we ideally wanted to detect a difference in neonate survival of <0.15 between experimental units. Based on Bishop et al. (2002), we determined that 60 radio-collared does (30 treatment and 30 control) equipped with vaginal implant transmitters (VITs) would be necessary to capture a minimum of 80 newborn fawns. We also assumed that some fawns would be captured from other treatment and control radio-collared does not equipped with VITs. The 60 radio-collared does with VITs were also used to evaluate fetus survival; however, logistical constraints limited the power of fetus survival comparisons among experimental units. Early winter fawn:doe ratios: We desired to detect an effect size, i.e., an increase in fawn:doe ratios in response to the treatments, in the range of 15 to 20 fawns per 100 does. These values were based on population models with overwinter fawn survival of 0.444, adult female survival of 0.853, and December fawn:doe ratios of 66 fawns per 100 does to obtain a stationary population (Unsworth et al. 1999). Based on surveys of the Uncompahgre deer population during the 1990s, the standard deviation of the fawns:100 does ratio for groups with at least one adult female was 57, with a mean of 41. Using an expected standard deviation of 57, the standard error of the mean fawns:100 does ratio for 40 radiocollared does is 57/(401/2) = 9.0, which is the expected standard deviation of measured fawns:100 does ratios on each experimental unit. We assessed power using a two-sample t-test with a sample size of 4, representing the 4 years of the study where fawn:doe ratios were measured in response to enhanced nutrition. Our power to detect an increase of 20 fawns per 100 does based on classification of 40 radiocollared doe groups in each experimental unit was about 0.87. Overwinter fawn survival: Our sample size of 40 fawns per experimental unit per year provided a power of 0.81 to detect a difference of 0.15 in survival between the 2 experimental units assuming a control survival rate of 0.40. We expected to see an increase in fawn survival (effect size) of approximately 0.15, because this was the difference measured in the density reduction experiment conducted by White and Bartmann (1998). We assumed a control survival rate of 0.40 based on longterm data from Colorado, Idaho, and Montana (Unsworth et al. 1999). However, recent data from 5 deer populations in Colorado indicates overwinter fawn survival has commonly been ≥70% during the past 6 years (Colorado Division of Wildlife, unpublished data). Adult and 6-month Old Fawn Capture We captured adult does and 6-month-old fawns during November and December using baited drop nets (Ramsey 1968, Schmidt et al. 1978) and helicopter net guns (Barrett et al. 1982, van Reenen 1982). We baited drop nets with certified weed-free alfalfa hay and apple pulp. We used drop nets as the principle capture technique for a 3−4 week capture period; we then used helicopter net-gunning at the end of the drop-net capture to secure the remainder of deer needed to meet our target sample sizes. All deer were hobbled and blind-folded after being captured. We used stretchers to carry deer away from the net when using drop nets. Deer were fitted with nylon-belting radio collars equipped with mortality sensors; pulse rate increased after remaining motionless for 4 hours. We placed permanent collars on adult females and temporary collars on fawns. To make collars temporary, we cut one end of the collar in half and reattached the two ends using rubber surgical tubing; fawns shed the collars ≥6 months post-capture. We stitched a rectangular piece of flexible plastic (Ritchey® neck band material) engraved with a unique identifier to the side of each collar. The unique identifier consisted of 2 symbols for adult females, and 1 symbol on 2 different colors of plastic for fawns. We used the identifiers to visually identify deer from the ground, which allowed us to effectively document use of the treatment, measure fawn:doe ratios, and assess experimental unit population size via mark-resight estimators. We recorded mass (kg), hind foot length (cm), and chest girth (cm) of each deer, and collected blood samples to evaluate disease prevalence. 42 �During late February and early March, we captured an additional 30 adult female deer in each experimental unit by net-gunning. Captured deer were ferried by the helicopter to a central processing location, where deer were carried by stretchers to a tent for handling. We used ultrasonography to measure pregnancy status, fetal rate, and body condition of each captured deer. We retained and radiocollared pregnant does only. We then inserted a vaginal implant transmitter (VIT) in each doe as a technique for locating the timing and location of her birth site the following June. We also recorded the weight (kg), hind foot length (cm), and chest girth (cm) of each deer, and collected blood samples to evaluate disease prevalence. Body Condition and Reproductive Status We estimated body fat of treatment and control adult does during mid-late winter using an Aloka 210 (Aloka, Inc., Wallinford, Conn.) or SonoVet 2000 (Universal Medical Systems, Bedford Hills, NY) portable ultrasound unit with a 5 MHz linear transducer. We measured maximum subcutaneous fat thickness on the rump (MAXFAT) following the methodology of Stephenson et al. (1998, 2002). We also measured thickness of the longissimus dorsi muscle via ultrasound (Cook et al. 2001, Stephenson et al. 2002). A small area of hair was shaved to ensure contact between the transducer and the skin. Lubricant was applied to the shaved area for conduction purposes and fat and muscle thickness were measured using electronic calipers. We coupled the ultrasound measurements with body condition scores (BCS) obtained from palpation of the ribs, withers, and rump (Cook 2000). MAXFAT and rump BCS measurements were combined into a condition index used to estimate percent body fat (Cook and Cook 2002): % Fat = -6.6387617 + 7.4271417x – 1.11579443x2 + 0.07733803x3 where x = rLIVINDEX = (MAXFAT – 0.15) + rump BCS (if MAXFAT < 0.15, then rLIVINDEX = rump BCS). The rLIVINDEX and body fat regression was initially developed and validated for elk by Cook et al. (2001), and then modified by incorporating a validation of MAXFAT for mule deer performed by Stephenson et al. (2002). We also evaluated differences in serum thyroid hormone concentrations between treatment and control adult does during mid-late winter. Specifically, we measured total thyroxine (T4), free T4 (FT4), total tri-iodothyronine (T3), and free T3 (FT3) following the methodologies of Watkins et al. (1983, 1991). Blood samples were collected at the time of capture, and serum hormone analyses were performed by the Michigan State University Animal Health Diagnostic Laboratory (East Lansing, Michigan). We compared serum thyroid hormone concentrations between treatment and control adult does, and also compared hormone levels to body fat estimates derived from the ultrasonography. We quantified reproductive status (Stephenson et al. 1995, Andelt et al. 2004) with ultrasound via transabdominal scanning using a 3 MHz linear transducer. We searched for fetuses by scanning a portion of the abdomen that was shaved caudal to the last rib and left of the midline. We systematically searched each uterine horn to identify fetal numbers ranging from 0 to 3. Whenever possible, we measured eye diameter of each fetus to approximately estimate fetal age and parturition date. Vaginal Implant Transmitters (VITs) We used VITs manufactured by Advanced Telemetry Systems, Inc. (Isanti, MN). The VIT was 76 mm long, excluding antenna length, and had 2 silicone wings with a width of 57 mm when fully spread apart. The silicone wings were used to retain the transmitter in the vagina until parturition. The VIT weighed 15 grams and contained a 10−28 lithium battery programmed to a 12-hour on/off cycle. The diameter of the transmitter (excluding wings) was 14 mm, and was encased in an impermeable, water-proof, electrical resin. The transmitter contained an embedded heat-sensor which dictated the frequency pulse rate. When the heat sensor dropped below 90°F, synonymous with transmitter expulsion from the deer, the pulse rate changed from 40 PPM to 80 PPM. VIT batteries were programmed to be active from 0430 to 1630 hrs prior to daylight savings, and thus were active from 0530 to 1730 hrs after daylight savings and during the fawning period. We inserted VITs into deer using a vaginoscope 43 �(Jorgensen Laboratories, Inc., Loveland, CO) and alligator forceps. The vaginoscope was 6” long with a 5/8” internal diameter and had a machined end (smooth surface) to minimize trauma when inserted into the vagina. A discreet mark was placed on the applicator showing approximate insertion distance. We obtained the length of a typical mule deer vaginal tract by taking measurements from road-killed deer and other fresh deer carcasses obtained in the study area. Prior to use in the field, VITs were sterilized using chlorhexidine, air-dried, and sealed in a 3” × 8” sterilization pouch. We used sterilization containers with diluted chlorhexidine on site during capture to sterilize the vaginoscope and alligator forceps between each use. We used a new pair of nitrile surgical gloves to handle the vaginoscope and VIT for each deer. To insert a VIT, the plastic wings were folded together and placed into the end of the vaginoscope. We liberally applied sterile KY Jelly® to the scope and inserted it into the vaginal canal until the tip of the VIT antenna was approximately flush with the vulva. We used the alligator forceps, which extended through the vaginoscope, to firmly hold the VIT in place while the scope was pulled out from the vagina. The VIT silicone wings spread apart upon removal of the scope to hold the transmitter in place. The transmitter antenna was typically flush with the vulva, but on occasion extended up to 1 cm beyond the vulva. The tip of the antenna was encapsulated in a wax bead to protect the deer. All capture and handling procedures, including VIT techniques, were approved by the Colorado Division of Wildlife’s Animal Care and Use Committee (project protocols 11−2000 and 1−2002). Neonate Fawn Capture All radio-collared adult does were relocated from the air during late May to identify likely fawning areas. During each morning of June we checked VIT signal status by aerially relocating radiocollared does having VITs. Implant radio-signals could not be easily monitored from the ground because of weak signal strength and a large study area. Flights began at 0530 hours and were usually completed by 1000–1100 hours. Early flights were necessary to detect fast signals because temperature sensors of VITs expelled in open habitats and subject to sunlight often exceeded 90°F by mid-day, which caused VITs to switch back to a slow (i.e. prepartum) pulse. When a fast (i.e. postpartum) pulse rate was detected, we ground-tracked both the VIT and radio-collar frequencies simultaneously because the shed VIT and adult doe were typically in close proximity to one another. We attempted to observe behavior of the collared doe, establish whether the VIT was shed at a birth site, and search for fawns in the vicinity of the doe and expelled VIT. In cases where the doe had moved away from the VIT (e.g. >200 m), we located the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawn(s) were present, and subsequently located the collared doe to search for fawns at her location. We attempted to account for each doe’s fetuses as live or stillborn fawns in order to quantify in utero fetus survival from February to birth. All personnel wore surgical gloves when handling fawns to help minimize human scent. We placed a drop-off radio-collar on each live fawn; radio collars were constructed with elastic neck-band material to facilitate expansion. Hole-punched, vinyl-belting tabs extended from the end of the elastic and from the transmitter for attachment purposes. We made collars temporary by cutting the vinyl tab extending from the elastic and reattaching the belting with latex tubing, which caused the collars to shed from the animal >6 months post-capture. Some collars were shed prematurely (i.e. 4−5 months postcapture) in association with fences during fall migration. For each fawn, mass (kg) and hind foot length (cm) were recorded, and a nasal swab sample was collected to screen for Bovine Viral Diarrhea. We then recorded basic vegetation characteristics of the birth site and promptly exited the site. We ground-relocated most of the radio-collared does not receiving VITs approximately every other day during June in an attempt to capture additional fawns from treatment and control does. We did the same for any VIT doe whose implant failed because of premature expulsion or battery failure. We relied on doe behavior and searches in the vicinity of the collared does to locate fawns. We worked in 44 �pairs and partitioned the study area into segments, whereby each 2-person team was responsible for one segment. We used 3−4 teams during 2002 and 5−6 teams during 2003 and 2004. Measurement of Survival Rates and Fawn:Doe Ratios We measured survival rates by radio-monitoring collared deer from the ground and air to determine fate (i.e. lived or died). We also attempted to determine the cause of each mortality, with a primary goal of distinguishing between predation and non-predation mortality causes. We radiomonitored deer from the ground on a daily basis year-round and from the air on approximately a biweekly basis. We detected signals from nearly all radio-collared deer each day during winter, which typically allowed us to arrive at mortality sites within 24 hours of the mortality event. During summer and migration periods, deer were distributed widely and thus were more difficult to radio-monitor. All radiocollared neonates were checked daily throughout the summer and fall, whereas some adult and yearling deer could not be ground-monitored on a routine basis. In result, we typically located neonate mortalities within 24 hours of death, but some adult deer mortalities were not detected for several days, or on rare occasion, for one or more weeks. Fresh, intact neonate carcasses were collected and submitted to the Colorado Division of Wildlife’s Wildlife Health Laboratory or the Colorado State University Diagnostic Laboratory for necropsy and tissue analyses. Fresh, intact adult and 6-month-old fawn carcasses were also submitted for laboratory necropsy when feasible. Field necropsies were performed on all other deer mortalities, and when appropriate, tissue samples were collected and submitted for analysis. Each winter we used the radio-collared does to measure fawn:doe ratios in each experimental unit. The resulting fawn:doe ratio was a measurement of the previous year’s treatment effect. We measured fawn:doe ratios using 2 techniques: (1) We located the sample of radio-collared does in each experimental unit from a fixed-wing airplane, and used the set of locations to define boundaries for the experimental unit. Shortly after (i.e. 1−2 days), we used a helicopter to systematically fly the defined unit and classify all deer groups encountered. For each group, we documented whether a radio-collared doe was present. (2) We located each radio-collared doe by radio telemetry from the ground. The group of deer with the collared doe was counted and classified by age and sex. Both methods were employed to gather as much information as possible to determine whether there was a treatment effect. The “true” value cannot be measured perfectly because of the inherent biases and potential sources of error associated with each technique. Thus, by employing both techniques, we had a greater chance of fully understanding whether the treatment caused an effect. Treatment Delivery We enhanced deer nutrition in the treatment experimental unit by providing a safe, pelleted supplemental feed. The supplemental feed was developed through extensive testing with both captive and wild deer (Baker and Hobbs 1985, Baker et al. 1998), and has been safely used in both applied research and management projects. We distributed pellets daily using 4wd pickup trucks, ATVs, and snowmobiles on primitive roads throughout the experimental unit to provide a food source for the entire deer population in the treatment unit. We carried each 50 lb. bag of pellets ≤200 m from the vehicle and distributed it by hand in approximately 20−30 small piles of feed in a linear fashion. We distributed numerous bags in successive order to create straight lines of feed that spanned most of the treatment area, which prevented animal concentrations. Our feeding technique also prevented dominant animals from restricting access to the food supply because of the large area over which pellets were distributed. We attempted to supply pellets ad libitum such that residual pellets remained when the next day’s ration was provided. We closely monitored collared deer to ensure that treatment deer remained in the experimental unit and actually consumed the feed, and to make sure that non-treatment deer remained in the control unit, which they did. The few treatment adult does that distinctly moved away from the treatment unit were withdrawn from the sample for purposes of measuring treatment effects. However, to avoid any biases, all 6-month-old fawns captured in the treatment unit were included in survival analyses regardless 45 �of whether they accessed the supplement or not. Some fawns died shortly after capture (i.e. 2−3 weeks), before we could document whether they had access to the feed. Censoring these individuals would have biased treatment survival high relative to control survival. Also, very few fawns that survived more than 2−3 weeks moved away from the treatment unit. The pelleted ration was commercially produced in the form of 2×1×0.5-cm wafers (Baker and Hobbs 1985). Feed quality (e.g. digestible energy, protein) vastly exceeded those of typical winter range deer diets; exact constituent values are provided by Baker et al. (1998). When provided ad libitum, the feed should have allowed deer to meet or exceed nutritional requirements for growth and maintenance (Ullrey et al. 1967, Verme and Ullrey 1972, Thompson et al. 1973, Smith et al. 1975, Baker et al. 1979, Holter et al. 1979). The basis for feeding such high quality pellets was to ensure that the treatment (enhanced nutrition) was effectively delivered to the deer. Our intent was not to determine the exact level of nutrition necessary to increase fawn recruitment, but rather to determine if nutrition was a significant limiting factor to recruitment. We will rely on habitat manipulation treatments to evaluate what exactly can be done via management to increase fawn survival and recruitment if nutrition is deemed a critical limiting factor. Statistical Methods We estimated deer numbers in each experimental unit during the first year of research using helicopter and ground mark-resight surveys. We used the joint hypergeometric maximum likelihood estimator for helicopter surveys and the Bowden estimator for ground surveys, and we analyzed data in Program NOREMARK (Neal et al. 1993, Bowden 1993, White 1996). We used a general linear model in PROC GLM in SAS (SAS Institute 1989) to test for differences in estimated percent body fat between treatment and control adult does and a multivariate model to test for differences in T4, FT4, T3, and FT3 thryoid hormones between treatment and control does. We used PROG REG (SAS Institute 1989) to evaluate the relationship between estimated percent body fat and serum thyroid hormone concentrations. We entered all fawn:doe ratios from helicopter surveys into the CDOW Deer, Elk, and Antelope Management (DEAMAN) database (G. C. White, Colorado State University, software) and computed standard errors based on groups (Bowden et al. 1984). We analyzed fawn:doe ratios from ground surveys using PROC MIXED in SAS (SAS Institute 1997). We used a reduced model with experimental unit as the independent variable; we considered experimental unit as a fixed effect and radio-collared does within an experimental unit as random effects. We analyzed fetus survival with a binomial survival rate from the subset of does where all fetuses had known fates. We also indirectly analyzed fetus survival by comparing the February fetus rate with the number of live newborn fawns/doe observed in June using a change-in-ratio estimator (White et al. 1996). We estimated neonate and overwinter fawn survival and adult doe survival using a Kaplan-Meier survival analysis (Kaplan and Meier 1958, Pollock et al. 1989), and we contrasted survival among experimental units using chi-square analyses. We used a common entry date for analyzing neonate survival because staggered entry would have biased survival rates low due to early mortalities that occurred before most of the sample was captured. We analyzed continuous fetus-neonate-overwinter fawn survival from March of one year to June of the following year using a staggered-entry Kaplan-Meier survival analysis (Pollock et al. 1989). All neonates were entered into the survival analysis on a common date rather than the exact date of capture for the same reason mentioned above. We computed the finite rate of increase, λ, for treatment and control deer by constructing a deterministic age-structured population model using measured pregnancy and fetus rates, fetus survival, neonate survival, overwinter fawn survival, and annual adult doe survival. Results are based on preliminary analyses and should be treated as such. Other results are presented as data summaries incorporating means and standard errors, or in some cases, raw data values. 46 �RESULTS AND DISCUSSION Deer Capture During November and December 2000−2003, we captured and radio-collared 139 adult female mule deer evenly distributed among the treatment and control units. We also captured and radio-collared 241 6-month-old fawns during November and December 2001−2003 (40 fawns/unit/year). Due to budgeting constraints, we were unable to radio-collar 6-month old fawns during 2000. We captured an additional 154 adult females during late February and early March 2002−2004 and equipped them with radio collars and VITs. During June 2002−2004, we captured and radio-collared 276 newborn fawns from radio-collared adult females. Thus, the following results are based upon radio-monitoring of 810 individual mule deer evenly distributed among treatment and control units during November 2000−June 2004. Treatment Delivery 2000−01: We distributed 88 tons of supplemental pellets from December 15, 2000, through April 19, 2001. We distributed an average of 0.85 tons of feed each day throughout 22 feeding sites across the 2.3 mi2 treatment unit during most of the winter and spring. Deer were fed ad libitum because there was always residual feed remaining the next day during the feeding routine. We distributed each sack in approximately 20−30 distinct, small piles, resulting in >1000 small piles of feed throughout the treatment unit. Deer were able to effectively access the feed in small groups, and no aggression was ever observed among deer seeking access to the feed. Deer adapted to the pelleted supplement immediately and utilized it extensively throughout the winter. We continually monitored deer use of the feed from ground observation points, where we obtained 440 visual observations of radio-collared does consuming the feed. These observations, coupled with daily radio-monitoring and periodic aerial relocations, indicated 32 of the 37 radio-collared treatment does spent the entire winter and spring within the boundaries of the treatment unit and received the supplement on a daily basis. Mark-resight population estimates from March helicopter (489 deer, SE = 62) and ground (494 deer, SE = 81) surveys, coupled with feed consumption, indicated we fed roughly 450 to 500 deer during most of the winter and spring. Feed consumption declined coincident with spring green-up, although deer continued to use the feed through mid-late April, at which point they began migrating to summer range. We also fed approximately 25 to 30 elk, but the elk did not affect deer access to the feed. Deer in the control experimental unit did not receive feed or any other treatment. Based on helicopter mark-resight surveys, the deer density in the treatment unit in December was 120 deer/mi2 (SE = 9), but increased shortly after and was 213 deer/mi2 (SE = 27) in March. Deer densities in the control unit changed little from 83 deer/mi2 (SE = 12) in December to 101 deer/mi2 (SE = 14) in March. 2001−02: We distributed 194 tons of the supplement throughout the treatment unit from December 15, 2001, through April 25, 2002. We distributed 2.0−2.1 tons of feed each day for most of the winter and spring. The large increase in supplement distribution from the previous year occurred because a large number of elk descended into the Uncompahgre Valley during late fall. Elk arrived in unusually large numbers throughout much of the valley prior to the onset of treatment delivery. Once feeding was initiated, approximately 300−500 elk adapted to the feed and remained in or around the treatment unit throughout most of the winter. We could not deliver >2.1 tons of pellets per day given myriad logistical and budgetary constraints. Feed was not delivered ad libitum to all deer and elk in the treatment unit throughout the winter because residual feed was rarely observed during the next day’s distribution. However, daily field observations indicated most deer approached ad libitum consumption of the supplement. In contrast to the previous winter, deer were waiting for the daily supplement to arrive each morning. Deer then consumed the supplement immediately after it was distributed. Elk were rarely observed utilizing the 47 �feed until late morning or afternoon, and elk continued to forage in fields below the treatment unit, whereas deer did not. We observed numerous radio-collared deer consuming pellets each day; not all of these observations were recorded because of time constraints with distributing the feed. Given this time limitation, we still recorded 818 observations of radio-collared deer consuming the supplemental feed (497 collared doe observations and 321 collared fawn observations). We observed 100−300 deer utilizing the pellets most days during the course of distributing the supplement. These observations rarely included elk; thus, direct deer-elk competition was minimized because of temporal differences in feeding, and deer had first access to the feed. 2002−03: We switched the treatment and control units consistent with the cross-over experimental design in December 2002. We distributed 97 tons of supplement from December 15, 2002 through April 30, 2003 across the new treatment unit, which had been the control unit the previous 2 years. The supplement was distributed daily throughout 29 sites over a larger area (~7 mi2) than the first 2 years of research because of the greater size of the experimental unit and broader distribution of radiocollared deer. Residual feed was always present throughout the winter, thus deer were fed ad libitum. Only small groups of elk periodically accessed the supplement, and did not affect deer access. We obtained 286 observations of radio-collared deer consuming the supplement, which were difficult to obtain because the supplement was spread out over a large area and only a single feed site could be observed at any given moment. We also used daily ground radio-monitoring and periodic aerial relocations to document deer access to the supplement. 2003−04: We distributed 197 tons of pellets throughout the treatment unit from December 10, 2003, through April 30, 2004. The increase in supplement distribution occurred because elk numbers increased on the upper portion of the experimental unit. However, unlike winter 2001−02, residual feed was present throughout the winter and deer were fed ad libitum. We restricted elk to the upper extent of the deer winter range for most of the winter by allocating a portion of the daily feed distribution exclusively to elk. Thus, elk had a minimal affect on deer access to the supplement. We obtained 413 observations of radio-collared deer consuming the supplement. As before, we also used daily ground radio-monitoring and periodic aerial relocations to document deer access to the supplement. Body Condition Estimated percent body fat of adult does during late February and early March, 2002–2004, was higher for treatment deer than control deer (F1, 148 = 153.41, P < 0.001). Over all years combined, mean predicted body fat was 9.8% (SE = 0.36) for treatment adult does and 4.3% (SE = 0.26) for control does. The interaction of experimental unit × year for predicted body fat was also significant (F2, 148 = 14.39, P < 0.001). This interaction occurred because the difference in body fat between treatment and control deer was greater during 2003 than during 2002 or 2004. Mean predicted body fat was 8.2% (SE = 0.92) for treatment adult does and 5.0% (SE = 0.71) for control does during 2002, and 9.0% (SE = 0.53) for treatment does and 4.7% (SE = 0.36) for control does during 2004. The difference was greater during 2003, where mean predicted body fat was 11.7% (SE = 0.35) for treatment does and 3.4% (SE = 0.35) for control does. The body fat estimates reported here should accurately reflect deer, but may be further refined in the future as additional research provides more data on the relationship between body condition indices and estimated percent body fat. Serum thyroid hormone concentrations, measured during 2003 and 2004, were higher in treatment does than control does (F4, 108 = 46.59, P < 0.001) (Table 1). Hormone concentrations also varied between years (F4, 108 = 14.21, P < 0.001), but the experimental unit × year interaction was not significant (F4, 108 = 1.68, P = 0.160). Thus, each year thyroid hormone concentrations were higher in treatment does than control does. T4 was the most important thyroid hormone in describing the canonical variable for differences between treatment and control does (1.04*T4 − 0.02*T3 + 0.77*FT4 – 48 �0.17*FT3). As expected, there was a high partial correlation between T4 and FT4 (r = 0.67, P < 0.001) and between T3 and FT3 (r = 0.60, P < 0.001), which has been documented previously (Watkins et al. 1983). When treated as 4 separate ANOVAs, T4 (F1, 111 = 165.97, P < 0.001), FT4 (F1, 111 = 144.37, P < 0.001), T3 (F1, 111 = 13.84, P < 0.001), and FT3 (F1, 111 = 8.26, P = 0.005) were significantly higher in treatment does than control does. Given these results, we evaluated the relationship between T4 concentrations and estimated percent body fat (derived from ultrasound and BCS indices) using a simple linear regression model (% Fat = −3.122 + 0.090*T4, r2 = 0.52, P < 0.001). Similar correlations between T4 and actual percent body fat during mid-late winter have been previously documented for white-tailed deer and elk (Watkins et al. 1991, Cook et al. 2001). Pregnancy and Fetus Rates 2002: Adult doe pregnancy rate was 0.95 (SE = 0.037, n = 38) in February−March 2002. We measured an average of 1.80 fetuses/doe (SE = 0.10, n = 36), which included 1.77 fetuses/doe (SE = 0.14, n = 18) in the treatment unit and 1.83 fetuses/doe (SE = 0.15, n = 18) in the control unit. 2003: Adult doe pregnancy rate was 0.92 (SE = 0.034, n = 63) in February−March 2003. Critical personnel and equipment for measuring fetus rates were not continuously available due to capture delays associated with helicopter mechanical problems. Some deer fetus counts were performed by inexperienced observers without optimum ultrasound equipment. VITs worked very well, though, allowing us to determine fetus numbers at parturition for many of the deer. Thus, we determined winter fetus rates by using the greatest fetus count for each individual deer, whether obtained using ultrasound during February−March or by locating newborn fawns and stillborns at birth sites during June. We were unable to determine a fetus count for 8 treatment deer because only pregnancy was established with ultrasound and no birth site assessments were possible in June. These 8 deer were removed from the fetus rate estimates. Of the 50 deer where a fetus count was obtained, 5 were yearlings (2 treatment yearlings, 3 control yearlings). We measured 1.74 fetuses/doe (SE = 0.069, n = 50) overall including yearlings, and 1.82 fetuses/doe (SE = 0.066, n = 45) excluding yearlings. Fetus rates with yearlings included were 1.77 fetuses/doe (SE = 0.091, n = 22) in the treatment unit and 1.70 fetuses/doe (SE = 0.10, n = 28) in the control unit. 2004: In February 2004, adult doe pregnancy rate was 0.94 (SE = 0.029, n = 66) and the fetus rate was 1.97 fetuses/doe (SE = 0.053, n = 60), which included 4 yearlings. Excluding yearlings, the fetus rate was 2.00 fetuses/doe (SE = 0.051, n = 56). Fetus rates were 1.90 fetuses/doe (SE = 0.074, n = 30) in the treatment unit and 2.03 fetuses/doe (SE = 0.076, n = 30) in the control unit with yearlings included, and 1.93 (SE = 0.069, n = 29) in the treatment unit and 2.07 (SE = 0.074, n = 27) in the control unit with yearlings excluded. Pregnancy and fetus rates during our study equaled or exceeded other measured rates recorded in Colorado (Andelt et al. 2004), indicating moderate to high innate productivity potential for both treatment and control does. Our data also indicate that adequate numbers of bucks were available to breed does during the years of our study. Fetus and Neonate Survival/Fawn:Doe Ratios 2000: Fawn:doe ratios were similar in the 2 experimental units in December 2000, prior to the first year’s treatment delivery. Pre-treatment fawn:doe ratios were 52.6 fawns:100 does (SE = 5.3) in the Colona experimental unit and 51.6 fawns:100 does (SE = 5.0) in the Shavano experimental unit. 2001: We conducted 2 age classification helicopter surveys in the treatment and control units in late December 2001 and early January 2002, following the first year’s treatment. On 23 December 2001, we observed 52.8 fawns:100 does (SE = 6.7) in the treatment unit and 36.7 fawns:100 does (SE = 3.8) in 49 �the control unit. On 8 January 2002, we observed 54.7 fawns:100 does (SE = 6.6) in the treatment unit and 50.5 fawns:100 does (SE = 6.0) in the control unit. During December 2001 – February 2002, we obtained fawn:doe ratio estimates from ground observations of radio-collared deer groups for both treatment and control deer. This survey resulted in 61.2 fawns:100 does (SE = 7.8) in the treatment unit and 74.5 fawns:100 does (SE = 8.5) in the control unit, although the result was not statistically significant (t74 = 1.16, P = 0.249). Our fawn:doe ratio results were conflicting and did not provide evidence that there was any treatment effect. We could not make any sound conclusions based on the data, although we generally concluded the nutrition enhancement treatment did not cause a substantial increase in neonatal production and survival during 2001. These data provided the incentive to incorporate direct measurements of fetus and neonate survival into our research. 2002: We measured fetus and neonate survival directly during March – December, 2002, following the second year’s treatment; however, sample sizes were based on a technique assessment of VITs and were relatively small for contrasting survival rates among treatment and control fetuses and neonates (Bishop et al. 2002). During June 2002, we determined the fate of all fetuses (live or stillborn) from only 14 of 36 VIT does, largely because of a high VIT battery failure rate. Numbers of stillborns were similar among treatment and control deer, so we did not differentiate by experimental unit. The survival rate of fetuses (n = 22) from the 14 does was 0.86 (SE = 0.073). We also assessed fetus survival using a change-in-ratio estimator between the fetal rate measured in February−March and the observed number of live fawns/doe postpartum in June. In June 2002, considering all does (n = 43) that we located any fawn from, whether live or stillborn, we observed 1.42 (SE = 0.11) live fawns/doe postpartum. This rate should represent a conservative estimate of live fawns/doe postpartum because we inevitably failed to locate all live fawns from each doe. In other words, this estimate would treat any unaccounted fetuses (from the February measurement) as if they were stillborns. For radio-collared does that did not have VITs, and thus we did not have a winter fetus rate measurement, singletons would infer that either the deer only had 1 fetus, or that the other fetus died. It is likely that some of these singletons had a twin that we did not locate. This equates to a conservative fetus survival rate estimate of 0.79 (SE = 0.18). Treatment fawn survival (Jun – Dec) was 0.613 (SE = 0.115, n = 29) and control fawn survival was 0.511 (SE = 0.108, n = 25). In late December 2002 and early January 2003, we once again conducted 2 age classification helicopter surveys in the treatment and control units. On 31 December 2002, we observed 91.9 fawns:100 does (SE = 8.4) in the treatment unit and 52.2 fawns:100 does (SE = 6.9) in the control unit. On 21 January 2003, we observed 52.6 fawns:100 does (SE = 6.4) in the treatment unit and 36.8 fawns:100 does (SE = 3.9) in the control unit. The combined helicopter survey data indicated 68.1 fawns:100 does (SE = 5.6) in the treatment unit and 42.8 fawns:100 does (SE = 3.5) in the control unit. Conversely, fawn:doe ratio estimates from ground classifications of doe groups during December 2002 – February 2003 were 47.7 fawns:100 does (SE = 6.3) in the treatment unit and 63.4 fawns:100 does (SE = 7.5) in the control unit (t108 = 1.61, P = 0.110). As in 2001, fawn:doe ratio results were conflicting. Helicopter survey data varied between 2 different flights, but consistently indicated a treatment effect. Ground classification data did not indicate a treatment effect. 2003: During June 2003, we determined the fate of all fetuses (live or stillborn) from 33 of 58 VIT does; we had better success because VITs commonly shed at birth sites. The survival rate of fetuses (n = 58) from these 33 does was 0.97 (SE = 0.024). In June 2003, incorporating all does (n = 71) from which we located any fawn, whether live or stillborn, we observed 1.49 (SE = 0.072) live fawns/doe postpartum. Using the change-in-ratio estimator described above, this results in an overall conservative fetus survival rate estimate of 0.86 (SE = 0.15). As in 2002, fetus survival was similar among treatment and control deer and not analyzed separately. During June 2003, we captured and radio-collared 103 newborn fawns born from treatment and control radio-collared does (55 treatment fawns, 48 control fawns). The VITs worked well; we captured 50 �fawns from 41 of the 58 does fitted with VITs. Treatment fawn survival (Jun – Dec) was 0.624 (SE = 0.082) and control fawn survival was 0.483 (SE = 0.093). Final standard errors were larger than expected because a number of fawns shed collars prematurely when crossing fences during fall migration. Using helicopter surveys, we measured 62.4 fawns:100 does (SE = 5.3) in the treatment unit and 50.0 fawns:100 does (SE = 4.9) in the control unit. Estimates from ground classifications of doe groups were 68.0 fawns:100 does (SE = 7.6) in the treatment unit and 62.1 fawns:100 does (SE = 7.6) in the control unit. Age ratio estimates from the helicopter and the ground were more consistent during 2003 than in past years. Overall, observed fawn:doe ratios were consistent with treatment and control fawn survival rates measured from June to December. 2004: We determined the fate of all fetuses from 31 of 60 VIT does. The overall fetus survival rate was 0.90 (SE = 0.040, n = 58). Different from 2002 or 2003, all stillborns were from control does. The survival rate of control fetuses was 0.76 (SE = 0.085, n = 25) as compared to a survival rate of 1.00 (n = 33) for treatment fetuses. Using data from all does (n = 82) in which we located any fawn, the conservative change-in-ratio fetus survival estimate was 0.79 (SE = 0.13) overall, 0.88 (SE = 0.17) for treatment deer, and 0.69 (SE = 0.14) for control deer. We captured and radio-collared 119 newborn fawns born from treatment and control radiocollared does during June 2004 (68 treatment fawns, 51 control fawns). Vaginal implants worked well again, and we had a large sample of non-VIT radio-collared does that we could relocate to opportunistically capture additional treatment and control fawns. Treatment fawn survival (Jun – Dec) was 0.438 (SE = 0.068) and control fawn survival was 0.414 (SE = 0.092). As in 2003, final standard errors were larger than expected because fawns shed collars prematurely during fall migration. Although neonate survival rates were similar among treatment and control fawns, fewer control fawns survived to December because of lower fetus survival. The proportion of fetuses measured in March that were born alive and survived to December during 2004 (i.e. fetus-neonate survival) was 0.438 (SE = 0.068) for treatments and 0.304 (0.073) for controls. Similar to 2002 and 2003, we observed higher December fawn recruitment among treatment deer based on measured survival rates. The difference during 2004 was that stillborn deaths factored in as a larger mortality factor among control deer than during 2002 or 2003. We measured 64.6 fawns:100 does (SE = 5.8) in the treatment unit and 52.7 fawns:100 does (SE = 5.1) in the control unit during helicopter surveys in 2004. Our ground classification estimates were 78.5 fawns:100 does (SE = 6.6) in the treatment unit and 68.7 fawns:100 does (SE = 5.1) in the control unit. Similar to 2003, observed fawn:doe ratios were consistent with treatment and control survival rates. 2002−2004 Fetus-Neonate Survival Summary: Fetus-neonate survival combined over all years of study (1 Mar–15 Dec, 2002–2004) was higher (χ21 = 3.089, P = 0.079) for treatment deer (S(t) = 0.519, SE = 0.048) than for control deer (S(t) = 0.409, SE = 0.052). The high censor rate from shed collars during fall reduced power of the analysis and therefore increased standard errors and the resulting Pvalue. However, at roughly the same time neonate radio-collars were being shed, we captured new samples of fawns for measuring overwinter fawn survival. When fawns captured during November and early December were incorporated into the analysis via staggered entry, fetus-neonate treatment survival (S(t) = 0.528, SE = 0.027) and control survival (S(t) = 0.401, SE = 0.025) rates had tighter standard errors, which reduced the p-value associated with the survival rate comparison (χ21 = 3.846, P = 0.050). The nutrition enhancement treatment had a positive effect on fetus and neonate survival through about the first month postpartum, at which point the treatment stopped having an effect (Figure 4). Fetus-neonate survival through 15 July, 2002–2004, was much higher (χ21 = 6.013, P = 0.014) for treatment fawns (S(t) = 0.746, SE = 0.035) than control fawns (S(t) = 0.583, SE = 0.043). In summary, enhanced nutrition of adult does during winter and early spring caused higher survival of fetuses and fawns, resulting in higher December fawn recruitment (Figure 4). 51 �2001−2004 Fawn:Doe Ratio Summary: Our results from 2001 and 2002 emphasize the inherent difficulties and biases associated with precisely measuring fawn:doe ratios, particularly in this research study. Ratios obtained from helicopter surveys were based on 2 short-duration flights/unit/year over spatially small units. Helicopter surveys were complicated by high deer densities in heavy cover, making both deer detection and fawn:doe classifications a considerable challenge. There were a variety of potential biases that may have affected the helicopter surveys, including differential sightability of does and fawns, double classification of some deer, and incorrect classification of yearling bucks with small antlers. Ground fawn:doe ratio observations of radio-collared doe groups were made using spotting scopes and field glasses, where we commonly studied the deer for some time. Incorrect classifications during these surveys were likely minimal. For example, small-antlered yearling bucks (e.g. 3 – 6” spikes) were detected from the ground, whereas they were undoubtedly missed on occasion during helicopter surveys. We also obtained repeated observations for some of the radio-collared doe groups from the ground. The main potential bias affecting ground fawn:doe classifications was how observations were made. Many of the ground classifications in the Shavano Valley experimental unit were made by radiotracking does during the day. On the other hand, a majority of ground classifications in the Colona experimental unit were based on observing deer groups as they entered openings to feed during the late afternoon. Our age ratio results were more consistent with survival data during 2003 and 2004. Deer were not as concentrated during helicopter surveys, and unlike previous years, a majority of the ground classification data for the Colona experimental unit was obtained by radio-tracking does during the day rather than sitting and waiting for deer to emerge from pinyon-juniper hillsides to feed on sagebrush-grass benches. We relied primarily on fetus-neonate survival data to make inferences regarding treatment effects because of the inherent difficulties measuring fawn:doe ratios in the 2 experimental units. However, we plan to compare observed helicopter and ground fawn:doe ratios with predicted ratios based on fetusneonate survival data as a technique assessment of fawn:doe ratio measurements. This analysis will be incorporated into the job completion report. Neonate Mortality Causes 2002−2003: During June − December of 2002 and 2003, 37 treatment fetuses-neonates died: 3 – stillborn, 8 – coyote predation, 2 – bear predation, 2 – felid predation, 3 – predation where the predator was undetermined, 11 – disease-starvation-malnutrition, 1 – abandonment, 3 – trauma-injury, 2 – unknown, and 2 – poached. The two poached fawns were censored from analyses evaluating the effect of the treatment. Converted to mortality rates based on the Kaplan-Meier survival analysis, 11.4% of all treatment fawns died from disease-starvation-malnutrition, 8.3% from coyote predation, 7.7% were stillborn, 3.1% died each from injury-trauma and from predation where the predator was undetermined, 2.1% each from bear predation, felid predation, and unknown causes, and 1.0% from abandonment. Simplified, 15.6% of all treatment fawns died from predation, 11.4% died from disease-starvationmalnutrition, 7.7% were stillborn, and 6.2% died from other or unknown causes. During June – December of 2002 and 2003, 38 control fetuses-neonates died: 2 – stillborn, 12 – coyote predation, 4 – felid predation, 2 – bear predation, 1 – predation where the predator was undetermined, 12 – diseasestarvation-malnutrition, 1 – trauma-injury, and 4 – unknown. Converted to mortality rates based on the Kaplan-Meier survival analysis, 16.0% of all control fawns died from disease-starvation-malnutrition, 16.0% died from coyote predation, 5.3% each from felid predation and unknown causes, 4.9% were stillborn, 2.7% from bear predation, and 1.3% each from trauma-injury and predation where the predator was undetermined. Simplified, 25.3% of all control fawns died from predation, 16.0% from diseasestarvation-malnutrition, 6.7% from other or unknown causes, and 4.9% were stillborn. In summary, mortality rates due to predation and disease-starvation-malnutrition were lower for treatment fawns than control fawns. 52 �2004: During June – December, 2004, 36 treatment neonates died: 0 – stillborn, 13 – coyote or dog predation, 7 – bear predation, 3 – felid predation, 5 – predation where the predator was undetermined, 2 – disease-starvation-malnutrition, 1 – trauma-injury, and 5 – unknown. Converted to mortality rates based on the Kaplan-Meier survival analysis, 20.3% of all treatment fawns died from canid predation, 10.9% died from bear predation, 7.8% each from unknown causes and from predation where the predator was undetermined, 4.7% from felid predation, 3.1% from disease-starvation-malnutrition, and 1.6% from injury-trauma. Simplified, 43.7% of all treatment fawns died from predation, 9.4% died from other or unknown causes, and 3.1% died from disease-starvation-malnutrition. During June – December, 2004, 32 control fetuses-neonates died: 6 – stillborn, 5 – coyote predation, 4 – bear predation, 1 – felid predation, 2 – predation where the predator was undetermined, 4 – disease-starvation-malnutrition, 5 – injurytrauma, and 5 – unknown. We actually observed 9 stillborns from control does with fetus counts, although only 6 were associated with does in which all fetuses were accounted at parturition. Thus, we used only 6 of the stillborns in our estimate of fetus survival, and therefore stillborn mortality. Converted to mortality rates based on the Kaplan-Meier survival analysis, 24.0% of all control neonates were stillborn, 8.8% died each from coyote predation, injury-trauma, and unknown causes, 7.0% each from bear predation and disease-starvation-malnutrition, 3.5% from predation where the predator was undetermined, and 1.8% from felid predation. Simplified, 24.0% of all control fawns were stillborn, 21.0% died from predation, 17.5% died from other or unknown causes, and 7.0% died from diseasestarvation-malnutrition. Mortality causes were much different during 2004 than either 2002 or 2003. Predation rates were high on treatment fawns while stillborn mortality rates were high among control fawns. Several specific observations during 2004 are worthy of note. Three of the treatment fawn mortalities attributed to coyotes or dogs occurred amongst large herds of sheep which had been released to pasture immediately prior to the mortality events. Bear predation was higher among all fawns during 2004, although 3 of the 7 treatment bear mortalities involved triplets that were killed simultaneously by a bear 1−2 days after the fawns were born. Six treatment fawns captured in the same drainage tributary were killed within a 1-mi2 area; the drainage was in a portion of the study area where no control fawns were captured. However, a single animal did not kill each of the fawns because the mortalities encompassed coyote, felid, and bear predation. Finally, we observed more accidental deaths than typical among control fawns. One control fawn drowned in a river, another fell, one became lodged in a water-filled mudhole, and both a control fawn and a treatment fawn died from injuries sustained while stuck in a woven wire fence. 2002−2004 Summary: Combining all years of data, the survival and cause-specific mortality rates of treatment fawns were: 52.8% survived, 27.2% died from predation (i.e. 13.3% canid, 5.7% bear, 3.2% felid, 5.1% undetermined), 8.2% died from disease-starvation-malnutrition, 4.2% were stillborn, and 7.6% died from other or unknown causes. Survival and cause-specific mortality rates of control fawns were: 40.1% survived, 24.3% died from predation (i.e. 12.9% canid, 4.6% bear, 3.8% felid, 3.0% undetermined), 12.1% died from disease-starvation-malnutrition, 12.1% were stillborn, and 11.4% died from other or unknown causes. The relatively high predation rate of treatment fawns was largely explained by 2004 data alone. As a general summary, control fawns suffered higher rates of disease, illness, malnutrition, and stillborn mortality (i.e. non-predator related mortalities) than did treatment fawns, which explains why survival was higher among treatment fawns (Figure 5). Overwinter Fawn Survival and Mortality Causes During winter 2001−02 (10 Dec 2001–15 Jun 2002), the survival rate of fawns was higher (χ21 = 13.216, P < 0.001) in the treatment unit (S(t) = 0.865, SE = 0.056) than in the control unit (S(t) = 0.510, SE = 0.080). Similarly, in 2002−03 (10 Dec 2002–15 June 2003), the overwinter survival rate of fawns was higher (χ21 = 5.734, P = 0.017) in the treatment unit (S(t) = 0.900, SE = 0.047) than in the control unit (S(t) = 0.691, SE = 0.074). Again in 2003−04 (10 Dec 2003–15 June 2004), the overwinter survival 53 �rate of fawns was higher (χ21 = 3.852, P = 0.050) in the treatment unit (S(t) = 0.920, SE = 0.045) than in the control unit (S(t) = 0.756, SE = 0.067). Combining survival data across all 3 winters, treatment fawn survival (S(t) = 0.895, SE = 0.029) was 0.24 higher (χ21 = 18.781, P < 0.001) than control fawn survival (S(t) = 0.655, SE = 0.044) (Figure 6). The treatment unit during winter 2001−02 became the control unit during winters 2002−03 and 2003−04, and vice versa. Thus, the overwinter survival treatment effect was replicated across each experimental unit. Fawn survival also varied as a function of early winter fawn mass (χ21 = 21.19, P < 0.001). Surviving fawns averaged 3.5 kg heavier than fawns that died. The importance of early winter fawn mass as a predictor of overwinter survival has been documented previously (White et al. 1987, Bishop 1998, White and Bartmann 1998, Unsworth et al. 1999). Early winter mass of treatment fawns ( x = 34.2 kg, SE = 0.418) was similar to control fawns ( x = 34.4, SE = 0.423); thus the effect of the treatment was not confounded with pre-treatment fawn mass. It follows that fawns born from treatment does did not arrive to winter heavier than fawns born from control does, which was not necessarily surprising considering the treatment primarily effected neonate survival through about 1 month postpartum. In summary, the nutrition enhancement treatment improved overwinter fawn survival, and heavier fawns in each experimental unit had higher survival probabilities. During winters 2001−04, 12 of 115 treatment fawns died: 5 from coyote predation, 3 from disease/illness, 2 from malnutrition, 1 from trauma-injury, and 1 unknown. Each of the 3 fawns that died from disease had adequate fat stores. At least one of these fawns died as a result of pneumonia. Converted to mortality rates based on the Kaplan-Meier survival analysis, 4.3% of all treatment fawns died from coyote predation, 2.6% from disease-illness, 1.7% from malnutrition, 0.9% from trauma-injury, and 0.9% from unknown causes. Simplified, 4.3% of all treatment fawns died from predation, 4.3% from disease-malnutrition, and 1.8% from other or unknown causes (Figure 7). During winters 2001−04, 41 of 120 control fawns died: 13 from coyote predation, 8 from mountain lion predation, 8 from malnutrition, 6 from unknown causes, 3 from predation where the predator was undetermined, 2 were road-killed, and 1 from trauma-injury. Converted to mortality rates based on the Kaplan-Meier survival analysis, 10.9% of all control fawns died from coyote predation, 6.7% from mountain lion predation, 6.7% from malnutrition, 5.0% from unknown causes, 2.5% from predation where the predator was undetermined, 1.7% from road-kill, and 0.8% from trauma-injury. Simplified, 20.1% of all control fawns died from predation, 6.7% from malnutrition, and 7.5% from other or unknown causes (Figure 7). Most fawns killed by predators had little or no femur marrow fat remaining, indicating the predation was likely compensatory in nature. Fetus-Neonate-Overwinter Fawn Survival We combined the preceding survival data into a single analysis to express the effect of the treatment across all stages of fawn production and survival. Using a staggered entry survival process with data combined over years, we estimated fawn survival from the fetus stage until one year of age, when fawns were recruited to the yearling (adult) age class (Figure 8). Survival of treatment fetuses to the yearling age class (S(t) = 0.458, SE = 0.031) was 0.18 higher (χ21 = 13.20, P < 0.001) than survival of control fetuses to the yearling age class (S(t) = 0.276, SE = 0.026). Adult Female Survival and Causes of Mortality During winter 2000−01 (1 Dec 2000–31 May 2001), the adult doe survival rate in the treatment unit (S(t) = 0.968, SE = 0.032) was greater (χ21 = 2.649, P = 0.104) than the survival rate in the control unit (S(t) = 0.861, SE = 0.058). However, annual adult doe survival rates (1 Dec 2000–30 Nov 2001) were similar among treatment and control deer (Trt: S(t) = 0.839, SE = 0.066; Control: S(t) = 0.833, SE = 0.062; χ21 = 0.004, P = 0.947). We observed a similar result the following year. The 2001−02 overwinter adult doe survival rate in the treatment unit (S(t) = 0.942, SE = 0.030) was greater (χ21 = 3.116, P = 0.078) than survival in the control unit (S(t) = 0.848, SE = 0.044), yet annual adult doe survival was similar among treatment and control deer (Trt: S(t) = 0.824, SE = 0.049; Control: S(t) = 0.818, SE = 54 �0.047; χ21 = 0.090, P = 0.764). Thus, mortalities of control deer occurred primarily during the winter months, while treatment does died primarily during the summer and fall months. During winter 2002−03, following the treatment cross-over, overwinter adult doe survival rates were similar among treatment and control deer (Trt: S(t) = 0.945, SE = 0.024; Control: S(t) = 0.924, SE = 0.028; χ21 = 0.360, P = 0.549). However, annual adult doe survival rates (1 Dec 2002–30 Nov 2003) were higher (χ21 = 2.016, P = 0.156) for treatment does (S(t) = 0.888, SE = 0.034) than control does (S(t) = 0.813, SE = 0.041). The main difference from the previous 2 years was that overwinter survival of adult does in the Shavano experimental unit increased in 2002−03 upon receiving the treatment. Summer-fall survival was similar in that Colona adult does had higher mortality rates than Shavano adult does. Thus, in 2002−03, there was no difference between survival rates of treatment and control adult does during winter but there was evidence of higher annual survival of treatment adult does. During winter 2003−04, overwinter adult doe survival rates were higher (χ21 = 3.843, P = 0.050) among treatment does (S(t) = 0.979, SE = 0.014) than control does (S(t) = 0.915, SE = 0.027). The annual adult doe survival rate (1 Dec 2003–30 Nov 2004) was 0.895 (SE = 0.030) for treatment does and 0.832 (SE = 0.036) for control does, which was marginally different (χ21 = 1.562, P = 0.211). Considering all years, the treatment improved overwinter adult doe survival but had a relatively minor affect on annual survival. Considering only the past 2 years, the treatment had a positive affect on annual survival. Annual survival rates measured in this study align reasonably well with expected survival based on other studies (Unsworth et al. 1999, Bishop et al. 2005, B. E. Watkins, Colorado Division of Wildlife, unpublished data). During 2000−02, when the Colona experimental unit received the treatment and the Shavano experimental unit was the control, 16 treatment and 16 control does died. The 16 treatment does died from the following categories: 4 – road-killed, 3 – while giving birth, 3 – predation (undetermined predator), 2 – non-predation unknown (intact carcasses with no evidence of predation or scavenging), 1 – disease (chronic arthritis), 1 – mountain lion predation, and 2 – unknown. Predation was not a major mortality factor for treatment does, and a majority of mortalities were independent of nutrition (does were in good condition). The 16 control doe mortalities included the following causes: 5 – mountain lion predation, 3 – malnutrition, 2 – non-predation unknown, 1 – road-killed, 1 – bear predation, 1 – fence injury, 1 – legal harvest, and 2 – unknown. Predation and malnutrition were the major mortality causes of control deer. Interestingly, during this 2-year period, we did not document any coyote predation on adult does. During 2002–04, with Shavano as the treatment and Colona as the control, there were 20 treatment doe mortalities: 6 – disease/infection, 3 – coyote predation, 1 – road-killed, 1 – broken jaw which led to starvation, 1 – fence injury, 1 poached, and 7 unknown causes. As we saw during 2000-02, predation was not a major mortality factor for treatment does, and a majority of mortalities were independent of nutrition. We observed 33 control adult doe mortalities during the same time period: 8 – road-kill, 7 – malnutrition-disease, 5 – coyote predation, 3 – mountain lion predation, 3 – non-predation unknown, 1 – bear predation, 1 – predation where the predator was undetermined, and 5 – unknown causes. Road kill, malnutrition-disease, and predation were the major mortality factors of control does during 2002−04. Road kill was a significant mortality factor of Colona adult does but not Shavano adult does, which partially explains why we failed to see a treatment effect during 2000−02 but did see one during 2002−04. If road-killed deer were censored, greater evidence would exist for a treatment effect during 2000−02 while there would be less evidence of a treatment effect during 2002−04. However, road-kill had minimal effect on the overall 4-year interpretation of the treatment effect on adult doe survival 55 �because of the cross-over design. Ignoring road kill, treatment does tended to die of causes unrelated to nutrition whereas control does were more susceptible to malnutrition and predation. Population Growth Rate The finite rate of population increase, λ, based on our measurements of treatment population parameters was 1.20 (Table 2), which would cause the deer population to double in approximately 4 years. The finite rate of increase calculated from control deer was 1.04 (Table 2), indicating a stable or slightly increasing population. The nutrition enhancement treatment therefore had a dramatic effect on deer population performance, indicating habitat quality was ultimately limiting the population. SUMMARY We successfully enhanced nutrition of deer occupying the treatment units based on our body fat estimates of treatment and control does. Pregnancy and fetus rates were similar among treatment and control does. The treatment caused an increase in both fetus-neonate survival and overwinter fawn survival, resulting in higher yearling recruitment. Overwinter adult doe survival increased as a result of the treatment, but annual survival was more similar among treatment and control adult does. Combining all parameter estimates into a deterministic population model, the treatment population indicated an exceptionally high rate of increase (λ = 1.20) while the control population (λ = 1.04) was indicative of the overall Uncompahgre deer population during 2000−2004. The nutrition enhancement treatment was artificial in the sense that we applied it only to test whether habitat quality was ultimately more limiting than predation or other factors. Our results to do not provide support for managing deer populations with nutrition supplements because our treatment delivery approach could not be applied to a large number of animals over a large area. 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Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. VERME, L. J., AND D. E. ULLREY. 1972. Feeding and nutrition of deer. Pages 275−291 in D. C. Church, editor. Digestive physiology and nutrition of ruminants. Volume 3 – Practical Nutrition. D. C. Church, Corvallis, Oregon, USA. WATKINS, B. E., D. E. ULLREY, R. F. NACHREINER, AND S. M. SCHMITT. 1983. Effects of supplemental iodine and season on thyroid activity of white-tailed deer. Journal of Wildlife Management 47:45−58. _____, J. H. WITHAM, D. E. ULLREY, D. J. WATKINS, AND J. M. JONES. 1991. Body composition and condition evaluation of white-tailed deer fawns. Journal of Wildlife Management 55:39−51. WHITE, G. C. 1996. NOREMARK: Population estimation from mark-resighting surveys. Wildlife Society Bulletin 24:50−52. _____, AND R. M. BARTMANN. 1998. Effect of density reduction on overwinter survival of free-ranging mule deer fawns. Journal of Wildlife Management 62:214−225. _____, R. A. GARROTT, R. M. BARTMANN, L. H. CARPENTER, AND A. W. ALLDREDGE. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Management 51:852−859. _____, A. F. REEVE, F. G. LINDZEY, AND K. P. BURNHAM. 1996. Estimation of mule deer winter mortality from age ratios. Journal of Wildlife Management 60:37−44. Prepared by _______________________ Chad J. Bishop, Wildlife Researcher 58 �Table 1. Total thyroxine (T4) and total tri-iodothyronine (T3) concentrations (nmol/l), and free T4 (FT4) and free T3 (FT3) concentrations (pmol/l), measured during late February in adult female mule deer occupying a nutrition enhancement treatment unit and a control unit on the Uncompahgre Plateau in southwest Colorado, 2003−04. Thyroid Hormone T3 (SE) FT3 (SE) 146.6 (3.53) FT4 (SE) 30.0 (1.27) 1.65 (0.058) 4.10 (0.130) Control 92.3 (3.56) 17.1 (0.65) 1.42 (0.080) 3.71 (0.210) Treatment 131.9 (4.48) 24.8 (1.39) 2.08 (0.075) 4.21 (0.154) Control 90.0 (3.54) 12.5 (0.59) 1.70 (0.104) 3.60 (0.188) Year Exp. Unit T4 (SE) 2003 Treatment 2004 Table 2. Population parameter estimates and population finite rate of increase, λ, for treatment deer that received a nutrition enhancement and control deer that accessed existing habitat only, southwest Colorado, 2002−04. Population Parameter Treatment Control 0.937 0.937 Adult doe fetus rate 1.84 1.84 Fetus survival to birth 0.958 0.879 Neonate survival to December 0.551 0.456 Overwinter fawn survival to June 0.895 0.655 Annual adult doe survival 0.860 0.824 Finite Rate of Increase, λ 1.20 1.04 Adult doe pregnancy ratea a a We used overall estimates of pregnancy and fetus rates because we did not detect meaningful differences between treatment and control deer. Year Unit A Unit B 2000-01 Treatment Control 2001-02 Treatment Control 2002-03 Control Treatment 2003-04 Control Treatment Figure 1. Schematic representation of experimental units and nutrition enhancement treatment allocation. Units A and B were located in winter range habitat on the Uncompahgre Plateau in southwest Colorado. The nutrition enhancement cross-over design encompassed 4 years. 59 �Uncompahgre Plateau Mesa County GRAND JUNCTION Delta County m co Un GMU 62 r hg pa e u ea at Pl Montrose County GMU 61 Sanmiguel County Gunnison County DELTA Shavano E.U. Winter Range MONTROSE Colona Montrose County E.U. Summ er Ouray County Figure 2. Location of Colona and Shavano (Units A and B) experimental units on the Uncompahgre Plateau, southwest Colorado; and location of the summer range study area encompassing the southern Uncompahgre Plateau and adjacent San Juan Mountains. 60 �Hwy 550 Uncompahgre Valley Colona Exp. Unit Shavano Valley Shavano Exp. Unit Figure 3. Colona and Shavano experimental units (Units A and B), located in Game Management Unit 62 on the Uncompahgre Plateau, southwest Colorado. 61 �1 0.9 Treatment 0.8 Control 0.7 0.6 0.5 0.4 0.3 3/1 3/31 4/30 5/30 6/29 7/29 8/28 9/27 10/27 11/26 Figure 4. Survival (1 Mar –15 Dec, 2002–2004) of mule deer fetuses-neonates born from adult does receiving enhanced nutrition during winter (Treatment, S(t) = 0.528, SE = 0.027) and from adult does accessing existing winter habitat only (Control, S(t) = 0.401, SE = 0.025), southwest Colorado. 0.6 Treatment Control 0.5 0.4 0.3 0.2 0.1 0 Survived Predation Illness/Malnutrition Stillborn Other/ Unknow n Figure 5. Survival and cause-specific mortality rates (1 Mar –15 Dec, 2002–2004) of mule deer fetusesneonates born from adult does receiving enhanced nutrition during winter (Treatment) and from adult does accessing existing winter habitat only (Control), southwest Colorado. 62 �1 0 .9 0 .8 0 .7 Treatment 0 .6 Control 0 .5 12/1 12/16 12/31 1/15 1/30 2/14 3/1 3/16 3/31 4/15 4/30 5/15 5/30 6/14 Figure 6. Overwinter fawn survival (10 Dec –15 Jun, 2001–2004) in a nutrition enhancement treatment unit (S(t) = 0.895, SE = 0.029) and a control unit (S(t) = 0.655, SE = 0.044) on the Uncompahgre Plateau, southwest Colorado. 0.9 Treatment Control 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Survived Predation Illness/Malnutrition Other/ Unknow n Figure 7. Overwinter fawn survival and cause-specific mortality rates (10 Dec–15 Jun, 2001–2004) in a nutrition enhancement treatment unit and a control unit on the Uncompahgre Plateau, southwest Colorado. 63 �1 Treatment 0.9 Control 0.8 0.7 0.6 0.5 0.4 0.3 0.2 3/1 4/15 5/30 7/14 8/28 10/12 11/26 1/10 2/24 4/10 5/25 Figure 8. Fawn survival from fetus stage (March) to 1 year of age (June of the following year) for deer receiving enhanced nutrition during winter (Treatment, S(t) = 0.458, SE = 0.031) and deer accessing existing winter habitat only (Control, S(t) = 0.276, SE = 0.026), southwest Colorado, 2002−2004. 64 �APPENDIX I We submitted the following manuscript (referenced here by Abstract) to the Journal of Wildlife Management during summer 2005. USING VAGINAL TRANSMITTERS TO CAPTURE NEONATES FROM MARKED MULE DEER CHAD J. BISHOP, DAVID J. FREDDY, GARY C. WHITE, BRUCE E. WATKINS, THOMAS R. STEPHENSON, AND LISA L. WOLFE ABSTRACT Measuring reproductive success of previously-marked, adult female ungulates enables study of certain complex ecological factors limiting populations. We evaluated the effectiveness of using vaginal implant transmitters (VITs, n = 154) in mule deer (Odocoileus hemionus) combined with repeated relocations of other radio-collared deer for capturing effective samples of neonates (e.g. >100/year) from free-ranging, marked females. We also evaluated the effectiveness of VITs, when used in conjunction with in utero fetus counts, for obtaining direct estimates of fetus survival. During 2003 and 2004, when VIT batteries were placed on a 12-hour duty cycle to lower failure rates, the proportion of VITs that shed ≤3 days prepartum or during parturition was 0.623 (SE = 0.0456), and the proportion shed during parturition was 0.447 (SE = 0.0468). Our neonate capture success rate was 0.880 (SE = 0.0359) from does with VITs shed ≤3 days prepartum or during parturition and 0.307 (SE = 0.0235) from radiocollared does without VITs or whose implants failed to function properly. Combining techniques we captured 275 neonates and 21 stillborns during 2002−2004. We accounted for all fetuses at birth (i.e. live or stillborn) from 78 of the 147 does (0.531, SE = 0.0413) with winter fetus counts, which was heavily dependent on VIT retention success. Deer that shed VITs prepartum were larger and older than deer that retained implants to parturition, indicating a need to develop variable-sized VITs which may be individually fitted to deer in the field. We demonstrated that direct estimates of fetus and neonate survival may be obtained from previously-marked female mule deer in free-ranging populations, thus expanding opportunities for conducting field experiments. Resulting neonate survival estimates lacked bias that is typically associated with other neonate capture techniques. However, current vaginal implant failure rates and overall expense limit applicability of the technique to well-funded studies with adequate personnel. 65 �66 �Colorado Division of Wildlife July 2004 – June 2005 WILDLIFE RESEARCH REPORT State of Colorado Cost Center 3430 Work Package 3001 Task No. 5 Federal Aid Project: W-185-R : Division of Wildlife : Mammals Research : Deer Conservaton : Multispecies Investigations Consulting Services for Mark-Recapture Analysis : Period Covered: July 1, 2004 - June 30, 2005 Author: G. C. White Personnel: C. Bishop, G. Miller, T. E. Remington, D. J. Freddy, T. M. Shenk, L. Stevens, J. Craig, R. Kahn, D. C. Bowden, F. Pusateri, J. Dennis, P. Schnurr, B. Andelt, A. Seglund, D. Finley, A. Linstrom, K. Strohm, P. Conn. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Progress towards the objectives of this job include: 1. Consulting assistance to CDOW on harvest surveys, terrestrial inventory systems, and population modeling procedures was provided. Assistance with estimation of spring and fall turkey, spring snow goose, sharp-tailed and sage grouse, chukars, ptarmigan, Abert’s squirrels, and general small game harvest was provided, and programs and harvest estimates provided to CDOW via email and CD ROM. Computer code written in SAS to compute these estimates and display results graphically was also provided. Computer code was also written in SAS to estimate the compliance rate of Colorado small game license holders with the Harvest Information Program. 2. The DEAMAN software package for the storage, summary, and analysis of big game population and harvest data was revised further as a Windows XP program. A User’s Manual has been provided to terrestrial biologists via the WWW at http://www.cnr.colostate.edu/~gwhite/deaman. I met with the CDOW software group to discuss conversion of DEAMAN to a central server application. 3. Consultation with CDOW Terrestrial Biologists in the use of DEAMAN and population modeling procedures continued. Numerous questions were answered via meetings with biologists, and via email. 4. A paper on the estimation of mule deer population sizes in GMU 10 was published in the Wildlife Society Bulletin: Freddy, D. J., G. C. White, M. C. Kneeland, R. H. Kahn, J. W. Unsworth, W. J. deVergie, V. K. Grahm, J. H. Ellenberger, and C. H. Wagner. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. 5. A paper on the peregrine falcon population dynamics in Colorado was published in the Journal of Wildlife Management: Craig, G. R., G. C. White, and J. H. Enderson. 2004. Survival, recruitment, and rate of population change of the peregrine falcon population in Colorado. Journal of Wildlife Management 68:1032-1038. 67 �6. A paper on the impact of limited antlered harvest on mule deer sex and age ratios was accepted for publication in the Wildlife Society Bulletin: Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2005. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin. In Press. 7. A paper on the estimation of the area of black-tailed prairie dog colonies in eastern Colorado was accepted for publication in the Wildlife Society Bulletin: White, G. C., J. R. Dennis, and F. M. Pusateri. 2005. Area of black-tailed prairie dog colonies in eastern Colorado. Wildlife Society Bulletin. In Press. 8. A paper on methodologies to obtain more rigorous population monitoring data was accepted for publication in Wildlife Research: White, G. C. 2004. Correcting counts: techniques to de-index. Wildlife Research. In Press. 9. A paper evaluating methods of estimating the impact of harvest on survival rates was published in Animal Diversity and Conservation: Otis, D. L., and G. C. White. 2004. Evaluation of ultrastructure and random effects band recovery models for estimating relationships between survival and harvest rates in exploited populations. Animal Biodiversity and Conservation 27.1: 157-173. 10. A paper on the procedures to monitor swift fox populations in eastern Colorado was accepted for publication in the Journal of Wildlife Management: Finley, D. J., G. C. White and J. P. Fitzgerald. 2004. Estimation of swift fox population size and occupancy rates in eastern Colorado. Journal of Wildlife Management. In Press. 11. A research study to examine the impact of nutrition on the decline of mule deer fecundity during the last 20 years was continued in cooperation with Chad Bishop. Portions of this work will serve as his doctoral dissertation. 12. A graduate research project (M. S.) to develop a sage grouse population model, using North Park sage grouse data to develop parameter estimates, was completed. The graduate student is Kristen Strohm and her thesis is “Sage Grouse Population Dynamics in North Park, Colorado”. 13. A graduate research project (M. S.) To evaluate line transect methodology for estimating pronghorn populations in eastern Colorado was continued. The graduate student is Aaron Linstrom, and the project is in addition to his full-time duties as a terrestrial biologist with CDOW. 14. A graduate research project (Ph. D.) to develop statistical models to monitor puma and black bear populations in Colorado based on checks of harvested animals and DNA and/or radio-tracking data was continued (with funding for 04-05 through the CSU PRIMES program). The graduate student is Paul Conn. 15. Development of the design of a monitoring system for white-tailed prairie dogs in western Colorado and eastern Utah was continued. This effort is in cooperation with Pam Schnurr, Bill Andelt, and Amy Seglund. 16. Development of the design of a monitoring system for swift fox in eastern Colorado was continued, and data analysis for this project was initiated. This effort is in cooperation with Francie Pusatari and Darby Finley. 68 �WILDLIFE RESEARCH REPORT CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSES GARY C. WHITE P. N. OBJECTIVE Monitor swift fox populations in eastern Colorado. SEGMENT OBJECTIVES 1. Extend a mark-recapture monitoring scheme to estimate occupancy rates of swift foxes (Vulpes velox) on 12-mi2 quadrats in eastern Colorado. 2. Contrast estimates from the current survey with thoses obtained in 1998 and published in Finley et al. (2005). ABSTRACT A randomly selected sample of 15 ~12-mi2 grids in eastern Colorado were trapped with a 4 × 5 grid of traps between August, 2004 and February, 2005. Swift foxes were trapped on 36 of the 51 grids, with 136 total fox captures. Comparison of the estimates of the percent of 12-mi2 grids occupied by swift foxes in eastern Colorado does not appear to have changed since a comparable sample was taken of 72 grids in March, 1995 – January, 1997 (Finley et al. 2005). Using the average percentage of the grids in short grass prairie with the minimum AICc model, the earlier estimate was ψ̂ = 0.821 (SE 0.0659), compared to the current estimate of ψ̂ = 0.777 (SE = 0.0786). The estimated change is −0.044 (SE = 0.103, 95% CI −0.245 – 0.157). Summing the predicted occupancy values across the sampled grids for the respective studies provides a similar conclusion: Finley et al. (2005) found ψ̂ = 0.790 (SE = 0.0574), whereas this study found ψ̂ = 0.742 (SE = 0.0869), providing an estimate of the change of −0.048 (SE = 0.104, 95% CI −0.252 – 0.156). These differences are well within the sampling variation of the estimates, and do not suggest a decline in swift fox populations in eastern Colorado. RESULTS Sample of Grids Finley et al. (2005) found that the covariate percent Short Grass Prairie (SGP) is a good predictor of the presence of foxes in eastern Colorado. The distribution of this covariate is bimodal (Figure 1). To build the best relationship between SGP and fox numbers, we sampled across this continuum of SGP values. Thus, the 2,566 trapping grids considered in the sampling frame of grids (Figure 1) to be trapped were sorted by the percentage of SGP predicted by the CDOW GIS system. Then a random start between 1 and 66 was picked, and every 50th grid was selected to be sampled. This procedure resulted in a sample of 51 blocks. When I multiply the frequency of the sample by 50, I obtain a close relationship between the sampling frame and the grids sampled (Figure 2). Statistical Methods Analysis methods to estimate occupancy rates followed the procedures of Finley et al. (2005), using the occupancy model of MacKenzie et al. (2002) in Program MARK (White and Burnham 1999). I considered a set of a priori models that incorporated month as sine and cosine functions to model detection probabilities (p), and the percentage of short grass prairie on the trapping grid to model both 69 �detection probabilities and probability of occupancy, ψ (psi). Model selection was performed with information-theoretic methods following Burnham and Anderson (2002). Analysis methods to estimate the population of foxes using a trapping grid also followed Finley et al. (2005), using the Huggins estimator (Huggins 1989, 1991) to estimate population size. Model selection was performed with information-theoretic methods following Burnham and Anderson (2002). Occupancy Estimation Model selection results for occupancy estimation are shown in Table 1. The sine and cosine functions for month did not improve model fit of detection probabilities, nor did the percentage of short grass prairie improve estimates of detection probabilities. However the percentage of short grass prairie did provide an important predictor of occupancy (Figure 3) with the logit predictive equation: exp[βˆ 0 + βˆ 1 (SGP%)] Occupancy Probability = , 1+ exp[βˆ 0 + βˆ 1 (SGP%)] where β̂ 0 = -0.287 (SE = 0.624, 95% CI −1.510 – 0.936) and β̂1 = 2.775 (SE = 1.299, 95% CI 0.229 – 5.322). The estimated occupancy rate using the average amount of short grass prairie found on the 51 grids samples was ψ̂ = 0.777 (SE = 0.0786, 95% CI 0.589 – 0.894). When the estimated occupancy was summed across the 51 grids using the observed amount of short grass prairie on each grid, ψ̂ = 0.742 (SE = 0.0869, 95% CI 0.572 – 0.912). Finally, the entire population of grids from which the 51 sampled grids were drawn was used to compute the proportion of eastern Colorado occupied by swift foxes: ψ̂ = 0.711. The amount of short grass prairie for each of the grids in the population was estimated based on a GIS layer. Population Estimation Model selection results for population estimation (Table 2) suggest a behavioral effect in response to initial capture, with capture probabilities a function of month and SGP. Initial capture probabilities (Figure 4) and recapture probabilities (Figure 5) from the minimum AICc model are a function of month through a sin transformation, and SGP. The mean number of animals estimated per grid for all 51 grids was 4.83 (SE = 1.990, 95% CI 0.933 – 8.735), ranging from 0 to 26. DISCUSSION Simulations reported in Finley et al. (2005) reported expected power to detect declines given various combinations of numbers of trapping occasions and numbers of grids trapped. For 50 grids trapped with 3 occasions, their simulation results suggested a SE of about 0.070 for ψ = 0.8. The estimated SEs from this study are slightly greater then this value, likely because of the variation in SGP over the range of the sample. However, the values are close enough to make the simulation results reported in Finley et al. (2005) useful if taken a bit conservatively. The results from this study concerning the importance of SGP in predicting swift fox occupancy compared favorably with the results obtained by Finley et al. (2005) (Figure 6). Basically, the same relationship of SGP to occupancy was found. However, the minimum AICc model for occupancy in this study was much simpler than that of Finley et al. (2005), mainly because grids were trapped only during 70 �the period late August through March when the highest detection probabilities were expected based on Finley et al. (2005) work. When Finley et al. (2005) used the percentage of short grass prairie for each of their sampled grids to estimate a grid-specific ψ value, the sum of ψ̂ values was 56.9 (SE = 4.13), or 56.9 of the 72 ˆ = 0.790, SE = 0.0574). Alternatively, they estimated ψ of 0.821 grids actually contained foxes ( ψ (SE = 0.0659) using the mean (66.9%) of the short-grass prairie habitat for the 72 grids. In either case, their estimates are slightly greater than the values of ψ estimated in this study with the same approaches, but negligibly so when the uncertainty of the estimates is taken into account. As cautioned in Finley et al. (2005), the mean number of animals estimated per grid cannot be extrapolated to a population estimate for eastern Colorado because the grids attract foxes from some unknown distance outside the trapping grid. SUMMARY Comparison of the estimates of the percent of 12-mi2 grids occupied by swift foxes in eastern Colorado does not appear to have changed since a comparable sample was taken of 72 grids in March, 1995 – January, 1997 (Finley et al. 2005). Using the average percentage of the grids in short grass prairie with the minimum AICc model, the earlier estimate was ψ̂ = 0.821 (SE 0.0659), compared to the current estimate of ψ̂ = 0.777 (SE = 0.0786). The estimated change is −0.044 (SE = 0.103, 95% CI −0.245 – 0.157). Summing the predicted occupancy values across the sampled grids for the respective studies provides a similar conclusion: Finley et al. (2005) found ψ̂ = 0.790 (SE = 0.0574), whereas this study found ψ̂ = 0.742 (SE = 0.0869), providing an estimate of the change of −0.048 (SE = 0.104, 95% CI −0.252 – 0.156). These differences are well within the sampling variation of the estimates, and do not suggest a decline in swift fox populations in eastern Colorado. LITERATURE CITED FINLEY, D. J., G. C. WHITE AND J. P. FITZGERALD. 2005. Estimation of swift fox population size and occupancy rates in eastern Colorado. Journal of Wildlife Management. In Press. BURNHAM, K. P., AND D. R. ANDERSON. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer-Verlag, New York, New York, USA. HUGGINS, R. M. 1989. On the statistical analysis of capture-recapture experiments. Biometrika 76: 133– 140. ______________. 1991. Some practical aspects of a conditional likelihood approach to capture experiments. Biometrics 47: 725–732. MACKENZIE, D. I., J. D. NICHOLS, G. B. LACHMAN, S. DROEGE, J. A. ROYLE, AND C. A. LANGTIMM. 2002. Estimating site occupancy when detection probabilities are less than one. Ecology 83: 2248–2255. WHITE, G. C., AND K. P. BURNHAM. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement: 120–138. Prepared by: ________________________ Dr. Gary C. White, Department Fishery & Wildlife Conservation Biology Colorado State University 71 �Table 1. Occupancy model selection results for 51 swift fox grids trapped in eastern Colorado, August 2004 to February, 2005. Model {p(.) ψ(SGP)} {p(sinMonth) ψ(SGP)} {p(SGP) ψ(SGP)} {p(cosMonth) ψ(SGP)} {p(.) ψ(.)} {p(sinMonth+cosMonth) ψ(SGP)} {p(T) ψ(.)} {p(cosMonth+cosMonth^2) ψ(SGP)} {p(t) ψ(.)} AICc ∆AICc 196.785 198.882 198.891 199.133 200.412 201.176 201.242 201.522 203.449 0 2.0969 2.1065 2.3486 3.6277 4.3916 4.4573 4.7372 6.6642 AICc Model Weights Likelihood 0.39689 1 0.1391 0.3505 0.13843 0.3488 0.12265 0.309 0.0647 0.163 0.04416 0.1113 0.04273 0.1077 0.03715 0.0936 0.01418 0.0357 Num. Deviance Par 3 190.274 4 190.012 4 190.022 4 190.264 2 196.162 5 189.843 3 194.731 5 190.189 4 194.579 Table 2. Closed population estimator model selection results for 51 swift fox grids trapped in eastern Colorado, August 2004 to February, 2005. Model {p(SGP+sinMonth)= c(SGP+sinMonth)+additive effect} {p(SGP+sinMonth+ cosMonth)=c(SGP+ sinMonth+cosMonth)+additiv e effect} {p(SGP)=c(SGP)+ additive effect} {p(sinMonth)= c(sinMonth)+ additive effect} {p(cosMonth)= c(cosMonth)+ additive effect} {p(cosMonth+ sinMonth)= c(cosMonth+ sinMonth)+additive effect} {p(.) c(.)} {p(T)=c(T)} {p(.)=c(.)} {p(T)=c(T)+ additive effect} {p(t)=c(t)+ additive effect} {p(g*t)=c(g*t)} AICc Delta AICc AICc Weights Model Likelihood No. Par Deviance 331.785 0 0.4213 1 4 323.666 333.739 1.9538 0.15861 0.3765 5 323.56 334.006 2.2207 0.13879 0.3294 3 327.935 334.421 2.636 0.11277 0.2677 3 328.35 336.195 4.4094 0.04646 0.1103 3 330.124 336.322 337.474 337.658 338.619 339.211 339.84 537.81 4.5372 5.6892 5.8723 6.8334 7.4255 8.0543 206.024 0.04359 0.0245 0.02236 0.01383 0.01028 0.00751 0 0.1035 0.0582 0.0531 0.0328 0.0244 0.0178 0 4 2 2 1 3 4 108 328.204 333.439 333.622 336.607 333.14 331.721 220.762 72 �350 Frequency ` 300 250 200 150 100 50 90 -9 5 80 -8 5 70 -7 5 60 -6 5 50 -5 5 40 -4 5 30 -3 5 20 -2 5 10 -1 5 05 0 Percent Short Grass Prairie Figure 1. Histogram of percentage of short grass prairie on 12-mi2 trapping grids comprising the sampling frame for this study. 350 Frame Sample Frequency ` 300 250 200 150 100 50 90 -9 5 80 -8 5 70 -7 5 60 -6 5 50 -5 5 40 -4 5 30 -3 5 20 -2 5 10 -1 5 05 0 Percent Short Grass Prairie Figure 2. Histogram showing the close relationship between the grids included in the sample compared to the sampling frame. A representative sample relative to the availability of the SGP variable was selected. 73 �` Occupancy Probability 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0% 20% 40% 60% 80% 100% Short Grass Prairie (Percent) Figure 3. Prediction of the probability of occupancy with 95% confidence intervals as a function of the percentage of short grass prairie on the 12-mi2 trapping grid. Ticks on the 0 and 1 lines indicate the status of the 51 trapping grids, with 36 of the grids recording foxes captured. Capture Probability ` 0.6 0.5 0.4 0.3 0.2 0.1 0 0% 20% 40% 60% 80% 100% Short Grass Prairie (Percent) p Sep p Jan p Oct p Feb p Nov p Dec Figure 4. Changes in initial capture probability for swift fox trapped in eastern Colorado on 12-mi2 grids, August 2004 – February, 2005. 74 �Reapture Probability 0.25 0.2 0.15 0.1 0.05 0 0% 20% 40% 60% 80% 100% Short Grass Prairie (Percent) c Sep c Jan c Oct c Feb c Nov c Dec Figure 5. Changes in recapture probability for swift fox trapped in eastern Colorado on 12-mi2 grids, August 2004 – February, 2005. 1 Probability of occupancy 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 20 40 60 80 100 Short grass grairie (%) Figure 6. Effect of the percentage of the 12–mi2 grid consisting of short-grass prairie habitat on the probability of occupancy by swift foxes trapped on 72 grids in eastern Colorado, March, 1995 – January, 1997, for the top-ranked AICc model {p(T + cos(Month) + cos2(Month)) ψ (SGP Proportion)} from Finley et al. (2005). The dashed lines are 95% confidence intervals for the estimated probability of occupancy. Ticks across the 0 and 1 occupancy lines are the observed occupancy values plotted against the percentage of short grass prairie for the 72 grids, with short grass prairie values dithered so that grids would not plot on top of each other. 75 �76 �Colorado Division of Wildlife July 2004 – June 2005 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3002 2 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Elk Conservation : Evaluation of GnRH Vaccine as a Long-term Contraceptive Agent in Female Elk: Effects on Reproduction and Behavior : Period Covered: July 1, 2004 – June 30, 2005 Author: D. L. Baker and J. G. Powers Personnel: J. Powers, M. Wild (National Park Service), L. Miller, J. Rhyan (National Wildlife Research Center), M. Conner (Utah State University), T. Nett (Colorado State University). All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without the permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We conducted a pilot experiment to evaluate the potential of GnRH vaccine as a long-term contraceptive agent in female elk. The objectives of this preliminary investigation were to characterize the antibody response of captive female elk to GnRH vaccine, evaluate the effectiveness of dart delivery of the agent, and document the presence and severity of systemic reactions (if any) to the treatment. Intramuscular injection of GnRH vaccine was accomplished in 4 female elk. Serum antibody responses were collected each month beginning in February, 2005 and submitted for analysis. Ultrasound imaging of the injection site was conducted in conjunction with monthly blood collections. Analysis of antibody levels have not been completed, however initial results from ultrasound imaging of vaccine injection sites reveal changes in muscle fiber and muscle tissue echogenicity compared to pre-treatment conditions. All animals show some level of disruption of normal muscle fiber patterns and changes in the quality of muscle tissue. These changes began to appear approximately 2 weeks post-treatment, peaked in severity in April then diminished during July, 2005. Based on results of this trial and similar ongoing investigations with captive white-tailed deer (Odocoileus virginianus), we prepared a detailed study plan describing research to evaluate GnRH vaccine as a long-term contraceptive agent in female elk (Appendix I). The objectives of this experiment are to evaluate the effects of this fertility control agent on pregnancy rates, reproductive behavior, and neonatal health and survival. We performed a power analysis to determine the sample sizes needed to detect treatment differences for pregnancy rates and reproductive behavior for captive female elk maintained at the Colorado’s Foothills Wildlife Research Facility in Fort Collins, Colorado. Based on this analysis, a sample size of 18-26 elk (equally divided between control and treatment groups) should provide adequate statistical power to detect treatment differences in pregnancy rates and reproductive behavior. A detailed description of hypotheses, rationale, methods, and statistical analyses are provided in this report. The status of publications in process is also provided (Appendix II). 77 �WILDLIFE RESEARCH REPORT EVALUATION OF GnRH VACCINE AS A LONG-TERM CONTRACEPTIVE AGENT IN FEMALE ELK: EFFECTS ON REPRODUCTION AND BEHAVIOR DAN L. BAKER P. N. OBJECTIVE Evaluate the effects of GnRH vaccine on pregnancy rates, fetal and neonatal growth and development, and reproductive behaviors in captive female elk. SEGMENT OBJECTIVES 1. Conduct a pilot experiment to evaluate individual animal variation in antibody response to GnRH vaccine and assess any side-effects of treatment. 2. Using results from the pilot experiment prepare a study plan program narrative and submit for internal peer review and extramural funding. 3. Summarize and analyze data from previous fertility control experiments and submit manuscripts to appropriate scientific journals. INTRODUCTION Hunting and culling have traditionally been used to regulate ungulate numbers but there are a growing number of situations where these methods are not feasible. Such places include urban and suburban areas where lethal removal is often opposed because of safety concerns or on ethical grounds (Decker and Connelly 1989, McAninch 1993, Wright 1993, McCullough et al. 1997). In addition, there are many conservation areas, and state and national parks where hunting may be inconsistent with other goals of resource management or where it is proscribed by law and policy (Leopold et al.1963, Frost et al.1997, Porter and Underwood 1999). In these situations, fertility control offers a potential alternative for limiting the growth of ungulate populations (Kirkpatrick and Turner 1985, Bomford 1990, Garrott et al. 1993). Additionally, development of fertility control technology may provide resource managers benefits beyond its value as a tool for balancing ungulates and their forage resources. Fertility control may reduce the rate of disease transmission in ungulates by regulating local host densities and pathogen shedding (Rhyan and Drew 2002, Miller et al. 2004). Simulation modeling suggests that, in some situations, fertility control can be as effective as culling in reducing endemic disease or the density of susceptible hosts (Hone 1992, Barlow 1996). Extensive research has been devoted to developing anti-fertility agents that are safe, effective, reversible and economical (Fagerstone et al. 2002) and models have been developed to represent effects of fertility control on population dynamics of wild ungulates (Garrott and Siniff 1992, Seagle and Close 1996, Hobbs et al. 2000). To date, however, only modest successes have been achieved and a practical and acceptable method of controlling reproduction in free-ranging wildlife populations has not yet been attained. In previous research, we administered gonadotropin-releasing hormone (GnRH) agonist (leuprolide acetate) in a biodegradable implant to captive and free-ranging female elk and achieved 100% contraception for one breeding season, without significant behavioral or physiological side-effects (Baker et al. 2002,2004). However, despite the demonstrated efficacy and safety of this approach over existing technology, practical application is compromised by the need for annual treatments in fall, prior to the breeding season, a time when capture efficiency is low compared to winter and early spring. 78 �GnRH Vaccine An alternative approach involves immunization against GnRH. GnRH is a small, 10 amino acid, neuropeptide with an obligatory role in reproduction. It is naturally secreted in a pulsatile pattern from neurons in the hypothalamus and specifically directs gonadotropes in the anterior pituitary gland to synthesize and release luteinizing hormone (LH) and follicle stimulating hormone (FSH). These latter two hormones, in turn, control proper functioning of ovaries in females and testes in males (Hazum and Conn 1998). To successfully immunize an animal against GnRH, it is necessary to make this endogenous protein appear foreign to the host. Therefore, many copies of the peptide are coupled to the highly immunogenic carrier molecule keyhole limpet hemocyanin (KLH). When combined with a potent adjuvant the GnRH-KLH conjugate stimulates the host’s immune system to produce antibodies against GnRH as well as KLH. Anti-GnRH antibodies bind to GnRH in the hypothalamic -pituitary portal vessels and prevent the hormone from attaching to receptors on the gonadotropes. This suppresses secretion of LH and FSH, halting the hormonal cascade that is ultimately responsible for folliculogenesis and ovulation. This condition persists as long as there are sufficient antibodies to bind to all circulating GnRH. The use of GnRH vaccine as a fertility control agent is not new. It has been administered to a variety of domestic ungulates including horses (Rabb et al. 1990), cattle (Adams and Adams 1986), swine (Meloen et al. 1994), and sheep (Brown et al. 1994). It’s use as a contraceptive agent in wild ungulates has been limited, however by the need for multiple initial treatments, annual boosters, and the use of the controversial FCA and FIA to enhance the immune response of the vaccine (Miller et al. 2000b, Curtis et al. 2002). Recently, the impracticality of this approach for wildlife applications has been largely overcome by the development of a new adjuvant by scientists at the National Wildlife Research Center (NWRC) in Fort Collins, Colorado, USA. The alternative adjuvant is thought to be safer and, equally as effective in eliciting an antibody response, as FCA or FIA. The new adjuvant (AdjuVacTM) is derived from a USDAapproved Johne’s disease vaccine (MycoparTM) which has previously been approved for use in food animals by USDA/APHIS(http://www.aphis.usda.gov/ws/nwrc/research/gnrh.html) . A single application of GnRH-KLH and AdjuVacTM) may prove to be a safe, practical, and effective multi-year immunocontraceptive for wild ungulates. This approach has several potential advantages over other methods of contraception. These include: 1) a single treatment may provide long-term (2 + years) of infertility when administered to pregnant animals during winter 2) effectiveness of treatment may be > 90% during the first breeding season following immunization 3) infertility should be reversible 4) the agent should not cause significant behavioral or physiological side-effects 5) the agent should be safe for pregnant animals and the developing fetus 6) the proteinaceous nature of the GnRH-KLH immunogen should eliminate the possibility of passage through the food chain 7) the small volume required for effective contraception should facilitate administration by syringe dart 8) the agent is currently being evaluated for FDA approval as a New Animal Drug and therefore may be available for commercial use in the near future. Preliminary investigations evaluating GnRH-KLH vaccine in captive wild horses (Killian et al. 79 �2005, in preparation), bison (Miller et al. 2004) and white-tailed deer (Miller et al. 2004, unpublished data) are promising and USDA/APHIS is seeking FDA registration of the new vaccine and adjuvant (GonaCon/AdjuVacTM). However, many unanswered questions must be addressed before this potential contraceptive can be considered an effective and acceptable method of population control in free-ranging elk. Research is needed to evaluate the effectiveness and duration of this approach in elk, the effects on elk reproductive physiology, the effect on elk social structure of removing individuals from the breeding population, and the practicality/feasibility of application in wild populations. Captive Elk Experiments Rationale: The efficacy of GnRH-KLH vaccine depends on sufficient stimulation of the immune system and subsequent production of antibodies against this reproductive hormone. Thus, an initial step in assessing the potential of a single application of GnRH-KLH vaccine as a contraceptive agent in elk is to evaluate antibody response to treatment. Such studies have been conducted in wild horses (Killian et al. unpublished data), bison (Miller et al. 2004, in press), and white-tailed deer (Miller et al. unpublished data) but not in elk. Results of these studies indicate that the immunological response to GnRH-KLH vaccine is not uniform across species and highly variable within species. As a consequence, a species specific experiment is required to measure peak antibody response in female elk, time to peak response, and duration of response. Although such titers may not provide a quantitative measure of infertility, their characterization is of interest because sustained elevation of anti-GnRH antibody titers has been consistently associated with infertility in other species. Thus, the primary purpose here was to provide preliminary information on antibody response in elk, to determine optimum sample sizes for future experiments, to assess gross and clinicopathalogical side-effects of treatment (if any), and to evaluate remote delivery of the vaccine. Objectives: We conducted a controlled pilot experiment with captive elk to: 1) characterize serum antibody response of captive female elk to GnRH-KLH vaccine. 2) evaluate the effectiveness of dart delivery of GnRH-KLH vaccine. 3) evaluate presence and severity of systemic reactions or abscesses (if any) to the GnRH-KLH/AdjuVacTM vaccine treatment 4) determine if vaccination with GnRH/AdjuVacTM causes seroconversion to Johne’s disease mycobacteria. This experiment was conducted at the Colorado Division of Wildlife’s Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado, USA with the approval of the Colorado Division of Wildlife Animal Care and Use Committee (# 1-2005) and in compliance with U.S. Federal Animal Welfare Act Regulations). METHODS We conducted an experiments with 4, non-pregnant, multiparous adult female elk beginning 7 February 2005. These elk were closely monitored into July 2005 to meet initial objectives of the pilot experiment, but the health of these elk and responses to the vaccine will be monitored until 1 August 2007. The captive elk used in this experiment were permanently maintained at FWRF and were trained to repeated handling, weighing, and blood sampling procedures. On the day before treatment (7 February), elk were moved from holding pastures (5 ha) and placed in individual isolation pens. The next day, each elk received a single injection of 1000µ :g of GnRH-KLH conjugate (0.5 ml aqueous solution) emulsified in 1.0 ml of AdjuVacTM, as a water in oil emulsion. The conjugate was be transferred into single use, 1 ml, 13-mm-diameter, barbless darts equipped with gel-collared 32-mm-long needles (Pneu-dart, Williamsport, Pennsylvania, USA). 80 �Prior to darting, individual elk were placed in a handling chute and lightly sedated with xylazine hydrochloride (15-20 mg/animal, IV). This dose allowed the animal to remain standing in the chute and minimized excitation associated with discharge of the dart gun. We examined of the reproductive tract of each elk using rectal palpation and ultrasonographic techniques, collected blood samples (20-30 ml) and measured body weight (∀ 0.5 kg). Elk were remotely injected in the biceps femoris muscle with a dart fired from a CO2-powered pistol (DanInjectTM, Wildlife Pharmaceuticals, Fort Collins, Colorado, USA) from a distance of approximately 3 meters. In order to accurately determine the precise dose of GnRHKLH delivered to each elk, darts were weighed before and after injection. If a dart failed to discharge or only partially injected the prescribed dose, additional darts were fired until the complete dose was delivered to the animal. Once the vaccine had been administered, sedation was reversed with yohimbine (30 mg, IV) (Antagonil®, Wildlife Laboratories, Fort Collins, Colorado, USA) and elk were returned to holding pastures. One of the elk (F86) used in this experiment was previously used in a Brucella abortus Strain 19 vaccination study (1998). It may still retain antibodies or immune modulation relative to this organism that could influence its immune response to the AdjuVacTM portion of the GnRH vaccine. This elk has not shown any evidence of being affected by Johne’s disease (Mycobacterium avium partuberculosis). However, the AdjuVacTM adjuvant uses small amounts of a remarkably similar killed bacterium (derived from the Johne’s vaccine MycoparTM). This could cause seroconversion indistinguishable from Johne’s disease. Pre-vaccination serum was submitted for a large animal biochemistry profile, Johne’s disease ELISA, and Strain 19 brucellosis vaccination serology. Elk were monitored for local injection site reactions (swelling, erythema, drainage) on a daily basis for 1 week, and on a biweekly basis for the following 2 months. A second biochemistry profile was submitted if elk showed symptoms of local or systemic inflammation. Ultrasound examination of the injection site may was used to evaluate abscess and granuloma formation. Serum anti-GnRH antibody production was monitored on a bimonthly basis until peak anti-body titers were determined, then on a bimonthly basis thereafter until termination of the experiment. Once a measurable (P < 0.05) decrease in anti-body levels is observed, the need to continue monitoring antiGNRH antibodies will be reevaluated. Once peak response in each elk has been achieved, a second reproductive examination will be performed to evaluate any changes in ovarian structures. Analysis: This was a descriptive experiment and no hypotheses were tested. We used descriptive statistics to examine changes in antibody titers over time. Schedule: Date Activity 12 January 2005 Submit study plan for ACUC approval 7 February 2005 Move experimental elk to individual isolation pens 8 February 2005 Perform pre-treatment exams and administer GnRH-KLH conjugate to elk 8 February to 8 March 2005 Intensive health monitoring of elk February 2005 to August 2006 Ongoing health and anti-GnRH antibody monitoring, and compile and analyze data pertinent to Expt. 2 81 �RESULTS AND DISCUSSION Intramuscular injection of GnRH vaccine was accomplished in 4 female elk. Serum antibody responses of experimental elk were collected each month beginning in February, 2005 and submitted for analysis. Initial results from ultrasound imaging of vaccine injection sites reveal changes in muscle fiber and muscle tissue echogenicity compared to pre-treatment conditions. All animals show some level of disruption of normal muscle fiber patterns and changes in the quality of muscle tissue. These changes began to appear approximately 2 weeks post-treatment and have not been resolved to date. SUMMARY Results of the pilot experiment are incomplete at this time. Initial results suggest that GnRH vaccine can be delivered via intramuscular dart injection. However, until laboratory results are completed, it is unknown if the antibody response of elk to GnRH vaccine will be sufficiently high to suppress fertility. Regardless, injection site reaction to the vaccine is a concern and warrants further evaluation. LITERATURE CITED ADAMS, T. H., AND B. M. ADAMS. 1990. Reproductive function and feedlot performance of beef heifers actively immunized against GnRH. Journal of Animal Science 68:2793-2802. BAKER, D. L., M. A. WILD, M. M. CONNER, H. B. RAVIVARAPU, R. L. DUNN, AND T. M. NETT. 2002. Effects of GnRH agonist (leuprolide) on reproduction and behavior in female wapiti (Cervus elaphus nelsoni). Reproduction Supplement 60:155-167. ____________, _________, M. M. CONNER, H. B. RAVIVARAPU, R. L. DUNN, AND T. M. NETT. 2004. Gonadotropin-releasing hormone agonist: a new approach to reversible contraception in female deer. Journal of Wildlife Diseases 40:713-724. BARLOW, N. D. 1996.The ecology of wildlife disease control: simple models revisited. Journal of Applied Ecology 33:303-314. BOMFORD, M. 1990. A role for fertility control in wildlife management. Department of Primary Industries and Energy, Bureau of Rural Resources Bulletin No. 7, Australian Government Publishing Service, Canberra, Australia. BROWN, D. B., T. T. CAI, AND A. DASGUPTA. 2001.Interval estimation for a binomial proportion. 2001. Statistical Science 16:101-133. CURTIS, P. D., R. L. POOLER, M. E. RICHMOND, L. A. MILLER, G. F. MATTFELD, AND F. W. QUIMBY. 2002. Comparative effects of GnRH and porcine zona pellucida (PZP) immunocontraceptive vaccines for controlling reproduction in white-tailed deer (Odocoileus virginianus). Reproduction Supplement 60:131-141. DECKER, D., AND A. N. CONNELLY.1989. Deer in suburbia-pleasure or pets. Conservationist 43:46-49. FAGERSTONE, K. A., M. A. COFFEY, P. D. CURTIS, R. A. DOLBEER, G. J. KILLIAN, L. A. MILLER, AND L. WILMOT. 2002. Wildlife fertility control. Wildlife Society Technical Review 02-2. The Wildlife Society, Bethesda, Maryland, USA. FROST, H. C., G. L. STORN, M. J. BATCHELLER, AND M. J. LOVALLO. 1997. White-tailed deer management at Gettysburg National Military Park and Eisenhower National Historic Site. Wildlife Society Bulletin 25:462-469. GARROTT, R. A., AND D. B. SINIFF. 1992. Limitations of male-oriented contraception for controlling feral horse populations. Journal of Wildlife Management 56:456-464. ______________, P. J. WHITE, AND C. A. VANDERBIL WHITE. 1993. Overabundance: an issue for conservation biologist? Conservation Biology 7:946-949. HAZUM, E., AND P. M. CONN. 1998. Molecular mechanism of gonadotropin releasing hormone (GnRH) action. I. The GnRH receptor. Endocrine Review 9: 379-386. 82 �HOBBS, N. T., D. C. BOWDEN, AND D. L. BAKER. 2000. Effects of fertility control on populations of ungulates: general stage-structured models. Journal of Wildlife Management 64: 473-491. HONE, J. 1992. Rate of increase and fertility control. Journal of Applied Ecology 29:695-698. KIRKPATRICK, J. F., AND J. W. TURNER, JR. 1985. Chemical fertility control and wildlife management. Bioscience 35: 485-491. LEOPOLD, A. S., S. A. CAIN, C. M. COTTAM, AND I. GABRIELSON. 1963. Wildlife management in the national parks. Transactions of the North American Wildlife and Natural Resources Conference 28:28-45. MCCULLOUGH, D. R., K. W. JENNINGS, N. B. GATES, B. G. ELLIOT, AND J. E. DIDONATO. 1997. Overabundant deer populations in California. Wildlife Society Bulletin 25: 478-483. MCANINCH, J. B., editor. 1993. Urban deer: a manageable resource? Proceedings of the 1993 Symposium of the North Central Section, The Wildlife Society, St. Louis, Missouri, USA. MELOEN, R. H., J. A. TURKSTRA, H. LANKHOF, W. C. PUIJK, W. M. M. SCHAAPER, G. DIJKSTRA, C. J. G. WENSING, AND R. B. OONK.1994. Efficient immunocastration of male piglets by immunoneutralization of GnRH using a new GnRH-like peptide. Vaccine 12:741-746. MILLER, L. A., J. C. RHYAN, AND M. DREW. 2004. Contraception of bison by GnRH vaccine: a possible means of decreasing transmission of brucellosis in bison. Journal of Wildlife Diseases 40:725730. __________ , _________, AND ___________ . 2000. Immunocontraception of white-tailed deer with GnRH vaccine. American Journal of Reproductive Immunology 44:266-274. PORTER, W. F., AND B. UNDERWOOD. 1999. Of elephants and blind men: deer management in the U.S. national parks. Ecological Applications 9:3-9. RABB, M. H., D. L. THOMPSON, JR., B. E. BARRY, D. R. COLBORN, K. E. HEHNKE, AND F. GARZA, JR. 1990. Effects of active immunization against GnRH on LH, FSH, and prolactin storage, secretion, and response to their secretagogues in pony geldings. Journal of Animal Science 68:3322-3329. RHYAN, J. C., AND M. D. DREW. 2002. Contraception: A possible means of decreasing transmission of brucellosis in bison. In: Brucellosis in elk and bison in the Greater Yellowstone Area, T.J. Kreeger (ed.). Greater Yellowstone Interagency Brucellosis Committee, Wyoming Game and Fish Department, Cheyenne, Wyoming, 99-108. SEAGLE, S. W., AND J. D. CLOSE.1996. Modeling white-tailed deer population control by contraception. Biological Conservation 76:87-91. WRIGHT, R. G. 1993. Wildlife management in parks and suburbs: alternatives to sport hunting. Renewable Resources Journal 11: 18-22. Prepared by: _____________________ Dan L. Baker, Wildlife Researcher 83 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2004 – FY 2007 State of: Cost Center: Work Package: Task No.: Colorado 3430 3002 2 Federal Aid Project No.: N/A : Division of Wildlife : Mammals Research : Elk Conservation : Evaluation of GnRH Vaccine as a LongTerm Contraceptive Agent in Female Elk: Effects on Reproduction and Behavior : EVALUATION OF GnRH VACCINE AS A LONG-TERM CONTRACEPTIVE AGENT IN FEMALE ELK: EFFECTS ON REPRODUCTION AND BEHAVIOR Principal Investigator Dan L. Baker, Wildlife Researcher, Mammals Research Cooperators Lowell A. Miller, USDA/APHIS, National Wildlife Research Center Jack C. Rhyan, USDA/APHIS, National Wildlife Research Center Mary M. Conner, Department of Forestry, Range, and Wildlife Science, Utah State University Terry M. Nett, Department of Biomedical Science, Colorado State University Jenny G. Powers, National Park Service Margaret A. Wild, National Park Service STUDY PLAN APPROVAL Prepared by: ____________________________ _ Date: ______________________ Submitted by: _____________________________ Date: ______________________ Reviewed by: _____________________________ Date: _______________________ _____________________________ Date: _______________________ _____________________________ Date: _______________________ Reviewed by: _____________________________ Biometrician Date:________________________ Approved by: _____________________________ Mammals Research Leader Date:_________________________ 84 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH State of : Cost Center: Work Package: Study No.: Colorado 3430 3002 : : : : Division of Wildlife Mammals Research Program Elk Conservation Evaluation of GnRH Vaccine as a LongTerm Contraceptive Agent in Female Elk: Effect on Reproduction and Behavior A. STUDY TITLE: Evaluation of GnRH Vaccine as a Long-term Contraceptive Agent in Female Elk: Effects on Reproduction and Behavior B. NEED: Overabundant wild ungulate populations have become a significant problem for natural resource managers in many areas of North America. Unregulated populations can cause adverse effects that are ecological, economic, or political in scope and resolving these problems often requires managing excessive animal numbers (Jewell and Holt 1981, Garrott et al. 1993). Hunting and culling have traditionally been used to regulate ungulate numbers but there are a growing number of situations where these methods are not feasible. Such places include urban and suburban areas where lethal removal is often opposed because of safety concerns or on ethical grounds (Decker and Connelly 1989, McAninch 1993, Wright 1993, McCullough et al. 1997). In addition, there are many conservation areas, and state and national parks where hunting may be inconsistent with other goals of resource management or where it is proscribed by law and policy (Leopold et al.1963, Frost et al.1997, Porter and Underwood 1999). In these situations, fertility control offers a potential alternative for limiting the growth of ungulate populations (Kirkpatrick and Turner 1985, Bomford 1990, Garrott et al. 1993). Additionally, development of fertility control technology may provide resource managers benefits beyond its value as a tool for balancing ungulates and their forage resources. Fertility control may reduce the rate of disease transmission in ungulates by regulating local host densities and pathogen shedding (Rhyan and Drew 2002, Miller et al. 2004). Simulation modeling suggests that, in some situations, fertility control can be as effective as culling in reducing endemic disease or the density of susceptible hosts (Hone 1992, Barlow 1996). Extensive research has been devoted to developing anti-fertility agents that are safe, effective, reversible and economical (Fagerstone et al. 2002) and models have been developed to represent effects of fertility control on population dynamics of wild ungulates (Garrott and Siniff 1992, Seagle and Close 1996, Hobbs et al. 2000). To date, however, only modest successes have been achieved and a practical and acceptable method of controlling reproduction in free-ranging wildlife populations has not yet been attained. GnRH Agonist Gonadotropin-releasing hormone (GnRH) is an endogenous neuropeptide that has an obligatory role in reproduction. It is naturally secreted in a pulsatile pattern from neurons in the hypothalamus and specifically directs gonadotropes in the anterior pituitary gland to synthesize and release luteinizing hormone (LH) and follicle-stimulating hormone (FSH). These latter two hormones, in turn, control proper functioning of the ovaries in females and testes in males (Hazum and Conn 1988). 85 �The chemical structure of endogenous GnRH has been determined (Matsuo et al. 1971) and alterations in the molecule have led to the synthesis of potent GnRH agonist analogs (Karten and Rivier 1986). Long-term treatment with GnRH agonists has been shown to prevent ovulation by decreasing GnRH receptors on gonadotropes, receptor sensitivity to GnRH (Nett et al. 1981), pituitary LH content (Aspden et al. 1996), and by suppressing pulsatile secretion of LH and FSH (D’Occhio et al. 1996). Agonists of GnRH have been used in domestic animals as fertility agents for controlling ovarian activity, gonadal steroidogeneis, and reproduction (McNeilly and Fraser 1987, Montovan et al. 1990, D’Occhio et al. 2002). In previous research, the GnRH agonist, leuprolide, was administered to captive female elk (Cervus elaphus) and mule deer (Odocoileus hemionus) in a controlled release bioimplant and achieved 100% infertility for one breeding season, without significant behavioral or physiological sideeffects (Baker et al. 2002, 2003, 2004). However, despite the demonstrated efficacy and safety of this approach over existing technology, practical application is compromised by the need for annual treatments in fall, prior to the breeding season, a time when capture efficiency is low compared to winter and early spring. Immunocontraception To date, most wildlife contraceptive efforts have been directed toward development of a safe and effective immunocontraceptive vaccine. The immunocontraceptive target antigen that has received the most research and management attention is porcine zona pellucida (PZP). Porcine zona pellucida has been administered experimentally to more than 70 species of wild mammals (Kirkpatrick et al. 1997). This approach relies on host antibodies formed against PZP to block sperm receptor sites on the ovum, thereby preventing fertilization and pregnancy (Dunbar and Schwoebel 1988). The PZP vaccine has been shown to be 85-90% effective in most ungulates, can be administered by syringe dart, is reversible, does not interfere with ongoing pregnancies, and most importantly, the immunogen is proteinaceous and therefore, is not likely to pose a threat to the environment or to non-target species, including humans (Kirkpatrick et al. 1990, Turner et al. 1992, Miller et al. 2000a, Kirkpatrick and Turner 2002, Shideler et al. 2002, Naugle et al. 2002). However, despite these desirable characteristics treatment inefficiency and undesirable sideeffects have limited management application of PZP vaccine (Rudolph et al. 2000, Turner and Kirpatrick 2002, Naugle et al. 2002). Specifically, practical application is compromised by the requirement that the target animal must receive two initial injections within 1-2 months of each other (Walter et al. 2002). Second, with the exception of SpayVacTM which encapsulates PZP within a cholesterol/phospholipid formulation (Fraker et al. 2002), effective duration is typically < 1 year; consequently, annual booster inoculations are required (Kirkpatrick et al. 1996; Turner et al. 1996). Third, while no long-term health effects have been reported for animals treated with PZP (Kirkpatrick et al. 1995, Miller et al. 2000a, Turner and Kirkpatrick 2002), extended estrous cycling and associated breeding behavior have been reported for white-tailed deer (Turner et al. 1992, 1996; McShea et al. 1997), horses (Plotka et al. 1989), elk (Heilmann et al. 1997), and fallow deer (Fraker et al. 2002). By prolonging the breeding season in males and females, PZP vaccine treatments could result in late pregnancies, parturition beyond the normal early summer period, and unpredictable and abnormal behavioral consequences. Finally, for an effective immune response, the PZP antigen must be administered with an adjuvant - a substance that enhances the specific immune response to the antigen. At present, the most effective adjuvants used with PZP are Freund’s complete (FCA) and Freund’s incomplete adjuvant (FIA). In some species, however, this combination has been shown to cause severe systemic reactions, chronic pain, and abscesses at the injection site (Anderson and Alexander 1983, Stills and Bailey 1991, Leenaars et al. 1996) and, as a consequence, it is unlikely that the Food and Drug Administration (FDA) will grant approval for the use of PZP vaccine containing these adjuvants. Thus, in the near future, practical application of immunocontraception for wildlife species will depend on development and use of improved vaccines with different adjuvants. 86 �GnRH Vaccine An alternative to PZP immunocontraception involves immunization against GnRH. To accomplish this, it’s necessary to make this endogenous protein appear foreign to the host. Therefore, many copies of the peptide are typically coupled to a highly immunogenic carrier molecule such as keyhole limpet hemocyanin (KLH) (Levy et al. 2004). When combined with a potent adjuvant, the GnRH-KLH conjugate stimulates the host’s immune system to produce antibodies against GnRH as well as KLH. Anti-GnRH antibodies bind to endogenous GnRH in the hypothalamic - pituitary portal vessels and prevent the hormone from attaching to receptors on the gonadotropes. This mechanism suppresses secretion of LH and FSH and interrupts the normal cascade of hormonal events that are ultimately responsible for folliculogenesis and ovulation. The use of GnRH vaccine as a fertility control agent is not new. It has been administered to a variety of domestic ungulates including horses (Rabb et al. 1990, Turkstra et al. 2005), cattle (Adams and Adams 1990), swine (Meloen et al. 1994), and sheep (Brown et al. 1994). However, its use as a contraceptive agent in wild ungulates has been limited by the need for multiple initial treatments, annual boosters, and the use of the controversial FCA and FIA to enhance the immune response of the vaccine (Miller et al. 2000b, Curtis et al. 2002). Recently, however, the impracticality of this approach for wildlife applications has been largely overcome by the development of a new adjuvant by scientists at the National Wildlife Research Center (NWRC) in Fort Collins, Colorado, USA. This adjuvant is thought to be safer than, and equally as effective, as FCA and FIA in eliciting an antibody response. The new adjuvant (AdjuVacTM) is derived from a United States Department of Agriculture (USDA)-approved Johne’s disease vaccine (MycoparTM) which has previously been approved for use in food animals by the USDA, Animal and Plant Health Inspection Service (APHIS) (http://www.aphis.usda.gov/ws/nwrc/research/gnrh.html). A single application of GnRH-KLH and AdjuVacTM (GonaCon™) has the potential to be a safe, practical, and effective multi-year immunocontraceptive for wild ungulates. As a contraceptive for wildlife, this agent offers the following desirable characteristics: 1) A single treatment should provide long-term infertility (2 + years) when administered either to non-pregnant females prior to the breeding season or to pregnant females during gestation. 2) Treatment effectiveness should be 85-90% the first breeding season. 3) Infertility should be reversible. 4) The agent should be safe for pregnant animals and the developing fetus 5) The agent should not cause significant behavioral or physiological side-effects. 6) The proteinaceous nature of the GnRH-KLH immunogen should eliminate the possibility of passage through the food chain. 7) The small volume required for effective contraception should facilitate administration by syringe dart. 8) The agent is currently being evaluated for FDA approval as a New Animal Drug and therefore, could be available for commercial use in deer and elk. Preliminary investigations evaluating a single application of GnRH-KLH vaccine (GonaCon™) in captive female wild horses (Equus caballus) (Killian et al. 2004), bison (Bison bison) (Miller et al. 2004), white-tailed deer (Odocoileus virginianis) (Miller et al. unpublished data), California ground squirrels (Spermophilus beecheyi) (Nash et al. 2004), New Zealand white rabbits (Oryctolagus cunniculi) (Powers et al. in preparation) and domestic male cats (Felis catus) (Levy et al. 2004) are promising. All female bison (n = 5) treated with a single injection containing 1800µg GnRH-KLH and AdjuVac™ have remained infertile for 3 breeding seasons (Miller et al. 2004, Rhyan and Miller unpublished data). Similarly, mares (n = 18) treated with either 1800µg or 2800µg GnRH-KLH vaccine have been shown to be 100% infertile after one breeding season (Killian et al. 2004). While these results are encouraging, 87 �additional species specific studies are needed to confirm the safety and effectiveness of this contraceptive approach in wildlife. Our goal in this investigation is to conduct controlled experiments with captive elk to investigate the important attributes of this technology prior to management application in free-ranging wild ungulates. C. OBJECTIVES 1. To evaluate the effective duration of a single dose application of GnRH-KLH vaccine in preventing subsequent reproduction in pregnant elk. 2. To evaluate the effect of GnRH-KLH immunization on serum concentrations of LH and progesterone, corpus luteum (CL) function and viability, and neonatal health and survival. 3. To evaluate the effect of the GnRH-KLH vaccine on breeding behavior of captive elk following a contraceptive treatment applied during the second trimester of pregnancy. 4. To evaluate the physiological side-effects (if any) of GnRH-KLH vaccination on female elk, the developing fetus, and/or neonate. D. EXPECTED RESULTS OR BENEFITS The Colorado Division of Wildlife’s Strategic Plan (2002-2007), charges the agency with “finding alternatives for game management when hunting is not a viable option” (H-1.5, p 9). One of the performance measures for accomplishing this objective is to develop alternative methods of population control. Successful development and testing of the fertility control technology described in this proposal has the potential to accomplish this objective and provide resource managers with a non-lethal strategy for controlling the growth of some wild ungulate populations when sport hunting is infeasible. E. APPROACH Proposed Research: Working Hypothesis.: In this investigation, we test the general hypothesis that a single intramuscular application of a novel anti-GnRH vaccine in mid-gestation female elk will prevent pregnancy the following breeding season and may prevent pregnancy for two or more subsequent seasons. The exact duration of infertility is unknown but will be determined in this investigation. However, permanent sterility is not anticipated and we expect treated females to eventually return to normal estrous behavior and fertility as antibody titers decline. Furthermore, we don’t expect immunization against GnRH-KLH to cause substantial negative physiological or behavioral effects in peri-parturient females or neonatal calves. However, since GnRH-KLH vaccine is expected to suppress reproductive hormones, we predict diminished breeding behaviors in treated female elk compared to controls. Design: We will test the effects of GnRH-KLH vaccine treatments on pregnancy rates in elk using a Fisher’s exact test and evaluate serology of reproductive hormones, anti-GnRH antibody titers, and breeding behavior using a one-way ANOVA for a completely randomized design with repeated measures structure. Animals: Approximately, 20 adult female elk (2-12 years of age), 2 mature, and 2 sub-adult male elk will be used in this study. Elk are permanently maintained at the Colorado Division of Wildlife’s Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado. The female elk used in these experiments have been previously trained to repeated handling, weighing, ultrasound, and blood sampling procedures. When not involved in periodic intensive sampling procedures required by this study, elk are maintained in fenced paddocks (5 ha) containing native vegetation and fed a diet consisting of ad libitum quantities of grass-alfalfa hay, grain supplement, trace mineral block, and water. 88 �Experiment 1: Effects of GnRH-KLH vaccine on pregnancy rates (objective 1) Hypothesis: One year post-vaccination, female elk vaccinated intramuscularly with 1000µg GnRH-KLH + adjuvant (AdjuVacTM) during the second trimester of gestation will have significantly (P < 0.05) higher anti-GnRH antibody concentrations and lower pregnancy rates than females treated with adjuvant alone. Rationale: Vaccination with GnRH-KLH + AdjuVacTM has successfully stimulated sufficient anti-GnRH antibody production to prevent pregnancy in a wide range of species including many ungulate species (Curtis et al. 2002, Miller et al. 2004, and Killian et al. 2004). Of particular importance to our experiment is the ongoing study with white-tailed deer (Miller, personal communication). Preliminary results suggest that multiple year infertility has been achieved with a single treatment of GnRH-KLH vaccine. Since elk and deer are taxonomically similar and share many common ecological, morphological and physiological traits, we expect to observe a similar contraceptive response for both species. Methods: Many of the measurements in this experiment (i.e. conception/parturition dates, pregnancy rates, luteal function, and hormone concentrations) will be facilitated by controlling the breeding period of female elk. To do this, we will attempt to synchronize estrous cycles of female elk by using progesterone secreting controlled internal drug release (CIDR) implants (Fennessy et al. 1990, Asher et al. 1993, Lucy et al. 2001). The CIDR implants will be placed in female elk during the last week of August 2005 (see appendix A for detailed protocol). Following CIDR removal (approximately the first week of September 2005), reproductively sound male elk will be released into the same pasture as females (see appendix B for breeding soundness exam protocol). During January 2006, we will determine pregnancy status of all females. Once pregnancy status is determined, pregnant elk will be blocked according to age and body condition, and randomly assigned to either a control or treatment group. We will determine pregnancy rates of treatment and control elk each year thereafter until differences in treatment effects can no longer be detected (P > 0.05). Treatment and control formulations will be applied in the following the manner. On the day of application (approximately mid-January, 2006), animals will be moved from paddocks, weighed (± 0.5 kg), and lightly sedated with xylazine hydrochloride (Rompun; Bayer AG, Leverkusen, Germany; 45-55 mg/animal, IM). This dose should allow animals to remain standing in the handling chute and minimize any possible stress or pain associated with blood collection, reproductive tract examination, ultrasound imaging of injection site, and dart delivery of treatments. All elk will be remotely injected in the area of the biceps femoris muscle with 1 ml, 13-mm-diameter, barbless darts equipped with gel-collared 32-mmlong needles (Pneu-dart, Williamsport, Pennsylvania, USA) fired from a CO2 – powered pistol (DanInjectTM, Fort Collins, Colorado, USA). Darts will be fired from approximately 3 m and will contain either GnRH-KLH vaccine + AdjuVacTM) (treatment) or AdjuVacTM alone (control). In order to accurately determine the precise dose delivered to each elk, darts will be weighed (0.001g) before and after injection. Once all elk have been treated, sedation will be reversed with yohimbine (30 mg, IV) (Antagonil®, Wildlife Pharmaceuticals, Fort Collins, Colorado, USA) and animals will be returned to holding pastures. Antibody titers will be measured immediately prior to treatment application and then on a monthly or bimonthly basis until maximal levels are reached. Following peak response, these measurements will be made on a less frequent basis until just prior to subsequent breeding seasons (September 2006, 2007, 2008). At that time, females will be sampled again. Except for this period, monthly sampling will be terminated following October 2006. 89 �The effective duration of GnRH-KLH vaccine in controlling fertility in elk will be determined by comparing pregnancy rates of treated and control elk during January 2007 and 2008. Once pregnancy rates are determined, pregnant elk will be aborted using a combination of prostaglandin F2 α and dexamethasone (Bates et al. 1982) (see appendix C for detailed protocol). Blood sampling procedures for antibody determination, pregnancy rates, hormone concentrations, and serum chemistry and hematology will follow methods previously described. While elk are sedated, blood samples (20-40 ml) will be collected via jugular venipuncture. Serum will be stored at – 70 ºC until analyzed for LH, progesterone, and anti-GnRH antibodies. Following the last blood collection, sedation will be reversed and elk returned to paddocks. Measurements: Anti-GnRH antibodies will be measured using an enzyme linked immunosorbent assay (ELISA) developed by scientists at the NWRC (USDA/APHIS) and/or using radioimmunoassay (RIA) techniques at Colorado State University’s Animal Reproduction and Biotechnology Laboratory (ARBL). The effect of GnRH-KLH vaccine on reproduction will determined in January 2007 and 2008 by measuring pregnancy rates using the presence or absence of pregnancy specific protein B (PSPB) (Huang et al. 2000), rectal palpation (Greer and Hawkins 1967, Hein et al. 1991) and/or ultrasound (Curran et al. 1986). Analysis: To determine the sample sizes needed to detect treatment differences for pregnancy rates, we performed a power-based sample size determination for a one-sided Fisher’s exact test using a software program (NCSS Pass 2000) (Kang and Kim 2004, Krishnamoorthy and Thompson 2002). For this analysis, we used the highest reported pregnancy rate (approximately 30%) for GnRH-KLH vaccine treated white-tailed deer, 1 year post-vaccination (Curtis et al. 2002). To represent the best and worst case scenarios for control elk, we calculated the sample size requirements for a 90% and 100% pregnancy rate. Based on this analysis, between 18−26 female elk (equally divided between control and treatment groups) should provide an adequate sample size to detect expected differences in pregnancy rates (Table 1). Because the pregnancy rates of the control and treatment groups are expected to be close to 1.0 and 0, respectively, the normal approximation invoked for testing the difference between 2 proportions is not valid (Brown et al. 2001). 90 �Table 1. Estimated sample sizes required to detect differences in pregnancy rates, in control and treatment groups, based on a Fisher’s exact test power analysis (NCSS Pass 2000). Power Control Group Pregnancy Rate Treatment Group Pregnancy Rate Total Sample Sizea 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.80 1.0 1.0 1.0 1.0 0.9 0.9 0.9 0.9 1.0 1.0 1.0 1.0 0.9 0.9 0.9 0.9 0.0 0.1 0.2 0.3 0.0 0.1 0.2 0.3 0.0 0.1 0.2 0.3 0.0 0.1 0.2 0.3 8 12 14 18 12 14 20 26 8 10 12 16 10 12 16 22 a Total sample size assumes an equal number for each group, e.g. 18 means 9 treatment and 9 control female elk. Experiment 2: Effects of GnRH-KLH vaccine on luteal function and neonatesurvival (objective 2) Hypothesis: We are uncertain of the effects of GnRH-KLH vaccine treatments on LH secretion, luteal viability and fetal/neonatal survival. Little conclusive research has been conducted on these relationships in wild or domestic ungulates. Limited evidence suggests that GnRH-KLH-induced suppression of LH and progesterone levels in late gestation are not low enough to terminate pregnancy or negatively affect fetal/neonatal survival. Rationale: Corpora lutea (CL) secrete progesterone and are an essential ovarian structure for maintenance of pregenancy in all mammals (Baird 1992). Progesterone is obligatory for early embryonic development and peaks in the blood of pregnant females at different stages of gestation for different species. While progesterone is always produced by the CL in early pregnancy, its role in maintenance of pregnancy varies among species. In some species (i.e. mare, cow, ewe, and women) the CL is not needed for the entire gestational period because the feto-placental unit begins producing sufficient progestins to maintain pregnancy (Squires 1993, Stevenson 1997, Stellflug et al. 1997) In other species (i.e. sow, rabbit, whitetailed deer), surgical removal of the CL will terminate pregnancy regardless of when it occurs during gestation (Plotka et al. 1982, Tomas 1997, Tast et. al 2000). It is well-documented that progesterone secretion is regulated by several hormones, including LH, which plays a principal role in CL function during both the estrus cycle and pregnancy (Niswender et al. 1976, 1994, Rahe et al. 1980, Farin et al. 1990, Okuda et al. 1999). In contrast, however, studies in cattle (Peters et al. 1994), pigs (Buhr 1987), dogs (Onclin et al. 2000), and to some extent sheep (McNeilly and Fraser 1987) provide evidence that LH may not be essential for all aspects of luteal function, including 91 �pregnancy. For wild ungulates, LH suppression due to high doses of the GnRH agonist, leuprolide, were not sufficiently luteolytic to terminate pregnancy when administered to elk during the first 60 days of gestation (Baker et al. 2001). Likewise, bison vaccinated with GnRH-KLH during the second and third trimesters of pregnancy, maintained a viable fetus throughout gestation and delivered healthy calves at parturition (Miller et al. 2004). In this experiment, elk will be vaccinated with GnRH-KLH at approximately 120 days gestation and should develop sufficient antibody titers to suppress LH by 180-200 days of gestation (Miller et al. 2000b).Because the average gestation period in elk is 255 days (Haigh and Hudson 1993), the animals in this experiment will be in the third trimester of pregnancy before the CL is significantly affected by lack of LH. If the elk respond similarly to cattle and bison they will likely retain the pregnancy despite expected declines in progesterone. Alternatively, if elk are highly sensitive to small changes in progesterone concentrations they may abort the fetus. Methods: One day prior to GnRH-KLH vaccine treatments in January, 2006, we will collect blood for antibody titers, LH and progesterone concentrations (Niswender et al. 1969, Niswender 1973), and perform reproductive examinations on all experimental elk. Beginning approximately 4 weeks posttreatment, and in conjunction with scheduled monthly measurements of antibody titers, we will monitor changes in these parameters until 15 April, 2006. Following parturition (approximately June 1-15), we will monitor neonatal health, survival, and growth to 30 days post-parturition. Weaned calves, not needed as replacement animals in other experiments or at other captive research facilities, will be humanely euthanized. At present, we have received a proposal from scientist at USDA/APHIS National Wildlife Research Center to use surplus elk calves in a terminal experiment to develop and test orally active vaccines for managing infectious diseases such as bovine tuberculosis and brucellosis. Analysis: We will use descriptive statistical methods to analyze hormonal data. Hormone concentrations, fetal and CL measurements will be reported as arithmetic means ± ŜE . We will estimate the correlation coefficient between antibody titers, hormone concentrations, CL measurements, and test whether these relationships are significantly different from zero (Zar 1984). We will compare the differences in growth rates (g/da) of calves born to treatment and control females from birth to 30 days of age using a two sample t-test. Experiment 3: Effects of GnRH-KLH vaccine on breeding behavior (objective 3) Hypothesis: The effectiveness of GnRH-KLH vaccine as a contraceptive agent is dependent on the suppression of ovulation and steroidogeneis. Because GnRH-KLH vaccine is expected to suppress estradiol and therefore sexual receptivity during estrus, we predict that 1) rates of male precopulatory, female precopulatory, and copulatory behavior will be lower for treated females compared to untreated controls, and 2) that rates of general breeding behavior (i.e. herding, establishing and/or defending a harem) will be similar for both treated and untreated females. Rationale: In previous research (Baker et al. 2002), we reported that breeding behavior rates of female elk treated with GnRH agonist were not different from those of untreated elk. We attributed this response to basal estradiol concentrations inducing reproductive receptivity in animals that had been exposed to progesterone earlier in the breeding season or during a “silent estrus” (Harder and Moorhead 1980, Asher 1985). However, in the present experiment, GnRH-KLH vaccine should suppress progesterone secretion, 92 �estrogen, folliculogenesis and ovulation well in advance of the onset of the September 2006 breeding season. Therefore, there should be no progesterone “priming” effect and no estrous behavior in treated females. Limited observations of male elk engaged in general breeding behaviors related to establishing and/or defending a harem suggest that they don’t discriminate between cycling and non-cycling females (Baker et al. 2002). If true, general breeding behavior rates of females treated with GnRH-KLH vaccine in the present experiment should not be different from untreated females. Methods: We will test these hypotheses by examining the effects of GnRH-KLH vaccine on reproductive behaviors of female elk during the breeding season (15 September to 31 October 2006). Our experimental unit for analysis will be individual females within each treatment group. On 15 August 2006, two male elk will be placed with treated and control female elk in the same paddocks. All females will be individually identified with color numeric-coded neck collars. Observers will not know which elk are treatments or controls. Behavior observations will be made from a distance of 50-250 m from an elevated tower using binoculars and spotting scope during day, and a spotlight and night vision scope at night. Selected behaviors (Geist 1982) will be recorded using a lap-top computer with a behavioral software program. All-animal all occurrences sampling procedures will be used to sample reproductive behaviors of all experimental animals over a 24 h period (Leaner 1996). Time-of-day sampling periods will be assigned each week using a randomized block design. Each sampling period will consist of at least 2 h of continuous observations. We will group individual sexual behaviors into four general categories (Table 2).Because behavioral interactions are generally short duration (< 30 sec) relative to the sampling interval, we will record the number of occurrences of each behavior rather than the length of time, and calculate rates of sexual interactions as behaviors per animal per hour, then multiply hourly behavior rates by 24 for a daily rate. Table 2. Elk reproductive behavior and associated behavior categories (Baker et al. 2002). Behavior Category General Breeding Male Precopulatory Female Precopulatory Copulatory Reproductive Behavior Male directed behavior related to establishing, maintaining and defending a group or harem of female elk (i.e. Herding, guarding, tending) Male courtship behavior directed toward an individual female to induce or detect estrus or ovulation (i.e. urine testing, flehmen, tongue flick, smell or rub) Female courtship behavior directed toward dominant male to arouse copulatory behavior (i.e. lick and rub male, mount, lordosis, twitch hocks) Male behavior directed toward a receptive female in estrus (i.e. intromission) Analysis: Based on the sample sizes required to detect differences in pregnancy rates (Table 1), we conducted a simulation to estimate the power to detect differences in behavior rates. To complete this simulation, we bootstrapped data from a previous study which examined the effects of an alternate fertility control agent, leuprolide, on female elk reproductive behavior during the breeding season (Baker et al. 2002). Each sample was run through Proc Mixed (SAS 1996) using repeated measures mixed effects structure. The following parameters were used to estimate power based on total experimental sample sizes of 18, 20, or 26 female elk (Table 3). 1. Male pre-copulatory behavior rate was previously shown to be higher than other reproductive behavior rates (Baker et al. 2002). Consequently, this measurement will likely be the most sensitive to detection of treatment effects. Therefore, we used the previously reported male precopulatory behavior rates to estimate power for our simulation. 2. The peak of breeding season is approximately one month in length. Therefore, we estimated power using 60 total observation periods. [4wks x 3 observation periods/da x 5 da/wk = 60 obs. periods] 93 �3. We estimated power for 3 different sample sizes using 60 observation periods and bootstrapping data from the previous leuprolide experiment. Ten control elk were randomly selected (with replacement) from the 5 control female elk of the previous leuprolide experiment (thus some elk were used multiple times in a sample). The behavioral response (male precopulatory behavior rate) for each elk was recorded; thus a complete sample consisted of 10 behavior rates for each of the 60 observation periods. Behavior data from control elk was considered the benchmark for comparison. Hence, to estimate power for treatment elk in the current experiment, we followed the same procedure except that the response was multiplied by the effect size. To represent a 50% decrease in the male precopulatory rate directed toward treatment elk, we multiplied the control response by 0.5. 4. Although our behavioral hypothesis predicts that treated female elk will have reduced reproductive behaviors compared to controls, we also estimated sample size for the possibility of increased behavior rates. Thus, we estimated sample sizes for a 75% and 50% reduction in male precopulatory behavior rates toward treated female elk compared to controls, as well as a 50% increase in male precopulatory behavior rates. 5. Power results are based on the number of times an effect was detected during 100 simulations. Because the variance is larger for higher behavior rates, there is less power to detect a 50% increase compared to a 50% decrease. From this analysis we conclude that a sample size of 20; 10 treatment and 10 control animals, and 60 observation periods would provide adequate power (>90%) to detect most of the differences in reduced reproductive behavior rates as well as reasonable power (>75%) to detect a 50% increase in behavior rates between treated and untreated elk. Table 3. Power results for detecting differences in male precopulatory behavior rates directed toward treated and untreated female elk based on 100 simulations and 60 observation periods. Difference Between Treatment and Controlsa 0.25 0.25 0.25 0.50 0.50 0.50 1.50 1.50 1.50 Total Sample Sizeb 18 20 26 18 20 26 18 20 26 a Power α=0.05 1.00 1.00 1.00 0.99 1.00 1.00 0.70 0.76 0.92 Power α=0.10 1.00 1.00 1.00 0.99 1.00 1.00 0.81 0.84 0.95 Effect size Total sample size assumes an equal number for each group, e.g. 18 means 9 treatment and 9 control female elk. b 94 �Experiment 4: Effects of GnRH-KLH vaccine on maternal behavior, neonatal survival and growth, blood chemistry and hematology (objective 4) Hypothesis: GnRH-KLH vaccine treatments will not result in significant secondary negative behavioral or physiological side-effects in female elk. Rationale: To date, the GnRH-KLH vaccine formulated with AdjuVacTM has produced few reported behavioral or physiological side-effects in any species in which it has been tested (Levy et al. 2004, Miller et al. 2004, Killian et al. 2004). However, it’s not clear from these studies how extensively the side-effects of this agent have been evaluated. In this investigation, we will evaluate the effects of GnRHKLH vaccine on maternal/neonatal behavior, neonatal growth and development, serum biochemistry, and injection site reactions. Methods: Injection site reactions. On the day prior to treatment application (early January 2006) and while elk are lightly sedated (see pages 6-7 for details), we will perform ultrasound examination of the area of the expected injection site. After dart delivery of the vaccine, we will grossly monitor the injection site on a daily basis for one month for signs of inflammation or drainage. In addition, we will use ultrasound imaging each month for 6 months in conjunction with scheduled animal handling and blood collections to monitor changes in muscle echogenicity that would indicate sub-clinical abscesses or granuloma formation. Blood Chemistry and hematology. The physiological side-effects of GnRH-KLH treatment will be assessed by comparing serum chemistry, hematology, and body weight dynamics of treated and control elk. Blood samples will be collected in conjunction with previously described measurements just prior to GnRH-KLH vaccination and one week post-vaccination for evidence of short-term inflammation or infection. At three months post-vaccination, additional blood will be collected and analyzed for biochemistry profiles and evidence of abnormal organ function. These samples will be submitted for analysis to Colorado State University, Veterinary Teaching Hospital, Clinical Pathology Laboratory, Fort Collins, Colorado for analysis. Maternal Bonding, neonatal survival and growth. We will compare maternal/neonatal bonding and neonatal survival and growth of treated and control female elk for 30 days post-parturition during approximately 1 June to 1 July 2006. Parturition behavior of elk will be monitored daily beginning in late May and early June. We will document evidence of dystocia for each adult female, calf birth weight and health, acceptance or rejection by the dam, and growth to 30 days of age. For the purpose of this experiment, we assume that calf survival after 30 days is no longer a function of GnRH-KLH vaccine treatment and multiple factors other than maternal bonding will influence neonatal survival and body weight dynamics. Analysis: Means and standard errors of blood parameters, and neonatal growth rates will be estimated using least–squares ANOVA. Hypothesis tests will be based on type III generalized equations that account for correlations in repeated measures. 95 �Project Schedule: Date 1 May – June 2005 1 Sept 2005 7 Sept 2005 1 Jan 2006 1 Jan 2006 1 Feb – Sept. 2006 1 Feb – June 2006 1 June – July 2006 15 Sept. 2006 – 31 Oct. 2006 Jan 2007 Jan 2008 Jan 2009 Mar – July 2009 Activity Submit study plan for CDOW peer review and ACUC approval Semen evaluation and CIDR’s in all experimental female elk. Remove CIDR and combine males and females. Determine pregnancy status of females and assign to experimental groups. Apply contraceptive and monitor short term health effects. Monitor antibody titers of experimental elk. Monitor hormone levels Monitor birth rates, calf survival, calf weights and cow/calf behavior. Evaluate reproductive behavior Evaluate pregnancy rates 1 year post- vaccination. If funding is available, evaluate pregnancy rates 2 year post-vaccination If funding is available, evaluate pregnancy rates 3 year post-vaccination and/or reversibility of contraceptive treatments. Analyze data and prepare final report. Budget: This research proposal has been submitted to the Morris Animal Foundation for possible funding during the period June 2006 to Jan 2008. Category 2005-‘06 2006-‘07 Total Personal Services 0 0 0 1. Co-Investigator(s) 2. Biometrician 3. Wildlife Technicians (TBA) 5,000 6,675 2,500 11,175 7,500 17,850 Total Salaries and Wages 11,675 13,675 25,350 3,600 3,600 500 2,160 1,600 1,000 1,200 1,200 500 2,160 0 1,000 4,800 4,800 1,000 4,320 1,600 2,000 12,460 6,060 18,520 Operating Supplies & Services 1.Hormone serology LH analysis (240 x $20) Progesterone (240 x $20) PSPB (40 x $25) 2. GnRH Antibody Assays (360 x $12) 3. Biochemistry profile and CBC’s (40 x $40) 4. 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Endocrinology 84:1166-1173. 100 �___________, T. J., REIMERS, M. A. DIEKMAN, AND T. M. NETT. 1976. Blood flow: a mediator of ovarian function. Biology of Reproduction 14: 64-81. OKUDA, K., Y. UENOYAMA, C. NAITO, Y. SAKABE, AND N. KAWATE. 1999. Luteinizing hormone receptors in the bovine corpus luteum during the oestrous cycle and pregnancy. Reproduction, Fertility, and Development 11:147-151. ONCLIN, K., J. P. VERSTEGEN, AND P. W. CONCANNON. 2000. Time-related changes in canine luteal regulation: in vivo effects of LH on progesterone and prolactin during pregnancy. Journal of Reproduction and Fertility 118:417-424. PETERS, K. E., E. G. BERGFELD, A. S. CUPP.1994. Luteinizing hormone has a role in development of fully functional corpora lutea (CL) but is not required to maintain CL function in heifers. Biology of Reproduction 52 (Suppl) 1:35. PLOTKA, E. D., U. S. SEAL, L. J. VREME, AND J. J. OZOGA. 1982. Reproductive steroids in white tailed deer. IV. 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Pattern of plasma luteinizing hormone in the cyclic cow: dependence upon the period of the cycle. Endocrinology 107:498-503. RHYAN, J. C., AND M. D. DREW. 2002. Contraception: A possible means of decreasing transmission of brucellosis in bison. In: Brucellosis in elk and bison in the Greater Yellowstone Area, T.J. Kreeger (ed.). Greater Yellowstone Interagency Brucellosis Committee, Wyoming Game and Fish Department, Cheyenne, Wyoming, 99-108. ROPSTAD, E., AND D. LENVIK. 1991. The use of cloprostenol and prostaglandin F2α to induce luteolysis in reindeer calves (Ranger tarandus). Rangifer 11:13-16. RUDOLPH, B. A., W. F. PORTER, AND H. B. UNDERWOOD. 2000. Evaluating immunocontraception for managing suburban white-tailed deer in Irondequoit, New York. Journal of Wildlife Management 64:463-473. SAS INSTITUTE. 1997. SAS/STAT® users guide 6.03 edition. SAS Institute, Inc., Cary, North Carolina, USA SEAGLE, S. W., AND J. D. CLOSE.1996. Modeling white-tailed deer population control by contraception. Biological Conservation 76:87-91. SHIDELER, S. E., M. A. STOOPS, N. A. GEE, J. A. HOWELL, AND B. L. LASLEY. 2002. Use of porcine zona pellucida (PZP) vaccine as a contraceptive agent in free-ranging tule elk (Cervus elaphus nannodes). Reproduction Supplement 60:169-176. STELLFLUG, J. N. Y. S. WEEMS, AND W. W. WEEMS. 1997. Clinical reproductive physiology of ewes. In: Current Therapy in Large Animal Theriogenology. R.S Youngquist (ed.) W.B. Saunders Co. pp594-598 STEVENSON, J. S. 1997. Clinical reproductive physiology of the cow. In: Current Therapy in Large Animal Theriogenlogy. R.S Youngquist (ed.) W.B. Saunders Co. pp257-267 STILLS, H. F., JR., AND M. Q BAILEY. 1991. The use of Freund’s complete adjuvant. Laboratory Animals 20:25-30. SQUIRES, E. L.1993. Endocrinology of pregnancy. In: Equine Reproduction A. O. McKinnon and J. L. Voss (Eds). Williams and Wilkins, Pennsylvania, USA. pp495-508 TAST, A., R. J. LOVE, I. J. CLARKE, AND G. EVANS. 2000. Effects of active and passive gonadotrophin101 �releasing hormone immunization on recognition and establishment of pregnancy in pigs. Reproduction, Fertility and Development 12:277-282. TOMAS, P. G. A. 1997. Induced abortion. In: Current therapy in large animal theriogenology, R. S. Youngquist (ed.).W.B. Saunders Co. 303-306 TURKSTRA, J. A., F. J. U. M. VAN DER MEER, J. KNAAP, P. J. M. ROTTIER, K. J. TEERDS, B. COLENBRANDER, AND R. H. MELOEN. 2005. Effects to GnRH immunization in sexually mature pony stallions. Animal Reproduction Science 86:247-259. TURNER, J. W., JR., I. K. M. LIU, AND J. F. KIRKPATRICK. 1992. Remotely delivered immunocontraception in captive white-tailed deer. Journal of Wildlife Management 56:154-157. __________, J. F. KIRKPATRICK, AND I. K. M. LIU. 1996. Effectiveness, reversibility and serum antibody titers associated with immunocontraception in captive white-tailed deer. Journal of Wildlife Management 60:45-51. __________, AND _________. 2002. Effects of immunocontraception on population longevity and body condition in wild mares (Equus caballus). Reproduction Supplement 60:187-195. WALTER, W. D., P. J. PERKINS, A. T. RUTBERG, AND H. J. KILPATRICK. 2002. Evaluation of immunocontraception in a free-ranging suburban white-tailed deer herd. Wildlife Society Bulletin 30:186-192. WRIGHT, R. G. 1993. Wildlife management in parks and suburbs: alternatives to sport hunting. Renewable Resources Journal 11: 18-22. ZAR J. H. 1984. Biostatistical analysis. Prentice-Hall, Inc. Englewood Cliffs, New Jersey, USA. 102 �APPENDIX II BAKER, D. L., M. A. WILD, M. M. CONNER, H. B. RAVIVARAPU, R. L. DUNN, AND T. M. NETT. 2005. Evaluation of a remotely delivered formulation of leuprolide acetate as a contraceptive agent in female elk (Cervus elaphus nelsoni). Journal of Wildlife Diseases 41: in press. Abstract: Practical application of fertility control technology in free-ranging wild ungulates often requires remote delivery of the contraceptive agent. The objective of this investigation was to evaluate the potential of remote delivery of leuprolide acetate for suppressing fertility in female elk (Cervus elaphus nelsoni). Fifteen captive adult female elk were randomly allocated to one of three experimental groups. Six elk were injected intramuscularly with a dart containing leuprolide, and the remaining nine elk received the same formulation without leuprolide. We determined pregnancy rates, suppression of luteinizing hormone (LH) and progesterone concentrations, and reversibility of treatments during 1 August 2002 to 3 September 2003. Leuprolide formulation caused a decrease in concentrations of LH and progesterone, temporary suppression of ovulation and steroidogenesis, and effective contraception (100%) for one breeding season. These results extend the practical application of this contraceptive agent to include dart delivery, where in the absence of such technology, wild elk must first be captured and restrained prior to treatment. BAKER, D. L., M. A. WILD, M. M. CONNER, M. D. HUSSAIN, R. L. DUNN, AND T. M. NETT. 2006. Evaluation of leuprolide as a contraceptive agent in free-ranging elk in Rocky Mountain National Park, Colorado. Journal of Wildlife Management (in preparation). ___________., _________, M. D. HUSSAIN, R.L. DUNN, AND T. M. NETT. 2006. Leuprolide acetate as a contraceptive agent in female elk: determination of minimum effective dose. Reproduction (in preparation) LUKACS, P., J. GROSS, AND D. BAKER. 2006. Estimating confidence intervals for fawn:doe and buck:doe ratios from counts across days. Journal of Wildlife Management (in preparation). INSLERMAN, R. A., J. E. MILLER, D. L. BAKER, J. E. KENNAMER, R. CUMBERLAND, B. STINSON, P. DOERR, AND S. J. WILLIAMSON. 2005. The Wildlife Society Technical Review Committee on Baiting and Artificial Feeding of Game Wildlife Species (in preparation). 103 �104 �Colorado Division of Wildlife June 2004 – July 2005 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3003 1 : : : : Federal Aid Project: N/A : Division of Wildlife Mammals Research Predatory Mammals Conservation Puma Population Structure And Vital Rates On The Uncompahgre Plateau, Colorado Period covered: July 1, 2004―June 30, 2005 Author: K. A. Logan. Personnel: S. Waters, T. Murphy, K. Crane, T. Mathieson, M. Caddy, and T. Smith of CDOW, J. Bauer of Colorado Cooperative Fishery and Wildlife Research Unit, J. Kane of U.S.D.A. Wildlife Services, volunteers, cooperators including: private landowners, U.S. Forest Service, Bureau of Land Management, and Colorado State Parks, with project support received from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT To begin conducting research on puma population characteristics and dynamics on the Uncompahgre Plateau, public meetings were held, puma hunting regulations were altered for an experimental design, and a study plan was developed and approved along with animal care and handling procedures. Field research began on December 2, 2004. From December 2, 2004 to July 22, 2005 fifteen puma were captured, sampled, tagged and released, including 7 adult pumas (3 males, 4 females) and 8 cubs (3 males, 5 females). Three other pumas were captured with the aid of dogs, but were released without sampling or tagging for safety reasons. One adult female puma was hit and killed by a car on highway 62 at the southern boundary of the study area. The 7 adult pumas wore GPS collars that yielded 355 to 779 locations per puma. GPS locations indicated 139 clusters that were investigated. Prey use was found at 112 clusters, with mule deer (n = 61) and elk (n = 48) comprising the most important items. Tissue samples collected from all puma handled will be used for proposed research on laboratory and field methods to estimate puma numbers using DNA mark-recapture methods. Puma GPS locations will also be used in proposed efforts to develop and test puma habitat suitability models and maps. Information on evaluations of the GPS collar technology and findings at GPS clusters will be used to develop proposed research on puma-prey relationships on the Uncompahgre Plateau. 105 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates― all to improve the Colorado Division of Wildlife’s (CDOW) model-based approach to managing puma in Colorado. SEGMENT OBJECTIVES 1. Hold public meetings and contact individuals to inform citizens in the area of Uncompahgre Plateau about the CDOW desires to conduct the puma research. 2. Obtain needed regulations from the Wildlife Commission for experimental research on the study area. 3. Develop a peer-reviewed study plan that is authorized by the Leader of Mammals Research in the CDOW. Develop proper procedures for the capture, restraint, handling, and sampling of puma for research which are authorized by the CDOW Animal Care and Use Committee. 4. Begin quantifying puma population sex and age structure. 5. Begin process of estimating female puma reproduction rates. 6. Begin process of estimating puma sex and age-stage survival rates. 7. Begin process of estimating agent-specific mortality rates. 8. Begin gathering quantitative data on puma movements for the development of sampling methods for direct and DNA-genotype mark-recapture population estimates. Begin gathering puma tissue samples for individual puma genotyping procedures. 9. Evaluate other data sources that could come from this research that might be developed into other puma research relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing puma while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma-prey interactions. Staff on the Front Range placed greater emphasis on puma-human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified 106 �by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field experiments. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared puma. Those objectives include: 1. Describe and quantify puma population sex and age structure. 2. Estimate puma population vital rates, including: birth rates, age-stage-specific survival rates, emigration rates, immigration rates. 3. Estimate agent-specific mortality rates. 4. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of population abundance (i.e., numbers and density) and attendant annual population growth rates, such as, direct capture-resight, and DNA genotype capture-recapture. 107 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Recreational puma hunting management in Colorado Game Management Units (GMUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are deemed to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,λ = 1.15) for the adult and subadult puma population (J. Apker, Carnivore Management Specialist, CDOW, Monte Vista). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). The key assumption is that the CDOW can manage puma population growth through recreational hunting: for a stable puma population hunting removes the annual increment of population growth (i.e., as estimated from estimates of population density, structure, and λ); for a declining population, hunting removes more than the annual increment of population growth. Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, age-specific natality, sexand age-specific survival, immigration and emigration. A descriptive study will ascertain these population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. The treatment period will involve the use of controlled recreational hunting to manage the puma population into a decline phase. H1a: Population parameters measured during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15, which is currently assumed in the CDOW’s model-based management. H1aA: Population parameters measured during a 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will be substantially lower (i.e., ≥50% lower, λ≤1.075) than the assumed λ = 1.15. H1b: Population parameters during a 5-year treatment period (controlled puma hunting) will differ substantially from those measured during the preceding 5-year reference period (hunting closure) and will yield an estimated annual adult plus subadult population growth rate that will be approximately λ=0.8 for at least the first 2 years of the treatment period. Hunting-caused mortality will be strongly additive, and will require removal of the annual growth increment (of adults plus subadults) plus 20% (e.g., assume λ = 1.15, so, 0.15 × 0.2 + 0.15 = 0.18; 0.18 × 100 = 18% annual harvest of adults plus subadults). H1bA: Population parameters during a 5-year treatment period (controlled puma hunting) will not differ substantially from those measured during the preceding 5-year reference period (hunting closure), and the adult plus subadult population will not decline on average as a result of hunting mortality. Hunting-caused mortality, reproduction, immigration, and emigration might be compensatory. 108 �2. Considering limitations (i.e., methods, number of years, assumption violations) to the Coloradospecific studies on puma densities cited above (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973, Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0―4.6 puma/100 km2 to extrapolate to Data Analysis Units to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using capture, mark, re-capture techniques developed and refined during the study to estimate the puma population, the following will be tested: H2a: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 3. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H2b: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent puma will cause an older age structure in harvest-age puma (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. H2c: As hunting is re-instated in the treatment period, the age structure of harvested puma and the harvest-age puma in the population will vary as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters useful for estimating puma population abundance, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help those managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for estimating puma abundance (capture-mark-recapture) of known reliability will allow managers to “ground truth” modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will require development of reliable monitoring techniques based on capture-mark-recapture methods and models. Potential methods include direct and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and when we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. 109 �STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties, Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinon-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing summer residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Experimental Treatment Periods This research is structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period is expected to cause a population increase phase. The treatment period will be managed to cause a population decline phase. In both phases, puma population structure, and vital rates will be quantified, and some management assumptions and hypotheses regarding population dynamics will be tested. Contingent upon results of pilot studies, we will also estimate puma numbers, population growth rates, evaluate enumeration methods, and test other hypotheses (Logan 2004). The reference period, without recreational puma hunting as a major limiting factor, is consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000―12,000 years (Culver et al. 2000) that enable puma to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma evolution in western North America for the past 100 years. Hence, the reference period, years 1―5, will provide conditions where individual puma in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factors will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before the treatment (i.e., controlled recreational hunting). In the reference period, all puma in the study area will be protected, except for individual puma that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged puma that range in a buffer zone, that includes the northern halves of GMUs 61 and 62, will be protected from recreational hunting. The reference period will allow researchers to quantify baseline demographic data on the puma population to estimate parameters for the CDOW’s model-based approach to puma management. Moreover, it will allow researchers to develop and test puma enumeration methods when population growth is known to be in one direction― increasing. Without the hunting closure, pilot data for enumeration methods could be confounded by not knowing if the population was increasing, declining, or stable. The reference period will also facilitate other operational needs (because hunters will not be killing the animals) including the marking of a large proportion of the puma population for capture-mark110 �recapture estimates, and the gathering of movement data from GPS-collared puma to help formalize exact sampling designs for enumeration methods. During the treatment period, years 6―10, experimentally structured recreational puma hunting will occur on the same study area with the intent of causing a decline phase in the puma population by using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or population suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, puma survival will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared puma. The portion of adults and subadults in the population will be reduced by approximately 20% in year 6 and 20% more in year 7. The 20% change was identified by Division managers that requested enumeration tools that might detect 20% changes in puma populations. For managers, detecting the magnitude of puma population decline phases is probably more important that detecting the magnitude of population increase phases. This will also allow quantification of puma population characteristics and vital rates and initial tests of enumeration methods during a decline phase. Additional reductions may be made to test enumeration methods and other hypotheses that may be related to effects of hunting (i.e.,: relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting) and puma-prey interactions (i.e., lines of research identified in the Colorado Research Program, Fig. 1). Those decisions can be made later in project development and as late as years 8―10. The killing of tagged and collared puma during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a large majority of independent puma in the population will be marked, and sampling schemes will be formalized. Puma on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW of Wildlife if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that puma live at low densities and capturing puma is difficult, as a starting point, our logistical aim will be to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim is to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of puma might represent the large majority of the puma population on the study area, and will provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration rates, and movement data pertinent to sampling designs for various projects. Assuming that the puma population density on the study area is relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio is equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might be 22 adults, 11 males and 11 females. Also assuming that the total population contains 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might be 4 subadults and 13 cubs with equal sex ratios in a total population of 39 puma. If we achieve our logistical aim in the first 1―2 years (recognizing that the population might grow), then we should be able to quantify population characteristics and vital rates for a majority of the puma population in those years and build upon the tagged number in each subsequent year. Thus, our inferences will pertain to the large 111 �majority of the puma population, if not the population on the study area, instead of a relatively small sample of it. We anticipate it may take 2 years to mark the large majority of puma in the population. In addition, the study area is large and will require some time to learn to access it efficiently. Puma capture and handling procedures have been approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured puma will be examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses; disease screening; hair (from various body regions) and fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Puma will be captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, walking, and possibly horse- or mule-back. When puma tracks ≤1 day old are detected, trained dogs will be released to pursue puma to capture. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent will be delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2005). Efficiency of the trap might be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Manchester, NH). A cage trap will be set only if a target puma scavenges on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers will continuously monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized puma will be restrained and monitored as described above. If non-target animals are caught in the cage trap, we will open the door and allow the animal to leave the trap. Foot-hold snares will be used to capture adults, subadults, and large cubs only when safe snare sites at puma kills can be located as described by Logan et al. (1999). Snares set at puma kills will be monitored continuously with VHF beacons on the snares from about 1 km distance. We will not set snares at sites where tracks indicate that other mammals (e.g., deer, elk, bear, bighorn sheep, livestock) are also active. Puma will be immobilized with Telazol injected into the caudal thigh with a pole syringe. 112 �Vital signs will be monitored during the handling procedures. Efficiency of snares might also be enhanced with the use of an automated call box with puma or prey vocalizations. Small cubs (≤10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System, and Radio-telemetry: Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual puma is essential to a number of project objectives, including estimating vital rates and gathering movement data on puma to formalize designs for developing and testing enumeration methods. Adult, subadult, and cub puma will be marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna is permanent and cannot be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) will be inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old will be eartagged in only one pinna. Locations of GPS- and VHF-collared puma will be fixed about once per week from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using ArcGIS software. Adult and subadult female puma will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada). Initially, GPS-collars will be programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for puma will provide precise, quantitative data on puma movements mainly to provide data to formalize study designs, to test assumptions for capture-mark-recapture methods for this project, and to assess the relevance of puma DAU boundaries. The GPS-collars also will provide basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and predation frequency on mule deer and elk. Subadult male puma will be fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male puma reach adulthood on the study area, we will recapture them and fit them with GPS collars. VHF radio transmitters on GPS collars will enable researchers to find those puma on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters on GPS- and VHF-collars will have a mortality mode 113 �set to alert researchers when puma have been immobile for at least 3 hours so that dead puma can be found to quantify survival rates and agent-specific mortality rates by gender and age. We will attempt to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar (~100g, MOD 210, Telonics, Inc., Mesa, Arizona) when cubs weigh 2.3―11 kg (5―25 lb). Cubs with mass ≥11 kg can still wear these small expandable collars until they are about 12 months old. Cubs approaching the age of independence (~11―14 mo. old) may be fit with Lotek LMRT-3 VHF collars (~400 g) with expansion links. Cubs will be recaptured to replace collars as necessary. Monitoring radioed cubs allow quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Capture-Mark-Recapture: Capture-mark-recapture methods will be evaluated initially as a pilot study. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during capture-recapture occasions needed for population estimation. Therefore, we will capture and mark puma prior to performing capture-recapture occasions using houndsmen teams. In addition, by marking puma before capture-recapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked on the study area. After cubs are weaned, the mothers’ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Capture-recapture occasions to estimate the population of independent puma may not begin until the end of the second winter or the third winter when we have a large majority of the puma population sampled and marked. Occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, performance of field methods (e.g., detection differences by sex or life stage as revealed by GPS data on collared puma), and precision of capture-recapture models used to estimate the puma population. Analytical Methods Population Characteristics: Population characteristics each year will be tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allow, age categories may be further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates will be estimated for GPS- and VHF-collared female puma directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male puma (Murphy et al. 1998). Methods will be tested in Dr. M. Douglas’s Laboratory (Colorado State University, Department of Fishery and Wildlife Biology). Survival and Agent-specific Mortality Rates: Radio-collared puma will provide known fate data which can be used to analyze survival rates in program MARK (White and Burnham 1999, Cooch and White 2004). Agent-specific mortality rates will be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will be plotted with survival rate on age in months (Logan and Sweanor 2001:119). Population Estimates: Capture-recapture models will be evaluated initially as a pilot study to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of adult and subadult puma present in the survey area) and puma density (i.e., number of independent puma/100 km2) each winter― December through March― when snow facilitates detection and capture of 114 �puma, provided that we meet model assumptions. The December―March period also corresponds with Colorado’s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma that can be legally killed by recreational hunters. Furthermore, adults comprise the breeding segment of the population and subadults are non-breeders that are potential recruits into the adult population in ≤1 year. Thus, the sampling unit is the individual independent puma (~≥1 yr. old). General assumptions for closed capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). The robust design is a combination of closed and open models; thus, assumptions are a combination of the assumptions for closed and open population methods (Kendall 2001). To analyze capture-recapture data, closed, open, and the robust design models are available in program MARK. Akaike’s Information Criterion will be used to select the most parsimonious models based on AICc score ranks and the difference in AIC (∆AIC) between models (Burnham and Anderson 1998). MARK results also include estimates of abundance. Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of at least 0.5 for each animal per capture occasion. Capture simulations using MARK software (Cooch and White 2004) indicate that greater capture probabilities and more capture occasions yield more precise estimates. The capture probability for the simplest closed model [M(o)], which assumes that every member of the population has the same probability of capture (p) for each sampling period, suggest that for a population of 30 animals (i.e., adults plus subadult puma, which might be present by the end of year 2, see Puma Capture above) p must equal 0.5 for 3 capture occasions to attain a coefficient of variation (V) of 0.1. If 6 capture occasions are used, then a p of 0.3 might yield a V of 0.09. In addition, behavior, movements, survival and mortality of GPS- and VHF-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we might expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models and the robust design would be more appropriate (Pollock et al. 1990, Williams et al. 2001). Collared puma will allow us to determine the number of marked puma present in the search area each capture-recapture occasion. Furthermore, GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information, too. ArcView geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frames. Rate of Population Increase: Finite rates of increase (λ=Nt+1/Nt) between consecutive years and average annual rates of increase (r) for 3- to 5-year periods and levels of precision will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. 115 �Functional Relationships: Graphical methods will be used to examine functional relationships between puma density and vital rates, relationships between puma density estimated with direct capturerecapture methods (i.e., houndsmen teams) and possibly later (depending upon funding) by using estimates from DNA genotype mark- recapture methods. Linear regression procedures and coefficients of determination can be used to assess these functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, can also be used to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Statistical analyses will be performed using SYSTAT and SAS software. The risk of committing a type I error (i.e., rejecting a null hypothesis that is actually true) will be controlled at alpha = 0.10 because we will normally have small population sizes (typical of studies of large obligate carnivores). The higher alpha level will increase the probability of detecting a change and reduce the risk of a type II error (i.e., failing to reject a null hypothesis that is false). For managers, the risk of a type II error is probably more important. RESULTS AND DISCUSSION Segment Objective 1 The Division of Wildlife held public meetings in Redvale (August 23, 2004) and Montrose (August 30, 2004) where DOW staff informed attendees from the Uncompahgre Plateau area about the puma research project and addressed their questions. Meetings were held with over 70 private landowners, ranchers, hunters, outfitters, and guides that live and operate on the Uncompahgre Plateau to inform them about the puma research, address questions, and request permission to access private lands for puma research activities. Additional meetings were with representatives of the U.S. Forest Service, Bureau of Land Management, National Park Service, and Colorado State Parks who were also informed about the puma research. Segment Objective 2 The Wildlife Commission passed regulations allowing for the experimental design of this puma research. Their decision resulted in a closure to puma sport-hunting for the first 5-years of the research (Nov. 11, 2004 to Mar. 31, 2009) on the study area. In addition, the Commission allowed the creation of a buffer zone during the same time period comprised of the remaining parts of Game Management Units 61 and 62 north of the 25 Mesa Road (i.e., north of the study area) where pumas tagged on the study area can not be legally taken by puma sport-hunters. The buffer zone is intended to protect puma that are originally captured and sampled in the study area and that range to the north so that pumas in the study population will express life history traits not affected by sport-hunting off-take. A larger buffer zone to protect pumas tagged on the study area was requested of the CDOW Regulations Review Committee. That buffer zone would have protected all puma tagged in the study area even if they ranged off the study area but were west of the continental divide in Colorado. However, that request was denied by the Regulations Review Committee. Segment Objective 3 A study plan was developed, peer-reviewed, modified with the peers’ recommendations (Logan 2004), and then initiated to begin the long-term, experimental research on puma population dynamics on the Uncompahgre Plateau. Procedures for the capture, restraint, handling, and sampling of pumas for this research were reviewed and approved (file #08-2004) by the Colorado Division of Wildlife Animal Care and Use Committee. 116 �Segment Objectives 4―7 Field research to begin quantifying puma population structure, vital rates, and causes of mortality began on Dec. 2, 2004. From December 2, 2004 to May 12, 2005, trained dogs were used as our main method to capture, sample, and mark pumas. Our search efforts on the east slope of the study area were from 25 Mesa Road south to Fisher Creek. On the west slope, our efforts were from the 25 Mesa Road south to Goodenough Gulch. Those efforts resulted in 78 search days, 109 puma tracks, 35 pursuits, and the capture of 14 pumas (Table 1). Eight of those pumas were restrained, sampled, tagged, and released (Table 2). Puma M1 was unintentionally recaptured when we thought we were pursuing an unmarked puma. Puma F3 was recaptured during our effort to capture her male offspring M5 for the first time. Pumas were bayed in trees by dogs on 4 other occasions, but we did not attempt to anesthetize the puma because of concern for the pumas safety on 3 occasions, and concern for the puma’s and the researchers’ safety on one occasion (Table 3). In those cases, a puma was treed in cliffs at night, and on 3 occasions the pumas were bayed in trees too dangerous for researchers to attempt to safely dart the pumas and then climb the trees to retrieve the cats. These pumas included 1 large adult female that was probably caught twice, 1 adult male, and 1 puma that was either a large cub or a subadult (sex undetermined). A summary of capture efforts with dogs is in Table 4. We attempted to capture a female puma on Ridgeway State Park on April 1, 2005. The puma killed an adult mule deer doe, and had begun to eat the deer on the sidewalk beside the Fishing Pond at Pa-Co-Chu-Puk Campground. This location was about 520 m east of where our trained dogs treed, but we could not handle a large female puma on February 1, 2005. We used a cage trap designed for black bears to attempt to capture the puma, but the bear trap was not sufficient. The puma entered the trap, but apparently the cage door did not latch because the puma’s tail was caught in the door jam. The puma did not return to cage trap. We did not pursue the puma with dogs because of the close proximity of highway 550 and private lands directly north and east of the park. We captured 8 cubs from 4 litters born to GPS-collared female pumas. Two litters were born in May, 1 litter was born in June, and 1 litter was born in August. There were 3 males and 5 females (Table 5). One puma death was detected on July 28, 2005. A female, about 49 months old, was hit and killed by a car between 06:00―08:00 on state highway 62 about 10.4 km west of Ridgeway in lower Cottonwood Creek. This location was on the southern boundary of the study area. A necropsy showed that the puma appeared to be in excellent physical condition prior to its death. Her mass was 46 kg; she apparently was not pregnant; and her mammary glands were not producing milk. Segment Objectives 8―9 Seven adult pumas were fit with Lotek 4400S GPS collars programmed to fix 4 locations per day (00:00, 06:00, 12:00, and 19:00). The number of GPS locations per individual puma ranged from 355 to 779 (Table 6). Because none of the puma have yet been monitored for a complete year and the sample is small, annual and seasonal home ranges sizes were not estimated for this report. However, we estimated the activity areas used by the 7 GPS-collared adult pumas (Table 6) during the monitoring periods and overlaid 100% Minimum Convex Polygons on a map of the study area (Fig. 2). In addition, we are collaborating with colleagues at Colorado State University― Dr. K. Crooks, Dr. D. Theobald, and Dr. K. Wilson― to develop a proposal and funding that would allow us to develop and validate puma habitat suitability models and maps for Colorado in which these puma GPS location data will be used. Tissue samples from all of the captured pumas and the unmarked female puma hit and killed by a car have been archived with geneticist Dr. M. Douglas. We are currently collaborating with Dr. Douglas to develop a study plan and funding for the development and assessment of laboratory and field methods 117 �for genotyping pumas and for estimating puma abundance in the wild using DNA mark-recapture techniques. We conducted a preliminary assessment of the usefulness of GPS-collar technology for investigations of puma-prey relationships. The average GPS location fix rate for the 7 GPS-collared pumas was 70.7% (range = 54―87%) (Table 6). We investigated 139 GPS location clusters for 7 adult pumas where individual GPS-collared pumas spent ≥1 day during the span December 26, 2004 to July 31, 2005. The estimated error between 101 collar-fixed GPS locations and prey remains found on the ground averaged 3.2 m (range = 0―50 m, SE = 0.6). Prey remains were found at 112 of the 139 clusters, with mule deer and elk comprising 54% and 43%, respectively (Table 7). The sex and age stage structure of 60 mule deer and 48 elk used by puma at GPS clusters is in Table 8. On average, puma spent 2.3 days on mule deer (range = 1―6, SE = 0.2) and 2.9 days on elk (range = 1―10, SE = 0.3). Ungulate use rates by the GPS-collared pumas estimated from these data are in Table 9. Evidence that black bears (Ursus Americana) used portions of the same ungulates used by GPS-collared pumas was found at remains of 7 mule deer and 10 elk. Evidence that coyotes (Canis latrans) used portions of the same ungulates used by GPS-collared pumas was found at remains of 7 mule deer and 14 elk. We are currently assessing how this GPS-collar capability could be used to structure research on puma-ungulate relationships on the Uncompahgre Plateau and the additional funding and personnel needed to thoroughly execute the research. SUMMARY Experimental, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. From December 2004 to July 2005 fifteen pumas were captured, sampled, marked, and released. The number of pumas handled is partially contingent upon effort, the number of pumas present on the study area, and safety concerns. Individual pumas sampled in the population provide quantitative information on population structure, vital rates, and dynamics over time in reference and treatment periods to improve the CDOW’s puma management. All pumas were sampled as part of developing research for genotype mark-recapture procedures. Seven adult puma were fit with GPS collars, yielding 487―779 locations. Puma GPS location data will be used to: design enumeration methods in the field, develop and test puma habitat suitability models and maps, and develop potential research on puma-ungulate relationships on the Uncompahgre Plateau contingent upon funding and support. Research efforts for year 2 will focus on increasing numbers and distribution of sampled, marked, and GPS/radio-collared puma on the study area for data to address the objectives, management assumptions, and hypotheses in the study plan. We will further develop proposals for the puma genetics research, puma habitat suitability models and maps, and puma-prey relationships. 118 �LITERATURE CITED ANDERSON, A. E., D. C. BOWDEN, AND K. M. KATTNER. 1992. The puma on Uncompahgre Plateau, Colorado. Technical Publication No. 40. Colorado Division of Wildlife, Denver. ANDERSON, C. R., JR., AND F. G. LINDZEY. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. BURNHAM, K. P., AND D. R. ANDERSON. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. CAUGHLEY, G. 1978. Analysis of vertebrate populations. John Wiley and Sons, New York. COLORADO DIVISION OF WILDLIFE 2002-2007 Strategic Plan. 2002. Colorado Department of Natural Resources, Division of Wildlife. Denver. CONOVER, W. J. 1999. Practical nonparametric statistics. John Wiley & Sons, Inc., New York. COOCH, E., AND G. WHITE. 2004. Program MARK- a gentle introduction, 3rd edition. Colorado State University, Fort Collins. CULVER, M., W. E. JOHNSON, J. PECON-SLATTERY, AND S. J. O’BRIEN. 2000. Genomic ancestry of the American puma (Puma concolor). The Journal of Heredity 91:186-197. CURRIER, M. J. P., AND K. R. RUSSELL. 1977. Mountain lion population and harvest near Canon City, Colorado, 1974-1977. Colorado Division of Wildlife Special Report No. 42. HEISEY, D. M., AND T. K. FULLER. 1985. Evaluation of survival and cause specific mortality rates using telemetry data. Journal of Wildlife Management 49:668-674. KENDALL, W.L. 2001. The robust design for capture-recapture studies: analysis using program MARK. Pages 357-360 in R. Field, R. J. Warren, H. Okarma, and P. R. Sievert, editors. Wildlife, land, and people: priorities for the 21st century. Proceedings of the Second International Wildlife Management Congress. The Wildlife Society, Bethesda, Maryland, USA. KOLOSKI, J. H. 2002. 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Colorado puma research and development program: population characteristics and vital rates study plan. Colorado Division of Wildlife, Ft. Collins Research Center, Ft. Collins. MURPHY, K., M. CULVER, M. MENOTTI-RAYMOND, V. DAVID, M. G. HORNOCKER, AND S. J. O’BRIEN. 1998. Cougar reproductive success in the Northern Yellowstone Ecosystem. Pages 78-112 in The ecology of the cougar (Puma concolor) in the Northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow. OTIS, D. L., K. P. BURNHAM, G. C. WHITE, AND D. R. ANDERSON. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. OTT, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. PIERCE, B. K., V. C. BLEICH, AND R. T. BOWYER. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. POLLOCK, K. H., S. R. WINTERSTEIN, C. M. BUNCK, AND P. D. CURTIS. 1989a. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. 119 �_____, S. R. WINTERSTEIN, AND M. J. CONROY. 1989b. Estimation and analysis of survival distributions for radio tagged animals. Biometrics 45:99-109. _____, J. D. NICHOLS, C. BROWNIE, AND J. E. HINES. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs 107:1-97. POJAR, T. M., AND D. C. BOWDEN. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. ROSS, P. I., AND M. G. JALKOTZY. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. STONER, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. SWEANOR, L. L., K. A. LOGAN, J. W. BAUER, B. MILSAP, AND W. M. BOYCE. 2005 in review. Pumahuman relationships in Cuyamaca Rancho State Park, California. Wildlife Society Bulletin. VAN BALLENBERGHE, V. 1983. Rage of increasse of white-tailed deer on the George Reserve: a reevaluation. Journal of Wildlife Management 47:1245-1247. WATKINS, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. WILLIAMS, B. K., J. D. NICHOLS, AND M. J. CONROY. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. WHITE, G. C., D. R. ANDERSON, K. P. BURNHAM, AND D. L. OTIS. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. WORTON, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 120 �Table 1. Puma capture efforts with dogs from December 2, 2004 to May 12, 2005, Uncompahgre Plateau, Colorado. Month No. No. & type of puma No. & type of pumas No. & I.D. or type of pursued pumas captured Search tracks founda Days December 19 20 tracks: 11 male, 9 4 pursuits: 3 males, 1 2 pumas captured: female female M1, 1 female not handled January 15 26 tracks: 9 male, 15 8 pursuits: 4 males, 4 4 pumas captured: female, 2 cub females M1 recaptured, F2, F3, M4 February 17 22-23 tracks: 5 male, 11 pursuits: 2 males, 7 6 pumas captured: 14 female, 2-4 cubs, females, 2 cubs, or 1 1 female not handled, or 2-3 cubs & 1 cub & 1 subadult F3 recaptured, cub subadult M5, M6, 1 cub or subadult, F7 March 11 17 tracks: 8-9 male or 2 pursuits: 2 females 1 puma captured: F8 1 large cub, 7 female, 1 unspecified sex April 9 13 tracks: 10 male, 3 2 pursuits: 2 males 1 puma captured: female 1 male not handled May 7 10 tracks: 4 male, 6 8 pursuits: 3 males, 5 0 pumas captured female females 78 109 tracks found: 47- 35 pursuits: 14 males, 14 captures: (6 males, TOTALS 6 females, 1 male cub, 19 females, 1 male 48 male, 54 female, 1 cub (unknown sex) cub, 1 cub (unknown 4-6 cub or 0-1 or 1 subadult sex) or 1 subadult subadult, 1 (unknown sex) (unknown sex) unspecified a Puma hind-foot tracks with plantar pad widths >52 mm wide are assumed to be male; ≤52 mm are assumed to be female. Table 2. Pumas that were captured with aid of dogs, sampled, tagged, and released from December 2, 2004 to May 12, 2005, Uncompahgre Plateau, Colorado. Puma Sex Estimated Mass Capture Location I.D. Age (mo.) (kg) date M1 male 33 68 12-08-04 Shavano Valley M4 male 25-33 65 01-28-05 McKenzie Butte Mesa M5 male 6 12 02-04-05 Spring Creek M6 male 33 59 02-18-05 Happy Canyon F2 female 49 43 01-07-05 Dolores Canyon F3 female 41 40 01-21-05 Spring Creek F7 female 56-64 32 02-24-05 Dolores Canyon F8 female 21 30 03-21-05 Cottonwood Creek (W) 121 �Table 3. Pumas that were captured with aid of dogs, but were not handled for safety reasons, from December 2, 2004 to May 12, 2005, Uncompahgre Plateau, Colorado. Puma sex Age Capture Location Comments stage date Female adult 12-23-05 McKenzie Butte Mesa Large female. Female adult 02-01-05 South McKenzie Butte Mesa This puma probably same animal caught 12-23-05. Unspecified cub or 02-24-05 Dolores Canyon This puma apparently in subadult association with F7 at an elk kill. Possibly F7’s offspring or an unrelated subadult. Male adult 04-05-05 Horsefly Canyon (E) This puma, or another male, was pursued on 4 other occasions in the San Miguel River-toCottonwood Creek area. Table 4. Summary of puma capture efforts with dogs, December 2004 to May 2005, Uncompahgre Plateau, Colorado. Period Track Pursuit effort Puma capture Effort to capture a detection effort puma for the first time effort 11 pumas captured for 14/78 = 0.18 109/78 = 1.40 35/78 = 0.45 Dec. 2, first time (minus M1, F3, capture/day tracks/day pursuit/day 2004 & large female) to 11/78 = 0.14 capture/day 78/14 = 5.57 78/35 = 2.23 May 12, day/capture day/pursuit 2005 78/11 = 7.09 day/capture Table 5. Puma cubs sampled on the Uncompahgre Plateau Puma Study area, 2004 to 2005. Cub Sex Estimated Estimated age Mass Mother Estimated age of I.D. birth date at capture (kg) mother at birth of this litter (mo) a M5 male August 2004 6 months 12 F3 36 F9 female May 28, 2005b 31 days 2.27 F2 44 F10 female May 28, 2005b 31 days 2.04 “ “ M11 male May 28, 2005b 31 days 2.27 “ “ F12 female May 19, 2005b 42 days 2.63 F7 59-67 F13 female May 19, 2005b 42 days 1.72 “ “ F14 female June 26, 2005b 26 days 1.90 F8 24 26 days 2.0 “ “ M15 male June 26, 2005b a Estimated age of M5 was based on morphometric comparisons with known-age cubs (Logan and Sweanor 2001, and unpublished data). b Estimated age of cubs sampled at nurseries is based on the starting date for GPS location foci for mothers at nurseries. 122 �Table 6. Numbers of GPS locations for adult puma on the Uncompahgre Plateau, Colorado, December 2004 to August 2005. No. Acquisition rate Use areas estimated (km2) Puma I.D. Sex Age Dates monitored a b locations average, range, n with 100% Minimum stage Convex Polygonc M1 male adult 12-08-04 to 08-19-05 779 76, 73―83, 5 815 M4 male adult 01-28-05 to 07-25-05 487 73, 57―84, 5 254 M6 male adult 02-18-05 to 07-25-05 543 87, 82―93, 5 552 F2 female adult 01-07-05 to 08-10-05 565 65, 43―82, 7 120 F3 female adult 01-21-05 to 08-02-05 586 76, 67―85, 6 174 F7 female adult 02-24-05 to 07-26-05 362 54, 26―78, 5 94 F8 female adult 03-21-05 to 08-08-05 355 64, 48―78, 4 245 a GPS collars on pumas are remotely downloaded at approximately 1-month intervals. The last date in Dates monitored is for the last location from the last GPS data download for an individual puma for this report. b n = number of remote downloads. c Polygons for individual GPS-collared puma are overlaid on a study area map in Figure 2. Table 7. Observations at GPS location clusters for 7 GPS-collared puma on the Uncompahgre Plateau, Colorado, December 2004 to July 2005. Puma No. Dates of GPS clusters Mule Elk Porcupine Beaver Puma Only Only Nothing No. GPS I.D. GPS that were deer scavenge Puma Black bear found clusters clusters investigated or sharea signb signc not visitedd M1 23 12-26-04 to 07-10-05 4 14 1 4 2 M4 16 02-03-05 to 07-12-05 4 7 1 4 2 M6 17 02-18-05 to 07-07-05 3 11 2 1 0 4 F2 26 01-12-05 to 07-26-05 12 9 2 2 1 0 1 F3 27 01-27-05 to 07-31-05 22 5 0 0 F7 18 03-08-05 to 07-22-05 9 1 5 1 2 0 F8 11 03-23-05 to 07-03-05 7 2 1 1 1 0 139 61 48 2 1 4 10 2 11 9 Total a A GPS-collared puma either shared a prey item with another GPS-collared puma (2 instances), or a GPS-collared puma scavenged on remains of prey previously used by another GPS-collared puma (2 instances). b Only puma tracks, feces, and/or beds were found at the GPS cluster. c Only black bear sign (e.g., feces) was found at the puma GPS cluster. d Some puma GPS clusters were not investigated because clusters fell on small private land holdings where we did not have permission for access at the time, or other principal objectives of our research were priority. 123 �Table 8. Sex and age structure of mule deer and elk found at GPS location clusters for 7 GPS-collared adult puma on the Uncompahgre Plateau, Colorado, December 2004 to August 2005. Sex No. Fawn/Calf Yearling 2+ years Unknown age Mule deer Female 26 2 2 20 2 Male 10 0 3 7 0 Unknown 25 13 3 3 6 Total 61 15 8 29 8 Elk Female Male Unknown Total 25 5 18 48 12 0 16 28 1 0 0 1 12 5 1 18 0 0 1 1 Table 9. Estimated ungulate use rates of adult GPS-collared pumas on the Uncompahgre Plateau, Colorado, December 2004 to July 2005. Puma Dates starting with & No. days inclusive in No. Estimated No. I.D. ending with ungulate use date span ungulates ungulates used used per yeara M1 12-26-04 to 07-10-05 196 18 33.5 M4 02-03-05 to 07-04-05 152 11 26.4 M6 02-18-05 to 07-07-05 140 14 36.5 F2 01-12-05 to 07-26-05 195 21 39.3 F3 01-27-05 to 07-31-05 185 27 53.3 F7 03-08-05 to 07-16-05 131 9 25.1 F8 03-23-05 to 07-03-05 103 9 31.9 a Estimated ungulate use rates per year are based on the key assumption that the individual puma would use ungulates throughout the year equal to the same rate recorded during the monitoring span in Dates starting with & ending with ungulate use. This assumption is probably not reliable especially for adult female pumas, because their reproductive status, and thus energetic needs vary throughout the year. For example, F3 was raising cubs born in August 2004; yet, F2, F7, and F8 started raising cubs born in May, May, and June of 2005, respectively. In addition, not all GPS clusters were investigated for M1, M4, M6, and F2 (see Table 7). 124 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population G h Vulnerability to Harvest Puma Habitat Human Development Habitat Use Effects of Translocation Estimation Methods for Monitoring Deer, Elk, Other Natural Prey & Species of Concern Domestic Animals Puma― Human Relationships Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Habitat Maps Puma―Prey Relationships Models Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this report and the puma management goal (at top). 125 �![ ![ ![ Delta M1 ![ Olathe ![ Montrose F8 F3 ![ Nucla Naturita F7 ![ M4 F2 Norwood M6 ![ ![ Ridgeway ![ ![ Legend County Boundaries 0 5 10 20 Kilometers Study Area . Figure 2. The Uncompahgre Plateau Puma Study Area with activity areas of adult GPS-collared pumas depicted with 100% Minimum Convex Polygons, December 2004 to August 2005. 126 �Colorado Division of Wildlife July 2004 - June 2005 WILDLIFE RESEARCH REPORT State of Cost Center Work Package No. Task No. Colorado 3430 7210 1 Federal Aid Project: ____N/A : Division of Wildlife : Mammals Research : Customer Support Services/Research Support : Library Services : Period Covered: July 1, 2004 – June 30, 2005 Author: J. A. Boss Personnel: J. A. Boss All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT During the Segment, the following were accomplished: 722 Publications acquired by the Research Center Library for the use of Colorado Division of Wildlife (CDOW) employees, cooperators, wildlife educators, and the public. These publications include books, interlibrary loan materials, periodicals, and newsletters. 1,593 Items of information delivered to CDOW employees, cooperators, wildlife educators, and the public, resulting from requests and literature searches. 469 Items of information cataloged into the electronic and card catalogues, which including duplicates and additional volumes expanded the Research Center Library inventory to 24,293 items. 703 Items of information entered into the electronic catalog for the maintenance of the materials collection of the Research Center Library. 1,322 Items checked-out by CDOW employees, cooperators, wildlife educators, and the public indicating use of library services. 2,251 Items of information delivered that are produced by the CDOW employees, cooperators, wildlife educators, and the public. These items include CDOW and other publications (1,552) research articles by CDOW personnel (464), and CDOW Wildlife Research Reports (235). 127 �WILDLIFE RESEARCH REPORT COLORADO DIVISION OF WILDLIFE RESEARCH LIBRARY SERVICES JACQUELINE A. BOSS P.N. OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Division of Wildlife (CDOW) employees, cooperators, wildlife educators, and the public. SEGMENT OBJECTIVES 1. Continue to improve and modernize library services by implementing the Dynix Horizon library automation system via an Application Service Provider (ASP) model (project began in June 2002). By joining the Automation System Colorado Consortium (ASCC) we were able to take advantage of a LSTA grant written by the Colorado State Library staff, which facilitated the implementation of this system. 2. Continue to develop, improve, and implement the CDOW Research Center Library web-site (started in June 2004) by implementing the Dynix Horizon system online to serve a broader spectrum of patrons of the CDOW Research Center Library. 3. Continue to attended ASCC meetings and participate Dynix Horizon online classes to enhance utilization of the Dynix system. SUMMARY OF LIBRARY SERVICES Maintain and Build Electronic Catalogs of all Research Library Holdings 469 Total number of items cataloged during this period of time. This includes not only new acquisitions, but also older materials from the library collection being entered into the electronic catalog for the first time. Among the new acquisitions are Federal Aid : Job Progress Reports and manuscripts written by CDOW researchers and other employees. 703 Total number of items of information added to the electronic circulation system during this period. This includes not only the above mentioned newly cataloged items, but also newly acquired serials, volumes, additional copies, and other items being assigned scanning numbers for the electronic circulation system for the first time. $227,820 Estimated value of the 24,293 items in the Research Center Library collection as of June 30, 2005. The project to determine the value of the library collection began in May 2000. As time permits, the value of books already in the collection is determined, and added to the already “estimated value.” Each month’s addition of values of older materials, plus the new materials, increases the value of the Library collection. Not included in the “assumed value” of the Library collection are all of the periodicals, older materials, and government documents, which continue to be a large part of the collection, thus the “estimated value” of the Library collection continues to grow month by month. 128 �Publications Acquired in the Research Center Library ANDERSON, C. R., JR. 2003. Cougar ecology, management, and population genetics in Wyoming. Laramie, WY : Univ. of Wyo. Dissertation (Ph.D.) University of Wyoming, Laramie, WY. 124 leaves ASSOCIATION OF MIDWEST FISH AND WILDLIFE AGENCIES. [2004] Midwest Association of Fish and Wildlife Agencies : 71st Annual Directors Meeting : Proceedings : July 11-13, 2004 : Bismarck, North Dakota. [S.l.: s.n.] Hosted by North Dakota Game and Fish Department. 502 leaves BAKER, R. O. AND R. M. TIMM. 1998. Management of conflicts between urban coyotes and humans in southern California. [Hopland, CA] : Univ. of Calif. Pp.299-312 BANASCH, U. AND G. HOLROYD, eds. 2004. The 1995 peregrine falcon survey in Canada. Ottawa, Ont. : Environment Canada. Occasional paper; no. 110. 43pp. BAUMANN, R. W. 2004. Monographs of the Western North American naturalist. Provo, UT : Brigham Young University. Monographs of the Western North American naturalist; vol. 2. 135pp. BERGMAN, E. J. 2003. Assessment of prey vulnerability through analysis of wolf movements and kill sites. Bozeman, MT : Montana State Univ. Thesis (M.S.) Montana State University, Bozeman, MT. 56 leaves CAILTEUX, R. L., L. DEMONG, B. J. FINLAYSON, W. HORTON, W. MCCLAY, R. A. SCHNICK, AND C. THOMPSON. 2000. Rotenone in fisheries : Are the rewards worth the risks? Bethesda, MD : Am. Fish. Soc. Trends in fisheries science and management; 1. 122pp. CAIRNS, S. D., D. R. CALDER, A. BRINCKMANN-VOSS, C. B. CASTRO, D. G. FAUTIN, P. R. PUGH, C. E. MILLS, W. C. JAAP, M. N. ARAI, S. H. D. HADDOCK, AND D. M. OPRESKO. 2002. Common and scientific names of aquatic invertebrates from the United States and Canada : Cnidaria and Ctenophora. Bethesda, MD : American Fisheries Society. 2nd edition. Special publication; 28. 115pp. CARSEY, K., G. KITTEL, K. DECKER, D. J. COOPER, AND D. CULVER. 2003. Field guide to the wetland and riparian plant associations of Colorado. Fort Collins, CO : Colorado Natural Heritage Program. 466 leaves CLARK, L. 2002. Human conflicts with wildlife : economic considerations. Fort Collins, CO : National Wildlife Research Center. Proceedings of the Third NWRC Special Symposium : Fort Collins, Colorado, Aug. 1-3, 2000. 180pp. CLUTTON-BROCK, T. H. AND J. M. PEMBERTON. 2004. Soay sheep : dynamics and selection is an island population. Cambridge, U. K. : Cambridge Univ. Press. 383pp. COLORADO DEPT. OF NATURAL RESOURCES. DIV. OF WATER RESOURCES. [2004]. Stream flow data for Colorado : water year 2003. [Denver, CO : Colo. Dept. of Natural Resources. Div. of Water Resources.] 217+pp. COLORADO DIV. OF WILDLIFE. [2004]. Recommended survey protocol and actions to protect nesting burrowing owls. Denver, CO : Colo. Div. of Wildl. 3 leaves. __________. 2003. State of Colorado River Otter Recovery Plan : revision of 1980, 1984, & 1998 draft plans.. Denver, CO : Colo. Div. of Wildl. 51 leaves. COOK, J. G., B. K. JOHNSON, R. C. COOK, R. A. RIGGS, T. DELCURTO, L. D. BRYANT, AND L. L. IRWIN. 2004. Effects of summer-autumn nutrition and parturition date on reproduction and survival of elk. Bethesda, MD : The Wildlife Society. Wildlife monograph; 155. 61pp. CRONIN-JONES, L. 1992. The schoolyard wildlife activity guide. [Tallahassee, FL] : Florida Game & Fresh Water Fish Commission. 208pp. CYPHER, B. L., ed. [2004]. Transactions of the Western Section of The Wildlife Society : 2002/2003 – Volume 38/39. [Cordova, CA] : The West. Sect. of The Wildl. Soc. 40pp. DOUGLAS, C. L. 1966. Amphibians and reptiles of Mesa Verde National Park, Colorado. Lawrence, KS : Univ. of Kan. Publications; vol. 15, no. 15, pp.711-744 129 �DRONKERT, A. AND M. R. GRODE. 1984. The river otter (Lutra canadensis) in northwest Colorado : historical distribution, present status, and future prospects – 1984.. Grand Junction, CO : Colo. Div. of Wildl. 83 leaves. EVERSOLE, A. G. [2004]. Proceedings of the Fifty-seventh Annual Conference : Southeastern Association of Fish & Wildlife Agencies: Oct. 11-15, 2003 : Mobile, AL. S.l : Assoc. of Fish & Wildl.Agencies. 389pp. FAGERSTONE, K. A. AND G. W. WITMER, eds. [2003]. Proceedings of the Tenth Wildlife Damage Management Conference : April 6-9, 2003 : Hot Springs, Arkansas. [Fort Collins, CO : National Wildlife Research Center]. 444pp. FLOYD, M. L., ed. 2003. Ancient pin~on-juniper woodlands : a natural history of Mesa Verde country. Boulder, CO : Univ. Press of Colorado. 389pp. FOWLER, C. W. AND T. D. SMITH. 2004. Dynamics of large mammal populations. New York : John Wiley & Sons. Based on conference papers : Utah State University, Logan Utah, 1979. 477pp. FOX, C. H. AND C. M. PAPOUCHIS. 2005. Coyotes in our midst : coexisting with an adaptable and resilient carnivore. Sacramento, CA : Animal Protection Institute. 60pp. GRIGG, N. S. 2003. Colorado’s water : science & management, history & politics. Fort Collins, CO : Aquamedia Publishing. 179pp. HAFNER, D. J. 1998. Evaluation of the taxonomic, genetic, and conservation status of Preble’s jumping mouse, Zapus hudsonius preblei, and associated subspecies. [Albuquerque, NM : New Mexico Museum of Natural History]. 7 leaves + HALLERMAN, E. M., ed. 2003. Population genetics : principles and applications for fisheries scientists. Bethesda, MD : American Fisheries Society. 458pp. HANNA, J. D. [2002]. Desert Bighorn Council : 2001 Transactions : a compilation of papers presented at the 45th Annual Meeting : Hermosillo, Sonora, Mexico: April 18-21, 2001. [S.l. : Desert bighorn Council]. 279pp. ________. [2003]. Desert Bighorn Council : 2002 Transactions : a compilation of papers presented at the 46th Annual Meeting : Palm Springs, CA: April 10-11, 2002. [S.l. : Desert bighorn Council]. 67pp. HARRIS, R. B., ed. 2003. Ursus: an official publication of the International Association for Bear Research and Management. [S.l.] : International Assoc. for Bear Research & Management. Vol. 14(1 & 2). 2 issues _________, ed. 2004. Ursus: an official publication of the International Association for Bear Research and Management. [S.l.] : International Assoc. for Bear Research & Management. Vol. 15(1 & 2). 2 issues HILL, C. G. 2004. Dynamics of northern pike spawning and nursery habitat in the Yampa River, Colorado. Fort Collins, CO : Colo. State Univ. Thesis (M.S.) Colorado State University, Fort Collins, CO. 87 leaves HUNDERTMARK, K. J. AND A. R. RODGERS, eds. [2004]. Alces : supplement no. 2 : additional papers from the 3rd International Moose Symposium as convened by Komi Science Centre of the Ural Division of the U.S.S.R Academy of Sciences : Aug. 27 - Sept. 5, 1990 : Syktyvkar, Komi Autonomous Socialist Republic, U.S.S.R. Thunder Bay, Ont. : Lakehead Univ. 142pp. HUWER, S. L. 2004. Evaluating greater sage-grouse brood habitat using human-imprinted chicks. Fort Collins, CO : Colo. State Univ. Thesis (M.S.) Colorado State University, Fort Collins, CO. 85 leaves IN-SITU, INC. 1985. Aquatics report for the Parachute Creek shale oil program. Lakewood, CO : In-situ, Inc. Project No. 4156. 50+ leaves JOHNSGARD, P. A. 2005. Prairie dog empire : a saga of the shortgrass prairie. Lincoln, NE : Univ. of Nebr. Press. 243pp. JONES, S. R. 2004. A field guide to the North American prairie. Boston, MA : Houghton Mifflin. The Peterson Field Guide Series. 510pp. _________. 2003. Owls of Boulder County. Boulder, CO : Boulder County Nature Assoc. 51pp. 130 �KAMINSKY, P. 2001. The moon pulled up an acre of bass : a flyrodder’s odyssey at Montauk Point. New York : Hyperion. 244pp. KERLINGER, P., R. CURRY, AND R. A. RYDER. 2000. Ponnequin Wind Energy Project : reference site avian study : January 1, 1998 – December 31, 1998. Golden, CO : National Renewable Energy Laboratory. Contract No. DE-AC36-99-GO10337. 26 leaves KRAUSMAN, P. R., L. K. HARRIS, C. L. BLASCH, K. K. G. KOENEN, AND J. FRANCINE. 2004. Effects of military operations on behavior and hearing of endangered Sonoran pronghorn. Bethesda, MD : The Wildlife Society. Wildlife monographs; 157. 41pp. KUHN, G. AND C. A. WILLIAMS. 2004. Evaluation of streamflow losses along the Gunnison River from Whitewater downstream to the Redlands Canal diversion dam, water years 1995 – 2003. Reston, VA : U.S. Geological Survey. Scientific investigations report; 2004-5095. 22pp. MCCABE, R. E., B. W. O’GARA AND H. M. REEVES. 2004. Prairie ghost : pronghorn and human interaction in early America. Boulder, CO : Univ. Press of Colorado. A Wildlife Management Institute book. 175pp. MILLER, B., D. FOREMAN, M. FINK, D. SHINNEMAN, J. SMITH, M. DEMARCO, M. E. SOULE, AND R. HOWARD. Southern Rockies Wildlands Newtwork Vision : a science-based approach to rewildling the Southern Rockies. Golden, CO : The Colorado Mountain Club Press. 248pp. MONSEN, S. B. [2004]. Restoration manual for Colorado sagebrush and associated shrubland communities. [S.l. : s.n.] 2 sections MORTENSON, J. A., D. G. WHITTAKER, E. C. MESLOW, D. H. JACKSON J. J. HENDRICK, AND B. K. JOHNSON, eds. [2004]. Proceedings of the Western States & Provinces Deer and Elk Workshop : Wilsonville, Oregon : August 1-3, 2001. [Portland, OR : Oregon Dept. of Fish & Wildlife. 133 leaves MOSER, T. J., R. D. LIEN, K. C. VERCAUTEREN, K. F. ABRAHAM, D. E. ANDERSEN, J. G. BRUGGINK, J. M. COLUCCY, D. A. GRABER, J. O. LEAFLOOR, D. R. LUUKKONEN, AND R. E. TROST, eds. 2004. Proceedings of the 2003 International Canada Goose Symposium, Madison, Wisconsin, USA. S.l. : s.n. 265pp. NELSON, J. S., E. J. CROSSMAN, H. ESPINOSA-PEREZ, L. T. FINDLEY, C. R. GILBERT, R. N. LEA, AND J. D. WILLIAMS. 2004. Common and scientific names of fishes from the United States, Canada, and Mexico. Bethesda, MD : American Fisheries Society. 6th edition. Special publication; 29. 386pp. NEPTUN, K. S. 2001. The riffle quality triad : a novel approach to assessing pollution-induced degradation in cobble-bottom streams. M.S. Thesis, Fort Collins, CO, Colorado State Univ. 57pp. ODEH, M., ed. 2000. Advances in fish passage technology : engineering design and biological evaluation. Bethesda, MD : American Fisheries Society. 154pp. O’GARA, B. W. AND J. D. YOAKUM. 2004. Pronghorn : ecology and management. Boulder, CO : Univ. of Colo Pres. A Wildlife Management Institute book. 903pp. POWELL, R. A. 1982. The fisher : life history, ecology, and behavior. Minneapolis, MN : Univ. of Minn. Press. 217pp. REINHARDT, V. AND A. REINHARDT. 2002. Comfortable quarters for laboratory animals. Washington, DC : Animal Welfare Institute. 9th ed. 114pp. RENSHAW, E. 1993. Modelling biological populations in space and time. New York : Cambridge Univ. Press. 403pp. RODGERS, A. R. AND G. W. REDMOND, eds. [2004]. Alces 38 : a journal devoted to the biology and management of moose. Thunder Bay, Ont. : Lakehead Univ. 226pp. SCHALLER, G. B. 1967. The deer and the tiger : a study of wildlife in India. Chicago, IL : Univ. of Chicago Press. 370pp. SCHANZLE, R. W., G. W. KRUSE, J. A. KATH, R. A. KLOCEK, AND K. S. CUMMINGS. 2004. The freshwater mussels (Bivalvia: Unionidae) of the Fox River basin, Illinois and Wisconsin. Champaign, IL : Illinois Natural History Survey. Biological notes; 141. 35pp. 131 �SCHROEDER, M. A., ed. 2004. Western Agencies Sage and Sharp-tailed Grouse Technical Committee (24th : 2004 : Wenatchee, WA). [S.l. : Western Agencies Sage & Columbian Sharp-tailed Grouse Technical Committee]. 38 leaves SEALING, C. AND G. BENNETT. 1980. Middle Park reservoir studies : final report. Grand Junction, CO : Colo. Div. of Wildl. 116 leaves. SHEAFFER, S. E., D. H. RUSCH, D. D. HUMBURG, J. S. LAWRENCE, G. G. ZENNER, M. M. GILLESPIE, F. D. CASWELL, S. WILDS, AND S. C. YAICH. 2004. Survival, movements, and harvest of eastern prairie population Canada geese. Bethesda, MD : The Wildlife Society. Wildlife monographs; 156. 54pp. SMITH, D. W., D. R. STAHLER, AND D. S. GUERNSEY. 2004. Yellowstone Wolf Project : annual report : 2003. Yellowstone National Park, WY : Yellowstone Center for Resour. 18pp. SOCIETY OF RANGE MANAGEMENT. 1995-2003. Abstracts : annual meeting : Society of Range Management. S.l. : Soc. of Range Manage. 7 vols. SOUTHWICK, R. I. AND A. J. LOFTUS, eds. 2003. Investigation and monetary values of fish and freshwater mussel kills. Bethesda, MD : American Fisheries Society. Special publication; 30. 177pp. SUNDBERG, W. C. 2004. Fort Collins’ first water works. Fort Collins, CO : Poudre Landmarks Foundation, Inc. 98pp. TESSMANN, S. A., ed. 2004. Proceedings of the Fifth Western States & Provinces Deer and Elk Workshop - 2003 : Jackson, Wyoming. [S.l.] : Wyoming Chapter of The Wildlife Society. 138pp. THOMPSON, S. K. 2002. Sampling. New York : John Wiley & Sons. 2nd edition. 367pp. TIMM, R. M., R. O. BAKER, J. R. BENNETT, AND C. C. COOLAHAN. 2004. Coyote attacks : an increasing suburban problem. [Hopland, CA] : Univ. of Calif. pp.47-57 TRAINOR, A. M. 2004. Influence of resource supplementation on movements of Preble’s meadow jumping mouse (Zapus hudsonius preblei) and habitat use characteristics. Thesis (M.S.) Colorado State University, Fort Collins, CO. 105pp. VAN TIGHEM, K. 1999. Predators : wild dogs & cats. Denver, CO : Altitude Publishing. An Altitude SuperGuide. 160pp. WINTER, S. L. 1999. Plant and breeding bird communities of black-tailed prairie dog colonies and noncolonized areas in southwest Kansas and southeast Colorado. Thesis (M.S.) Kansas State University, Manhattan, KS. 202 leaves WOHL, E. E. 2000. Disconnected rivers : linking rivers to landscapes. New Haven, CT : Yale Univ. Press. 210pp. ________ 2004. Mountain rivers. Washington, DC : American Geophysical Union. Water resources monograph; 14. 320pp. ________ 2001. Virtual rivers : lessons from the mountain rivers of the Colorado Front Range. New Haven, CT : Yale Univ. Press. 301pp. ________, R. MCCONNELL, J. SKINNER, AND R. STENZEL. 1998. Inheriting our past : river sediment sources and sediment hazards in Colorado. Fort Collins, CO : Colorado Water Resources Research Institute. Water in the balance; no.7. 28 leaves YAGER, T. J. B., D. B. SMITH, AND J. G. CROCK. 2004. Biosolids, soil, crop, ground-water, and streambed-sediment data for a biosolids-application area near Deer Trail, Colorado 2001. Reston, VA : U.S. Geological Survey. Open-file report; 2004-1388. 69pp. ZAHRATKA, J. L. 2004. The population and habitat ecology of snowshoe hares (Lepus americanus) in the southern Rocky Mountains. Thesis (M.S.) University of Wyoming, Laramie, WY. 88 leaves ZIMMER, J. P. 2004. Winter habitat use and diet of snowshoe hares in the Gardiner, Montana area. Thesis (M.S.) Montana State University, Bozeman, MT. 65 leaves 132 �Publications Donated to the Research Center Library ATON, J. M. 2000. River flowing from the sunrise : an environmental history of the Lower San Juan. Logan, UT : Utah State Univ. Press. 216pp. BAILEY, J. 2001. Trout at ten thousand feet : reflections of a passionate fisherman. Mechanicsburg, PA : Stackpole Books. 175pp. BRIDGES, W. 2003. Managing transitions : making the most of change. Cambridge, MA : Perseus Publishing. 2nd edition. 163pp. DINES, L. 2001. The American mustang guidebook : history, behavior, and state-by-state directions on where to best view America’s wild horses. Minocqua, WI : Willow Creek Press. 150pp. DEVINNE, C. AND L. MORROW. 2000. The Orvis field guide to first aid for sporting dogs. Minocqua, WI : Willow Creek Press. The Orvis field guide series. 126pp. GIERACH, J. 2000. Death, taxes, and leaky waders. New York : Simon & Schuster. 414pp. HUGHES, D. 2005. Handbook of hatches : introductory guide to the foods trout eat & the most effective flies to match them. Mechanicsburg, PA : Stackpole Books. 276pp. ________. 2001. Matching mayflies. Portland, OR : Frank Amato Publications. 83pp. ________. 2002. Taking trout : good, solid, practical advice for fly fishing streams and still waters. Mechanicsburg, PA : Stackpole Books. 210pp. ________. 2002. Trout from small streams. Mechanicsburg, PA : Stackpole Books. 167pp. INCORPORATING FIREARMS SAFETY. 2000. The Orvis Shooting School method of wingshooting. Minocqua, WI : Willow Creek Press. The Orvis field guide series. 83pp. JAWOROWSKI, E. 1999. Troubleshooting the cast. Mechanicsburg, PA : Stackpole Books. Illus. by H. W. Robertson III. JUDY, J. 2002. Slack line strategies for fly fishing. Mechanicsburg, PA : Stackpole Books. 196pp. KLUCAS, G. 2004. Leadville : the struggle to revive an American town. Washington, DC : Island Press. A Shearwater Book. 304pp. KUGACH, G. 2002. Fishing tips for freshwater. Mechanicsburg, PA : Stackpole Books. 214pp. ________. 2000. Fly fisher’s pattern book. Mechanicsburg, PA : Stackpole Books. 1st ed. 258pp. ________. 2001. Fly tier’s handbook. Mechanicsburg, PA : Stackpole Books. 1st ed. 261pp. LARSEN, D. 2002. don’t shoot the decoys : original stories of waterfowling obsession. New York : Ducks Unlimited. 236pp. LOUV, R. 2000. Fly-fishing for sharks : an angler’s journey across America. New York : Simon & Schuster. 494pp. MACKENZIE, G. 2001. Hair-hackle typing techniques & fly patterns. Portland, OR : Frank Amato Publications. 87pp. MCLENNAN, J. 2003. Fly-fishing western trout streams. Mechanicsburg, PA : Stackpole Books. 207pp. MORROW, T. 2000. The Orvis field guide to shotgun care & maintenance. Minocqua, WI : Willow Creek Press. The Orvis field guide series. 176pp. MURIE, M. E. 1997. Two in the far north. Portland, OR : Alaska Northwest Books. Illus. by O. J. Murie. 369pp. MURRAY, H. 2003. Trout stream fly-fishing. Portland, OR : Frank Amato Publications. 103pp. OSTHOFF, R. 2001. No hatch to match : aggressive strategies for fly-fishing between hatches. Mechanicsburg, PA : Stackpole Books. 138pp. RICHARDS, M. 2004. Deerskins into buckskins : how to tan with brains, soap or eggs. Cave Junction, OR : Backcountry Publishers. 2nd edition. 240pp. SANDERS, C. J. 2005. The boys of winter : life and death in the U.S. ski troops during the Second World War. Boulder, CO : University Press of Colorado. 256pp. SCHOLLMEYER, J. 2001. Nymph fly-tying techniques. Portland, OR : Frank Amato Publications. 125pp. SUZUKI, D. AND W. GRADY. 2004. Tree : a life story. Vancouver, B.C. : Greystone Books. Illus. by R. Bateman. 190pp. 133 �TREMPER, B. 2001. Staying alive in avalanche terrain. Seattle, WA : The Mountaineers Books. 284pp. VERRENGIA, J. Vanishing Colorado : rediscovering a western landscape. Boulder, CO : Court Wayne Press. 112pp. AV Materials Acquired in the Research Center Library ALAN MADISON PRODUCTIONS, INC. n.d. Firearms safety & the hunter. Chatham, NY : Alan Madison Productions, Inc. DVD 21:23 min. ________. n.d. Hunter’s Path. Chatham, NY : Alan Madison Productions, Inc. DVD 21:23 min. ________. n.d. The last shot. Chatham, NY : Alan Madison Productions, Inc. DVD 14:28 min. ________. n.d. Shoot / don’t shoot. Chatham, NY : Alan Madison Productions, Inc. DVD 14:33 min. ________. n.d. The skill of survival : desert region. Chatham, NY : Alan Madison Productions, Inc. VHS 29:40 min. ________. n.d. Survival. Chatham, NY : Alan Madison Productions, Inc. DVD 21:30 min. AMERICAN OUTDOOR PRODUCTIONS. 2004. Shedding light on chronic wasting disease. Fort Collins, CO : American Outdoor Productions. DVD 21:23 min. COLORADO DIV. OF WILDLIFE AND COLORADO GRASSLAND SPECIES WORKING GROUP. 2003. Conservation plan for grassland species in Colorado. [Denver, CO] : Colo. Div. of Wildl. 1 CD O’DELL, D. R. 1990. Cougar : ghost of the Rockies. Standford, CT : ABC Video. VHS 21:30 min. HUNTDATA LLC. 2003. Colorado Outdoors : big game CD deluxe update. Denver, CO : HuntData LLC. 1 CD RICHARDS, M. 2003. Deerskins into buckskins : how to tan with brains, soap or eggs a field guide for hunters and gatherers. Cave Junction, OR : Backcountry Publishers. DVD (no time given). U.S. FISH AND WILDLIFE SERVICE. [2004]. Status of waterfowl 2003 : 2003 report on North America’s waterfowl populations and habitat conditions. S.l. : Stefan Dobert Productions, Inc. VHS 16:00 min. Theses, Documents and Books Obtained on Interlibrary Loan Literature Searches and Information Delivered AITKEN, G. 2004. A new approach to conservation : the importance of the individual through wildlife rehabilitation. Burlington, VT : Ashgate Pub. Co. Ashgate studies in environmental policy and practice. 204pp. BABEY, G. J. 1983. Evaluation of three strains of rainbow trout stocked in a reservoir where the ectoparasite Lernaea cyprinacea is endemic. M.S. Thesis, Logan, UT, Utah State Univ. 83pp. BALLARD, B, AND R. CHEEK, eds. 2003. Exotic animal medicine for the veterinary technician. Ames, IA : Iowa State Press. 379pp. BARBOUR, M. G. AND W. D. BILLINGS, eds. 1988. North American terrestrial vegetation. Melbourne, Australia : Cambridge Univ. Press. 434pp. BLACK, J. M., ed. 1996. Partnerships in birds : the study of monogamy. New York : Oxford University Press. Oxford ornithology series; 6. 420pp. BRANCH, M. P., ed. 2004. Reading the roots : American nature writing before Walden. Athens, GA : Univ. Of Georgia Press. 408pp. CALIFORNIA. DEPT. OF FISH AND GAME. INLAND FISHERIES BRANCH. 1971 – 1973. Inland fisheries administrative report. [Sacramento, CA] : State of Calif. Dept of Fish & Game. var. pagination CALIFORNIA. DEPT. OF FISH AND GAME. INLAND FISHERIES BRANCH. 1979 – 1981. Inland fisheries administrative report. [Sacramento, CA] : State of Calif. Dept of Fish & Game. var. pagination CAREY, C., L. FLORANT, B. A. WUNDER, AND B. HORWITZ, eds. 1993. Life in the cold : ecological, physiological and molecular mechanisms. Boulder, CO : Westview Press. 575pp. CHAPPELL, W. R. AND K. K. PETERSEN. 1976. Molybdenum in the Environment. New York : Marcel Dekker. Vol. 1. 315pp. 134 �CLADY, M. D. 1973. Competition and fish cultural study of rainbow trout : a literature review. Portland, OR : Oregon State Game Commission. F-94-R-1. 37 leaves CLOSE, T. AND R. HASSINGER. 1981. Evaluation of Madison, Donaldson and Kamloops strains of rainbow trout (Salmo gairdneri) in Lake Superior. [St.Paul, MN] : Minn. Dept. of Natural Resour., Div. of Fish & Wildlife. Investigational report; no. 372. 17pp. COUNCIL OF BIOLOGY EDITORS. STYLE MANUAL COMMITTEE. 1994. Scientific style and format : the CBE manual for authors, editors, and publishers. New York: Cambridge Univ. Press. 6th edition. 825pp. EBEDES, H. ed. 1992. The use of tranquillizers in wildlife. Pretoria, South Africa : Dept. of Agricultural Development. Proceedings of the Wildlife Tranquillizer Symposium held at the National Zoological Gardens, Boom Street, Pretoria, Republic of South Africa 17 and 18 March 1989. 69pp. EDDLEMAN, L. E. 1967. A study of phyto-edaphic relationships in alpine tundra of northern Colorado. Ph.D. Dissertation, Fort Collins, CO, Colorado State University. 148pp. ELECTRIC POWER RESEARCH INSTITUTE. 1986. Assessment of downstream migrant fish protection technologies for hydroelectric application. Palo Alto, CA : Electric Power Research Institute. AP-4711 Research Project 2694-1. 1 vol. (various pagings) ELLIOTT, J. M. 1994. Quantitative ecology and the brown trout. New York : Oxford University Press. Oxford series in ecology and evolution. 286pp. FAY, C. W. 1982. An evaluation of harvest, survival, growth, and movement of five strains of rainbow trout (Salmo gairdneri) in Virginia streams. M.S. Thesis, Blacksburg, VA, Virginia Polytechnic Institute and State University. 143pp. FREMONT, J. C. 1966. Report of the exploring expedition to the Rocky Mountains. Ann Arbor, MI : Univ. Microfilms, Inc. March of America facsimile series; No. 79. Originally printed 1845. 327pp. GRANT, J. H., IV. 1995. Dispersal, activity and behavior of white-tailed prairie dogs. M.S. Thesis, Laramie, WY, Univ. of Wyoming. 138pp. HALASI, J. A. 1978. Environmental report : Keota Project, Weld County, Colorado. Lakewood, CO : Wyoming Mineral Corp. 2 vols. HEPWORTH, D. K. AND D. J. DUFFIELD. 1991. Survival and return of the creel of fingerling rainbow trout stocked at different times of year in Minersville Reservoir, Utah. Salt Lake City, UT : Utah Dept. of Natural Resources, Div. of Wildlife Resources. Publication; no. 91-8. 18 leaves HILMES, M. M. 1933. Changes in channel morphology associated with placer mining near Fairplay, Colorado. M.S. Thesis, Fort Collins, CO, Colo. State Univ. 261pp. HOPKINSON, S. J. AND P. GUBBELS. 1990. Estimated costs and returns for rainbow trout production in the Thompson-Okanagan region, 1990. Victoria, BC : Province of British Columbia, Aquaculture and Commercial Fisheries Branch. Aquaculture industry development report; no. 90-5. 28pp. HUDY, M. 1980. Evaluation of six strains of rainbow trout (Salmo gairdneri) stocked as fingerlings in Porcupine Reservoir, Utah. M.S. Thesis, Logan, UT, Utah State Univ. 79pp. JACOBS, S. K. 2003. Healers of the wild : rehabilitating injured and orphaned wildlife. Boulder, CO : Johnson Books. 2nd ed. 214pp. KEATING, J. F. 1968. Tests for increasing returns of hatchery trout. [Boise, ID] : Idaho Fish & Game. Lochsa River investigations; F-32-R-9. 26 leaves KESTERSON, M. B. 1988. Lynx home range and spatial organization in relation to population density and prey abundance. M.S. Thesis, Fairbanks, AK, Univ. of Alaska. 66 leaves KMIECIK, N. E. 1980. An evaluation of rainbow trout strains in the sport fishery of three Wisconsin lakes and for trout ranching in Minnesota winterkill lakes. M.S. Thesis, Stevens Point, WI, Univ. of Wisc. – Stevens Point. 107pp. KNIGHT, D. H. 1994. Mountains and plains : the ecology of Wyoming landscapes. New Haven, CT : Yale Univ. Press. 338pp. 135 �LARISON, J. R. 2001. Cadmium-induced calcium stress in natural populations of white-tailed ptarmigan in Colorado. Ph.D. Thesis, Ithaca, NY, Cornell Univ. 184pp. LIGON, J. S. 1961. New Mexico birds and where to find them. Albuquerque, NM : Univ. of New Mexico. 360pp. MACKIE, R. J., D. F. PAC, K. L. HAMLIN, AND G. L. DUSEK. 1998. Ecology and management of mule deer and white-tailed deer in Montana. Helena, MT : Mont. Fish, Wildl. & Parks. Federal Aid Project W-120-R. 180pp. MACLULICH, D. A. 1937. Fluctuations in the numbers of the varying hare (Lepus americanus). Toronto, Ont. : Univ. of Toronto Press. University of Toronto studies. Biological series; no. 43. 136pp. MARR, C. A. 1994. Effects of acclimation and pulsed exposure on the lethal and sub-lethal responses of brown and rainbow trout exposed to a metals mixture. Ph.D. Dissertation, Laramie, WY, Univ. of Wyoming. 96 leaves MCCULLOUGH, D. R. 1992. Wildlife 2001 : populations. New York : Elsevier Applied Science. 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Growth, heterosis, heterozygosity and effects of temperature and competition in pure and hybrid strains of rainbow trout, Salmo gairdneri Richardson. Ph.D. Dissertation, Winnipeg, Man., Can., Univ. of Manitoba. 3 microfiches (268 fr.) WOODWARD-CLYDE CONSULTANTS AND UNION OIL COMPANY OF CALIFORNIA. 1980. Keota Uranium Project, Weld County, Colorado environmental report for Union Oil Company of California. San Francisco, CA : Woodward-Clyde Consultants. 1 v. (various pagings) CDOW Manuscripts Published July, 2004 – June, 2005 In addition to CDOW Research Progress Reports for avian, aquatic, and mammal research studies, the following publications were completed. ANDELT, W. F., T. M. POJAR, AND L. W. JOHNSON. 2004. Long-term trends in mule deer pregnancy and fetal rates in Colorado. Journal of Wildlife Management 68(3):542-549 BAKER, D. L., M. A. WILD, M. M. CONNER, H. B. RAVIVARAPU, R. L. DUNN, AND T. M. NETT. 2004. Gonadotropin-releasing hormone agonist : a new approach to reversible contraception in female deer. Journal of Wildlife Diseases 40(4):713-724 BELAY, E. D., R. A. MADDOX, E. S. WILLIAMS, M. W. MILLER, P. GAMBETTI, AND L. B. SCHONBERGER. 2004. Chronic wasting disease and potential transmission to humans. Emerging Infectious Diseases 10(6):977-984 BISHOP, C. J. [2004]. Effects of nutrition and habitat enhancements on mule deer fawn recruitment : preliminary results. In: Proceedings of the Western States & Provinces Deer and Elk Workshop : Wilsonville, Oregon : August 1-3, 2001, ed., J. A. Mortenson, et al. Oregon Dept. of Fish and Wildlife. p.55 (abstract) ________, G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2004. Effect of enhanced winter nutrition of free-ranging mule deer on fawn survival and recruitment. In: Proceedings of the Fifth Western States and Provinces Deer and Elk Workshop – 2003 : Jackson, Wyoming, ed., S. A. Tessmann. Wyoming Chapter of The Wildlife Society. p.31 (abstract) BROWNING, S. R., G. L. MASON, T. SEWARD, M. GREEN, G. A. J. ELIASON, C. MATHIASON, M. W. MILLER, E. S. WILLIAMS, E. HOOVER, AND G. C. TELLING. 2005. Transmission of prions from mule deer and elk with chronic wasting disease to transgenic mice expressing cervid PrP. Journal of Virology 78(23):13345-13350 CARPENTER, L. H. 2004. Non-government organizations and deer and elk management : a changing role? In: Proceedings of the Fifth Western States and Provinces Deer and Elk Workshop – 2003 : Jackson, Wyoming, ed., S. A. Tessmann. Wyoming Chapter of The Wildlife Society. p.102 (abstract) COLORADO DIVISION OF WILDLIFE. [2004]. Bighorn sheep & mountain goats : Colorado’s mountain monarchs. [Denver, CO] : Colo. Div. of Wildl. Watchable Wildlife. u.p. ________. [2004]. Colorado Division of Wildlife : 2003 annual report. [Denver, CO : Colo. Div. of Wildl.] u.p. ________. [2005]. Colorado Division of Wildlife : 2004 annual report. [Denver, CO : Colo. Div. of Wildl.] u.p. ________. 2004. 2004 fish distribution schedule. [Denver, CO] : Colo. Dept. of Natural Resources. Div. of Wildl. 37pp. ________. [2005]. 2004 fish / egg distribution. [Denver, CO] : Colo. Dept. of Natural Resources. Div. of Wildl. 54pp.+ ________. [2004]. 2004 hunting guide. [Denver, CO] : Colo. Div. of Wildl. Special edition of Colorado Outdoors. 40pp. 137 �________. 2004. 2004 state trust lands. Denver, CO : Colo. Div. of Wildl. 38pp. ________.AND COLORADO GRASSLAND SPECIES WORKING GROUP. 2003. Conservation plan for grassland species in Colorado. [Denver, CO] : Colo. Div. of Wildl. var. pagination CONNER, M. M., AND M. W. MILLER. 2004. Movement patterns and spatial epidemiology of a prion disease in mule deer population units. Ecological Applications 14(6):1870-1881. DREITZ, V. J., W. M. KITCHENS, AND D. L. DEANGELIS. 2004. Effects of natal departure and water level on survival of juvenile snail kites (Rostrhamus sociabilis) in Florida. Auk 121 (3):894-903 CRAIG, G. R. AND J. H. ENDERSON. 2004. Peregrine falcon biology and management in Colorado : 1973 - 2001. Fort Collins, CO : Colo. Div. of Wildl. Technical publication; no. 43. 80pp. ________, G. C. WHITE, AND J. H. ENDERSON. 2004. Survival, recruitment, and rate of population change of the peregrine falcon population in Colorado. Journal of wildlife Management 68(4):1032-1038 FARNSWORTH, M. L., L. L. WOLFE, N.T. HOBBS, K. P. BURNHAM, E. S. WILLIAMS, D. M. THEOBALD, M. M. CONNER, AND M. W. MILLER. 2005. Human land use influences chronic wasting disease prevalence in mule deer. Ecological Applications 15(1):119-126 FLOHRS, A. T. 2004. The `otter spotter’ handbook : a manual for Colorado Division of Wildlife’s volunteer river otter surveys. [Fort Collins, CO : Colo. Div. of Wildl.] 41pp. FREDDY, D. J., G. C. WHITE, M. C. KNEELAND, V. K. GRAHAM, W. J. DEVERGIE, J. H. ELLENBERGER, J. W. UNSWORTH, C. H. WAGNER, P. M. SCHNURR, AND V. W. HOWARD, JR. [2004]. Estimating mule deer population size using Colorado quadrat system corrected for Idaho mule deer sightability : a sportsmen’s issue. In: Proceedings of the Western States & Provinces Deer and Elk Workshop : Wilsonville, Oregon : August 1-3, 2001, ed., J. A. Mortenson, et al. Oregon Dept. of Fish and Wildlife. p.71 (abstract) ________, ________, ________, R. H. KAHN, J. W. UNSWORTH, W. J. DEVERGIE, V. K. GRAHAM, J. H. ELLENBERGER, AND C. H WAGNER. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32(3):916-927 GARROTT, R. A., J. A. GUDE, AND E. J. BERGMAN. [2004]. Demographic impacts of wolves on two wintering elk populations. In: Proceedings of the Fifth Western States and Provinces Deer and Elk Workshop – 2003 : Jackson, Wyoming, ed. by S. A. Tessmann. Wyoming Chapter of The Wildlife Society. p.91 (abstract) GORMAN, E., D. BROWNNE, AND M. GALLAGHER. 2004. 2004 Colorado walk-in access program atlas. Denver, CO : Colo. Div. of Wildl. u.p. HAGEN, C. A., B. E. JAMISON, K. M. GIESEN, AND T. Z. RILEY. 2004. Guidelines for managing lesser prairie-chicken populations and their habitats. Wildlife Society Bulletin 32(1):69-82 JUNGWIRTH, T. 2004. Report on the status and conservation of the boreal toad : Bufo boreas boreas : in the southern Rocky Mountains : 2003. Denver, CO : Colo. Div. of Wildl. 60pp. LUKACS, P. M., V. J. DREITZ, F. L. KNOPF, AND K. P. BURNHAM. 2004. Estimating survival probabilities of unmarked dependent young when detection is imperfect. Condor 106:926-931 MANFREDO, J. J., P. J. FIX, T. L. TEEL, J. SMELTZER, AND R. KAHN. 2004. Assessing demand for biggame hunting opportunities : applying the multiple-satisfaction concept. Wildlife Society Bulletin 32(4):1147-1155 MILLER, M. W. AND M. A. WILD. 2004. Epidemiology of chronic wasting disease in captive white-tailed and mule deer. Journal of Wildlife Diseases 40(2):330-327 ________ , E. S. WILLIAMS, N. T. HOBBS, AND L. L. WOLFE. 2004. Environmental sources of prion transmission in mule deer. Emerging Infectious Diseases 10(6):1003-1006 PHILLIPS, G. E, A. W. ALLDREDGE, AND W. W. ANDREE. 2004. Mitigating disturbance of migrating mule deer caused by cyclists and pedestrians at a highway underpass near Vail, Colorado. In: Proceedings of the Fifth Western States and Provinces Deer and Elk Workshop – 2003 : Jackson, Wyoming, ed., S. A. Tessmann. Wyoming Chapter of The Wildlife Society. p.131-132 (abstract) 138 �POJAR, T. M. 2004. Survey methods to estimate population. In: Pronghorn ecology and management. eds., B. W. O’Gara and J. D. Yoakum. Boulder, CO : University Press of Colorado. A Wildlife Management Institute book. pp.631-644 ________ AND D. C. BOWDEN. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68(3):550-560 ROCKE, T. E., J. MENCHER, S. R. SMITH, A. M. FRIEDLANDER, G. P. ANDREWS, AND L. A. BAETEN. 2004. Recombinant F1-V fusion protein protects black-footed ferrets (Mustela nigripes) against virulent Yersinia pestis infection. Journal of Zoo and Wildlife Medicine 35(2):142-146 SNYDER, D. E. AND R. T. MUTH. 2004. Catostomid fish larvae and early juveniles of the Upper Colorado River Basin – morphological descriptions, comparisons, and computer-interactive key. Fort Collins, CO : Colo. Div. of Wildl. Technical publication; no. 42. 110pp. WAGNER, C. H., B. E. WATKINS, J. VAYHINGER, AND S. STEINERT. [2004]. Summary of mule deer survival studies in Colorado 1997 – 2001. In: Proceedings of the Western States & Provinces Deer and Elk Workshop : Wilsonville, Oregon : August 1-3, 2001, ed., J. A. Mortenson, et al. Oregon Dept. of Fish and Wildlife. p.81 (abstract) WALSH, D. P., G. C. WHITE, T. E. REMINGTON, AND D. C. BOWDEN. 2004. Evaluation of the lek-count index for greater sage-grouse. Wildlife Society Bulletin 32(1):56-68 WATKINS, B. E., J. H. OLTERMAN, AND T. M. POJAR. [2004]. Mule deer survival studies on the Uncompahgre Plateau, Colorado 1997-2001. In: Proceedings of the Western States & Provinces Deer and Elk Workshop : Wilsonville, Oregon : August 1-3, 2001, ed., J. A. Mortenson, et al. Oregon Dept. of Fish and Wildlife. p.78 (abstract) WINWARD, A. H. 2004. Sagebrush of Colorado : taxonomy, distribution, ecology & management. Denver, CO : Colo. Div. of Wildl. 42pp. WITMER, G., M. BRENNAN, D. DEES, B. HOFFMANN, F. PUSATERI, C. RICHARDSON, AND D. SEERY. 2003. Black-tailed prairie dog management in urban-suburban settings : opportunities and challenges. Transactions of the North American Wildlife and Natural Resources Conference 68:209-221 WOLFE, L. L., W. R. LANCE, AND M. W. MILLER. 2004. Immobilization of mule deer with thiafentanil (A-3080) or thiafentanil plus xylazine. Journal of Wildlife Diseases 40(2):282-287 ________, M. W. MILLER, AND E. S. WILLIAMS. 2004. Feasibility of “test and cull” for managing chronic wasting disease in urban mule deer populations. Wildlife Society Bulletin 32(2):500-505 Prepared by ___________________________ Jacqueline A. Boss, Librarian 139 � https://cpw.cvlcollections.org/files/original/fd42a83972d279e50d778e7da81db0eb.pdf 209513bc163cedd1dca0057c40dba0f6 PDF Text Text MAMMALS - JULY 2006 ��WILDLIFE RESEARCH REPORTS JULY 2005 – JUNE 2006 MAMMALS PROGRAM COLORADO DIVISION OF WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author. i �STATE OF COLORADO Bill Owens, Governor DEPARTMENT OF NATURAL RESOURCES Russell George, Executive Director WILDLIFE COMMISSION Jeffrey Crawford, Chair …………………………………………………………………….…..… Denver Tom Burke, Vice Chair ………………………………….…………...………….…........…Grand Junction Ken Torres, Secretary ……………………………………...…………….……………..……….... Weston Robert Bray………………………………………………….......................................................…Redvale Rick Enstrom………………………………………………………………….………….……...Lakewood Philip James …………………………………………………………………..….………….…Fort Collins Claire M. O’Neal………………………………………………..…………….………..…………..Holyoke Richard Ray ………………………………………………………………………………...Pagosa Springs Robert T. Shoemaker…………………………………………………………….………..…….Canon City Don Ament, Dept. of Ag, Ex-officio…………………………………………………….…….....Lakewood Russell George, Executive Director, Ex-officio……………………………………………..………Denver DIRECTOR’S STAFF Bruce McCloskey, Director Mark Konishi, Deputy Director-Education and Public Affairs Steve Cassin, Chief Financial Officer Jeff Ver Steeg, Assistant Director-Wildlife Programs John Bredehoft, Assistant Director-Field Operations Marilyn Salazar, Assistant Director-Support Services MAMMALS RESEARCH STAFF David Freddy, Mammals Research Leader Eric Bergman, Wildlife Researcher Chad Bishop, Wildlife Researcher Ken Logan, Wildlife Researcher Tanya Shenk, Wildlife Researcher Jackie Boss, Librarian Margie Michaels, Program Assistant ii �Colorado Division of Wildlife July 2005 – June 2006 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS LYNX CONSERVATION WP 0670 POST-RELEASE MONITORING OF LYNX REINTRODUCED TO COLORADO by T. Shenk………………………………………………………………………….…….1 DEER CONSERVATION WP 3001 PROGRAM FINAL REPORT DEER CONSERVATION RESEARCH FOR 5-YEAR FEDERAL AID GRANT W-185-R, JULY 2001-JUNE 2006 by D. Freddy..……...…..47 WP 3001 EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES by C. Bishop………..…………...59 WP 3001 EVALUATIONOF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITIONOF MULE DEER by E. Bergman…………………………………………………………………………...67 WP 3001 MULTISPECIES INVESTIGATIONS CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSIS by G. White………………………………………91 PREDATORY MAMMALS CONSERVATION WP 3003 PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU by K. Logan………………….……………………….95 SUPPORT SERVICES WP 7210 LIBRARY SERVICES by J. Boss…………………..…………………………………123 iii �iv �Colorado Division of Wildlife July 2005 - June 2006 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 0670 1 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Lynx Conservation : Post-Release Monitoring of Lynx Reintroduced to Colorado : Period Covered: July 1, 2005 - June 30, 2006 Author: T. M. Shenk Personnel: L. Baeten, B. Diamond, R. Dickman, D. Freddy, L. Gepfert, J. Ivan, R. Kahn, A. Keith, G. Merrill, T. Spraker, S. Wait, S. Waters, L. Wolfe, D. Younkin All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to establish a viable population of lynx (Lynx canadensis) in Colorado, the Colorado Division of Wildlife (CDOW) initiated a reintroduction effort in 1997 with the first lynx released in February 1999. From 1999-2005, 204 lynx were released in Colorado. Fourteen additional animals (8 males: 6 females) were released in spring 2006 resulting in a total of 218 lynx reintroduced to southwestern Colorado. We documented survival, movement patterns, reproduction, and habitat-use through aerial (n = 8680) and satellite (n = 18, 963) tracking. Most lynx remained near the core release area in southwestern Colorado. From 1999-2006, there were 80 mortalities of released adult lynx. Approximately 31.3% were human-induced which were attributed to collisions with vehicles or gunshot. Malnutrition and disease/illness accounted for 21.3% of the deaths while 32.5% of the deaths were from unknown causes. Reproductive females had the smallest 90% utilization distribution home ranges ( x = 75.2 km2, SE = 15.9 km2 ), followed by attending males ( x = 102.5 km2, SE = 39.7 km2) and nonreproductive animals ( x = 653.8 km2, SE = 145.4 km2). Reproduction was first documented in 2003 with subsequent successful reproduction in 2004 and 2005. Four dens with 11 kittens were found in 2006. Lynx CO04F07, a female lynx born in Colorado in 2004 was the mother of one of these litters which documented the first recruitment of Colorado-born lynx into the Colorado breeding population. From snow-tracking, the primary winter prey species (n = 426) were snowshoe hare (Lepus americanus, annual x = 75.1%, SE = 5.17) and red squirrel (Tamiasciurus hudsonicus, annual x = 15.3%, SE = 3.09); other mammals and birds formed a minor part of the winter diet. Mature Engelmann spruce (Picea engelmannii)-subalpine fir (Abies lasiocarpa) forest stands with 42-65% canopy cover and 15-20% conifer understory cover were the most commonly used areas in southwestern Colorado. Little difference in aspect (slight preference for north-facing slopes), slope ( x = 15.7°) or elevation ( x = 3173 m) were detected for long beds, travel and kill sites (n = 1841). Den sites (n = 37) however, were located at higher 1 �elevations ( x = 3354 m, SE = 31 m) on steeper ( x = 30°, SE = 2°) and more commonly north-facing slopes with a dense understory of coarse woody debris. A study to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands was initiated in 2005 and will continue through 2009. Results to date have demonstrated that CDOW has developed release protocols that ensure high initial post-release survival followed by high long-term survival, site fidelity, reproduction and recruitment of Colorado-born lynx into the Colorado breeding population. What is yet to be demonstrated is whether Colorado can support sufficient recruitment to offset annual mortality for a viable lynx population over time. Monitoring continues in an effort to document such viability. 2 �WILDLIFE RESEARCH REPORT POST RELEASE MONITORING OF LYNX (LYNX CANADENSIS) REINTRODUCED TO COLORADO TANYA M. SHENK P. N. OBJECTIVE The initial post-release monitoring of lynx reintroduced into Colorado will emphasize 5 primary objectives: 1. Assess and modify release protocols to ensure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival of lynx reintroduced to Colorado. 5. Estimate reproduction of lynx reintroduced to Colorado. Three additional objectives will be emphasized after lynx display site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of lynx conservation strategies in the southern Rocky Mountains. SEGMENT OBJECTIVES 1. Release additional adult lynx captured in Canada in southwestern Colorado during spring 2006. 2. Complete winter 2005-06 field data collection on lynx habitat use, hunting behavior, diet, mortalities, and movement patterns. 3. Complete winter 2005-06 lynx trapping field season to collar Colorado born lynx and re-collar adult lynx. 4. Complete spring 2006 field data on lynx reproduction. 5. Summarize and analyze data and publish information as Progress Reports, peer-reviewed manuscripts for appropriate scientific journals, or CDOW technical publications. 6. Complete a study plan to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands. INTRODUCTION The Canada lynx occurs throughout the boreal forests of northern North America. Colorado represents the southern-most historical distribution of lynx, where the species occupied the higher elevation, montane forests in the state. Little was known about the population dynamics or habitat use of this species in their southern distribution. Lynx were extirpated or reduced to a few animals in the state by the late 1970’s due, most likely, to predator control efforts such as poisoning and trapping. Given the isolation of Colorado to the nearest northern populations, the CDOW considered reintroduction as the only option to attempt to reestablish the species in the state. 3 �A reintroduction effort was begun in 1997, with the first lynx released in Colorado in 1999. To date, 218 wild-caught lynx from Alaska and Canada have been released in southwestern Colorado. The goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of lynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing if the reintroduction effort is progressing towards success. There are 7 critical criteria for achieving a viable population: 1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, 2) long-term survival of lynx in Colorado, 3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, 4) reintroduced lynx must breed, 5) breeding must lead to reproduction of surviving kittens 6) lynx born in Colorado must reach breeding age and reproduce successfully, and 7) recruitment must equal or be greater than mortality over an extended period of time. The post-release monitoring program for the reintroduced lynx has 2 primary goals. The first goal is to determine how many lynx remain in Colorado and their locations relative to each other. Given this information and knowing the sex of each individual, we can assess whether these lynx can form a breeding core from which a viable population might be established. From these data we can also describe general movement patterns and habitat use. The second primary goal of the monitoring program is to estimate survival of the reintroduced lynx and, where possible, determine causes of mortality for reintroduced lynx. Such information will help in assessing and modifying release protocols and management of lynx once they have been released to ensure their highest probability of survival. Additional goals of the post-release monitoring program for lynx reintroduced to the southern Rocky Mountains included refining descriptions of habitat use and movement patterns and describing successful hunting habitat once lynx established home ranges that encompassed their preferred habitat. Specific objectives for the site-scale habitat data collection include: 1) describe and quantify site-scale habitat use by lynx reintroduced to Colorado, 2) compare site-scale habitat use among types of sites (e.g., kills vs. long-duration beds), and 3) compare habitat features at successful and unsuccessful snowshoe hare chases. Documenting reproduction is critical to the success of the program and lynx are monitored intensively to document breeding, births, survival and recruitment of lynx born in Colorado. Site-scale habitat descriptions of den sites are also collected and compared to other sites used by lynx. The program will also investigate the ecology of snowshoe hare in Colorado. A study comparing snowshoe hare densities among mature stands of Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), lodgepole pine (Pinus contorta) and Ponderosa pine (Pinus ponderosa) was completed in 2004 with highest hare densities found in Engelmann spruce/subalpine fir stands and no hares found in Ponderosa pine stands. A study to evaluate the importance of young, regenerating lodgepole pine and mature Engelmann spruce/subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each was initiated in 2005 and will continue through 2009. Lynx is listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.)(U. S. Fish and Wildlife Service 2000). Colorado is included in the federal listing as lynx habitat. Thus, an additional objective of the post-release monitoring program is to develop conservation strategies relevant to lynx in Colorado. To develop these conservation strategies, information specific to the ecology of the lynx in its southern Rocky Mountain range, such as habitat use, movement patterns, mortality factors, survival, and reproduction in Colorado is needed. 4 �STUDY AREA Southwestern Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce-subalpine fir is the most widely distributed coniferous forest type at elevations most typically used by lynx. The Core Release Area is defined as areas bounded by the New Mexico state line to the south, Taylor Mesa to the west and Monarch Pass on the north and east and > 2900 m in elevation (Figure 1). The lynx-established core area is roughly bounded by areas used by lynx in the Taylor Park/ Collegiate Peak areas in central Colorado and includes areas of continuous use by lynx, including areas used during breeding and denning (Figure 1). METHODS REINTRODUCTION Effort All 2006 lynx releases were conducted under the protocols found to maximize survival (see Shenk 2001). Estimated age, sex and body condition were ascertained and recorded for each lynx prior to release (see Wild 1999). Specific release sites were those used in earlier years of the project and were selected based on land ownership and accessibility during times of release (Byrne 1998). Lynx were transported from the Frisco Creek Wildlife Rehabilitation Center, where they were held from their time of arrival in Colorado, to their release site in individual cages. Release site location was recorded in Universal Transverse Mercator (UTM) coordinates and identification of all lynx released at the same location, on the same day, was recorded. Behavior of the lynx on release and movement away from the release site were documented. Distribution and Movement Patterns All lynx released in 1999 were fitted with TelonicsTM radio-collars. All lynx released since 1999, with the exception of 5 males released in spring 2000, were fitted with SirtrackTM dual satellite/VHF radio-collars. These collars have a mortality indicator switch that operated on both the satellite and VHF mode. The satellite component of each collar was programmed to be active for 12 hours per week. The 12-hour active periods for individual collars were staggered throughout the week. Signals from the collars allowed for locations of the animals to be made via Argos, NASA, and NOAA satellites. The location information was processed by ServiceArgos and distributed to the CDOW through e-mail messages. To determine general movement patterns of reintroduced lynx, regular locations of released lynx were collected through a combination of aerial, satellite and ground radio-tracking. Locations were recorded in UTM coordinates and general habitat descriptions for each ground and aerial location were recorded. Home Range Annual home ranges were calculated as a 95% utilization distribution using a kernel home-range estimator for each lynx we had at least 30 locations for within a year. A year was defined as March 15 – March 14 of the following year. Locations used in the analyses were collected from September 1999 – January 2006 and all locations obtained for an individual during the first six months after its release were eliminated from any home range analyses as it was assumed movements of lynx initially post-release may not be representative of normal habitat use. Locations were obtained either through aerial VHF surveys or locations or the midpoint (ArcView Movement Extension) of all high quality (accuracy rating of 01km) satellite locations obtained within a single 24-hour period. All locations used within a single home range analysis were taken a minimum of 24 hours apart. 5 �Home range estimates were classified as being for a reproductive or non-reproductive animal. A reproductive female was defined as one that had kittens with her; a reproductive male was defined as a male whose movement patterns overlapped that of a reproductive female. If a litter was lost within the defined year a home range described for a reproductive animal were estimated using only locations obtained while the kittens were still with the female. Survival Survival was estimated as ragged telemetry data using the nest survival models in Program MARK (White and Burnham 1999). Mortality Factors When a mortality signal (75 beats per minute [bpm] vs. 50 bpm for the Telonics™ VHF transmitters, 20 bpm vs. 40 bpm for the Sirtrack™ VHF transmitters, 0 activity for Sirtrack™ PTT) was heard during either satellite, aerial or ground surveys, the location (UTM coordinates) was recorded. Ground crews then located and retrieved the carcass as soon as possible. The immediate area was searched for evidence of other predators and the carcass photographed in place before removal. Additionally, the mortality site was described and habitat associations and exact location were recorded. Any scat found near the dead lynx that appeared to be from the lynx was collected. All carcasses were transported to the Colorado State University Veterinary Teaching Hospital (CSUVTH) for a post mortem exam to 1) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, and 3) archive samples for future reference (research or forensic). The gross necropsy and histology were performed by, or under the lead and direct supervision of a board certified veterinary pathologist. At least one research personnel from the CDOW involved with the lynx program was also present. The protocol followed standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing (see Shenk 1999 for details). Some additional data/samples were routinely collected for research, forensics, and archiving. Other data/samples were collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). From 1999–2004 the CDOW retained all samples and carcass remains with the exception of tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, and other diagnostic samples. Since 2005 carcasses are disposed of at the CSUVTH with the exception of the lower canine, fecal samples, stomach content samples and tissue or bone marrow samples to be delivered by CDOW to the Center for Disease control for plague testing. The lower canine, from all carcasses, is sent to Matson Labs (Missoula, Montana) for aging and the fecal and stomach content samples are evaluated for diet. Reproduction Females were monitored for proximity to males during each breeding season. We defined a possible mating pair as any male and female documented within at least 1 km of each other in breeding season through either flight data or snow-tracking data. Females were then monitored for site fidelity to a given area during each denning period of May and June. Each female that exhibited stationary movement patterns in May or June were closely monitored to locate possible dens. Dens were found when field crews walked in on females that exhibited virtually no movement for at least 10 days from both aerial and ground telemetry. Kittens found at den sites were weighed, sexed and photographed. Each kitten was uniquely marked by inserting a sterile passive integrated transponder (PIT, Biomark, Inc., Boise, Idaho, USA) tag subcutaneously between the shoulder blades. Time spent at the den was minimized to ensure the least amount of disturbance to the female and the kittens. Weight, PIT-tag number, sex and any distinguishing 6 �characteristics of each kitten was also recorded. Beginning in 2005, blood and saliva samples were collected and archived for genetic identification. During the den site visits, den site location was recorded as UTM coordinates. General vegetation characteristics, elevation, weather, field personnel, time at the den, and behavioral responses of the kittens and female were also recorded. Once the females moved the kittens from the natal den area, den sites were visited again and site-specific habitat data were collected (see Habitat Use section below). Captures Captures were attempted for either lynx that were in poor body condition or lynx that needed to have their radio-collars replaced due to failed or failing batteries or to radio-collar kittens born in Colorado once they reached at least 10-months of age when they were nearly adult size. Methods of recapture included 1) trapping using a Tomahawk™ live trap baited with a rabbit and visual and scent lures, 2) calling in and darting lynx using a Dan-Inject CO2 rifle, 3) custom box-traps modified from those designed by other lynx researchers (Kolbe et al. 2003) and 4) hounds trained to pursue felids were also used to tree lynx and then the lynx was darted while treed. Lynx were immobilized either with Telazol (3 mg/kg; modified from Poole et al. 1993 as recommended by M. Wild, DVM) or medetomidine (0.09mg/kg) and ketamine (3 mg/kg; as recommended by L. Wolfe, DVM)) administered intramuscularly (IM) with either an extendible pole-syringe or a pressurized syringe-dart fired from a Dan-Inject air rifle. Immobilized lynx were monitored continuously for decreased respiration or hypothermia. If a lynx exhibited decreased respiration 2mg/kg of Dopram was administered under the tongue; if respiration was severely decreased, the animal was ventilated with a resuscitation bag. If medetomidine/ketamine were the immobilization drugs, the antagonist Atipamezole hydrochloride (Antisedan) was administered. Hypothermic (body temperature < 95o F) animals were warmed with hand warmers and blankets. While immobilized, lynx were fitted with replacement SirtrackTM VHF/satellite collar and blood and hair samples were collected. Once an animal was processed, recovery was expedited by injecting the equivalent amount of the antagonist Antisedan IM as the amount of medetomidine given, if medetomodine/ketemine was used for immobilization. Lynx were then monitored while confined in the box-trap until they were sufficiently recovered to move safely on their own. No antagonist is available for Telezol so lynx anesthetized with this drug were monitored until the animal recovered on its own in the box-trap and then released. If captured and in poor body condition, lynx were anesthetized with either Telezol (2 mg/kg) or medetomodine/ketemine and returned to the Frisco Creek Wildlife Rehabilitation Center for treatment. HABITAT USE Gross habitat use was documented by recording canopy vegetation at aerial locations. More refined descriptions of habitat use by reintroduced lynx were obtained through following lynx tracks in the snow (i.e., snow-tracking) and site-scale habitat data collection conducted at sites found through this method to be used by lynx. Snow-tracking Locations from aerial- and satellite-tracking were used to help ground-trackers locate lynx tracks in snow. Snowmobiles, where permitted, were used to gain the closest possible access to the lynx tracks without disturbing the animal. From that point, the tracking team used snowshoes to access tracks. Once tracks were found, the ground crew back- or forward-tracked the animal if it was far enough away not to be disturbed. Back-tracking generally avoided the possibility of disturbing the lynx by moving away from the animal rather than towards the animal. However, monitoring of the lynx through radio-telemetry was used to assure that the ground crew was staying a sufficient distance away from the lynx in the event the lynx might double back on its tracks. Radio-telemetry was also used in forward-tracking to make sure 7 �the team did not disturb the animal. If it appeared the lynx began to move in response to the observers, the observers stopped following the tracks. If the lynx began to move and the movement did not appear to be a response to the observers, the ground crew continued following the track. An attempt was made in Season 1 (February-May 1999) and Season 2 (December 1999-April 2000) to snow-track each lynx. In Season 3 (December 2000-April 2001), we attempted to snow-track all lynx within the Core Release Area. In tracking Season 4 (December 2001-April 2002), Season 5 (December 2002-April 2003), Season 6 (December 2003-April 2004), Season 7 (December 2004-April 2005) and Season 8 (December 2005-March 2006) we attempted to track all accessible lynx in the Core Release Area and some lynx north of the Core Release Area. Ground crews were instructed to track lynx only where it was safe to travel. Restrictions to safe travel included avalanche danger and extremely rugged terrain. Ground crews worked in pairs and were fully equipped for winter back-country survival. Data Collection For each day of tracking the date, lynx being tracked, slope, aspect, UTM coordinates, elevation, general habitat description, and summary of the days tracking were recorded. Aspect was defined as the direction of 'downhill' or 'fall line' on a slope. This is the direction along the ground in a dihedral angle between the horizontal and the plane of the ground surface. Units were compass degrees. Slope was defined as the dihedral angle between the horizontal and the plane of the ground surface (e.g., 45°). Once a track was located there were 2 types of 'sites' that were encountered. Site I areas needed documentation but either did not reflect areas lynx selected for specific habitat features, or were sites that occurred too frequently to measure each in detail. These sites included the start and end of the track being followed, the location of scat, and short-duration beds defined as being small in size (approximating an area a lynx would crouch), and with little ice formed in the bed indicating little time spent there. Site II areas included areas that might reflect specific habitat features lynx selected for and included locations where the following were found: kills, start of chases, territory marks (e.g., spray sites, buried scat, scat placed on prominent locations), long-duration beds (encompasses an area where a lynx would have lain for an extended period, iced bottom), and road crossing (both sides of road). In addition, habitat plots were conducted along lynx travel routes if no other sites were sampled in the last hour. At each of the 2 types of sites the date, lynx tracked, slope, aspect, forest structure class, UTM coordinates, and elevation were recorded. Forest structure classes included grass/forb, shrub/seedling, sapling/pole, mature, and old growth as defined in Table 1. For Site I areas, the only additional data that was collected was identification of what the site was used for (e.g., short-duration bed), and a brief description of the site. Habitat plots (see below) were conducted at Site II areas. Description of the Habitat Plot The habitat plot consisted of a 12 m x 12 m square defined by a series of 25 points placed in 5 rows of 5 with the center point being on the object that defined the site (e.g., a kill)(Figure 2). Each point was 3 m apart. The 12 m x 12 m sampling square exceeded the minimum requirement of 0.01 ha. recommended by Curtis (1959) for sampling trees. Measurements taken at each of the 25 points included: 1. Snow depth - measured vertically by an avalanche probe marked in cm. 2. Understory - measured from top of snow to 150 cm above snow in a column of 3-cm radius around the avalanche probe. Because understory measurements were influenced by vegetation outside the perimeter of the 25 sampling points (12 m x 12 m) the area used for estimating undersory cover was 15 m by 15 m. At each point, crews recorded all shrubs, trees and coarse woody debris (CWD) that fell within this column and was visible above the snow. Crews also recorded number of branches of each species that fell within the column at 3 different height categories (0-0.5 m, 0.51-1.0 m, 1.01-1.5 m). 8 �3. 4. 5. Overstory: measured at 150 cm above snow with a sighting tube. The tube was made of PVC pipe, with a curved viewing end and a crosshair made of wire on the opposite end. The sighting tube was attached to the avalanche probe used to measure snow depth. Species that hit the crosshair were recorded at each of the 25 points in the vegetation plot. Ganey and Block (1994) found this method of measuring canopy cover (with 20 sample points per plot; Laymon 1988) provided greater precision among observers. Species composition: all the different species of tree or shrub that hit the crosshair of the sighting tube at each of the 25 points were recorded. Tree composition of the vegetation plot was recorded by species and diameter at breast height (DBH). Snow depth was used in conjunction with this recorded DBH to estimate true DBH. Within the 12 m x 12 m square all conifers and deciduous trees were recorded by DBH size class (A = 0-6 in, B = 6.1-12 in, C = 12.1 -18 in, D = 18.1-24 in, E = > 24 in). Area for the tree composition analysis was 12 m x 12 m. Understory was estimated as: 1) percent occurrence within the vegetation plot (number of points with understory/total number of points surveyed) and 2) mean percent occurrence and variance by species and height category over the total points sampled within the vegetation plot. Overstory was estimated as percent occurrence over the vegetation plot (number of points with overstory/total number of points surveyed). DIET AND HUNTING BEHAVIOR Winter diet of reintroduced lynx was estimated by documenting successful kills through snowtracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. Scat samples were collected wherever found and labeled with location and individual lynx identification. Only part of the scat was collected (approximately 75%); the remainder was left in place in the event that the scat was being used by the animal as a territory mark. Site-scale habitat data collected for successful and unsuccessful snowshoe hare kills were compared. SNOWSHOE HARE ECOLOGY A study plan was designed to evaluate the importance of young, regenerating lodgepole pine (Pinus contorta) and mature Engelmann spruce / subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each. Specifically, the study was designed to evaluate small and medium lodgepole pine stands and large spruce/fir stands where the classes “small”, “medium”, and “large” refer to the diameter at breast height (dbh) of overstory trees as defined in the United States Forest Service R2VEG Database (small = 2.54−12.69 cm dbh, medium = 12.70−22.85 cm, and large = 22.86−40.64 cm dbh; J. Varner, United States Forest Service, personal communication). The study design was also developed to identify which of the numerous density-estimation procedures available perform accurately and consistently using an innovative, telemetry augmentation approach as a baseline. Movement patterns and seasonal use of deciduous cover types such as riparian willow will be assessed. Finally, the study was designed to further expound on the relationship between density, demography, and stand type by examining how snowshoe hare density and demographic rates vary with specific vegetation, physical, and landscape characteristics of a stand. 9 �RESULTS REINTRODUCTION Effort From 1999 through 2005 204 lynx were reintroduced into southwestern Colorado. An additional 14 lynx were released in April 2006 (6 females: 8 males), bringing the total number of lynx released in Colorado to 218 (Table 2). Lynx released in 2006 were captured in British Columbia and Yukon. These 14 lynx were released in the Core Release Area of southwestern Colorado at or near previously used release sites in southwestern Colorado. Lynx were released with dual VHF/satellite radio collars so they could be monitored for movement, reproduction and survival. The CDOW does not plan to release any additional lynx in 2007. Distribution and Movement Patterns A total of 8680 aerial VHF locations for all 218 reintroduced lynx have been collected to date (June 30, 2006). An additional 18,963 satellite locations have been collected. Most lynx released in 2006 remained in southwestern Colorado. The majority of surviving lynx from the entire reintroduction effort continue to use high elevation (> 2900 m), forested areas from New Mexico north to Gunnison, west as far as Taylor Mesa and east to Monarch Pass. Most movements away from the Core Release Area were to the north. Numerous travel corridors have been used repeatedly by more than one lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-SilvertonLizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast through the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. Such movement patterns have also been documented by native lynx in Wyoming and Montana (Squires and Laurion 1999). Home Range Reproductive females had the smallest 90% utilization distribution annual home ranges ( x = 75.2 km2, SE = 15.9 km2, n = 19), followed by attending males ( x = 102.5 km2, SE = 39.7 km2, n = 4). Nonreproductive females had the largest annual home ranges ( x = 703.9 km2, SE = 29.8 km2, n = 32) followed by non-reproductive males ( x = 387.0 km2, SE = 73.5 km2, n = 6). Combining all nonreproductive animals yielded a mean annual home range of 653.8 km2 (SE = 145.4 km2, n = 38). Survival Initial survival rate estimates for reintroduced lynx were completed, however, further analyses need to be conducted before estimates will be presented. As of June 30, 2006, CDOW was actively tracking 95 of the 138 lynx still possibly alive. There are 43 lynx that we have not heard signals on since at least June 30, 2005 and these animals are classified as ‘missing’ (Table 3). One of these missing lynx is a mortality of unknown identity, thus only 42 are truly missing. Possible reasons for not locating these missing lynx include 1) long distance dispersal, beyond the areas currently being searched, 2) radio failure, or 3) destruction of the radio (e.g., run over by car). CDOW continues to search for all missing lynx during both aerial and ground searches. Two of the missing lynx released in 2000 are thought to have slipped their collars. Mortality Factors Of the total 218 adult lynx released from 1999-2006 there are 80 known mortalities as of June 30, 2006. Causes of death are listed in Table 4. Starvation was a significant cause of mortality in the first 10 �year of releases only. Mortalities occurred throughout the areas through which lynx moved. Approximately 31.3% were human-induced which were attributed to collisions with vehicles or gunshot. Malnutrition and disease/illness accounted for 21.3% of the deaths while 32.5% of the deaths were from unknown causes (Table 4). Reproduction 2003.-- Nine pairs of lynx were documented during the 2003 breeding season (March and April) from the 17 females we were monitoring. In May and June, 6 dens and a total of 16 kittens were found in the lynx Core Release Area in southwestern Colorado (Table 5, Figure 1). At all dens the females appeared in excellent condition, as did the kittens. The kittens weighed from 270-500 grams. Lynx kittens weigh approximately 200 grams at birth and do not open their eyes until they are 10-17 days old. The dens were scattered throughout the Core Release Area, with no dens found outside the core area. All the dens were in Engelmann spruce/subalpine fir forests in areas of extensive downfall. Elevations ranged from 3240-3557 m. Field crews weighed, photographed, PIT-tagged the kittens and took hair samples from the kittens for genetic work in an attempt to confirm paternity. Kittens were processed as quickly as possible (11-32 minutes) to minimize the time the kittens were without their mother. While working with the kittens the females remained nearby, often making themselves visible to the field crews. The females generally continued a low growling vocalization the entire time personnel were at the den. In all cases, the female returned to the den site once field crews left the area. Four of the 6 females that we know had kittens in summer 2003 were still with kittens at the end of April 2004. Two of those females still had 2 kittens with them at that time. Visual observations in February 2004 of one female with 2 kittens indicated all 3 were in good body condition. The mortality of female YK00F16 and her 1 kitten in October 2003 from plague was not due to poor habitat or prey conditions, and thus we might assume she would have raised the 1 kitten to this stage as well. Three probable kitten deaths from female YK00F19 were from 1 litter that most likely failed very early. Through snow-tracking in winter 2003-04 an unknown female (no radio frequency heard in the area of the tracks) we also documented 1-2 additional kittens born spring 2003 and still alive in winter 2004. Of the 16 kittens we found in summer 2003, we documented the following by April 2004: 6 confirmed alive, 7 confirmed dead, and 3 some evidence dead. Although we tried, we were not able to capture any of the 6 surviving kittens to fit them with radio-collars for subsequent monitoring. 2004.-- In Spring 2004, 26 females from the releases in 1999, 2000 and 2003 had active radiocollars. Of these, we documented 18 possible mating pairs of lynx during breeding season. All 4 of the females that had kittens with them through winter 2003-04 bred again spring 2004; 2 with the same male they successfully bred with spring 2003. During May-June 2004 we found 11 dens and a total of 30 kittens (Table 6). At all dens the females appeared in excellent condition, as did the kittens. The kittens weighed from 250-770 grams. Three of the 11 females with kittens were from the 2003 releases (Table 6). Three additional litters were documented after denning season through either observation of a female lynx with kittens or snow-tracking females with kittens that were not one of the 11 females found on dens. From the size of the kittens they would have been born during the normal denning season in May or June. Nine additional kittens were observed from these litters for a total of 39 known kittens born in 2004. Two of these additional litters were documented from direct follow-ups to sighting made by the public and reported to CDOW. Two females that had kittens in 2003 and reared at least part of their litters through March 2004, bred and had kittens again in 2004. Two of the litters documented by direct observation or snow-tracking are from females whose collars were no longer functioning. Seven kittens born in 2004 were captured at approximately 10-months of age and fitted with dual satellite/VHF collars. Six of the 7 were still alive 11 �and being monitored as of June 30, 2006. The cut collar of one kitten CO04M15 was left at the Silverton Post Office on October 25, 2005. We assume this lynx is dead. 2005.-- In spring 2005 we had 40 females from the releases in 1999, 2000, 2003 and 2004 that had active radio-collars. We documented 23 possible mating pairs of lynx during breeding season. During May-June 2005 we visited 16 dens and found a total of 46 kittens (Table 7). At all dens the females appeared in excellent condition, as did the kittens. An additional female (BC03F10) had a den we were not able to get to during May or June due to high water during spring run-off. Female BC03F03 was hit and killed on I-70 on 5/19/2005. She had 2 fetuses in her uterus, so would have contributed to reproduction this year had she lived. We weighed, photographed, PIT-tagged the kittens and recorded sex. We also took blood samples from the kittens for genetic work in an attempt to confirm paternity. While we were working with the kittens the females remained nearby, often remaining visible to us. The females generally continued a low growling vocalization the entire time we were at the den. In all cases, the female returned to the den site once we left the area. All of the 2005 dens were scattered throughout the high elevation areas of Colorado, south of I70. Most of the dens were in Engelmann spruce/subalpine fir forests in areas of extensive downfall. Elevations ranged from 3117-3586 m. We weighed, photographed, and PIT-tagged the kittens, recorded sex and took hair samples from the kittens for genetic work in an attempt to confirm paternity. Four of the females would not leave the den until we reached out to pick up a kitten. While we were working with the kittens the females remained nearby, often remaining visible to us. The females generally continued a low growling vocalization the entire time we were at the den. In all cases, the female returned to the den site once we left the area. One female, YK00F10 has had litters 3 years in a row. In 2003 she had 4 kittens and raised 2 through the winter. In 2004 she had 2 kittens and raised both through the winter, in 2005 she had 4 kittens again. She has had all 3 litters in the same general area and has had the same mate for 3 years. Eight additional females had their second litter in Colorado in 2005. Three females from the 2004 releases had litters in 2005. Year 2005 was the second consecutive year that we had females released the prior spring, find a territory and a mate within a year and produced live young. In reproduction season 2004 we had 3 females released in spring 2003 that also produced live young the next year. Of those 3, 2 successfully raised at least part of their litters through winter 2005. Seven kittens born in 2005 were captured at approximately 10-months of age and fitted with dual satellite/VHF collars. One of the 7 was still alive and being monitored as of June 30, 2006. 2006.--In spring 2006, 42 females were being monitored. We found 4 dens in May and June 2006 with 11 kittens total (Table 8). Lynx CO04F07, a female lynx born in Colorado in 2004, was the mother of one of these litters which documented the first recruitment of Colorado-born lynx into the Colorado breeding population. The percent of tracked females found with litters in 2006 was lower (0.095) than in the 3 previous years (0.413, SE = 0.032, Table 9). However, all demographic and habitat characteristics measured at the 4 dens that were found in 2006 were comparable to all other dens found (Table 9). Mean number of kittens per litter from 2003-2006 was 2.78 (SE = 0.05) and sex ratio of females to males was equal ( x = 1.14, SE = 0.14). 12 �Den Sites.--A total of 37 dens have been found from 2003-2006. All of the dens except one have been scattered throughout the high elevation areas of Colorado, south of I-70. In 2004, 1 den was found in southeastern Wyoming, near the Colorado border. Dens were located on steep ( x slope = 30o , SE=2o), north-facing, high elevation ( x = 3354 m, SE = 31 m) slopes (Figure 3). The dens were typically in Engelmann spruce/subalpine fir forests in areas of extensive downfall of coarse woody debris (Figures 4, 5, 6). All dens were located within the winter use areas used by the females. Captures Two adult lynx were captured in 2001 for collar replacement. One lynx was captured in a tomahawk live-trap, the other was treed by hounds and then anesthetized using a jab pole. Five adult lynx were captured in 2002; 3 were treed by hounds and 2 were captured in padded leghold traps. In 2004, 1 lynx was captured with a Belisle snare and 6 other adult lynx were captured in box-traps. Trapping effort was substantially increased in winter and spring 2005 and 12 adult lynx were captured and re-collared. Eight reintroduced lynx were captured in winter and spring 2006. All lynx captured in 2005 and 2006 were caught in box-traps. All captured lynx were fitted with new Sirtrack TM dual VHF/satellite collars. Seven adult lynx were captured from March 1999-June 30, 2006 because they were in poor body condition. Five of these lynx were successfully treated at the Frisco Creek Rehabilitation Center and rereleased in the Core Release Area. One lynx, BC00F7, died from starvation and hypothermia. Lynx QU04M07 died on February 5, 2006 at the rehabilitation center. Necropsy results documented starvation as the cause of death that was precipitated by hydrocephalus and bronchopneumonia (unpublished data T. Spraker, CSUVTH). Two lynx were captured because they were in atypical habitat outside the state of Colorado. They were held at Frisco Creek Rehabilitation Center for a minimum of 3 weeks and rereleased in the Core Release Area in Colorado. Prior to release these lynx were fitted with new Sirtrack TM dual VHF/satellite collars. In addition, 14 Colorado-born kittens were captured and collared at approximately 10-months of age. Seven 2004-born kittens were collared in spring 2005, and 7 2005-born kittens collared in spring 2006. HABITAT USE Landscape-scale daytime habitat use was documented from 7421 aerial locations of lynx collected from February 1999-June 30, 2005. Throughout the year Engelmann spruce / subalpine fir was the dominant cover used by lynx. A mix of Engelmann spruce, subalpine fir and aspen (Populus tremuloides) was the second most common cover type used throughout the year. Various riparian and riparian-mix areas were the third most common cover type where lynx were found during the daytime flights. Use of Engelmann spruce-subalpine fir forests and Engelmann spruce-subalpine fir-aspen forests was similar throughout the year. There was a trend in increased use of riparian areas beginning in July, peaking in November, and dropping off December through June. Site-scale habitat data collected from snow-tracking efforts indicate Engelmann spruce and subalpine fir were also the most common forest stands used by lynx for all activities during winter in southwestern Colorado. Comparisons were made among sites used for long beds, dens, travel and where they made kills. Little difference in aspect, mean slope and mean elevation were detected for 3 of the 4 site types including long beds, travel and kills where lynx typically use gentler slopes ( x = 15.7o ) at an mean elevation of 3173 m, and varying aspects with a slight preference for north-facing slopes (Figure 3). Mean percent total overstory was higher for long bed and kill sites than travel or den sites (Figure 4). Engelmann spruce provided a mean of 35.87% overstory for kills and long beds, with travel sites averaging 28% and den sites having the lowest mean percent overstory of 23% (Figure 4). Mean percent 13 �subalpine fir or aspen overstory did not vary across use sites (Figure 4). Willow overstory was highly variable and no dens were located in willow overstory. A total of 1841 site-scale habitat plots were completed in winter from December 2002 through April 2005. The most common understory species at all 3 height categories above the snow (low = 00.5m, medium = 0.51 - 1.0 m, high = 1.1 - 1.5 m) was Engelmann spruce, subalpine fir, willow (Salix spp.) and aspen (Figure 5). Various other species such as Ponderosa pine (Pinus ponderosa), lodgepole pine (Pinus contorta), cottonwood (Populus sargentii), birch (Betula spp.) and others were also found in less than 5% of the habitat plots. If present, willow provided the greatest percent cover within a plot followed by Engelmann spruce, subalpine fir, aspen and coarse woody debris for long beds, kills and travel sites. Areas documented in willow used by lynx are typically on the edge of willow thickets as tracks are quickly lost within the thicket. Den sites had significantly higher percent understory cover for all three height categories. Understory at den sites was primarily made up of coarse woody debris (Figure 5). The most common tree species documented in the site-scale habitat plots was Engelmann spruce Figure 6). Subalpine fir and aspen were also present in >35% of the plots. Most habitat plots were vegetated with trees of DBH < 6" (Figure 6). As DBH increased, percent occurrence decreased within the plot. Although decreasing in abundance as size increased, most lynx use sites had trees in each of the DBH categories, indicating mature forest stands except for dens. Den sites had a broad spectrum of Engelmann spruce tree sizes, including > 18” but no large subalpine fir or aspen trees. While Engelmann spruce and subalpine fir occurred in similar densities for kills, long beds and travel sites, den sites had twice the density of subalpine firs found at all other sites (Figure 6). DIET AND HUNTING BEHAVIOR Winter diet of lynx was documented through detection of kills found through snow-tracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. A total of 400 kills were located from February 1999-April 2005. We collected 671 scat samples from February 1999-April 2004 that will be analyzed for content. In each winter, the most common prey item was snowshoe hare, followed by red squirrel (Table 10). A comparison of percent overstory for successful and unsuccessful snowshoe hare chases indicated lynx were more successful at sites with slightly higher percent overstory, if the overstory species were Englemann spruce, subalpine fir or willow. Lynx were slightly less successful in areas of greater aspen overstory (Figure 7). This trend was repeated for percent understory at all 3 height categories (Figure 8) except that higher aspen understory improved hunting success. Higher density of Engelmann spruce and subalpine fir increased hunting success while increased aspen density decreased hunting success (Figure 9). SNOWSHOE HARE ECOLOGY A study plan was completed to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands (Appendix I). DISCUSSION In an effort to establish a viable population of lynx in Colorado, CDOW initiated a reintroduction effort in 1997 with the first lynx released in winter 1999. From 1999 through spring 2005, 204 lynx were 14 �released in the Core Release Area. The reintroduction effort was augmented with the release of 14 additional animals in April 2006, bringing the total to 218 lynx reintroduced to southwestern Colorado. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns and to detect mortalities. Most lynx remain in the high elevation, forested areas in southwestern Colorado. Dispersal movement patterns for lynx released in 2000 and subsequent years were similar to those of lynx released in 1999. However, more animals released in 2000 and subsequent years remained within the Core Release Area than those released in 1999. This increased site fidelity may have been due to the presence of con-specifics in the area on release. Numerous travel corridors have been used repeatedly by more than 1 lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-Silverton-Lizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast to the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. Most lynx currently being tracked are within the Core Release Area. During the summer months, lynx were documented to make extensive movements away from their winter use areas. Extensive summer movements away from areas used throughout the rest of the year have been documented in native lynx in Wyoming and Montana (Squires and Laurion 1999). Humancaused mortality factors such as gunshot and vehicle collision are currently the highest causes of death. Reproduction is critical to achieving a self-sustaining viable population of lynx in Colorado. Reproduction was first documented from the 2003 reproduction season and again in 2004, 2005 and 2006. Reproduction in 2006 included a Colorado-born female giving birth to 2 kittens, documenting the first recruitment of Colorado-born lynx into the Colorado breeding population. Additional reproduction is likely to have occurred in all years from females we are no longer tracking, and from Colorado-born lynx that have not been collared. The dens we find are more representative of the minimum number of litters and kittens in a reproduction season. To achieve a viable population of lynx, enough kittens need to be recruited into the population to offset the mortality that occurs in that year and hopefully even exceed the mortality rate for an increasing population. Mowat et al. (1999) suggest lynx and snowshoe hare select similar habitats except that hares select more dense stands than lynx. Very dense understory limits hunting success of the lynx and provides refugia for hares. Given the high proportion of snowshoe hare in the lynx diet in Colorado, we might then assume the habitats used by reintroduced lynx also depict areas where snowshoes hare are abundant and available for capture by lynx in Colorado. From both aerial locations taken throughout the year and from the site-scale habitat data collected in winter, the most common areas used by lynx are in stands of Engelmann spruce and subalpine fir. This is in contrast to adjacent areas of Ponderosa pine, pinyon juniper, aspen and oakbrush. The lack of lodgepole pine in the areas used by the lynx may be more reflective of the limited amount of lodgepole pine in southwestern Colorado, the Core Release Area, rather than avoidance of this tree species. Hodges (1999) summarized habitats used by snowshoe hare from 15 studies as areas of dense understory cover from shrubs, stands that are densely stocked, and stands at ages where branches have more lateral cover. Species composition and stand age appears to be less correlated with hare habitat use than is understory structure (Hodges 1999). The stands need to be old enough to provide dense cover and browse for the hares and cover for the lynx. In winter, the cover/browse needs to be tall enough to still provide browse and cover in average snow depths. Hares also use riparian areas and mature forests with understory. Site-scale habitat use documented for lynx in Colorado indicate lynx are most commonly using areas with Engelmann spruce understory present from the snow line to at least 1.5 m above the snow. The mean percent understory cover within the habitat plots is typically less than 15% regardless of understory species. However, if the understory species is willow, percent understory cover is typically 15 �double that, with mean number of shrubs per plot approximately 80, far greater than for any other understory species. In winter, hares browse on small diameter woody stems (<0.25"), bark and needles. In summer, hares shift their diet to include forbs, grasses, and other succulents as well as continuing to browse on woody stems. This shift in diet may express itself in seasonal shifts in habitat use, using more or denser coniferous cover in winter than in summer. The increased use of riparian areas by lynx in Colorado from July to November may reflect a seasonal shift in hare habitat use in Colorado. Major (1989) suggested lynx hunted the edge of dense riparian willow stands. The use of these edge habitats may allow lynx to hunt hares that live in habitats normally too dense to hunt effectively. The use of riparian areas and riparian-Engelmann spruce-subalpine fir and riparian-aspen mixes documented in Colorado may stem from a similar hunting strategy. However, too little is known about habitat use by hares in Colorado to test this hypothesis at this time. Lynx also require sufficient denning habitat. Denning habitat has been described by Koehler (1990) and Mowat et al. (1999) as areas having dense downed trees, roots, or dense live vegetation. We found this to be in true in Colorado as well. In addition, the dens used by reintroduced lynx were at high elevations and on steep north-facing slopes. All females that were documented with kittens denned in areas within their winter-use area. Snow-tracking of released lynx provided information on hunting behavior and diet through documentation of kills, food caches, chases, and diet composition estimated through prey remains. Snowtracking results indicate the primary winter prey species are snowshoe hare and red squirrel, with other mammals and birds forming a minor part of the winter diet. In winter, lynx reintroduced to Colorado appear to be feeding on their preferred prey species, snowshoe hare and red squirrel in similar proportions as those reported for northern lynx during lows in the snowshoe hare cycle (Aubry et al., 1999). Caution must be used in interpreting the proportion of identified kills. Such a proportion ignores other food items that are consumed in their entirety and thus are biased towards larger prey and may not accurately represent the proportion of smaller prey items, such as microtines, in lynx winter diet. Through snowtracking we have evidence that lynx are mousing and several of the fresh carcasses have yielded small mammals in the gut on necropsy. The summer diet of lynx has been documented to include less snowshoe hare and more alternative prey than in winter (Mowat et al., 1999). All evidence suggests reintroduced lynx are finding adequate food resources. SUMMARY From results to date it can be concluded that CDOW has developed release protocols that ensure high initial post-release survival, and on an individual level lynx have demonstrated they can survive long-term in areas of Colorado. It has also been documented that reintroduced lynx could exhibit site fidelity, engage in breeding behavior and produce kittens that are recruited into the Colorado breeding population. What is yet to be demonstrated is whether current conditions in Colorado can support the recruitment necessary to offset annual mortality for a population to sustain itself. Monitoring of reintroduced lynx will continue in an effort to document such viability. ACKNOWLEDGEMENTS The lynx reintroduction program involves the efforts of literally hundreds of people across North America, in Canada and the U. S. Any attempt to properly acknowledge all the people who played a role in this effort is at risk of missing many people. The following list should be considered to be incomplete. 16 �CDOW CLAWS Team (1998-2001): Bill Andree, Tom Beck, Gene Byrne, Bruce Gill, Mike Grode, Rick Kahn (Program Leader), Dave Kenvin, Todd Malmsbury, Jim Olterman, Dale Reed, John Seidel, Scott Wait, Margaret Wild. CDOW: John Mumma (Director 1996-2000), Bruce McCloskey (Director 2001-present), Conrad Albert, Jerry Apker, Laurie Baeten, Cary Carron, Don Crane, Larry DeClaire, Phil Ehrlich, Lee Flores, Delana Friedrich, Dave Gallegos, Juanita Garcia, Drayton Harrison, Jon Kindler, Ann Mangusso, Jerrie McKee, Melody Miller, Mike Miller, Kirk Navo, Robin Olterman, Jerry Pacheo, Mike Reid, Ellen Salem, Eric Schaller, Mike Sherman, Jennie Slater, Steve Steinert, Kip Stransky, Suzanne Tracey, Anne Trainor, Brad Weinmeister, Nancy Wild, Perry Will, Lisa Wolfe, Brent Woodward, Kelly Woods, Kevin Wright. Lynx Advisory Team (1998-2001): Steve Buskirk, Jeff Copeland, Dave Kenny, John Krebs, Brian Miller (Co-leader), Mike Phillips, Kim Poole, Rich Reading (Co-leader), Rob Ramey, John Weaver. U. S. Forest Service: Kit Buell, Joan Friedlander, Dale Gomez, Jerry Mastel, John Squires, Fred Wahl, Nancy Warren. U. S. Fish and Wildlife Service: Lee Carlson, Gary Patton (1998-2000), Kurt Broderdorp. State Agencies: Gary Koehler (Washington). National Park Service: Steve King. Colorado State University: Alan B. Franklin, Gary C. White. Colorado Natural Heritage Program: Rob Schorr, Mike Wunder. Alaska: ADF&G: Cathie Harms, Mark Mcnay, Dan Reed (Regional Manager), Wayne Reglin (Director), Ken Taylor (Assist. Director), Ken Whitten, Randy Zarnke, Other:Ron Perkins (trapper), Dr. Cort Zachel (veterinarian). British Columbia: Dr. Gary Armstrong (veterinarian), Mike Badry (government), Paul Blackwell (trapper coordinator), Trappers: Dennis Brown, Ken Graham, Tom Sbo, Terry Stocks, Ron Teppema, Matt Ounpuu. Yukon: Government: Arthur Hoole (Director), Harvey Jessup, Brian Pelchat, Helen Slama, Trappers: Roger Alfred, Ron Chamber, Raymond Craft, Lance Goodwin, Jerry Kruse, Elizabeth Hofer, Jurg Hofer, Guenther Mueller (YK Trapper’s Association), Ken Reeder, Rene Rivard (Trapper coordinator), Russ Rose, Gilbert Tulk, Dave Young. Alberta: Al Cook. Northwest Territories: Albert Bourque, Robert Mulders (Furbearer Biologist), Doug Steward (Director NWT Renewable Res.), Fort Providence Native People. Quebec: Luc Farrell, Pierre Fornier. Colorado Holding Facility: Herman and Susan Dieterich, Loree Harvey, Rachel Riling. Pilots: Dell Dhabolt, Larry Gepfert, Al Keith, Jim Olterman, Matt Secor, Whitey Wannamaker, Steve Waters, Dave Younkin. Field Crews (1999-2006): Steve Abele, Brandon Barr, Bryce Bateman, Todd Bayless, Nathan Berg, Ryan Besser, Mandi Brandt, Brad Buckley. Patrick Burke, Braden Burkholder, Paula Capece, Stacey Ciancone, Doug Clark, John DePue, Shana Dunkley, Tim Hanks, Dan Haskell, Matt Holmes, Andy Jennings, Susan Johnson, Paul Keenlance, Patrick Kolar, Tony Lavictoire, Clay Miller, Denny Morris, Kieran O’Donovan, Gene Orth, Chris Parmater, Jake Powell, Jeremy Rockweit, Jenny Shrum, Josh Smith, Heather Stricker, Adam Strong, Dave Unger, David Waltz, Andy Wastell, Lyle Willmarth, Leslie Witter, Kei Yasuda, Jennifer Zahratka. Research Associates: Bob Dickman, Grant Merrill. Data Analysts: Karin Eichhoff, Joanne Stewart, Anne Trainor. Data Entry: Charlie Blackburn, Patrick Burke, Rebecca Grote, Angela Hill, Mindy Paulek. Photographs: Tom Beck, Bruce Gill, Mary Lloyd, Rich Reading, Rick Thompson. Funding: CDOW, Great Outdoors Colorado (GOCO), Turner Foundation, U.S.D.A. Forest Service, Vail Associates. LITERATURE CITED AUBRY, K. B., G. M. KOEHLER, J. R. SQUIRES. 1999. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. BYRNE, G. 1998. Core area release site selection and considerations for a Canada lynx reintroduction in Colorado. Report for the Colorado Division of Wildlife. CURTIS, J. T. 1959. The vegetation of Wisconsin. University of Wisconsin Pres, Madison. GANEY, J. L. AND W. M. BLOCK. 1994. A comparison of two techniques for measuring canopy closure. Western Journal of Applied Forestry 9:1: 21-23. 17 �HODGES, K. E. 1999. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. KOEHLER, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. KOLBE, J. A., J. R. SQUIRES, T. W. PARKER. 2003. An effective box trap for capturing lynx. Journal of Wildlife Management 31:980-985. LAYMON, S. A. 1988. The ecology of the spotted owl in the central Sierra Nevada, California. PhD Dissertation University of California, Berkeley, California. MAJOR, A. R. 1989. Lynx, Lynx canadensis canadensis (Kerr) predation patterns and habitat use in the Yukon Territory, Canada. M. S. Thesis, State University of New York, Syracuse. MOWAT, G., K. G. POOLE, AND M. O’DONOGHUE. 1999. Ecology of lynx in northern Canada and Alaska. Pages 265-306 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. POOLE, K. G., G. MOWAT, AND B. G. SLOUGH. 1993. Chemical immobilization of lynx. Wildlife Society Bulletin 21:136-140. SHENK, T. M. 1999. Program narrative: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Report for the Colorado Division of Wildlife. __________. 2001. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. SQUIRES, J. R. AND T. LAURION. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. U. S. FISH AND WILDLIFE SERVICE. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. WHITE, G.C. AND K. P. BURNHAM. 1999. Program MARK: Survival estimation from populations of marked animals. Bird Study 46 Supplement, 120-138. WILD, M. A. 1999. Lynx veterinary services and diagnostics. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. Prepared by _______________________________ Tanya M. Shenk, Wildlife Researcher 18 �Table 1. Definitions of forest structure classes used to describe habitat sites (Thomas 1979). Forest Structure Class Definition Grass/forb The grass/forb stage is created naturally by a catastrophic event, such as wildfire, and is typified by the near complete absence of snags, litter or down material in the aspen and ponderosa pine types, or vice versa in the lodgepole or subalpine forest types. Shrub/seedling The shrub/seedling stage occurs when tree seedlings or shrubs grow up to 2.5 cm at diameter breast height (DBH), either naturally or artificially through planting. Sapling/pole The sapling/pole stage is a young stage where tree DBH's range from 2.517.5 cm with tree heights ranging 1.8-13.5 m. These trees are 5-100 years of age, depending on species and site condition. Mature The mature stage occurs when tree diameters reach a relatively large size (25-50 cm) and the trees are usually 90 or more years old. Forest stands begin to experience accelerated mortality from disease and insects. Old-growth The old-growth stage occurs when a mature stand is at advanced age (100 years for aspen or 200 years for spruce), is very slow growing, and has advanced degrees of disease, insects, snags, and down, dead material. An exception to this occurs in ponderosa pine and aspen types where these old-growth stands typically experience low densities of down dead material or snags. Table 2. Lynx released in Colorado from February 1999 through June 30, 2006. Year Females Males TOTAL 1999 22 19 41 2000 35 20 55 2003 17 16 33 2004 17 20 37 2005 18 20 38 2006 6 8 14 TOTAL 115 103 218 Table 3. Status of adult lynx reintroduced to Colorado as of June 30, 2006. Females Released Known Dead Possible Alive Missing Tracking a 1 is unknown mortality 115 46 69 20 49 Males 103 33 70 24 46 19 Unknown 1 TOTALS 218 80 138 43a 95 �Table 4. Causes of death for lynx released into southwestern Colorado from 1999-2006 as of June30, 2006. Cause of Death Unknown Hit by Vehicle Starvation Shot Other Trauma Probable Shot Plague Predation Probable Predation Illness Total Mortalities Number of Mortalities 26 11 10 9 7 5 5 3 2 2 80 Table 5. Lynx reproduction documented in 2003. Female BC00F8 BC00F19 YK00F16 YK99F1 YK00F19 YK00F10 Release Year 2000 2000 2000 1999 2000 2000 Date Den Found 5/21/03 5/26/03 6/19/03 6/10/03 6/11/03 5/31/03 TOTAL Females ? 1 1 2 1 2 7 Number of Kittens Males ? 1 1 1 2 2 7 Total 2 2 2 3 3 4 16 Table 6. Lynx reproduction documented in 2004. Female ID YK00F2 AK00F2 YK00F1 YK00F15 BC00F14 BC00F18 YK00F10 BC03F02 BC03F10 BC03F09 YK00F7 YK99F1 Unknown Unknown TOTAL Release Year 2000 2000 2000 2000 2000 2000 2000 2003 2003 2003 2000 1999 Previous Litters Date Den Found 5/28/2004 5/31/2004 6/1/2004 6/4/2004 6/7/2004 6/10/2004 6/17/2004 6/25/2004 6/26/2004 6/29/2004 6/30/2004 6/2004 Date Kittens Found Dec 2004 Sept 2004 Feb 2005 20 Number of Kittens Females Males Total 3 1 4 2 1 3 3 3 1 2 3 1 2 3 4 4 1 1 2 2 2 2 2 1 1 2 1 1 2 2 4 3 19 11 39 �Table 7. Lynx reproduction documented in 2005. Female ID AK00F02 YK00F15 YK00F10 YK00F11 YK00F01 YK00F07 BC00F18 BC03F02 BC03F01 QU03F06 QU03F04 QU03F07 BC03F09 BC03F10 BC04F01 BC04F03 BC04F05 BC04F04 TOTAL Release Year 2000 2000 2000 2000 2000 2000 2000 2003 2003 2003 2003 2003 2003 2003 2004 2004 2004 2004 Previous Litters 2004 2004 2003, 2004 2004 2004 2004 2004 2004 2004 Date Den Found 5/21/2005 5/28/2005 6/1/2005 6/9/2005 6/10/2005 6/14/2005 6/24/2005 5/25/2005 5/27/2005 6/5/2005 6/14/2005 6/16/2005 6/27/2005 6/2005 6/11/2005 6/19/2005 6/23/2005 Date Kittens Found 12/20/2005 12/10/2005 Number of Kittens Males Females Total 2 1 3 1 1 2 2 2 4 2 2 2 1 3 1 2 3 1 1 2 1 1 2 2 2 4 3 3 1 2 3 3 1 4 1 1 2 2 2 1 3 1 3 4 3 3 1 1 26 22 50 Table 8. Lynx reproduction in 2006. Female ID AK00F15 AK00F05 BC03F10 CO04F07 TOTAL Release Year 2000 2000 2003 Year Born in Colorado Previous Litters 2004, 2005 2004 2004, 2005 Date Den Found 5/21/2006 6/7/2006 6/9/2006 6/17/2006 2004 Number of Kittens Males Females Total 1 3 4 1 2 3 1 1 2 2 2 5 6 11 Table 9. Lynx reproduction summary statistics for 2003-2006. Additional Litters Found in Winter Mean # Kittens/Litter 16 0.462 2 0.425 1 2.67 (SE = 0.33 2.83 (SE = 0.24) 2.88 (SE = 0.18) 2.75 (SE = 0.47) 2.78 (SE = 0.05) 11 Year # Females Tracked # Dens Found in May/June % Tracked Females with Kittens 2003 17 6 0.353 2004 26 11 2005 40 17 Mean 2003-06 39 50 Sex Ratio M/F 1.0 1.5 0.8 0.413 (SE =0.032) Mean 2003-05 2006 Total Kittens Found 42 4 0.095 0.334 (SE = 0.083) 21 TOTAL 116 1.2 1.14 (SE = 0.14) �Table 10. Number of kills found each winter field season through snow-tracking of lynx and percent composition of kills of the three primary prey species. Field Season 1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 n 9 83 89 54 65 37 78 Snowshoe Hare 55.56 67.47 67.42 90.74 90.77 67.57 83.33 Prey (%) Red Squirrel Cottontail 22.22 0 19.28 1.20 19.10 8.99 5.56 0 6.15 0 27.03 2.70 10.26 0 Other 22.22 12.05 4.49 3.70 3.08 2.70 6.41 Figure 1. Lynx are monitored throughout Colorado and by satellite throughout the western United States. The lynx core release area, where all lynx were released, is located in southwestern Colorado. A lynxestablished core use area has developed in the Taylor Park and Collegiate Peak area in central Colorado. 22 �Figure 2. Design of site-scale habitat plot sampling plot. Each of the 25 points are 3 meters apart (the first 6 points are labeled 1-6). The object that triggered a habitat plot (e.g., kill ) is the center point, depicted by the hollow circle. The actual pints encompass a 12 m x 12 m square but the understory and overstory data collected are influenced by vegetation occurring within a 15 m x 15 m square. Figure 3. Frequency of aspect with mean vector and 95%confidence interval depicted as grey bars on graphs for 4 lynx use sites; dens, long beds, kills and travel as well as mean elevation and SE and mean slope and SE . 23 �Figure 4. Mean percent overstory by tree species Engelmann spruce (ES), subalpine fir (SF), aspen (AS), willow (WI) and total cover for 4 different lynx use sites: long beds, kill sites, travel and den sites. Confidence intervals (95%) are depicted by error bars. Figure 5. Mean percent understory by tree species Engelmann spruce (ES), subalpine fir (SF), coarse woody debris (CWD), aspen (AS), willow (WI), and total cover for 4 different lynx use sites: long beds, kill sites, travel, and den sites. 24 �Figure 6. Mean tree density by species Engelmann spruce (ES), subalpine fir (SF), and aspen (AS) and dbh size class for 4 different lynx use sites. Figure 7. Mean percent overstory by tree species Engelmann spruce (ES), subalpine fir (SF), aspen (AS), willow (WI) and total cover for successful and unsuccessful snowshoe hare chases. Confidence intervals (95%) are depicted by error bars. 25 �Figure 8. Mean percent understory by tree species Engelmann spruce (ES), subalpine fir (SF), apsen (AS), willow (WI), and total cover for 3 different understory height categories for successful and unsuccessful snowshoe hare chases. Confidence intervals (95%) are depicted by error bars. Figure 9. Mean tree density by species Engelmann spruce (ES), subalpine fir (SF), and aspen (AS) and 5 dbh size classes for successful chases (SC) and unsuccessful chases (UC) of snowshoe hares. 26 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2005-06 – FY 2009-10 State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 2 Federal Aid Project No.: : Division of Wildlife : Mammals Research : Lynx Conservation : Density, Demography, and Seasonal Movements of Snowshoe Hare in Colorado N/A : DENSITY, DEMOGRAPHY, AND SEASONAL MOVEMENTS OF SNOWSHOE HARES IN COLORADO Principal Investigators Jacob S. Ivan, Ph. D. Candidate, Colorado State University Tanya M. Shenk, Wildlife Researcher, Mammals Research, Colorado Division of Wildlife Cooperators Gary C. White, Professor, Fishery and Wildlife Biology, Colorado State University STUDY PLAN APPROVAL Prepared by: _____________________________ Date: __________________ Submitted by: ____________________________ Date: ___________________ Reviewed by: ____________________________ Date: ___________________ ____________________________ Date: ___________________ ____________________________ Date: ___________________ Reviewed by: ____________________________ Biometrician Date: ___________________ Approved by: ____________________________ Mammals Research Leader Date: ___________________ 27 �DENSITY, DEMOGRAPHY, AND SEASONAL MOVEMENTS OF SNOWSHOE HARES IN COLORADO NEED A program to reintroduce the threatened Canada lynx (Lynx canadensis) into Colorado was initiated in 1997. Since that time, 204 lynx have been released in the state, and an extensive effort to determine their movements, habitat use, reproductive success, and food habits has ensued (Shenk 2005). Analysis of scat collected from winter snow tracking indicates that snowshoe hares (Lepus americanus) comprise 65–90% of the winter diet of reintroduced lynx (T. Shenk, Colorado Division of Wildlife, unpublished data). Thus, as in the far north where the intimate relationship between lynx and snowshoe hares has captured the attention of ecologists for decades, it appears that the existence of lynx in Colorado and the success of the reintroduction effort may hinge on maintaining adequate and widespread populations of hares. Colorado represents the extreme southern range limit for both lynx and snowshoe hares (Hodges 2000). At this latitude, habitat for each species is less widespread and more fragmented compared to the continuous expanse of boreal forest at the heart of lynx and hare ranges. Neither exhibits dramatic cycles as occur farther north, and typical lynx (≤2−3 lynx/100km2; Aubry et al. 2000) and hare (≤1−2 hares/ha; Hodges 2000) densities in the southern part of their range correspond to cyclic lows form northern populations (2-30 lynx/100 km2, 1−16 hares/ha; Aubry et al. 2000, Hodges 2000, Hodges et al. 2001). Whereas extensive research on lynx-hare ecology has occurred in the boreal forests of Canada, literature regarding the ecology of these species in the southern portion of their range is relatively sparse. This scientific uncertainty is acknowledged in the “Canada Lynx Conservation Assessment and Strategy,” a formal agreement between federal agencies intended to provide a consistent approach to lynx conservation on public lands in the lower 48 states (Ruediger et al. 2000). In fact, one of the explicit guiding principles of this document is to “retain future options…until more conclusive information concerning lynx management is developed.” Thus, management recommendations in this agreement are decidedly conservative, especially with respect to timber management, and are applied broadly to cover all habitats thought to be of possible value to lynx and hare. This has caused controversy where recommendations conflict with competing resource management goals. Accurate identification and detailed description of lynx-hare habitat in the southern Rocky Mountains would permit more informed and refined management recommendations. A commonality throughout the snowshoe hare literature, regardless of geographic location, is that hares are associated with dense understory vegetation that provides both browse and protection from elements and predators (Wolfe et al. 1982, Litvaitis et al. 1985, Hodges 2000, Homyack et al. 2003, Miller 2005). In western mountains, this understory can be provided by relatively young conifer stands regenerating after stand-replacing fires or timber harvest (Sullivan and Sullivan 1988, Koehler 1990, Koehler 1990, Bull et al. 2005) as well as mature, uneven-aged stands (Beauvais 1997, Griffin 2004). Hares may also take advantage of seasonally abundant browse and cover provided by deciduous, open habitats (e.g., riparian willow [Salix spp.], aspen [Populus tremuloides]; Wolff 1980, Miller 2005). In drier portions of hare range, such as Colorado, regenerating stands can be relatively sparse, and hares may be more associated with mesic, late-seral forest and/or riparian areas than with young stands (Ruggiero et al. 2000). Numerous investigators have sought to determine the relative importance of these distinctly different habitat types with regards to snowshoe hare ecology. Most previous evaluations were based on hare density or abundance (Bull et al. 2005), indices to hare density and abundance (Wolfe et al. 1982, Koehler 1990, Beauvais 1997, Miller 2005), survival (Bull et al. 2005), and/or habitat use (Dolbeer and 28 �Clark 1975). Each of these approaches provides insight into hare ecology, but taken singly, none provide a complete picture and may even be misleading. For example, extensive use of a particular habitat type may not accurately reflect the fitness it imparts on individuals, and density can be high even in “sink” habitats (Van Horne 1983). A more informative approach would be to measure density, survival, and habitat use simultaneously in addition to recruitment and population growth rate through time. Griffin (2004) employed such an approach and found that summer hare densities were consistently highest in young, dense stands. However, he also noted that only dense mature stands held as many hares in winter as in summer. Furthermore hare survival seemed to be higher in dense mature stands, and only dense mature stands were predicted (by matrix projection) to impart a mean positive population growth rate on hares. Griffin’s (2004) study occurred in the relatively moist forests of Montana, which share many similarities but also many notable differences with Colorado forests including levels of fragmentation, species composition, elevation, and annual precipitation. Density estimation is a key component in assessing the value of a particular stand type and is the common currency by which hare populations are compared across time and space. However, it can be a difficult metric to estimate accurately. Density estimation based on capture-recapture methods is a welldeveloped field (Otis et al. 1978, White et al. 1982), but is often too costly and labor intensive to be implemented on scales necessary to effectively monitor density over a biologically meaningful area. Also, density can be difficult to assess from grid-trapping efforts because it is often unclear how much area was effectively sampled by the grid (Williams et al. 2002:314). Different approaches can produce density estimates that differ by an order of magnitude even when calculated from the same data (Zahratka 2004). Indices such as pellet plot counts and distance sampling of pellet groups can be used to estimate density, but each of these has limitations as well (Krebs et al. 1987, Eriksson 2006). Pellet plot counts are typically conducted by laying out numerous rectangular or circular plots along transect lines randomly placed within a study site. All pellets occurring within the plot are counted and removed on an annual basis. The mean number of pellets per plot is then inserted into a regression equation that gives an estimate of hare density (Krebs et al. 1987). Estimates from this technique correlate well with density estimates derived from simultaneous mark-recapture studies occurring in the same area (Krebs et al. 2001, Murray et al. 2002, Mills et al. 2005, Homyack et al. 2006). However, because fecal deposition rates can vary by season and diet, and because pellet decomposition rates can vary with altitude, climate, aspect, precipitation, and cover type, region-specific, stand-specific, and/or season-specific equations should be developed before this technique is employed for a given area and season (Krebs et al. 2001, Prugh and Krebs 2004, Murray et al. 2005). Density estimates vary with plot size and shape, requiring equations specific to these geometric considerations as well (McKelvey et al. 2002). Pellet counts tend to yield more precise and unbiased density estimates when plots are visited and cleared more than once per year (e.g., plots cleared in the fall and then counted in the spring to estimate winter density) because variability in deposition and decomposition rates is reduced (Homyack et al. 2006). However, this requires considerably more work and expense than an annual survey. Some studies have conducted pellet plot counts without first clearing plots (e.g., Bartmann and Byrne 2001). This saves time and money, but requires the ability to discern fresh (this year) pellets from old pellets, which can be difficult and is generally not a recommended approach (Prugh and Krebs 2004, Murray et al. 2005). Distance sampling is a well-developed method for estimating the density of objects in a given area (Buckland et al. 2001). In general, observers walk a pre-defined sampling transect and record each object of interest along with the perpendicular distance of that object from the transect line. This information is then used to develop a detection function which is in turn used to estimate density (Buckland et al. 2001). The method assumes all objects on the line are seen with certainty, objects are not double-counted, distance measures are accurate, and transect lines are located randomly within a study area (Buckland et al. 2001). Recently, distance sampling has been used to indirectly estimate hare density 29 �by first estimating the pellet group density of hares, then using fecal deposition and decomposition rates as a link back to hare density (Eriksson 2006). In general, distance sampling is more efficient than pellet plot counts as it does not require the tedious layout of hundreds of plots or counting individual pellets. This advantage is most recognizable in situations where pellet groups occur at low densities. Conversely, at extremely high densities, it may become difficult to distinguish pellet groups, and plots may be preferable (Marques et al. 2001). Regardless, distance sampling of pellet groups to estimate animal density also requires habitat and season specific decomposition and defecation rates, which can be difficult to obtain (Marques et al. 2001). For this project, I have chosen to provide land managers with information relating demographic rates, as well as density, to stand characteristics. Thus, I will use mark-recapture techniques as data from such an approach can provide information on both density and demography. I will address the “effective trapping area” issue using a new approach that augments mark-recapture data with telemetry locations of animals using the grid. The study outlined below is designed principally to evaluate the importance of young, regenerating lodgepole pine (Pinus contorta) and mature Engelmann spruce (Picea engelmannii)/ subalpine fir (Abies lasiocarpa) stands in Colorado by examining density and demography of snowshoe hares that reside in each (Figure 1). My hope is that information gathered from this research will be drawn upon as managers make routine decisions, leading to landscapes that include stands capable of supporting abundant populations of hares. I assume that if management agencies focus on providing habitat, hares will persist. Specifically, I will evaluate small and medium lodgepole pine stands and large spruce/fir stands where the classes “small”, “medium”, and “large” refer to the diameter at breast height (dbh) of overstory trees as defined in the United States Forest Service R2VEG Database (small = 2.54−12.69 cm dbh, medium = 12.70−22.85 cm, and large = 22.86−40.64 cm dbh; J. Varner, United States Forest Service, personal communication). To maximize comparability, I will choose lodgepole stands so that all are generating from harvest or all are regenerating following fire. I also intend to identify which of the numerous density-estimation procedures available perform accurately and consistently using an innovative, telemetry augmentation approach as a baseline. I will assess movement patterns and seasonal use of deciduous cover types such as riparian willow. Finally, I will further expound on the relationship between density, demography, and stand type by examining how snowshoe hare density and demographic rates vary with specific vegetation, physical, and landscape characteristics of a stand. Figure 1. Purported high quality snowshoe hare habitat in Colorado. From left to right: small lodgepole pine, medium lodgepole pine, and large Engelmann spruce/subalpine fir. 30 �OBJECTIVES 1) Compare telemetry-corrected estimates of density to those that would have been obtained from other commonly employed techniques used to convert population size estimated from a trapping grid to density (i.e., mean maximum distance moved, ½ mean maximum distance moved, ½ trap interval, nested grids, Program DENSITY). The purpose is to determine which common technique requiring less effort most consistently matches estimates from the intensive, telemetry-corrected approach. 2) Assess the relative value of the 3 stand types that purportedly provide high quality hare habitat by estimating and comparing survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each type. 3) Describe the timing, duration, and extent of broad-scale, seasonal movement patterns of snowshoe hares. 4) Relate specific vegetation, physical, and landscape characteristics of the 3 stand types to snowshoe hare density and demographics. APPROACH Hypotheses 1) In general, snowshoe hare density in Colorado will be relatively low (≤0.5 hares/ha) compared to densities reported in northern boreal forests, even immediately post-breeding when an influx of juveniles will bolster hare numbers. 2) Snowshoe hare density will be consistently highest in small lodgepole pine stands, followed by large spruce/fir and medium lodgepole pine, respectively. 3) Survival will generally be highest in mature (large) spruce/fir stands followed by small and medium lodgepole pine, respectively. 4) Finite population growth rate will be consistently at or above 1.0 in mature spruce/fir stands with survival contributing most significantly to the growth rate. Finite growth rates for the lodgepole pine stands will be more variable. 5) Snowshoe hares will significantly shift their home ranges to make use of abundant food and cover provided by riparian willow (and/or aspen) habitats in summer. 6) Snowshoe hare density, survival, and recruitment will be highly correlated with understory cover and stem density. Experimental Design/Procedures Variables.--The response variables of interest for this project include stand-specific snowshoe hare density (D), apparent survival (φ), recruitment (f), finite population growth rate (λ), and a metric of seasonal movement. Density is the number of hares per unit area and will be estimated using a variety of conventional techniques as well as a rigorous method that incorporates radio telemetry. The standspecific demographic parameters will be estimated primarily from capture-mark-recapture methods. As such, apparent survival is defined as the probability that a marked animal alive and in the population at time i survives and is in the population at time i + 1. Apparent survival encompasses losses due to both death and emigration. Recruitment is the number of new animals in the population at time i + 1 per animal in the population at time i. New recruits can arise from on-site reproduction as well as immigration. The finite population growth rate is the number of animals in a given age class at time i + 1 divided by the number present at time i. Shifts in home range will be assessed by comparing the seasonal proportion of telemetry locations in deciduous habitats using multi-response permutation procedures (MRPP; Zimmerman et al. 1985, White and Garrott 1990). Potential explanatory variables for snowshoe hare density, demographics, and movement include general species composition and structural stage of each stand in which response variables are measured. Additionally, stem density, horizontal cover, and canopy cover (to a lesser extent) are highly correlated 31 �with snowshoe hare abundance and habitat use (Wolfe et al. 1982, Litvaitis et al. 1985, Hodges 2000, Zahratka 2004, Miller 2005). Thus, I will further characterize vegetation in each stand by measuring stem density by size class (1-7 cm, 7.1-10 cm, and >10 cm), percent canopy cover, percent horizontal cover of understory and basal area. Basal area is an easily obtainable metric that may be correlated with the other variables and is recorded routinely during timber cruises, whereas the others are not. Thus, it might prove a useful link for biologists designing management strategies for snowshoe hare. Additionally, I will record physical covariates such as ambient temperature, precipitation, and snow depth at each stand during sampling periods as well as precipitation 1-3 years prior to sampling. Finally, I will calculate potentially important landscape metrics such as patch size and level of fragmentation. Location--.Identification of a suitable study area for this project and others that may follow is ongoing. The general study area must consist of an interspersion of young lodgepole pine and mature spruce/fir forest juxtaposed closely with open, seasonal habitats such as riparian willow. Within this general area, 3 sites will be selected such that 1) the 3 stand types of interest (small and medium lodgepole, large spruce/fir) occur within each site, 2) sites are close enough geographically to minimize differences due to climate, weather, and topography, but are far enough apart to be considered independent (e.g., 3 sites might occur in 3 different, but adjacent drainages), 3) each stand type within a site is adjacent to a riparian area, and 4) stand types of interest occur within 1 km of an access road (for logistical purposes). Such an arrangement often occurs in east-west drainages where spruce/fir grows on the north-facing slope, lodgepole pine covers the south-facing slope, and a riparian/willow area with road access separates the two (Figure 2). Additionally, sites must 1) include stands of suitable size and shape to admit a 16.5-ha trapping grid, 2) be consistent in their management history (i.e., all lodgepole pine stands in all sites must be either thinned or un-thinned, all regenerating after fire or all regenerating after harvest), and 3) be consistent in their intensity of use by lynx (core areas or not). I recently obtained the U.S. Forest Service R2VEG GIS database (newest, most detailed stand inventory information available statewide) and am currently working to objectively select a suite of potential study sites that satisfy the above-stated conditions. Depending on the number of potential sites within this suite, I will choose a small set of provisional study areas to ground-truth based on logistical considerations (e.g, housing, access). I will randomly select the final study sites from among those that appeared qualitatively suitable during ground-truthing. Prior to data collection I will more intensively sample the vegetation characteristics of the various stand types within the selected study sites to ensure that they represent intended conditions. Sampling.--All trapping and handling procedures will be approved by the Colorado State University Animal Care and Use Committee and filed with the Colorado Division of Wildlife. Snowshoe hares breed synchronously and generally exhibit 2 birth pulses in Colorado (although in some years, some individuals may have 3 litters), with the first pulse terminating approximately June 5−20 and the second approximately July 15–25 (Dolbeer 1972). To obtain a maximum density estimate, I will begin data collection on site 1 immediately following the second birth pulse in late July. Along with a crew of 5 technicians, I will deploy one 7 × 12 trapping grid (50-m spacing between traps; grid covers 16.5 ha) in each of the 3 stand types of interest following Griffin (2004) and Zahratka (2004). Grid locations and orientation will be chosen randomly within each stand subject to the logistical constraint that they must be within 1 km of a road. Traps will be deployed in all 3 stands in a single day. As traps are deployed, they will be locked open and “pre-baited” with apple slices and commercial rabbit chow. On days 2-4, the crew will continue pre-baiting, replacing apples and rabbit chow as necessary. The purpose of this extended pre-baiting is to maximize capture rates when trapping begins. This will minimize the number of trap-nights needed to capture the desired number of animals which in turn will minimize trappingrelated stress as well as the likelihood that American marten (Martes americana) will key into trap lines and prey on entrapped hares, as has occurred in previous studies (J. Zahratka, personal communication). During pilot work in winter 2005, I observed low but increasing capture rates (<0.20) during the first 3 32 �nights of trapping, with higher, more stable capture probabilities after 3 days (approximately 0.35–0.45). Thus 3 days of pre-baiting seems reasonable. Study Area Site 1 Site 2 Site 3 Summer Winter FY06-07 FY08-09 FY07-08 Figure 2. Experimental design for study of snowshoe hare density, demography, and movement. Within the study area, 3 sites, each consisting of 3 forest stand types (light to dark gray shades) and a riparian area (medium gray shade), will be sampled (dotted trapping grids) during late summer and late winter for 3 years. 33 �Traps will be set on the afternoon of the 4th day and checked early each morning and again in the evening on days 5–9. By checking traps in both morning and evening I prevent hares from being entrapped >13 hours, which should minimize capture stress. Based on Zahratka (2004) and personal experience, I anticipate capturing up to 10–15 individual hares per grid. A crew of 2 people will work together on each grid to check traps and process captures as quickly as possible. All captured hares will be coaxed out of the trap and into a dark handling bag by blowing quick shots of air on them from behind. Hares will remain in the handling bag, physically restrained with their eyes covered, for the entire handling process. Each individual will be aged, sexed, marked with a passive integrated transponder (PIT) tag and temporary ear mark (to track PIT tag retention), then released. Aging will consist of assigning each individual as either juvenile (<1 year old, <1000 g) or adult (≥1 year old, ≥1000 g) based on weight. This criterion is accurate through the end of September at which point juveniles are difficult to distinguish from adults (K. Hodges, University of British Columbia; P. Griffin, University of Montana, personal communication). After the first day of trapping, all captured hares will be scanned for a PIT tag prior to any handling and those already marked will be recorded and immediately released. Traps and bait will be completely removed from the grid on day 10. In addition to PIT tags and ear marks, I will radio collar up to 10 hares captured on each grid with a 28-g mortality-sensing transmitter (BioTrack, LTD) to facilitate unbiased density estimation as well as assessment of seasonal movements. I expect heterogeneity in snowshoe hare movements and use of the grid area, with potential bias surfacing due to location at which a hare is captured (e.g., hares captured on the edge of a grid may use the grid area differently than those captured at the center), and differential behavioral responses to trapping (e.g., young individuals may have lower capture probabilities and thus may be more likely to be captured on later occasions). To guard against the first potential bias, I will randomly select a starting trap location each morning and run the grid systematically from that point. Thus, the first several hares encountered (and collared) will be as likely to be from the inner part of the grid as from the edge. To protect against the second potential source of bias, I will refrain from deploying the final 3 collars until days 4 and 5 of the trapping session. Immediately following the removal of traps, the field crew will begin work locating each radiocollared hare 1–2 times per day for 10 days. Locations will be obtained by “homing” on a signal (Samuel and Fuller 1996, Griffin 2004) taking care not to push hares while approaching them. Technicians will record their location with hand-held GPS units (Garmin model 12XL) as soon as a visual of the collared hare is obtained or if the signal can be picked up by the receiver without an antenna. Using the same make and model collars, Griffin (2004) found that hares are usually within ~15m when the signal came be received without an antenna (Griffin 2004). I will test this assumption with my telemetry equipment over a variety of transmitter locations and orientations. Because hares are largely nocturnal (Keith 1964, Mech et al. 1966, Foresman and Pearson 1999), an effort will be made to conduct telemetry work at various times of the night (safety and logistics permitting) and day to gather a representative sample of locations for each hare. The crew will gather telemetry locations for radio-collared hares on site 1 for 8−9 days. Then the 10−day trapping procedure and 8 to 9−day telemetry work will be repeated on the 3 grids comprising site 2 (Figure 3). The cycle will be repeated once more for grids on site 3 (Figure 3). The entire process will be repeated during the following winter when densities should be at a minimum. In summary, for any given 9-week sampling period, I will collect data from 9 total grids, 1 grid in each of 3 habitat types (stand types) across 3 sites. Sampling will occur during 2 such 9-week periods each year − once in late summer and once in late winter – and will continue for 3 years (Figure 2). During the interim between intensive trapping and telemetry work, a single technician and myself will attempt to gather 1–2 telemetry locations/hare/month in order to keep closer tabs on these individuals, 34 �determine more precisely when mortality occurs, and retrieve collars from dead hares. Telemetry work will also occur during “pre-baiting” days to determine which hares are still alive and immediately available to be sampled by the grid during the ensuing trapping period. Jul Aug Sep 1 Jan 1 2 3 4 2 3 4 5 6 7 8 5 6 7 8 9 10 11 9 10 11 12 13 14 15 12 13 14 15 16 17 18 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1 2 3 4 6 7 8 9 10 13 14 15 16 19 20 21 22 23 24 25 26 27 28 29 30 31 1 5 2 3 4 5 6 7 8 11 12 9 10 11 12 13 14 15 17 18 19 16 17 18 19 20 21 22 Feb 20 21 22 23 24 25 26 23 24 25 26 27 28 1 27 28 29 30 31 1 2 Mar 2 3 4 5 6 7 8 3 4 5 6 7 8 9 9 10 11 12 13 14 15 10 11 12 13 14 15 16 16 17 18 19 20 21 22 17 18 19 20 21 22 23 23 24 25 26 27 28 29 24 25 26 27 28 29 30 30 31 Figure 3. Approximate annual data collection schedule for trapping (�) and telemetry (�). Dates and weeks will change depending on calendar year and pay schedule. During telemetry work, the 6-person crew will be divided into 2 teams, only one of which will be working at any given time. Monthly locations on radio-collared hares will also be collected in the interim between the intensive sampling periods indicated here. Vegetation sampling at each stand will follow protocols established through previous snowshoe hare and lynx work in Colorado (Zahratka 2004, T. Shenk, Colorado Division of Wildlife, personal communication). Specifically, on each of the 9 live-trapping grids, I will lay out 5 × 5 grids (3-m spacing) of vegetation sampling points centered on 15 of the 84 trap locations (Figure 4). At each of the 25 vegetation sampling points, I will record: 1) distance to the nearest woody stem 1.0−7.0 cm, 7.1−10.0 cm, and >10.0 cm in diameter at heights of 0.1 m and 1.0 m above the ground (to capture both summer [0.1 m] and winter [1.0 m] stem density; Barbour et al. 1999), 2) horizontal cover in 0.5-m increments above the ground up to 2 m (Nudds 1977), and 3) canopy cover [present or absent] using a densitometer. Additionally, at the center of all 15 vegetation sampling grid points (i.e., at the trap location), I will measure basal area using an angle gauge. These measurements will be gathered once at the start of the project, unless conditions change due to disturbance such as fire. Temperature will be monitored hourly at each grid during the 6-week intensive sampling periods using data loggers. During winter sampling periods, snow depth measurements will be recorded daily at the same 15 trap locations used to quantify the vegetative attributes of that stand. 35 �Figure 4. 15 trap locations (•) on 7 × 12 trapping grid where vegetation will be sampled by measuring stem density horizontal cover, and canopy cover at the 25 points on each 5 × 5 subgrid (inset). In addition, basal area will be measured at the trap location (�) on which each of the 15 subgrids are centered. Data Analysis Density.--I will assume that hare populations are demographically and geographically closed during the short 5-day mark-recapture sampling periods. To obtain a density estimate for each grid, I will use the Huggins closed capture model (Huggins 1989, 1991) in Program MARK (White and Burnham 1999) with some modifications. The basic Huggins estimator (no individual covariates) is based on the fact that if pj is the probability that a hare in the population will be captured (and marked) for the first time on trapping occasion j, then p * = 1 − (1 − p1 )...(1 − p5 ) is the probability that an individual is captured at least once during a 5-day trapping period (i.e., j = 1,…,5). Accordingly, the basic Huggins estimator for population size, N̂ , is Nˆ = M t +1 / p* where M t +1 is the total number of hares captured. The estimator can be re-written to allow each of the M t +1 individuals captured to have their own p*. In that case, Nˆ = M t +1 ∑1 / p . Presumably hares that reside near the edge of a grid encounter fewer traps and * i i =1 are less likely to be captured than hares residing near the center of a grid. To account for this, I will take advantage of the Huggins model with individual covariates to model p* by using the logit link function of program MARK to model pi* as a function of di, where di is distance from the edge of the grid for hare i based on mean capture coordinates. A naïve density estimate for each grid would then be Dˆ = Nˆ / A where A is the area of the grid. However, this gives full credit to all hares, even those whose home range only partially overlaps the grid, which results in a density estimate that is biased high. To correct for this bias, I will determine the proportion, ( ~ pk ), of telemetry locations for each of the k = 1,…,10 radiocollared hares that fall within the “naïve grid area.” By incorporating data from multiple grids, a logistic regression model will be developed to estimate p% i for all M t +1 animals captured on a grid based on 36 �distance from the edge of the grid for hare i (di). Replacing the numerator (i.e., 1) in the Huggins ⎛ M t +1 ⎞ ~ p / p ⎟ A. ⎜∑ ⎟ estimator with ( p% i ), gives a density estimate, Dˆ = ⎜ ⎝ i =1 i * i ⎠ The above-stated approach assumes that radio-collared hares neither gravitate toward nor avoid the former grid area after the 5 days of trapping, 10–20 locations per hare is enough to provide a reasonable representation of the proportion of time they spend on the grid, and their use of the grid area is representative of other hares that were captured but not collared (i.e., that the logistic regression model of p% i is a useful model). I contend that this type of estimate from grid-based trapping can be construed as a relatively unbiased estimate of density. Using these point estimates and their associated confidence intervals, I will compare hare density among seasons, years, and stand types. I will also compare these “true” density estimates to those that would have been obtained using other available methods such as ½ mean maximum distance moved (Wilson and Anderson 1985, Williams et al. 2002:314-315), full mean maximum distance moved (Parmenter et al. 2003), ½ trap interval (Parmenter et al. 2003), “nested grids” (White et al. 1982:120-131), and Program DENSITY (Efford et al. 2004). Demography.--I will analyze mark-recapture data using Pradel temporal symmetry models (Pradel 1996, Nichols and Hines 2002) in a robust design framework (Williams et al. 2002:523-554), which will be available in Program MARK by summer 2006. Thus, I will treat summer and winter sampling occasions as primary periods, and the 5-day trapping sessions within each as secondary periods. The Pradel temporal symmetry models employ both forward and reverse-time evaluation of capture histories to provide estimates of apparent survival ( φ̂ ) and seniority ( γ̂ ). Apparent survival, φi, is the probability that a marked animal alive and in the population at time i survives and is in the population at time i + 1. The seniority parameter, γi , is the reverse-time analogue of survival. Reading backward through a capture history, it is the probability that a marked animal alive and in the population at time i was alive and in the sampled population at time i − 1. If N is the number of animals present in the population, N i φi ≈ N i +1γ i +1 and N i +1 / N i = φi / γ i +1 = λ i . Also, if fi is recruitment rate, or the number of recruits at time i + 1 per animal present at time i, then N i +1 = N i φi + N i f i . Rearranging and substituting into the previous equation gives f i = φi (1/ γ i − 1) . Thus, using Pradel models, one can estimate recruitment and finite population growth rate in addition to survival (Pradel 1996, Nichols and Hines 2002). I will use Akaike’s Information Criterion corrected for small sample size (AICc; Burnham and Anderson 1998) to determine whether models with time-dependent parameters or constant parameters are best supported by the data. I will derive estimates of the above-mentioned parameters from the best model or from model averaging. I anticipate pooling capture data across sites to obtain φˆ i , λˆ i , and fˆi for each stand type for each interval between primary sampling periods (5 estimates of each). I also anticipate simply estimating these parameters for “generic hares”, treating both juveniles and adults as a single group or age class. Given that juveniles are morphometrically indistinguishable from adults by their first fall of life (K. Hodges, University of British Columbia; P. Griffin, University of Montana, personal communication), adult and juvenile survival rates are similar (Griffin 2004), and there is little evidence for age-specific differences in pregnancy rates or litter size (Dolbeer 1972), this approach seems justified. However, if I happen to capture sufficient numbers of juveniles and adults, the design I have laid out here allows for treating the age classes separately. This, in turn, may permit me to decompose the contribution that fi makes to λi into the portion of that contribution due to on-site reproduction and that due to immigration (Nichols et al. 2000). Similarly, it may also be possible using my telemetry data to decompose apparent survival, φi , into emigration and mortality. Such fortuitous situations would facilitate the identification of source and sink habitats if they exist. 37 �Seasonal Movements.--I will assess whether snowshoe hares seasonally shift their home ranges using the multi-response permutation procedure (MRPP; Zimmerman et al. 1985, White and Garrott 1990:134-135). Under this approach, telemetry locations are grouped by season (summer and winter), and an MRPP statistic is calculated as the weighted average of the distance between all possible pairs of locations within groups compared to the average distance between all possible pairs ignoring groups. The null hypothesis is that the distribution of locations is the same for both groups (seasons). Sufficiently small values of the test statistic suggest that within group distances are smaller than distances measured ignoring groups, which is evidence against the null in favor of a group (seasonal) effect. P-values are obtained by calculating the percentile of the observed test statistic relative to all possible test statistics that could be computed by re-arranging the data into all possible groups of 2. The MRPP procedure is sensitive and can detect even small changes in use of an area (White and Garrott 1990:136). I propose a priori that changes in proportional use of deciduous habitats <0.10 in magnitude are unlikely to be biologically significant. Vegetation.--I will calculate mean stem density, horizontal cover, canopy cover, and basal area for each season−stand type as well as temperature, precipitation, snow depth information, and landscape metrics. These will be entered into the MARK design matrix as covariates to population size (~density) and survival in a random effects analysis. As such, I will be able to quantify the amount of variation in population size or survival that is due to differences in vegetation, landscape, or weather relative to the amount left to other causes. Sample size.--I conducted power analyses to determine the probability of discerning meaningful differences in density and survival for hares occupying different stand types. For density, I postulated that foraging lynx likely do not discriminate among stands that differ by only a few hares. However, it seems probable that if hare density in one stand is twice that of another, a lynx would choose the former given the opportunity. Thus, I conducted power calculations to determine the probability of distinguishing differences in densities between 2 stand types in which one had twice the density of hares as the second. Specifically, using the Huggins closed capture model (Huggins 1989, Huggins 1991) in Program MARK, I specified the number of hares (N) present in each of 2 groups (i.e., 2 stand types), allowed capture (p) and recapture (c) probabilities to vary with time but constrained them to be equal and the same for each group, then simulated this scenario 1000 times for a range of realistic capture probabilities. For each simulation I calculated a 95% confidence interval for the mean difference in N̂ between the 2 groups and determined the proportion of all simulations in which this confidence interval did not include zero. This proportion is the power, or probability of discerning a difference between the 2 groups when one actually exists. I compared 2-fold differences in density at the low (5 vs. 10 hares/grid) and high (15 vs. 30 hares/grid) end of the range of hare numbers and I expect to observe (Zahratka 2004). I also simulated the power to detect differences between 17 and 39 hares/grid, corresponding to recently published cut-points for low and high hare densities in the context of lynx conservation (Mills et al. 2005). Given capture/recapture probabilities I observed during winter 2005 (approximately 0.35–0.45), I expect to have reasonable power to detect 2-fold differences in density even if I encounter relatively few hares per grid (Figure 5). 38 �Density Power Analysis % Non-overlapping 95% CIs 100 90 80 70 60 50 40 30 20 10 0.60 0.55 0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0 capture/recapture probability N=5 vs. N=10 N=15 vs. N=30 N=17 vs. N=39 Figure 5. Power for distinguishing differences in snowshoe hare density between 2 habitat types when a difference actually exists. Gray area indicates the capture probability realized by the 3rd day of trapping during a pilot study in winter 2005. N indicates number of hares per grid, a range of roughly 0.1 (N = 5) to 0.7 hares/ha (N = 39). I conducted power analyses for survival in a similar manner using the Huggins estimator (Huggins 1989, Huggins 1991) in a robust design framework (Williams et al. 2002:524-556). For this analysis, I specified 3 primary periods (e.g., 3 years) with 5 secondary occasions for each. I established either 30 or 45 hares in each of 2 groups (i.e., pooled an expected 10-15 hares/grid across the 3 grids in a given habitat type), specified a different survival rate for each, and allowed p and c to vary with time but constrained them to be equal and the same for each group as before. I then specified a general model that assumed survival rates varied among groups and a second, reduced model that assumed survival rates were the same for each group. After 1000 simulations under a given scenario of hare numbers, capture probabilities, and survival rates, I conducted a likelihood ratio test between each pair of general and reduced models. As before, I used the proportion of significant tests as an estimate of power to detect differences in survival. I compared survival rates of 0.4 vs. 0.5, 0.3 vs. 0.5, and 0.2 vs. 0.5. These rates span the range of annual hare survival rates reported in the literature (Dolbeer 1972, Dolbeer and Clark 1975, Griffin 2004). Also, because each comparison is anchored at 0.5, these calculations provide a conservative estimate of power due to the nature of binomial probabilities. That is, I would be more likely to distinguish the difference between 0.1 and 0.2 than between 0.4 and 0.5 even though the difference in both cases is 0.1 because the sampling variance of the estimate for the same sample size is maximal at 0.5 and declines to 0 for survival rates of 0 or 1. Results indicate that I have ≥80% chance of discerning real differences in survival of ≥0.3 (Figure 6), but only 40-65% chance (depending on number of hares captured) of detecting a difference of 0.2, and very little chance of detecting differences smaller than 0.2. However, I plan to combine my telemetry data with my trapping data in the MARK Robust design model using separate groups for each data type. This should enhance my precision and power, thus making the prospect of detecting differences as small as 0.2 a possibility. 39 �Survival Power Analysis (N = 45) 100 100 90 % Significant LR Tests 80 70 60 50 40 30 20 10 90 80 70 60 50 40 30 20 0.2 vs. 0.5 0.3 vs. 0.5 0.60 0.55 0.50 0.45 0.40 0.35 0.30 0.25 0.10 0.60 0.55 0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 Capture/Recapture Probability 0.20 10 0 0 0.15 % Significant LR Tests Survival Power Analysis (N = 30) Capture/Recapture Probability 0.4 vs. 0.5 0.2 vs. 0.5 0.3 vs. 0.5 0.4 vs. 0.5 Figure 6. Power, or probability of distinguishing differences in snowshoe hare survival between 2 habitat types when differences actually exist. N = 30 (left) and N = 45 (right) correspond to reasonable estimates of the number of hares I expect to capture in each habitat type. Gray area indicates the capture probability realized by the 3rd day of trapping during a pilot study in winter 2005. To complete a power analysis for λ̂ requires running simulations of Pradel models in a robust design framework. This capability is not yet available in Program MARK, so such an analysis has not been completed. Sampling 15 vegetation plots per trapping grid provided reasonably precise characterizations of similar stands in similar locations during a previous study (Zahratka 2004). I trust this level of sampling will be adequate for the present study as well. If not, more plots can be established at a later date given that vegetative characteristics are unlikely to change appreciably over a few years. Project Schedule I will begin the first 9-week data collection period in mid July 2006. The first winter sampling period will begin in February 2007. Intensive sampling will occur across a total of 3 summer and 3 winter periods, with monthly telemetry work interspersed between the main sampling periods. All fieldwork will terminate with the winter 2009 sampling period. Analysis, write-up, and submission to journal outlets will occur during summer and Fall 2009. I plan to graduate during spring semester 2010. Personnel Jacob S. Ivan, Ph. D. student, Colorado State University will be the primary investigator responsible for the design and conduct of the study. Tanya M. Shenk, Mammals Research, Colorado Division of Wildlife, and Gary C. White, Professor, Colorado State University will serve as primary advisors. Also, as most lynx/hare habitat occurs on United States Forest Service (USFS) land, this project will require cooperation and coordination with USFS biologists and district rangers for permission and possibly logistical support (housing, campsites, trucks). As presented here, this project will require an estimated minimum of 3,600 person-hours/year (5 technicians, 720 hours) in technician labor to complete the intensive 9-week sampling periods as well as 360 person-hours/year of technician labor to run the monthly telemetry operation. Thus, completion of the 3-year project will require an estimated minimum of 11,880 person-hours in addition to time spent by the primary investigator, advisors, and cooperators. 40 �Estimated Annual Cost FY06-07 FY07-08 FY08-09 TFTE (5 techs, 360, $11.13/hr, 11.16% overhead)* $ 22,270 $ 22,830 $ 23,410 TFTE (1 tech, 360 hours, $11.13/hr, 11.16% overhead)** $ $ 4,565 $ 4,679 Personnel 4,454 Operating PURCHSERV (Ph.D. Stipend, tuition, minimal supplies)*** $ 27,500 $ 27,500 $ 27,500 SUPPLIES (bait, snowmobile repairs, handling supplies, etc.) $ $ 4,000 $ 4,000 EQUIPMENT (radio collars) $ 11,500 $ 11,500 $ 11,500 INSTTRAV $ 1,500 $ 1,500 $ 1,500 VEHICLE LEASE/MILEAGE (3 vehicles, 5 months/year)** $ 5,328 $ 5,328 $ 5,328 4,000 Travel TOTAL COST $76,552 $77,223 $77,917 TOTAL COST TO SSH BUDGET $43,724 $44,395 $45,089 *Assumes 2.5% cost-of-living wage increase/year **Telemetry work during interim between sampling periods ***Will be charged to budget centers other than lynx/snowshoe hare EXPECTED RESULTS/BENEFITS 1) Seasonal density estimates and associated variability will help establish where Colorado lies on the continuum of hare densities reported in the literature. Whether densities are relatively high or low, stable or highly variable, or drastically different or roughly equal among cover types could influence future land management decisions as well as decisions regarding the lynx reintroduction process. 2) Combined with Zahratka (2004) and future research, density estimates from this project may elucidate the degree to which hare populations fluctuate or cycle in Colorado, a phenomenon of interest to wildlife ecologists and managers. 3) Comparison of “known” densities to those obtained from other commonly used methods will inform future research and monitoring programs which techniques are likely to produce results that are most consistently in agreement with the intensively derived estimates reported from this project. This knowledge will also enhance interpretation of previously reported hare densities in Colorado and elsewhere. 4) Assessment of density, demographic parameters, and their variability among habitat types will help identify which type(s) consistently support(s) high hare numbers and productivity. The current, conservative approach to lynx/hare conservation is to treat all potential habitat as equally and highly valuable, although this has not been substantiated scientifically, especially in Colorado. This project should determine if the current approach is justified or if there is a disparity in the value of different habitat types relative to lynx-hare conservation. If the latter is true, those charged with managing forests may be allowed more flexibility to accommodate competing resource uses while maintaining lynx/hare habitat. 41 �5) Assessment of density and demographic parameters should help identify the general time period over which succession carries young, regenerating lodgepole pine stands into and then out of service as snowshoe hare habitat. It is apparent that stands in fresh clear cuts and mature lodgepole stands do not provide quality hare habitat (Zahratka 2004). The value of small and medium lodgepole stands to hares has not been quantified in Colorado and is of interest to resource managers. 6) Knowledge regarding the presence or absence of large-scale seasonal movements, and the extent to which this occurs will inform managers about the value of peripheral vegetation (other than conifer forest, such as riparian willow or aspen), will identify when and for how long peripheral vegetation is likely to be used, and will potentially identify other snowshoe hare management issues that have not received prior consideration. 7) A description and comparison of vegetation and landscape characteristics among the 3 stand types and their relationship to snowshoe hare demography and movement patterns should further aid land managers in creating and maintaining lynx/hare habitat. RELATED FEDERAL PROJECTS Given that the majority of lynx/hare habitat occurs on United States Forest Service land, this project will require cooperation with local ranger districts, regional biologists, and researchers within that agency. As soon as I have completed provisional study site selection, I will contact the appropriate collaborators to obtain permission, appropriate permits, etc. LITERATURE CITED AUBRY, K. B., G. M. KOEHLER, AND J. R. SQUIRES. 2000. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA. BARBOUR, M. G., J. H. BURK, W. E. PITTS, F. S. GILLIAM, AND M. W. SCHWARTZ. 1999. Terrestrial plant ecology, Addison Wesley Longman, Inc., Menlo Park, California, USA. BARTMANN, R. M. 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Ecology 66:606-611. 45 �46 �Colorado Division of Wildlife July 2005 – June 2006 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Colorado 3430 3001 Federal Aid Project W-185-R : Division of Wildlife : Mammals Research : Deer Conservation Program Final Report Deer Conservation Research For 5-Year Federal Aid Grant W-185-R July 2001 – June 2006 : Period Covered: July 1, 2001 – June 30, 2006 Author: David J. Freddy, Mammals Research Leader, 1 June 2006 Principal Investigators: D. L. Baker, C. J. Bishop, E. J. Bergman, D. J. Freddy, and T. M. Pojar, Colorado Division of Wildlife; W. F. Andelt, N. T. Hobbs, and G. C. White, Colorado State University All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT This report highlights the accomplishments of mule deer research and associated activities conducted by the Colorado Division of Wildlife (CDOW) with the funding support of Federal Aid Grant W-185-R during the 5-year grant segment, July 2001-June 2006. Five major multi-year research projects addressing mule deer population limiting factors, habitat status, and habitat enhancements were designed, implemented, completed, and reported upon during this segment in response to addressing stakeholder interests that influenced the direction of mule deer management and research beginning in the late 1990s. Additionally, funding provided critical scientific and technical expertise quality control oversight for statewide deer hunter harvest surveys, statewide deer population databases, mule deer survival and population estimate management surveys, mule deer population modeling, and mule deer research projects. Funding also partially supported research projects addressing chronic wasting disease and fertility control in mule deer. Research experiments provided strong evidence that habitat nutritional quality had a greater impact on net productivity of mule deer than did existing levels of coyote, cougar, and black bear predation and therefore, future research and management efforts should focus on improving the nutritional capabilities of senescent pinyon-juniper winter ranges for deer. Research also provided strong evidence that the timing and rate of breeding were within normal ranges for mule deer and therefore concerns about the breeding cycle could be dismissed as a major contributor to declining performance of mule deer populations. Comparative assessments of vegetation inside and outside sagebrush and mountain brush exclosures indicated that after 40 to 50 years of protection from ungulate herbivory, woody species increased in cover dominance with only minor changes in herbaceous cover. Increasing plant species diversity in these types of winter ranges will probably not be accomplished by excluding herbivory. In a highly scrutinized public experiment, research and management expertise codemonstrated that methods used by Colorado to estimate mule deer population size and to develop 47 �population management models provided reliable information to adequately guide mule deer harvest management decisions. From activities supported by this Grant during this segment, principal investigators published 15 peer-reviewed scientific articles pertaining to mule deer for prominent wildlife research journals with an additional 4 manuscripts currently in review with journals, provided 18 annual CDOW Wildlife Research Reports summarizing yearly progress of projects, and provided 13 presentations at prominent professional workshops or symposia. The cumulative impact of this programmatic effort provides Colorado the basis to progress and proactively sustain the mule deer resource in an increasingly demanding and complex landscape, social, and political environment. The relative success of mule deer management in Colorado reflects the positive synergy between the terrestrial research and management sections in sharing expertise, financial resources, manpower, and common goals. 48 �WILDLIFE RESEARCH REPORT PROGRAM FINAL REPORTDEER CONSERVATION RESEARCH FOR 5-YEAR FEDERAL AID GRANT W-185-R JULY 2001 – JUNE 2006 DAVID J. FREDDY Mammals Research Leader PROGRAM NEED During the late 1990s, the Colorado Division of Wildlife (CDOW) was challenged by sportsmen and other stakeholders to investigate potential causes of declining numbers of mule deer in Colorado. Additionally, sportsmen were critical of methods used to estimate numbers of mule deer and subsequently did not trust the CDOWs assessment of the overall status of mule deer in Colorado. The concerns of stakeholders gained the attention of the Colorado Legislature which directed CDOW to prepare a document to address causes of the mule deer decline and outline a plan of action to reverse the perceived trend in mule deer populations. That document was prepared for the legislature in 1999 (Gill et al. 2001) and established the direction and objectives for mule deer management and research beginning in 1999. Research objectives and program implementation were outlined and initiated in 1999 with most of the research effort directed at the Uncompahgre Plateau mule deer population which was of high concern to various stakeholders. This Federal Aid Grant Final Report highlights the accomplishments of the research pertaining to the mule deer program that was conducted from July 1, 2001 through June 30, 2006 and wholly or partially supported by Federal Aid Grant funds. PROGRAM NARRATIVE OBJECTIVES The primary Program Narrative research objectives were: I. Identify factors limiting the growth of mule deer populations. II. Assess methods to reduce impacts of limiting factors. III. Improve and evaluate statewide systems and technical methods used to determine status of mule deer populations. IV. Assess the impacts of chronic wasting disease on mule deer populations. V. Develop alternative approaches to control over-abundant urban-exurban mule deer populations. RESULTS Objective I. Factors Limiting Growth of Mule Deer Populations. Initially, stakeholders expressed concern that statewide declines in mule deer populations were caused by low pregnancy rates in adult females due to inadequate numbers of mature bucks to breed females, and by low recruitment of neonatal fawns due to excessive predation on neonates. Two primary projects were funded to focus on: 1) estimating pregnancy and fetal rates in adult female mule deer; and, 2) estimating survival rates of neonate fawn mule deer. 49 �Result Highlights: • Pregnancy and fetal rates were determined with ultrasonography and PSPB blood values to be within normal limits for the Poudre River and Uncompahgre Plateau mule deer in 1998 and 1999. Therefore, numbers of mature mule deer bucks were adequate to assure acceptable rates and timing of breeding for adult female deer. • Survival of radio-collared neonatal fawns from birth in June to December averaged 0.50 during 3 years from 1999 through 2001. This rate of neonate survival was only marginally adequate to assure population growth. Primary cause of death in neonates was sick/starve implicating inadequate nutrition for either adult does or neonates. Predation on neonates by canids, ursids, and felids occurred but not at rates considered to be limiting the population. Coyotes were the primary predator accounting for about 13% of the neonate deaths. Resulting Peer-Reviewed Publications: ANDELT, W.F., T.M. POJAR, AND L.W. JOHNSON. 2004. Long-term trends in mule deer pregnancy and fetal rates in Colorado. Journal of Wildlife Management 68:542-549. POJAR, T.M., AND D.C. BOWDEN. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Associated Annual Wildlife Research Progress Reports Available from the Colorado Division of Wildlife Research Library, Fort Collins, Colorado: POJAR, T.M., AND D.C. BOWDEN. 2002. Mule deer life-cycle-neonatal fawn survival. Colorado Division of Wildlife, Wildlife Research Report July: 47-63. POJAR, T.M. 2003. Mule deer life-cycle-neonatal fawn survival. Colorado Division of Wildlife, Wildlife Research Report July: 55. Objective II. Assess Methods to Reduce Impacts of Limiting Factors. A widespread debate throughout the western states in the late 1990s was whether mule deer were declining primarily due to predation from perceived abundant coyote, cougar, and black bear populations or if the decline was due to long-term losses in habitat quality and availability which negatively affected mule deer nutrition and subsequent recruitment and survival. Both predation and habitat quality were judged by various stakeholders to be the ‘cause’ of declining mule deer in Colorado and specifically the Uncompahgre deer population. Although painting the picture that the mule deer decline was caused by one major factor versus another major factor oversimplified the situation, such a dichotomy of thought quickly helped focus thrusts for potential research and management actions. The case for predation was assessed by Ballard et al. (2001) in their influential overview of predation and deer populations. The potential effects of habitat deterioration resulting from successional senescence of important plant communities and direct losses of habitat space due to human encroachment was argued by deVos, Jr. et al. (2003) in their overview of mule deer conservation strategies. As this debate evolved, Colorado was fortunate to have developed a strong working relationship with the Idaho Department of Fish and Game in our mutual attempts to address causes of the mule deer decline. The research sections of these 2 agencies decided to cooperatively investigate whether predation or habitat was the cause of the mule deer decline. Idaho, because of political, social, and legal aspects, was more capable of addressing the impacts of predation on mule deer than was Colorado and therefore, Idaho designed and implemented an intensive experimental reduction of coyote and cougar populations to measure the impacts of such actions on mule deer net recruitment (Hurley et al. 2002, Hurley et al. 2005). To compliment Idaho’s efforts, Colorado designed and implemented a series of experiments to measure the impacts of improving the nutritional quality of habitats on mule deer net recruitment (Bishop and White 2000). 50 �Three primary projects were funded to focus on: Phase 1A) effect of enhanced nutrition on mule deer population parameters; Phase 1B) long-term effects of herbivory on sagebrush and mountain brush winter ranges; and Phase 2A) effects of landscape habitat alterations within senescent old-growth pinyonjuniper winter ranges to enhance mule deer population parameters. Result Highlights: Phase 1A • Survival of fawns receiving an enhanced nutrition treatment from December through April had an over-winter survival rate of 0.89 which was higher (P < 0.001) than the survival rate of 0.65 for control fawns not receiving enhanced nutrition. The over-winter survival period was 15 December to 15 June during 3 years, 2001-02, 2002-03, 2003-04, and survival rates were based on 240 6-month old fawns with 120 fawns captured and radio-collared in each of the control and treatment areas. The effect of enhanced nutrition was highly evident even with the presence of ongoing predation by coyotes and cougars. • Survival rates of fetuses to neonate and through 1-year of age that were born to adult females receiving enhanced winter nutrition were 0.46 and higher (P < 0.001) than survival rate of 0.28 for fetuses born to adult females not receiving enhanced nutrition. Survival rates were over 3years, 2002-2004, and based on 276 fawns monitored across 293 adult females that were radiocollared of which, 154 adults received vaginal implant transmitters to aid in capture and monitoring neonate survival. Ultrasonography was used to determine in-utero fetal rates. • Body condition on about 1 March, as estimated from percent body fat and depth of longissimus dorsi muscle via ultrasonographpy, was better (P < 0.001) in adult females receiving enhanced winter nutrition (n = 78) than for control adult females not receiving enhanced nutrition (n= 76). Serum thyroid hormone levels were also higher in adult females receiving enhanced nutrition compared to control adult females not receiving better nutrition. Pregnancy and fetal rates were similar (0.95 and 1.80 fetuses per female) for adult females receiving and not receiving enhanced nutrition. • The finite rate of population increase, λ, was 1.20 for those deer receiving enhanced nutrition. For those deer not receiving enhanced nutrition, the finite rate of increase was 1.04 indicating a stable or slightly increasing population. The nutrition enhancement therefore, had a dramatic effect on deer population performance, indicating habitat quality was ultimately limiting the population that was also subject to natural levels of predation. In comparison, intensive control of coyote and cougar populations in Idaho had marginal positive impacts on survival rates of neonate fawns, 6-month old fawns, and adult mule deer and ultimately, net population growth (Hurley et al. 2005). • These enhanced nutrition experimental results provided a foundation for focusing deer management efforts on improving habitat quality in Colorado’s pinyon-juniper mule deer winter ranges rather than trying to intensively control or reduce coyote and/or cougar populations. • Phase 1B Excluding herbivory from semi-arid sagebrush and mountain brush plant communities resulted in increased dominance by shrub species and only minor changes in herbaceous species in nongrazed compared to adjacent grazed areas. Comparisons were based on measurements made in summer 2000 at 17 permanently fenced exclosures in western Colorado where ungulate herbivory was excluded for 40 to 50 years. Improving herbaceous and overall species diversity within established shrub dominated habitats will not likely occur by excluding grazing. 51 �• • Phase 2A Evaluating the effects of landscape alterations within senescent old-growth pinyon-juniper winter ranges on mule deer population performance parameters was initiated in 2004-05 as a pilot study and precursor to full-scale study implementation. Over-winter fawn survival was estimated on 2 critical pinyon-juniper winter range habitat treatment evaluation areas on the Uncompahgre Plateau in 2004-05. Both areas were found to be logistically adequate for future work and fawn survival was 0.84 to 0.96 on both sites (n = 25 radio-collared fawns per site). A project study plan for evaluating landscape habitat treatments was completed in 2005. Fullscale 4-year implementation began during winter 2005-06 as over-winter fawn survival, adult female body condition, and mule deer density were estimated among 8 habitat treatment evaluation areas (each 10-20 km2 in size) on the Uncompahgre Plateau. Pinyon-juniper habitat areas were categorized as controls (non-treated and senescent), pre-treatmeant (treated to reduce density of pinyon-juniper during last 10-15 years), and treatment (receiving additional habitat enhancements during this study). Initial survival rate estimates ranging from 0.76 to 0.88 suggest over-winter fawn survival may vary among habitat treatment levels. Estimates of deer density reaffirmed that deer densities in the northern study areas were lower (4-8 deer/km2) than densities in the southern study areas (19-57 deer/km2). Continued estimation of deer performance parameters over the next 3 years should allow detecting whether altering senescent pinyonjuniper habitats improves mule deer net productivity. Resulting Peer-Reviewed Publications: BISHOP, C.J., G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2003. How habitat quality affects hunting. Mule Deer 8:18-20. BISHOP, C.J., D.J. FREDDY, G.C. WHITE, B.E. WATKINS, T.R. STEPHENSON, AND L.L. WOLFE. 2006 In Review. Using vaginal implant transmitters to aid in capture of neonates from marked mule deer. Journal of Wildlife Management. MANIER, D.J., AND N.T. HOBBS. 2006. Large herbivores influence the composition and diversity of shrub-steppe communities in the Rock Mountains, USA. Oecologia 146:641-651. SCHULTHEISS, P.C., H. VAN CAMPEN, C.J. BISHOP, L.L. WOLFE, AND B. PODELL. 2006 In Review. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer (Odocoileus hemionus) in Colorado. Journal of Wildlife Disease. Associated Annual Wildlife Research Progress Reports Available from the Colorado Division of Wildlife Research Library, Fort Collins, Colorado: BERGMAN, E.J., C.J. BISHOP, D.J. FREDDY, AND G.C. WHITE. 2005. Pilot evaluation of winter range habitat treatments on over-winter mule deer fawn survival. Colorado Division of Wildlife, Wildlife Research Report July: 24-35. BERGMAN, E.J., C.J. BISHOP, D.J. FREDDY, AND G.C. WHITE. 2006 In Press. Evaluation of winter range habitat treatments on over-winter mule deer fawn survival. Colorado Division of Wildlife, Wildlife Research Report July: Available September 2006. BISHOP, C.J. AND G.C. WHITE. 2002. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 65-79. BISHOP, C.J., D.J. FREDDY, AND G.C. WHITE. 2002. Pilot study: use of ultrasound and vaginal implants. Colorado Division of Wildlife, Wildlife Research Report July: 81-92. BISHOP, C.J. G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2003. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 33-54. 52 �BISHOP, C.J. G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2004. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 21-43. BISHOP, C.J. G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2004. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 21-43. BISHOP, C.J. G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2005. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 37-65. BISHOP, C.J. G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2006 In Press. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: Available September 2006. Associated Presentations at Professional Workshops/Symposia: BISHOP, C.J., G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2001. Effects of nutrition and habitat enhancements on mule deer fawn recruitment: preliminary results. Fourth Western States and Provinces Deer and Elk Workshop, August 1-3, Wilsonville, Oregon, USA. BISHOP, C.J., G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2003. Effects of enhanced winter nutrition of free-ranging mule deer on fawn recruitment and recruitment. Fifth Western States and Provinces Deer and Elk Workshop, May 21-24, Jackson, Wyoming, USA. BISHOP, C. J., G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2004. The effect of habitat quality on mule deer fawn survival and recruitment: interim report. Society for Range Management 57th Annual Meeting, January 24−30, Salt Lake City, Utah, USA. BISHOP, C. J., G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2004. Effect of enhanced nutrition of free-ranging mule deer on fawn survival and recruitment rates. The Wildlife Society 11th Annual Conference, September 18−22, Calgary, Alberta, Canada. BISHOP, C. J., G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2005. Effect of enhanced nutrition of free-ranging mule deer on population performance. Sixth Western States and Provinces Deer and Elk Workshop, May 16−18, Reno, Nevada, USA. BISHOP, C. J., G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2005. Effect of enhanced nutrition on mule deer population performance in pinyon-juniper habitat. Ecology and Management of Pinyon-Juniper and Sagebrush Communities Workshop, May 16−19, Montrose, Colorado, USA. III. Improve and Evaluate Statewide Systems and Technical Methods Used to Determine Status of Mule Deer Populations. Monitoring the status of mule deer in Colorado has advanced due to the synergy of the research section developing population monitoring systems and terrestrial management section implementing those monitoring systems as appropriate on a statewide basis. Developing, implementing, and maintaining, statistically rigorous systems to estimate statewide hunter harvest of mule deer, population densities and size for selected deer populations, adult female and fawn survival rates for selected populations, and developing future research projects requires scientific input, oversight and periodic evaluations. Additionally, proper evaluation requires a rigorously maintained and updated database containing statewide mule deer population data. As part of a multi-functional quality control process, the CDOW obtains oversight of key statewide mule deer research and management activities via a contract to a qualified individual through this Federal Aid Grant. Result Highlights: 53 �• Provided annual assistance to maintaining and improving statewide deer hunter harvest survey sampling systems and harvest data acquisition. • Provided annual maintenance and oversight of the DEAMAN (Deer-Elk-Antelope-Management) database representing 20 years of statewide data acquisition and storage. Included updating data files, updating user’s manual, converting DEAMAN operating system to Windows 2000 and then Windows XP, and facilitating the conversion of DEAMAN to a server-based operating system. • Provided 1- and 3-day training workshops in 2002 and 2004 in population modeling and use of DEAMAN for up to 18 terrestrial management biologists. Provided annual support to up to 18 management biologists in their day-to-day use of DEAMAN and associated population modeling spreadsheet analyses. • Provided annual assistance to management biologists in analyzing survival rates of adult female and fawn mule deer and estimates of population density and size within 5 key deer populations used to critically assess the statewide trends mule deer. • Provided critical technical expertise and credibility to designing and implementing a public demonstration experiment to evaluate the reliability of Colorado’s methods to estimate mule deer population size and to model mule deer populations. • Provided scientific and technical expertise annually to all facets of the mule deer research program inclusive of experimental designs and approaches to addressing mule deer population estimation techniques, habitat enhancement studies, and spatial analyses of deer as related to the spread of chronic wasting disease. • Senior or co-authored multiple peer-reviewed publications regarding mule deer research and statewide management in Colorado and provided scientific comment and expertise and several professional workshops pertaining to mule deer and other ungulate research and management. Resulting Peer-Reviewed Publications: BISHOP, C.J., G.C. WHITE, D.J. FREDDY, AND B.E. WATKINS. 2005. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin 33:662-668. BOWDEN, D.C., G.C. WHITE, A.B. FRANKLIN, AND J.L. GANEY. 2003. Estimating population size with correlated sampling unit estimates. Journal of Wildlife Management 67:1-10. FREDDY, D.J., G.C. WHITE, M.C. KNEELAND, R.H. KAHN, J.W. UNSWORTH, W.J. DEVERGIE, V.K. GRAHAM, J.H. ELLENBERGER, AND C.H. WAGNER. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. MASON. R., L.H. CARPENTER, M. COX, J.C. DEVOS, JR., J. FAIRCHILD, D.J. FREDDY, J.R. HEFFELFINGER, R.H. KAHN, S.M MCCORQUODALE, D.F. PAC, D. SUMMERS, G.C. WHITE, AND B.K. WILLIAMS. 2006 In Press. A case for standardized ungulate surveys and data management in the western United States. Wildlife Society Bulletin. WHITE, G.C. 2004 In Press. Correcting counts: techniques to de-index. Wildlife Research. WHITE, G.C., D.J. FREDDY, R.B. GILL, AND J.H. ELLENBERGER. 2001. Effect of adult sex ratio on mule deer and elk productivity in Colorado. Journal of Wildlife Management 65: 436444. WHITE, G.C., AND B.C. LUBOW. 2002. Fitting spreadsheet population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. 54 �Associated Annual Wildlife Research Progress Reports Available from the Colorado Division of Wildlife Research Library, Fort Collins, Colorado: FREDDY, D.J. 2002. Deer aerial survey population estimation Rangely deer data analysis unit D6, GMU 10. Colorado Division of Wildlife, Wildlife Research Report July: 117-168. WHITE, G.C. 2002. Improved population modeling-DEAMAN system administration. Colorado Division of Wildlife, Wildlife Research Report July: 93-102. WHITE, G.C. 2003. Multispecies Investigations: consulting services for mark-recapture analysis. Colorado Division of Wildlife, Wildlife Research Report July: 189-196. WHITE, G.C. 2004. Multispecies Investigations: consulting services for mark-recapture analysis. Colorado Division of Wildlife, Wildlife Research Report July: 151-161. WHITE, G.C. 2005. Multispecies Investigations: consulting services for mark-recapture analysis. Colorado Division of Wildlife, Wildlife Research Report July: 67-75. Associated Presentations at Professional Workshops/Symposia: FREDDY, D.J., G.C. WHITE, M.C. KNEELAND, V.K. GRAHAM, W.J. DEVERGIE, J.H. ELLENBERGER, J.W. UNSWORTH, C.H. WAGNER, P.M. SCHNURR, V.W. HOWARD, JR., AND T.S. BICKLE. 2001. Estimating mule deer populatin size using Colorado quadrat system corrected for Idaho mule deer sightability: a sportsmen’s issue. Fourth Western States and Provinces Deer and Elk Workshop, August 1-3, Wilsonville, Oregon, USA. FREDDY, D.J. 2005. Moderator: Session on Representative Strategies. International Association of Fish and Wildlife Agencies Ungulate Data Gathering, Analysis, and Use Workshop, 19 May. Reno, Nevada, USA. WATKINS, B.E., J.H. OLTERMAN, AND T.M. POJAR. 2001. Mule deer survival studies on the Uncompahgre Plateau, Colorado 1997-2001. Fourth Western States and Provinces Deer and Elk Workshop, August 1-3, Wilsonville, Oregon, USA. WAGNER, C.H., B.E. WATKINS, J. VAYHINGER, AND S. STEINERT. 2001. Summary of mule deer survival studies in Colorado, 1997-2001. Fourth Western States and Provinces Deer and Elk Workshop, August 1-3, Wilsonville, Oregon, USA. WHITE, G.C. 2001. Effect of adult sex ratio on mule deer and elk productivity in Colorado. Fourth Western States and Provinces Deer and Elk Workshop, August 1-3, Wilsonville, Oregon, USA. WHITE, G.C. 2005. Featured Speaker: Theoretical considerations and practical implications. International Association of Fish and Wildlife Agencies Ungulate Data Gathering, Analysis, and Use Workshop, 19 May. Reno, Nevada, USA. IV. Assess the Impacts of Chronic Wasting Disease on Mule Deer Populations. Chronic wasting disease (CWD) in mule deer has been a focal point of various research efforts within the CDOW since the early 1990s. Research on CWD was proposed to be funded within this Federal Aid 5-Year Grant. Partial funding from Federal Aid occurred during 2001 but after that year, funding for CWD was obtained from sources other than the Federal Aid Grant. As such, research potentially occurring while Federal Aid funding was in effect was limited to supporting activities associated with publications. Resulting Peer-Reviewed Publications: GROSS, J.E., AND M.W. MILLER. 2001. Chronic wasting disease in mule deer: disease dynamics and control. Journal of Wildlife Management 65:205-215. MILLER, M.W., AND E.S. WILLIAMS. 2002. Detecting PrPCWD in mule deer by immunohistochemistry of lymphoid tissues. Veterinary Record 151:610-612. 55 �WILLIAMS, E.S., AND M.W. MILLER. 2002. Chronic wasting disease in deer and elk in North America. Revue Scientifique et Technique Office International des Epizooties 21:305316. WILLIAMS, E.S., M.W. MILLER, T.J. KREEGER, R.H. KAHN, AND E.T. THORNE. 2002. Chronic wasting disease of deer and elk: a review with recommendations for management. Journal of Wildlife Management 66:551-563. WOLFE, L.L., M.M. CONNER, T.H. BAKER, V.J. DREITZ, K.P. BURNHAM, E.S. WILLIAMS, N.T. HOBBS, AND M.W. MILLER. 2002. Evaluation of antemortem sampling to estimate chronic wasting disease prevalence in free-ranging mule deer. Journal of Wildlife Management 66:564-573. Associated Annual Wildlife Research Progress Reports Available from the Colorado Division of Wildlife Research Library, Fort Collins, Colorado: Miller, M.W. 2002. Chronic wasting disease in mule deer; monitoring and management. Colorado Division of Wildlife, Wildlife Research Report July: 113-116. Associated Presentations at Professional Workshops/Symposia: Conner, M.M. 2005. Increasing the efficacy of chronic wasting disease detection via selective and targeted sampling. Sixth Western States and Provinces Deer and Elk Workshop, May 16−18, Reno, Nevada, USA. V. Develop Alternative Approaches to Control Over-abundant Urban-exurban Mule Deer Populations. An increasing problem with mule deer in Colorado and other states is localized over-abundance of deer in urban-exurban areas. Deer have successfully invaded highly developed human habitats where increasing incidences of browsing damage to lawns, ornamentals, and gardens, and vehicle-deer collisions created the need for some form of deer population control. In these urban-exurban situations, traditional hunting or even highly controlled hunting or culling may not be feasible or socially acceptable. The potential to develop and use hormonal fertility control to reduce net recruitment of deer into these localized populations was recognized by CDOW during the 1990s. Research was initiated to test available hormonal therapies using captive mule deer at the CDOW Foothills Wildlife Research Facility. A portion of this fertility control research was supported by this Federal Aid Grant. After late 2002, other sources of funding were applied to continue this research. Resulting Peer-Reviewed Publications: Baker, D.L., M.A. Wild, M.M. Conner, H.B. Ravivarapu, R.L. Dunn, and T.M. Nett. 2004. Gonadotropin-releasing hormone agonist: a new approach to reversible contraception in female deer. Journal of Wildlife Diseases 40:713-724. Associated Annual Wildlife Research Progress Reports Available from the Colorado Division of Wildlife Research Library, Fort Collins, Colorado: Baker, D.L. 2002. Evaluation of GnRH-PAP as a long-term fertility control agent in female mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 103-112. 56 �SUMMARY Five major multi-year research projects addressing mule deer population limiting factors, habitat status, and habitat enhancements were designed, implemented, completed, and reported upon during this segment. Furthermore, funding partially supported research projects addressing chronic wasting disease and fertility control in mule deer. Additionally, funding provided critical scientific and technical expertise quality control oversight for statewide deer hunter harvest surveys, statewide deer population databases, mule deer survival and population estimate management surveys, mule deer population modeling, and mule deer research projects. LITERATURE CITED BALLARD, W.B., D. LUTZ, T.W. KEEGAN, L.H. CARPENTER, AND J.C. DEVOS, JR. 2001. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin 29:99-115. BISHOP, C.J., AND G.C. WHITE. 2000. Effects of habitat enrichment on mule deer recruitment and survival rates-a program study plan narrative. Colorado Division of Wildlife, Wildlife Research Report July: 135-180. DEVOS, JR., J.C., M.R. CONOVER, AND N.E. HEADRICK (EDITORS). 2003. Mule deer conservation: issues and management strategies. Berryman Institute Press, Utah State University, Logan, USA. GILL, R.B., T.D.I BECK, C.J. BISHOP, D.J. FREDDY, N.T. HOBBS, R.H. KAHN, M.W. MILLER, T.M. POJAR, AND G.C. WHITE. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report 77. Fort Collins, Colorado, USA. HURLEY, M.A., M. SCOTT, AND J.W. UNSWORTH. 2002. Influence of predators on mule deer populations. Federal Aid in Wildlife Restoration, Job Progress Report, Project W-160-R-28. Idaho Department of Fish and Game, Boise, USA. HURLEY, M.A., J.W. UNSWORTH, P. ZAGER, E.O. GARTON, AND D.M. MONTGOMERY. 2005. Mule deer survival and population response to experimental reduction of coyotes and mountain lions. Sixth Western States and Provinces Deer and Elk Workshop, May 16−18, Reno, Nevada, USA. Prepared by ______________________________________ David J. Freddy, Mammals Research Leader 57 �58 �Colorado Division of Wildlife July 2005 − June 2006 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 4 Federal Aid Project: W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Effect of Nutrition and Habitat Enhancements on Mule Deer Recruitment and Survival Rates : Period Covered: July 1, 2005 − June 30, 2006 Authors: C. J. Bishop, G. C. White, D. J. Freddy, and B. E. Watkins All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We measured mule deer (Odocoileus hemionus) population parameters in response to a nutrition enhancement treatment to evaluate the relative importance of habitat quality as a limiting factor of mule deer in western Colorado during November 2000 – January 2005. We conducted preliminary data analyses upon completion of field work. We found strong evidence that enhanced nutrition increased fawn recruitment to the yearling age class. During 2002−2004, fetus-neonate survival from 1 March−15 December was higher (χ21 = 3.846, P = 0.050) for treatment fawns (S(t) = 0.528, SE = 0.027) than control fawns (S(t) = 0.401, SE = 0.025). During 15 December–15 June, 2001−2004, the overwinter survival rate of fawns was greater (χ21 = 18.781, P < 0.001) in the treatment unit (S(t) = 0.895, SE = 0.029) than in the control unit (S(t) = 0.655, SE = 0.044). Using a staggered entry survival process with data combined over years, survival of treatment fetuses to 1 year of age (S(t) = 0.458, SE = 0.031) was 0.18 higher (χ21 = 13.20, P < 0.001) than survival of control fetuses to 1 year of age (S(t) = 0.276, SE = 0.026). The finite rate of population increase, λ, was 1.20 for treatment deer and 1.04 for control deer. Our preliminary results provided a foundation for focusing deer management efforts on improving habitat quality in western Colorado pinyon-juniper (Pinus edulis-Juniperus osteosperma) ecosystems with corresponding research efforts to quantify the effects of habitat manipulations on deer performance. During the past year, we monitored post-treatment adult doe survival, identified a set of publications to be completed for submission to scientific journals, initiated final data analyses corresponding to the set of publications, and worked on or completed several manuscripts. A manuscript on the effectiveness of vaginal implant transmitters was accepted for publication in the Journal of Wildlife Management, and a manuscript documenting malignant catarrhal fever in the deer population was submitted to the Journal of Wildlife Diseases. The lead investigator also wrote a portion of a book chapter regarding the effects of excessive herbivory on mule deer populations. 59 �WILDLIFE RESEARCH REPORT EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES CHAD J. BISHOP, GARY C. WHITE, DAVID J. FREDDY, AND BRUCE E. WATKINS P. N. OBJECTIVE To determine experimentally whether enhancing mule deer nutrition during winter and early spring via supplementation increases fetus survival, neonate survival, overwinter fawn survival, or ultimately, population productivity. SEGMENT OBJECTIVES 1. Radio-monitor and measure post-treatment survival of the sample of radio-collared mule deer adult does. 2. Identify a set of publications to be generated from the research. 3. Initiate final data analyses to support preparation of manuscripts. 4. Prepare manuscripts for submission to scientific journals for publication. INTRODUCTION Mule deer (Odocoileus hemionus) numbers apparently declined during the 1990s throughout much of the West, and have clearly decreased since the peak population levels documented during the 1940s−1960s (Unsworth et al. 1999, Gill et al. 2001). Biologists and sportsmen alike have concerns as to what factors may be responsible for declining population trends. Although previous and current research indicates multiple interacting factors are responsible, habitat and predation have typically received the focus of attention. A number of studies have evaluated whether predator control increases deer survival, yet results are highly variable (Connolly 1981, Ballard et al. 2001). Together, predator control studies with adequate rigor and statistical power indicate predation effects on mule deer are variable as a result of time-specific and site-specific factors. Studies which have demonstrated deer population responses to predator control treatments have failed to determine whether predation is ultimately more limiting than habitat when considering long term population changes. Numerous research studies have evaluated mule deer habitat quality, but virtually no studies have documented population responses to habitat improvements. In many areas where declining deer numbers are of concern, predation is common yet habitat quality appears to have declined. The question remains as to whether predation, habitat, or some other factor is more limiting to mule deer in these situations, and whether habitat quality can be improved for the benefit of deer. It may also be that no single factor is responsible for observed deer declines, and a more comprehensive understanding of multi-factor interactions is needed. We designed and implemented a field experiment where we measured deer population responses to a nutrition enhancement treatment to further understand the causative factors underlying observed deer population dynamics. We conducted the study on the Uncompahgre Plateau in southwest Colorado, where several predator species were present in abundant numbers: coyotes (Canis latrans), mountain lions (Felis concolor), and bears (Ursus americanus). In addition to predation, myriad diseases in combination have proximately affected survival of the Uncompahgre deer population (Pojar and Bowden 2004, B. E. Watkins, Colorado Division of Wildlife, unpublished data). Predator numbers were not manipulated in any manner during the course of the study. All factors were left constant with the exception of deer nutrition. Deer nutrition was enhanced by providing supplemental feed to deer occupying a treatment area during winter. We measured December fawn recruitment and overwinter fawn 60 �survival in response to the treatment to determine whether deer nutrition was ultimately more limiting than predation or disease. A second phase of research was initiated in 2005 to quantify deer population parameters in response to manipulations of pinyon-juniper (Pinus edulis-Juniperus osteosperma) habitat (Bergman et al. 2006). The objective of this research is to determine whether habitat can be effectively improved for mule deer by introducing disturbance into late-seral pinyon-juniper stands. STUDY AREA We non-randomly selected two experimental units (A−B) within mule deer winter range on the Uncompahgre Plateau (Figure 1) to facilitate a cross-over experimental design for evaluating the effects of enhanced deer nutrition during winter on annual population performance. Unit A received a nutrition enhancement treatment during the first 2 winters of research (2000 – 2002) while Unit B served as a control unit. During winters 2002−03 and 2003−04, Unit B received the treatment while Unit A served as the control. In late April and May, prior to fawning, deer from the winter range experimental units migrated to summer range. We defined the summer range study area by movements of the radio-collared deer captured on winter range; summer range encompassed >1000 mi2 covering the southern portion of the Uncompahgre Plateau and adjacent San Juan Mountains (Figure 2). Winter range elevations ranged from 1830 m (6000 ft) in Shavano Valley to 2318 m (7600 ft) adjacent to the Dry Creek Rim above Shavano Valley. Winter range habitat was dominated by pinyon-juniper with interspersed sagebrush adjacent to agricultural fields in the Shavano and Uncompahgre Valleys. Summer range elevations occupied by deer ranged from 1891 m (6200 ft) in the Uncompahgre Valley to 3538 m (11,600 ft) in Imogene Basin southwest of Ouray, CO. Summer range habitats were dominated by spruce-subalpine fir (Picea spp.-Abies lasiocarpa), aspen (Populus tremuloides), sagebrush, ponderosa pine (Pinus ponderosa), Gambel oak (Quercus gambelii), and to a lesser extent, pinyon-juniper at lower elevations. Bishop et al. (2005) provide a detailed study area description. METHODS Refer to Bishop et al. (2005) for field methodology employed during 2000−2005. During fiscal year 2005-06, we continued to monitor radio-collared adult female deer occupying the two experimental units. Our primary research efforts were focused on data analysis and the preparation of manuscripts for publication in scientific journals. The lead investigator completed additional coursework in mathematical statistics, data analysis, and animal nutrition. We submitted or intend to submit the following manuscripts for publication: 1. Effect of enhanced nutrition on the population performance of free-ranging mule deer. Journal of Wildlife Management. a. A separate publication may be submitted to Science focused on the documentation of coyote predation as a compensatory mortality factor during winter. 2. Using vaginal implant transmitters to aid in capture of neonates from marked mule deer. Journal of Wildlife Management. 3. Evaluation of overdispersion in survival analyses of neonate mule deer associated with sibling fawns. Journal of Wildlife Management. 4. Evaluation of serum thyroid hormone levels as an indicator of body condition during late winter. Journal of Wildlife Management. 5. Evaluation of mule deer age and sex ratios as a response variable in field research. Journal of Wildlife Management. 6. Bovine viral diarrhea isolation and seroprevalence in a free-ranging mule deer (Odocoileus hemionus) population in southwest Colorado. Journal of Wildlife Diseases. 7. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer (Odocoileus hemionus) in Colorado. Journal of Wildlife Diseases. 61 �8. Spatial patterns in mortality causes of neonatal mule deer across a land use gradient in southwest Colorado. (This could go to several different journals or be published as an internal CDOW publication.) 9. Disease assessment in a Colorado mule deer population following a decline. Journal of Wildlife Diseases (or internal CDOW publication). RESULTS AND DISCUSSION A comprehensive presentation and discussion of preliminary results was provided by Bishop et al. (2005). These results have not changed and therefore we do not repeat them here. The following manuscript was accepted for publication (Appendix I): Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. Using vaginal implant transmitters to aid in capture of neonates from marked mule deer. Journal of Wildlife Management. The following manuscript was submitted for publication (Appendix II): Schultheiss, P. C., H. Van Campen, T. R. Spraker, C. J. Bishop, L. L. Wolfe, and B. Podell. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer (Odocoileus hemionus) in Colorado. Journal of Wildlife Diseases. The following book chapter was completed and currently undergoing external peer review: Watkins, B. E., C. J. Bishop, E. J. Bergman, A. Bronson, B. Hale, D. W. Lutz, B. F. Wakeling, and L. C. Carpenter. Habitat guidelines for mule deer: Colorado Plateau Ecoregion. Mule Deer Working Group, Western Association of Fish and Wildlife Agencies. The lead investigator completed the following courses to assist with data analysis and manuscript preparation: mathematical statistics (2), population dynamics, population analysis, wildlife nutrition, and animal metabolism. A data bootstrap analysis in SAS was initiated to quantify the degree of overdispersion in our neonate survival data. Overdispersion represents extra-binomial variation in sample data arising from violations of independence. Functionally, undetected overdispersion will result in overly precise variance estimates, and ultimately, incorrect inference. Our neonate samples were subject to independence violations because all captured siblings were routinely radio-collared and treated as independent sample units. A known fates analysis will be conducted using Program MARK to quantify the effect of the nutrition enhancement treatment on various stages of fawn survival while simultaneously accounting for temporal variation and individual heterogeneity (i.e., fawn weight and hind foot length). Once these analyses are completed, we will write and submit manuscripts accordingly. The remaining manuscripts will then be handled in order of priority. Our anticipated timeline is detailed below. Draft manuscripts completed in FY 06-07: 1. Effect of enhanced nutrition on the population performance of free-ranging mule deer. Journal of Wildlife Management. 2. Evaluation of overdispersion in survival analyses of neonate mule deer associated with sibling fawns. Journal of Wildlife Management. 3. Evaluation of serum thyroid hormone levels as an indicator of body condition during late winter. Journal of Wildlife Management. Draft manuscripts completed in FY 07-08: 62 �1. Evaluation of mule deer age and sex ratios as a response variable in field research. Journal of Wildlife Management. 2. Bovine viral diarrhea isolation and seroprevalence in a free-ranging mule deer (Odocoileus hemionus) population in southwest Colorado. Journal of Wildlife Diseases. 3. Spatial patterns in mortality causes of neonatal mule deer across a land use gradient in southwest Colorado. The final proposed manuscript related to disease assessment will be completed as time allows. SUMMARY Enhanced winter nutrition of free-ranging deer caused an increase in both fetus-neonate survival and overwinter fawn survival, resulting in higher yearling recruitment (Bishop et al. 2005). Overwinter adult doe survival increased as a result of the treatment, but annual survival was more similar among treatment and control adult does. Combining all parameter estimates into a deterministic population model, the treatment population indicated an exceptionally high rate of increase (λ = 1.20) while the control population (λ = 1.04) was indicative of the overall Uncompahgre deer population during 2000−2004. The nutrition enhancement treatment was artificial in the sense that we applied it only to test whether habitat quality was ultimately more limiting than predation or other factors. Our results to do not provide support for managing deer populations with nutrition supplements because our treatment delivery approach could not be applied to a large number of animals over a large area. Rather, our results provide a foundation for focusing deer management efforts on improving habitat quality in western Colorado pinyon-juniper ecosystems with corresponding research efforts to quantify the effects of habitat manipulations on deer. We are presently in the process of conducting final data analyses and preparing and submitting manuscripts for publication in scientific journals. LITERATURE CITED BALLARD, W. B., D. LUTZ, T. W. KEEGAN, L. H. CARPENTER, AND J. C. DEVOS, JR. 2001. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin 29:99−115. BERGMAN, E. J., C. J. BISHOP, D. J. FREDDY, AND G. C. WHITE. 2006. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Federal Aid in Wildlife Restoration Project W−185−R, Job Progress Report. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. BISHOP, C. J., G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2005. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Federal Aid in Wildlife Restoration Project W−185−R, Job Progress Report. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. CONNOLLY, G. E. 1981. Limiting factors and population regulation. Pages 245−285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. GILL, R. B., T. D. I. BECK, C. J. BISHOP, D. J. FREDDY, N. T. HOBBS, R. H. KAHN, M. W. MILLER, T. M. POJAR, AND G. C. WHITE. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Denver, USA. POJAR, T. M., AND D. C. BOWDEN. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. UNSWORTH, J. W., D. F. PAC, G. C. WHITE, AND R. M. BARTMANN. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315−326. Prepared by _______________________ Chad J. Bishop, Wildlife Researcher 63 �Year Unit A Unit B 2000-01 Treatment Control 2001-02 Treatment Control 2002-03 Control Treatment 2003-04 Control Treatment Figure 1. Schematic representation of experimental units and nutrition enhancement treatment allocation. Units A and B were located in winter range habitat on the Uncompahgre Plateau in southwest Colorado. The nutrition enhancement cross-over design encompassed 4 years. Uncompahgre Plateau Mesa County GRAND JUNCTION Delta County m co Un GMU 62 r hg pa e Shavano E. U. u ea at Pl Montrose County GMU 61 Sanmiguel County Gunnison County DELTA Winter Range Exp. Units MONTROSE Colona Montrose County Summer Range E.U. Ouray County Figure 2. Location of Colona and Shavano (Units A and B) experimental units on the Uncompahgre Plateau, southwest Colorado; and location of the summer range study area encompassing the southern Uncompahgre Plateau and adjacent San Juan Mountains. 64 �APPENDIX I The following manuscript (referenced here by Abstract) was accepted for publication by the Journal of Wildlife Management. USING VAGINAL IMPLANT TRANSMITTERS TO AID IN CAPTURE OF NEONATES FROM MARKED MULE DEER CHAD J. BISHOP, DAVID J. FREDDY, GARY C. WHITE, BRUCE E. WATKINS, THOMAS R. STEPHENSON, AND LISA L. WOLFE ABSTRACT Measuring reproductive success of previously marked, adult female ungulates enables study of certain ecological factors that limit populations. We evaluated the feasibility and efficiency of capturing large samples (i.e., >80/year) of neonate mule deer (Odocoileus hemionus) exclusively from free-ranging, marked adult does using vaginal implant transmitters (VITs, n = 154) and repeated locations of radiocollared does without VITs. We also evaluated the effectiveness of VITs, when used in conjunction with in utero fetal counts, for obtaining direct estimates of fetal survival. During 2003 and 2004, after VIT batteries were placed on a 12-hour duty cycle to lower electronic failure rates, the proportion of VITs that shed ≤3 days prepartum or during parturition was 0.623 (SE = 0.0456), and the proportion shed only during parturition was 0.447 (SE = 0.0468). Our neonate capture success rate was 0.880 (SE = 0.0359) from does with VITs shed ≤3 days prepartum or during parturition and 0.307 (SE = 0.0235) from radiocollared does without VITs or whose implants failed to function properly. Using a combination of techniques, we captured 275 neonates and found 21 stillborns during 2002−2004. We accounted for all fetuses at birth (i.e., live or stillborn) from 78 of the 147 does (0.531, SE = 0.0413) having winter fetal counts, and this rate was heavily dependent on VIT retention success. Deer that shed VITs prepartum were larger than deer that retained VITs to parturition, indicating a need to develop variable-sized VITs that may be fitted individually to deer in the field. We demonstrated that direct estimates of fetal and neonatal survival may be obtained from previously marked female mule deer in free-ranging populations, thus expanding opportunities for conducting field experiments. Survival estimates using VITs lacked bias that is typically associated with other neonate capture techniques. However, current vaginal implant failure rates, and overall expense, limit broad applicability of the technique. 65 �APPENDIX II The following manuscript (referenced here by Abstract) was submitted to the Journal of Wildlife Diseases. MALIGNANT CATARRHAL FEVER ASSOCIATED WITH OVINE HERPESVIRUS-2 IN FREERANGING MULE DEER (Odocoileus hemionus) IN COLORADO PATRICIA C. SCHULTHEISS, HANA VAN CAMPEN, TERRY R. SPRAKER, CHAD J. BISHOP, LISA L. WOLFE, AND BRENDAN PODELL ABSTRACT Malignant catarrhal fever (MCF) was diagnosed in 4 free-ranging mule deer (Odocoileus hemionus) in January and February of 2003. Diagnosis was based on typical histologic lesions of lymphocytic vasculitis and PCR identification of ovine herpesvirus-2 (OHV-2) viral genetic sequences in formalin fixed tissues. The animals were from the Uncompahgre Plateau of southwestern Colorado. Deer from these herds occasionally resided in close proximity to domestic sheep (Ovis aries), the reservoir host of OHV-2, in agricultural valleys adjacent to their winter range. These cases indicate that fatal OHV-2 associated MCF can occur in free-ranging mule deer exposed to domestic sheep that overlap their range. 66 �Colorado Division of Wildlife July 2005 – June 2006 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 2 Federal Aid Project W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Evaluation of Winter Range Habitat Treatments on Over-Winter Survival and Body Condition of Mule Deer. : Period Covered: July 1, 2005 - June 30, 2006 Author: E.J. Bergman; project cooperators, C.J. Bishop, D.J. Freddy and G.C. White Personnel: L. Baeten, D. Baker, B. Banulis, J. Boss, A. Cline, D. Coven, M. Cowardin, K. Crane, B. deVergie, K. Duckett, D. Hale, C. Harty, E. Joyce, R. Lockwood, J. McMillan, M. Michaels, G. Miller, M. Miller, M. Sirochman, T. Sirochman, R. Swygman, C. Tucker, B. Watkins, L. Wolfe, M. Zeaman CDOW, L. Carpenter - Wildlife Management Institute, D. Felix - Olathe Spray Service, P. Johnston and R. Swisher - Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We designed and initiated a multi-year, multi-area study to assess the impacts of landscape level winter range habitat improvement treatments on mule deer population performance on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado. During this first year, we measured all response variables on 5 study areas. Compared to results from other research throughout the west, as well as on the Uncompahgre Plateau, survival estimates for 6-month old mule deer fawns were high (mean survival rate of 0.82 (.036 SE)) for the winter of 2005-2006. Preliminary evidence suggests that areas that have received habitat treatments may positively influence survival. However, based on estimates of total body fat for adult female deer, there was no apparent distinction between our habitat treatment study areas. Point estimates of deer density on the 5 study areas during the winter of 2005-2006 confirmed the latitudinal trend that areas on the northern portion of the Uncompahgre Plateau typically have lower deer densities than the southern portion of the Plateau. Due to overlap of 95% confidence intervals for our deer density estimates, a refinement of sampling techniques will be implemented for future years of this study. 67 �WILDLIFE RESEARCH REPORT EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER. ERIC J. BERGMAN P.N. OBJECTIVE 1. To assess whether mechanical/chemical habitat treatments increase over-winter fawn survival. 2. To assess whether mechanical/chemical habitat treatments increase the local carrying capacity of deer, measured through deer density. 3. To assess whether the impacts of enhancing mule deer habitat via mechanical/chemical habitat treatments can be detected through improvement of adult doe body condition. SEGMENT OBJECTIVES 1. Capture and radio-collar the minimum necessary sample (n=25) of 6 month-old fawns during November through early January in each of 5 study areas. 2. Measure overwinter fawn survival from mid-December through mid-June. 3. Estimate late-winter deer densities in each study area via helicopter resighting of marked deer. 4. Capture and sample a minimum number of adult female deer (n=30) to estimate late-winter body condition in 2 study areas. INTRODUCTION A common trend among many terrestrial, mammalian systems is a tendency to cycle between population highs and lows (Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001, Clutton-Brock and Pemberton 2004). While the true cause of these cycles is likely a merger of habitat quality, weather, disease, predation, sport hunting, competition and community population dynamics, it is often necessary or intriguing for wildlife managers and ecologists to identify the primary limiting factor to population growth. Without exception, mule deer populations have also demonstrated a tendency to show large fluctuations. Several dramatic declines have been observed since the turn of the 19th century (Connolly 1981, Gill 2001, Hurley and Zager 2004). However, only one period of increase, a general trend during the 1940's and 1950's, has been noted. The most recent and pressing decline took place during the 1990's (Unsworth et al. 1999). Colorado has not escaped these tendencies, with certain parts of the state experiencing population declines by as much as 50% between the 1960's and present time (Gill 2001, B. Watkins personal communication). Primarily due to the value of mule deer as a big game hunting species, wildlife managers' challenges are two-fold: understanding the underlying causes of mule deer population change and managing populations to dampen the effects of these fluctuations. In Colorado, the role of habitat as the limiting factor for mule deer populations was recently tested. Specifically, the role of forage quality and quantity on over-winter fawn survival was tested using a treatment/control cross-over design with ad libitum pelleted food supplements as a substitute for instantaneous high quality habitat improvements (Bishop et al. 2004). The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e. if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the primary limiting factor on populations. As such, preliminary evidence suggests that nutrition enhancement treatments increased fawn survival by as much as 20% (C.J. Bishop, personal communication). This research effectively identified some of the underlying processes in mule deer population regulation, but did not test the effectiveness of acceptable 68 �habitat management techniques. Due to the undesirable effects of feeding wildlife (e.g. artificially elevating density, increased potential for disease transmission and cost), a more appropriate technique for achieving a high quality nutrition enhancement needs to be assessed. Based on this past research and the above mentioned objectives, we designed and initiated a multi-year, multi-area study to assess the impacts of landscape level winter range treatments on mule deer population performance. This study is being conducted on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado. Due to the active habitat treatment history in this area, the Uncompahgre Plateau stood out as the most opportune place for addressing these issues. Additionally, there are several tracts from 2 state wildlife areas that are located in key locations, thereby allowing additional habitat treatments to occur on the level and schedule necessary of this project. To assess the impacts of habitat treatments on mule deer in these areas, we will measure overwinter fawn survival, mule deer density and late winter body condition. STUDY AREA At the onset (Bergman et al. 2005, Appendix I), we identified 2 pairs of treatment/control study areas, stratified into historically known high and low deer density areas. The selection process for these pairs of experimental units followed several strict guidelines: 1) Treatment/control units could not be further than 10km apart, but needed to have adequate buffer to minimize the movement of animals between the treatment and control areas. 2) Control study areas could not have received any mechanical treatment during the past 30 years. 3) Strata were defined by winter range type (all experimental units had to be in pinyon/juniper winter range) and deer density. 4) Treatment units needed to have received mechanical treatment in the past, but also had to be capable of receiving further treatments during the study period. A 5th study area (Shavano Valley, 20 km2) was added to increase the level of inference that could be drawn from this study. The existing treatments on this 5th area occurred on two occasions. During the late 1960's, parts of this area was anchor chained. During the early 2000's, these areas were retreated with rollerchopping. In total, ~14.5 km2 were treated out of the 20 km2 within this study area. The high density treatment area is located on Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). The high density control area is located around Beaton Creek (approximately 15km south of Montrose, CO and approximately 5km north of Billy Creek State Wildlife Area). Both of the high density study areas are located in GMU 65 (DAU D-40). The low density treatment area is located on Peach Orchard Point, on/near Escalante State Wildlife Area (approximately 25km southwest of Delta, CO). The low density control area is located on Sowbelly and Tatum draws (approximately 25km west of Delta, CO and approximately 8km from Peach Orchard Point). Both of the low density study areas are located in GMU 62 (DAU D-19). Shavano Valley was also located in GMU 62 (DAU D-19) to the west of Montrose, CO (see figure of study areas in Appendix I). METHODS Twenty-five mule deer fawns were captured and radio-collared in each of the 5 study areas. Fawns were captured via baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) and helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) between mid-November and lateDecember. Fawns were fitted with radio collars made of vinyl belting and equipped with mortality sensors, which after remaining motionless for 4 hours, increase the pulse rate of received signals. To make fawn collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars after approximately 6 months. 69 �On a daily basis, from December through May, we monitored the radioed fawns in order to document live/death status. This allowed us to determine accurately the date of death and estimate the proximate cause of death. Daily monitoring was done from the ground to maximize efficient collection of mortalities and assessment of cause specific mortality. Weekly aerial telemetry flights were conducted to insure that all deer were heard at least once a week, allowing weekly survival estimates for each study area. To estimate body composition, an additional 30 adult female deer were captured via helicopter net-gunning and fitted with permanent radio-collars, also having mortality sensors, in late February within each of 2 study areas; our low density control area and on our high density treatment area. For body condition work, we relied on methods that employed the use of ultrasonography to estimate total body fat (Stephenson et al. 1998, Cook 2000, Stephenson et al. 2002). Blood samples were also collected for endocrinology and pregnancy tests. During late winter (early-March) we estimated deer density on each of our study areas. Helicopter based mark-resight techniques were used for density estimation (Gill 1969, Bartmann et al. 1986, Kufeld et al. 1980, Freddy et al. 2004). Preliminary survival analyses were conducted on this first year of data, plus data collected during a pilot year. In addition to including individual covariates (fawn sex and mass), we wished to explore the role of habitat treatment history on survival. Due to the preliminary nature of these analyses and the ongoing status of the habitat treatment work, we did not attempt to rank individual study areas. Rather, our analyses were conducted such that areas were included and compared using two different approaches. With the first approach, areas were included as either treated or untreated. The second approach allowed for 3 levels of habitat treatment intensity (untreated, single treatment or ongoing treatments). All survival models were conducted in program MARK (White and Burnham 1999). Known-fate models were tested using the logit link function. All models are compared using Akaike's Information Criterion corrected for small sample size (Burnham and Anderson 2003). RESULTS AND DISCUSSION Minimum necessary sample sizes were met in all study areas for all components of this research (n = 25 fawns per area, n = 30 adult females for body condition). Capture related mortalities occurred on 3 of 188 occasions (1.6%, 1 of 127 fawns, 2 of 61 does). Mean mass of all fawns was 36.3 kg (Table. 1). Compared to results from other research throughout the west, as well as on the Uncompahgre Plateau, estimates of fawn survival for the winter of 2005-2006 were high (Unsworth et al. 1999, Bishop et al. 2004). Across our 5 study areas, estimated survival rates ranged between 0.76 (.085 SE) and 0.88 (.065), with mean survival rate of 0.82 (.036) (Table 2). While these rates are lower than those measured during the pilot year of this research, they remain higher than average (Bergman et al. 2005). Based on anecdotal climate information, we suspect that winter conditions during these past two winters have been much milder than what historically is considered an average winter. Preliminary survival models indicate that the single most influential parameter affecting overwinter fawn survival has been fawn mass as was documented by Bishop et al. (2004). Additionally, the survival model composed solely of fawn mass was also the most parsimonious of all models (Table 3). However, based on ∆AICc scores, there was minimal differentiation between models also including sex and study area (with study area being classified as either treatment or control). While model weights preliminarily indicate that study area treatment history is not the strongest variable influencing survival, our data suggests that habitat treatments positively influence survival. While models including study area 70 �treatment intensity were consistently within a ∆AICc score of 3 of the most supported model, the weights for these models were quite low. We feel the lack of support for these models is an artifact of the preliminary nature of these analyses and the small number of study areas included. When categorized by treatment intensity, 7 study areas are split into 3 categories. When categorized as treatment/control, 7 study areas are split into 2 categories. As the study progresses and more study areas are included, a treatment intensity effect is likely to be more supported, if an intensity effect exists. Similar to the trend observed with overwinter survival, late winter body condition estimates for adult females during the winter of 2005-2006 were higher than those collected during previous winters on the Uncompahgre Plateau (Bishop et al. 2004 and C.J. Bishop, personal communication). However, based on estimates of total body fat, there was no apparent distinction between our study areas. While significant differences (p = .009) in the levels of the T3 hormone (nmol/l) were observed between study areas, this did not appear to translate to differences in body condition or survival (Table 4). Based on blood samples drawn at the time of capture, differences in pregnancy rates, based on PSPB and prevalence of disease titers (BT and EHD) between study areas were not observed. Overall, pregnancy rates were high in both study areas (BCSWA = 29/29, Sowbelly = 27/29). Titers for BT were observed at low/moderate rates in both study areas (BCSWA = 8/29, Sowbelly = 7/29), as were titers for EHD (BCSWA = 8/29, Sowbelly = 5/29). Point estimates of deer density on the 5 study areas during the winter of 2005-2006 confirmed the latitudinal trend that has been historically observed (i.e. areas on the northern portion of the Uncompahgre Plateau typically have lower deer densities than the southern portions of the Plateau) (Fig. 1). However, there was almost universal overlap of 95% confidence intervals between study areas, weakening any conclusions that can be drawn from these data. Based on these results, a refinement of sampling techniques is needed and more resources need to be directed towards density estimation. In particular, during future years we will increase the total number of flights and the overall percent of the population marked in each high density study area (Fig. 2). SUMMARY Survival rates for mule deer fawns across our study areas averaged 82% with a measured high of 88% and measured low of 76%. Overall body condition parameter estimates for late-winter adult female deer were high, highlighting the general mild winter conditions that were observed throughout deer winter range in southwestern Colorado. Preliminary evidence of higher deer survival in treatment areas was observed, but data were not strong enough to draw strong conclusions at this preliminary stage. Estimates of total deer density across our study areas are in line with historical estimates, however, overall precision of our estimates need to be improved before habitat treatment effects can potentially be detected. LITERATURE CITED BARRETT, M.W., J.W. NOLAN, and L.D. ROY. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. BARTMANN, R.M., L.H. CARPENTER, R.A. GARROTT, and D.C. BOWDEN. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. —————, G.C. WHITE, and L.H. CARPENTER. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. BERGMAN, E.J., C.J. BISHOP, D.J. FREDDY, G.C. WHITE. 2005. Pilot evaluation of winter range habitat treatments of mule deer fawn over-winter survival. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. 71 �BISHOP, C.J., G.C. WHITE, D. J. FREDDY, and B.E. WATKINS. 2004. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. BURNHAM, K.P. and D.R. ANDERSON. 2003. Model selection and multi-model inference. Springer, New York, USA. CLUTTON-BROCK, T., and J. PEMBERTON, editors. 2004. Soay sheep: dynamics and selection in an island population. Cambridge University Press, UK. CONNOLLY, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. COOK, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain Elk. Thesis, University of Idaho, Moscow, USA. FREDDY, D.J., G.C. WHITE, M.C. KNEELAND, R.H. KAHN, J.W. UNSWORTH, W.J. DEVERGIE, V.K. GRAHAM, J.H. ELLENBERGER, and C.H. WAGNER. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. GILL, R.B. 1969. A quadrat count system for estimating game populations. Colorado Division of Game, Fish and Parks, Game Information Leaflet 76. Fort Collins, USA. ————— 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. HURLEY, M., and P. ZAGER. 2004. Southeast mule deer ecology - Study I: Influence of predators on mule deer populations. Progress Report, Idaho Department of Fish and Game, Boise, USA. JEDRZEJEWSKA, B., and W. JEDRZEJEWSKI. 1998. Predation in Vertebrate Communities: the Białowieża Primeval Forest as a case study. Springer-Verlag, Berlin, Germany. KREBS, C.J., S. BOUTIN, and R. BOONSTRA, editors. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. KUFELD, R.C., J.H. OLTERMAN, AND D.C. BOWDEN. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. RAMSEY, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. SCHMIDT, R.L., W.H. RUTHERFORD, and F.M. BODENHAM. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. STEPHENSON, T.R., V.C. BLEICH, B.M. PIERCE, and G.P. MULCAHY. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. ————— , T. R., K. J. HUNDERTMARK, C. C. SCHWARTZ, and V. VAN BALLENBERGHE. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717-722. UNSWORTH, J.W., D.F. PAC, G.C. WHITE, and R.M. BARTMANN. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. VAN REENEN, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. WHITE, G.C., and R.M. BARTMANN. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. __________, and K. P. BURNHAM. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Prepared by Eric J. Bergman, Wildlife Researcher 72 �Table 1. Mass (mean + SE) and sex of mule deer fawns captured on the Uncompahgre Plateau from lateNovember through early-January of each year. All fawns were captured by baited drop-nets or helicopter net-gunning. Area BCSWA Sowbelly BCSWA Buckhorn Shavano Peach Orchard Sowbelly Year 2004 2004 2005 2005 2005 2005 2005 Mean Mass Males Females Total 36.8 (12) 35.6 (13) 36.1 (26) 35.4 (10) 34.7 (15) 35.0 (25) 37.1 (14) 32.0 (11) 34.9 (25) 37.4 (11) 35.0 (15) 36.0 (26) 39.4 (11) 37.2 (14) 38.2 (25) 37.0 (11) 35.3 (14) 36.1 (25) 37.1 (16) 34.2 (9) 36.1 (25) Table 2. Overwinter mule deer fawn survival rates for study areas across the Uncompahgre Plateau, 2005-2006. Study areas designated with asterisks are areas where fawns were captured above winter range in the transitional habitat zone. Fawns from this zone were expected to winter on the Sowbelly study area. However, 12 of these deer wintered on a separate study area, 5 wintered on Sowbelly and 8 were ultimately censored due to collar failure. Sample size equals 25 fawns in each area. Area BCSWA Buckhorn Shavano Peach Orchard Sowbelly* Other* Ŝ (S.E.) 0.83 (.076) 0.76 (.088) 0.76 (.085) 0.88 (.065) 1.00 (.000) 0.83 (.108) 73 �Table 3. Preliminary survival model results for radio collared fawns from the winters of 2004-2005 and 2005-2006. Models including year as a covariate were not competitive, based on ∆AICc values. Model Mass Mass + Sex TreatmentControl + Mass TreatmentControl + Mass + Sex TreatmentIntensity + Mass TreatmentIntensity + Mass + Sex TreatmentControl Sex Treatment Intensity Area TreatmentIntensity + Sex AICc 300.152 301.182 301.237 302.164 302.808 303.789 305.199 305.570 306.755 307.578 308.652 ΔAICc 0.00 1.03 1.09 2.01 2.66 3.64 5.05 5.42 6.60 7.43 8.50 ωi 0.313 0.187 0.182 0.114 0.083 0.051 0.025 0.021 0.012 0.008 0.004 Table 4. Late-winter body condition estimates for female adult mule deer from 2 study areas on the Uncompahgre Plateau, 2005-2006. Parameters designated with an asterisk indicate a significant difference (p ≤ .05) existed between study areas. Sample sizes were 29 does in each area. Mean T3 and T4 samples are reported in nmol/l. Area Parameter % Body Fat T3* T4 BCSWA Sowbelly 8.80% (2.02 S.E.) 9.81% (2.88 S.E.) 1.12 (0.28 S.E.) 1.41 (0.51 S.E.) 70.69 (20.94 S.E.) 79.97 (15.80 S.E.) 74 �120 100 Deer/km 80 60 40 20 0 Sowbelly PeachOrchard Shavano Buckhorn BillyCreek Figure 1. Deer density estimates, based on helicopter mark-resight flights, in all study areas, 20052006. Density estimates confirmed a priori expectations of latitudinal gradients from low in the northern (Sowbelly) to high in the southern (Billy Creek) study areas, based on historical density information. During future years of the study, between year variation within each study area will help identify treatment effects. 1200 # of Deer 1000 800 600 400 200 0 3 4 5 6 # of Flights Figure 2. Simulated precision of mark-resight density estimates for areas with high deer densities. Different lines represent estimates of precision for varying percentages of the population marked. Bold solid lines depict estimates for 5% of the population, small dotted lines depict estimates for 7.5% of the population and bold dashed lines depict estimates for 10% of the population marked. During future years, six sampling flights will occur. We will also attempt to increase the proportion of the population marked via temporary marking techniques. 75 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2005-06 - 2008-09 State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 2 : Division of Wildlife : Mammals Research : Deer Conservation : Evaluation of Winter Range Habitat Treatments On Over-winter Survival and Body Condition of Mule Deer : Federal Aid Project No.:W-185-R Evaluation of Winter Range Habitat Treatments on Overwinter Survival and Body Condition of Mule Deer. Principal Investigators Eric J. Bergman, Wildlife Researcher, Mammals Research Chad J. Bishop, Wildlife Researcher, Mammals Research David J. Freddy, Mammals Research Leader Gary C. White, Professor of Wildlife Biology, Colorado State University Cooperators Brad Banulis, Terrestrial Biologist Bruce Watkins, State Big Game Analyst Area 18 Personnel Study Plan Approval Prepared by: Date: Submitted by: Date: Reviewed by: Date: Date: Date: Reviewed by: Date: Biometrician Date: Approved by: Mammals Research Leader 76 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. A research study proposal submitted by: E.J. Bergman, Colorado Division of Wildlife C.J. Bishop, Colorado Division of Wildlife G.C. White, Colorado State University D.J. Freddy, Colorado Division of Wildlife A. NEED A common trend among many terrestrial, mammalian systems is a tendency to cycle between population highs and lows (Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001, Clutton-Brock and Pemberton 2004). While the true cause of these cycles is likely a merger of habitat quality, weather, disease, predation, sport hunting, competition and community population dynamics, it is often necessary or intriguing for wildlife managers and ecologists to identify the primary limiting factor to population growth. Without exception, mule deer populations have demonstrated a tendency to show large fluctuations. Several dramatic declines have been observed since the turn of the 19th century (Connolly 1981, Gill 2001, Hurly and Zager 2004). In summary, a general increase in mule deer populations was observed as early as the 1920's, with subsequent peak numbers being observed during the 1940's through the early-1960's. A subsequent decline occurred during the late-1960's through the 1970's. An increase was again observed during the 1980's before the most recent and pressing decline occurred during the early-1990's (Unsworth et al. 1999). Colorado has not escaped these tendencies, with certain parts of the state experiencing population declines by as much as 50% between the 1960's and present time (Gill 2001, B. Watkins personal communication). Primarily due to the value of mule deer as a big game hunting species, wildlife managers' challenges are two-fold: understanding the underlying causes of mule deer population change and managing populations to dampen the effects of these fluctuations. Management efforts to regulate populations have traditionally encompassed a number of approaches including predator control, interspecific/intraspecific competition and efforts to regulate habitat. Of specific interest to this study, state and federal land management agencies have conducted large scale habitat treatments under the guise of improving habitat quality for wildlife over the past 40 years. Many treatments have attempted to directly increase the quality of winter range for mule deer. Additionally, programs such as the Habitat Evaluation Program (HEP) (USFWS 1976) have been developed to assess habitat quality for different species, including mule deer. However, experimental research connecting mule deer population performance to actual habitat quality has been minimal (Kie et al. 1980, Kie 1984). As such, habitat evaluation programs that measure the productivity and availability of browse species, as well as assess cover quality, cannot be directly translated into deer population performance. The nature of the relationship between improving habitat quality and population performance needs to be concretely established to facilitate future habitat management efforts and before habitat evaluation programs can reliably be used to predict deer response to habitat management. Past Research As a result of the numerous objectives and challenges surrounding mule deer management, considerable amounts of energy and money have been invested in assessing the role of different factors on mule deer populations. During the past 15 years the role of predation and habitat quality as limiting factors have been experimentally tested in a number of ways (Bartmann et al. 1992, Hurly and Zager 2004, Bishop et al. 2005). Initial work conducted in Colorado used experimental manipulation to test the 77 �hypothesis of compensatory mortality. Results from this work demonstrated that density played an ultimate role in population performance, whereas the function of predators was found to be a proximate source of mortality. More recently, collaborative research conducted by the Colorado Division of Wildlife and Idaho Fish and Game has further assessed the roles of predators and habitat on over-winter fawn survival. In Idaho, the effect of predator removal on over-winter fawn survival was experimentally tested by applying different levels of predator control to different study areas. No positive effect on fawn survival was observed through these experiments and significant changes in population trends were not observed (M. Hurly, personal communication). In Colorado, the role of forage quality and quantity on over-winter fawn survival was tested using a treatment/control cross-over design with ad libitum pelleted food supplements as a substitute for instantaneous high quality habitat (Bishop et al. 2005). The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e. if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the primary limiting factor on populations. As such, preliminary evidence suggests that nutrition enhancement treatments increased fawn survival by as much as 20% (C.J. Bishop, personal communication). This research effectively identified some of the underlying processes in mule deer population regulation, but did not test the effectiveness of acceptable habitat management techniques. Due to the undesirable effects of feeding wildlife (e.g. artificially elevating density, increased potential for disease transmission, cost and manpower), a more appropriate technique for achieving a high quality nutrition enhancement needs to be assessed. Based on this past research, there is an increasing amount of evidence that habitat plays the central role in mule deer population performance. Mule Deer Response Mule deer can be expected to respond to effective habitat improvements at variable rates and in a number of ways. A basic assumption of how mule deer respond to improved habitat quality is that fawn survival is elevated in higher quality areas for as long as a treatment effect is maintained. However, fawn survival is highly variable and also has the ability to remain exceptionally high for short periods under optimum weather conditions. Therefore, an alternative scenario is that a pulse of very high survival would be followed by an increase in density and a subsequent return to moderate survival rates. In this case, habitat treatment effects would be observed primarily through increased deer density. However, uncertainty regarding the impact of habitat improvement efforts also exists due to the difficulty in determining if treatment effects are actually delivered to deer. While increases in forage quality and quantity improve survival if they are present at ad libitum levels, as suggested by supplemental feeding, the levels attained via landscape manipulations may be effectively too low to detect. In this case, the use of over-winter fawn survival as the sole parameter for determining if a treatment was delivered may be inappropriate and the potential for making a Type II error would be high. Therefore, a more sensitive measurement of treatment effect may be rooted in the body condition of adult female mule deer. As observed in past research (C.J. Bishop, personal communication), an effect of providing ad libitum food as a substitute for habitat improvement was an increase from 4% to 10% in estimable total body fat. With landscape level manipulations increases would be expected to be substantially smaller, though still measurable. While a direct link between adult body condition and fawn survival hasn't been made, body condition can serve as an indicator of whether a landscape treatment was delivered. B. OBJECTIVES 1. To conduct a one-year pilot study to assess the logistical feasibility of the proposed study herein and to gather preliminary data to improve the study’s efficiency and experimental design (completed during 2004-2005). 2. To determine if habitat improvement efforts change the density and biomass of preferred mule deer browse species. 78 �3. To determine experimentally (assuming a positive increase occurs under objective 2) whether enhancing mule deer nutrition during winter and early-spring via mechanical/chemical habitat treatments increases over-winter fawn survival. 4. To determine experimentally (assuming a positive increase occurs under objective 2) whether enhancing mule deer nutrition during winter and early-spring via mechanical/chemical habitat treatments increases the local carrying capacity of treatment areas, measured through deer density. 5. To assess whether the impacts of enhancing mule deer habitat via mechanical/chemical habitat treatments (assuming a positive increase occurs under objective 2) can be detected through measurement of adult doe body condition. Null Hypotheses a. Landscape level treatments on mule deer winter range do not increase the density and biomass of preferred mule deer browse species. b. Over-winter survival of fawns in habitat treatment areas is not different from survival of fawns in nontreated control areas. c. Mid-winter density of deer in habitat treatment areas is not different from mid-winter density of deer in non-treated control areas. d. Late-winter body condition of adult female deer in habitat treatment areas is not different from latewinter body condition of adult female deer that occupy non-treated control areas. C. EXPECTED RESULTS A need for information relating mule deer population response to habitat improvement efforts currently exists. This study, measuring over-winter fawn survival on a total of six treatment areas and two control areas, will evaluate whether traditional habitat management approaches have measurable population level impacts on mule deer. We will accomplish this by monitoring over-winter mule deer fawn survival, total deer density and adult female body condition in relation to controlled habitat treatments. Across much of the mule deer range in North America, and substantiated by historical data for the Uncompahgre Plateau, resource limitation for deer typically occurs on winter range (Carpenter and Wallmo 1981, C. J. Bishop, unpublished data). If a population level response (change in survival or density) is detected during this study, then we will establish that certain landscape management practices are beneficial to mule deer. If a population level response (change in survival or density) is not detected during this study, yet a change in adult female body condition is detected, we can deduce that current habitat management efforts do impact mule deer populations. However, under this scenario, if treatments impact population performance parameters, these responses occur over longer time periods and at finer scales than we are capable of detecting. If neither a population level response (change in survival or density) nor a change in adult female body condition is detected during this study, we will know that our current habitat management practices are in need of refinement in order to more efficiently benefit mule deer. D. APPROACH 1. Pilot Study One winter of pilot data collection has occurred. The reasons for using this first winter as a pilot study were two-fold: 1) To determine feasibility of capture and monitoring in the chosen study areas. One control study area is located in an area that historically has had low deer densities, has never received habitat treatments and is not close in proximity to agricultural lands (see Experimental Approach and Habitat Manipulations). It was unknown if deer densities were high enough to meet minimum sample size requirements in this area. Due to the remote location of this study site, helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) is the only feasible capture technique. Helicopter net-gunning can become cost prohibitive in low 79 �density areas, emphasizing the need to test this approach prior to committing to four additional years. In a separate study area, densities of both deer and elk are traditionally higher, possibly due to the extensive number of habitat treatments and higher proximity to agricultural fields (hay, alfalfa and/or grass). Because this second area is easily accessible from roads, baited drop nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) are the preferred method of capture. However, the feasibility and efficiency of drop nets also needed to be evaluated in light of elk presence. By assessing these potential problems through a pilot study, we improved the efficiency and design of this final research study design. 2) To collect one year of data in both high and low density areas prior to instituting an experiment in the treatment areas. This will allow us to improve our estimates of process variation in fawn survival, because fawn survival has been shown to vary significantly among areas and years (Unsworth et al. 1999, Bishop et al. 2005). Based on results of our pilot study, our ability to meet adequate sample size requirements in the low density area was confirmed. Deer densities were sufficiently high to allow helicopter net-gunning to occur at lower capture rates. All deer were captured within 1.5 days of capture effort. Concerns over non-target capture of elk in the high density area were also addressed during the pilot study. Elk presence in the study area and around drop-nets during the time of capture was moderate to high. However, capture of elk was minimized (i.e. limited to a single animal) and there were no threats to human safety, animal safety or destruction of equipment. The confounding of capture methods did not introduce measurable bias into our results as no capture myopathy mortalities occurred. The need to assess process variation in over-winter fawn survival was justified; measured survival rates in both study areas were high relative to reported rates (low density ŝ = 0.96 (UCI = 0.963, LCI = 0.956), high density ŝ = 0.84 (UCI = 0.829, LCI = 0.851)). 2. Experimental Approach a. Experimental Units During the next 4 years, we will measure all response variables on a total of 8 study areas. Due to the abundance of mechanical treatments across the Uncompahgre Plateau (see Habitat Manipulations) and in surrounding valleys, we were unable to randomly select which areas could be maintained as controls (i.e. areas already having received a mechanical treatment could not be used as a control). As such, a mixed design with paired treatment/controls, with additional pre-treated areas was necessary. Four areas on or near the Uncompahgre Plateau were selected as the treatment/control experimental units (Fig. 1). These 4 experimental areas are stratified into known high density and low density areas. Within each stratum, one area has been identified as a treatment area while the other will be maintained as a control area (Table 1). The selection process for these experimental units followed several strict guidelines: 1) Treatment/control units could not be further than 10km apart, but needed to have adequate buffer to prevent/minimize the movement of animals between the treatment and control areas. 2) Control study areas could not have received any mechanical treatment during the past 30 years. 3) Strata were defined by winter range type (all experimental units had to be in pinyon/juniper winter range) and deer density. 4) Treatment units needed to have received mechanical treatment in the past, but also had to be capable of receiving further treatments during the study. 5) Elk presence and density, relative to deer density, needed to be consistent across all study areas. Data collection throughout the pilot year of this study confirmed that while elk are present, elk density appears to be highly correlated with deer density on all study areas. In light of potential elk response to habitat treatments during this study, the general presence/absence of elk on each study area will be noted during weekly monitoring activities. As mentioned above, we will also measure over-winter fawn survival on a 5th, pre-treated, study area each winter (Table 1). This 5th study area was added to increase the level of inference that could be drawn from this study. As such, the 5th study area will randomly change between 4 areas with existing treatments on an annual basis (Fig. 1 & Table 1). The existing treatments on these 4 areas were 80 �conducted within the last 10 years and were primarily composed of roller-chopping or hydro-ax disturbances (Appendix 1). Pre-treated study areas were selected using a stratified, random sampling approach, without replacement. Study areas were stratified by identifying locations with known treatment histories between the previously identified treatment/control pairs (i.e. between Sowbelly and Billy Creek). Areas identified where then buffered to minimize the capture and marking of deer that might move away from the targeted treatments and the year which they will be included in the study was randomly assigned, without replacement. Regardless of type (control, treatment or pre-treated), all study areas were initially drawn such that they include the targeted treatments, but also account for geographical features that likely serve as natural barriers to movement. As such, our hypotheses will be tested on 6 treatment areas over a 4 year period. b. Response Variables To allow for competing hypotheses in regards to potential treatment effects, 3 primary response variables will be measured. 1) To determine if habitat treatments elicit a chronic survival response with a long-term population level effect, we will measure over-winter fawn survival in all experimental units (s-fawnstreatment vs. s-fawns control). Based on past research, treatment effects can elicit as much as a 20% increase in survival. Power calculations were structured such that minimum sample size requirements will provide adequate power to detect a similar response. 2) To determine if habitat treatments elicit a brief survival response with a long-term population level effect, we will estimate deer density to determine if there is a difference in carrying capacity between treatment and control experimental units. Because mule deer may respond to habitat change at variable rates, we may not be able to detect differences in fawn survival, but estimating deer density will still allow us to determine if habitat treatment efforts have a population level effect (i.e. assuming s-fawns treatment = s-fawns control, then we will test Densitycontrol vs. Densitytreatment) Figure 1. Experimental units shown in relation to the towns of Delta and Montrose, CO and the Uncompahgre Plateau. Low deer density areas include Sowbelly and Peach Orchard study areas, high deer density units include all other study areas. Beaton Creek and Sowbelly will be maintained as experimental controls, while Peach Orchard Point and BCSWA will be treatment areas. Cushman, Shavano, Colona and McKenzie depict areas that will be included as additional, pre-treated areas. Sowbelly Peach Orchard Delta Cushman Montrose Beaton Crk. Shavano Colona McKenzie 81 BCSWA �Table 1. Schematic and temporal representation of experimental units and their designation as high/low density, treatment/control and random treatment areas. The pilot study received no treatments to allow for the assessment of capture methods as well as to confirm the relative similarity in survival between strata as well as treatment/control areas. Areas designated as control units will not receive any mechanical treatments during this study, areas classified as pre-treated have received treatments during the past 10 years, but will receive no further treatments during this study. Areas classified as treatment areas will receive directed chemical and mechanical disturbance during the next 4 years. Low Density High Density Year Low Quality High Quality Low Quality High Quality Old Treament Pilot Control Control 1 Control Treatment Control Treatment Shavano 2 Control Treatment Control Treatment Colona 3 Control Treatment Control Treatment McKenzie 4 Control Treatment Control Treatment Cushman 3) To determine if habitat treatment efforts are effectively delivered, we will measure late-winter body condition of adult female deer. In the situation that a population level effect is not present, this final response variable will allow us to determine if the lack of response was due to a lack of statistical power (i.e. too small of a sample) or if it was due to a lack of a treatment effect (i.e. assuming s-fawns treatment = sfawns control and Densitycontrol = Densitytreatment, then we will test BodyConditioncontrol vs. BodyConditiontreatment).treatments during this study. Areas classified as treatments will receive directed chemical and mechanical disturbance during the next 4 years. 3. Sample Size / Power Calculations All sample size and power calculations were structured with an alpha level of 0.05 and a beta level of 0.30 (α = 0.05 and power = 1- β = 0.70). The number of flights and percent of population marked for density flights were estimated via simulation data, using historical data (C.J. Bishop, unpublished data, B. Banulis, personal communication, B. Watkins, personal communication). Point estimates and estimates of variance for each response variable were extracted from existing literature or unpublished data. For over-winter fawn survival, estimates of ŝ = 0.44 and SD = 0.217 (Unsworth et al. 1999), and the desire to detect a 20% difference in survival allowed us to calculate a minimum adequate sample size of 25 fawns per experimental unit (Fig. 3). We wish to have enough power to detect a 1.5% difference in total estimable body fat between treatment and control does during the late-winter period. Based on existing experimental data, differences of as much as 6% have been detected between treatment and control animals (treatment does = 10.39%, SD = 3.30, control does = 4.00%, SD = 2.47; C.J. Bishop, unpublished data). Again using α = 0.05 and β = 0.30, and using a standard deviation of 2.61 (computed by removing group and year effects), a minimum sample size requirement of 30 does/area will be needed each year (Fig. 4). For density estimation purposes, but due to logistical constraints, the number of density flights will vary by area and the number of marks will vary by both area and flight. In low density areas, substantial gains in estimate precision are made by increasing both the total number of flights and the number of marked deer in the population (Fig. 5). However, due to the financial limitations of marking large numbers of deer with radio collars in this area, we will make it a priority to maximize the number of flights. Based on financial constraints, this will be 6 flights in the low density areas. As needed, and if logistical constraints permit, we will also try to temporarily mark groups of deer. If this 82 �Power 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 1 2 3 4 5 6 7 8 # of Study Areas Figure 3. Expected power, based on simulation, of detecting a 20% (d = 0.20) difference in fawn survival across study areas at an α-level of 0.05. Different lines represent different samples sizes with squares, triangles, diamonds and circles representing 20, 25, 30 and 35 fawns/area. Estimated power for 25 fawns/ area, using 6 treatment areas is 0.713. Power 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.0 0.8 1.5 2.3 3.0 Difference in % Body Fat Figure 4. Expected power when detecting differences in estimable total body fat between treatment and control does during late-winter. Different lines represent different sample sizes with triangles, circles and squares representing 30, 35 and 40 does/area. Estimated power for detecting a 1.5% difference in body fat with 30 does/area is 0.710. 83 �1400 1200 # of Deer 1000 800 600 400 200 0 3 4 5 6 # of Flights Figure 5. Expected relationship, based on simulation, between number of flights and precision of total number of deer estimated in low deer density areas. Different lines represent precision estimates from populations with different numbers of deer marked. Lines with squares represent populations with 2.5% of the population marked, lines with triangles represent populations with 5% of the population marked and lines with circles represent populations with 7.5% of the population marked. 1200 # of Deer 1000 800 600 400 200 0 3 4 5 6 # of Flights Figure 6. Expected relationship, based on simulation, between number of flights and precision of total number of deer estimated in high deer density areas. Different lines represent precision estimates from populations with different numbers of deer marked. Lines with squares represent populations with 2.5% of the population marked, lines with triangles represent populations with 5% of the population marked and lines with circles represent populations with 7.5% of the population marked. 84 �latter approach is taken, we will attempt to increase the number of marks to 7.5% of the population. In high density study areas, the impact of increasing the number of marks in the population appears to be higher than that of increasing the number of flights (Fig. 6). As such, we will make it a priority to maximize the number of marks in each of these study areas, but we will limit the number of flights to 3 per area. 4. Procedures a. Capture and Handling Methods Twenty-five mule deer fawns will be captured and radio-collared in each of the experimental units. In the high density areas, we will attempt to capture all fawns with baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992). If needed, helicopter net-gunning will be used to complete the necessary sample. In the low density units, all fawns will be captured via helicopter net-gunning (Barrett et al. 1982, van Reenen 1982). The confounding of area and capture methods should not be a problem, as indicated by our pilot study and by White and Bartmann (1994) who found no significant difference in survival of fawns 2 and 4 weeks after capture by these 2 methods for samples of 86 and 79 fawns. Captures will occur between mid-November and late-December of each year. Additionally, 30 adult doe deer will be captured via helicopter net-gunning in each experimental unit. Adult does will be captured late-February for body condition scoring purposes. All deer will be fitted with radio collars made of vinyl belting and equipped with mortality sensors, which after remaining motionless for 4 hours, increase the pulse rate of received signals. Permanent collars will be placed on females, while temporary collars will be placed on fawns. To make fawn collars temporary, one end of the collar will be cut in half and reattached using rubber surgical tubing; fawns will shed the collars after approximately 6 months. Fawn collars will be reused annually, reducing costs after the initial year of the full-scale study. b. Survival Monitoring On a daily basis, from December through May, we will monitor the radioed fawns in order to document live/death status. This will allow us to estimate date and proximate cause of death. Daily monitoring will be done from the ground to maximize efficient collection of mortalities and assessment of cause specific mortality. Weekly aerial telemetry flights will be scheduled to insure that all deer are heard at least once a week, allowing weekly survival estimates for each experimental unit. While estimation of weekly survival rates for does is not a high priority for this study, we will attempt to monitor does for live/dead status as the same rate as fawns. c. Body Condition Scoring Methods employing the use of ultrasonography to predict total body fat have been established for moose, elk and mule deer (Stephenson et al. 1998, Cook 2000, Stephenson et al. 2002). For each adult female deer captured during late-winter, body condition will be assessed using an in vivo approach. Specifically, we will measure maximum rump fat thickness and thickness of the longissimus dorsi (loin) muscle using a portable ultrasonography machine. Each deer will also be scored using a subjective condition score developed for elk (Cook 2000). In conjunction, these measurements will allow for calculation/estimation of total percent body fat of each animal. d. Density Estimation During late-winter (late-February) of each field season we will estimate deer density on each of our study areas. Modified mark-resight techniques, via helicopter quadrats and/or randomized search patterns will be used for density estimation (Gill 1969, Bartmann et al. 1986, Kufeld et al. 1980, Freddy et al. 2004). For density estimation purposes, all deer that are captured will be collared with radio transmitters modified with color coded neck band material that identify groups of deer by method of capture (see Capture and Handling Methods). Additionally, as needed, we will mark adult deer <1 week prior to density estimation flights with a temporary mark to increase the number of marks in the 85 �population to be sampled. Temporary marks will consist of paint that is applied to the backs of deer at bait sites via paintballs. According to these marking techniques, we will have up to 3 groups of deer marked in each study area (neckband color #1 = drop-net (group 1), neckband color #2 = helicopter netgun (group 2), body paint marks = temporary (group 3)). As such, we will be able to estimate resight probabilities, improving precision of density estimates. Additionally, because groups will be defined by capture method, we will be able to estimate resight biases that are associated with capture technique. Prior to density estimation, the winter range for deer within each study area will be estimated. A quadrat for each study area will be defined prior to each flight by estimating a 95% adaptive kernel polygon from all deer locations collected prior to our helicopter flights. Once generated, all quadrat boundaries will be modified to accommodate nearby (<500m) topographical and geographical features that may serve as natural movement barriers to deer. For quadrats ≤ 10 km2, we will attempt to count all deer within the quadrat on each flight. Upon initiation of each flight in these areas, quadrat boundaries will be flown prior to systematically covering the remainder of the study area. For those study areas with quadrats that exceed 10 km2, we will create unique random flight paths for each flight. Random flight paths will be generated by overlaying these larger areas with a 1 km2 grid. Each cell within the grid will be uniquely identified and a sample of 10 cells will be randomly selected (without replacement). These 10 cells will then be used to create a flight path. Flight paths will incorporate all randomly selected cells, but cells will be incorporated in the most efficient and continuous order possible (i.e. cells will not be flown in the order that they were selected). Deer observed in the process of flying between randomly selected cells will be counted and utilized in the sample for that flight. Each study area will be flown 3-6 times/winter. Weather permitting, flights will be flown on consecutive days. Total population estimates for the quadrat will be generated using program NOREMARK (White 1996). e. Habitat Manipulations Each of the experimental areas was selected based on its habitat treatment history. The low density treatment area (Peach Orchard Point, see Experimental Units and Location of Work) received a variety of mechanical treatments between 1999 and the present. Additionally, much of this area is located on Escalante State Wildlife Area. The high density treatment area (Billy Creek State Wildlife Area, see Experimental Units and Location of Work) received a series of anchor-chaining treatments during the 1970's. This area has also received continual treatment since that time in the form of weed control and agricultural grass/hay production for big game purposes. Part of each treatment area is located on a State Wildlife Area (SWA). SWA's are managed by the Colorado Division of Wildlife, and thus, management authority is controlled by the agency conducting this research. In addition to the existing manipulations, each of these treatment areas will receive additional habitat improvement efforts in the form of weed eradication and/or further mechanical disturbance. During the first year of treatments, efforts will be primarily directed at removing noxious/non-native weeds. During subsequent years, treatments will be mechanical in nature. Due to the relatively small areas and the need for a more surgical approach to delivering mechanical treatments, the primary tool for delivering treatments will be the contracted use of a hydro-ax. The motivation for a lag effect in the application of mechanical treatments stems from two objectives: 1) Without the initial removal of weeds, the application of mechanical disturbance can facilitate the spread of non-preferred plant species. Such a sequence of events would limit the intended increase in native browse species and could potentially take the form of a negative treatment. 2) A lag effect in mechanical disturbance will allow for a more spatially precise application of treatments. With 1 year of knowledge on deer movement and space use across the treatment areas, a more effective disturbance design can be applied. An assessment of our habitat improvement efforts will also be incorporated into this study. This assessment will follow a 2 step approach. First, in order to compare between study areas, we will randomly sample each study area to estimate total cover and browse via cover and density plots. Second, in order to assess whether our treatment efforts impacted the vegetative landscape, we will sample our 86 �specific treatment areas for percent cover and percent browse before treatments occur and again at the end of study. f. Statistical Analyses We will test for differences between experimental units and years using the generic statistical model: yi(jk) = μ + αj + βk + αβjk + єi(jk), where yijk = parameter of interest (e.g., over-winter fawn survival or adult female body condition) for the ith individual in treatment combination jk; i = 1, 2, ..., njk (individual); j = 1, 2, ...,8 experimental units; k = 1, 2, 3, 4 years; αβjk = interactions among experimental units and years; and єi(jk) = random error associated with yijk. A similar model will be used to analyze density on each experimental unit. For survival analyses, a logit transformation will be used. Estimation of year effects will allow for quantification of process variation in survival throughout the study. Additional covariates, such as gender and body mass, will also be incorporated into the linear model. 5. Project Schedule FY2004-05 FY2005-06 FY2006-07 FY2007-08 FY2008-09 Pilot Results/Revised Program Narrative Progress Report Progress Report Progress Report Completion Report 8/1/2005 8/1/2006 8/1/2007 8/1/2008 8/1/2009 6. Estimate annual Cost Fiscal Year 2005-2006 2006-2007 2007-2008 2008-2009 Equipment/ Supplies $35,940 $37,018 $38,129 $39,273 Rental Services Operating $107,633 $31,200 $110,862 $32,136 $114,188 $33,100 $117,613 $34,093 Vehicles $12,805 $13,190 $13,585 $13,993 FTE Requirements PFTE TFTE 1.0 2.0 1.0 2.0 1.0 2.0 1.0 2.0 Total Costs $282,719 $291,201 $299,937 $308,935 7. Personnel Eric J. Bergman, Mammals Researcher, Project Leader, Colorado Division of Wildlife Chad J. Bishop, Mammals Researcher, Project Co-Leader, Colorado Division of Wildlife David J. Freddy, Mammals Research Leader, Colorado Division of Wildlife Gary C. White, Professor of Wildlife Biology, Colorado State University E. LOCATION OF WORK This study will be conducted on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado. The high density treatment area is located on Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). The high density control area is located around Beaton Creek (approximately 15km south of Montrose, CO and approximately 5km north of Billy Creek State Wildlife Area). Both of these study areas are located in GMU 65 (DAU D-40). The low density treatment area is located on Peach Orchard Point, on/near Escalante State Wildlife Area (approximately 25km southwest of Delta, CO). The low density control area is located on Sowbelly and Tatum draws (approximately 25km west of Delta, CO and approximately 8km from Peach Orchard Point). Both of these study areas are located in GMU 62 (DAU D-19). The pre-treated areas are also located in GMU 62 (DAU D-19) to the 87 �west and southwest of Montrose, CO. These areas, largely based on drainages, will be in the areas of Shavano Valley, Colona, McKenzie Buttes and Cushman Creek and will be incorporated into the study during years 1,2,3, and 4, respectively. F. RELATED FEDERAL PROJECTS This study is the second phase to a mule deer/habitat relationship study that began in 2000 (described above and in Bishop et al. 2005). G. LITERATURE CITED BARRETT, M.W., J.W. NOLAN, and L.D. ROY. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. BARTMANN, R.M., L.H. CARPENTER, R.A. GARROTT, and D.C. BOWDEN. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. —————, G.C. WHITE, and L.H. CARPENTER. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. BISHOP, C.J., J.W. UNSWORTH, AND E.O. GARTON. 2005. Mule deer survival among adjacent populations in southwest Idaho. Journal of Wildlife Management 69:311-321. —————, G.C. WHITE, D.J. FREDDY, and B.E. WATKINS. 2005. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. CARPENTER, L.H. and O.C. WALLMO. 1981. Rocky mountain and intermountain habitats: habitat evaluation and management. Pages 399-422 in O.C. Wallmo, ed. Mule and black-tailed deer of North America, University of Nebraska Press, Lincoln. CLUTTON-BROCK, T., and J. PEMBERTON, editors. 2004. Soay sheep: dynamics and selection in an island population. Cambridge University Press, UK. CONNOLLY, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. COOK, R.C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain Elk. Thesis, University of Idaho, Moscow, USA. FREDDY, D.J., G.C. WHITE, M.C. KNEELAND, R.H. KAHN, J.W. UNSWORTH, W.J. DEVERGIE, V.K. GRAHAM, J.H. ELLENBERGER, and C.H. WAGNER. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. GILL, R.B. 1969. A quadrat count system for estimating game populations. Colorado Division of Game, Fish and Parks, Game Information Leaflet 76. Fort Collins, USA. ————— 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. HURLEY, M., and P. ZAGER. 2004. Southeast mule deer ecology - Study I: Influence of predators on mule deer populations. Progress Report, Idaho Department of Fish and Game, Boise, USA. JEDRZEJEWSKA, B., and W. JEDRZEJEWSKI. 1998. Predation in Vertebrate Communities: the Białowieża Primeval Forest as a case study. Springer-Verlag, Berlin, Germany. KIE, J.G. 1984. Deer habitat use after prescribed burning in northern California. Research Note, PSW369. USDA, Forest Service, Pacific Southwest Forest and Range Experiment Station, Berkeley, CA, USA. KIE, J.G., J.W. MENKE, J.R. DAVID and W.M. LONGHURST. 1980. Mitigating the effects of reservoir development on black-tailed deer in Trinity County, California. Cal-Neva Wildl. Trans. pp.129148. KREBS, C.J., S. BOUTIN, and R. BOONSTRA, editors. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. 88 �KUFELD, R.C., J.H. OLTERMAN, AND D.C. BOWDEN. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. RAMSEY, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. SCHMIDT, R.L., W.H. RUTHERFORD, and F.M. BODENHAM. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. STEPHENSHON, T.R., V.C. BLEICH, B.M. PIERCE, and G.P. MULCAHY. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. ————— , T.R., K.J. HUNDERTMARK, C.C. SCHWARTZ, and V. VAN BALLENBERGHE. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717-722. UNITED STATES FISH AND WILDLIFE SERVICE. 1976. Habitat as a basis for environmental assessment 101 ESM. Department of Interior, Washington, D.C., USA. UNSWORTH, J. W., D. F. , G. C. WHITE, and R. M. BARTMANN. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. VAN REENEN, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. WHITE, G.C. 1996. NOREMARK: Population estimation from mark-resighting surveys. Wildlife Society Bulletin 24:50-52. WHITE, G.C., and R.M. BARTMANN. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. 89 �90 �Colorado Division of Wildlife July 2005 – June 2006 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 5 Federal Aid Project: W-185-R : Division of Wildlife : Mammals Research : Deer Conservaton : Multispecies Investigations Consulting Services for Mark-Recapture Analysis : Period Covered: July 1, 2005 - June 30, 2006 Author: G. C. White Personnel: C. Bishop, D. J. Freddy, T. M. Shenk, L. Stevens, R. Kahn, F. Pusateri, E. O’Dell, D. Martin, P. Schnurr, K. Navo, B. Andelt, D. Finley, A. Linstrom, K. Strohm, P. Conn. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Progress towards meeting the objectives of this job include: 1. Consulting assistance to Colorado Division of Wildlife (CDOW) on harvest surveys, terrestrial inventory systems, and population modeling procedures was provided. Assistance with estimation of spring and fall turkey, spring snow goose, sharp-tailed and sage grouse, chukars, ptarmigan, Abert’s squirrels, and general small game harvest was provided, and programs and harvest estimates provided to CDOW via email and CD ROM. Computer code written in SAS to compute these estimates and display results graphically was also provided. Computer code was also written in SAS to estimate the compliance rate of Colorado small game license holders with the Harvest Information Program. 2. The CDOW DEAMAN software package for the storage, summary, and analysis of big game population and harvest data was revised further as a Windows XP program. A User’s Manual has been provided to terrestrial biologists via the WWW at http://www.cnr.colostate.edu/~gwhite/deaman. I met with the CDOW software group to discuss conversion of DEAMAN to a central server application. 3. Consultation with CDOW Terrestrial Biologists in the use of DEAMAN and population modeling procedures continued. Numerous questions were answered via meetings with biologists, and via email. 4. A paper comparing the population levels of swift foxes in eastern Colorado to a previous study in cooperation with CDOW was submitted to Southwestern Naturalist: Martin, D. J., G. C. White, and F. M. Pusateri. 2006. Monitoring swift fox populations in eastern Colorado. Southwestern Naturalist. Submitted. 5. A paper on the use of vaginal implant transmitters in cooperation with CDOW was submitted and accepted for publication in the Journal of Wildlife Management: Bishop, C. J., D. J. Freddy, G. C. 91 �White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2006. Using vaginal implant transmitters to aid in capture of neonates from marked mule deer. Journal of Wildlife Management. In Press. 6. A paper resulting from Dan Walsh’s M.S. project in cooperation with CDOW was submitted to Ecological Applications: Walsh, D. P., G. C. White, T. E. Remington, and D. C. Bowden. 2006. Population Estimation of Greater Sage-Grouse. Ecological Applications. Submitted. 7. A paper resulting from Sherri Huwer’s M.S. project in cooperation with CDOW was submitted to the Journal of Wildlife Management: Huwer, S. L., D. R. Anderson, T. E. Remington, and G. C. White. 2006. Evaluating the importance of forbs to sage-grouse using human-imprinted chicks. Journal of Wildlife Management. Submitted. 8. A paper on mountain sheep populations in Rocky Mountain National Park was submitted and accepted for publication in the Wildlife Society Bulletin: McClintock, B. T., and G. C. White. 2006. Bighorn sheep abundance following a suspected pneumonia epidemic in Rocky Mountain National Park. Wildlife Society Bulletin. In Press. 9. A paper on extending the mark-resight estimator using a beta-binomial distribution was submitted and accepted in the Journal of Agricultural, Biological, and Ecological Statistics: McClintock, B. T., G. C. White, and K. P. Burnham. 2006. A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities. Journal of Agricultural, Biological, and Ecological Statistics. In Press. 10. A paper resulting from the May, 2005 Elk and Deer Workshop was submitted and accepted for publication in the Wildlife Society Bulleting: Mason, J. R., L. H. Carpenter, M. Cox, J. C. Devos, J. Fairchild, D.J. Freddy, J. R. Heffelfinger, R. H. Kahn, S. M. McCorquodale, D. F. Pac, D. Summers, G. C. White, and B. K. Williams. 2006. A case for standardized ungulate surveys and data management in the western United States. Wildlife Society Bulletin. In Press. 11. A paper describing the use of closed captures models to estimate population size with Program MARK was submitted and accepted for publication in Environmental and Ecological Statistics: White, G. C. 2006. Closed population estimation models and their extensions in program MARK. Environmental and Ecological Statistics. In Press. 12. A paper on the application of multistate models in Program MARK was submitted and accepted for publication in the Journal of Wildlife Management: White, G. C., W. L. Kendall, and R. J. Barker. 2006. Multistate survival models and their extensions in program MARK. Journal of Wildlife Management. In Press. 13. A paper on the estimation of female grizzly bears was submitted to the Journal of Agricultural, Biological, and Ecological Statistics: Cherry, S., G. C. White, K. A. Keating, M. A. Haroldson, C. C. Schwartz. 2006. Evaluating estimators of the numbers of females with cubs-of-the-year in the Yellowstone grizzly bear population. Journal of Agricultural, Biological, and Ecological Statistics. Submitted. 14. A paper on the survival of mule deer in the Bridger Mountains, Montana, was submitted and accepted for publication in the Journal of Wildlife Management: Pac, D. F., and G. C. White. 2006. Survival and cause-specific mortality of mule deer in the Bridger Mountains, Montana. Journal of Wildlife Management. In Press. 92 �15. A paper on the impact of limited antlered harvest on mule deer sex and age ratios in cooperation with CDOW was published in the Wildlife Society Bulletin: Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2005. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin 33: 662–668. 16. A paper on estimation of nest survival was submitted and accepted for publication in Studies in Avian Biology: Heisey, D. M., T. L. Shaffer, and G. C. White. 2006. The ABCs of nest survival: theory and application from a biostatistical perspective. Studies in Avian Biology. In Press. 17. A paper on the estimation of the area of black-tailed prairie dog colonies in eastern Colorado in cooperation with CDOW was published in the Wildlife Society Bulletin: White, G. C., J. R. Dennis, and F. M. Pusateri. 2005. Area of black-tailed prairie dog colonies in eastern Colorado. Wildlife Society Bulletin 33:265–272. 18. A paper in response to a critique by Sterling Miller was published in the Wildlife Society Bulletin in cooperation with CDOW: White, G. C., J. R. Dennis, and F. M. Pusateri. 2005. Response to: Overestimation bias in estimate of black-tailed prairie dog abundance in Colorado. Wildlife Society Bulletin 33:1452–1455. 19. A paper on methodologies to obtain more rigorous population monitoring data was published in Wildlife Research: White, G. C. 2005. Correcting wildlife counts with detection probabilities. Wildlife Research 32:211–216. 20. A paper on the procedures to monitor swift fox populations in eastern Colorado was published in the Journal of Wildlife Management: Finley, D. J., G. C. White and J. P. Fitzgerald. 2005. Estimation of swift fox population size and occupancy rates in eastern Colorado. Journal of Wildlife Management 69:861–873. 21. A research study to examine the impact of nutrition on the decline of mule deer fecundity during the last 20 years was continued in cooperation with Chad Bishop and CDOW. Portions of this work will serve as his doctoral dissertation in addition to his full-time duties as a researcher with CDOW. 22. A graduate research project (M. S.) was continued in cooperation with CDOW to evaluate line transect methodology for estimating pronghorn populations in eastern Colorado. The graduate student is Aaron Linstrom, and the project is in addition to his full-time duties as a biologist with CDOW. 23. A graduate research project (Ph. D.) in cooperation with CDOW to develop statistical models to monitor puma and black bear populations in Colorado based on checks of harvested animals and DNA and/or radio-tracking data was continued. The graduate student is Paul Conn. 24. A graduate research project (M. S.) in cooperation with CDOW to evaluate methods of redistributing elk in and around Great Sand Dunes National Park was started and then discontinued. The student, Greg Davidson, switched his work to evaluate habitat use by elk on the Grand Mesa. 25. Development of the design of a monitoring system for white-tailed prairie dogs in western Colorado and eastern Utah was continued in cooperation with CDOW with P. Schnurr, K. Navo and B. Andelt. 26. Design of a monitoring system for black-tailed prairie dogs in eastern Colorado in cooperation with CDOW was continued. This effort is in cooperation with Francie Pusateri and Eric O’Dell of CDOW. 93 �WILDLIFE RESEARCH REPORT CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSES GARY C. WHITE P. N. OBJECTIVE Provide expert biostatistical and experimental design services to the Colorado Division of Wildlife, Wildlife Programs Branch. SEGMENT OBJECTIVES 1. Provide biostatisitical support to implement and analyze CDOW hunter harvest surveys. 2. Provide professional oversight, critiques, and analytical support to CDOW terrestrial management and avian and mammals research sections. 3. Convey to CDOW research and management sections new and pertinent information obtained in various collaborative projects conducted with other agencies and entities. RESULTS, DISCUSSION, SUMMARY See ABSTRACT for summary of key activities and publications. Prepared by: Dr. Gary C. White, Department of Fish, Wildlife, and Conservation Biology Colorado State University 94 �Colorado Division of Wildlife July 2005 – June 2006 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3003 1 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Predatory Mammals Conservation : Puma Population Structure and Vital Rates on the Uncompahgre Plateau : Period covered: July 1, 2005―June 30, 2006 Author: K. A. Logan. Personnel: K. Logan, S. Waters, B. Bavin, B. Simpson, K. Crane, T. Mathieson, M. Caddy, and T. Smith of CDOW, J. Bauer of Colorado Cooperative Fishery and Wildlife Research Unit, J. Kane, V. Johnson, S. Young, and J. McNamara of U.S.D.A. Wildlife Services, volunteers, cooperators including: private landowners, U.S. Forest Service, Bureau of Land Management, and Colorado State Parks, with financial support received from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Research continued on puma population characteristics and dynamics on the Uncompahgre Plateau. Puma capture efforts resulted in a total of 36 puma captures (14 adults [1 adult female captured twice], 4 subadults, 14 cubs, and 2 adult or subadult males [1 captured twice] but not handled) with 20 radio-collared pumas within the study area as of July 2006. Efforts to capture, sample, and mark pumas with the use of trained dogs extended from November 21, 2005 to May 26, 2006. This resulted in 14 puma captures, including 1 adult female, 1 subadult female, 2 adult males, and 1 subadult or adult male captured and processed for the first time. Two other males were captured (one of them twice), but were not handled for safety reasons. The remainder was recaptures of previously marked pumas, including 2 adult females (1 recaptured twice), 1 adult male, 1 subadult male, and 1 male cub. We substantially increased puma capture efforts with ungulate carcasses to bait pumas into cage traps. From August 2, 2005 to June 27, 2006, we used 77 road-killed mule deer, 3 road-killed elk, 3 puma-killed mule deer, and 1 puma killed elk at 23 different sites. This resulted in 11 puma captures, including 4 adult females, 1 adult male, and 1 male cub captured and processed for the first time, and 3 adult females, 1 subadult male, and 1 male cub that were recaptured. Eleven other puma cubs (4 males, 7 females) from 4 litters were captured by hand at nurseries and processed for the first time. We investigated 4 puma mortalities: one adult male was killed by another male puma, 2 cubs (1 male, 1 female) were killed and eaten by other pumas, and 1 female cub died due to the expandable radiocollar she was wearing. To date, 14 pumas (5 males, 9 females) have been monitored with GPS collars, yielding 113 to 1,784 locations per puma, and a total of 13,139 GPS locations. We began quantifying the frequency that puma mothers are away from their cubs during the Colorado puma hunting season (Nov. through Mar.) as a preliminary assessment of potential vulnerability of mothers to harvest. Radio-collared members (mothers and cubs) of 5 families were located 79 times during fixed-wing flights from November 9, 2005 to March 29, 2006. Mothers 95 �were apart from their cubs >600 m during 12 of those occasions (15.2%). Preliminary comparisons between our current puma research on the Uncompahgre Plateau (~21 months duration) and results of the Anderson et al. (1992) puma research on the plateau (~7 years duration 1981-1988) are made where appropriate. We collaborated with colleagues to develop 3 proposals to contribute to the Colorado puma management program. Proposed work includes: testing genetic techniques for non-invasive methods to estimate puma numbers using mark-recapture methods and models, developing state-wide puma habitat models and maps, and assessing puma health. In addition, we will resume quantifying puma use frequencies of ungulates, and considering how research of pumas on developed areas on the Uncompahgre Plateau can contribute to the CDOW’s efforts to study puma-human interactions on the Colorado Front Range. 96 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates― all to improve the Colorado Division of Wildlife’s (CDOW) model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. 5. Continue gathering data on puma population sex and age structure. Continue gathering data for estimates of puma reproduction rates. Continue gathering data to estimate puma sex and age-stage survival rates. Continue gathering data to estimate agent-specific mortality rates. Continue gathering data on puma movements for the development of sampling methods for markresight or recapture population estimates that might involve sampling puma DNA-genotypes, trail cameras, or direct observations. 6. Begin gathering data on spatial relationships of puma mothers to their cubs during the Colorado puma hunting season as a preliminary assessment of the vulnerability of puma mothers to sport-hunting harvest. 7. Evaluate other data sources that could come from this research that can be developed into other puma research relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing puma while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma-prey interactions. Staff on the Front Range placed greater emphasis on puma-human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): 97 �Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field experiments. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared puma. Those objectives include: 1. Describe and quantify puma population sex and age structure. 2. Estimate puma population vital rates, including: birth rates, age-stage-specific survival rates, emigration rates, immigration rates. 3. Estimate agent-specific mortality rates. 4. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of population abundance (i.e., numbers and density) and attendant annual population growth rates, such as, direct capture-resight, and DNA genotype capture-recapture. TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Recreational puma hunting management in Colorado Game Management Units (GMUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004). Basic model parameters are: puma population density, sex and age structure, and annual 98 �population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are deemed to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,λ = 1.15) for the adult and subadult puma population (J. Apker, Carnivore Management Specialist, CDOW, Monte Vista). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). The key assumption is that the CDOW can manage puma population growth through recreational hunting: for a stable puma population hunting removes the annual increment of population growth (i.e., as estimated from estimates of population density, structure, and λ ; for a declining population, hunting removes more than the annual increment of population growth. Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, agespecific natality, sex- and age-specific survival, immigration and emigration. A descriptive study will ascertain these population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. The treatment period will involve the use of controlled recreational hunting to manage the puma population into a decline phase. H1a: Population parameters measured during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15, which is currently assumed in the CDOW’s model-based management. H1aA: Population parameters measured during a 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will be substantially lower (i.e., ≥ 50% lower, λ ≤ 1.075) than the assumed λ = 1.15. H1b: Population parameters during a 5-year treatment period (controlled puma hunting) will differ substantially from those measured during the preceding 5-year reference period (hunting closure) and will yield an estimated annual adult plus subadult population growth rate that will be approximately λ = 0.8 for at least the first 2 years of the treatment period. Hunting-caused mortality will be strongly additive, and will require removal of the annual growth increment (of adults plus subadults) plus 20% (e.g., assume λ = 1.15, so, 0.15 × 0.2 + 0.15 = 0.18; 0.18 × 100 = 18% annual harvest of adults plus subadults). H1bA: Population parameters during a 5-year treatment period (controlled puma hunting) will not differ substantially from those measured during the preceding 5-year reference period (hunting closure), and the adult plus subadult population will not decline on average as a result of hunting mortality. Hunting-caused mortality, reproduction, immigration, and emigration might be compensatory. 2. Considering limitations (i.e., methods, number of years, assumption violations) to the Coloradospecific studies on puma densities cited above (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973, Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0―4.6 puma/100 km2 to extrapolate to Data Analysis Units to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using capture, 99 �mark, re-capture techniques developed and refined during the study to estimate the puma population, the following will be tested: H2a: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 3. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H2b: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent puma will cause an older age structure in harvest-age puma (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. H2c: As hunting is re-instated in the treatment period, the age structure of harvested puma and the harvest-age puma in the population will vary as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters useful for estimating puma population abundance, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help those managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for estimating puma abundance (capture-mark-recapture) of known reliability will allow managers to “ground truth” modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will require development of reliable monitoring techniques based on capture-mark-recapture methods and models. Potential methods include direct and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and when we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties, Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. 100 �The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinon-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing summer residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Experimental Treatment Periods This research is structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period is expected to cause a population increase phase. The treatment period will be managed to cause a population decline phase. In both phases, puma population structure, and vital rates will be quantified, and some management assumptions and hypotheses regarding population dynamics will be tested. Contingent upon results of pilot studies, we will also estimate puma numbers, population growth rates, evaluate enumeration methods, and test other hypotheses (Logan 2004). The reference period, without recreational puma hunting as a major limiting factor, is consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000―12,000 years (Culver et al. 2000) that enable puma to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma evolution in western North America for the past 100 years. Hence, the reference period, years 1―5, will provide conditions where individual puma in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factors will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before the treatment (i.e., controlled recreational hunting). In the reference period, all puma in the study area will be protected, except for individual puma that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged puma that range in a buffer zone, that includes the northern halves of GMUs 61 and 62, will be protected from recreational hunting. The reference period will allow researchers to quantify baseline demographic data on the puma population to estimate parameters for the CDOW’s model-based approach to puma management. Moreover, it will allow researchers to develop and test puma enumeration methods when population growth is known to be in one direction― increasing. Without the hunting closure, pilot data for enumeration methods could be confounded by not knowing if the population was increasing, declining, or stable. The reference period will also facilitate other operational needs (because hunters will not be killing the animals) including the marking of a large proportion of the puma population for capture-markrecapture estimates, and the gathering of movement data from GPS-collared puma to help formalize exact sampling designs for enumeration methods. During the treatment period, years 6―10, experimentally structured recreational puma hunting will occur on the same study area with the intent of causing a decline phase in the puma population by using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or population suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, puma survival will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared puma. 101 �The portion of adults and subadults in the population will be reduced by approximately 20% in year 6 and 20% more in year 7. The 20% change was identified by Division managers that requested enumeration tools that might detect 20% changes in puma populations. For managers, detecting the magnitude of puma population decline phases is probably more important that detecting the magnitude of population increase phases. This will also allow quantification of puma population characteristics and vital rates and initial tests of enumeration methods during a decline phase. Additional reductions may be made to test enumeration methods and other hypotheses that may be related to effects of hunting (i.e.,: relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting) and puma-prey interactions (i.e., lines of research identified in the Colorado Research Program, Fig. 1). Those decisions can be made later in project development and as late as years 8―10. The killing of tagged and collared puma during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a large majority of independent puma in the population will be marked, and sampling schemes will be formalized. Puma on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW of Wildlife if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that puma live at low densities and capturing puma is difficult, as a starting point, our logistical aim will be to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim is to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of puma might represent the large majority of the puma population on the study area, and will provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration rates, and movement data pertinent to sampling designs for various projects. Assuming that the puma population density on the study area is relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio is equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might be 22 adults, 11 males and 11 females. Also assuming that the total population contains 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might be 4 subadults and 13 cubs with equal sex ratios in a total population of 39 puma. If we achieve our logistical aim in the first 1―2 years (recognizing that the population might grow), then we should be able to quantify population characteristics and vital rates for a majority of the puma population in those years and build upon the tagged number in each subsequent year. Thus, our inferences will pertain to the large majority of the puma population, if not the population on the study area, instead of a relatively small sample of it. We anticipate it may take 2 years to mark the large majority of puma in the population. In addition, the study area is large and will require some time to learn to access it efficiently. Puma capture and handling procedures have been approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured puma will be examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements 102 �recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses; disease screening; hair (from various body regions) and fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Puma will be captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, walking, and possibly horse- or mule-back. When puma tracks ≤ 1 day old are detected, trained dogs will be released to pursue puma to capture. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent will be delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤ 2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2005). Efficiency of the trap might be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Manchester, NH). A cage trap will be set only if a target puma scavenges on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers will continuously monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized puma will be restrained and monitored as described above. If non-target animals are caught in the cage trap, we will open the door and allow the animal to leave the trap. Foot-hold snares will be used to capture adults, subadults, and large cubs only when safe snare sites at puma kills can be located as described by Logan et al. (1999). Snares set at puma kills will be monitored continuously with VHF beacons on the snares from about 1 km distance. We will not set snares at sites where tracks indicate that other mammals (e.g., deer, elk, bear, bighorn sheep, livestock) are also active. Puma will be immobilized with Telazol injected into the caudal thigh with a pole syringe. Vital signs will be monitored during the handling procedures. Efficiency of snares might also be enhanced with the use of an automated call box with puma or prey vocalizations. Small cubs (≤ 10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to the exact nurseries where they were found (Logan and Sweanor 2001). 103 �Marking, Global Positioning System- and Radio-telemetry: Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual puma is essential to a number of project objectives, including estimating vital rates and gathering movement data on puma to formalize designs for developing and testing enumeration methods. Adult, subadult, and cub puma will be marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna is permanent and cannot be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) will be inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤ 10 weeks old will be eartagged in only one pinna. Locations of GPS- and VHF-collared puma will be fixed about once per week from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using ArcGIS software. Adult and subadult female pumas will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada). Initially, GPS-collars will be programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for puma will provide precise, quantitative data on puma movements mainly to provide data to formalize study designs, to test assumptions for capture-mark-recapture methods for this project, and to assess the relevance of puma DAU boundaries. The GPS-collars also will provide basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and predation frequency on mule deer and elk. Subadult male pumas will be fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male puma reach adulthood on the study area, we will recapture them and fit them with GPS collars. VHF radio transmitters on GPS collars will enable researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters on GPS- and VHF-collars will have a mortality mode set to alert researchers when puma have been immobile for at least 3 hours so that dead puma can be found to quantify survival rates and agent-specific mortality rates by gender and age. We will attempt to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar (~100g, MOD 210, Telonics, Inc., Mesa, Arizona) when cubs weigh 2.3―11 kg (5―25 lb). Cubs with mass ≥ 11 kg can still wear these small expandable collars until they are about 12 months old. Cubs approaching the age of independence (~11―14 mo. old) may be fit with Lotek LMRT-3 VHF collars (~400 g) with expansion links. Cubs will be recaptured to replace collars as necessary. Monitoring radioed cubs allow quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). 104 �Capture-Mark-Recapture: Capture-mark-recapture methods will be evaluated initially as a pilot study. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during capture-recapture occasions needed for population estimation. Therefore, we will capture and mark pumas prior to performing capture-recapture or re-sight occasions using using methods such as houndsmen teams or trail cameras. In addition, by marking puma before capture-recapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked on the study area. After cubs are weaned, the mothers’ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Capture-recapture occasions to estimate the population of independent puma may not begin until the end of the second winter or the third winter when we have a large majority of the puma population sampled and marked. Occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, performance of field methods (e.g., detection differences by sex or life stage as revealed by GPS data on collared puma), and precision of capture-recapture models used to estimate the puma population. Analytical Methods Population Characteristics: Population characteristics each year will be tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥ 24 months old, or younger breeders), subadults (young puma independent of mothers, < 24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allow, age categories may be further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates will be estimated for GPS- and VHF-collared female puma directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male puma (Murphy et al. 1998). Methods will be tested in Dr. M. Douglas’s Laboratory (Colorado State University, Department of Fishery and Wildlife Biology). Survival and Agent-specific Mortality Rates: Radio-collared puma will provide known fate data which can be used to estimate survival rates for each age stage using the binomial survival model (Williams et al. 2001:343-344) or analyzed in program MARK (White and Burnham 1999, Cooch and White 2004). Agent-specific mortality rates can be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will be plotted with survival rate on age in months (Logan and Sweanor 2001:119). Population Estimates: Capture-recapture models will be evaluated initially as a pilot study to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of adult and subadult puma present in the survey area) and puma density (i.e., number of independent puma/100 km2) each winter― December through March― when snow facilitates detection and capture of puma, provided that we meet model assumptions. The December―March period also corresponds with Colorado’s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma that can be legally killed by recreational hunters. Furthermore, adults comprise the breeding segment of the population and subadults are non-breeders that are potential recruits into the adult population in ≤ 1 year. Thus, the sampling unit is the individual independent puma (~≥ 1 yr. old). General assumptions for closed capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture 105 �occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). The robust design is a combination of closed and open models; thus, assumptions are a combination of the assumptions for closed and open population methods (Kendall 2001). To analyze capture-recapture data, closed, open, and the robust design models are available in program MARK. Akaike’s Information Criterion will be used to select the most parsimonious models based on AICc score ranks and the difference in AIC (∆AIC) between models (Burnham and Anderson 1998). MARK results also include estimates of abundance. Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of at least 0.5 for each animal per capture occasion. Capture simulations using MARK software (Cooch and White 2004) indicate that greater capture probabilities and more capture occasions yield more precise estimates. The capture probability for the simplest closed model [M(o)], which assumes that every member of the population has the same probability of capture (p) for each sampling period, suggest that for a population of 30 animals (i.e., adults plus subadult puma, which might be present by the end of year 2, see Puma Capture above) p must equal 0.5 for 3 capture occasions to attain a coefficient of variation (V) of 0.1. If 6 capture occasions are used, then a p of 0.3 might yield a V of 0.09. In addition, behavior, movements, survival and mortality of GPS- and VHF-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we might expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models and the robust design would be more appropriate (Pollock et al. 1990, Williams et al. 2001). Collared puma will allow us to determine the number of marked puma present in the search area each capture-recapture occasion. Furthermore, GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information, too. ArcView geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frames. Rate of Population Increase: Finite rates of increase (λ = Nt+1/Nt) between consecutive years and average annual rates of increase (r) for 3- to 5-year periods and levels of precision will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. Functional Relationships: Graphical methods will be used to examine functional relationships between puma density and vital rates, relationships between puma density estimated with direct capturerecapture methods (i.e., houndsmen teams) and possibly later (depending upon funding) by using estimates from DNA genotype or other mark- recapture methods. Linear regression procedures and coefficients of determination can be used to assess these functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank 106 �correlation coefficient, can also be used to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Statistical analyses will be performed using SYSTAT and SAS software. The risk of committing a type I error (i.e., rejecting a null hypothesis that is actually true) will be controlled at alpha = 0.10 because we will normally have small population sizes (typical of studies of large obligate carnivores). The higher alpha level will increase the probability of detecting a change and reduce the risk of a type II error (i.e., failing to reject a null hypothesis that is false). For managers, the risk of a type II error is probably more important. RESULTS AND DISCUSSION Segment Objective 1 Field research to quantify puma population structure, vital rates, and causes of mortality for this report extended from August 2005 to July 2006. Our searches to detect puma presence covered the entire study area, but, we allocated most of our effort in areas where we consistently found tracks that we thought were of unmarked pumas. Less effort was allocated to the northeast and southwest areas where we found little or no evidence of pumas. We made 36 puma captures during the period (10 adult females [1 adult female captured twice], 4 adult males, 1 subadult female, 2 subadult males, 14 cubs, and 3 adult or subadult males [1 captured twice] but not handled). As our main method to capture, sample, and mark adult and subadult pumas, we used trained dogs from November 21, 2005 to May 26, 2006. Those efforts resulted in 82 search days, 149 puma tracks detected, 43 pursuits, and 14 puma captures (Table 1). Puma capture efforts with dogs in this period was similar to our efforts in the last (first) report period (Table 2). Only the number of pumas captured for the first time is lower in this period (7 vs. 11). These included 2 males (1 of them captured twice) that could not be handled for safety reasons (Table 3). It is possible that we captured 1 or both of those male pumas in subsequent capture efforts. Moreover, we substantially increased our puma capture efforts by using ungulate carcasses and cage traps from August 2005 to June 2006. We used 77 road-killed mule deer, 3 road-killed elk, 3 puma-killed mule deer, and 1 puma killed elk at 23 sites to capture pumas 11 times (Tables 4, 5, 6). Pumas scavenged 16 of 80 (20%) of the roadkilled ungulate carcasses we used for bait. A total of 11 pumas were captured, sampled, and marked for the first time by using dogs and cage traps, (Table 5), including 1 cub caught with its mother in a cage trap (Table 7). Eleven recaptures of 10 marked pumas were made with the use of dogs and cage traps; GPS/VHF collars were replaced as needed (Table 6). We captured, sampled, and marked 11 other cubs in 4 litters that were captured by hand at nurseries (Table 7). Anderson et al. (1992) studied pumas on the east slope of the Uncompahgre Plateau (i.e., GMU 62) during 1981 to 1988. Sport-hunting was banned during that study as it is in this current study. Although our current puma research on the Uncompahgre Plateau has been underway for only about 21 months (compared to 7 years of Anderson et al. 1992), there might be some useful preliminary comparisons between the 2 efforts that we can begin to make in this annual report. As our current effort results in larger samples and progresses in time through the Reference and Treatment periods, similarities and differences in results of the 2 research efforts, now separated by more than 15 years, should become robust, and illuminate new knowledge for pumas in Colorado. In the first 2 winters of puma capture efforts with dogs (1981-82 and 1983), Anderson et al. (1992:33) attempted to capture pumas in 32 and 59 days, respectively, compared to our efforts of 78 and 82 days (2004-05 and 2005-06). In the first winter, they captured 3 female pumas for the first time with an effort of 10.6 days per capture, compared to our 11 pumas (5 males, 6 females) captured for the first time, and an effort of 7.1 days per capture. In the second winter, they captured 7 pumas (4 males, 3 females) for the first time with an effort of 8.4 days per capture, compared to our 7 pumas (5 males, 2 females) captured for the first time with an effort of 11.7 days per capture. In the 7 winters of the 107 �Anderson et al. (1992) study, the average effort was 91.1 days per winter (range = 32 to 136) resulting in average capture effort of 13.9 days per capture. Other capture efforts and results between the 2 studies are not comparable, because Anderson et al. (1992) did not attempt to capture pumas using cage traps or at nurseries like we are (e.g., in about the first 25 months, Anderson et al. captured 11 pumas; we captured 37 pumas in about 20 months). Puma mass recorded by Anderson et al. (1992:86) for puma having an estimated age ≥ 24 months, averaged 61.6 kg for 8 males, (SD = 5.7, range = 51.8 to 70.8) and 44.5 kg for 14 females (SD = 3.6, range = 38.5 to 49.9). So far in the current study, mass for pumas ≥ 24 months old averaged 59.3 kg for 7 males (SD = 9.3, range 40 to 68 kg) and 39.7 kg for 8 females (SD = 4.8, range = 32 to 46). Sexual dimorphism has been described for puma throughout the species range (Young and Goldman 1946) and has been explained as the result of sexual selection (Logan and Sweanor 2001:109). Segment Objective 2 We observed 12 puma cubs produced by 5 females (Table 7). Eleven of the cubs were examined at nurseries when the cubs were 29 to 37 days old; the sexes were 4 males and 7 females. A twelfth cub was caught in a cage trap when he was about 183 days (~6 mo.) old. No evidence of siblings was found during that event. The 5 litters were born in May (1), June (1), August (1), and September (2). Puma F3 has produced 2 litters; 1 in August 2005 and 1 in September 2006; for a birth interval of 13 months. Puma M6 is a candidate sire of F3’s September 2006 litter; he and F3 consorted during June 22―24, 2005 (based on their joint GPS location data). From those consorting dates to the estimated birth date, the estimated gestation period for F3’s litter was 93―95 days. Anderson et al. (1992:47) reported of “17 postnatal litters about 10-240 days in estimated age from 12 individual females, the mean (±SD) and extremes of litter sizes were 2.41 ± 0.8, 1-4)”. “Because most postnatal young were not handled, their sex ratio is unknown” (Anderson et al (1992:48). So far in our current research, for 7 postnatal litters about 26 to 42 days old from 7 individual females, the mean (±SD) and extremes of litter sizes were 2.57 ± 0.79, 2 to 4. Sexes of the 18 cubs we examined in 7 litters aged about 26 to 42 days old were 6 males and 12 females. Anderson et al. (1992:47-48) found that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. So far, the monthly distribution of puma births we have observed in the current study is: May (3), June (2), August (2), September (2). Considering an average 92-day gestation period (Anderson 1983:33, Logan and Sweanor 2001), breeding of pumas that produced these litters occurred from February through June. Anderson’s observation of two 12-month birth intervals for one female (Anderson et al. 1992:48) compares with our sole observation of a 13-month birth interval for F3 (above). Segment Objective 3 & 4 From December 2, 2004 (start of our research) to June 30, 2006, we monitored 7 adult male and 10 adult female pumas to quantify survival and agent-specific mortality rates (Table 8). One adult male is known to have died. M4 was about 37 to 45 months old when he was killed by an unidentified male puma along the southeast boundary of the study area. We lost contact with 2 adult males; 1 due to GPS/VHF collar failure (M6). Evidence in the field suggests that M6 might still be alive. The other male (M31) was classified as an adult at first capture because his estimated age was 25 months. However, he might still be in the latter part of the subadult stage and could have moved away from the study area. Our radiotelemetry flights beyond the boundaries of the study area have yet to locate him. All adult female pumas have survived. Adult pumas with which we have lost contact might be recaptured on the study area as our research efforts continue. 108 �Twenty puma cubs (8 males, 12 females) have been monitored by radiotelemetry (Table 10). Two males (M5, M11) are known to have survived to the subadult stage. Two cubs (F13, M22) were killed and eaten by other pumas. F35 died 1 week after we marked her probably as a result of starvation caused when the radiocollar transmitter box got caught in her mouth. We lost contact with 9 cubs (5 females, 4 males) because they shed their expandable radiocollars. Of those 9, three females (F10, F12, F14) subsequently disappeared from the family groups (i.e., we were unable to find tracks of them with other family members) and are believed to have died. As this study proceeds, some cubs with which we have lost contact will probably be re-captured or re-observed, and thus, provide more complete survival information. Anderson et al. (1992:50) reported on the fates of 21 radio-collared pumas (11 < 24 months old, 10 ≥ 24 months old) from a total of 49 in the previous study where pumas were not hunted. Yet, 19 of those pumas died due to human causes, attributed to: legal kill outside the study area (7), capture-related (6), predator management (3), illegal kill (2), and suspected predacide (1). Other causes of mortality included, intraspecies strife (1) and disease (1). Actual age-stage and annual survival rates and agentspecific survival rates from our current effort will be compared with the Anderson et al. (1992) data set at a later date when we have greater samples, duration in research time, and more complete fate data (i.e., pumas currently without functional collars) to make such comparisons meaningful. Differences might be illuminated. For example, research of a puma population in New Mexico that was not hunted for 10 years indicated that the major cause of death for both sexes and all age stages of pumas was intraspecifies strife, cannibalism, and infanticide (Logan and Sweanor 2001). We have monitored the fates of 3 subadult pumas so far (Table 9). Males M5 and M11 were born on the study area, entered the subadult stage at about 13 months old, and have dispersed from their natal areas. F23 was captured as a subadult, survived to the adult stage, and has given birth to her first litter. Anderson et al. (1992) found that all 9 radio-collared male pumas dispersed from their natal areas, and 2 of 6 radio-collared females did not disperse from their natal areas (A. E. Anderson, Sep. 1993, errata for Anderson et al. 1992:61). Mean ± SD and range of dispersal distances (km) for 8 males, aged 10 to 13 months old at dispersal, were 86.2 ± 51.3, 23 to 151. For 4 females, aged 11 to 31 months old at dispersal, mean ± SD and range of dispersal distances (km) were 37.0 ± 15.3, 17 to 54 (Anderson et al. 1992:63). Although we have observed 2 male pumas disperse from natal areas, and no females disperse, our current research is too short in duration and samples too small yet to make meaningful comparisons with Anderson’s earlier effort, particularly regarding offspring dispersal rates, distances moved, and philopatry. Dispersal and philopatry have been explained as life history strategies in pumas that assist gene flow, colonization, population maintenance, and individual survival and reproductive success (Logan and Sweanor 2001). Thus, such strategies would be expected to be conserved, and thus expressed in puma populations at different times and different locations. In addition, because puma emigration and immigration (i.e., via dispersal) have been shown to be important processes in puma population dynamics (Sweanor et al. 2000), we need larger samples and longer research duration in this study to estimate those parameters. Segment Objective 5 Fourteen adult pumas (5 males, 9 females) were fit with Lotek 4400S GPS collars since field research began in December 2004. The collars are programmed to fix 4 locations per day (00:00, 06:00, 12:00, and 19:00). The number of GPS locations per individual puma ranged from 113―1,784 (Table 11). Activity areas for GPS-collared pumas during this report period were estimated (Table 12) with fixed kernel and minimum convex polygon home range estimators (ArcView 3.2 Animal Movement Extension), and mapped (Fig. 2). In addition, 1 adult female (F30), 1adult male (M32), and 1 independent male (M31, i.e., subadult or adult) were monitored with VHF radiocollars. The number of locations for those 3 pumas were not sufficient to estimate the size of activity areas (Table 13), however, their activity areas or locations are mapped on Fig. 2. 109 �Anderson et al. (1992) provided an exhaustive analysis of seasonal puma home ranges and movements using data collected from VHF-collared animals during 1982 to 1988. We have not yet conducted an exhaustive analysis of adult puma home ranges and movements with the GPS data from our current puma research efforts in the past 21 months. Instead, we provide only limited descriptive information in Table 13 and Fig. 2. Given the different types of location data and analytical methods, only broad descriptive comparisons might be made between the 2 studies at this time. Elemental similarities in home range attributes of pumas in the Anderson et al. (1992) research and our current effort, include: current home ranges of some puma overlap extensively with home ranges of puma documented by Anderson et al (1992), home ranges of male and female pumas are large, male home ranges are larger that female home ranges, male home ranges overlap multiple female home ranges, female home ranges overlap other female home ranges sometimes extensively, male home ranges overlap other male home ranges to a lesser extent than female home ranges. These characteristics are generally similar for pumas in other populations that have been studied with adequate intensity and duration (Beier and Barrett 1993, Logan and Sweanor 2001), and reflect behavioral tactics of male and female pumas that might contribute to individual survival and reproductive success (Logan and Sweanor 2001). Segment Objective 6 To investigate the potential that puma hunters might detect puma mothers away from their cubs, we started gathering data on spatial associations of puma mothers and their cubs during the puma hunting season, which extends from November through March each winter in Colorado. Female pumas are fare game in Colorado, unless they are accompanied by 1 or more cubs. Mothers that are caught away from their cubs could be legally harvested. Such incidents would result in cubs being orphaned. Orphaned cubs that ≤ 6 months old could have a survival rate (to the subadult stage) of < 0.05. Orphaned cubs 7 to 12 months old might have a survival rate (to the subadult stage) of about 0.7 (K. Logan, unpublished data). From November 9, 2005 to March 29, 2006 we located 4 to 5 radio-collared families of puma mothers and cubs from fixed-wing aircraft 79 times (Table 14).To assess whether mothers were apart or in close association with cubs, we needed to consider error in aerial locations. We recovered 7 puma radiocollars that we located from the airplane and fixed with GPS and then fixed the actual locations of collars on the ground with GPS. Range of location error was 20 to 520 m (mean = 282.86, SD = 164.75). We decided to use distances greater than the extreme high range of location error (520 m) as the metric to decide if puma mothers might be detected away from their cubs by hunters. Sixty-seven (84.8%) of observations located mothers and cubs ≤ 500 m apart, within the extreme margin of location error. Mothers were ≥ 650 m from their cubs during 12 (15.2%) of the observations (mean distance = 1,060 m, SD = 325.99, range = 650 to 1,600). Anderson et al. (1992:70-71) recorded 69 instances of simultaneous aerial locations of 7 pairs of puma mothers and dependent young. They reported that mothers and young were together in 21 (30.4%) of those instances, and they were 1 to 2.2 km apart in 48 (69.6%) of those instances. Segment Objective 7 Three proposals were developed with colleagues in the CDOW and Colorado State University to meet some of the objectives of the Uncompahgre Plateau puma population research and to enhance the state-wide puma management program. CDOW and our CSU colleagues are currently seeking funding to support the proposals. A proposal titled: A Non-invasive Method to Estimate Puma Populations based on DNA Genotype Mark-recapture, was developed in collaboration with geneticist Dr. Marlis Douglas (CSU). We propose to use the intensively studied puma population on the Uncompahgre Plateau for gathering genetic material to develop and test molecular techniques as a means of individually genotyping puma. If successful, the methods will be used in the field and laboratory to estimate the puma population on the 110 �Uncompahgre Plateau study area. As part of our current puma capture protocol, we collect puma tissues (i.e., integument, blood, feces, hair) and archive them with Dr. Douglas, who will lead the genetics research. We developed a proposal titled: Colorado Puma Habitat Models and Maps in collaboration with Dr. Kevin Crooks, Dr. Dave Theobald, and Dr. Ken Wilson (CSU) to develop puma habitat models and maps for the entire state of Colorado. Furthermore, we are collaborating with Dr. Crooks to assess if the GPS data currently available on pumas from this project can be used to develop a graduate degree program that investigates puma habitat use on the Uncompahgre Plateau. We collaborated with Dr. Sue VandeWoude (CSU) to develop a pilot study titled: Puma concolor immune health― Relationship to management paradigms and disease. Tissue samples (i.e., blood, saliva, feces) from pumas we capture are collected and shipped to her laboratory for pending analysis. Intensive effort to quantify puma use rates on ungulates by investigating puma GPS clusters was suspended in this report period, because we discovered in our work last year that such effort was time consuming and distracted some members of our research team from our principal objectives pertaining to puma population dynamics. Yet, our work last year proved the reliability of the GPS technology to allow us to gather quantitative information on ungulate prey use rates by pumas. In that effort, 7 GPS-collared adult pumas (3 males, 4 females) used 61 mule deer and 48 elk at 139 puma GPS clusters we investigated. In contrast, when Anderson et al. (1992) studied the pumas during 1981 to 1988, they found 68 mule deer and 3 elk used by pumas. These differences might reflect a greater number and distribution of elk currently on the Uncompahgre Plateau (~1,500 elk in GMU 62 vs. 9,663 elk in E20, sources Anderson et al. 1992:15, CDOW unpubl. 2004 post-hunt elk estimate, respectively), and poses new questions about the impact of puma predation on mule deer as a function of greater availability of elk. Consequently, the CDOW has provided additional support for a 6-month temporary technician to gather such data during the next year. An assessment will be made at the end of that work on whether we should expand the effort to investigate year-round puma use rates of ungulates on the Uncompahgre Plateau. We will evaluate the potential for collaborative research on puma-human relationships on the Uncompahgre Plateau with the developing CDOW puma-human research on the Colorado Front Range. To date, we have gathered location data on 6 (4 adult females, 2 adult males) GPS-collared pumas that have activity areas on the developed southeast portion of our study area, which includes: Fairway Pines, Loghill Village, and Fisher Creek subdivisions, numerous other private homes, Fairway Pines golf course and driving range, all adjacent to Ridgeway State Park (Fig. 3). This is the same area that Anderson et al. (1992:80) received 17 useable questionnaires on puma observations from residents, and also had some radio-collared puma frequenting these same developments. Linking puma-human research on the Uncompahgre Plateau and Front Range provides opportunities for increasing sample size (i.e., puma numbers, study sites) and observing variation in puma-human relationships. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 20 months of effort, 36 pumas (14 adults, 3 subadults, 19 cubs) have been captured, sampled, marked, radio-collared and released to quantify vital rates and puma population dynamics in a reference situation (i.e., without sport-hunting off-take). Data on research efforts and puma capture, fates, reproduction, and activity areas are presented. As of July 2006, 20 radio-collared puma are within the study area. Fourteen adult pumas were fit with GPS collars, yielding 113 to 1,784 locations per puma. We started investigating the potential vulnerability of puma mothers to capture by hunters while away from their cubs. Preliminary comparisons of aspects of puma biology and ecology were made between our new research effort on the Uncompahgre 111 �Plateau and that of Anderson et al. (1992) in GMU 62 during 1981 to 1988. Research efforts for year 3 will focus on increasing numbers and distribution of sampled, marked, and GPS/radio-collared pumas on the study area, especially in the northeast and southwest portions of the study area where we have been finding relatively little evidence of pumas, possibly due to low density. Efforts will resume to estimate frequency of puma use of mule deer and elk on the Uncompahgre Plateau. Puma GPS location data will be used to: design enumeration methods in the field, develop and test puma habitat models and maps, and develop research on puma-ungulate relationships on the Uncompahgre Plateau contingent upon funding and support. We will increase our efforts to obtain outside funding for other projects we have proposed on puma genetics, puma habitat use, modeling, and mapping, and puma diseases. We will consider incorporating pumas on the Uncompahgre Plateau to address questions pertaining to research on pumahuman relationships on the Colorado Front Range. 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STONER, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. SWEANOR, L. L., K. A. LOGAN, AND M. G. HORNOCKER. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. _____, L. L., K. A. LOGAN, J. W. BAUER, W. M. BOYCE, AND B. MILSAP. 2006 in review. Puma-human relationships in a California, USA state park. Biological Conservation. VAN BALLENBERGHE, V. 1983. Rate of increase of white-tailed deer on the George Reserve: a reevaluation. Journal of Wildlife Management 47:1245-1247. WATKINS, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. WILLIAMS, B. K., J. D. NICHOLS, AND M. J. CONROY. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. WHITE, G. C., D. R. ANDERSON, K. P. BURNHAM, AND D. L. OTIS. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. WORTON, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. YOUNG, S. P. AND E. A. GOLDMAN. 1946. The puma: mysterious American cat. The Wildlife Institute, Washington, D. C. Prepared by: Kenneth A. Logan, Wildlife Researcher 113 �Table 1. Summary of puma capture efforts with dogs from November 21, 2005 to May 26, 2006, Uncompahgre Plateau, Colorado. Month November No. Search Days 4 December 18 January No. & type of puma tracks founda No. & type of pumas pursued No. & I.D. or type of pumas captured 12 tracks: 2 male, 9 female, 1 unspecified sex 16 tracks: 10 male, 4 female, 2 unspecified sex 0 pursuits 0 captures 5 pursuits: 4 males, 1 female 19 50 tracks: 15 male, 23 female, 12 cub 11 pursuits: 4 males, 4 females, 3 cubs February 19 9 pursuits: 2 males, 3 females, 4 cubs March 7 39 tracks: 11 male, 14 female, 9 cub, 5 unspecified sex 11 tracks: 2 male, 5 female, 4 cub 11 tracks: 3 male, 5 female, 3 cub 2 pumas captured 3 times: M5 recaptured, 1 male captured twice but not handledb 3 pumas captured: F23, F24, 1 male not handled 1 puma captured: F8 recaptured 7 pursuits: 1 male, 3 females, 3 cubs 9 pursuits: 3 males, 4 females, 2 cubs 2 pumas captured: M27, F8 recaptured April 7 3 puma captured: M29 & M31 captured, M15 recaptured May 8 10 tracks: 5 male, 5 2 pursuits: 1 male, 1 female 2 pumas captured: F24 female recaptured, M1 recaptured 82 149 tracks found: 48 male, 43 pursuits: 15 males, 16 14 captures: 3 males & 2 TOTALS 65 female, 28 cub, 8 females, 12 cubs females captured for the 1st time, 2 different males unspecified sex captured 3 times but not handled, 1 male recaptured, 2 females recaptured 3 times, 1 subadult male recaptured, 1 subadult or adult male recaptured, 1 male cub recaptured a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female. b Pumas are not handled for a variety of safety reasons: tree to dangerous to climb for researchers, puma treed near river, creek or cliff, puma might fall from tree after drug induction. Table 2. Summary of puma capture efforts with dogs, December 2004 to May 2006, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Track detection effort 109/78 = 1.40 tracks/day 149/82 = 1.82 tracks/day Pursuit effort 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 82/43 = 1.91 day/pursuit 82/14 = 5.86 day/capture 114 Effort to capture a puma for the first time 11 pumas captured for first time (minus M1, F3, & large female) 11/78 = 0.14 capture/day 78/11 = 7.09 day/capture 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture �Table 3. Pumas that were captured with aid of dogs, but were not handled for safety reasons, from December 2005 to January 2006, Uncompahgre Plateau, Colorado. Puma sex Age stage Capture date 12-04-05 Male subadult or adult Male Male Location Roatcap Mesa subadult or adult 12-05-05 Cushman Creek adult 01-22-06 San Miguel River Canyon Comments Puma climbed to top of huge Ponderosa pine tree. This puma might be M32. This puma was the same animal caught 12-04-05. Climbed tall spruce tree on a ledge. Puma climbed Ponderosa pine tree beside the river. This puma might be M29. Table 4. Summary of puma capture efforts with ungulate road-kill baits, puma kills, and cage traps from August 2, 2005 to June 27, 2006, Uncompahgre Plateau, Colorado.a Month August No. of Sites 4 Puma activity & capture effort results Male puma scavenged a mule deer on 8-20-05. Cage trap set 8-20 & 8-21-05; puma did not return. September 7 Male puma scavenged a mule deer on 9-16-05; subadult M5 was recaptured there and was fit with a VHF collar (he had shed the expandable collar he wore as a cub). October 10 Puma F16 captured 10-11-05 at an elk kill. Puma scavenged mule deer on 10-17-05. Cage trap set 10-18 and 10-19-05; puma did not return. November 12 Puma F16 recaptured 11-1-05 at a mule deer kill; her faulty GPS collar was replaced. Puma F16 scavenged a mule deer on 11-27-05. No attempt to recapture her. December 1 No puma activity detected. January 2 No puma activity detected. February 9 Puma F25 and cub M26 captured 2-8-06 at a mule deer kill. Puma F7 scavenged a mule deer on 2-26 & 2-17-06. No attempt to recapture her. Puma F3 scavenged a mule deer on 2-26-06. No attempt to recapture her. March 11 Male puma completely scavenged a mule deer over the weekend of 3-18 & 1906. Female puma completely scavenged a mule deer over the weekend of 3-18 & 19-06. Female puma scavenged a mule deer 3-21 to 3-23-06; puma F28 was captured there 3-23-06. Pumas F3 & cub F21 scavenged a mule deer 3-23 to 3-27-06. No attempt was made to recapture the pumas. Female puma completely scavenged a mule deer over the weekend of 3-25 & 26-06. Puma F7 was recaptured at a mule deer she scavenged on 3-30-06; her GPS collar was replaced. April 11 Puma F30 captured 4-15-06 at a mule deer kill. Male puma scavenged a mule deer on 4-20-06. Cage trap was set 4-20 & 4-2106; puma did not return. Male puma scavenged the same mule deer on 4-26-06; M32 was captured there on 4-26-06. Puma F2 and cubs F9 & M11 scavenged a mule deer on 4-2-06. Cub M11 was recaptured on 4-2-06 and fit with a VHF collar. F2 was recaptured there 4-3-06 and her GPS collar was replaced. May 0 No fresh road-killed ungulate carcasses were available. June 3 No puma activity. a We used 77 road-killed mule deer, 3 road-killed elk, 3 puma-killed mule deer, and 1 puma-killed elk at 23 different sites. Of the road-killed ungulate baits, 16 of 80 (20.0%) were scavenged by pumas. 115 �Table 5. Adult and subadult pumas captured for the first time, sampled, tagged, and released from October 2005 to April 2006, Uncompahgre Plateau, Colorado. Puma I.D. Sex Estimated Age (mo.) Mass (kg) Capture date Capture method F16 F 33 42 10-11-05 Cage trap F23 F24 F25 M27 F28 M29 F30 M31 M32 F F F M F M F M M 17 57 80 55 33 80 33 25 56 42 38 46 61 43 65 34 40 57 01-04-06 01-17-06 02-08-06 03-10-06 03-23-06 04-14-06 04-15-06 04-19-06 04-26-06 Dogs Dogs Cage trap Dogs Cage trap Dogs Cage trap Dogs Cage trap Location Ridgeway Reservoir Dam, Ridgeway State Park San Miguel River Canyon Horsefly Creek (west) Loghill Mesa Big Bucktail Creek Big Bucktail Creek Big Bucktail Creek Wildcat Canyon Craig Draw Spring Creek Table 6. Pumas recaptured with dogs and cage traps, September 2005 to May 2006, Uncompahgre Plateau, Colorado. Puma I.D. Recapture date Mass kg Estimated Age (mo.) M5 F16 M5 F8 F8 F7 M11 F2 M15 F24 M1 09-16-05 11-01-05 12-30-05 02-07-06 03-21-06 03-30-06 04-02-06 04-03-06 04-13-06 05-17-06 05-26-06 39 42 Observed Observed Observed 35 32 43 23 Observed Observed 13 34 16 32 33 69-77 10 64 9.5 61 51 Capture Method Cage trap Cage trap Dogs Dogs Dogs Cage trap Cage trap Cage trap Dogs Dogs Dogs Process Re-collared Re-collared None None None Re-collared Re-collared Re-collared Re-collared None None Table 7. Puma cubs sampled August 2005 to June 2006 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) F17 F Sept. 22, 2005 34 2.5 F16 32 F18 F Sept. 22, 2005 34 2.0 “ “ M19 M Sept. 22, 2005 34 2.0 “ “ M20 M Sept. 22, 2005 34 2.1 “ “ F21b F Sept. 26, 2005 37 2.8 F3c 49 M Sept. 26, 2005 37 2.8 “ “ M22b M26d M Aug. 2005 183 12.0 F25 74 F33 F May 30, 2006 31 1.9 F23 21 F34 F May 30, 2006 31 1.9 “ “ F35 F May 30, 2006 31 2.2 “ “ F36 F June 9, 2006 29 1.9 F28 36 M37 M June 9, 2006 29 2.1 “ “ a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location foci for mothers at nurseries. b Puma M6 is a candidate sire of cubs F21 & M22; he consorted with F3 (based on their joint GPS location data) during June 22―24, 2005. This would indicate a gestation period of 93―95 days. c F3 gave birth to a previous litter in August 2004. From that litter, offspring M5 survived to independence. Birth interval is 13 months (Aug. 2004 to Sept. 2005). d Estimated age of M26 was based on morphometric comparisons with known-age cubs (Logan and Sweanor 2001, and unpublished data, i.e., ~6 mo. ≈183 days). He was initially captured in a cage trap with his mother F25 on Feb. 8, 2006. 116 �Table 8. Summary for individual adult puma survival and mortality, December 2004 to June 2006, Uncompahgre Plateau, Colorado. Puma I.D. Monitoring span No. days Status: Alive/Lost contact/Dead; Cause of death M1 12-08-04 to 06-30-06 569 Alive. M4 01-28-05 to 12-28-05 333 Dead; killed by a male puma.a M6 02-18-05 to 02-22-06 369 Lost contact― failed GPS/VHF collar. M27 03-10-06 to 06-30-06 112 Alive. M29 04-14-06 to 06-30-06 77 Alive. M31 04-19-06 to 04-26-06 7 Lost contact.b M32 04-26-06 to 06-30-06 65 Alive. F2 01-07-05 to 06-30-06 539 Alive. F3 01-21-05 to 06-30-06 525 Alive. F7 02-24-05 to 06-30-06 491 Alive. F8 03-21-05 to 06-30-06 466 Alive. F16 10-11-05 to 06-30-06 262 Alive. F23 02-05-06 to 06-30-06 146 Alive. F24 01-17-06 to 06-30-06 164 Alive. F25 02-08-06 to 06-30-06 142 Alive. F28 03-23-06 to 06-30-06 99 Alive. F30 04-15-06 to 06-30-06 76 Alive. a Puma M4 died at the estimated age of 37―45 months old. b Puma M31 estimated age at capture was 25 months, at the lower margin of puberty. But he might have been a dispersing subadult, instead of an adult. He may have moved away from the study area. No VHF signals have been received of M31 in the area surrounding the study area as of 07-29-06. Table 9. Summary of subadult puma survival and mortality, December 2004 to June 2006, Uncompahgre Plateau, Colorado. Puma Monitoring span No. Status: Alive/Survived to adult stage/ Lost contact/Dead; I.D. days Cause of death M5 09-16-05 to 06-30-06 287 Alive; dispersed from natal area. M11 06-21-06 to 06-30-06 7 Alive; dispersed from natal area. F23 01-04-06 to 02-04-06 31 Alive; survived to adult stage; gave birth to first litter at ~21 months old. 117 �Table 10. Summary for individual puma cub survival and mortality, December 2004 to July 2006, Uncompahgre Plateau, Colorado. Puma I.D. Estimated Age at capture (days) Estimated survival span from 1st capture to fate or last monitor date Age to last monitor date alive or at death Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/Dead; Cause of death Mother I.D. M5 183 02-04-05 to 06-30-06 22 mo. F3 F9 31 F10 31 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 329 days 207―246 days M11 31 06-27-05 to 07-11-06 14 mo. F12 42 07-01-05 to 12-08-05― 01-26-06 245―294 days F13 42 F14 26 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 100 days 226―257 days M15 26 F17 34 F18 34 M19 34 M20 34 F21 37 M22 37 07-22-05 to 06-06-06 10-26-05 to 06-06-06 10-26-05 to 06-30-06 10-26-05 to 07-27-06 10-26-05 to 05-24-06 11-02-05 to 06-30-06 11-02-05 to 12-21-05― 12-22-05 345 days 257 days 281 days 306 days 244 days 277 days 86―87 days Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 13 mo. old . Lost contact― shed radiocollar 04-1906―04-26-06. Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 12-30-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Lost contact― shed radiocollar 07-2805―08-01-05. Tracks of F12 found in association with mother F7 on 12-08-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Dead; killed and eaten by a puma (sex unspecified). Lost contact― shed radiocollar 01-2006―01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-0606―06-14-06. Lost contact― shed radiocollar 06-0606―06-14-06. Alive. M26 183 F33 31 F34 31 F35 31 F36 29 M37 29 02-08-06 to 03-21-06 06-30-06 to 07-31-06 06-30-06 to 07-31-06 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 224 days 62 days 62 days 38 days 49 days 49 days a F2 F2 F2 F7 F7 F8 F8 F16 F16 Lost contact― shed radiocollar 07-2706―08-02-06. Lost contact― shed radiocollar 05-2406―05-25-06. Alive. F16 Dead; killed and eaten by male puma 12-2105―12-22-05. F3 Lost contact― shed radiocollar 03-2106―03-24-06. Alive. F25 Alive. F23 Dead; research-related fatality.a F23 Alive. F28 Alive. F28 F16 F3 F23 Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. 118 �Table 11. Numbers of GPS locations for adult puma on the Uncompahgre Plateau, Colorado, December 2004 to June 2006. Puma I.D. M1 M4 M6 M27 M29 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a No. locations M M M M M F F F F F F Acquisition rate average, range, nb 77, 73―84, 13 70, 57―84, 10 84, 73―93, 9 77, 67―84, 3 68, 63―75, 3 75, 43―90, 18 76, 55―88, 17 67, 26―86, 17 70, 48―81, 14 76, 58―90, 10 79, 45―92, 6 adult 12-08-04 to 06-21-06 1,784 adult 01-28-05 to 12-28-05e 910 adult 02-18-05 to 11-23-05f 926 adult 03-11-06 to 06-21-06 316 adult 04-14-06 to 07-27-06 287 adult 01-07-05 to 07-12-06 1,664 adult 01-21-05 to 07-26-06 1,649 adult 02-24-05 to 07-26-06 1,423 adult 03-21-05 to 07-05-06 1,328 adult 10-12-05 to 07-03-06 833 subadult, 01-04-06 to 02-04-06 113 02-05-06 to 07-17-06 511 adult F24 F adult 01-17-06 to 06-14-06 523 88, 86―93, 5 F25 F adult 02-09-06 to 07-12-06 551 78, 68―87, 5 F28 F adult 03-24-06 to 07-07-06 321 74, 61―89, 4 a GPS collars on pumas are remotely downloaded at approximately 1-month intervals. The last date in Dates monitored includes last location from the last GPS data download for an individual puma in this report. b n = number of remote downloads. Table 12. Estimated use areas of GPS-collared pumas on the Uncompahgre Plateau, Colorado, 2005 to 2006.a Puma I.D. No. locations Time span No. months 95% Fixed kernel (km2) 50% Fixed kernel (km2) 100% Minimum convex polygon (km2) 1,129.0 318.5 542.0 504.0 288.3 183.0 194.0 139.0 215.0 74.3 226.0 111.7 115.9 114.8 M1 1,083 07-01-05 to 06-21-06 12 988.1 189.1 M4b 481 07-01-05 to 12-28-05 5 208.8 29.6 M6c 465 07-01-05 to 11-23-05 4.8 550.8 67.3 M27 316 03-11-06 to 06-21-06 3.3 452.0 40.3 M29 220 04-14-06 to 06-30-06 2.5 276.1 14.0 F2 1,173 07-01-05 to 06-30-06 12 67.6 6.9 F3 1,079 07-01-05 to 06-30-06 12 84.3 11.7 F7 1,058 07-01-05 to 06-30-06 12 110.4 16.2 F8 1,043 07-01-05 to 06-30-06 12 84.1 7.7 F16 825 10-12-05 to 06-30-06 8.6 39.9 4.8 F23 566 01-04-06 to 06-30-06 5.9 109.2 13.0 F24 574 01-17-06 to 06-30-06 5.5 26.8 2.4 F25 453 02-09-06 to 06-30-06 4.7 105.5 16.1 F28 306 03-24-06 to 06-30-06 3.2 86.2 14.8 a Use areas were estimated by using the Animal Movement extension in ArcView 3.2. b Puma M4 died on 12-28-05; he was killed by a male puma. c Puma M6’s GPS collar malfunctioned on 11-23-05. His last VHF location was fixed on 02-22-06. The VHF beacon failed after that date. Table 13. VHF-radio-collared independent pumas on the Uncompahgre Plateau, Colorado, 2006. Puma I.D. F30 M31 Sex Age stage Dates monitored No. locations F M 04-15-06 to 06-28-06 04-09-06 to 04-26-06 11 2 M32 M Adult Adult or subadult Adult 04-26-06 to 06-28-06 6 119 �Table 14. Summary of puma mother and cub associations by distance (m) during fixed-wing flights, November 9, 2005 to March 29, 2006. Month No. flights No. puma familiesa Ages of cubs (mo.) No. observations with No. observations with mothers & cubs mothers & cubs ≤500 m >600 m apartb apart Nov. 3 4 2―6 10 2 Dec. 4 4 3―7 16 4 Jan. 5 4 4―8 16 4 Feb. 4 5 5―9 16 2 Mar. 2 5 6―10 9 0 Totals 18 4―5 2―10 67 12 a All puma mothers wore GPS-radiocollars. At least 1 cub in the litter wore a VHF radiocollar. b Mean = 1,060 m, SD = 325.99, range = 650―1,600. GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Estimation Methods for Monitoring Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Habitat Maps Puma―Prey Relationships Models Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this report for the puma management goal (at top). 120 �! ( ! ( ! ( ! ( ! ( Clifton County Boundary Highways Study Area ! ( ! ( ! ( ! ( ! ( Delta ! ( M1 ! ( ! ( M32 Montrose F8 M27 ( ! F23 ! ( ! ( F28 F3 M31 F24 M4 F7 F30 F2 M6 ( ! F16 F25 ! ( Ridgeway M29 ! ( Norwood ! ( ! ( 0 5 10 20 30 40 Kilometers ! ( Figure 2. The Uncompahgre Plateau Puma Study Area with activity areas of GPS- and VHF- radiocollared pumas depicted with 100% Minimum Convex Polygons (for ease of viewing), and 2 locations of one independent puma for which we lost contact (M31), 2005 to 2006. 121 �Figure 3. Locations of 6 GPS-collared pumas on the human-developed southeast portion of the Uncompahgre Plateau puma study area, 2005-2006, intended only to show potential for developing research on puma-human relationships on this study area and the Colorado Front Range. 122 �Colorado Division of Wildlife July 2005 – June 2006 WILDLIFE RESEARCH REPORT State of Cost Center Work Package No. Task No. Colorado 3430 7210 1 : Division of Wildlife : Mammals Research : Customer Services/Research Support : Library Services Federal Aid Project: N/A : Period Covered: July 1, 2005 – June 30, 2006 Author: J. A. Boss Personnel: J. A. Boss, B. C. Jones, and A. R. Taylor. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT During the Segment, the following were accomplished: 850 Publications acquired by the Research Center Library for the use of Colorado Division of Wildlife (CDOW) employees, cooperators, wildlife educators, and the public. These publications include books, interlibrary loan materials, periodicals, and newsletters. 2,297 Items of information delivered to CDOW employees, cooperators, wildlife educators, and the public, resulting from requests and literature searches. 775 Items of information cataloged into the electronic catalog, which including duplicates and additional volumes, expanded the Research Center Library inventory to 25,104 items. 1,441 Items of information entered into the electronic catalog for the maintenance of the inventory and circulation system of the Research Center Library. 1,232 Items checked-out by CDOW employees, cooperators, wildlife educators, and the public indicating use of library services. 3,436 Items of information delivered that are produced by the CDOW employees, cooperators, wildlife educators, and the public. These items include CDOW and other publications (2,938), research articles by CDOW personnel (274), and CDOW federal aid reports (224). 123 �WILDLIFE RESEARCH REPORT COLORADO DIVISION OF WILDLIFE RESEARCH LIBRARY SERVICES JACQUELINE A. BOSS P.N. OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Division of Wildlife (CDOW) employees, cooperators, wildlife educators, and the public. SEGMENT OBJECTIVES 1. Continue to improve and modernize library services by implementing the SirsiDynix Horizon library automation system via an Application Service Provider (ASP) model (project began in June 2002). By joining the Automation System Colorado Consortium (ASCC) we were able to take advantage of a LSTA grant written by the Colorado State Library staff, which facilitated the implementation of this system. 2. Continue to develop, improve, and implement the CDOW Research Center Library web-site (started in June 2004) by implementing the SirsiDynix horizon system online to serve broader spectrum of patrons of the CDOW Research Center Library. 3. Continue to attend ASCC meetings and participate in SirsiDynix Horizon online classes to enhance utilization of the SirsiDynix system. SUMMARY OF LIBRARY SERVICES Maintain and Build Electronic Catalogs of all Research Library Holdings 775 Total number of items cataloged during this period of time. This includes not only acquisitions, but also older materials from the library collection being entered into the electronic catalog for the first time. Among the acquisitions are Federal Aid: Job Progress Reports and manuscripts written by CDOW researchers and other employees. 1,441 Total number of items of information added to the electronic circulation system during this period. This includes not only the above mentioned newly cataloged items, but also newly acquired serials, volumes, additional copies, and other items being assigned scanning numbers for the electronic circulation system for the first time. $239,772 Estimated value of the 25,104 items in the Research Center Library collection as of June 30, 2006. The project to determine the value of the library collection began in May 2000. As time permits, the value of books already in the collection is determined, and added to the already “estimated value.” Each month’s addition of values of older materials, plus the new materials, increases the value of the Library collection. Not included in the “assumed value” of the Library collection are all of the periodicals, older materials, and government documents, which continue to be a large part of the collection, thus the “estimated value” of the Library collection continues to grow month by month. 124 �Publications Acquired in the Research Center Library ANTHONISE, E. I., R. E. AUTENRIETH, D. E. BROWN, J. CANCINO, R. M. LEE, R. A. OCKENFELS, B. W. O’GARA, T. M. POJAR, AND J. D. YOAKUM., compilers. 2006. Pronghorn management guides. 4th edition. Pronghorn Workshop and Montana Department Game and Fish, Bismarck, North Dakota, USA. AUSTIN, D., editor. 2003. Proceedings of the Western Association of Fish and Wildlife Agencies : Port Angeles, Washington : July 17 – 23, 2003. Washington. Department of Fish and Wildlife 83rd Annual Conference. BANKS, A. J. 2001. A guide to North American bird conservation – the four major plans and NABCI. Rocky Mountain Bird Observatory, Brighton, Colorado, USA. BEAUSOLEIL, R. A. AND D. A. MARTORELLO., editors. 2005. Proceedings of the Eighth Mountain Lion Workshop : Olympia, Washington. Washington Department of Fish and Wildlife, Olympia, Washington, USA. BEISSINGER, S. R., J. R. WALTERS, D. G. CATANZARO, K. G. SMITH, J. B. DUNNING, JR., S. M. HAIG, B. R. NOON, AND B. M. STITH. 2006. Modeling approaches in avian conservation and the role of field biologists. Ornithological monograph; no. 59. The American Ornitholoogists’ Union, Washington, D.C., USA. BETTAS, G. A., C. R. BYERS, AND J. RENEAU. 2001. Boone and Crockett Club's 24th big game awards : 1998 - 2000 : a book of the Boone and Crockett Club containing tabulations of outstanding North American big game trophies accepted during the 24th awards entry period of 1998 – 2000. Boone and Crockett Club, Missoula, Montana, USA. BYERS, C. R. 2004. Boone and Crockett Club's 25th big game awards : 2001 - 2003 : a book of the Boone and Crockett Club containing tabulations of outstanding North American big game trophies accepted during the 25th awards entry period of 2001 – 2003. Boone and Crockett Club, Missoula, Montana, USA. BISHOP, C. J. 1998. Mule deer fawn mortality and habitat use, and the nutritional quality of bitterbrush and cheatgrass in southwest Idaho. M.S. Thesis, University of Idaho, Moscow, Idaho, USA. BOYER, M., editor. 2004. Proceedings of the Western Association of Fish and Wildlife Agencies : Sun Valley, Idaho : July 23 – 30, 2004. 84th Annual Conference. Idaho Dept. of Fish and Game. BRAUN, C. E., editor. 2005. Techniques for wildlife investigations and management. 6th edition. The Wildlife Society, Bethesda Maryland, USA. BYERS, E. AND K. M. PONTE. 2005. The conservation easement handbook. 2nd edition, revised and expanded. Land Trust Alliance, Washington, D. C., USA. CWD ALLIANCE. [2005]. The Second International Chronic Wasting Disease Symposium : July 12 – 14, 2005 : Madison, Wisconsin. CDW Alliance, Madison, Wisconsin, USA. CASE, S. R. 1995. The Poudre : a photo history. S.R. Case, Bellvue, Colorado, USA. COLLINS, J. A. AND L. A. SPRAGUE. 2005. The Cache la Poudre River, Colorado, as a drinking-water source. Fact sheet; FS-05-3037. U.S. Geological Survey, Reston, Virginia, USA. COLORADO. DIVISION OF WILDLIFE. AQUATIC SECTION. 1995. Colorado Division of Wildlife : state fish hatcheries disease prevention and construction project recommendations. Colorado Division of Wildlife, Denver, Colorado, USA. COUGAR MANAGEMENT GUIDELINES WORKING GROUP. 2005. Cougar management guidelines. 1st edition. WildFutures, Bainbridge Island, Washington, USA. DUNN, E. H., J. BART, B. T. COLLINS, B. CRAIG, B. DALE, C. M. FRANCIS, S. WOODLEY, AND P. ZORN. 2006. Monitoring bird populations in small geographic areas. Special publication. Canadian Wildlife Service, Ottawa, Ontario, Canada. DURR, P. A. AND A. C. GATRELL. 2004. GIS and spatial analysis in veterinary science. CABI Publishing, Cambridge, Massachusetts, USA. EVERSOLE, A. G., editor. [2005]. Proceedings of the Fifty-eighth Annual Conference : Southeastern Association of Fish and Wildlife Agencies : October 31 – November 3, 2004 : Hilton Head 125 �Island, South Carolina. Southeastern Association of Fish and Wildlife Agencies, Tallahassee, Florida, USA. FESTA-BIANCHET, M. AND M. APOLLONIO. 2003. Animal behavior and wildlife conservation. Island Press, Washington, D.C., USA. GROOM, M. J., G. K. MEFFE, AND C. R. CARROLL. 2006. Principles of conservation biology. Sinauer Associates, Sunderland, Massachusetts, USA. GUSTAFSON, SID. 2003. First aid for the active dog. Alpine Blue Ribbon Books, Loveland, Colorado, USA. GUTHERY, F. S., A. R. RYBAK, S. D. FUHLENDORF, T. L. HILLER, S. G. SMITH, W. H. PUCKETT, JR., AND R. A. BAKER. 2005. Aspects of the thermal ecology of bobwhites in north Texas. Wildlife monograph no. 159. The Wildlife Society, Bethesda, Maryland, USA. HEIMER, W., D. TOWEILL, AND K. HURLEY, editors. 2006. Northern Wild Sheep and Goat Council : Proceedings of the Fourteenth Biennial Symposium : May 15-22, 2004 : Alaska’s Inside Passage. Northern Wild Sheep and Goat Council, Cody, Wyoming, USA. HENDRICKSON, D. A. AND L. T. FINDLEY. 2002. Proceedings of the Desert Fishes Council : Volume XXXIII : 2001 annual symposium : 15 – 18 November : Sul Ross State University : Alpine, Texas U.S.A. Desert Fishes Council , Bishop, California, USA. HENDRICKSON, D. A. AND L. T. FINDLEY. 2005. Proceedings of the Desert Fishes Council : Volume XXXIV and XXXV : 2002 and 2003. Desert Fishes Council, Bishop, California, USA. HUDSON, P. J., A. RIZZOLI, B. T. GRENFELL, H. HEESTERBEEK, AND A. P. DOBSON. 2002. The ecology of wildlife diseases. Oxford University Press, United Kingdom. JENSEN, W. F., editor. 2006. Proceedings of the 21st Biennial Pronghorn Workshop : 2004 : May 1 May 4, 2004 : Bismarck, North Dakota. North Dakota Game and Fish Department, Bismarck, North Dakota, USA. LAFLEUR, J. A. 2001. Master bird checklist for the mountain west ecoregion : national parks, monuments and recreation areas. Better Birdwatching CD-ROMs, Fort Collins, Colorado, USA. LASEE, B. A., editor. 1995. Introduction to fish health management. 2nd edition. U.S. Fish and Wildlife Service, Onalaska, Wisconsin, USA. LEATHERMAN, D. A., H. E. MCNULTY, M. E. SCHOMAKER, AND D. L. LYNCH. 1996. Aspen : a guide to common problems in Colorado. Bulletin 559A. Colorado State University Cooperative Extension, Fort Collins, Colorado, USA. LUKACS, P. M. 2005. Statistical aspects of using genetic markers for individual identification in capturerecapture studies. Ph.D. Dissertation, Colorado State University, Fort Collins, Colorado, USA. MASTERSON, L. 2006. Living with bears : a practical guide to bear country. 1st edition. PixyJack Press, Masonville, Colorado, USA. MCCARTER, J., editor. [2002]. Proceedings of the Western Association of Fish and Wildlife Agencies : Albuquerque, NM : July 11 – 17, 2002. 82nd annual conference. New Mex. Dept. of Game and Fish. MECH, L. D. AND L. BOITANI, editors. 2003. Wolves : behavior, ecology, and conservation. University of Chicago Press, Chicago, Illinois, USA. MIRANDA, L. E., AND D. R. DEVRIES, editors. 1996. Multidimensional approaches to reservoir fisheries management. American Fisheries Society Symposium; 16. American Fisheries Society, Bethesda, Maryland, USA. O’GARA, B. W. AND J. D. YOAKUM, editors. 2004. Pronghorn : ecology and management. A Wildlife Management Institute Book. University Press of Colorado, Boulder, Colorado, USA. PETERSEN, D. 1998. Ghost grizzlies : Does the great bear still haunt Colorado? Johnson Books, Inc., Boulder, Colorado USA. PRYOR, K. 1984. Don’t shoot the dog! How to improve yourself and others through behavioral training. Bantam Books, New York, New York, USA. PRYOR, K. 1999. Don’t shoot the dog! The new art of teaching and training. Bantam Books, New York, New York, USA. 126 �RAMIREZ, K. 1999. Animal training : successful animal management through positive reinforcement. Shedd Aquarium, Chicago, Illinois, USA. RODGERS, A. R. AND G. W. REDMOND, editors. [2005]. Alces 39 : 2003 : a journal devoted to the biology and management of moose. Lakehead University, Thunderbay, Ontario, Canada. RONI, P., editor. 2005. Monitoring stream and watershed restoration. American Fisheries Society, Bethesda, Maryland, USA. ROLLEY, R. E. 2005. Controlling chronic wasting disease in Wisconsin : a progress report and look toward the future. Wisconsin Department of Natural Resources, Madison, Wisconsin, USA. SCHWARTZ, C. C., M. A. HAROLDSON, G. C. WHITE, R. B. HARRIS, S. CHERRY, K. A. KEATING, D. MOODY, AND C. SERVHEEN. 2006. Temporal, spatial, and environmental influences on the demographics of grizzly bears in the Greater Yellowstone Ecosystem. Wildlife monographs; 161. The Wildlife Society, Lawrence, Kansas, USA. SMITH, D. W., D. R. STAHLER, AND D. S. GUERNSEY. 2005. Yellowstone Wolf Project : annual report : 2004. Yellowstone Center for Resources, Yellowstone National Park, Wyoming, USA. SOIL AND WATER CONSERVATION SOCIETY. 2001. Realizing the promise of conservation buffer technology. Soil and Water Conservation Society, Ankeny, Iowa, USA.. STROHM, K. M. 2005. Modeling sage-grouse demographic rates and population change. M.S. Thesis, Colorado State University, Fort Collins, Colorado, USA. THOMPSON, R. W., AND J. C. HALFPENNY. 1989. Canada lynx presence on Vail Ski Area. Western Ecosystems, Inc., Lafayette, Colorado USA. THOMPSON, R. W., AND J. C. HALFPENNY. 1991. Canada lynx presence on the proposed East Fork Ski Area. Western Ecosystems, Inc., Boulder, Colorado USA. TORRES, S. 2005. Lion sense. 2nd edition. A Falcon Guide. Globe Pequot Press, Helena, Montana, USA. TOWEILL, D. E. AND V. GEIST. 1999. Return of royalty : wild sheep of North America. Boone and Crockett Club, Foundation for North American Wild Sheep Missoula, Montana, USA. WRIGHT, P. L. AND W. H. NESBITT. 2003. A Boone and Crockett Club field guide to measuring and judging big game. A Boone and Crockett Club publication. Boone and Crockett Club, Missoula, Montana, USA. U.S. DEPARTMENT OF AGRICULTURE. NATURAL RESOURCES CONSERVATION SERVICE. n.d. Buffers : common-sense conservation ; tried buffers yet? A communication toolkit. U.S. Department of Agriculture, National Resources Conservation Service. Publications Donated to the Research Center Library KERSHAW, L., A. MACKINNON, AND J. POJAR. 1998. Plants of the Rocky Mountains. Lone Pine field guide. Lone Pine Publishing, Auburn, Washington, USA. MCBRIDE, C. 1977. The white lions of Timbavati. Paddington Press, Ltd, New York, New York, USA. WOCKNER, G., G. MCNAMEE, AND SUEELLEN CAMPBELL, editors. 2005. Comeback wolves : western writers welcome the wolf home. Johnson Books, Inc., Boulder, Colorado USA. WRIGHT, W. H. 1977. The grizzly bear : the narrative of a hunter-naturalist. Reprint of the 1913 issue of the editor. Scribner, New York, New York, USA. AV Materials Acquired in the Research Center Library OBMASCIK, M. 2004. The big year : a tale of man, nature, and fowl obsession. 5 CDs : 6 hours. Random House, Inc. New York, New York, USA. OQUIRRH PRODUCTIONS. 2005. Hunter education tools : the ultimate teaching tool for hunter education instructors. CD and DVD editions. Oquirrh Productions, LC. Salt Lake City, Utah, USA. 127 �U.S. FISH AND WILDLIFE SERVICE. 2005. America’s duck chasers. DVD 2:43 min. U.S. Fish and Wildlife Service. Shepherdstown, West Virginia, USA. U.S. FISH AND WILDLIFE SERVICE. 2005. Status of waterfowl 2005 : 2005 report on North America’s waterfowl populations and habitat conditions. VHS and DVD 19:51 min. Stefan Dobert Productions, Inc. Theses, Documents and Books Obtained on Interlibrary Loan Literature Searches and Information Delivered ALDEN RESEARCH LABORATORY, EMPIRE STATE ELECTRIC ENERGY CORPORATION AND STONE AND WEBSTER ENGINEERING CORPORATION. 1981. Laboratory evaluation of fine-mesh screening for the protection of fish larvae at intakes. Worcester Polytechnic Institute, Holden, Massachusetts, USA. ALDEN RESEARCH LABORATORY AND STONE AND WEBSTER ENGINEERING CORPORATION. 1981. Laboratory evaluation of fish protective devices at intakes. Worcester Polytechnic Institute, Holden, Massachusetts, USA. ARENT, L. AND M. MARTELL. 1996. Care and management of captive raptors. University of Minnesota, The Raptor Center, St. Paul, Minnesota, USA. THE ASPEN PANEL. 1985. Guidelines for managing aspen. The Aspen Panel, Denver, Colorado, USA. BALLOU, J. D., G. GILPIN, AND T. J. FOOSE, editors. 1995. Population management for survival and recovery : analytical methods and strategies in small population conservation. Methods and cases in conservation science. Columbia University Press, New York, New York, USA. BARNHISEL, R. I., R. G. DARMODY, AND W. L. DANIELS, editors. 2000. Reclamation of drastically disturbed lands. Agronomy no. 41. American Society of Agronomy, Madison, Wisconsin, USA. BARNOSKY, A. D., editor. 2004. Biodiversity response to climate change in the middle Pleistocene : the Porcupine Cave fauna from Colorado. University of California Press, Berkeley, California, USA. BATES, K., comp. 1993. Fish passage policy and technology, proceedings of a symposium. American Fisheries Society, Bethesda, Maryland, USA. BATESON, P., editor. 1983. Mate choice. Cambridge University Press. New York, New York, USA. CRISP, D. J., editor. 1964. Grazing in terrestrial and marine environments : a Symposium of the British Ecological Society : Bangor 11-14 April 1962. Blackwell Scientific Publications. Oxford, England. DUNNE, T. AND L. B. LEOPOLD. 1978. Water in environmental planning. W. H. Freeman and Company. New York, New York, USA. DUVALL, D., D. MUELLER-SCHWARZE, AND R. M. SILVERSTEIN, editors. 1986. Proceedings of the Fourth International Conference on Chemical Signals in Vertebrates, held July 27-30, 1985 in Laramie, Wyoming. Plenum Press, New York, New York, USA. EMPIRE STATE ELECTRIC ENERGY RESEARCH CORPORATION. 1986. Fish protection : sonic deterrents. Ontario Hydro, Toronto, Ontario, Canada. FEIST, B. E. AND J. J. ANDERSON. 1991. Review of fish behavior relevant to fish guidance systems. FRIUW-9102. University of Washington, Seattle, Washington, USA GRAFFAM, W. S. 1995. Determination of vitamin E status in nyala and Rocky Mountain bighorn sheep. M.S. Thesis, Colorado State University, Fort Collins, Colorado, USA. GREEN, J. C. AND B. S. C. LEADBEATER. 1994. The haptophyte algae. The Systematics Association special volume; no. 51. Oxford University Press, United Kingdom. GREEN, R. H. 1979. Sampling design and statistical methods for environmental biologists. John Wiley & Sons, New York, New York, USA. HAFEN, L. R., editor. 1950. Ruxton of the Rockies. 1st edition. University of Oklahoma Press, Norman, Oklahoma, USA. 128 �INTERNATIONAL GRASSLAND CONGRESS. 1966. Proceedings of the 9th International Grassland Congress : Sao Paul, Brazil : 7/20 of January 1965. Anais do Congresso Internacional de Pastagens (9th : 1965 : Sao Paulo, Brazil). 2 vols. Haries, Sao Paulo, Brazil. JOHNSTON, R. F., editor. 1987. Annual review of ecology and systematics. Vol. 18. Annual Reviews Inc. Palo Alto, California, USA. LEBRETON, J. –D. AND PH. M. NORTH. 1993. Marked individuals in the study of bird population. Advances in life sciences. Birkhauser Verlag, Basel, Switzerland. LEOPOLD, L. B. 1997. Water, rivers and creeks. University Science Books, Sausalito, California, USA. LEWIS, M. E. 1970. Alpine rangelands of the Uinta Mountains : Ashley and Wasatch national Forests : Region 4 : 1970. U.S. Forest Service, Ogden, Utah, USA. LINK, R. 1999. Landscaping for wildlife in the Pacific Northwest. University of Washington Press, Seattle, Washington, USA. MANLY, B. F. J. 2001. Statistics for environmental science and management. Chapman and Hall, Boca Raton, Florida, USA. MASLIN, T. P. 1959. An annotated check list of the amphibians and reptiles of Colorado. University of Colorado studies. Series in biology, no. 6. University of Colorado Press, Boulder, Colorado USA. MATTISE, S. N. 1995. Sage grouse in Idaho : Forum ’94. Boise, ID : U.S. Bureau of Land Management. Technical bulletin; no. 95-15. Bureau of Land Management, Boise District Office, Boise, Idaho, USA. MCCULLOUGH, D. R. 1992. Wildlife 2001 : populations : Proceedings of “Wildlife 2001 : populations,” an International Conference on Population Dynamics and Management of Vertebrates (Exclusive of Primates and Fish) held at Oakland, Calif., U.S.A., July 29-31, 1991. Elsevier Applied Science, New York, New York, USA. MORRISON, M. L., W. M. BLOCK, M. D. STRICKLAND, AND W. L. KENDALL. 2001. Wildlife study design. Springer Verlag, New York, New York, USA. MUELLER, K. W. AND M. R. DOWNEN. 2000. 1997 Black Lake survey : a coastal warmwater fish community before the introduction of grass carp. Report #FPT 00-05. Washington (state) Department of Fish and Wildlife, La Conner, Washington, USA. MUELLER-SCHWARZE, D. AND R. M. SILVERSTEIN, editors. 1983. Proceedings of the Third International Symposium on Chemical Signals in Vertebrates, held April 11-13, 1982 in Sarasota, Florida. Plenum Press, New York, New York, USA. NIELSEN, J. L., editor. 1995. Evolution and the aquatic ecosystem : defining unique units in population conservation. Symposium; 17. American Fisheries Society, Bethesda, Maryland, USA. PACKARD, S. AND C. F. MUTEL, editors. 1997. The tallgrass restoration handbook : for prairies, savannas, and woodlands. Island Press, Washington, D.C., USA. PAMPLIN, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. M.S. Thesis, Oregon State University, Corvallis, Oregon, USA. PUCKETT, K. J. AND J. J. ANDERSON. 1988. Behavioral responses of juvenile salmonids to strobe and mercury lights. University of Washington. FRI-UW-8717. University of Washington Press, Seattle, Washington, USA. RICHARDS, K. 1982. Rivers : form and process in alluvial channels. Methuen, New York, New York, USA. RUBENSTEIN, D. I. AND R. W. WRANGHAM, editors. 1986. Ecological aspects of social evolution : birds and mammals. Princeton University Press, Princeton, New Jersey, USA. SANDERS, K. AND J. DURHAM. 1985. Rangeland fire effects : a symposium : proceedings of a symposium sponsored by Bureau of Land Management and University of Idaho, November 2729, 1984. Bureau of Land Management, Boise District Office, Boise, Idaho, USA. SCHALLER, F. W. AND P. SUTTON, editors. 1978. Reclamation of drastically disturbed lands : proceedings of a symposium held 9-12 August 1976 at the Ohio Agricultural Research and Experiment Station, Wooster, Ohio. American Society of Agronomy, Madison, Wisconsin, USA. 129 �SETON, E. T. 1953. Lives of game animals : an account of those land animals in America, north of the Mexican border, which are considered “game,” either because they have held the attention of sportsmen, or received the protection of law. Volume III – Part II Hoofed animals. Charles T. Branford, Company, Boston, Massachusetts, USA. SMITH, H. M., T. P. MASLIN, AND R. L. BROWN. 1965. Summary of the distribution of the herpetofauna of Colorado : a supplement to an annotated check list of the amphibians and reptiles of Colorado. University of Colorado studies. Series in biology, no. 15. University of Colorado Press, Boulder, Colorado USA. STEFFEY, D. L. AND N. M. BRADBURN, editors. 1994. Counting people in the information age. National Academy Press, Washington, D.C., USA. STONE AND WEBSTER ENGINEERING CORP. 1986. Assessment of downstream migrant fish protection technologies for hydroelectric application. Electric Power Research Institute, Palo Alto, California, USA. STONE AND WEBSTER ENGINEERING CORP. 1990. Fish protection systems for hydro plants : test results. Electric Power Research Institute, Palo Alto, California, USA. THWAITES, R. G., editor. 1966. Early western travels : 1748-1846 : a series of annotated reprints of some of the best and rarest contemporary volumes of travel, descriptive of the aborigines and social and economic conditions in the middle and far west, during the period of early American settlement. Volume XVI. Part III of Jame’s account of S. H. Long’s expedition, 1819-1820. AMS Press, New York, New York, USA. URBANSKA, K. M., N. R. WEBB, AND P. J. EDWARDS. 1997. Restoration ecology and sustainable development. Cambridge University Press, Cambridge, United Kingdom. WALLACE, L. L., editor. 2004. After the fires : the ecology of change in Yellowstone National Park. Yale University Press, Connecticut, USA. WEEDEN, R. B. 1959. The ecology and distribution of ptarmigan in western North America. Ph.D. Dissertation, University of British Columbia, Vancouver, British Columbia, Canada. WINCHELL, F. C., S. V. AMARAL, AND E. P. TAFT. 1994. Research update on fish protection technologies for water intakes : final report, May 1994. TR-104122 Research Project. Electric Power Research Institute, Palo Alto, California, USA. CDOW Manuscripts Published July, 2005 – June, 2006 In addition to CDOW Research Progress Reports for avian, aquatic, and mammal research studies, the following publications were completed. BAETEN, L. 2005. Waste disposal from chronic wasting disease surveillance – a national issue. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.46 (abstract) BAKER, D. L., M. A. WILD, M. D. HUSSAIN, R. L. DUNN, AND T. N. NETT. 2005. Evaluation of remotely delivered leuprolide acetate as a contraceptive agent in female elk. Journal of Wildlife Diseases 41(4):758-767 BERGMAN, E. J., R. A. GARROTT, S. CREEL, J. J. BORKOWSKI, R. JAFFE, AND F. G. R. WATSON. 2006. Assessment of prey vulnerability through analysis of wolf movements and kill sites. Ecological Applications 16(1):273-284 BRINKMAN, S. F. AND J. D. WOODLING. 2005. Zinc toxicity to the mottled sculpin (Cottus bairdi) in high-hardness water. Environmental Toxicology and Chemistry. 24(6):1515-1517 COLORADO DIVISION OF WILDLIFE. [2006]. 2006 fishing guide. Special edition of Colorado Outdoors. Colorado Division of Wildlife, Denver, Colorado. USA. COLORADO DIVISION OF WILDLIFE. [2005]. 2005 hunting guide. Special edition of Colorado Outdoors. Colorado Division of Wildlife, Denver, Colorado. USA. 130 �CONNOR, M. M., C. E. KURMM, AND M. W. MILLER. 2005. Increasing the efficacy of chronic wasting disease detection via selective and targeted sampling. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.51 (abstract) DECKER, D. J., M. A. WILD, S. J. RILEY, W. SIEMER, AND M. W. MILLER. 2005. Describing the wildlife disease management system : a practical perspective on chronic wasting disease management planning. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.64 (abstract) DREITZ, V. J., M. B. WUNDER, AND F. L. KNOPF. 2005. Movements and home ranges of mountain plovers raising broods in three Colorado landscapes. Wilson Bulletin 117:128-132 FARNSWORTH, M. L., J. HOETING, N. T. HOBBS, AND M. W. MILLER. 2005. Linking mule deer movement scales to the spatial distribution of chronic wasting disease. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.35 (abstract) FARNSWORTH, M. L., J. A. HOETING, N. T. HOBBS, AND M. W. MILLER. 2006. Linking chronic wasting disease to mule deer movement scales : a hierarchical Bayesian approach. Ecological Applications 16(3):1026-1036 GREAR, D., M. M. CONNER, M. D. SAMUEL, AND M. W. MILLER. 2005. Epidemiology of chronic wasting disease in free-ranging deer : common factors that drive transmission. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.35 (abstract) HANOPHY, W. 2005. Quick key to amphibians and reptiles of Colorado : Colorado herpetofaunal atlas. Colorado Division of Wildlife, Denver, Colorado. USA JEWELL, J. E., M. M. CONNER, L. L. WOLFE, M. W. MILLER, AND E. S. WILLIAMS. 2005. Low frequency of PrP genotype 225SF among free-ranging mule deer (Odocoileus hemionus) with chronic wasting disease. Journal of General Virology 86:2127-2134 KRUMM, C. E., M. M. CONNER, AND M. W. MILLER. 2005. Relative vulnerability of chronic wasting disease infected mule deer to vehicle collisions. Journal of Wildlife Diseases 41(3):503-511 LUKACS, P. M. AND K. P. BURNHAM. 2005. Estimating population size from DNA-based closed capturerecapture data incorporating genotyping error. Journal of Wildlife Management 69(1):396-403 MILLER, M. W., AND M. M. CONNER. 2005. Epidemiology of chronic wasting disease in free-ranging mule deer : spatial, temporal, and demographic influences on observed prevalence patterns. Journal of Wildlife Diseases 41(2):275-290 MILLER, M. W. AND K. GREEN. 2005. Chronic wasting disease policy and management in Colorado, 2001-2004. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. pp.1-4 (panel presentation) NEEDHAM, M. D., J. J. VASKE, K. GREEN, J. PETCHENIK, AND N. R. TIMMONS. 2005. Hunter’s knowledge, information sources, and beliefs about chronic wasting disease. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.61 (abstract) RAYMOND, G. J., E. A. OLSEN, K. S. LEE, L. D. RAYMOND, P. K. BRYANT III, G. S. BARON, W. S. CAUGHEY, D. A. KOCISKO, L. E. MCHOLLAND, C. FAVARA, J. P. M. LANGEVELD, F. G. VAN ZIJDERVELD, R. T. MAYER, M. W. MILLER, E. S. WILLIAMS, AND B. CAUGHEY. 2006. Inhibition of protease-resistant prion protein formation in a transformed deer cell line infected with chronic wasting disease. Journal of Virology 80(2):596-604 OYLER-MCCANCE, S. J., J. ST. JOHN, S. E. TAYLOR, A. D. APA. 2005. Population genetics of Gunnison sage-grouse : implications for management. Journal of Wildlife Management 69(2):630-637 RODGERS, R. D. AND R. W. HOFFMAN. 2005. Prairie grouse population response to Conservation Reserve Program grasslands : an overview. Pgs. 120-128 in A. W. Allen and M. W. Vandever, 131 �editors. The Conservation Reserve Program – planting for the future : Proceedings of a National Conference, Fort Collins, Colorado, June 6 - 9 , 2004. U.S. Geological Survey, Biological Resources Division, Scientific Investigation Report 2005-5145. 248pp. SCHISLER, G. J., K. A. MYKLEBUST, AND R. P. HEDRICK. 2006. Inheritance of Myxobolus cerebralis resistance among F1-generation crosses of whirling disease resistant and susceptible rainbow trout strains. Journal of Aquatic Animal Health 18(2):109-115 SIGURDSON, C., A. AGUZZI, E. HOOVER, C. MATHIASON, M. PERROTT, M. GLATZEL, J. C. BARTZ, G. MANCO, T. SPRAKER, AND M. W. MILLER. 2005. Chronic wasting disease : across the species barrier. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.39 (abstract) TAMGUNEY, G., P. NELKEN, J. YANG, K. GILES, P. J. BOSQUE, M. W. MILLER, J. SAFAR, S. J. DEARMOND, AND S. B. PRUSINER. 2005. Interspecies transmission of prions causing chronic wasting disease. In: The Second International Chronic Wasting Disease Symposium : July 12 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.76 (abstract) WATRY, M. K., L. L. WOLFE, J. G. POWERS, AND M. A. WILD. 2005. Implementation of a test and cull program for managing chronic wasting disease in wildland and urban settings. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.52 (abstract) WHITE, G. C., J. R. DENNIS, AND F. M. PUSATERI. 2005. Area of black-tailed prairie dog colonies in eastern Colorado. Wildlife Society Bulletin 33(1):265-272 WILD, M. A., M. W. MILLER, AND N. T. HOBBS. 2005. Could wolves control chronic wasting disease? In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. p.67 (abstract) WOLFE, L. L., M. K. WATRY, M. A. SIROCHMAN, J. G. POWERS, M. A. WILD, AND M. W. MILLER. 2005. Preliminary assessment of “test & cull” as a chronic wasting disease management strategy. In: The Second International Chronic Wasting Disease Symposium : July 12 - 14, 2005 : Monona Terrace Convention Center : Madison, Wisconsin, USA. CDW Alliance. pp.66-67 (abstract) WOLFE, L. L., AND M. W. MILLER. 2005. Suspected secondary thiafentanil intoxication in a captive mountain lion (Puma concolor). Journal of Wildlife Diseases 41(4):829-833 Prepared by ___________________________ Jacqueline A. Boss, Librarian 132 � https://cpw.cvlcollections.org/files/original/95a63bc9e621a95f4fc120e37073aaf3.pdf 5835322bf651d38f0cef6763a8ed04f9 PDF Text Text MAMMALS - JULY 2007 �WILDLIFE RESEARCH REPORTS JULY 2006 – JUNE 2007 MAMMALS PROGRAM COLORADO DIVISION OF WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). i �STATE OF COLORADO Bill Ritter, Governor DEPARTMENT OF NATURAL RESOURCES Harris Sherman, Executive Director WILDLIFE COMMISSION Jeffrey Crawford, Chair …………………………………………………………………….…..… Denver Tom Burke, Vice Chair ………………………………….…………...………….…........…Grand Junction Claire M. O’Neal, Secretary ……………………………………...…………….…………………Holyoke Robert Bray………………………………………………….......................................................…Redvale Brad Coors…………………………………………………………………………………………..Denver Rick Enstrom………………………………………………………………….………….……...Lakewood Roy McAnally………………………………………………..…………….………..………………...Craig Richard Ray ………………………………………………………………………………...Pagosa Springs Ken Torres…………………………………………………………….………..…………………....Weston Harris Sherman, Executive Director, Ex-officio………….…………………...…………….…….....Denver John Stulp, Dept. of Agriculture, Ex-officio….………………………………..……………………Denver DIRECTOR’S STAFF Bruce McCloskey, Director Mark Konishi, Deputy Director John Bredehoft, Assistant Director-Field Operations Marilyn Salazar, Assistant Director-Support Services Jeff Ver Steeg, Assistant Director-Wildlife Programs Steve Cassin, Chief Financial Officer MAMMALS RESEARCH STAFF Dave Freddy, Mammals Research Leader Mat Alldredge, Wildlife Researcher Chuck Anderson, Wildlife Researcher Eric Bergman, Wildlife Researcher Chad Bishop, Wildlife Researcher Ken Logan, Wildlife Researcher Tanya Shenk, Wildlife Researcher Jackie Boss, Librarian Margie Michaels, Program Assistant ii �Colorado Division of Wildlife July 2006 – June 2007 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS LYNX CONSERVATION WP 0670 POST-RELEASE MONITORING OF LYNX REINTRODUCED TO COLORADO by T. Shenk………………………………………………………………………….…….1 DEER CONSERVATION WP 3001 EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES by C. Bishop………..…………...59 WP 3001 EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER by E. Bergman…………………………………………………………………………...73 WP 3001 MULTISPECIES INVESTIGATIONS CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSIS by G. White………………………………….……97 WP 3001 POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson..……………………………………………………………………......103 PREDATORY MAMMALS CONSERVATION WP 3003 PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU by K. Logan………………….………………………111 WP 3003 COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBAN-EXURBAN FRONT RANGE OF COLORADO by M. Alldredge…………153 SUPPORT SERVICES WP 7210 LIBRARY SERVICES by D. Freddy..……………..…………………………………203 iii �iv �Colorado Division of Wildlife July 2006 - June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 0670 1 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Lynx Conservation : Post-Release Monitoring of Lynx : Reintroduced to Colorado : Period Covered: July 1, 2006 - June 30, 2007 Author: T. M. Shenk Personnel: L. Baeten, B. Diamond, R. Dickman, D. Freddy, L. Gepfert, J. Ivan, R. Kahn, A. Keith, G. Merrill, M. Schuette, B. Smith, T. Spraker, S. Wait, S. Waters, L. Wolfe, D. Younkin All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to establish a viable population of lynx (Lynx canadensis) in Colorado, the Colorado Division of Wildlife (CDOW) initiated a reintroduction effort in 1997 with the first lynx released in February 1999. From 1999-2007, 218 lynx were released in Colorado. We documented survival, movement patterns, reproduction, and landscape habitat-use through aerial (n = 9496) and satellite (n = 23,791) tracking. Most lynx remained near the core release area in southwestern Colorado. From 1999June 2007, there were 98 mortalities of released adult lynx. Approximately 30.6% were human-induced which were attributed to collisions with vehicles or gunshot. Starvation and disease/illness accounted for 19.4% of the deaths while 35.7% of the deaths were from unknown causes. Reproductive females had the smallest 90% utilization distribution home ranges ( x = 75.2 km2, SE = 15.9 km2 ), followed by attending males ( x = 102.5 km2, SE = 39.7 km2) and non-reproductive animals ( x = 653.8 km2, SE = 145.4 km2). Reproduction was first documented in 2003 with subsequent successful reproduction in 2004, 2005 and 2006. No dens were documented in 2007. From snow-tracking, the primary winter prey species (n = 506 kills) were snowshoe hare (Lepus americanus, annual x = 74.9%, SE = 4.6, n = 9) and red squirrel (Tamiasciurus hudsonicus, annual x = 16.5%, SE = 4.1, n = 9); other mammals and birds formed a minor part of the winter diet. Lynx use-density surfaces were generated to illustrate relative use of areas throughout Colorado and areas of use in New Mexico, Utah and Wyoming. Within the areas of high use in southwestern Colorado, site-scale habitat use, documented through snow-tracking, supports mature Engelmann spruce (Picea engelmannii)-subalpine fir (Abies lasiocarpa) forest stands with 42-65% canopy cover and 15-20% conifer understory cover as the most commonly used areas in southwestern Colorado. Little difference in aspect (slight preference for north-facing slopes), slope ( x = 15.7°) or elevation ( x = 3173 m) were detected for long beds, travel and kill sites (n = 1841). Den sites (n = 37) 1 �however, were located at higher elevations ( x = 3354 m, SE = 31 m) on steeper ( x = 30°, SE = 2°) and more commonly north-facing slopes with a dense understory of coarse woody debris. The first year of a study to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands was completed in 2006-2007 and will continue through 2009 (see Appendix I of this report). Results to date have demonstrated that CDOW has developed lynx release protocols that ensure high initial post-release survival followed by high long-term survival, site fidelity, reproduction and recruitment of Colorado-born lynx into the Colorado breeding population. What is yet to be demonstrated is whether Colorado can support sufficient recruitment to offset annual mortality for a viable lynx population over time. Monitoring continues in an effort to document such viability. 2 �WILDLIFE RESEARCH REPORT POST RELEASE MONITORING OF LYNX (LYNX CANADENSIS) REINTRODUCED TO COLORADO TANYA M. SHENK P. N. OBJECTIVE The initial post-release monitoring of Canada lynx (Lynx canadensis) reintroduced into Colorado will emphasize 5 primary objectives: 1. Assess and modify release protocols to ensure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival of lynx reintroduced to Colorado. 5. Estimate reproduction of lynx reintroduced to Colorado. Three additional objectives will be emphasized after lynx display site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of lynx conservation strategies in the southern Rocky Mountains. SEGMENT OBJECTIVES 1. Complete winter 2006-07 field data collection on lynx habitat use at the landscape scale, hunting behavior, diet, mortalities, and movement patterns. 2. Complete winter 2006-07 lynx trapping field season to collar Colorado born lynx and re-collar adult lynx. 3. Complete spring 2007 field data on lynx reproduction. 4. Summarize and analyze data and publish information as Progress Reports, peer-reviewed manuscripts for appropriate scientific journals, or CDOW technical publications. 5. Complete the first year of field work to evaluate snowshoe hare (Lepus americanus) densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands (see Appendix I). INTRODUCTION The Canada lynx occurs throughout the boreal forests of northern North America. Colorado represents the southern-most historical distribution of lynx, where the species occupied the higher elevation, montane forests in the state. Little was known about the population dynamics or habitat use of this species in their southern distribution. Lynx were extirpated or reduced to a few animals in the state by the late 1970’s due, most likely, to predator control efforts such as poisoning and trapping. Given the isolation of Colorado to the nearest northern populations, the CDOW considered reintroduction as the only option to attempt to reestablish the species in the state. 3 �A reintroduction effort was begun in 1997, with the first lynx released in Colorado in 1999. To date, 218 wild-caught lynx from Alaska and Canada have been released in southwestern Colorado. The goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of lynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing if the reintroduction effort is progressing towards success. There are 7 critical criteria for achieving a viable population: 1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, 2) long-term survival of lynx in Colorado, 3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, 4) reintroduced lynx must breed, 5) breeding must lead to reproduction of surviving kittens 6) lynx born in Colorado must reach breeding age and reproduce successfully, and 7) recruitment must equal or be greater than mortality over an extended period of time. The post-release monitoring program for the reintroduced lynx has 2 primary goals. The first goal is to determine how many lynx remain in Colorado and their locations relative to each other. Given this information and knowing the sex of each individual, we can assess whether these lynx can form a breeding core from which a viable population might be established. From these data we can also describe general movement patterns and habitat use. The second primary goal of the monitoring program is to estimate survival of the reintroduced lynx and, where possible, determine causes of mortality for reintroduced lynx. Such information will help in assessing and modifying release protocols and management of lynx once they have been released to ensure their highest probability of survival. Additional goals of the post-release monitoring program for lynx reintroduced to the southern Rocky Mountains included refining descriptions of habitat use and movement patterns and describing successful hunting habitat once lynx established home ranges that encompassed their preferred habitat. Specific objectives for the site-scale habitat data collection include: 1) describe and quantify site-scale habitat use by lynx reintroduced to Colorado, 2) compare site-scale habitat use among types of sites (e.g., kills vs. long-duration beds), and 3) compare habitat features at successful and unsuccessful snowshoe hare chases. Documenting reproduction is critical to the success of the program and lynx are monitored intensively to document breeding, births, survival and recruitment of lynx born in Colorado. Site-scale habitat descriptions of den sites are also collected and compared to other sites used by lynx. The program will also investigate the ecology of snowshoe hare in Colorado. A study comparing snowshoe hare densities among mature stands of Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), lodgepole pine (Pinus contorta) and Ponderosa pine (Pinus ponderosa) was completed in 2004 with highest hare densities found in Engelmann spruce/subalpine fir stands and no hares found in Ponderosa pine stands. A study to evaluate the importance of young, regenerating lodgepole pine and mature Engelmann spruce/subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each was initiated in 2005 and will continue through 2009 (see Appendix I). Lynx is listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.)(U. S. Fish and Wildlife Service 2000). Colorado is included in the federal listing as lynx habitat. Thus, an additional objective of the post-release monitoring program is to develop conservation strategies relevant to lynx in Colorado. To develop these conservation strategies, information specific to the ecology of the lynx in its southern Rocky Mountain range, such as habitat use, movement patterns, mortality factors, survival, and reproduction in Colorado is needed. 4 �STUDY AREA Southwestern Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce-subalpine fir is the most widely distributed coniferous forest type at elevations most typically used by lynx. The Core Release Area is defined as areas bounded by the New Mexico state line to the south, Taylor Mesa to the west and Monarch Pass on the north and east and > 2900 m in elevation (Figure 1). The lynx-established core area is roughly bounded by areas used by lynx in the Taylor Park/Collegiate Peak areas in central Colorado and includes areas of continuous use by lynx, including areas used during breeding and denning (Figure 1). METHODS REINTRODUCTION Effort All lynx releases were conducted under the protocols found to maximize survival (see Shenk 2001). Estimated age, sex and body condition were ascertained and recorded for each lynx prior to release (see Wild 1999). Specific release sites were those used in earlier years of the project and were selected based on land ownership and accessibility during times of release (Byrne 1998). Lynx were transported from the Frisco Creek Wildlife Rehabilitation Center, where they were held from their time of arrival in Colorado, to their release site in individual cages. Release site location was recorded in Universal Transverse Mercator (UTM) coordinates and identification of all lynx released at the same location, on the same day, was recorded. Behavior of the lynx on release and movement away from the release site were documented. Movement, Distribution and Relative Use of Areas by Lynx To monitor lynx movements and thus determine distribution and relative use of areas all released lynx were fitted with radio collars. All lynx released in 1999 were fitted with TelonicsTM radio-collars. All lynx released since 1999, with the exception of 5 males released in spring 2000, were fitted with SirtrackTM dual satellite/VHF radio-collars. These collars have a mortality indicator switch that operated on both the satellite and VHF mode. The satellite component of each collar was programmed to be active for 12 hours per week. The 12-hour active periods for individual collars were staggered throughout the week. Signals from the collars allowed for locations of the animals to be made via Argos, NASA, and NOAA satellites. The location information was processed by ServiceArgos and distributed to the CDOW through e-mail messages. Datasets.-- To determine recent (post-reintroduction) movement and distribution of lynx reintroduced, born or initially trapped in Colorado and relative use of areas by these lynx, regular locations of lynx were collected through a combination of aerial and satellite tracking. Locations were recorded and general habitat descriptions for each aerial location was recorded. The first dataset of lynx locations included all locations obtained from daytime flights conducted with a Cessna 185 or similar aircraft to locate lynx by their VHF collar transmitters (hereafter aerial locations). VHF transmitters have been used on lynx since the first lynx were released in February 1999. The second type of lynx location data was collected via satellite from the satellite collar transmitters placed on the lynx (hereafter satellite locations). Satellite transmitter collars were first used for lynx in April 2000. These satellite collars also contained a VHF transmitter which also allowed locating lynx from the air or ground. All locations were recorded in Universal Transverse Mercator (UTM) coordinates using the CONUS NAD27 datum. Flights to obtain lynx aerial locations were typically conducted on a weekly basis throughout most summer and winter months and twice a week during the den search field season (May 15 – June 30), depending on weather and availability of planes and pilots. Flights were typically concentrated in the high elevation (> 2700 m) southwest quadrant of Colorado which encompasses the core lynx release and 5 �research area (Figure 1). Flights during the den seasons were conducted to obtain locations on all female lynx within the state wearing an active VHF transmitter. VHF transmitters were outfitted with sufficient batteries to last 60 months. The satellite transmitters were designed to provide locations on a weekly basis with sufficient batteries to last for 18 months. Lynx may not be exhibiting typical behavior or habitat use within the first few months after their release in Colorado. Therefore, a subset of each of the aerial and satellite datasets was created that eliminated the first 180 days (approximately 6 months) of locations obtained for each lynx immediately after their initial release. As a result, the truncated aerial location dataset contained lynx locations from September 1999 through March 2007 while the truncated satellite location dataset began October 2000 and extended through March 2007. Accuracy of both aerial and satellite locations varied with the environmental conditions at the time the location was obtained. Accuracy of aerial locations was influenced by weather with accuracy ranging from 50 - 500 meters. Satellite location accuracy was also influenced by atmospheric conditions and position of the satellites. Satellite location accuracy ranged from 150 meters -10 km. Movement and Distribution.-- To document all known lynx locations maps were generated with all aerial and satellite locations displayed. Due to lynx movements outside of Colorado, particularly into the states of New Mexico, Utah and Wyoming we further evaluated lynx use throughout those three states, as well as the data would allow. All individual lynx located at least once in these 3 states (nontruncated datasets) were identified and tallied for each year. To document consistency and known use of these states after the initial effect of being reintroduced was minimized (i.e., 180 days post-release), each individual lynx located at least once in these states from the truncated datasets were identified and tallied. Relative Use.-- To document relative use of areas by lynx, 90% kernel use-density surfaces were calculated for truncated satellite and aerial lynx locations using the ArcGIS Spatial Analyst Kernel Density Tool. Due to differences in data collection frequency and accuracy between datasets, the truncated satellite and truncated aerial data were analyzed separately for generating the lynx use-density surfaces. These use-density surfaces fit a smoothly curved surface over each lynx location. The surface value was highest at the location of the point and diminished with increasing distance from the point. A fixed kernel was used with a smoothing parameter of 5 km, reaching 0 at the search radius distance from the point. Only a circular neighborhood was possible. The volume under the surface equaled the total value for the point. The use-density at each output GIS raster cell was calculated by adding the values of all the kernel surfaces from all the lynx point locations that overlaid each raster cell center. The kernel function was based on the quadratic kernel function described in Silverman (1986, p. 76, equation 4.5). The use-density surfaces were calculated at 100 m resolution. To enhance graphic displays of higher usedensity areas, density values representing single locations were not displayed. Home Range Annual home ranges were calculated as a 95% utilization distribution using a kernel home-range estimator for each lynx we had at least 30 locations for within a year. A year was defined as March 15 – March 14 of the following year. Locations used in the analyses were collected from September 1999 – January 2006 and all locations obtained for an individual during the first six months after its release were eliminated from any home range analyses as it was assumed movements of lynx initially post-release may not be representative of normal habitat use. Locations were obtained either through aerial VHF surveys or locations or the midpoint (ArcView Movement Extension) of all high quality (accuracy rating of 01km) satellite locations obtained within a single 24-hour period. All locations used within a single home range analysis were taken a minimum of 24 hours apart. 6 �Home range estimates were classified as being for a reproductive or non-reproductive animal. A reproductive female was defined as one that had kittens with her; a reproductive male was defined as a male whose movement patterns overlapped that of a reproductive female. If a litter was lost within the defined year a home range described for a reproductive animal were estimated using only locations obtained while the kittens were still with the female. Survival Survival was estimated as ragged telemetry data using the nest survival models in Program MARK (White and Burnham 1999). Mortality Factors When a mortality signal (75 beats per minute [bpm] vs. 50 bpm for the Telonics™ VHF transmitters, 20 bpm vs. 40 bpm for the Sirtrack™ VHF transmitters, 0 activity for Sirtrack™ PTT) was heard during either satellite, aerial or ground surveys, the location (UTM coordinates) was recorded. Ground crews then located and retrieved the carcass as soon as possible. The immediate area was searched for evidence of other predators and the carcass photographed in place before removal. Additionally, the mortality site was described and habitat associations and exact location were recorded. Any scat found near the dead lynx that appeared to be from the lynx was collected. All carcasses were transported to the Colorado State University Veterinary Teaching Hospital (CSUVTH) for a post mortem exam to 1) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, and 3) archive samples for future reference (research or forensic). The gross necropsy and histology were performed by, or under the lead and direct supervision of a board certified veterinary pathologist. At least one research personnel from the CDOW involved with the lynx program was also present. The protocol followed standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing (see Shenk 1999 for details). Some additional data/samples were routinely collected for research, forensics, and archiving. Other data/samples were collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). From 1999–2004 the CDOW retained all samples and carcass remains with the exception of tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, and other diagnostic samples. Since 2005 carcasses are disposed of at the CSUVTH with the exception of the lower canine, fecal samples, stomach content samples and tissue or bone marrow samples to be delivered by CDOW to the Center for Disease control for plague testing. The lower canine, from all carcasses, is sent to Matson Labs (Missoula, Montana) for aging and the fecal and stomach content samples are evaluated for diet. Reproduction Females were monitored for proximity to males during each breeding season. We defined a possible mating pair as any male and female documented within at least 1 km of each other in breeding season through either flight data or snow-tracking data. Females were then monitored for site fidelity to a given area during each denning period of May and June. Each female that exhibited stationary movement patterns in May or June were closely monitored to locate possible dens. Dens were found when field crews walked in on females that exhibited virtually no movement for at least 10 days from both aerial and ground telemetry. Kittens found at den sites were weighed, sexed and photographed. Each kitten was uniquely marked by inserting a sterile passive integrated transponder (PIT, Biomark, Inc., Boise, Idaho, USA) tag subcutaneously between the shoulder blades. Time spent at the den was minimized to ensure the least 7 �amount of disturbance to the female and the kittens. Weight, PIT-tag number, sex and any distinguishing characteristics of each kitten was also recorded. Beginning in 2005, blood and saliva samples were collected and archived for genetic identification. During the den site visits, den site location was recorded as UTM coordinates. General vegetation characteristics, elevation, weather, field personnel, time at the den, and behavioral responses of the kittens and female were also recorded. Once the females moved the kittens from the natal den area, den sites were visited again and site-specific habitat data were collected (see Habitat Use section below). Captures Captures were attempted for either lynx that were in poor body condition or lynx that needed to have their radio-collars replaced due to failed or failing batteries or to radio-collar kittens born in Colorado once they reached at least 10-months of age when they were nearly adult size. Methods of recapture included 1) trapping using a Tomahawk™ live trap baited with a rabbit and visual and scent lures, 2) calling in and darting lynx using a Dan-Inject CO2 rifle, 3) custom box-traps modified from those designed by other lynx researchers (Kolbe et al. 2003) and 4) hounds trained to pursue felids were also used to tree lynx and then the lynx was darted while treed. Lynx were immobilized either with Telazol (3 mg/kg; modified from Poole et al. 1993 as recommended by M. Wild, DVM) or medetomidine (0.09mg/kg) and ketamine (3 mg/kg; as recommended by L. Wolfe, DVM)) administered intramuscularly (IM) with either an extendible pole-syringe or a pressurized syringe-dart fired from a Dan-Inject air rifle. Immobilized lynx were monitored continuously for decreased respiration or hypothermia. If a lynx exhibited decreased respiration 2mg/kg of Dopram was administered under the tongue; if respiration was severely decreased, the animal was ventilated with a resuscitation bag. If medetomidine/ketamine were the immobilization drugs, the antagonist Atipamezole hydrochloride (Antisedan) was administered. Hypothermic (body temperature < 95o F) animals were warmed with hand warmers and blankets. While immobilized, lynx were fitted with replacement SirtrackTM VHF/satellite collar and blood and hair samples were collected. Once an animal was processed, recovery was expedited by injecting the equivalent amount of the antagonist Antisedan IM as the amount of medetomidine given, if medetomodine/ketemine was used for immobilization. Lynx were then monitored while confined in the box-trap until they were sufficiently recovered to move safely on their own. No antagonist is available for Telezol so lynx anesthetized with this drug were monitored until the animal recovered on its own in the box-trap and then released. If captured and in poor body condition, lynx were anesthetized with either Telezol (2 mg/kg) or medetomodine/ketemine and returned to the Frisco Creek Wildlife Rehabilitation Center for treatment. HABITAT USE Gross habitat use was documented by recording canopy vegetation at aerial locations. More refined descriptions of habitat use by reintroduced lynx were obtained through following lynx tracks in the snow (i.e., snow-tracking) and site-scale habitat data collection conducted at sites found through this method to be used by lynx. See Shenk (2006) for detailed methodologies. DIET AND HUNTING BEHAVIOR Winter diet of reintroduced lynx was estimated by documenting successful kills through snowtracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. Scat samples were collected wherever found and labeled with location and individual lynx identification. Only part of the scat was collected (approximately 75%); the remainder was left in place in the event that the scat was being used by the animal as a territory mark. Site-scale habitat data collected for successful and unsuccessful snowshoe hare kills were compared. 8 �SNOWSHOE HARE ECOLOGY A study designed to evaluate the importance of young, regenerating lodgepole pine and mature Engelmann spruce / subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each was initiated in 2005. Specifically, the study was designed to evaluate small and medium lodgepole pine stands and large spruce/fir stands where the classes “small”, “medium”, and “large” refer to the diameter at breast height (dbh) of overstory trees as defined in the United States Forest Service R2VEG Database (small = 2.54−12.69 cm dbh, medium = 12.70−22.85 cm, and large = 22.86−40.64 cm dbh; J. Varner, United States Forest Service, personal communication). The study design was also developed to identify which of the numerous density-estimation procedures available perform accurately and consistently using an innovative, telemetry augmentation approach as a baseline. Movement patterns and seasonal use of deciduous cover types such as riparian willow were assessed. Finally, the study was designed to further expound on the relationship between density, demography, and stand-type by examining how snowshoe hare density and demographic rates vary with specific vegetation, physical, and landscape characteristics of a stand. RESULTS REINTRODUCTION Effort From 1999 through 2006, 218 lynx were reintroduced into southwestern Colorado (Table 1). No lynx were released in 2007. All lynx were released with either VHF or dual VHF/satellite radio collars so they could be monitored for movement, reproduction and survival. The CDOW does not plan to release any additional lynx in 2008. Movement Patterns and Distribution Numerous travel corridors were used repeatedly by more than one lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-SilvertonLizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast through the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. A total of 9496 aerial and 23791 satellite locations were obtained from the 218 reintroduced lynx, radio-collared Colorado kittens (n = 14) and unmarked lynx captured in Colorado (n = 2) as of June 30, 2007. The majority of these locations were in Colorado (Figure 2). Some reintroduced lynx dispersed outside of Colorado into Arizona, Idaho, Iowa, Kansas, Montana, Nebraska, Nevada, New Mexico, South Dakota, Utah and Wyoming (Figure 2). The majority of surviving lynx from the reintroduction effort currently continue to use high elevation (> 2900 m), forested terrain in an area bounded on the south by New Mexico north to Independence Pass, west as far as Taylor Mesa and east to Monarch Pass. Most movements away from the Core Release Area were to the north. Relative Use The lynx use-density surfaces resulting from the fixed kernel analyses provided relative probabilities of finding lynx in areas throughout their distribution. A single use-density surface was calculated separately for both the aerial (n = 8058) and satellite truncated datasets (n = 16240). Relative Use in Colorado.-- All 218 lynx released in Colorado, all radio-collared kittens and 2 captured unmarked adults were located at least once in Colorado. The majority of these lynx remained in Colorado. The use-density surfaces within Colorado were displayed separately for both the aerial (Figure 3) and satellite truncated datasets (Figure 4). Of the total locations available in the 9 �truncated datasets used to generate the use-density surfaces, 7953 of the aerial locations and 13,241 of the satellite locations were in Colorado. Aerial and satellite use-density surfaces indicated similar high usedensity areas. Satellite locations indicated broader spatial use by lynx because satellite collars provided more locations than flights. The use-density surface for lynx use in Colorado indicates two primary areas of use. The first is the Core Research Area (see Figure 1) and a secondary core centered in the Collegiate Peaks Wilderness (Figures 3 and 4). High use is also documented for 1) the area east of Dillon, on both the north and south sides of I70 and 2) the area north of Hwy 50 centered around Gunnison and then north to Crested Butte. These last 2 high use areas are smaller in extent than the 2 core areas. Relative Use in New Mexico.-- Combining the non-truncated aerial (n = 81) and satellite lynx location (n = 928) datasets, lynx used New Mexico consistently and with an increasing number of individuals from 1999 through 2006 (Table 2). Data for 2007 represents only a partial year and thus trend in numbers of individuals using New Mexico for 2007 cannot be made, however continued use of New Mexico into 2007 was documented Sixty lynx (37 females: 23 males) were found within New Mexico from February 1999 through March 2007 (Table 2). Excluding all aerial and satellite lynx locations collected in the first 180 days after release (truncated datasets; n = 61 aerial locations, n = 569 satellite locations), a total of 35 individual lynx (22 females: 13 males) were found within New Mexico from September 1999 through March 2007 (Table 3). The decrease in number of lynx frequenting New Mexico in 2001 through 2003 (Tables 2 and 3) was more likely due to fewer satellite collars functioning in those years rather than indicating less use of the area by lynx. The satellite transmitters placed on lynx in 2000 were failing and no new lynx were released or re-collared in 2001 and 2002. This decrease in satellite locations is present throughout the lynx distribution and is also reflected in the numbers presented below for Utah and Wyoming The use-density surface for lynx use in New Mexico indicates the primary area of use being located either immediately south of the Colorado border and south of the Conejos River Valley (an area of high use in Colorado) or east of Taos (Figure 5). The use-density surfaces throughout both Colorado and New Mexico are displayed so that lynx use within New Mexico can be directly compared to lynx use throughout Colorado (Figure 6). Relative Use in Utah.-- Combining the non-truncated aerial (n = 10) and satellite lynx location (n = 574) datasets, lynx used the analysis area consistently and with an increasing number of individuals from 1999 through 2006 (Table 4). Data for 2007 represents only a partial year and thus trend in numbers of individuals using the state for 2007 cannot be made, however continued use of Utah into 2007 was documented. Twenty-two lynx (7 females: 15 males) were found within Utah from February 1999 through March 2007 (Table 4). Excluding all aerial and satellite lynx locations collected in the first 180 days after release (truncated datasets; n = 7 aerial locations, n = 399 satellite locations), 17 individual lynx (6 females: 11 males) were found within Utah from September 1999 through March 2007 (Table 5). The use-density surface for lynx use in Utah indicates the primary area of use being located in the Uinta Mountains (Figure 7). The use-density surfaces throughout both Colorado and Utah are displayed so that lynx use within Utah can be directly compared to lynx use throughout Colorado (Figure 8). Relative Use in Wyoming.-- Combining the non-truncated aerial (n = 34) and satellite lynx location (n = 1780) datasets, lynx used the analysis area consistently and with an increasing number of individuals from 1999 through 2006 (Table 6). Data for 2007 represents only a partial year and thus trend in numbers of individuals using the state for 2007 cannot be made, however continued use of the Wyoming into 2007 was documented. Thirty-three lynx (14 females: 19 males) were found within 10 �Wyoming from February 1999 through March 2007 (Table 6). Excluding all aerial and satellite lynx locations collected in the first 180 days after release (truncated datasets; n = 28 aerial locations, n = 1533 satellite locations), 27 individual lynx (13 females: 14 males) were found within Wyoming from September 1999 through March 2007 (Table 7). The use-density surface for lynx use in Wyoming indicates the primary area of use being located either immediately north of the Colorado border in the Medicine Bow National Forest or in the northwest quadrant of the state including areas in Yellowstone and Teton National Parks and the Laramie Range (Figure 9). The use-density surfaces throughout both Colorado and Wyoming are displayed so that lynx use within Wyoming can be directly compared to lynx use throughout Colorado (Figure 10). Home Range Reproductive females had the smallest 90% utilization distribution annual home ranges ( x = 75.2 km2, SE = 15.9 km2, n = 19), followed by attending males ( x = 102.5 km2, SE = 39.7 km2, n = 4). Nonreproductive females had the largest annual home ranges ( x = 703.9 km2, SE = 29.8 km2, n = 32) followed by non-reproductive males ( x = 387.0 km2, SE = 73.5 km2, n = 6). Combining all nonreproductive animals yielded a mean annual home range of 653.8 km2 (SE = 145.4 km2, n = 38). Survival Initial survival rate estimates for reintroduced lynx were completed, however, further analyses need to be conducted before estimates will be presented. As of June 30, 2007, CDOW was actively monitoring/tracking 71 of the 120 lynx still possibly alive (Table 8). There are 50 lynx that we have not heard signals on since at least June 30, 2006 and these animals are classified as ‘missing’ (Table 8). One of these missing lynx is a mortality of unknown identity, thus only 49 are truly missing. Possible reasons for not locating these missing lynx include 1) long distance dispersal, beyond the areas currently being searched, 2) radio failure, or 3) destruction of the radio (e.g., run over by car). CDOW continues to search for all missing lynx during both aerial and ground searches. Two of the missing lynx released in 2000 are thought to have slipped their collars. Mortality Factors Of the total 218 adult lynx released, we have 98 known mortalities as of June 30, 2007 (Table 9). The primary known causes of death included 30.6% human-induced deaths which were confirmed or probably caused by collisions with vehicles or gunshot. Starvation and disease/illness accounted for 19.4% of the deaths; starvation was a significant cause of mortality in the first year of releases only. An additional 35.7% of known mortalities were from unknown causes. Mortalities occurred throughout the areas where lynx moved, including 13 in New Mexico, 4 in Wyoming and Nebraska, 3 in Utah and 1 each in Arizona, Kansas and Montana (Figure 2, Table 10). Reproduction Field crews weighed, photographed, PIT-tagged the kittens and took hair, blood and saliva samples from the kittens for genetic work in an attempt to confirm paternity. Lynx kittens weigh approximately 200 grams at birth and do not open their eyes until they are 10-17 days old. Kittens were processed as quickly as possible (11-32 minutes) to minimize the time the kittens were without their mother. While working with the kittens the females remained nearby, often making themselves visible to the field crews. The females generally continued a low growling vocalization the entire time personnel were at the den. In all cases, the female returned to the den site once field crews left the area. At all dens the females appeared in excellent condition, as did the kittens. 11 �2003.-- Nine pairs of lynx were documented during the 2003 breeding season (March and April) from the 17 females we were monitoring. In May and June, 6 dens and a total of 16 kittens were found in the lynx Core Release Area in southwestern Colorado (Table 11, Figure 1). The kittens weighed from 270-500 grams. The dens were scattered throughout the Core Release Area, with no dens found outside the core area. All the dens were in Engelmann spruce/subalpine fir forests in areas of extensive downfall. Elevations ranged from 3240-3557 m. Four of the 6 females that we know had kittens in summer 2003 were still with kittens at the end of April 2004. Two of those females still had 2 kittens with them at that time. Visual observations in February 2004 of one female with 2 kittens indicated all 3 were in good body condition. The mortality of female YK00F16 and her 1 kitten in October 2003 from plague was not due to poor habitat or prey conditions, and thus we might assume she would have raised the 1 kitten to this stage as well. Three probable kitten deaths from female YK00F19 were from 1 litter that most likely failed very early. Through snow-tracking in winter 2003-04 an unknown female (no radio frequency heard in the area of the tracks) we also documented 1-2 additional kittens born spring 2003 and still alive in winter 2004. Of the 16 kittens we found in summer 2003, we documented the following by April 2004: 6 confirmed alive, 7 confirmed dead, and 3 some evidence dead. Although we tried, we were not able to capture any of the 6 surviving kittens to fit them with radio-collars for subsequent monitoring. 2004.-- In Spring 2004, 26 females from the releases in 1999, 2000 and 2003 had active radiocollars. Of these, we documented 18 possible mating pairs of lynx during breeding season. All 4 of the females that had kittens with them through winter 2003-04 bred again spring 2004; 2 with the same male they successfully bred with spring 2003. During May-June 2004 we found 11 dens and a total of 30 kittens (Table 11). The kittens weighed from 250-770 grams. Three of the 11 females with kittens were from the 2003 releases. Three additional litters were documented after denning season through either observation of a female lynx with kittens or snow-tracking females with kittens that were not one of the 11 females found on dens. From the size of the kittens they would have been born during the normal denning season in May or June. Nine additional kittens were observed from these litters for a total of 39 known kittens born in 2004. Two of these additional litters were documented from direct follow-ups to sighting made by the public and reported to CDOW. Two females that had kittens in 2003 and reared at least part of their litters through March 2004, bred and had kittens again in 2004. Two of the litters documented by direct observation or snow-tracking are from females whose collars were no longer functioning. Seven kittens born in 2004 were captured at approximately 10-months of age and fitted with dual satellite/VHF collars. Six of the 7 were still alive and being monitored as of June 30, 2006. The cut collar of one kitten CO04M15 was left at the Silverton Post Office on October 25, 2005. We assume this lynx is dead. 2005.-- In spring 2005 we had 40 females from the releases in 1999, 2000, 2003 and 2004 that had active radio-collars. We documented 23 possible mating pairs of lynx during breeding season. During May-June 2005 we visited 16 dens and found a total of 46 kittens (Table 11). An additional female (BC03F10) had a den we were not able to get to during May or June due to high water during spring run-off. Female BC03F03 was hit and killed on I-70 on 5/19/2005. She had 2 fetuses in her uterus, so would have contributed to reproduction this year had she lived. All of the 2005 dens were scattered throughout the high elevation areas of Colorado, south of I70. Most of the dens were in Engelmann spruce/subalpine fir forests in areas of extensive downfall. Elevations ranged from 3117-3586 m. Four of the females would not leave the den until we reached out to pick up a kitten. 12 �One female, YK00F10 has had litters 3 years in a row. In 2003 she had 4 kittens and raised 2 through the winter. In 2004 she had 2 kittens and raised both through the winter, in 2005 she had 4 kittens again. She has had all 3 litters in the same general area and has had the same mate for 3 years. Eight additional females had their second litter in Colorado in 2005. Three females from the 2004 releases had litters in 2005. Year 2005 was the second consecutive year that we had females released the prior spring find a territory and a mate within a year and produced live young. In reproduction season 2004 we had 3 females released in spring 2003 that also produced live young the next year. Of those 3, 2 successfully raised at least part of their litters through winter 2005. Seven kittens born in 2005 were captured at approximately 10-months of age and fitted with dual satellite/VHF collars. One of the 7 was still alive and being monitored as of June 30, 2007. 2006.-- In spring 2006, 42 females were being monitored. We found 4 dens in May and June 2006 with 11 kittens total (Table 11). Lynx CO04F07, a female lynx born in Colorado in 2004, was the mother of one of these litters which documented the first recruitment of Colorado-born lynx into the Colorado breeding population. There were at least 2 surviving kittens as of spring 2007. We were unsuccessful in capturing these kittens for collar placement. The percent of tracked females found with litters in 2006 was lower (0.095) than in the 3 previous years (0.413, SE = 0.032, Table 11). However, all demographic and habitat characteristics measured at the 4 dens that were found in 2006 were comparable to all other dens found (Table 11). Mean number of kittens per litter from 2003-2006 was 2.78 (SE = 0.05) and sex ratio of females to males was equal ( x = 1.14, SE = 0.14). 2007.-- During May and June 2007 we monitored 34 females for reproduction (Table 11). No dens were found. Den Sites.-- A total of 37 dens have been found from 2003-2006. All of the dens except one have been scattered throughout the high elevation areas of Colorado, south of I-70. In 2004, 1 den was found in southeastern Wyoming, near the Colorado border. Dens were located on steep ( x slope = 30o , SE=2o), north-facing, high elevation ( x = 3354 m, SE = 31 m) slopes. The dens were typically in Engelmann spruce/subalpine fir forests in areas of extensive downfall of coarse woody debris (Shenk 2006). All dens were located within the winter use areas used by the females. Captures Two adult lynx were captured in 2001 for collar replacement. One lynx was captured in a tomahawk live-trap, the other was treed by hounds and then anesthetized using a jab pole. Five adult lynx were captured in 2002; 3 were treed by hounds and 2 were captured in padded leghold traps. In 2004, 1 lynx was captured with a Belisle snare and 6 adult lynx were captured in box-traps. Trapping effort was substantially increased in winter and spring 2005 and 12 adult lynx were captured and re-collared. Eight reintroduced lynx were captured in winter and spring 2006. In 2007, 11 reintroduced adult lynx were captured and re-collared. All lynx captured in Colorado from 2005-2007 were caught in box-traps. In addition, as part of the collaring trapping effort, 14 Colorado-born kittens were captured and collared at approximately 10-months of age. Seven 2004-born kittens were collared in spring 2005, and 7, 2005-born kittens were collared in spring 2006. We were not successful at capturing and collaring any kittens born in 2006 in winter 2006-07. We did however, capture 2 adults (approximate age 2 years old) in winter 2006-07 that had no PIT-tags or radio collars. We assume these 2 lynx were from litters born in Colorado that were never found at dens (i.e., why there were no PIT-tags). All lynx captured for collaring 13 �or re-collaring were fitted with new Sirtrack TM dual VHF/satellite collars and re-released at their capture locations. Seven adult lynx were captured from March 1999-June 30, 2007 because they were in poor body condition (Table 12). Five of these lynx were successfully treated at the Frisco Creek Rehabilitation Center and re-released in the Core Release Area. One lynx, BC00F7, died from starvation and hypothermia within 1 day of capture at the rehabilitation center. Lynx QU04M07 died 3 days after capture at the rehabilitation center. Necropsy results documented starvation as the cause of death that was precipitated by hydrocephalus and bronchopneumonia (unpublished data T. Spraker, CSUVTH). Seven lynx were captured (either by CDOW personnel or conservation personnel in other states) because they were in atypical habitat outside the state of Colorado (Table 12). They were held at Frisco Creek Rehabilitation Center for a minimum of 3 weeks, fitted with new Sirtrack TM dual VHF/satellite collars and re-released in the Core Release Area in Colorado. Five of these 7 lynx were still alive 6 months post-re-release but 3 had already dispersed out of Colorado and 2 stayed in Colorado through June 30, 2007. Two lynx died within 6 months of re-release: 1 died of starvation in Colorado and the other died of unknown causes in Nebraska. Two lynx captured out of state and re-released currently remain in Colorado. HABITAT USE Landscape-scale daytime habitat use was documented from 9496 aerial locations of lynx collected from February 1999-June 30, 2007. Throughout the year Engelmann spruce - subalpine fir was the dominant cover used by lynx. A mix of Engelmann spruce, subalpine fir and aspen (Populus tremuloides) was the second most common cover type used throughout the year. Various riparian and riparian-mix areas were the third most common cover type where lynx were found during the daytime flights. Use of Engelmann spruce-subalpine fir forests and Engelmann spruce-subalpine fir-aspen forests was similar throughout the year. There was a trend in increased use of riparian areas beginning in July, peaking in November, and dropping off December through June. Site-scale habitat data collected from snow-tracking efforts indicate Engelmann spruce and subalpine fir were also the most common forest stands used by lynx for all activities during winter in southwestern Colorado. Comparisons were made among sites used for long beds, dens, travel and where they made kills. Little difference in aspect, mean slope and mean elevation were detected for 3 of the 4 site types including long beds, travel and kills where lynx typically use gentler slopes ( x = 15.7o ) at an mean elevation of 3173 m, and varying aspects with a slight preference for north-facing slopes. See Shenk (2006) for more detailed analyses of habitat use. DIET AND HUNTING BEHAVIOR Winter diet of lynx was documented through detection of kills found through snow-tracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. A total of 506 kills were located from February 1999-April 2007. We collected over 900 scat samples from February 1999-April 2007 that will be analyzed for content. In each winter, the most common prey item was snowshoe hare, followed by red squirrel (Tamiusciurus hudsonicus; Table 13). The percent of snowshoe hare kills found however, varied annually from a low of 55.56% in 1999 to a high of 90.77% in winter 2002-2003. SNOWSHOE HARE ECOLOGY The first year of a study to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands was completed and preliminary results presented (Appendix I). 14 �DISCUSSION In an effort to establish a viable population of lynx in Colorado, CDOW initiated a reintroduction effort in 1997 with the first lynx released in winter 1999. From 1999 through spring 2007, 218 lynx were released in the Core Release Area. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns and to detect mortalities. Most lynx remain in the high elevation, forested areas in southwestern Colorado. The use-density surfaces for lynx use in Colorado indicate two primary areas of use. The first is the Core Research Area (see Figure 1) and a secondary core centered in the Collegiate Peaks Wilderness (Figures 3, 4). High use is also documented for 1) the area east of Dillon, on both the north and south sides of I70 and 2) the area north of Hwy 50 centered around Gunnison and then north to Crested Butte. These last 2 high use areas are smaller in extent than the 2 core areas. Dispersal movement patterns for lynx released in 2000 and subsequent years were similar to those of lynx released in 1999 (Shenk 2000). However, more animals released in 2000 and subsequent years remained within the Core Release Area than those released in 1999. This increased site fidelity may have been due to the presence of con-specifics in the area on release. Numerous travel corridors within Colorado have been used repeatedly by more than 1 lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-Silverton-Lizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast to the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. Reproductive females had the smallest 90% utilization distribution home ranges ( x = 75.2 km2, SE = 15.9 km2), followed by attending males ( x = 102.5 km2, SE = 39.7 km2) and non-reproductive animals ( x = 653.8 km2, SE = 145.4 km2). Most lynx currently being tracked are within the Core Release Area. During the summer months, lynx were documented to make extensive movements away from their winter use areas. Extensive summer movements away from areas used throughout the rest of the year have been documented in native lynx in Wyoming and Montana (Squires and Laurion 1999). Current data collection methods used for the Colorado lynx reintroduction program were not specifically designed to address the reintroduced lynx movements or use of areas in other states. In particular, the core research and release area were in Colorado. Therefore, the number of aerial locations obtained would be far fewer in other states than in Colorado which would bias low the number of lynx and intensity of lynx use documented outside the state. In contrast, obtaining satellite locations is not biased by the location of the lynx. Satellite locations are, however, biased by the shorter time the satellite transmitters function, approximately 18 months versus 60 months for the VHF transmitters used to obtain the aerial locations. However, data collected to meet objectives of the lynx reintroduction program were used to provide information to help address the question of lynx use outside of Colorado. Due to the rarity of flights conducted outside Colorado, only use-density surfaces generated from satellite locations were used to document relative lynx use of areas in New Mexico, Utah and Wyoming. New Mexico and Wyoming have been used continuously by lynx since the first year lynx were released in Colorado (1999) to the present (Tables 2, 6). Lynx reintroduced in Colorado were first documented in Utah in 2000 (Table 4) and are still being documented there to date. In addition, all levels of lynx use-density documented throughout Colorado are also represented in New Mexico, Utah and Wyoming from none to the highest level of use (Figures 5, 7, 9). One den was found in Wyoming. Although no reproduction has been documented in New Mexico or Utah to date, documenting areas of the 15 �highest intensity of use and the continuous presence of lynx within these states for over six years does suggest the potential for year-round residency of lynx and reproduction in those states. The use-density surface for lynx use in New Mexico indicates the primary areas of use being located immediately south of the Colorado border and south of the Conejos River Valley (an area of high use in Colorado) or east of Taos (Figure 5). In Utah, the primary area of use is located in the Uinta Mountains (Figure 7). Lynx use in Wyoming is focused in 2 primary areas, the Medicine Bow National Forest in south-central Wyoming and in the northwest quadrant of the state including areas in Yellowstone and Teton National Parks and the Laramie Range (Figure 9). From 1999-June 2007, there were 98 mortalities of released adult lynx. Human-caused mortality factors are currently the highest causes of death with approximately 30.6% attributed to collisions with vehicles or gunshot. Starvation and disease/illness accounted for 19.4% of the deaths while 35.7% of the deaths were from unknown causes. Lynx mortalities were documented throughout all areas lynx used, including 28 (28.6%) occurring in other states (Figure 2, Table10). Half of the out-of-state mortalities were documented in New Mexico. Reproduction is critical to achieving a self-sustaining viable population of lynx in Colorado. Reproduction was first documented from the 2003 reproduction season and again in 2004, 2005 and 2006. Lower reproduction occurred in 2006 (Table 11) but did include a Colorado-born female giving birth to 2 kittens, documenting the first recruitment of Colorado-born lynx into the Colorado breeding population. No reproduction was documented in 2007. The cause of the decreased reproduction in 2006 and 2007 is unknown. One possible explanation would be a decrease in prey abundance. Additional reproduction is likely to have occurred in all years from females we were no longer tracking, and from Colorado-born lynx that have not been collared. The dens we find are more representative of the minimum number of litters and kittens in a reproduction season. To achieve a viable population of lynx, enough kittens need to be recruited into the population to offset the mortality that occurs in that year and hopefully even exceed the mortality rate to achieve an increasing population. The use-density surfaces depict intensity of use by location. Why certain areas would be used more intensively than others should be explained by the quality of the habitat in those areas. Characteristics of areas used by lynx, as documented through aerial locations and snow-tracking of lynx in the Colorado core research area, include mature Engelmann spruce-subalpine fir forest stands with 4265% canopy cover and 15-20% conifer understory cover (Shenk 2006). Within these forest stand types, lynx appear to have a slight preference for north-facing, moderate slopes ( x = 15.7°) at high elevations ( x = 3173 m; Shenk 2006). Snow-tracking of released lynx also provided information on hunting behavior and diet through documentation of kills, food caches, chases, and diet composition estimated through prey remains. The primary winter prey species (n = 506) were snowshoe hare (Table 12) with an annual x = 74.9% (SE = 4.6, n = 9) and red squirrel (annual x = 16.5%, SE = 4.1, n = 9). Thus, areas of good habitat must also support populations of snowshoe hare and red squirrel. In winter, lynx reintroduced to Colorado appear to be feeding on their preferred prey species, snowshoe hare and red squirrel in similar proportions as those reported for northern lynx during lows in the snowshoe hare cycle (Aubry et al. 1999). Environmental conditions in the springs and summers of 2003 and 2006 resulted in high cone crops during their following winters based on field observations, resulting in increased red squirrel abundance. This may partially explain the higher percent of red squirrel kills, and thus a lower percent of snowshoe hare kills, found in winters 2003-04 and 2006-07 (Table 12). 16 �Caution must be used in interpreting the proportion of identified kills. Such a proportion ignores other food items that are consumed in their entirety and thus are biased towards larger prey and may not accurately represent the proportion of smaller prey items, such as microtines, in lynx winter diet. Through snow-tracking we have evidence that lynx are mousing and several of the fresh carcasses have yielded small mammals in the gut on necropsy. The summer diet of lynx has been documented to include less snowshoe hare and more alternative prey than in winter (Mowat et al., 1999). All evidence suggests reintroduced lynx are finding adequate food resources to survive. Mowat et al. (1999) suggest lynx and snowshoe hare select similar habitats except that hares select more dense stands than lynx. Very dense understory limits hunting success of the lynx and provides refugia for hares. Given the high proportion of snowshoe hare in the lynx diet in Colorado, we might then assume the habitats used by reintroduced lynx also depict areas where snowshoes hare are abundant and available for capture by lynx in Colorado. From both aerial locations taken throughout the year and from the site-scale habitat data collected in winter, the most common areas used by lynx are in stands of Engelmann spruce and subalpine fir. This is in contrast to adjacent areas of Ponderosa pine, pinyon juniper, aspen and oakbrush. The lack of lodgepole pine in the areas used by the lynx may be more reflective of the limited amount of lodgepole pine in southwestern Colorado, the Core Release Area, rather than avoidance of this tree species. Hodges (1999) summarized habitats used by snowshoe hare from 15 studies as areas of dense understory cover from shrubs, stands that are densely stocked, and stands at ages where branches have more lateral cover. Species composition and stand age appears to be less correlated with hare habitat use than is understory structure (Hodges 1999). The stands need to be old enough to provide dense cover and browse for the hares and cover for the lynx. In winter, the cover/browse needs to be tall enough to still provide browse and cover in average snow depths. Hares also use riparian areas and mature forests with understory. Site-scale habitat use documented for lynx in Colorado indicate lynx are most commonly using areas with Engelmann spruce understory present from the snow line to at least 1.5 m above the snow. The mean percent understory cover within the habitat plots is typically less than 15% regardless of understory species. However, if the understory species is willow, percent understory cover is typically double that, with mean number of shrubs per plot approximately 80, far greater than for any other understory species. In winter, hares browse on small diameter woody stems (<0.25"), bark and needles. In summer, hares shift their diet to include forbs, grasses, and other succulents as well as continuing to browse on woody stems. This shift in diet may express itself in seasonal shifts in habitat use, using more or denser coniferous cover in winter than in summer. The increased use of riparian areas by lynx in Colorado from July to November may reflect a seasonal shift in hare habitat use in Colorado. Major (1989) suggested lynx hunted the edge of dense riparian willow stands. The use of these edge habitats may allow lynx to hunt hares that live in habitats normally too dense to hunt effectively. The use of riparian areas and riparian-Engelmann spruce-subalpine fir and riparian-aspen mixes documented in Colorado may stem from a similar hunting strategy. However, too little is known about habitat use by hares in Colorado to test this hypothesis at this time. Lynx also require sufficient denning habitat. Denning habitat has been described by Koehler (1990) and Mowat et al. (1999) as areas having dense downed trees, roots, or dense live vegetation. We found this to be in true in Colorado as well (Shenk 2006). In addition, the dens used by reintroduced lynx were at high elevations and on steep north-facing slopes. All females that were documented with kittens denned in areas within their winter-use area. 17 �SUMMARY From results to date it can be concluded that CDOW developed release protocols that ensure high initial post-release survival of lynx, and on an individual level, lynx demonstrated they can survive longterm in areas of Colorado. We also documented that reintroduced lynx exhibited site fidelity, engaged in breeding behavior and produced kittens that were recruited into the Colorado breeding population. What is yet to be demonstrated is whether current conditions in Colorado can support the recruitment necessary to offset annual mortality in order to sustain the population. Monitoring of reintroduced lynx will continue in an effort to document such viability. ACKNOWLEDGEMENTS The lynx reintroduction program involves the efforts of literally hundreds of people across North America, in Canada and USA. Any attempt to properly acknowledge all the people who played a role in this effort is at risk of missing many people. The following list should be considered to be incomplete. CDOW CLAWS Team (1998-2001): Bill Andree, Tom Beck, Gene Byrne, Bruce Gill, Mike Grode, Rick Kahn (Program Leader), Dave Kenvin, Todd Malmsbury, Jim Olterman, Dale Reed, John Seidel, Scott Wait, Margaret Wild. CDOW: John Mumma (Director 1996-2000), Russell George (Director 2001-2003), Bruce McCloskey (Director 2004-2007), Conrad Albert, Jerry Apker, Laurie Baeten, Cary Carron, Don Crane, Larry DeClaire, Phil Ehrlich, Lee Flores, Delana Friedrich, Dave Gallegos, Juanita Garcia, Drayton Harrison, Jon Kindler, Ann Mangusso, Jerrie McKee, Gary Miller, Melody Miller, Mike Miller, Kirk Navo, Robin Olterman, Jerry Pacheo, Mike Reid, Tom Remington, Ellen Salem, Eric Schaller, Mike Sherman, Jennie Slater, Steve Steinert, Kip Stransky, Suzanne Tracey, Anne Trainor, Scott Wait, Brad Weinmeister, Nancy Wild, Perry Will, Lisa Wolfe, Brent Woodward, Kelly Woods, Kevin Wright. Lynx Advisory Team (1998-2001): Steve Buskirk, Jeff Copeland, Dave Kenny, John Krebs, Brian Miller (Co-Leader), Mike Phillips, Kim Poole, Rich Reading (Co-Leader), Rob Ramey, John Weaver. U. S. Forest Service: Kit Buell, Joan Friedlander, Dale Gomez, Jerry Mastel, John Squires, Fred Wahl, Nancy Warren. U. S. Fish and Wildlife Service: Lee Carlson, Gary Patton (1998-2000), Kurt Broderdorp. State Agencies: Alaska: ADF&G: Cathie Harms, Mark Mcnay, Dan Reed (Regional Manager), Wayne Reglin (Director), Ken Taylor (Assist. Director), Ken Whitten, Randy Zarnke, Other:Ron Perkins (trapper), Dr. Cort Zachel (veterinarian). Washington: Gary Koehler. National Park Service: Steve King. Colorado State University: Alan Franklin, Gary White. Colorado Natural Heritage Program: Rob Schorr, Mike Wunder. Canada: British Columbia: Dr. Gary Armstrong (veterinarian), Mike Badry (government), Paul Blackwell (trapper coordinator), Trappers: Dennis Brown, Ken Graham, Tom Sbo, Terry Stocks, Ron Teppema, Matt Ounpuu. Yukon: Government: Arthur Hoole (Director), Harvey Jessup, Brian Pelchat, Helen Slama, Trappers: Roger Alfred, Ron Chamber, Raymond Craft, Lance Goodwin, Jerry Kruse, Elizabeth Hofer, Jurg Hofer, Guenther Mueller (YK Trapper’s Association), Ken Reeder, Rene Rivard (Trapper coordinator), Russ Rose, Gilbert Tulk, Dave Young. Alberta: Al Cook. Northwest Territories: Albert Bourque, Robert Mulders (Furbearer Biologist), Doug Steward (Director NWT Renewable Res.), Fort Providence Native People. Quebec: Luc Farrell, Pierre Fornier. Colorado Holding Facility: Herman and Susan Dieterich, Kate Goshorn, Loree Harvey, Rachel Riling. Pilots: Dell Dhabolt, Larry Gepfert, Al Keith, Jim Olterman, Matt Secor, Brian Smith, Whitey Wannamaker, Steve Waters, Dave Younkin. 18 �Field Crews (1999-2007): Steve Abele, Brandon Barr, Bryce Bateman, Todd Bayless, Nathan Berg, Ryan Besser, Jessica Bolis, Mandi Brandt, Brad Buckley. Patrick Burke, Braden Burkholder, Paula Capece, Stacey Ciancone, Doug Clark, John DePue, Shana Dunkley, Tim Hanks, Carla Hanson, Dan Haskell, Nick Hatch, Matt Holmes, Andy Jennings, Susan Johnson, Paul Keenlance, Patrick Kolar, Tony Lavictoire, Jenny Lord, Clay Miller, Denny Morris, Kieran O’Donovan, Gene Orth, Chris Parmater, Jake Powell, Jeremy Rockweit, Jenny Shrum, Josh Smith, Heather Stricker, Adam Strong, Dave Unger, David Waltz, Andy Wastell, Mike Watrobka, Lyle Willmarth, Leslie Witter, Kei Yasuda, Jennifer Zahratka. Research Associates: Bob Dickman, Grant Merrill. Data Analysts: Karin Eichhoff, Joanne Stewart, Anne Trainor. Data Entry: Charlie Blackburn, Patrick Burke, Rebecca Grote, Angela Hill, Mindy Paulek. Mary Schuette and Dave Theobald provided assistance with the GIS analysis and M. Schuette generated the maps used in this report Photographs: Tom Beck, Bruce Gill, Mary Lloyd, Rich Reading, Rick Thompson. Funding: CDOW, Great Outdoors Colorado (GOCO), Turner Foundation, U.S.D.A. Forest Service, Vail Associates, Colorado Wildlife Heritage Foundation. LITERATURE CITED AUBRY, K. B., G. M. KOEHLER, J. R. SQUIRES. 1999. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. BYRNE, G. 1998. Core area release site selection and considerations for a Canada lynx reintroduction in Colorado. Report for the Colorado Division of Wildlife. CURTIS, J. T. 1959. The vegetation of Wisconsin. University of Wisconsin Pres, Madison. HODGES, K. E. 1999. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. KOEHLER, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. KOLBE, J. A., J. R. SQUIRES, T. W. PARKER. 2003. An effective box trap for capturing lynx. Journal of Wildlife Management 31:980-985. LAYMON, S. A. 1988. The ecology of the spotted owl in the central Sierra Nevada, California. PhD Dissertation University of California, Berkeley, California. MAJOR, A. R. 1989. Lynx, Lynx canadensis canadensis (Kerr) predation patterns and habitat use in the Yukon Territory, Canada. M. S. Thesis, State University of New York, Syracuse. MOWAT, G., K. G. POOLE, AND M. O’DONOGHUE. 1999. Ecology of lynx in northern Canada and Alaska. Pages 265-306 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. POOLE, K. G., G. MOWAT, AND B. G. SLOUGH. 1993. Chemical immobilization of lynx. Wildlife Society Bulletin 21:136-140. SHENK, T. M. 1999. Program narrative Study Plan: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2001. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2006. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report July: 1-45. Colorado Division of Wildlife, Fort Collins, Colorado 19 �SILVERMAN, B.W. 1986. Density Estimation for Statistics and Data Analysis. Chapman and Hall. New York, New York, USA. SQUIRES, J. R. AND T. LAURION. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. U. S. FISH AND WILDLIFE SERVICE. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. WHITE, G.C. AND K. P. BURNHAM. 1999. Program MARK: Survival estimation from populations of marked animals. Bird Study 46 Supplement, 120-138. WILD, M. A. 1999. Lynx veterinary services and diagnostics. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. Prepared by ___________________________________ Tanya M. Shenk, Wildlife Researcher Table 1. Lynx released in Colorado from February 1999 through June 30, 2007. No lynx were released in 2001, 2002 or 2007. Year Females Males TOTAL 1999 22 19 41 2000 35 20 55 2003 17 16 33 2004 17 20 37 2005 18 20 38 2006 6 8 14 TOTAL 115 103 218 20 �Table 2. All individual lynx (n = 60) documented through either aerial or satellite locations (nontruncated datasets) by year in New Mexico from February 1999 – March 2007. Lynx ID AK99F10 AK99F13 AK99F17 AK99F3 AK99F5 AK99F8 AK99M11 AK99M26 AK99M9 BC99M4 YK99F3 YK99M3 YK99M6 YK99M7 AK00F2 AK00F5 BC00F10 BC00F14 BC00F6 BC00F8 BC00M04 BC00M11 BC00M4 YK00F11 YK00F2 YK00F4 YK00F7 BC03F03 BC03F04 BC03F06 BC03F08 BC03M02 BC03M05 BC03M08 QU03F01 QU03F04 QU03F07 BC04F02 BC04F03 BC04F05 BC04M02 BC04M13 QU04F05 QU04F08 QU04F09 QU04M02 QU04M04 BC05F04 BC05M02 QU05F03 QU05M01 QU05M05 YK05F01 YK05M01 BC06F05 BC06F07 BC06F09 BC06M12 YK06F01 YK06M01 Total Lynx 1999 X X X X X X X X 2000 2001 2002 Year 2003 2004 2006 2007 X X X X X X X X X X X X X X X X X X X X X X X X X X X 11 2 3 9 21 X X X X X 8 2005 X X X X X X X X X X X X X X X X X X X X X X X X 17 X X X X X X X X X X 17 X X X X X X X X 14 X 2 �Table 3. All individual lynx (n = 35) documented at least 180 days after their initial release (truncated datasets) through either aerial or satellite locations, by year in New Mexico from September 1999 – March 2007. Lynx ID AK99F13 AK99F3 AK99F5 AK99M11 AK99M9 BC99M4 YK99F3 YK99M6 AK00F2 AK00F5 BC00F14 BC00F8 BC00M04 BC00M11 BC00M4 YK00F11 YK00F2 YK00F4 YK00F7 BC03F03 BC03F06 BC03M02 BC03M08 QU03F04 QU03F07 BC04F02 BC04M13 QU04F05 QU04F08 QU04F09 QU05M05 YK05M01 BC06F07 BC06M12 YK06F01 Total Lynx 2000 X X 2001 2002 2003 Year 2004 X X X 2006 2007 X X X X X X X X X X X X 2 3 X X X X X X X X X X X X X X 6 2005 2 12 22 X X X X X X X X X X 10 X X X X X X 11 X 2 �Table 4. All individual lynx (n = 22) documented through either aerial or satellite locations (nontruncated datasets) by year in Utah from February 1999 – March 2007. Lynx ID AK99F5 AK00F5 AK00M3 BC00M09 BC00M13 YK00F7 BC03F03 BC03M06 BC03M08 BC03M10 QU03F03 BC04M01 QU04M04 QU04M05 BC05M01 BC05M03 CO05F20 QU05F05 QU05M03 QU05M08 YK05M01 YK06M01 Total Lynx 2000 2001 2002 2003 Year 2004 X 2005 X 2006 X X X X X X X X X X X X X X X X 1 0 X X X 1 2007 2 4 7 X X X X X 7 X 5 Table 5. All individual lynx (n = 17) documented at least 180 days after their initial release (truncated datasets) through either aerial or satellite locations, by year in Utah from September 1999 – March 2007. Lynx ID AK99F5 AK00F5 AK00M3 BC00M09 YK00F7 BC03M06 BC03M10 QU03F03 BC04M01 QU04M04 BC05M01 BC05M03 CO05F20 QU05F05 QU05M03 YK05M01 YK06M01 Total Lynx 2000 2001 2002 2003 X Year 2004 2005 X X X X X X X X 1 0 0 23 3 6 2007 X X X 0 2006 X X X X X X 7 X X X X 5 �Table 6. All individual lynx (n = 33) documented through either aerial or satellite locations (nontruncated datasets) by year in Wyoming from February 1999 – March 2007. Lynx ID AK99M6 BC00F14 BC00M13 YK00F11 BC03F03 BC03M02 BC03M06 BC03M09 QU03M01 BC04F02 BC04M01 BC04M08 BC04M13 CO04F10 CO04M05 CO04M06 QU04F01 QU04F02 QU04F07 QU04M04 QU04M05 BC05M03 BC05M08 MB05F01 MB05F02 MB05F03 QU05F04 QU05F05 QU05F08 QU05M08 YK05M03 BC06M10 BC06M13 Total Lynx 1999 X 2001 2003 X X Year 2004 2005 2006 2007 X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X 1 1 2 16 24 14 X X X X X X X X X 16 X X X X X 5 �Table 7. All individual lynx (n = 27) documented at least 180 days after their initial release (truncated datasets) through aerial or satellite locations, by year in Wyoming from September 1999 – March 2007. Year Lynx ID BC00F14 BC00M13 YK00F11 BC03F03 BC03M02 BC03M06 BC03M09 QU03M01 BC04F02 BC04M08 BC04M13 CO04F10 CO04M05 CO04M06 QU04F01 QU04F02 QU04M04 QU04M05 BC05M03 MB05F01 MB05F02 MB05F03 QU05F04 QU05F05 QU05F08 QU05M08 BC06M13 Total Lynx 2001 2003 2004 X X X X 2005 2006 2007 X X X X X X X X X X X X X X X X X X X X X X X X X 1 2 14 11 X X X X X X X X X X X X X X 15 X X X X X 5 Table 8. Status of adult lynx reintroduced to Colorado as of June 30, 2007. Lynx Released Known Dead Possible Alive Missing Monitoring/tracking a 1 is unknown mortality Females 115 54 61 23 38 Males 103 43 60 27 33 Unknown 1 TOTALS 218 98 120 49a 71 Table 9. Causes of death for all lynx released into southwestern Colorado 1999-2006 as of June30, 2007. Cause of Death Unknown Gunshot Hit by Vehicle Starvation Other Trauma Plague Probable Gunshot Predation Probable Predation Illness Total Mortalities Mortalities In Colorado (%) 20 (57.1) 7 (53.8) 8 (66.7) 9 (90.0) 7 (87.5) 7 (100) 4 (80) 3 (100) 3 (100) 2 (100) 70 (71.4) Total (%) 35 (35.7) 13 (13.3) 12 (12.2) 10 (10.2) 8 (8.1) 7 (7.1) 5 (5.1) 3 (3.1) 3 (3.1) 2 (2.0) 98 25 Outside Colorado (%) 15 (42.9) 6 (46.2) 4 (33.3) 1 (10.0) 1 (12.5) 0 (0) 1 (20) 0 (0) 0 (0) 0 (0) 28 (28.6) �Table 10. Known lynx mortalities (n = 28) and causes of death documented by state outside of Colorado from February 1999 – June 30, 2007. Lynx ID AK99F8 Unknown AK99M11 YK99M06 AK99F13 YK00F04 BC99M04 QU05M01 QU04F05 QU03F07 BC00M04 YK06F01 BC03M08 BC06F07 AK99M06 AK99M01 QU05M08 MB05F02 BC00F14 QU04F07 BC06M10 QU04F02 AK00M03 QU05M03 YK06M01 YK99F01 YK00M03 YK05M03 State Date Mortality Recorded Cause of Death New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico Nebraska Nebraska Nebraska Nebraska Wyoming Wyoming Wyoming Wyoming Utah Utah Utah Arizona Kansas Montana 7/30/1999 2000 1/27/2000 6/19/2000 6/22/2000 4/20/2001 6/7/2002 8/22/2005 8/26/2005 9/15/2005 7/19/2006 10/19/2006 10/19/2006 1/8/2007 11/16/1999 1/11/2005 10/1/2006 2/13/2007 7/28/2004 9/21/2004 8/15/2006 3/14/2007 7/2/2001 10/26/2005 12/4/2006 9/15/2005 9/30/2005 11/8/2005 Starvation Hit by Vehicle Unknown Probable Gunshot Unknown Gunshot Gunshot Unknown Hit by Vehicle Unknown Unknown Unknown Unknown Gunshot Gunshot Snared (Other Trauma) Unknown Gunshot Unknown Unknown Vehicle Collision Unknown Unknown Unknown Unknown Gunshot Vehicle Collision Unknown Table 11. Lynx reproduction summary statistics for 2003-2007. No reproduction was documented from 1999-2002 or in 2007. Year Females Tracked Dens Found in May/June 2003 2004 2005 2006 2007 Total 17 26 40 42 34 6 11 17 4 0 Percent Tracked Females with Kittens 0.353 0.462 0.425 0.095 0.0 Additional Litters Found in Winter 2 1 26 Mean Kittens Per Litter (SE) 2.67 (0.33) 2.83 (0.24) 2.88 (0.18) 2.75 (0.47) Total Kittens Found 16 39 50 11 0 116 Sex Ratio M/F (SE) 1.0 1.5 0.8 1.2 1.14 (0.14) �Table 12. Lynx captured because they were in poor body condition or were in atypical habitat and their fates 6 months post re-release and as of June 30, 2007. Lynx ID BC99F6 Date of Capture 3/25/1999 State Where Captured Colorado Reason For Capture Poor body condition Date of Re-release 5/28/1999 Status 6 Months Post Re-release Dead AK99M9 3/24/2000 Colorado 5/3/2000 Missing AK99F2 4/18/2000 Colorado 5/22/2000 BC00F7 2/11/2001 Colorado Alive in Colorado Dead BC00M13 3/21/2001 Wyoming BC03M08 9/5/2003 Colorado QU04M07 2/2/2006 Colorado Poor body condition Poor body condition Poor body condition Poor body condition Poor body condition Poor body condition BC04M01 11/5/2004 Utah QU04F02 4/10/2005 Nebraska QU05M08 11/25/2005 Wyoming QU04M04 12/5/2006 Utah YK00F7 12/12/2006 Utah YK05M02 1/1/2007 Kansas BC04M08 1/22/2007 Wyoming N/A 4/24/2001 1/1/2004 N/A Alive in Colorado Alive in Colorado Dead Died 7/19/1999 in Colorado from vehicle collision Last located 5/3/2000, collar failure Last located 7/30/2003 in Colorado Died at Rehab Center on 2/12/2001 Last located 10/26/2004 in Colorado Died in New Mexico of unknown causes 10/19/06 Died at Rehab Center on 2/5/2006 from hydrocephalous and pneumonia Atypical habitat Atypical habitat 12/5/2004 Atypical habitat Atypical habitat Atypical habitat Atypical habitat Atypical habitat 4/18/2006 Dead 1/20/2007 1/20/2007 Dead in Colorado Alive in Utah Died 3/14/2007 in Wyoming (good habitat) of unknown causes Died of unknown causes in Nebraska 10/1/2006 Died of starvation in Colorado, found 3/19/07 In Utah as of 6/30/2007 2/2/2007 Alive in Iowa In Iowa as of 6/30/2007 2/15/2007 Alive in Colorado In Colorado as of 6/30/2007 5/7/2005 Alive in Colorado Alive in Wyoming Current Status In Colorado as of 6/30/2007 Table 13. Number of kills found each winter field season through snow-tracking of lynx and percent composition of kills of the three primary prey species. Field Season 1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007 n 9 83 89 54 65 37 78 50 41 Snowshoe Hare 55.56 67.47 67.42 90.74 90.77 67.57 83.33 90.00 61.00 Prey (%) Cottontail Red Squirrel 22.22 0 19.28 1.20 19.10 8.99 5.56 0 6.15 0 27.03 2.70 10.26 0 0.08 0 39.0 0 27 Other 22.22 12.05 4.49 3.70 3.08 2.70 6.41 0.02 0 �Figure 1. Lynx are monitored throughout Colorado and by satellite throughout the western United States. The lynx core release area, where all lynx were released, is located in southwestern Colorado. A lynx-established core use area has developed in the Taylor Park and Collegiate Peak area in central Colorado. 28 �Figure 2. All documented lynx locations (non-truncated datasets) obtained from either aerial (yellow circles) or satellite (red circles) tracking from February 1999 through June 30, 2007. All known lynx mortality locations (n = 97) are displayed as stars. 29 �Figure 3. Use-density surface for lynx aerial locations (truncated dataset) in Colorado from September 1999-March 2007 30 �Figure 4. Use-density surface for lynx satellite locations (truncated dataset) in Colorado from September 1999-March 2007. 31 �Figure 5. Use-density surface for lynx satellite locations (truncated dataset) in New Mexico from September 1999-March 2007 32 �Figure 6. Use-density surface for lynx satellite locations (truncated dataset) in Colorado and New Mexico from September 1999-March 2007. 33 �Figure 7. Use-density surface for lynx satellite locations (truncated dataset) for Utah from September 1999-March 2007. 34 �Figure 8. Use-density surface for lynx satellite locations (truncated dataset) in Colorado and Utah from September 1999-March 2007. 35 �Figure 9. Use-density surface for lynx satellite locations (truncated dataset) in Wyoming from September 1999-March 2007. 36 �Figure 10. Use-density surface for lynx satellite locations (truncated dataset) in Colorado and Wyoming from September 1999-March 2007. 37 �APPENDIX I Colorado Division of Wildlife July 2006 - June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 0670 2 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Lynx Conservation : Density, Demography, and Seasonal Movements of Snowshoe Hare in Colorado : Period Covered: July 1, 2006- June 30, 2007 Author: J. S. Ivan, Ph. D. Candidate, Colorado State University Personnel: T. M. Shenk, CDOW and G. C. White of Colorado State University. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A program to reintroduce the threatened Canada lynx (Lynx canadensis) into Colorado was initiated in 1997 with the first lynx release in 1999. Analysis of scat collected from winter snow tracking indicated that snowshoe hares (Lepus americanus) comprised 65–90% of the winter diet of reintroduced lynx. Thus, existence of lynx in Colorado and success of the reintroduction effort hinge at least in part on maintaining adequate and widespread populations of hares. Beginning in July 2006, I initiated a study to assess the relative value of 3 forest stand types (mature [“large”] spruce/fir, sapling [“small”] lodgepole pine, pole-sized [“medium”] lodgepole pine) that purportedly provide high quality hare habitat in Colorado. Estimates and comparisons of survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each stand will provide the metrics for assessing value. Number of individuals captured, number of captures, and number of locations obtained per hare during the first year of the project appear adequate for attaining the objectives of this study. Some hare deaths due to capture myopathy (most likely cause) occurred during initial trapping periods in both the summer and winter sampling seasons. However, changes to the trapping protocol, trapping schedule, and bait provided seem to have alleviated the problem. Densities during summer were highest in small lodgepole stands (0.47 hares/ha, 95% CI: 0.41-0.54), followed by large spruce/fir (0.18 hares/ha, 95% CI: 0.12-0.25) and medium lodgepole (0.02 hares/ha, 95% CI: 0.01-0.03). During winter, densities in small lodgepole stands dropped and became more variable across replicates (0.18 hares/ha, 95% CI: 0.01-0.35). Medium lodgepole stands gained hares (0.07 hares/ha, 95% CI: 0.050.10). Spruce/fir stands remained at the same density as during summer (0.17 hares/ha, 95% CI: 0.110.23). 38 �WILDIFE RESEARCH REPORT DENSITY, DEMOGRAPHY, AND SEASONAL MOVEMENTS OF SNOWSHOE HARE IN COLORADO JACOB S. IVAN P. N. OBJECTIVE Assess the relative value of 3 forest stand types (old spruce/fir, sapling lodgepole, pole-sized lodgepole) that purportedly provide high quality snowshoe hare (Lepus americanus) habitat by estimating survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each type. SEGMENT OBJECTIVES 1. Complete mark-recapture work across all replicate stands during late summer (mid-July through midSeptember) and winter (mid-January through March). 2. Obtain daily telemetry locations on radio-tagged hares for 10 days immediately after capture periods, as well as monthly between primary trapping sessions. 3. Locate, retrieve, and refurbish radio tags as mortalities occur. 4. Summarize initial sampling efforts and provide initial density estimates for Wildlife Research Reports for Colorado Division of Wildlife (CDOW). INTRODUCTION A program to reintroduce the threatened Canada lynx (Lynx canadensis) into Colorado was initiated in 1997 with the first lynx released in 1999. Since that time, 204 lynx have been released in the state, and an extensive effort to determine their movements, habitat use, reproductive success, and food habits has ensued (Shenk 2006). Analysis of scat collected from winter snow tracking indicates that snowshoe hares (Lepus americanus) comprise 65–90% of the winter diet of reintroduced lynx (T. Shenk, Colorado Division of Wildlife, unpublished data). Thus, as in the far north where the intimate relationship between lynx and snowshoe hares has captured the attention of ecologists for decades, the existence of lynx in Colorado and success of the reintroduction effort may also hinge on maintaining adequate and widespread populations of hares. Colorado represents the extreme southern range limit for both lynx and snowshoe hares (Hodges 2000). At this latitude, habitat for each species is less widespread and more fragmented compared to the continuous expanse of boreal forest at the heart of lynx and hare ranges. Neither species exhibits dramatic cycles as occur farther north, and typical lynx (≤2−3 lynx/100km2; Aubry et al. 2000) and hare (≤1−2 hares/ha; Hodges 2000) densities in the southern part of their range correspond to cyclic lows form northern populations (2-30 lynx/100 km2, 1−16 hares/ha; Aubry et al. 2000, Hodges 2000, Hodges et al. 2001). Whereas extensive research on lynx-hare ecology has occurred in the boreal forests of Canada, literature regarding the ecology of these species in the southern portion of their range is relatively sparse. This scientific uncertainty is acknowledged in the “Canada Lynx Conservation Assessment and Strategy,” a formal agreement between federal agencies intended to provide a consistent approach to lynx conservation on public lands in the lower 48 states (Ruediger et al. 2000). In fact, one of the explicit guiding principles of this document is to “retain future options…until more conclusive information concerning lynx management is developed.” Thus, management recommendations in this agreement are 39 �decidedly conservative, especially with respect to timber management, and are applied broadly to cover all habitats thought to be of possible value to lynx and hare. This has caused controversy where recommendations conflict with competing resource management goals. Accurate identification and detailed description of lynx-hare habitat in the southern Rocky Mountains would permit more informed and refined management recommendations. A commonality throughout the snowshoe hare literature, regardless of geographic location, is that hares are associated with dense understory vegetation that provides both browse and protection from elements and predators (Wolfe et al. 1982, Litvaitis et al. 1985, Hodges 2000, Homyack et al. 2003, Miller 2005). In western mountains, this understory can be provided by relatively young conifer stands regenerating after stand-replacing fires or timber harvest (Sullivan and Sullivan 1988, Koehler 1990, Koehler 1990, Bull et al. 2005) as well as mature, uneven-aged stands (Beauvais 1997, Griffin 2004). Hares may also take advantage of seasonally abundant browse and cover provided by deciduous, open habitats (e.g., riparian willow [Salix spp.], aspen [Populus tremuloides]; Wolff 1980, Miller 2005). In drier portions of hare range, such as Colorado, regenerating stands can be relatively sparse, and hares may be more associated with mesic, late-seral forest and/or riparian areas than with young stands (Ruggiero et al. 2000). Numerous investigators have sought to determine the relative importance of these distinctly different habitat types with regards to snowshoe hare ecology. Most previous evaluations were based on hare density or abundance (Bull et al. 2005), indices to hare density and abundance (Wolfe et al. 1982, Koehler 1990, Beauvais 1997, Miller 2005), survival (Bull et al. 2005), and/or habitat use (Dolbeer and Clark 1975). Each of these approaches provides insight into hare ecology, but taken singly, none provide a complete picture and may even be misleading. For example, extensive use of a particular habitat type may not accurately reflect the fitness it imparts on individuals, and density can be high even in “sink” habitats (Van Horne 1983). A more informative approach would be to measure density, survival, and habitat use simultaneously in addition to recruitment and population growth rate through time. Griffin (2004) employed such an approach and found that summer hare densities were consistently highest in young, dense stands. However, he also noted that only dense mature stands held as many hares in winter as in summer. Furthermore hare survival seemed to be higher in dense mature stands, and only dense mature stands were predicted (by matrix projection) to impart a mean positive population growth rate on hares. Griffin’s (2004) study occurred in the relatively moist forests of Montana, which share many similarities but also many notable differences with Colorado forests including levels of fragmentation, species composition, elevation, and annual precipitation. Density estimation is a key component in assessing the value of a particular stand type and is the common currency by which hare populations are compared across time and space. However, density can be a difficult metric to estimate accurately. Density estimation based on capture-recapture methods is a well-developed field (Otis et al. 1978, White et al. 1982), but is often too costly and labor intensive to be implemented on scales necessary to effectively monitor density over a biologically meaningful area. Also, density can be difficult to assess from grid-trapping efforts because it is often unclear how much area was effectively sampled by the grid (Williams et al. 2002:314). Different approaches can produce density estimates that differ by an order of magnitude even when calculated from the same data (Zahratka 2004). Indices such as pellet plot counts and distance sampling of pellet groups can be used to estimate density, but each of these has limitations as well (Krebs et al. 1987, Eriksson 2006). Pellet plot counts are typically conducted by laying out numerous rectangular or circular plots along transect lines randomly placed within a study site. All pellets occurring within the plot are counted and removed on an annual basis. The mean number of pellets per plot is then inserted into a regression equation that gives an estimate of hare density (Krebs et al. 1987). Estimates from this technique correlate well with density estimates derived from simultaneous mark-recapture studies occurring in the 40 �same area (Krebs et al. 2001, Murray et al. 2002, Mills et al. 2005, Homyack et al. 2006). However, because fecal deposition rates can vary by season and diet, and because pellet decomposition rates can vary with altitude, climate, aspect, precipitation, and cover type, region-specific, stand-specific, and/or season-specific equations should be developed before this technique is employed for a given area and season (Krebs et al. 2001, Prugh and Krebs 2004, Murray et al. 2005). Density estimates vary with plot size and shape, requiring equations specific to these geometric considerations as well (McKelvey et al. 2002). Pellet counts tend to yield more precise and unbiased density estimates when plots are visited and cleared more than once per year (e.g., plots cleared in the fall and then counted in the spring to estimate winter density) because variability in deposition and decomposition rates is reduced (Homyack et al. 2006). However, this requires considerably more work and expense than an annual survey. Some studies have conducted pellet plot counts without first clearing plots (e.g., Bartmann and Byrne 2001). This saves time and money, but requires the ability to discern fresh (this year) pellets from old pellets, which can be difficult and is generally not a recommended approach (Prugh and Krebs 2004, Murray et al. 2005). Distance sampling is a well-developed method for estimating the density of objects in a given area (Buckland et al. 2001). In general, observers walk a pre-defined sampling transect and record each object of interest along with the perpendicular distance of that object from the transect line. This information is then used to develop a detection function which is in turn used to estimate density (Buckland et al. 2001). The method assumes all objects on the line are seen with certainty, objects are not double-counted, distance measures are accurate, and transect lines are located randomly within a study area (Buckland et al. 2001). Recently, distance sampling has been used to indirectly estimate hare density by first estimating the pellet group density of hares, then using fecal deposition and decomposition rates as a link back to hare density (Eriksson 2006). In general, distance sampling is more efficient than pellet plot counts as it does not require the tedious layout of hundreds of plots or counting individual pellets. This advantage is most recognizable in situations where pellet groups occur at low densities. Conversely, at extremely high densities, it may become difficult to distinguish pellet groups, and plots may be preferable (Marques et al. 2001). Regardless, distance sampling of pellet groups to estimate animal density also requires habitat and season specific decomposition and defecation rates, which can be difficult to obtain (Marques et al. 2001). For this project, I have chosen to provide land managers with information relating demographic rates, as well as density, to forest stand characteristics. Thus, I will use mark-recapture techniques as data from such an approach can provide information on both density and demography. I will address the “effective trapping area” issue using a new approach that augments mark-recapture data with telemetry locations of animals using the grid. The study outlined below is designed principally to evaluate the importance of young, regenerating lodgepole pine (Pinus contorta) and mature Engelmann spruce (Picea engelmannii)/ subalpine fir (Abies lasiocarpa) stands in Colorado by examining density and demography of snowshoe hares that reside in each (Figure 1). My hope is that information gathered from this research will be drawn upon as managers make routine decisions, leading to landscapes that include stands capable of supporting abundant populations of hares. I assume that if management agencies focus on providing habitat, hares will persist. Specifically, I will evaluate small and medium lodgepole pine stands and large spruce/fir stands where the classes “small”, “medium”, and “large” refer to the diameter at breast height (dbh) of overstory trees as defined in the United States Forest Service R2VEG Database (small = 2.54−12.69 cm dbh, medium = 12.70−22.85 cm, and large = 22.86−40.64 cm dbh; J. Varner, United States Forest Service, personal communication). I also intend to identify which of the numerous density-estimation procedures available perform accurately and consistently using an innovative, telemetry augmentation approach as a 41 �baseline. I will assess movement patterns and seasonal use of deciduous cover types such as riparian willow. Finally, I will further expound on the relationship between density, demography, and stand type by examining how snowshoe hare density and demographic rates vary with specific vegetation, physical, and landscape characteristics of a stand. Hypotheses 1) In general, snowshoe hare density in Colorado will be relatively low (≤0.5 hares/ha) compared to densities reported in northern boreal forests, even immediately post-breeding when an influx of juveniles will bolster hare numbers. 2) Snowshoe hare density will be consistently highest in small lodgepole pine stands, followed by large spruce/fir and medium lodgepole pine, respectively. 3) Survival will generally be highest in mature (large) spruce/fir stands followed by small and medium lodgepole pine, respectively. 4) Finite population growth rate will be consistently at or above 1.0 in mature spruce/fir stands with survival contributing most significantly to the growth rate. Finite growth rates for the lodgepole pine stands will be more variable. 5) Snowshoe hares will significantly shift their home ranges to make use of abundant food and cover provided by riparian willow (and/or aspen) habitats in summer. 6) Snowshoe hare density, survival, and recruitment will be highly correlated with understory cover and stem density. STUDY AREA The study area stretches from Taylor Park to Pitkin in central Colorado (Figure 2). Elevation ranges from 2700 m to 4000 m. Sagebrush (Artemisia spp.) dominates broad, low-lying valleys. Most montane areas are covered by even-aged, large-diameter lodgepole pine forests with sparse understory. Moist, north-facing slopes and areas near tree line are dominated by large-diameter Engelmann spruce/subalpine fir. Interspersed along streams and rivers are corridors of willow. Patches of aspen occur sporadically on southern exposures. This area was chosen over other potential study areas in the state because 1) it contained numerous examples of the 3 stand types of interest (more southern regions lack naturally occurring stands of lodgepole pine), 2) it was not subject to confounding effects of largescale mountain pine beetle outbreak as were more northern stands, and 3) an adequate number of radio frequencies were available to support a large study with hundreds of radio-tagged individuals. Within the study area I selected sample stands based on the following: Potential replicate stands were required to be 1) close enough geographically to minimize differences due to climate, weather, and topography, but are far enough apart to be considered independent, 2) adjacent to one or more riparian willow corridors, 3) within 1 km of an access road for logistical purposes, 4) of suitable size and shape to admit a 16.5-ha trapping grid, and 5) consistent in their management history (i.e., replicate lodgepole pine stands were clear-cut and/or thinned within 1-2 years of each other). I queried the U.S. Forest Service R2VEG GIS database using the criteria listed above to initially develop a suite of potential sample stands. I further narrowed this suite after obtaining updated standlevel information from local USFS personnel (Art Haines, Silviculturalist, USFS Gunnison Ranger District, personal communication). Finally, I ground-truthed potential stands and qualitatively assessed their representativeness and similarity to other potential replicates. Given the numerous constraints imposed, very few stands met all criteria. Thus, I was unable to randomly select sample stands from a population of suitable stands. Rather, I subjectively chose the “best” stands from among the handful that met my criteria. Small lodgepole stands rarely occur on the landscape in patches large enough to fit a full 42 �7 x 12 trapping grid. To accommodate this, I sampled 6 replicate small lodgepole stands (rather than 3) using 6 x 7 trapping grids (1/2 size). METHODS Experimental Design/Procedures Variables.--The response variables of interest for this project include stand-specific snowshoe hare density (D), apparent survival (φ), recruitment (f), finite population growth rate (λ), and a metric of seasonal movement. Density is the number of hares per unit area and will be estimated using a variety of conventional techniques as well as a rigorous method that incorporates radio telemetry. The standspecific demographic parameters will be estimated primarily from capture-mark-recapture methods. As such, apparent survival is defined as the probability that a marked animal alive and in the population at time i survives and is in the population at time i + 1. Apparent survival encompasses losses due to both death and emigration. Recruitment is the number of new animals in the population at time i + 1 per animal in the population at time i. New recruits can arise from on-site reproduction as well as immigration. The finite population growth rate is the number of animals in a given age class at time i + 1 divided by the number present at time i. Shifts in home range will be assessed by comparing the seasonal proportion of telemetry locations in deciduous habitats using multi-response permutation procedures (MRPP; Zimmerman et al. 1985, White and Garrott 1990). Potential explanatory variables for snowshoe hare density, demographics, and movement include general species composition and structural stage of each stand in which response variables are measured. Additionally, stem density, horizontal cover, and canopy cover (to a lesser extent) are highly correlated with snowshoe hare abundance and habitat use (Wolfe et al. 1982, Litvaitis et al. 1985, Hodges 2000, Zahratka 2004, Miller 2005). Thus, I will further characterize vegetation in each stand by measuring stem density by size class (1-7 cm, 7.1-10 cm, and >10 cm), percent canopy cover, percent horizontal cover of understory and basal area. Basal area is an easily obtainable metric that may be correlated with the other variables and is recorded routinely during timber cruises, whereas the others are not. Thus, it might prove a useful link for biologists designing management strategies for snowshoe hare. Additionally, I will record physical covariates such as ambient temperature, precipitation, and snow depth at each stand during sampling periods as well as precipitation 1-3 years prior to sampling. Finally, I will calculate potentially important landscape metrics such as patch size and level of fragmentation. Sampling.--All trapping and handling procedures have been approved by the Colorado State University Animal Care and Use Committee and filed with the Colorado Division of Wildlife. Snowshoe hares breed synchronously and generally exhibit 2 birth pulses in Colorado (although in some years, some individuals may have 3 litters), with the first pulse terminating approximately June 5−20 and the second approximately July 15–25 (Dolbeer 1972). To obtain a maximum density estimate, I began data collection on the first suite of sites immediately following the second birth pulse in late July. Along with a crew of 5 technicians, I deployed one 7 × 12 trapping grid (50-m spacing between traps; grid covers 16.5 ha) in the large spruce/fir and medium lodgepole stands within the first suite, along with 2 6 × 7 grids in 2 small lodgepole stands. Grid set up and trap deployment followed Griffin (2004) and Zahratka (2004). Grid locations and orientation within each stand were chosen subjectively to accommodate logistical constraints and to ensure that hares using the grid had ample opportunity to use adjacent riparian willow zones. Traps were deployed in all 4 stands in a single day. As traps are deployed, they were locked open and “pre-baited” with apple slices and commercial rabbit chow. During winter, hay cubes were added to traps as well (see Discussion). On days 2-4, the crew continued pre-baiting, replacing apples and rabbit chow as necessary. The purpose of this extended pre-baiting was to maximize capture rates when trapping began. This minimized the number of trap-nights needed to capture the desired number of animals which in turn minimized trapping-related stress as well as the likelihood that 43 �American marten (Martes americana) keyed into trap lines and preyed on entrapped hares, as has occurred in previous studies (J. Zahratka, personal communication). During pilot work in winter 2005, I observed low but increasing capture rates (<0.20) during the first 3 nights of trapping, with higher, more stable capture probabilities after 3 days (approximately 0.35–0.45). Thus 3 days of pre-baiting seems reasonable. Traps were set on the afternoon of the 4th day and checked early each morning and again in the evening on days 5–9. By checking traps in both morning and evening I prevent hares from being entrapped >13 hours, which should minimize capture stress. A crew of 2 people worked together on each grid to check traps and process captures as quickly as possible. All captured hares were coaxed out of the trap and into a dark handling bag by blowing quick shots of air on them from behind. Hares remained in the handling bag, physically restrained with their eyes covered, for the entire handling process. Each individual was aged, sexed, marked with a passive integrated transponder (PIT) tag and temporary ear mark (to track PIT tag retention), then released. Aging consisted of assigning each individual as either juvenile (<1 year old, <1000 g) or adult (≥1 year old, ≥1000 g) based on weight. This criterion is accurate through the end of September at which point juveniles are difficult to distinguish from adults (K. Hodges, University of British Columbia; P. Griffin, University of Montana, personal communication). After the first day of trapping, all captured hares were scanned for a PIT tag prior to any handling and those already marked were recorded and immediately released. Traps and bait were completely removed from the grid on day 10. In addition to PIT tags and ear marks, I radio collared up to 10 hares captured on each grid with a 28-g mortality-sensing transmitter (BioTrack, LTD) to facilitate unbiased density estimation as well as assessment of seasonal movements. I expected heterogeneity in snowshoe hare movements and use of the grid area, with potential bias surfacing due to location at which a hare is captured (e.g., hares captured on the edge of a grid may use the grid area differently than those captured at the center), and differential behavioral responses to trapping (e.g., young individuals may have lower capture probabilities and thus may be more likely to be captured on later occasions). To guard against the first potential bias, I randomly selected a starting trap location each morning and ran the grid systematically from that point. Thus, the first several hares encountered (and collared) were as likely to be from the inner part of the grid as from the edge. To protect against the second potential source of bias, I refrained from deploying the final 3 collars until days 4 and 5 of the trapping session. Immediately following the removal of traps, the field crew began work locating each radiocollared hare 1–2 times per day for 10 days. Most locations were obtained by triangulation from relatively close proximity, but some were obtained by “homing” on a signal (Samuel and Fuller 1996, Griffin 2004) taking care not to push hares while approaching them. Because hares are largely nocturnal (Keith 1964, Mech et al. 1966, Foresman and Pearson 1999), I made an effort to conduct telemetry work at various times of the night (safety and logistics permitting) and day to gather a representative sample of locations for each hare. The crew gathered telemetry locations for radio-collared hares on the initial sites for 8 to 10 days. Then the 10−day trapping procedure and 8 to 10−day telemetry work were repeated on the 3 grids comprising suite 2 (Figure 3). The cycle was repeated once more for grids in suite 3 (Figure 3). The entire process was repeated during the winter when densities should have been at a minimum. In summary, for any given 9-week sampling period, I collected data from 12 total grids, 1 spruce/fir, 1 medium lodgepole, and 2 small lodgepole across 3 replicates. Sampling will occur during 2 such 9-week periods each year − once in late summer and once in late winter – and will continue for 3 years. During the interim between intensive trapping and telemetry work, monthly telemetry checks were conducted from the air to track mortalities and facilitate retrieval of collars from dead hares. Telemetry 44 �work was also occur during “pre-baiting” days after the initial summer sampling session to determine which hares were still alive and immediately available to be sampled by the grid during the ensuing trapping period. Vegetation sampling at each stand will follow protocols established through previous snowshoe hare and lynx work in Colorado (Zahratka 2004, T. Shenk, Colorado Division of Wildlife, personal communication). Specifically, on each of the 12 live-trapping grids, I will lay out 5 × 5 grids (3-m spacing) of vegetation sampling points centered on 15 of the 84 trap locations (Figure 4; 9 points will be sampled on each of the ½-sized small lodgepole stands). At each of the 25 vegetation sampling points, I will record: 1) distance to the nearest woody stem 1.0−7.0 cm, 7.1−10.0 cm, and >10.0 cm in diameter at heights of 0.1 m and 1.0 m above the ground (to capture both summer [0.1 m] and winter [1.0 m] stem density; Barbour et al. 1999), 2) horizontal cover in 0.5-m increments above the ground up to 2 m (Nudds 1977), and 3) canopy cover [present or absent] using a densitometer. Additionally, at the center of all 15 vegetation sampling grid points (i.e., at the trap location), I will measure basal area using an angle gauge. These measurements will be gathered once at the start of the project, unless conditions change due to disturbance such as fire. Temperature will be monitored hourly at each grid during the 6-week intensive sampling periods using data loggers. During winter sampling periods, snow depth measurements will be recorded daily at the same 15 trap locations used to quantify the vegetative attributes of that stand. Data Analysis Density.--I assumed that hare populations were demographically and geographically closed during the short 5-day mark-recapture sampling periods. To obtain a density estimate for each grid, I used the Huggins closed capture model (Huggins 1989, 1991) in Program MARK (White and Burnham 1999) with some modifications. The basic Huggins estimator (no individual covariates) is based on the fact that if pj is the probability that a hare in the population is captured (and marked) for the first time on trapping occasion j, then p * = 1 − (1 − p1 )...(1 − p5 ) is the probability that an individual is captured at least once during a 5-day trapping period (i.e., j = 1,…,5). Accordingly, the basic Huggins estimator for population size, N̂ , is Nˆ = M t +1 / p* where M t +1 is the total number of hares captured. The estimator can be re-written to allow each of the M t +1 individuals captured to have their own p*. In that case, M t +1 Nˆ = ∑1 / pi* . Presumably hares that reside near the edge of a grid encounter fewer traps and are less i =1 likely to be captured than hares residing near the center of a grid. To account for this, I took advantage of the Huggins model with individual covariates to model p* by using the logit link function of program MARK to model pi* as a function of di, where di is distance from the edge of the grid for hare i based on mean capture coordinates. A naïve density estimate for each grid would then be Dˆ = Nˆ / A where A is the area of the grid. However, this gives full credit to all hares, even those whose home range only partially overlaps the grid, which results in a density estimate that is biased high. To correct for this bias, I determined the proportion, ( ~ pk ), of telemetry locations for each of the k = 1,…,10 radio-collared hares that fell within the “naïve grid area.” By incorporating data from multiple grids, a logistic regression model was developed to estimate p% i for all M t +1 animals captured on a grid based on distance from the edge of the grid for hare i (di). Replacing the numerator (i.e., 1) in the Huggins estimator with ( p% i ), gives ⎛ M t +1 ⎞ ~ p / p ⎟ A. ⎟ ⎜∑ a density estimate, Dˆ = ⎜ ⎝ i =1 i * i ⎠ The above-stated approach assumes that radio-collared hares neither gravitate toward nor avoid the former grid area after the 5 days of trapping, 10–20 locations per hare is enough to provide a 45 �reasonable representation of the proportion of time they spend on the grid, and their use of the grid area is representative of other hares that were captured but not collared (i.e., that the logistic regression model of p% i is a useful model). I contend that this type of estimate from grid-based trapping can be construed as a relatively unbiased estimate of density. Using these point estimates and their associated confidence intervals, I compared hare density among seasons and stand types. I will also compare these “true” density estimates to those that would have been obtained using other available methods such as ½ mean maximum distance moved (Wilson and Anderson 1985, Williams et al. 2002:314-315), full mean maximum distance moved (Parmenter et al. 2003), ½ trap interval (Parmenter et al. 2003), “nested grids” (White et al. 1982:120-131), and Program DENSITY (Efford et al. 2004). Demography.--I will analyze mark-recapture data using Pradel temporal symmetry models (Pradel 1996, Nichols and Hines 2002) in a robust design framework (Williams et al. 2002:523-554), which will be available in Program MARK by summer 2006. Thus, I will treat summer and winter sampling occasions as primary periods, and the 5-day trapping sessions within each as secondary periods. The Pradel temporal symmetry models employ both forward and reverse-time evaluation of capture histories to provide estimates of apparent survival ( φ̂ ) and seniority ( γ̂ ). Apparent survival, φi, is the probability that a marked animal alive and in the population at time i survives and is in the population at time i + 1. The seniority parameter, γi , is the reverse-time analogue of survival. Reading backward through a capture history, it is the probability that a marked animal alive and in the population at time i was alive and in the sampled population at time i − 1. If N is the number of animals present in the population, N i φi ≈ N i +1γ i +1 and N i +1 / N i = φi / γ i +1 = λ i . Also, if fi is recruitment rate, or the number of recruits at time i + 1 per animal present at time i, then N i +1 = N i φi + N i f i . Rearranging and substituting into the previous equation gives f i = φi (1/ γ i − 1) . Thus, using Pradel models, one can estimate recruitment and finite population growth rate in addition to survival (Pradel 1996, Nichols and Hines 2002). I will use Akaike’s Information Criterion corrected for small sample size (AICc; Burnham and Anderson 1998) to determine whether models with time-dependent parameters or constant parameters are best supported by the data. I will derive estimates of the above-mentioned parameters from the best model or from model averaging. I anticipate pooling capture data across sites to obtain φˆ i , λˆ i , and fˆi for each stand type for each interval between primary sampling periods (5 estimates of each). I also anticipate simply estimating these parameters for “generic hares”, treating both juveniles and adults as a single group or age class. Given that juveniles are morphometrically indistinguishable from adults by their first fall of life (K. Hodges, University of British Columbia; P. Griffin, University of Montana, personal communication), adult and juvenile survival rates are similar (Griffin 2004), and there is little evidence for age-specific differences in pregnancy rates or litter size (Dolbeer 1972), this approach seems justified. However, if I happen to capture sufficient numbers of juveniles and adults, the design I have laid out here allows for treating the age classes separately. This, in turn, may permit me to decompose the contribution that fi makes to λi into the portion of that contribution due to on-site reproduction and that due to immigration (Nichols et al. 2000). Similarly, it may also be possible using my telemetry data to decompose apparent survival, φi , into emigration and mortality. Such fortuitous situations would facilitate the identification of source and sink habitats if they exist. Seasonal Movements.--I will assess whether snowshoe hares seasonally shift their home ranges using the multi-response permutation procedure (MRPP; Zimmerman et al. 1985, White and Garrott 1990:134-135). Under this approach, telemetry locations are grouped by season (summer and winter), and an MRPP statistic is calculated as the weighted average of the distance between all possible pairs of locations within groups compared to the average distance between all possible pairs ignoring groups. The 46 �null hypothesis is that the distribution of locations is the same for both groups (seasons). Sufficiently small values of the test statistic suggest that within group distances are smaller than distances measured ignoring groups, which is evidence against the null in favor of a group (seasonal) effect. P-values are obtained by calculating the percentile of the observed test statistic relative to all possible test statistics that could be computed by re-arranging the data into all possible groups of 2. The MRPP procedure is sensitive and can detect even small changes in use of an area (White and Garrott 1990:136). I propose a priori that changes in proportional use of deciduous habitats <0.10 in magnitude are unlikely to be biologically significant. Vegetation.--I will calculate mean stem density, horizontal cover, canopy cover, and basal area for each season−stand type as well as temperature, precipitation, snow depth information, and landscape metrics. These will be entered into the MARK design matrix as covariates to population size (~density) and survival in a random effects analysis. As such, I will be able to quantify the amount of variation in population size or survival that is due to differences in vegetation, landscape, or weather relative to the amount left to other causes. Sample size.--I conducted power analyses to determine the probability of discerning meaningful differences in density and survival for hares occupying different stand types. For density, I postulated that foraging lynx likely do not discriminate among stands that differ by only a few hares. However, it seems probable that if hare density in one stand is twice that of another, a lynx would choose the former given the opportunity. Thus, I conducted power calculations to determine the probability of distinguishing differences in densities between 2 stand types in which one had twice the density of hares as the second. Specifically, using the Huggins closed capture model (Huggins 1989, Huggins 1991) in Program MARK, I specified the number of hares (N) present in each of 2 groups (i.e., 2 stand types), allowed capture (p) and recapture (c) probabilities to vary with time but constrained them to be equal and the same for each group, then simulated this scenario 1000 times for a range of realistic capture probabilities. For each simulation I calculated a 95% confidence interval for the mean difference in N̂ between the 2 groups and determined the proportion of all simulations in which this confidence interval did not include zero. This proportion is the power, or probability of discerning a difference between the 2 groups when one actually exists. I compared 2-fold differences in density at the low (5 vs. 10 hares/grid) and high (15 vs. 30 hares/grid) end of the range of hare numbers and I expect to observe (Zahratka 2004). I also simulated the power to detect differences between 17 and 39 hares/grid, corresponding to recently published cut-points for low and high hare densities in the context of lynx conservation (Mills et al. 2005). Given capture/recapture probabilities I observed during winter 2005 (approximately 0.35–0.45), I expect to have reasonable power to detect 2-fold differences in density even if I encounter relatively few hares per grid (Figure 5). I conducted power analyses for survival in a similar manner using the Huggins estimator (Huggins 1989, Huggins 1991) in a robust design framework (Williams et al. 2002:524-556). For this analysis, I specified 3 primary periods (e.g., 3 years) with 5 secondary occasions for each. I established either 30 or 45 hares in each of 2 groups (i.e., pooled an expected 10-15 hares/grid across the 3 grids in a given habitat type), specified a different survival rate for each, and allowed p and c to vary with time but constrained them to be equal and the same for each group as before. I then specified a general model that assumed survival rates varied among groups and a second, reduced model that assumed survival rates were the same for each group. After 1000 simulations under a given scenario of hare numbers, capture probabilities, and survival rates, I conducted a likelihood ratio test between each pair of general and reduced models. As before, I used the proportion of significant tests as an estimate of power to detect differences in survival. 47 �I compared survival rates of 0.4 vs. 0.5, 0.3 vs. 0.5, and 0.2 vs. 0.5. These rates span the range of annual hare survival rates reported in the literature (Dolbeer 1972, Dolbeer and Clark 1975, Griffin 2004). Also, because each comparison is anchored at 0.5, these calculations provide a conservative estimate of power due to the nature of binomial probabilities. That is, I would be more likely to distinguish the difference between 0.1 and 0.2 than between 0.4 and 0.5 even though the difference in both cases is 0.1 because the sampling variance of the estimate for the same sample size is maximal at 0.5 and declines to 0 for survival rates of 0 or 1. Results indicate that I have ≥80% chance of discerning real differences in survival of ≥0.3 (Figure 6), but only 40-65% chance (depending on number of hares captured) of detecting a difference of 0.2, and very little chance of detecting differences smaller than 0.2. However, I plan to combine my telemetry data with my trapping data in the MARK Robust design model using separate groups for each data type. This should enhance my precision and power, thus making the prospect of detecting differences as small as 0.2 a possibility. To complete a power analysis for λ̂ requires running simulations of Pradel models in a robust design framework. This capability is not yet available in Program MARK, so such an analysis has not been completed. Sampling 15 vegetation plots per trapping grid provided reasonably precise characterizations of similar stands in similar locations during a previous study (Zahratka 2004). I trust this level of sampling will be adequate for the present study as well. If not, more plots can be established at a later date given that vegetative characteristics are unlikely to change appreciably over a few years. RESULTS AND DISCUSSION Much of the analysis presented above is not possible or meaningful without several seasons of data, especially the survival, recruitment, and growth rate models. Below, I present a basic summary, relevant observations, and initial density estimates from the inaugural year of this project. I captured 75 hares 166 times during July-September 2006. I captured 99 hares 243 times during January-March 2007 (Table 1). Fourteen of these individuals were captured during both the summer and winter sampling sessions. During summer, I captured over twice as many individuals in small lodgepole stands as in spruce/fir. I captured only a few individuals in medium lodgepole stands. During winter, captures were more evenly distributed among the stands (Table 1). During the initial trapping session of the summer trapping period, 6 hares were captured, handled, and released (seemingly without harm) but were found dead in traps 1-3 days later. I collected the carcasses and submitted them for necropsy. Cause of death was attributed to capture myopathy, which is relatively common in lagomorphs (Laurie Baeten DVM, and Lisa Wolfe DVM, Colorado Division of Wildlife, personal communication). I subsequently altered my trapping protocol to further minimize both the amount of time a hare could be entrapped as well as the handling time at each capture. No trap deaths occurred during the remainder of the sampling season aside from 4 hares that succumbed to predation while inside traps. During the initial 2 trapping sessions of the winter trapping period, 6 more hares were captured, handled, and released multiple times, again with seemingly little adverse reaction, only to be found dead on a subsequent trapping occasion. Several more hares died during the 10-day telemetry session immediately following trapping. These “telemetry deaths” could have been due to natural causes, effects of capture, or a combination of both. Again, carcasses were submitted for necropsy, and again capture myopathy was cited as a potential cause of death. Further examination of the data indicated that hares trapped ≥3 days in a row were much more likely to die in a trap or during telemetry than other hares. Thus, I further modified the trapping protocol by locking traps open on day 3 of the 5-day trapping period so that hares could not be trapped more than 2 days in a row. Additionally, I began providing hay cubes 48 �in the traps as roughage to complement the high quality alfalfa pellets and apples. After implementing these changes, I did not observe any further trap-deaths or telemetry-deaths for the rest of the season. I averaged 9.9 and 6.3 locations per radio-tagged hare during the summer and winter sampling sessions, respectively (Table 2). Thus, “proportion of time on grid,” which is critical to my density estimation procedure, was based on relatively few points per individual for the first 2 sampling periods, and I was unable to attain my goal of 10-20 locations per individual. Following the winter field season, I conducted a series of simulations to examine the effects of sample size on precision of density estimates. I found that 1) the variability between hares (“proportion on grid” ranges from 0.00-1.00) overwhelms the variability within hares (i.e., the binomial variance for proportion of time on grid for any single individual, which decreases as number of locations increases), and 2) given a fixed effort, the variance of the density estimate is minimized by increasing the number of individuals collared as opposed to increasing the number of locations per individual. Thus, it is better to radio-tag more hares and get fewer locations than to tag fewer hares and get more locations. I will continue to deploy as many collars as possible, and will strive for 10-20 locations per individual, but the level of sampling achieved during the first 2 field seasons appears sufficient to detect the large differences in density that occur on the landscape. During summer, density estimates followed hypotheses 1) and 2) above. Specifically, hare density in small lodgepole stands was twice that observed in spruce/fir, which was more than twice that observed in medium lodgepole stands (Figure 7). However, even the relatively high density found in the small lodgepole stands was relatively low compared to densities that have been reported in other parts of hare range (Griffin 2004, Hodges 2000). However, different methods for computing density make this type of comparison difficult. During winter, hare densities remained the same in spruce/fir stands. Hare density in medium lodgpole stands more than doubled, although still remained relatively low compared to other stand types. Density in the small lodgepole stands dropped significantly compared to summer levels and was more variable among replicates. Hare density is likely driven by availability of food and cover. I submit that the interplay between food, cover, and snow depth provides a plausible explanation for the density patterns observed during the first year of this study. Spruce/fir stands probably provide adequate access to both necessities during both summer and winter due to their uneven-aged, multi-layered structure. Medium lodgepole stands, on the other hand, apparently provide very little forage/cover for hares during summer as the canopy in these stands is generally ≥1 meter off the ground. However, in winter, accumulated snow may bring that canopy back into reach for hares. Conversely, small lodgepole stands provided abundant food and cover during summer, but accumulated snow during winter brings hares closer to the crowns of the young trees, which then provide less cover. SUMMARY • The number of snowshoe hares captured, the number of captures, and the number of locations obtained per hare during the first year appeared adequate for attaining the objectives of this study. • Some deaths due to capture myopathy (most likely cause) occurred during initial trapping periods in each sampling season. Changes to the trapping protocol, trapping schedule, and bait provided seem to have alleviated the problem. • Snowshoe hare densities during summer were highest in small lodgepole stands, followed by large spruce/fir and medium lodgepole. During winter, densities in small lodgepole stands dropped and became more variable across replicates. Medium lodgepole stands gained hares. Spruce/fir stands remained at the same density as during summer. 49 �ACKNOWLEDGEMENTS Ken Wilson (CSU), Bill Romme (CSU), Paul Doherty (CSU), Dave Freddy (CDOW), Chad Bishop (CDOW), and Paul Lukacs (CDOW) provided helpful insight on the design of this study. We appreciate the invaluable logistical support provided by Mike Jackson (USFS), Jake Spritzer (USFS), Margie Michaels (CDOW), Gabriele Engler (CSU), Brandon Diamond (CDOW), Chris Parmeter (CDOW), Kathaleen Crane (CDOW), Lisa Wolfe (CDOW), and Laurie Baeten (CDOW). The following hardy individuals collected the hard-won data presented in this report: Braden Burkholder, Matt Cuzzocreo, Brian Gerber, Belita Marine, Adam Behney, Pete Lundberg, Katie Yale, Britta Schielke, Cory VanStratt, Mike Watrobka, Meredith Goss, Sidra Blake, Keith Rutz, Rob Saltmarsh, Jennie Sinclair, and Evan Wilson. Funding was provided by the Colorado Division of Wildlife. LITERATURE CITED AUBRY, K. B., G. M. KOEHLER, AND J. R. SQUIRES. 2000. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. 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Snowshoe hare cover relationships in northern Utah. Journal of Wildlife Management 46:662-670. WOLFF, J. O. 1980. The role of habitat patchiness in the population dynamics of snowshoe hares. Ecological Monographs 50:111-130. ZAHRATKA, J. L. 2004. The population and habitat ecology of snowshoe hares (Lepus americanus) in the southern Rocky Mountains. Thesis, The University of Wyoming, Laramie, Wyoming, USA. ZIMMERMAN, G. M., H. GOETZ, AND P. W. JR. MIELKE. 1985. Use of an improved statistical method for group comparisons to study effects of prairie fire. Ecology 66:606-611. Prepared by _________________________________________________ Jacob S. Ivan, Graduate Student, Colorado State University 52 �Table 1. Number of snowshoe hares (Lepus americanus) captured during 5-day trapping sessions conducted during July-September 2006 and January-March 2007 on 3 medium lodgepole, 3 spruce/fir, and 6 small lodgepole stands on the Gunnison National Forest, Taylor Park and Pitkin, Colorado. ____________________________________________________________________________________ Number of Hares Captured (Total Captures) ___________________________________________________________ Summer 2006 Winter 2007 Both Summer and Winter ____________________________________________________________________________________ Medium Lodgepole 3 24 2 Small Lodgepole 50 40 10 Spruce/Fir 22 35 2 ____________________________________________________________________________________ Table 2. Number of snowshoe hares (Lepus americanus) radio-collared and tracked during 10-day sessions immediately following 5-day trapping periods July-September 2006 and January-March 2007 on the Gunnison National Forest, Taylor Park and Pitkin, Colorado. ____________________________________________________________________________________ Summer 2006 Winter 2007 ____________________________________________________________________________________ Number of Hares Collared 41 79 Number of Locations 407 510 Number of Locations/Hare 9.9 6.5 ____________________________________________________________________________________ Figure 1. Purported high quality snowshoe hare habitat in Colorado. From left to right: small lodgepole pine, medium lodgepole pine, and large Engelmann spruce/subalpine fir. 53 �Figure 2. Study area near Taylor Park and Pitkin, Colorado including medium lodgepole (squares), small lodgepole (circles), and spruce/fir (triangles) stands selected for mark-recapture sampling. 54 �Jul Aug Sep 1 Jan 1 2 3 4 2 3 4 5 6 7 8 5 6 7 8 9 10 11 9 10 11 12 13 14 15 12 13 14 15 16 17 18 16 17 18 19 20 21 22 19 20 21 22 23 24 25 23 24 25 26 27 28 29 26 27 28 29 30 31 1 30 31 1 2 3 4 5 2 3 4 5 6 7 8 Feb 6 7 8 9 10 11 12 9 10 11 12 13 14 15 13 14 15 16 17 18 19 16 17 18 19 20 21 22 20 21 22 23 24 25 26 23 24 25 26 27 28 1 27 28 29 30 31 1 2 2 3 4 5 6 7 8 3 4 5 6 7 8 9 9 10 11 12 13 14 15 10 11 12 13 14 15 16 16 17 18 19 20 21 22 17 18 19 20 21 22 23 23 24 25 26 27 28 29 24 25 26 27 28 29 30 30 31 Mar Figure 3. Approximate annual data collection schedule for trapping (�) and telemetry (�). Dates and weeks will change depending on calendar year and pay schedule. During telemetry work, the 6-person crew will be divided into 2 teams, only one of which will be working at any given time. Monthly locations on radio-collared hares will also be collected in the interim between the intensive sampling periods indicated here. Figure 4. 15 trap locations (•) on 7 × 12 trapping grid where vegetation will be sampled by measuring stem density horizontal cover, and canopy cover at the 25 points on each 5 × 5 subgrid (inset). In addition, basal area will be measured at the trap location (�) on which each of the 15 subgrids are centered. 55 �Density Power Analysis % Non-overlapping 95% CIs 100 90 80 70 60 50 40 30 20 10 0.60 0.55 0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0 capture/recapture probability N=5 vs. N=10 N=15 vs. N=30 N=17 vs. N=39 Figure 5. Power for distinguishing differences in snowshoe hare density between 2 habitat types when a difference actually exists. Gray area indicates the capture probability realized by the 3rd day of trapping during a pilot study in winter 2005. N indicates number of hares per grid, a range of roughly 0.1 (N = 5) to 0.7 hares/ha (N = 39). Survival Power Analysis (N = 45) 100 100 90 80 90 80 % Significant LR Tests 70 60 50 40 30 20 10 0 70 60 50 40 30 20 Capture/Recapture Probability 0.2 vs. 0.5 0.3 vs. 0.5 0.60 0.55 0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.10 0.60 0.55 0.50 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 10 0 0.15 % Significant LR Tests Survival Power Analysis (N = 30) Capture/Recapture Probability 0.4 vs. 0.5 0.2 vs. 0.5 0.3 vs. 0.5 0.4 vs. 0.5 Figure 6. Power, or probability of distinguishing differences in snowshoe hare survival between 2 habitat types when differences actually exist. N = 30 (left) and N = 45 (right) correspond to reasonable estimates of the number of hares I expect to capture in each habitat type. Gray area indicates the capture probability realized by the 3rd day of trapping during a pilot study in winter 2005. 56 �Figure 7. Snowshoe hare density and 95% confidence intervals in 3 types of stands in central Colorado as determined by mark-recapture with telemetry augmentation, July-September 2006 and January-March 2007. 57 �58 �Colorado Division of Wildlife July 2006 − June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 4 Federal Aid Project: W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Effect of Nutrition and Habitat Enhancements on Mule Deer Recruitment and Survival Rates : Period Covered: July 1, 2006 − June 30, 2007 Authors: C. J. Bishop, G. C. White, D. J. Freddy, and B. E. Watkins All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We measured mule deer (Odocoileus hemionus) population parameters in response to a nutrition enhancement treatment to evaluate the relative importance of habitat quality as a limiting factor of mule deer in western Colorado during November 2000 – January 2005. The nutrition enhancement treatment increased survival of fetuses to the yearling age class by 0.14−0.20 depending on year and fawn sex, although 95% confidence intervals slightly overlapped 0. The nutrition treatment also had a positive effect on annual adult doe survival. Survival of does receiving the treatment (Ŝ = 0.879, SE = 0.0206) was higher than survival of control does (Ŝ = 0.833, SE = 0.0253). Our estimate of the population rate of change, λ̂ , was 1.15−1.17 for treatment deer and 1.02−1.06 for control deer, with some overlap in 95% confidence intervals. The treatment caused λ̂ to increase by 0.139 (95% CI: −0.0152, 0.2941) during 2001−02, 0.113 (95% CI: −0.0009, 0.2279) during 2002−03, and 0.145 (95% CI: 0.0176, 0.2723) during 2003−04.Our results provide a foundation for focusing deer management efforts on improving habitat quality in western Colorado pinyon-juniper (Pinus edulis-Juniperus osteosperma) ecosystems with corresponding research efforts to quantify the effects of habitat manipulations on deer performance. During the past year, we had 2 papers published in peer-reviewed journals, we completed final data analyses, and we prepared 3 other manuscripts for publication. The published manuscripts included: 1) a manuscript on the effectiveness of vaginal implant transmitters (Journal of Wildlife Management 71(3):945−954), and 2) a manuscript documenting malignant catarrhal fever in the Uncompahgre deer population (Journal of Wildlife Diseases 43(3):533−537). We also completed a publication on mule deer habitat guidelines for the Colorado Plateau ecoregion, which will be published by the Western Association of Fish and Wildlife Agencies. The estimated publication date is January 2008. 59 �WILDLIFE RESEARCH REPORT EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES CHAD J. BISHOP, GARY C. WHITE, DAVID J. FREDDY, AND BRUCE E. WATKINS P. N. OBJECTIVE To determine experimentally whether enhancing mule deer nutrition during winter and early spring via supplementation increases fetal survival, neonatal survival, overwinter fawn survival, or ultimately, population productivity. SEGMENT OBJECTIVES 1. Complete final data analyses to support preparation of manuscripts. 2. Prepare manuscripts for submission to scientific journals for publication. 3. Complete dissertation as part of PhD requirements at Colorado State University INTRODUCTION Mule deer (Odocoileus hemionus) numbers apparently declined during the 1990s throughout much of the West, and have clearly decreased since the peak population levels documented during the 1940s−1960s (Unsworth et al. 1999, Gill et al. 2001). Biologists and sportsmen alike have concerns as to what factors may be responsible for declining population trends. Although previous and current research indicates multiple interacting factors are responsible, habitat and predation have typically received the focus of attention. A number of studies have evaluated whether predator control increases deer survival, yet results are highly variable (Connolly 1981, Ballard et al. 2001). Together, predator control studies with adequate rigor and statistical power indicate predation effects on mule deer are variable as a result of time-specific and site-specific factors. Studies which have demonstrated deer population responses to predator control treatments have failed to determine whether predation is ultimately more limiting than habitat when considering long term population changes. Numerous research studies have evaluated mule deer habitat quality, but virtually no studies have documented population responses to habitat improvements. In many areas where declining deer numbers are of concern, predation is common yet habitat quality appears to have declined. The question remains as to whether predation, habitat, or some other factor is more limiting to mule deer in these situations, and whether habitat quality can be improved for the benefit of deer. It may also be that no single factor is responsible for observed deer declines, and a more comprehensive understanding of multi-factor interactions is needed. We designed and implemented a field experiment where we measured deer population responses to a nutrition enhancement treatment to further understand the causative factors underlying observed deer population dynamics. We conducted the study on the Uncompahgre Plateau in southwest Colorado, where several predator species were present in abundant numbers: coyotes (Canis latrans), mountain lions (Felis concolor), and bears (Ursus americanus). In addition to predation, myriad diseases in combination have proximately affected survival of the Uncompahgre deer population (Pojar and Bowden 2004, B. E. Watkins, Colorado Division of Wildlife, unpublished data). Predator numbers were not manipulated in any manner during the course of the study. All factors were left constant with the exception of deer nutrition. Deer nutrition was enhanced by providing supplemental feed to deer occupying a treatment area during winter. We measured December fawn recruitment and overwinter fawn survival in response to the treatment to determine whether deer nutrition was ultimately more limiting than predation or disease. A second phase of research was initiated in 2005 to quantify deer population 60 �parameters in response to manipulations of pinyon-juniper (Pinus edulis-Juniperus osteosperma) habitat (Bergman et al. 2006). The objective of this research is to determine whether habitat can be effectively improved for mule deer by introducing disturbance into late-seral pinyon-juniper stands. STUDY AREA We non-randomly selected two experimental units (A−B) within mule deer winter range on the Uncompahgre Plateau (Figure 1) to facilitate a cross-over experimental design for evaluating the effects of enhanced deer nutrition during winter on annual population performance. Unit A received a nutrition enhancement treatment during the first 2 winters of research (2000 – 2002) while Unit B served as a control unit. During winters 2002−03 and 2003−04, Unit B received the treatment while Unit A served as the control. In late April and May, prior to fawning, deer from the winter range experimental units migrated to summer range. We defined the summer range study area by movements of the radio-collared deer captured on winter range; summer range encompassed >1000 mi2 covering the southern portion of the Uncompahgre Plateau and adjacent San Juan Mountains (Figure 2). Winter range elevations ranged from 1830 m (6000 ft) in Shavano Valley to 2318 m (7600 ft) adjacent to the Dry Creek Rim above Shavano Valley. Winter range habitat was dominated by pinyon-juniper with interspersed sagebrush adjacent to agricultural fields in the Shavano and Uncompahgre Valleys. Summer range elevations occupied by deer ranged from 1891 m (6200 ft) in the Uncompahgre Valley to 3538 m (11,600 ft) in Imogene Basin southwest of Ouray, CO. Summer range habitats were dominated by spruce-subalpine fir (Picea spp.-Abies lasiocarpa), aspen (Populus tremuloides), sagebrush, ponderosa pine (Pinus ponderosa), Gambel oak (Quercus gambelii), and to a lesser extent, pinyon-juniper at lower elevations. Bishop et al. (2005) provide a detailed study area description. METHODS Refer to Bishop et al. (2005) for field methodology employed during 2000−2005. During fiscal year 2006-07, we had 2 papers published in peer reviewed wildlife journals, which were the result of work completed in the previous year. Our primary research efforts were focused on data analysis and the preparation of manuscripts for publication in scientific journals. We spent much of the year evaluating dependence among deer siblings with respect to fetal and neonatal survival analyses. Essentially all statistical analyses are based on an assumption that sample units are independent. In survival analyses, the assumption pertains to independence of fates. That is, we must assume that the death or survival of one sample unit is not related to the fate of another. Predation and maternal condition are both good examples of mechanisms that could cause sibling neonates to lack independent fates. If a coyote or bear kills twin fawns because both were together, clearly those mortality events were not independent. Similarly, a lack of independence would occur if twin fawns each die of starvation because their dam is in poor condition. Data are considered overdispersed when the independence assumption is violated. Overdispersion does not generally affect point estimates, but rather causes variances to be underestimated. We estimated overdispersion in fetal and neonatal survival datasets and incorporated a data bootstrap procedure into Program MARK (White and Burnham 1999), making it easier for others to conduct similar analyses. The procedure in MARK can be generalized to any situation where multiple individuals are marked from the same litter, clutch, pair, trap site, etc. Once we completed the overdispersion analysis, we spent the remainder of the year conducting final data analyses that quantified the effect of enhanced nutrition on population performance. We then prepared several manuscripts that incorporated the various analyses we conducted. The principal investigator also completed a draft of his PhD dissertation. 61 �RESULTS AND DISCUSSION A comprehensive presentation and discussion of preliminary results was provided by Bishop et al. (2005). These results have not changed and therefore we do not repeat them here. The final results are contained in peer-reviewed manuscripts that have either already been published or will be submitted for publication in 2007 or early 2008. The following manuscripts were published in 2007 (abstracts are provided in Appendix I): Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. . Schultheiss, P. C., H. Van Campen, T. R. Spraker, C. J. Bishop, L. L. Wolfe, and B. Podell. 2007. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer in Colorado. Journal of Wildlife Diseases 43:533−537. The following book chapter was completed should be published by January 2008: Watkins, B. E., C. J. Bishop, E. J. Bergman, A. Bronson, B. Hale, B. F. Wakeling, L. H. Carpenter., and D. W. Lutz. 2007. Habitat guidelines for mule deer: Colorado Plateau shrubland and forest ecoregion. Mule Deer Working Group, Western Association of Fish and Wildlife Agencies. The following draft manuscripts were prepared in 2007 and will be submitted for publication in 2007 or early 2008 (abstracts are provided in Appendix II): Bishop, C. J., G. C. White, and P. M. Lukacs. In review. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. In review. Effect of enhanced nutrition on mule deer population performance. Journal of Wildlife Management OR Wildlife Monographs. Bishop, C. J., B. E. Watkins, L. L. Wolfe, D. J. Freddy, and G. C. White. In review. Evaluating mule deer body condition during late winter using serum thyroid hormone concentrations. Journal of Wildlife Management. The following draft dissertation was prepared in 2007 and submitted for review at Colorado State University (abstract is provided in Appendix III): Bishop, C. J. In review. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. We intend to pursue several additional manuscripts as time allows, listed below in order of priority. 1. Evaluating dependence of fates among mule deer siblings in Colorado, Idaho, and Montana. Journal of Wildlife Management. 2. Bovine viral diarrhea isolation and seroprevalence in a free-ranging mule deer (Odocoileus hemionus) population in southwest Colorado. Journal of Wildlife Diseases. 3. Spatial patterns in mortality causes of neonatal mule deer across a land use gradient in southwest Colorado. Journal of Wildlife Management. 62 �4. Evaluation of mule deer age and sex ratios as a response variable in field research. Journal of Wildlife Management. SUMMARY Enhanced winter nutrition of free-ranging deer caused an increase in both fetus-neonate survival and overwinter fawn survival, resulting in higher yearling recruitment. Overwinter adult doe survival increased as a result of the treatment, and therefore annual survival was higher among treatment than control adult does. Combining all parameter estimates into a deterministic population model, the treatment population indicated an exceptionally high rate of increase while the control population was stable and indicative of the overall Uncompahgre deer population during 2000−2004. The nutrition enhancement treatment was artificial in the sense that we applied it only to test whether habitat quality was ultimately more limiting than predation or other factors. Our results to do not provide support for managing deer populations with nutrition supplements because our treatment delivery approach could not be applied to a large number of animals over a large area. Rather, our results provide a foundation for focusing deer management efforts on improving habitat quality in western Colorado pinyon-juniper ecosystems with corresponding research efforts to quantify the effects of habitat manipulations on deer. We are presently in the process of conducting final data analyses and preparing and submitting manuscripts for publication in scientific journals. LITERATURE CITED BALLARD, W. B., D. LUTZ, T. W. KEEGAN, L. H. CARPENTER, AND J. C. DEVOS, JR. 2001. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin 29:99−115. BERGMAN, E. J., C. J. BISHOP, D. J. FREDDY, AND G. C. WHITE. 2006. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Federal Aid in Wildlife Restoration Project W−185−R, Job Progress Report. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. BISHOP, C. J., G. C. WHITE, D. J. FREDDY, AND B. E. WATKINS. 2005. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Federal Aid in Wildlife Restoration Project W−185−R, Job Progress Report. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. CONNOLLY, G. E. 1981. Limiting factors and population regulation. Pages 245−285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. GILL, R. B., T. D. I. BECK, C. J. BISHOP, D. J. FREDDY, N. T. HOBBS, R. H. KAHN, M. W. MILLER, T. M. POJAR, AND G. C. WHITE. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Denver, USA. POJAR, T. M., AND D. C. BOWDEN. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. UNSWORTH, J. W., D. F. PAC, G. C. WHITE, AND R. M. BARTMANN. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315−326. Prepared by _______________________ Chad J. Bishop, Wildlife Researcher 63 �Year Unit A Unit B 2000-01 Treatment Control 2001-02 Treatment Control 2002-03 Control Treatment 2003-04 Control Treatment Figure 1. Schematic representation of experimental units and nutrition enhancement treatment allocation. Units A and B were located in winter range habitat on the Uncompahgre Plateau in southwest Colorado. The nutrition enhancement cross-over design encompassed 4 years. Uncompahgre Plateau Mesa County GRAND JUNCTION Delta County m co Un GMU 62 r hg pa e Shavano E.U. u ea at Pl Montrose County GMU 61 Sanmiguel County Gunnison County DELTA Winter Range Exp. Units MONTROSE Colona Montrose County Summer Range E.U. Ouray County Figure 2. Location of Colona and Shavano (Units A and B) experimental units on the Uncompahgre Plateau, southwest Colorado; and location of the summer range study area encompassing the southern Uncompahgre Plateau and adjacent San Juan Mountains. 64 �APPENDIX I The following manuscript (referenced here by Abstract) was published in the Journal of Wildlife Management in 2007. USING VAGINAL IMPLANT TRANSMITTERS TO AID IN CAPTURE OF MULE DEER NEONATES CHAD J. BISHOP, DAVID J. FREDDY, GARY C. WHITE, BRUCE E. WATKINS, THOMAS R. STEPHENSON, AND LISA L. WOLFE ABSTRACT Estimating survival of the offspring of marked female ungulates has proven difficult in freeranging populations yet could improve our understanding of factors that limit populations. We evaluated the feasibility and efficiency of capturing large samples (i.e., >80/year) of neonate mule deer (Odocoileus hemionus) exclusively from free-ranging, marked adult does using vaginal implant transmitters (VITs, n = 154) and repeated locations of radio-collared does without VITs. We also evaluated the effectiveness of VITs, when used in conjunction with in utero fetal counts, for obtaining direct estimates of fetal survival. During 2003 and 2004, after we placed VIT batteries on a 12-hour duty cycle to lower electronic failure rates, the proportion that shed ≤3 days prepartum or during parturition was 0.623 (SE = 0.0456), and the proportion of VITs shed only during parturition was 0.447 (SE = 0.0468). Our neonate capture success rate was 0.880 (SE = 0.0359) from does with VITs shed ≤3 days prepartum or during parturition and 0.307 (SE = 0.0235) from radio-collared does without VITs or whose implants failed to function properly. Using a combination of techniques, we captured 275 neonates and found 21 stillborns during 2002−2004. We accounted for all fetuses at birth (i.e., live or stillborn) from 78 of the 147 does (0.531, SE = 0.0413) having winter fetal counts, and this rate was heavily dependent on VIT retention success. Deer that shed VITs prepartum were larger than deer that retained VITs to parturition, indicating a need to develop variable-sized VITs that may be fitted individually to deer in the field. We demonstrated that direct estimates of fetal and neonatal survival may be obtained from previously marked female mule deer in free-ranging populations, thus expanding opportunities for conducting field experiments. Survival estimates using VITs lacked bias that is typically associated with other neonate capture techniques. However, current vaginal implant failure rates, and overall expense, limit broad applicability of the technique. Citation: Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. 65 �The following manuscript (referenced here by Abstract) was published in the Journal of Wildlife Diseases in 2007: MALIGNANT CATARRHAL FEVER ASSOCIATED WITH OVINE HERPESVIRUS-2 IN FREERANGING MULE DEER IN COLORADO PATRICIA C. SCHULTHEISS, HANA VAN CAMPEN, TERRY R. SPRAKER, CHAD J. BISHOP, LISA L. WOLFE, AND BRENDAN PODELL ABSTRACT Malignant catarrhal fever (MCF) was diagnosed in 4 free-ranging mule deer (Odocoileus hemionus) in January and February of 2003. Diagnosis was based on typical histologic lesions of lymphocytic vasculitis and PCR identification of ovine herpesvirus-2 (OHV-2) viral genetic sequences in formalin fixed tissues. The animals were from the Uncompahgre Plateau of southwestern Colorado. Deer from these herds occasionally resided in close proximity to domestic sheep (Ovis aries), the reservoir host of OHV-2, in agricultural valleys adjacent to their winter range. These cases indicate that fatal OHV-2 associated MCF can occur in free-ranging mule deer exposed to domestic sheep that overlap their range. Citation: Schultheiss, P. C., H. Van Campen, T. R. Spraker, C. J. Bishop, L. L. Wolfe, and B. Podell. 2007. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer in Colorado. Journal of Wildlife Diseases 43:533−537. 66 �APPENDIX II The following draft manuscripts (referenced here by Abstract) were prepared in 2007 and will be submitted to the Journal of Wildlife Management. EVALUATING DEPENDENCE AMONG MULE DEER SIBLINGS IN FETAL AND NEONATAL SURVIVAL ANALYSES CHAD J. BISHOP, GARY C. WHITE, AND PAUL M. LUKACS ABSTRACT The assumption of independent sample units is potentially violated in deer (Odocoileus spp.) fetal and neonatal survival analyses where twin and triplet siblings comprise a high proportion of the sample. Violation of the independence assumption causes sample data to be overdispersed relative to a binomial model, and therefore requires a variance inflation factor, c, to obtain appropriate estimates of sampling variances. We evaluated overdispersion in fetal and neonatal mule deer (O. hemionus) datasets where more than half of the sample units were comprised of siblings. We developed a likelihood function for estimating fetal survival when the fates of some fetuses are unknown, and we used several variations of the binomial model to estimate neonatal survival. We compared theoretical variance estimates obtained from these analyses with empirical variance estimates obtained from data bootstrap analyses to estimate the overdisperion parameter, c. Our estimates of c for fetal survival ranged from 0.678 to 1.118, which provided virtually no evidence of overdispersion. For neonatal survival, 3 different models indicated that ĉ ranged from 1.1 to 1.4 and averaged 1.24−1.26, providing evidence of limited overdispersion (i.e., limited sibling dependence). Our results indicate that fates of sibling mule deer fetuses and neonates may often be independent even though they have the same dam. Predation tends to act independently on sibling neonates because of dam-neonate behavioral adaptations, although we observed several cases of a predator(s) killing siblings. The effect of maternal characteristics on sibling fate dependence is less straightforward and may vary by circumstance. We recommend that future neonatal survival studies incorporate additional sampling intensity to accommodate modest overdispersion (i.e., ĉ = 1.25), which would facilitate a corresponding ĉ adjustment in a model selection analysis using quasi-likelihood without a reduction in power. 67 �EFFECT OF ENHANCED NUTRITION ON MULE DEER POPULATION PERFORMANCE CHAD J. BISHOP, GARY C. WHITE, DAVID J. FREDDY, BRUCE E. WATKINS, AND THOMAS R. STEPHENSON ABSTRACT Concerns over declining mule deer (Odocoileus hemionus) populations during the 1990s prompted research efforts to identify and understand key limiting factors of deer. Similar to past deer declines, a top priority of state wildlife agencies was to evaluate the relative importance of habitat and predation. We therefore evaluated the effect of enhanced nutrition of deer during winter and spring on fecundity and survival rates using a field experiment involving free-ranging mule deer on the Uncompahgre Plateau in southwest Colorado. The nutrition enhancement treatment represented an instantaneous increase in nutritional carrying capacity of a pinyon (Pinus edulis) and Utah juniper (Juniperus osteosperma) winter range, and was intended to simulate optimum habitat quality. Prior studies on the Uncompahgre Plateau indicated predation and disease were the most common proximate causes of deer mortality. By manipulating nutrition and leaving predation as it was, we determined whether habitat quality was ultimately a critical limiting factor of the deer population. We measured fetal, neonatal, and overwinter fawn survival, and annual adult doe survival, which we then used to estimate population rate of change as a function of enhanced nutrition. Pregnancy and fetal rates were high for all deer, regardless of the nutrition treatment. Fetal and neonatal survival rates were higher among deer that received the nutrition enhancement treatment than deer that served as experimental controls. Overwinter fawn survival was considerably higher among treatment deer than control deer. Overwinter survival increased by 0.16−0.31 depending on year and fawn sex, and none of the 95% confidence intervals associated with the effect overlapped 0. The nutrition enhancement treatment increased survival of fetuses to the yearling age class by 0.14−0.20 depending on year and fawn sex, although 95% confidence intervals slightly overlapped 0. The nutrition treatment also had a positive effect on annual adult doe survival. Survival of does receiving the treatment (Ŝ = 0.879, SE = 0.0206) was higher than survival of control does (Ŝ = 0.833, SE = 0.0253). Our estimate of the population rate of change, λ̂ , was 1.15−1.17 for treatment deer and 1.02−1.06 for control deer, with some overlap in 95% confidence intervals. The treatment caused λ̂ to increase by 0.139 (95% CI: −0.0152, 0.2941) during 2001−02, 0.113 (95% CI: −0.0009, 0.2279) during 2002−03, and 0.145 (95% CI: 0.0176, 0.2723) during 2003−04. We documented density dependence in the Uncompahgre deer population because survival of fawns and does increased considerably in response to enhanced nutrition. We found strong evidence that coyote (Canis latrans) predation of ≥6 month old fawns and adult does was compensatory. Our results demonstrate that observed coyote predation is not useful for evaluating whether coyotes are negatively impacting a deer population. We also found evidence that mountain lion (Puma concolor) predation was compensatory. Disease was not compensatory among adult does. We found that winter range habitat quality was a limiting factor of the Uncompahgre Plateau deer population. We recommend the implementation and evaluation of habitat treatments designed to set back succession and increase productivity of late-seral pinyon-juniper habitats that presently dominate the landscape because of the absence of fire. 68 �EVALUATING MULE DEER BODY CONDITION DURING LATE WINTER USING SERUM THYROID HORMONE CONCENTRATIONS CHAD J. BISHOP, BRUCE E. WATKINS, LISA L. WOLFE, DAVID J. FREDDY, AND GARY C. WHITE ABSTRACT Body condition of ungulates is ultimately a determinant of fecundity and survival rates. Researchers have recently developed ultrasonography and body condition scoring techniques that allow reliable estimation of body fat in several ungulate species, but the approach is not feasible to employ in all circumstances, particularly in routine population monitoring programs. There remains a need for a reliable blood chemistry index that could be used to assess relative condition of different deer populations or groups. We evaluated the relationship between estimated body fat of free-ranging mule deer and serum concentrations of total thyroxine (T4), total triiodothyronine (T3), free T4 (FT4), and free T3 (FT3), during late February−early March in southwest Colorado. Deer body fat varied widely because we imposed a nutrition treatment on one-half of our sample. Concentrations of T4 and FT4 were 48.23 nmol/l (SE = 3.88) and 12.69 pmol/l (SE = 1.12) higher, respectively, in deer that received the nutrition treatment than deer that did not receive the treatment. Our optimal model of estimated body fat included T4, T42, FT4 and deer chest girth (%Fât = –4.8015 – 0.0946×T4 + 0.000603×T42 + 0.1474×FT4 + 0.1426×chest girth, r2 = 0.609). Ultrasound and body condition scoring should be used to estimate body fat whenever possible. However, in cases where only a blood sample can be obtained, we documented the potential utility of T4 and FT4 during late winter for evaluating relative body condition of mule deer. 69 �APPENDIX III The following draft dissertation (referenced here by Abstract) was prepared in 2007 and will be submitted to Colorado State University. EFFECT OF ENHANCED NUTRITION DURING WINTER ON THE UNCOMPAHGRE PLATEAU MULE DEER POPULATION CHAD J. BISHOP ABSTRACT Mule deer (Odocoileus hemionus) populations declined across much of the West during the 1990s, prompting state wildlife agencies to pursue explorations of mule deer limiting factors. The greatest concern of agencies and sportsmen was whether declining habitat quality or predation was ultimately responsible for the observed declines. In Colorado, the Uncompahgre Plateau mule deer population received the most attention, having substantially declined from the 1980s through the late 1990s. Biologists hypothesized that poor winter range habitat quality was the primary cause of the observed decline. In contrast, many of the Colorado Division of Wildlife’s (CDOW) external constituents hypothesized that high rates of predation were keeping the mule deer herd below nutritional carrying capacity. The habitat quality hypothesis indicated CDOW should pursue habitat improvements in the pinyon (Pinus edulis) and juniper (Juniperus osteosperma) winter range, whereas the predator hypothesis suggested CDOW should pursue efforts to reduce predator populations, particularly coyote (Canis latrans) populations. The competing hypotheses represented very different paradigms of population limitation. I therefore evaluated the effect of enhanced nutrition during winter on the Uncompahgre deer population as a way to evaluate the importance of habitat quality versus that of predation. I conducted a field study incorporating a crossover experimental design to quantify the effect of enhanced nutrition on fetal, neonatal, overwinter fawn, and annual adult doe survival rates. I captured and radio-collared samples of deer in 2 experimental units (EUs) on winter range. I delivered the nutrition treatment to deer occupying one EU (treatment) and did not administer the treatment to deer in the other EU (control). Established field techniques were not sufficient to allow me to quantify the effect of the treatment on fetal and neonatal survival. I therefore pursued an exploration of vaginal implant transmitters as a mechanism to capture necessary samples of newborn fawns on summer range exclusively from radio-collared does that occupied the winter range EUs (Chapter 1). This effort allowed me to estimate fetal and neonatal survival as a function of the treatment. In broad terms, I demonstrated that direct estimates of fetal and neonatal survival may be obtained from previously marked female mule deer in free-ranging populations, thus expanding opportunities for conducting field experiments. I encountered additional challenges with estimation of fetal and neonatal survival. First, I was unable to determine the fate of all fetuses that I documented in utero. I therefore developed a likelihood function for estimating fetal survival when the fates of some fetuses are unknown (Chapter 2). Second, a majority of my fetal and neonatal samples were comprised of siblings, indicating my data were potentially overdispersed. Overdispersion causes sample variances to be underestimated and requires a variance inflation factor, c. To estimate c, I compared theoretical variance estimates with empirical variance estimates obtained from data bootstrap analyses (Chapter 2). I found little evidence of overdispersion in my fetal survival data, and I found modest overdispersion in my neonatal sample data (ĉ = 1.25). Although some overdispersion was detected, my result indicated that fates of sibling mule deer neonates may often be independent even though they have the same dam and use the environment similarly. I discuss reasons for this in Chapter 2. 70 �After resolving issues with fetal and neonatal survival estimation, I quantified the effect of the nutrition enhancement treatment on fetal, neonatal, overwinter fawn, and annual adult doe survival (Chapter 3). I then used these parameter estimates, along with estimated fecundity rates, in an agestructured, deterministic population model to estimate the effect of the treatment on the population rate of change, λ. The treatment caused λ̂ to increase by an average of 0.133 (SD = 0.0168) during the 3 years of my study. I documented density dependence in the Uncompahgre deer population because survival of fawns and does increased considerably in response to enhanced nutrition. I found strong evidence that coyote predation of ≥6-month-old fawns and adult does was compensatory. Finally, I found that winter range habitat quality was a limiting factor of the Uncompahgre Plateau deer population. I completed my principal study objectives in the first 3 chapters of the dissertation. However, my research afforded the opportunity to evaluate the utility of serum thyroid hormones in mule deer as an index to body condition (Chapter 4). Concentrations of total thyroxine (T4) and free T4 (FT4) were substantially higher in treatment deer than control deer. I also found that serum thyroid hormones were highly correlated with estimated body fat in mule deer during late winter. Concentrations of T4 and FT4 could be useful for evaluating relative condition of different deer groups or populations, and for roughly estimating body fat of individual animals during late winter. n summary, I demonstrated that winter range habitat quality was ultimately limiting the Uncompahgre mule deer population. Observed predation was primarily compensatory, particularly of ≥6month-old fawns and adult does. My findings indicate that CDOW should implement and evaluate habitat treatments in late-seral pinyon-juniper habitat as a means to increase habitat productivity for mule deer. My findings provide no support for predator reduction programs. 71 �72 �Colorado Division of Wildlife July 2006 – June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 2 Federal Aid Project W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Evaluation of Winter Range Habitat Treatments on Over-Winter Survival and Body Condition of Mule Deer. : Period Covered: July 1, 2006 - June 30, 2007 Author: E.J. Bergman; project cooperators, C.J. Bishop, D.J. Freddy and G.C. White Personnel: C. Anderson, L. Baeten, D. Baker, B. Banulis, J. Boss, A. Cline, D. Coven, M. Cowardin, K. Crane, R. Del Piccolo, B. deVergie, B. Diamond, K. Duckett, S. Duckett, D. Hale, C. Harty, A. Holland, E. Joyce, R. Lockwood, D. Lucchesi, D. Masden, J. McMillan, M. Michaels, G. Miller, M. Miller, M. Sirochman, T. Sirochman, R. Swygman, C. Tucker, D. Walsh, S. Waters, B. Watkins, P. Will, L. Wolfe, K. Yeager, M. Zeaman CDOW, L. Carpenter - Wildlife Management Institute, D. Felix, L. Felix - Olathe Spray Service, P. Johnston, M. Keech, R. Swisher, S. Swisher - Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We completed the second year of a multi-year, multi-area study to assess the impacts of landscape level winter range habitat improvement efforts on mule deer population performance. This study is occurring on the Uncompahgre Plateau and in adjacent valleys in southwestern Colorado. Data collection and analysis for this second year were consistent with that of the pilot study and first year of the study. We measured over-winter fawn survival and total deer density on 4 annual study areas, as well as on a fifth variable area that had previously not been involved in the study. Additionally, on 2 of the study areas we estimated body condition of does. Compared to results from other research throughout the west, as well as on the Uncompahgre Plateau, survival estimates for 6-month old mule deer fawns were highly variable between areas, but tended to be above average (mean survival rate of 0.76 (0.04 SE)). Preliminary evidence suggests that areas that have received habitat treatments have higher survival. However, based on estimates of total body fat for adult female deer, there was no apparent distinction between treatment and reference study areas. Point estimates of deer density on the 5 study areas during the winter of 2006-2007 were consistent with those colleted during the winter of 2005-2006. Attempts to refine and improve the precision of density estimates between the two winters were marginally successful and will be further refined during the next year of data collection. During the 2006-2007 winter, we also initiated a pilot study concerning elk spatial use as it relates to competition with deer as well as predatorprey dynamics. Due to the timing of the study, these data have will not be retrieved from elk GPS collars until fall 2007. 73 �WILDLIFE RESEARCH REPORT EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER ERIC J. BERGMAN P.N. OBJECTIVE To experimentally assess whether mechanical/chemical treatments of native habitat vegetation will increase over-winter mule deer fawn survival, adult doe body condition, and localized deer densities on Uncompahgre Plateau in southwest Colorado. SEGMENT OBJECTIVES 1. Capture and radio-collar the minimum necessary sample (n=25) of 6 month-old fawns during November through early January in each of 5 study areas. 2. Measure over-winter fawn survival from mid-December through mid-June. 3. Estimate late-winter deer densities in each study area via helicopter resighting of marked deer. 4. Capture and sample a minimum number of adult female deer (n=30) to estimate late-winter body condition in 2 study areas. 5. Capture and radio-collar 10 adult female elk with GPS or VHF collars. INTRODUCTION A common trend among many terrestrial, mammalian systems is a tendency to cycle between population highs and lows (Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001, Clutton-Brock and Pemberton 2004). While the true cause of these cycles is likely a merger of habitat quality, weather, disease, predation, sport hunting, competition and community population dynamics, it is often necessary or intriguing for wildlife managers and ecologists to identify the primary limiting factor to population growth. Without exception, mule deer populations have also demonstrated a tendency to show large fluctuations. Several dramatic declines have been observed since the turn of the 19th century (Connolly 1981, Gill 2001, Hurley and Zager 2004). However, only one period of increase, a general trend during the 1940's and 1950's, has been noted. The most recent and pressing decline took place during the 1990's (Unsworth et al. 1999). Colorado has not escaped these tendencies, with certain parts of the state experiencing population declines by as much as 50% between the 1960's and present time (Gill 2001, B. Watkins personal communication). Primarily due to the value of mule deer as a big game hunting species, wildlife managers' challenges are two-fold: understanding the underlying causes of mule deer population change and managing populations to dampen the effects of these fluctuations. In Colorado, the role of habitat as the limiting factor for mule deer populations was recently tested. Specifically, the role of forage quality and quantity on over-winter fawn survival was tested using a treatment/reference cross-over design with ad libitum pelleted food supplements as a substitute for instantaneous high quality habitat improvements (Bishop et al. 2004). The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e. if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the primary limiting factor on populations. As such, preliminary evidence suggests that nutrition enhancement treatments increased fawn survival by as much as 20% (C.J. Bishop, personal communication). This research effectively identified some of the underlying processes in mule deer population regulation, but did not test the effectiveness of acceptable habitat management techniques. Due to the undesirable effects of feeding wildlife (e.g. artificially 74 �elevating density, increased potential for disease transmission and cost), a more appropriate technique for achieving a high quality nutrition enhancement needs to be assessed. Based on this past research and the above mentioned objectives, we designed and initiated a multi-year, multi-area study to assess the impacts of landscape level winter range treatments on mule deer population performance. This study is being conducted on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado. Due to the active habitat treatment history in this area, the Uncompahgre Plateau stood out as the most opportune place for addressing these issues. Additionally, there are several tracts from 2 state wildlife areas that are located in key locations, thereby allowing additional habitat treatments to occur on the level and schedule necessary of this project. To assess the impacts of habitat treatments on mule deer in these areas, we are measuring over-winter fawn survival, mule deer density and late winter body condition. In addition to the above mentioned objectives, the opportunity to explore deer/elk interactions, as well as predator-prey dynamics is available in our study areas. As part of a pilot study to assess these interactions, we distributed elk GPS collars across the south end of the Uncompahgre Plateau where the density of radio-marked deer and mountain lions is highest (for further details on this pilot work, see Appendix I). Preliminary data will give basic information regarding elk distribution throughout the year, which can then be compared to similar data for deer and the spatial distribution of mountain lion kill sites. STUDY AREA At the onset of this study (Bergman et al. 2005), we identified 2 pairs of treatment/reference study areas, stratified into historically known high and low deer density areas. The selection process for these pairs of experimental units followed several strict guidelines: 1) Treatment/reference units could not be further than 10km apart, but needed to have adequate buffer to minimize the movement of animals between the treatment and reference areas. 2) Reference study areas could not have received any mechanical treatment during the past 30 years. 3) Strata were defined by winter range type (all experimental units had to be in pinyon/juniper winter range) and deer density. 4) Treatment units needed to have received mechanical treatment in the past, but also had to be capable of receiving further treatments during the study period. Each winter a 5th study area is added to increase the level of inference that can be drawn from this study. For each of the 4 winters that will cover the study period, this 5th study area shifts between 4 randomly selected areas. The treatment history on each of these additional study areas varies, but is representative of what can be expected of typical winter-range treatments. During the second winter of this study, this 5th study area fell on the Colona Tract (~5km2) of Billy Creek State Wildlife Area (approximately 15km south of Montrose, CO). The treatment history of Colona Tract is primarily composed of brush mowing and chemical control of weeds and dry land fertilization of preferred species. The high density treatment area is located on the Billy Creek tract of Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). The high density reference area is located around Beaton Creek (approximately 15km south of Montrose, CO and approximately 5km north of Billy Creek State Wildlife Area). Both of the high density study areas are located in GMU 65 (DAU D-40). The low density treatment area is located on Peach Orchard Point, on/near Escalante State Wildlife Area (approximately 25km southwest of Delta, CO). The low density reference area is located on Sowbelly and Tatum draws (approximately 25km west of Delta, CO and approximately 8km from Peach Orchard Point). Both of the low density study areas are located in GMU 62 (DAU D-19). Shavano Valley was also located in GMU 62 (DAU D-19) to the west of Montrose, CO. 75 �METHODS Twenty-five mule deer fawns were captured and radio-collared in each of the 5 study areas. Fawns were captured via baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) and helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) between mid-November and lateDecember. Ten adult female elk were captured via helicopter net-gunning during this same period. Fawns were fitted with radio collars made of vinyl belting and equipped with mortality sensors, which after remaining motionless for 4 hours, increase the pulse rate of received signals. To make fawn collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars after approximately 6 months. Elk were collared with either permanent VHF collars or temporary GPS collars that were fitted with timed blow-off devices. On a daily basis, from December through May, we monitored the radioed fawns in order to document live/death status. This allowed us to determine accurately the date of death and estimate the proximate cause of death. Daily monitoring was done from the ground to maximize efficient collection of mortalities and assessment of cause specific mortality. Weekly aerial telemetry flights were conducted to insure that all deer were heard at least once a week, allowing weekly survival estimates for each study area. Additionally, throughout the winter field season and as part of a related pilot field study, investigations of mountain lion GPS clusters were conducted (see Appendix I for details). To estimate body composition, an additional 30 adult female deer were captured via helicopter net-gunning and fitted with temporary radio-collars, also having mortality sensors, in late-February within each of the 2 high density study areas. For body condition work, we relied on methods that employed the use of ultrasonography to estimate total body fat (Stephenson et al. 1998, Cook 2000, Stephenson et al. 2002). Blood samples were also collected for endocrinology and pregnancy tests. During late winter (early-March) we estimated deer density on each of our study areas. Helicopter based mark-resight techniques were used for density estimation (Gill 1969, Bartmann et al. 1986, Kufeld et al. 1980, Freddy et al. 2004). Preliminary survival analyses were conducted on the first two years of data. In addition to including individual covariates (fawn sex and mass), we explored the role of habitat treatment history on survival. Due to the preliminary nature of these analyses and the ongoing status of the habitat treatment work, we did not attempt to rank individual study areas. Rather, our analyses were conducted such that areas were included and compared using three different approaches. With the first approach, areas were included individually and a unique survival rate was calculated for each area. The second approach allowed for 3 levels of habitat treatment intensity (untreated, single treatment or ongoing treatments). The final approach did not attempt to segregate treated areas by treatment history. Rather, any area with any treatment history was treated similarly, resulting in a unique survival rates being calculated for untreated (reference) areas and a different, unique survival rate being calculated for all other areas. All survival models were conducted in program MARK (White and Burnham 1999). Known-fate models were tested using the logit link function. All models are compared using Akaike's Information Criterion corrected for small sample size (Burnham and Anderson 2003). RESULTS AND DISCUSSION Minimum necessary sample sizes were met in all study areas for all components of this research (n = 25 fawns per area for survival work, n = 30 adult females in two areas for body condition 76 �assessment, n=10 adult female elk for pilot data collection). Capture related mortalities occurred on 1 of 186 occasions (0.5%, 1 fawn). Two fawns died of unknown causes within 1week of capture and were censored from the survival analysis. Mean mass of all fawns was 36.5 kg (Table. 1). Estimates of fawn survival collected during this study have been above average compared to results from other research throughout the west, as well as on the Uncompahgre Plateau. Across our 5 study areas, estimated survival rates ranged between 0.63 (0.10 SE) and 0.92 (0.05 SE), with mean survival rate of 0.76 (0.04 SE) (Table 2). While these rates are lower than those measured during the 2005-2006 winter, they remain higher than long term averages reported in the literature (Unsworth et al. 1999). Of particular note, survival rates in our low-density study areas have been exceptionally high during each winter of this study. Based on historical climate trends across the Uncompahgre Plateau, it is apparent that the stratification of treatment/reference study areas by density also captured a regional effect of climatic variation on over-winter fawn survival. Preliminary survival models indicate that the individual parameter most influencing over-winter fawn survival continues to be fawn mass (Table 3). Of particular interest to this study, however, is that incorporation of treatment history into model structure improved performance beyond that of models that only incorporate individual covariates. While ∆AICc scores reflect minimal differentiation between models that incorporate treatment history under different strategies, ∆AICc scores for models that do not include treatment history and estimate survival rates for each individual area are noticeably higher. When categorized by treatment intensity, 6 study areas are split into 3 categories. When categorized as treatment/reference, 6 study areas are split into 2 categories. Yearly effects on survival rates appear to have no meaningful contribution to model performance. While model results indicate that habitat treatments have a positive influence on survival, standard errors for parameter estimates remain high, effectively dampening any conclusions that can be drawn This is an artifact of the preliminary nature of these analyses and is ultimately linked to having collected only half of the necessary data. As the study progresses and more study areas are included, a treatment intensity effect is likely to be detected if it exists. Late winter body condition estimates for adult females during the winter of 2006-2007 were again higher than those collected during previous winters on the Uncompahgre Plateau (Bishop et al. 2004 and C.J. Bishop, personal communication). However, based on estimates of total body fat, there was no apparent distinction between our study areas. This apparent lack of distinction was also present in the levels of the T3 and T4 hormone (nmol/l) observed between study areas (Table 4). Differences in pregnancy rates, based on PSPB, between study areas were not observed. Overall, pregnancy rates were high in both study areas (Billy Creek = 27/30, Buckhorn = 25/28). Titers for BT and EHD were observed at low/moderate rates in Billy Creek (BT = 4/21, EHD = 2/21). Samples were not collected at Buckhorn. During the 2006-2007 winter, efforts were made to improve precision within our density estimation techniques. Specifically, the number of helicopter resight surveys was increased and attempts were made to increase the total number of marks in the population via temporary marking with paint pellets. It was found that marking deer with pellets during the time period of our flights (late-March) was not a viable mechanism for increasing the number of marks in the population. On 5 markings attempts, which accounted for 90 hours of effort, no deer were successfully marked. The lack of success in these attempts was primarily attributed to our inability to get deer to respond to bait sites due to increasing availability of new natural forage. To be successfully marked, deer needed to be hit with 5-10 pellets on the dorsal region of their body. In order to successfully mark deer with this many pellets, deer needed to be within a 50-80 foot range. During early-winter months (late-November through early-January), it is not difficult to bring large groups of deer within this range as natural food resources are typically restricted by snow cover. However, during late-winter months natural food resources such as grass and browse species were becoming increasingly available. In contrast to this, the number of helicopter resight 77 �flights was increased by 2 on all study areas. Comparison of precision for density estimates between 2005-2006 and 2006-2007 showed an overall improvement during the second winter (i.e. range of 95% confidence intervals were reduced) by 31%-35% via increasing the number of resight occasions (Figure 1). However, while not quantifiable, it is believed that further increasing the number of resight occasions would likely not result in substantial further improvements. The use of helicopter resights as a density estimation technique is dependent on the behavior that deer exhibit as a helicopter flies overhead. Sightability of deer is greatly improved by deer movement. With the addition of more flights during this past winter, deer appeared to adapt a behavioral strategy of standing under trees rather than running. While this behavior cannot be quantified, if actually occurring, it introduces bias into the data collection technique. As such, we conclude that increasing the number of resight occasions can improve precision, but there is a point of diminishing returns that can quickly be surpassed as deer grow accustomed to helicopter disturbance. Due to the timing of the pilot work on elk distribution, and to the timing of the elk GPS collar release mechanisms, elk location data will not be collected and analyzed until fall of 2007. Also due to timing of pilot work on predator/prey interactions, analysis of mountain lion GPS cluster data will not occur until fall 2007. SUMMARY Survival rates for mule deer fawns across our study areas averaged 76% with a measured high of 92% and measured low of 62%. Overall body condition parameter estimates for late-winter adult female deer were moderate to high, highlighting the general mild winter conditions that were observed throughout deer winter range in southwestern Colorado. Preliminary evidence of higher deer survival in treatment areas was observed, but we do not have enough data to draw strong conclusions at this preliminary stage. Estimates of total deer density across our study areas are in line with historical estimates. Precision of density estimates have improved with modification to techniques and additional years of data collection will be needed to determine if habitat treatment effects can potentially be detected. LITERATURE CITED BARRETT, M.W., J.W. NOLAN, and L.D. ROY. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. BARTMANN, R.M., L.H. CARPENTER, R.A. GARROTT, and D.C. BOWDEN. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. —————, G.C. WHITE, and L.H. CARPENTER. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. BERGMAN, E.J., C.J. BISHOP, D.J. FREDDY, G.C. WHITE. 2005. Pilot evaluation of winter range habitat treatments of mule deer fawn over-winter survival. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. BISHOP, C.J., G.C. WHITE, D. J. FREDDY, and B.E. WATKINS. 2004. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. BURNHAM, K.P. and D.R. ANDERSON. 2003. Model selection and multi-model inference. Springer, New York, USA. CLUTTON-BROCK, T., and J. PEMBERTON, editors. 2004. Soay sheep: dynamics and selection in an island population. Cambridge University Press, UK. CONNOLLY, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. 78 �COOK, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain Elk. Thesis, University of Idaho, Moscow, USA. FREDDY, D.J., G.C. WHITE, M.C. KNEELAND, R.H. KAHN, J.W. UNSWORTH, W.J. DEVERGIE, V.K. GRAHAM, J.H. ELLENBERGER, and C.H. WAGNER. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. GILL, R.B. 1969. A quadrat count system for estimating game populations. Colorado Division of Game, Fish and Parks, Game Information Leaflet 76. Fort Collins, USA. ————— 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. HURLEY, M., and P. ZAGER. 2004. Southeast mule deer ecology - Study I: Influence of predators on mule deer populations. Progress Report, Idaho Department of Fish and Game, Boise, USA. JEDRZEJEWSKA, B., and W. JEDRZEJEWSKI. 1998. Predation in Vertebrate Communities: the Białowieża Primeval Forest as a case study. Springer-Verlag, Berlin, Germany. KREBS, C.J., S. BOUTIN, and R. BOONSTRA, editors. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. KUFELD, R.C., J.H. OLTERMAN, AND D.C. BOWDEN. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. RAMSEY, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. SCHMIDT, R.L., W.H. RUTHERFORD, and F.M. BODENHAM. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. STEPHENSON, T.R., V.C. BLEICH, B.M. PIERCE, and G.P. MULCAHY. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. ————— , T. R., K. J. HUNDERTMARK, C. C. SCHWARTZ, and V. VAN BALLENBERGHE. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717-722. UNSWORTH, J.W., D.F. PAC, G.C. WHITE, and R.M. BARTMANN. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. VAN REENEN, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. __________, and K. P. BURNHAM. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Prepared by Eric J. Bergman, Wildlife Researcher 79 �Table 1. Mean mass (n) and sex of mule deer fawns captured on the Uncompahgre Plateau from lateNovember through early-January of each year, 2005-2006 and 2006-2007. All fawns were captured by baited drop-nets or helicopter net-gunning. Mass is reported in kg. Area Billy Creek Buckhorn Colona Peach Orchard Sowbelly Billy Creek Buckhorn Colona Peach Orchard Sowbelly Year 2005 2005 2005 2005 2005 2006 2006 2006 2006 2006 Male 37.1 (14) 37.4 (11) 39.4 (11) 37.0 (11) 37.1 (16) 38.3 (12) 36.7 (10) 38.1 (12) 37.0 (13) 44.3 (8) Females 32.0 (11) 35.0 (15) 37.2 (14) 35.3 (14) 34.2 (9) 34.4 (12) 34.7 (15) 32.5 (12) 35.5 (12) 35.5 (15) Total 34.9 (25) 36.0 (26) 38.2 (25) 36.1 (25) 36.1 (25) 36.5 (25) 35.5 (25) 35.4 (24) 36.3 (25) 38.7 (25) Table 2. Over-winter mule deer fawn survival rates for study areas across the Uncompahgre Plateau, for both winters of the study. Billy Creek, Peach Orchard, Colona and Shavano represent treatment areas. Buckhorn and Sowbelly are reference areas. Peach Orchard and Sowbelly are considered low-density study areas. Sample size equals 25 fawns in each area. 2005-2006 2006-2007 Area Ŝ (S.E.) Ŝ (S.E.) Billy Creek 0.83 (0.76) 0.72 (0.09) Buckhorn 0.76 (0.88) 0.63 (0.10) Colona N.A. 0.68 (0.09) Shavano 0.76 (0.85) N.A. Peach Orchard 0.88 (0.65) 0.92 (0.05) Sowbelly 1.00 (0.00) 0.88 (0.07) Other 0.83 (.108) N.A. 80 �Table 3. Preliminary survival model results for radio collared fawns on the Uncompahgre Plateau from the winters of 2005-2006 and 2006-2007. Model Treatment Reference + Mass Treatment Reference + Mass + Sex Treatment Type + Mass Treatment Type + Mass + Sex Area + Mass Area + Mass + Sex Area Treatment Reference Treatment Type Area + Year Treatment Reference + Year Treatment Type + Year AICc ΔAICc 544.784 0.00 544.954 0.17 545.592 0.81 545.860 1.08 548.908 4.12 549.877 5.09 555.220 10.44 555.279 10.50 555.615 10.83 555.655 10.87 556.371 11.59 556.426 11.64 ωi 0.294 0.270 0.196 0.172 0.037 0.023 0.002 0.002 0.001 0.001 0.000 0.000 Table 4. Late-winter body condition estimates for female adult mule deer on the Uncompahgre Plateau in 2 study areas each year, 2005-2006 and 2006-2007. Sample sizes were 30 does in each area. Mean T3 and T4 samples are reported in nmol/l. Parameters marked with an asterisk designate a significant difference at the 0.05 level. 2005-2006 2006-2007 Parameter % Body Fat T3* T4 % Body Fat T3 T4 Billy Creek Buckhorn Sowbelly 8.80% (2.02 S.E.) N.A. 9.81% (2.88 S.E.) 1.12 (0.28) N.A. 1.41 (0.51 S.E.) 70.69 (20.94) N.A. 79.97 (15.80 S.E.) 7.61% (1.94 S.E.) 7.03% (1.80 S.E.) N.A. 1.55 (0.53) 1.42 (0.31) N.A. 88.23 (19.53) 78.07 (22.34) N.A. 81 �120 100 Deer / km 2 80 60 40 20 0 Sowbelly Peach Orchard Buckhorn Billy Creek Figure 1. Deer density estimates for the 4 permanent study areas. Dark boxes reflect data from the 2005-2006 winter, white boxes reflect data from the 2006-2007 winter. Error bars represent the 95% confidence intervals for density estimates. 82 �APPENDIX I PROGRAM NARRATIVE PILOT STUDY PLAN FOR MAMMALS RESEARCH FY 2006-07 State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 3 Federal Aid Project No.:W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Pilot Evaluation of Predator-Prey Dynamics on the Uncompahgre Plateau : Pilot Evaluation of Predator-Prey Dynamics on the Uncompahgre Plateau. Principal Investigators Eric J. Bergman, Wildlife Researcher, Mammals Research Mathew W. Alldredge, Wildlife Researcher, Mammals Research Kenneth A. Logan, Wildlife Researcher, Mammals Research Mary Schuette, GIS Specialist, Mammals Research Chad J. Bishop, Wildlife Researcher, Mammals Research David J. Freddy, Mammals Research Leader Cooperators Brad Banulis, Terrestrial Biologist Bruce Watkins, State Big Game Analyst Area 18 Personnel Pilot Study Plan Approval Eric J. Bergman Date: November 2006 Submitted by: Eric J. Bergman Date: November 2006 Reviewed by: Date: Prepared by: Date: Date: Date: Reviewed by: Biometrician Approved by: David J. Freddy Date: Mammals Research Leader 83 November 2006 �PROGRAM NARRATIVE PILOT STUDY PLAN PILOT EVALUATION OF PREDATOR-PREY DYNAMICS ON THE UNCOMPAHGRE PLATEAU. A pilot study proposal submitted by: E.J. Bergman, Colorado Division of Wildlife M. W. Alldredge, Colorado Division of Wildlife K.A. Logan, Colorado Division of Wildlife M. Schuette, Colorado Division of Wildlife C.J. Bishop, Colorado Division of Wildlife D.J. Freddy, Colorado Division of Wildlife NEED Predator prey interactions have always been a topic of keen interest for wildlife managers and ecologists. However, due to the complexities of studying natural systems, behavioral theories pertaining to the subject are often developed in invertebrate, aquatic or small mammal systems, often under controlled laboratory conditions (Mathews et al. 2006, Schmitz 2006, Werner and Peacor 2006). Similarly, many models are developed within theoretical frameworks (Keeling et al. 2000, Mitchell and Lima 2002). While developing theories under these conditions is almost inherently necessary, their subsequent transition to free ranging systems is not frequent (Ryall and Fahrig 2006). Of the free ranging systems where theories are developed and tested, most deal with avian species (Lima and Bednekoff 1999, Roth et al. 2006), where as application to large mammalian systems is less frequent. Of the mammalian predator prey systems that have been studied, most have been conducted in preservation/park settings that largely exclude human influence (Kunkel and Pletscher 1999, Kunkel et al. 1999, Krebs et al. 2001, Creel and Creel 2002, Mao et al. 2005, Wilmers et al. 2006,). Additionally, due to the small number of large scale studies that have been conducted, the ability of managers to draw inference to separate systems (i.e. different species or different ecosystems) is limited. While this existing body of work is invaluable, extrapolation of theories to large mammalian systems could be limited and basing wildlife management decisions on this information may be tenuous. Due to the value of mule deer, elk and mountain lions as recreationally hunted species in Colorado, there is much interest in understanding the nature and relationship between the population dynamics of these species. However, resulting from the dearth of information pertaining to the interactions of these 3 species, a vast array of opinions and theories pertaining to their impacts on each other have been propagated. As a management agency, the Colorado Division of Wildlife is responsible for supporting or refuting claims with biological data that were collected in a scientifically unbiased manner. To date, these data are largely unavailable. Currently, the opportunity to develop a predator prey study exists on the Uncompahgre Plateau in southwestern Colorado. Two large scale research programs, independently studying mountain lion and mule deer, are underway in the same geographic area. Thus, the initial framework to study a top carnivore, and what are thought to be its primary prey species, is in place. However, to date there is little or no information pertaining to elk distribution or population dynamics in this area. The addition of elk spatial data will allow us to assess the feasibility of developing a full study addressing the influence and interactions of mountain lions, mule deer, and elk. 84 �OBJECTIVES The specific objectives for our pilot study are: 1) design and implement a pilot study that assesses mountain lion space use in relation to mule deer and elk distribution, 2) design and implement a sampling protocol that allows estimation of mountain lion use rates of deer and elk, 3) quantify prey selection patterns (number of elk versus number of deer), and 4) evaluate the feasibility of expanding this into a full study. EXPECTED RESULTS As part of the ongoing mountain lion research program, adult mountain lions have been captured and collared with GPS radio collars (Logan 2005). These collars are programmed to attain GPS locations 4 times per day. By design, GPS locations can be remotely downloaded from these radio collars via UHF signal by researchers at any chosen time. Through the investigation of GPS clusters of lion locations, a preliminary assessment of prey selection and ungulate use rates can be made (Anderson 2003, Logan 2005). Additionally, as part of the ongoing mule deer research program, quantification of mule deer survival rates is also being done. With nominal, additional flight time, distributions of radio collared deer can be estimated at bi-weekly intervals. Finally, the addition of 6-12 radio (VHF and GPS) collars on elk will allow us to collect elk group locations and distribution data at the same interval as those collected for mule deer. As a result of simultaneously collecting these data for all three species, we expect to make a preliminary assessment of the basic interaction behaviors of mountain lions and their 2 primary prey species on the Uncompahgre Plateau. Primarily, we expect to estimate kill rates for mountain lions, quantify prey selection behavior in light of prey distribution, and gather information on prey switching behavior by mountain lions. APPROACH Capture and Handling Methods: To date and as part of a completed mule deer study, approximately 150 adult female mule deer are marked with VHF radio collars in the area of interest (Bishop et al. 2005). Additionally, 25 mule deer fawns will be captured and radio-collared within the eastern portion of the study area between late-November and late-December 2006 as part of the ongoing mule deer research (Bergman et al. 2005; capture protocols previously approved by CDOW ACUC). All mule deer were, or will be, captured with baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) or via helicopter net-gunning (Barrett et al. 1982, van Reenen 1982). As part of the ongoing mountain lion research project, 7 mountain lions currently wear GPS collars that allow on-demand interaction with researchers and additional mountain lions will continue to be captured during the identified pilot study period. Mountain lions have and will continue to be captured primarily via pursuit by dogs as well as in live traps (Logan 2005, capture protocols previously approved by CDOW ACUC). As part of this pilot study, adult female elk (6-10) will be captured via helicopter net-gunning (Appendix A) during late-December/January 2006-07 with 6 adult females fitted with drop-off GPS/VHF collars and up to 6 adult females fitted with VHF permanent collars.. Elk will be captured on the eastern portion of the study area, directly overlapping areas including radio collared mule deer and mountain lion. Sample sizes for elk reflect an estimate of what we believe will be an adequate number of elk to provide an initial estimation of elk spatial use in the study area. As preliminary data are collected, future sample sizes will be modified in a full study plan. 85 �Ungulate Survival and Location Monitoring: On a daily basis, from December through May, we will monitor the radioed fawns and adult female deer and elk in order to document live/death status. This will allow us to determine accurately the date of death and estimate the proximate cause of death. For animals not heard from the ground, we will conduct weekly flights to assess live/death status. Additionally, every other week we will collect aerial locations on a random sample of the collared ungulates, allowing us to estimate temporal variation in distribution. Detailed locations of GPS collared elk will not be available until self-actuating mechanisms cause GPS collars to drop-off elk in September 2007. However, during the same bi-weekly monitoring flights, we will attempt to obtain a visual location and approximate group size count for elk groups containing marked elk. This will allow us to collect broad scale group dynamic data for comparison to fine scale spatial data. Identification of Mountain Lion GPS location clusters: Clusters of GPS locations thought to represent lion-killed ungulate sites can be determined subjectively by inspection, or objectively using a standard algorithm to group points together (Anderson and Lindzey 2003). Either approach may be effective at finding puma kill sites, but an objective approach provides a sound sampling frame from which statistical inference can be made about clusters that are not physically investigated. We have chosen to develop an objective clustering routine that will group GPS locations together that are spatially and temporally within a sampling window. The clustering routine is designed to identify clusters in five unique selection sets in order to identify clusters containing two or more points, those that contain missing locations, and those that are represented by single points. The clustering algorithm is written in Visual Basic and is designed to run within ARCGIS (Alldredge and Schuette, CDOW unpubl. data 2006). The widths of the spatial and temporal sampling windows are user specified, in order to meet multiple applications and research needs. This will enable adjustment of the sampling frames to improve cluster specifications as needed. The initial step is to prepare data files for ARCGIS. The main step priority is to number all downloaded GPS lat-long location records consecutively to provide a time stamp that can be used in the program. Failed locations must be numbered within the data files to maintain the proper time step (i.e. two locations that are separated by a missing location must be time stamped in such a way that the clustering algorithm can recognize that a missing location existed between the records). At this point data files can be imported to ARCGIS and coordinates converted to UTMs if necessary. The initial selection set of clusters (S1) is based on clusters consisting of two or more points within a specified distance and time interval. Working with temporal and spatial variables simultaneously is difficult, so we chose to create an association matrix of the combined variables. The units for time are based on GPS locations so that the time between consecutive downloads is one. Lion locations are attempted 4 times a day, so that one day consists of 4 time-steps. The association matrix is then constructed as Aij = ⎛ ti − t j ⎞ ⎜ ⎟ 1 − d max ⎜ tmax ⎟⎠ d ij ⎝ e 1 where Aij is the association in time and space between points i and j, dmax is the maximum distance between two points to be considered a cluster, dij is the distance between points i and j, tmax is the maximum number of time steps between points to be considered in a cluster, and ti and tj are the times for locations i and j. This formula weights the distance between two locations heavier than the time between two locations. It also causes the association Aij to be negative for any locations that are outside the temporal window (separated by more time-steps than tmax). The association between two locations within 86 �the specified time interval will be greatest for those locations that are spatially closer together. So, the largest value in the association matrix will correspond to the 2 points that are spatially the closest and within the time interval. Initially, dmax is set at 200 m and tmax is set at 16 time steps [4 DAYS] . The initial cluster is selected by choosing the 2 points with the largest association value from the association matrix. The distance is checked to verify that the points are within the specified maximum distance, dmax, and if it is, the centroid of the two points is calculated. An association vector Ac is made by calculating the association among the centroid and all other points using the above formula. If all values in Ac are negative, then no points are within the specified time interval, so no additional points can be added to the cluster. Then the greatest association value Acmax is selected from Ac and the distance from the centroid to the point corresponding to Acmax is compared to dmax. If the distance is less than dmax then the point is added to the cluster and a new centroid is calculated using all cluster points and a new vector Ac is constructed using the new centroid. This procedure is repeated until no additional points are added to the cluster because either no points are within the specified time interval or the distance from the centroid to all points is greater than dmax. After each cluster is constructed these points are omitted from the association matrix and a new cluster is started by again selecting the greatest value from the matrix and verifying that the distance between points are less than dmax. Points are again added to this cluster as previously described. This entire procedure is repeated until no 2 locations meet the temporal or spatial criteria. All clusters are given a unique identifier, which is based on the animal identification and the Julian date. This completes the selection set for clusters with two or more locations, which likely have a high probability of being a kill site. Additional selection sets can be constructed from the remaining points as single location clusters. However, not all locations are equal, so the remaining selection sets are created based on whether points are associated with missing locations and based on distance between consecutive locations. The second selection set (S2) of clusters is created from any 2 points that are within a distance dmiss, and are separated by 1 or more missing locations. The cluster is considered to be the area within the distance dmax of each of the known locations (2 areas make up the cluster, and dmiss is initially set at 500 m). The final 2 cluster selection sets consist of consecutive points that are within the ranges dmax to d2 (S3) and d2 to d3 (S4). To construct these selection sets, the distance between consecutive points is examined and if the distance is within the range dmax to d2 (500 m) then the initial point is added as a cluster to the set S3, or if the distance is within the range d2 to d3 (1000 m) then the initial point is added as a cluster to the set S4. These single-point clusters are assumed to have radius dmax. Points not used in selection sets S1 through S4 can then be used in a final selection set S5. These points represent larger movements between consecutive locations and thus are thought to have low probabilities of being associated with a kill site, although these points could be associated with use of small prey items, or kill sites where a lion was physically disturbed away from a kill site. These singlepoint clusters are also assumed to have radius dmax. Sampling of Mountain Lion GPS location clusters: A primary objective of the pilot study is to determine the probability that a given cluster represents a lion feeding site. Specifically, we will evaluate lion feeding sites as a function of the cluster association matrix. Using the clustering algorithm described above, we will attempt to classify each sampled cluster as a lion feeding site (1) or not a feeding site (0). We expect a high proportion of S1 clusters to represent lion feeding sites. Conversely, we expect a 87 �moderate proportion of S2 and S3 clusters, and a low proportion of S4 and S5 clusters, to represent lion feeding sites. A secondary objective of the pilot study is to gather preliminary biological data regarding lion prey utilization, primarily with respect to deer and elk. The secondary objective is most efficiently accomplished by sampling S1 clusters with greater intensity than other clusters. We therefore structured our sampling approach to allow adequate estimation of the proportion of clusters that are lion feeding sites for each cluster set, while more intensively sampling S1 clusters than all others. With no previous evidence to indicate similarities among individuals based on sex, age, or parental status, sampling will be stratified by each individual puma. GPS collars will be downloaded once a month for each lion and data will be analyzed through the clustering algorithm. Clusters within 2 weeks of the download date will be selected for the sampling frame, which will make the maximum time between the predation event and sampling about 1 month by the time field technicians can get to and assess evidence at each cluster site. Clusters will be randomly chosen from each selection set for each individual every month in the following manner: S1 = 2 clusters, S2 = 1 cluster, S3 = 1 cluster, and S4 and S5 = 1 cluster on alternating months. Five clusters will be sampled each month for each lion, for a total of 30 clusters per lion from 1 November 2006, to 30 April 2007. As time allows, additional clusters can be sampled from the selection sets, which will be used as a validation data set. Our approach forces constant sampling of each cluster set over time regardless of the frequency of clusters within a given set. This will prevent a scenario where nearly all sampled clusters in a given month are from sets, S3, S4 and/or S5 (i.e., low probability of finding feeding sites). Our assessment of prey utilization depends on relatively constant detection of lion feeding sites over time to avoid bias. However, for each cluster set, the true proportion of clusters representing feeding sites may possibly change over time corresponding to changes in lion use of feeding sites. If the GPS download data indicate major changes in set-specific cluster frequencies over the sampling period, we may choose to use a proportional-allocation sampling approach in future years. Assuming a binomial distribution and 0.90 of S1 clusters represent lion feeding sites, we will be able to estimate the true proportion with a 95% confidence interval of +/− 0.07. Assuming 0.5 of S2 clusters represent lion feeding sites, we will be able to estimate the true proportion with a 95% confidence interval of +/− 0.17. Assuming 0.3 of S3 clusters represent feeding sites, we will be able to estimate the true proportion with a 95% confidence interval of +/− 0.15. Finally, assuming 0.1 of S4 and S5 clusters represent feeding sites, we will be able to estimate the true proportion with a 95% confidence interval of +/− 0.10. These precision levels are acceptable for the pilot study, which will facilitate development of an optimal sampling scheme in future years for evaluating lion prey utilization from GPS cluster-location data. Finally, regarding our secondary objective of collecting preliminary prey use data, we should be able to estimate the overall proportion of feeding sites represented by deer (or the proportion of feeding sites represented by elk) with a 95% confidence interval of +/− 0.05 (Anderson and Lindzey 2003, Logan 2005). We anticipate using the following strategy to initially detect clusters in the field. For S1 clusters, we will go to each lion GPS location in the cluster and visually inspect the immediate area for prey remains. We anticipate discovering prey remains at one or more of the cluster points but if remains are not found, we will go to the central GPS location of the cluster and spiral out overlapping view fields to a distance of 50 m beyond the outermost GPS location associated with the cluster. This should produce a thorough search and provide adequate information to judge whether or not a kill site was likely located with the cluster. For S2 through S5 clusters, we will go to each lion GPS location and spiral out 150 m around each point, and depending on vegetation type and density, spend a minimum of 1 hour and a maximum of 2 hours per location point to judge whether the cluster is a kill site. Data will be recorded 88 �on a standard form (Appendix B). We will also initiate attempts to quantify omission errors (missing kill remains at a cluster site) as time allows. Estimating deer, elk, and lion distributions: We will examine locations, movements, and kernel home ranges of mule deer, elk, and lions for spatial overlap and time synchrony using ArcGIS. Our initial analyses will be descriptive and should provide insight into patterns of lion movements and feeding sites in relation to major ungulate species. Based on past observations, we do not expect deer distributions to fluctuate greatly during the winter. However, we do expect elk distributions to fluctuate depending on weather and time. As distribution varies, we also expect to observe variability in group size depending on elevation and vegetation type. We would anticipate being able to generate correlations between species of prey killed by lions and the relative presence of prey within lion home ranges. Hypothesis Testing: This preliminary sampling effort of lion clusters and ungulate distributions will not test any hypotheses but will provide estimates with measures of precision for lion kill rates and proportions of deer and elk killed. However, provided the cluster sampling protocols prove to be functional, future work may be able to examine the likelihood that: Lion prey mass is positively related to lion mass (male lions kill larger prey than female lions), Lions prey on deer and elk in proportion to availability (no selection by lions) Lions prey on sex or ages of deer or elk populations in proportion to availability (no selection by lions. Lions alter their use of prey among seasons of the year (lions prey-switch between deer and elk) Maternal lion home ranges include the highest available densities of ungulate prey and, many other investigative hypotheses LOCATION OF WORK This pilot study will be conducted on the southern half of the Uncompahgre Plateau in southwestern Colorado, near Montrose, Colorado. The study area is defined by the existing boundary for the ongoing mountain lion research project with prey populations being monitored only in the eastern half of the lion study area (Figure 1). SCHEDULE OF WORK Time Fall 2006, ongoing November 2006 November-December 2006 December 2006-May 2007 June-August 2007 Activity Capture of adult mountain lions Initiate sampling of GPS location clusters for lions Capture and deploy 25 VHF collars on mule deer fawns Capture and deploy 6 GPS/VHF collars on adult female elk Capture and deploy up to 6 VHF collars on adult female elk Monitor mule deer and elk distribution and survival Monitor mountain lion distribution and survival Continue sampling of GPS lion clusters Analyze cluster data and deer, elk, and lion spatial distributions and provide preliminary report on the effectiveness of cluster sampling techniques and feasibility of full study 89 �ESTIMATED COSTS Salaries of permanent employees, as well as many other logistical costs (vehicles and flights) will be covered by existing project funds in the CDOW mule deer research, carnivore research and terrestrial management programs. Additional expenditures specific to this pilot study will include: ITEM Wildlife Technician I for 6-months @ $12.49/hour GPS/VHF drop-off Collars for 6 elk @ $3,055 each Helicopter Capture costs 12 elk @$600 each Vehicles mileage (15K), lease for State Temporary Vehicle (6 months/$25/mo) COST $13,975 18,330 7,200 4,775 TOTAL COST $44,280 RELATED FEDERAL PROJECTS This pilot study is collaborative with 3 studies (2 ongoing, 1 completed) through the mammals research program of the Colorado Division of Wildlife. As mentioned above, the mule deer to be utilized in this pilot study were captured and radio collared as part of a previous mule deer research study (Bishop et al. 2004) as well through an ongoing mule deer study (Bergman et al. 2005). Each of these studies has received Federal-Aid research funds. Additionally, this pilot study is collaborative with an ongoing mountain lion research study through the Colorado Division of Wildlife that does not currently receive Federal-Aid research funds. LITERATURE CITED ANDERSON, C. R., JR., AND F. G. LINDZEY. 2003. Estimating cougar predation rates from GPS location clusters. Journal of Wildlife Management 67:307-316. BARRETT, M. W., J. W. NOLAN, and L. D. ROY. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. BARTMANN, R.M. 1983. Composition and quality of mule deer diets on pinyon-juniper winter range, Colorado. Journal of Range Management 36:534-541. BARTMANN, R. M., G. C. WHITE, and L. H. CARPENTER. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. BERGMAN, E.J., C.J. BISHOP, D.J. FREDDY and G.C. WHITE. 2005. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. CREEL, S. and N.M. CREEL. 2002. The African wild dog: behavior, ecology and conservation. Princeton University Press, New Jersey, USA. KEELING, M.J., H.B. WILSON and S.W. PACALA. 2000. Reinterpreting space, time-lags, and functional responses in ecological models. Science 290:1758-1761. KREBS, C.J., S. BOUTIN and R. BOONSTRA, eds. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, USA. KUNKEL, K. E., AND D. H. PLETSCHER. 1999. Species-specific population dynamics of cervids in a multipredator ecosystem. Journal of Wildlife Management 63:1082-1093. KUNKEL, K. E., T. K. RUTH, D. H. PLETSCHER, AND M. G. HORNOCKER. 1999. Winter prey selection by wolves and cougars in and near Glacier National Park, Montana. Journal of Wildlife Management 63:901-910. LIMA, S.L. and P.A. BEDNEKOFF. 1999. Back to the basics of antipredatory vigilance: Can nonvigilant animals detect attack? Animal Behaviour 58:537-543. 90 �LOGAN, K.A. 2005. Puma population structure an vital raties on the Uncompahgre Plateau, Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. MATHEWS, C.G., J.A. LESKU, S.L. LIMA and C.J. AMLANER. 2006. Asynchronous eye closure as an anti-predator behavior in the western fence lizard (Sceloporus occidentalis). Ethology 112:286292. MAO, J.S., M.S. BOYCE, D.W. SMITH, F.J. SINGER, D.J. VALES, J.M. VORE and E.H. MERRILL. 2006. Habitat selection by elk before and after wolf reintroduction in Yellowstone National Park. Journal of Wildlife Management 69:1691-1707. MITCHELL, W.A., and S.L. LIMA. 2002. Predator-prey shell games: large-scale movement and its implications for decision making by prey. Oikos 99:249-259. RAMSEY, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. ROTH, T.C., II, S.L. LIMA and W.E. VETTER. 2006. Determinants of predation risk in small wintering birds: the hawk's perspective. Behavioral Ecology and Sociobiology 60:195-204. RYALL, K.L. and L. FAHRIG. 2006. Response of predators to loss and fragmentation of prey habitat: a review of theory. Ecology 87:1086-1093. SCHMIDT, R. L., W. H. RUTHERFORD, and F. M. BODENHAM. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. SCHMITZ, O.J. 2006. Predators have large effects on ecosystem properties by changing plant diversity, not plant biomass. Ecology 87:1432-1437. VAN REENEN, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. WERNER, E.E. and S.D. PEACOR. 2006. Lethal and nonlethal predator effects on an herbivore guild mediated by system productivity. Ecology 87:347-361. WILMERS, C.C., E. POST, R.O. PETERSON and J.A. VUCETICH. 2006. Predator disease out-break modulates top-down, bottom-up and climatic effects on herbivore population dynamics. Ecology Letters 9:383-389. 91 �Figure 1. Ongoing mountain lion study area (solid gray), extensive mule deer study area (stippled gray), and intensive mule deer study areas (heavy black line polygons) located on the southeastern portion of the Uncompahgre Plateau immediately west of Montrose, Colorado (right center small shaded polygon). 92 �APPENDIX A HELICOPTER NET-GUNNING CAPTURE PROTOCOL FOR ELK Helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) is an established procedure for effectively and safely capturing elk and other cervids with minimal capture-related mortality (Bartmann et al. 1992, White and Bartmann 1994, Freddy 2001, Bishop 1998). Net-gunning will be done by Quicksilver Air, Inc., or other qualified vendor, through the current Division of Wildlife capture contract. Capture and Transport Methods: Wild elk will be pursued and netted by the helicopter netgunning crew. The crew will consist of one pilot and one net-gunner and up to two muggers. Netted animals will immediately be blind-folded and hobbled. Netted animals will be immediately processed and released by the capture crew at the site of capture site. The capture crew will be responsible for deploying radio collars on captured animals. Elk will be captured with net-guns in mid to late-December and in late-February or early-March in the southeast portion of GMU 62 and in the western portion of GMU 65. December snow depths rarely exceed 50 cm where elk will be captured, and mean daily temperatures during December have averaged –4.4 °C (24 °F) during the 1990’s. Under these conditions, elk can be captured safely without undue risk of hyperthermia (defined as anything over 103°). Maximum allowable pursuit time, or time necessary to chase and net a target animal, will not exceed 8 minutes and will be shortened to less than 5 minutes depending on weather conditions and animal behavior. For example, in warmer conditions (e.g. >4°C), pursuit times will be minimized, particularly if unfavorable snow conditions are present. The areas where capture will occur have variable, but high, elk densities. Throughout the study area, encounter rates with different groups of elk will be high, minimizing the need to pursue any given animal for a lengthy period. However, a spotter plane will be used to facilitate capture. The spotter plane will identify unique elk groups from higher elevations and communicate coordinates of the groups to the helicopter via radio. This approach will allow the helicopter to efficiently navigate to the group and quickly identify an individual for capture. Additionally, if any potential barriers that could potentially jeopardize any animal during a chase exist (i.e. fences, roads, etc.), the capture crew will be informed of their location in order minimize/remove the potential for injury around these obstacles. In the case of roads, DOW personnel will monitor/control traffic to reduce the potential of having vehicles stop in the capture area. The helicopter pilot and handling crew will be in radio contact with one another and with a ground crew at the helicopter refueling site. In the event of an accident, the Montrose Division of Wildlife office will be contacted by radio, and necessary emergency services will be sent to the site. The ground crew will have direct radio access to the Montrose County Sheriffs Office, Colorado State Police, Search and Rescue, and NLEEC (National Law Enforcement Emergency Channel). Training and Personnel: The helicopter net-gunning crew will be instructed as to procedures for minimizing stress and injury to the animals. Specifically, they will be instructed on pursuit times, transport distances, and safe handling procedures. The handling crew, comprised of DOW personnel, will be instructed on proper care and handling procedures to minimize stress and risk of injury to the captured elk. Eric Bergman will be ultimately responsible for all animal care and handling. PROCEDURES AND MANIPULATIONS OF ANIMALS Capture: As stated above, netted animals will immediately be blind-folded and hobbled. Elk will immediately be radio-collared. Elk will be removed from the net, and the blind-fold and hobbles will be checked. Elk will be radio-collared and approximately aged by qualitatively evaluating height and wear of incisors and premolars (yearling, 2-5 years, 6-9 years, ≥10 years). All radio collars will be of fixed-size and individually fitted to each animal. 93 �If a captured elk suffers a broken leg, back, neck, pelvis, or other similar wound, it will be euthanized at the capture site with a gunshot to the head following euthanasia protocols of the Colorado Division of Wildlife Animal Care and Use Committee. LITERATURE CITED BARRETT, M. W., J. W. NOLAN, and L. D. ROY. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. BARTMANN, R. M., G. C. WHITE, and L. H. CARPENTER. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. BISHOP, C. J. 1998. Mule deer fawn mortality and habitat use, and the nutritional quality of bitterbrush and cheatgrass in southwest Idaho. Thesis, University of Idaho, Moscow, Idaho, USA. FREDDY, D. J. 2001. Estimating calf and adult survival rates and pregnancy rates of Gunnison Basin elk. Wildlife Research Report, Colorado Division of Wildlife July: 191-238. Fort Collins, CO, USA. VAN REENEN, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. WHITE, G. C., and R. M. BARTMANN. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. 94 �APPENDIX B PUMA CLUSTER INVESTIGATION FORM Puma ID ____________. Puma Class (check): ____ AM; ____ AFS; ____ AFC-_____ mo.; ____ AM & AF. Cluster No. _________ ; Random Sample (y/n) ____; Cluster Dates ___________________________________; No. of GPS Locations at Cluster _____; Individual Location IDs: ________________________________________. Investigator(s) __________________________________________; Date investigated ______________________. Cluster Location (e.g., drainage, mt. name) __________________________________________________________. Findings: (y/n) Prey cache ___: Species ___________; Sex (M/F) _______; Age _______ (known or est); Incisor collected? ___. Puma sign ___: Tracks? ____; Bed with hair? ____; Scrape(s)? _____; Scat(s) _____, collected? ____________. Other ___: Describe (e.g., bear sign, deer beds) _________________________________________________. Dist. from closest GPS cluster location (pt # ___________) to Hand-held GPS fix where puma sign found = ____ m. Site Details: ] [ If matches individual GPS location(s), list number(s): _________________________________ Map Projection: NAD 27; Zone ______; UTM (E x N) __________________; Elev (m) _______; Aspect ____. Terrain features (e.g., boulders, cliffs) _____________________________________________________________. % Ground Cover (≥70 cm tall over 5 m area) ____; Vegetation association ________________________________ Dominant plant species at site (in order): ____________________________________________________________ Predation Evidence: Carcass: Cached? ____; Number of cache sites ___. Drag marks: Present? __; Length (m) _____; Blood/hair? ___. Rumen: Present?____; Removed from carcass? _____ Covered? _______________________________________. Tooth marks: Present? ____; Location_______________________; Distance between canines ___________mm Subcutaneous or internal hemorrhage ______________________________________________________________. Hair plucked? ____. Carcass fed upon? ___; Approx. % consumed:____. Point of first feeding:________________; Parts eaten:______________________________________________________. Large leg bones broken? ________. Signs of predation sequence (e.g., tracks, chase)?_____________________________________________________ . If found, UTM (E x N) of prey KILL site:___________________________________________________________ Other predators / scavengers present (incl. other pumas)?_______________________________________________ Carnivore tracks: Present? ___ ; Species? _______________; If puma, heel pad width (mm) __________________. Scrapes? ___ ; No. & dist. (m) from carcass ______________. Puma scat?____; on scrape or in mound? ________. Prey Condition: Antlers/horns present?(size) ________. External parasites?______________. Approx. date of death: __________. Fat on internal organs?__________________________________________________________________________. Pregnant? ________; No. fetuses ________. Lactating? ____. Dependent young? ________________________. Femur marrow: Too old (x)_____ Consistency-__________________________; Color-____________________. Injuries or disease?(e.g., jaw necrosis):_____________________________________________________________. 95 �Prey Cause of Death: Certain puma ___; Probable puma ___; Non-puma ____; Unknown ____. Bait station? ____; Scavenged? ____. If puma not cause, give probable cause & support notes (e.g., other predator) _______________________________ _____________________________________________________________________________________________. Samples Collected: Skull ____; Jaw ___; Incisors ____; Parasites ___; Puma feces __; Collar ____; Eartag ___; Photos ____; Other_____________ Notes? (on back) ___ 96 �Colorado Division of Wildlife July 2006 – June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 5 Federal Aid Project: W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Multispecies Investigations Consulting Services for Mark-Recapture Analysis : Period Covered: July 1, 2006 - June 30, 2007 Author: G. C. White Personnel: C. Bishop, D. J. Freddy, T. M. Shenk, P. Lukacs, R. Kahn, F. Pusateri, E. O’Dell, D. Martin, P. Schnurr, K. Navo, B. Andelt, A. Linstrom, P. Conn, B. McClintock, G. Davidson, and J. Ivan. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Progress towards meeting the objectives of this job include: 1. Consulting assistance to Colorado Division of Wildlife (CDOW) on harvest surveys, terrestrial inventory systems, and population modeling procedures was provided. Computer code written in SAS to compute these estimates and display results graphically was provided. Specific input involved estimation of variances for design of the E-2 elk aerial survey. 2. Support for the CDOW DEAMAN software package for the storage, summary, and analysis of big game population and harvest data was provided. I met with the CDOW software group to discuss conversion of DEAMAN to a central server application. 3. Consultation with CDOW Terrestrial Biologists in the use of DEAMAN and population modeling procedures continued. Numerous questions were answered via meetings with biologists, and via email. A workshop on modeling Colorado’s deer, elk, and antelope populations was conducted for biologist in Glennwood Springs, August, 2006. 4. A paper comparing the population levels of swift foxes in eastern Colorado to a previous study in cooperation with CDOW was accepted for publication in Southwestern Naturalist: Martin, D. J., G. C. White, and F. M. Pusateri. 2007. Monitoring swift fox populations in eastern Colorado. Southwestern Naturalist. In Press. 5. A paper on estimation of abundance and demography using age-at-harvest and mark-recovery data was submitted to Environmental and Ecological Statistics: Conn, P. B., G. C. White, and J. L. Laake. 2007. Estimating abundance and demography using age-at-harvest and mark-recovery data: a Bayesian approach. Environmental and Ecological Statistics. Submitted. 97 �6. A paper on Bayesian methods to analyze age-at-harvest data was submitted to Biometrics: Conn, P. B., J. L. Laake, D. R. Diefenbach, G. C. White, and M. A. Ternent. 2007. Bayesian analysis of wildlife age-at-harvest data. Biometrics. Submitted. 7. A paper on the use of vaginal implant transmitters in cooperation with CDOW was submitted and accepted for publication in the Journal of Wildlife Management: Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of neonates from marked mule deer. Journal of Wildlife Management 71:945–954. 8. A paper resulting from collaboration with Montana colleagues resulted in a publication in the Journal of Wildlife Management: Pac, D. F., and G. C. White. 2007. Survival and cause-specific mortality of male mule deer under different hunting regulations in the Bridger Mountains, Montana. Journal of Wildlife Management 71:816–827. 9. A paper resulting from Sherri Huwer’s M.S. project in cooperation with CDOW was accepted for publication in the Journal of Wildlife Management: Huwer, S. L., D. R. Anderson, T. E. Remington, and G. C. White. 2007. Evaluating the importance of forbs to sage-grouse using human-imprinted chicks. Journal of Wildlife Management. In Press. 10. A paper on mountain sheep populations in Rocky Mountain National Park was published in the Journal of Wildlife Management: McClintock, B. T., and G. C. White. 2007. Bighorn sheep abundance following a suspected pneumonia epidemic in Rocky Mountain National Park. Journal of Wildlife Management 71:183–189. 11. A paper on extending the mark-resight estimator using a beta-binomial distribution was published in the Journal of Agricultural, Biological, and Ecological Statistics: McClintock, B. T., G. C. White, and K. P. Burnham. 2006. A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities. Journal of Agricultural, Biological, and Ecological Statistics 11:231–248. 12. A paper resulting from the May, 2005 Elk and Deer Workshop was published in the Wildlife Society Bulletin: Mason, J. R., L. H. Carpenter, M. Cox, J. C. Devos, J. Fairchild, D.J. Freddy, J. R. Heffelfinger, R. H. Kahn, S. M. McCorquodale, D. F. Pac, D. Summers, G. C. White, and B. K. Williams. 2006. A case for standardized ungulate surveys and data management in the western United States. Wildlife Society Bulletin 34:1238–1242. 13. A paper describing the use of closed captures models to estimate population size with Program MARK remains in press in Environmental and Ecological Statistics: White, G. C. 2007. Closed population estimation models and their extensions in program MARK. Environmental and Ecological Statistics. In Press. 14. A paper on the application of multistate models in Program MARK was published in the Journal of Wildlife Management: White, G. C., W. L. Kendall, and R. J. Barker. 2006. Multistate survival models and their extensions in program MARK. Journal of Wildlife Management 70:1521–1529. 15. A paper on the estimation of female grizzly bears was published in the Journal of Agricultural, Biological, and Ecological Statistics: Cherry, S., G. C. White, K. A. Keating, M. A. Haroldson, C. C. Schwartz. 2007. Evaluating estimators of the numbers of females with cubs-of-the-year in the Yellowstone grizzly bear population. Journal of Agricultural, Biological, and Ecological Statistics 12:195–215. 98 �16. A paper on estimation of nest survival was published in Studies in Avian Biology: Heisey, D. M., T. L. Shaffer, and G. C. White. 2007. The ABCs of nest survival: theory and application from a biostatistical perspective. Studies in Avian Biology 34:13–33. 17. A paper on extending the mark-resight population estimation method was submitted to Environmental and Ecological Statistics: McClintock, B.T., G. C. White, K. P. Burnham, and M. A. Pryde. 2007. A robust design mixed effects mark-resight model for estimating abundance when sampling is without replacement. Environmental and Ecological Statistics. Submitted. 18. A paper on estimation of random effects with Bayesian methods was submitted to Environmental and Ecological Statistics: White, G. C., K. P. Burnham, and R. J. Barker. 2007. Evaluation of some Bayesian MCMC random effects inference methodology applicable to bird ringing data. Environmental and Ecological Statistics. Submitted. 19. A paper on analysis of small count data was submitted to Condor: McDonald, T. L., and G. C. White. 2007. A comparison of regression models for small counts. Condor. Submitted. 20. A paper on the impact of previous capture on sampling probabilities with DNA hair-snag grids for grizzly bear populations was submitted to the Journal of Wildlife Management: Boulanger, J., and G. C. White. 2007. Influence of past live captures on detection probabilities of grizzly bears using DNA hair snagging methods. Journal of Wildlife Management. Submitted. 21. A paper on detecting trends in the Yellowstone grizzly bear population was submitted to Ursus: Harris, R. L., G. C. White, C. C. Schwartz, and M. A. Haroldson. 2007. Population growth of Yellowstone grizzly bears: uncertainty and future monitoring. Ursus. Submitted. 22. A graduate research project (Ph. D.) in cooperation with CDOW to develop statistical models to monitor puma and black bear populations in Colorado based on checks of harvested animals and DNA and/or radio-tracking data was completed. The graduate student is Paul B. Conn. The dissertation is: Conn, P. B. 2007. Bayesian Analysis of Age-at-Harvest Data with Focus on Wildlife Monitoring Programs. Ph. D. Dissertation, Colorado State University, Fort Collins. 184 pp. 23. A research study to examine the impact of nutrition on the decline of mule deer fecundity during the last 20 years was continued in cooperation with Chad Bishop and CDOW. Portions of this work will serve as his doctoral dissertation in addition to his full-time duties as a researcher with CDOW. 24. A graduate research project (M. S.) was continued in cooperation with CDOW to evaluate line transect methodology for estimating pronghorn populations in eastern Colorado. The graduate student is Aaron Linstrom, and the project is in addition to his full-time duties as a biologist with CDOW. 25. A graduate research project (M. S.) in cooperation with CDOW to evaluate methods of redistributing elk in and around Great Sand Dunes National Park was started and then discontinued. The student, Greg Davidson, switched his work to evaluate habitat use by elk on the Grand Mesa. A report on the San Luis Valley elk work is nearly completed. 26. A graduate research project (Ph.D.) in cooperation with CDOW to evaluate snowshoe hare densities relative to lodge pole pine and mixed conifer habitats was continued. The graduate student is Jake Ivan. 27. Development of the design of a monitoring system for white-tailed prairie dogs in western Colorado and eastern Utah was continued in cooperation with CDOW with P. Schnurr, K. Navo and B. Andelt. 99 �A final draft of a manuscript on the use of occupancy monitoring for white-tailed and Gunnison prairie dogs was given to B. Andelt for submission to the Journal of Wildlife Management on 20 February, 2007. 28. Preliminary analysis of monitoring data on black-tailed prairie dogs in eastern Colorado in cooperation with CDOW was continued. This effort is in cooperation with Francie Pusateri and Eric O’Dell of CDOW. 100 �WILDLIFE RESEARCH REPORT CONSULTING SERVICES FOR MARK-RECAPTURE ANALYSES GARY C. WHITE P. N. OBJECTIVE Provide expert biostatistical and experimental design services to the Colorado Division of Wildlife, Wildlife Programs Branch. SEGMENT OBJECTIVES 1. Provide biostatistical support to implement and analyze CDOW hunter harvest surveys. 2. Provide professional oversight, critiques, and analytical support to CDOW terrestrial management and avian and mammals research sections. 3. Convey to CDOW research and management sections new and pertinent information obtained in various collaborative projects conducted with other agencies and entities. RESULTS, DISCUSSION, SUMMARY See ABSTRACT for summary of key activities and publications. Prepared by: ___________________________________ Dr. Gary C. White, Department of Fish, Wildlife, and Conservation Biology Colorado State University 101 �102 �Colorado Division of Wildlife July 2006 − June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 6 Federal Aid Project: W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Population Performance of Piceance Basin Mule : Deer in Response to Natural Gas Resource : Extraction and Mitigation Efforts to Address : Human Activity and Habitat Degradation : Period Covered: July 1, 2006 − June 30, 2007 Authors: C. R. Anderson, and D. J. Freddy Personnel: M. Alldredge, E. Bergman, C. Bishop, R. Kahn, P. Lukacs, T. Remington, M. Schuette; G. White, Colorado State University; H. Sawyer, Western Ecosystems Technology, Inc. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A researcher FTE vacancy was filled with a newly hired person in December 2006 who became the project leader for this project. No preliminary field work could be completed in winter-spring 2007 as originally planned for FY2006-07 but assessments of potential study areas, resource inventory maps, and tentative study plan outlines were completed by June 2007. As such, field work for this project will begin winter 2007 and be centered in the Piceance Basin area of northwestern Colorado which is currently undergoing intensive natural gas development in one of the most extensive and important mule deer winter and transition range areas within the state. Our approach will be to experimentally evaluate habitat treatments that may rehabilitate the landscape to benefit mule deer and to evaluate human-activity management alternatives to reduce the disturbance impacts on mule deer. This project will require a longterm commitment of at least 10-years from private industry, the BLM, and the CDOW to assess if sustainable mule deer populations can persist within a highly disturbed landscape following implementation of beneficial habitat treatments and development practices. 103 �WILDLIFE RESEARCH REPORT POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGREDATION CHARLES R. ANDERSON AND DAVID J. FREDDY P. N. OBJECTIVE To develop approaches to provide for energy extraction in a manner that maintains viable mule deer populations for future recreational and ecological purposes. SEGMENT OBJECTIVES 1. Consult with regional personnel to select potential study sites for addressing habitat mitigation and energy development practices that benefit mule deer. 2. Plot historic and current energy development activities to assess potential treatment and control sites for experimental evaluation. 3. Develop draft study proposals for peer review and funding solicitation. INTRODUCTION Extraction of natural gas from areas throughout western Colorado has raised concerns among many public stakeholders and the Colorado Division of Wildlife that the cumulative impacts associated with this intense industrialization will dramatically and negatively affect the wildlife resources of the region. Concern is especially high for mule deer due to their recreational and economic importance as a principal game species and their ecological importance as one of the primary herbivores of the Colorado Plateau Ecoregion. Research evaluating the most effective strategies for minimizing and mitigating these activities will greatly enhance future management efforts to sustain mule deer populations for future recreational and ecological values. Our primary goal of this study is to develop approaches to provide for energy extraction in a manner that maintains viable mule deer populations for future recreational and ecological purposes. This may be accomplished by restoring or enhancing habitat conditions on or adjacent to disturbed sites and by modifying development practices. Due to the extensive energy development that is projected to occur over the next 20 years throughout much of the mule deer winter range in the northern Rocky Mountains of the western US, innovative approaches to energy development and mitigation methods are essential to sustain viable mule deer populations in the region. Impacts from development and conversely success of mitigation efforts are often assumed but rarely demonstrated, and these assumptions can only be confirmed by application of well designed research efforts conducted over sufficiently long time periods to measure responses. This project proposes to identify habitat mitigation and energy development approaches that sustain mule deer survival and recruitment during and after habitat disturbance from development activities. This effort will require coordination and cooperation between Colorado Division of Wildlife and the major energy companies. We anticipate this partnership will benefit mule deer populations and foster the evolution of wildlife management and energy development practices that are compatible with other wildlife and human values associated with maintaining functional ecosystems over the long term. 104 �STUDY AREA The proposed study sites represent 6 segments of mule deer winter range in the Piceance Basin, southwest of Meeker, Colorado (Figure 1), and the primary energy companies developing these areas include Encana and Exxon-Mobile (Figure 2). Because of the varying levels of development and deer densities relative to differing winter population segments in the Piceance Basin, different experimental units (i.e., mule deer winter ranges) are uniquely suited for addressing different questions. Experimental designs monitoring mule deer responses to treatment (e.g., habitat mitigation) and control areas are necessary to differentiate cause-effect relationships from development versus environmental factors. Suitable control areas require that little or no previous development has occurred and that no development occurs during the experimental time frame. Ideally, both temporal and spatial control areas would be monitored to make valid comparisons to developed and subsequently mitigated sites; temporal controls provide measures of natural variability in mule deer population parameters over time and spatial controls provide measures of variability due to differences in geography. Once spatial and temporal variation is accounted for, inferences can be made relative to development disturbance or mitigation effects on mule deer. The North Ridge, Story/Willow Creek, and Yellow Creek deer population segment areas (Figure 1) currently exhibit little to no development, but it is currently unknown whether or not these areas will be developed in the future; there is potential for future oil shale development in the Story/Willow Creek and Yellow Creek deer areas. North Ridge appears least likely to be developed because it is outside of the current oil shale lease area and only a few wells have historically been drilled on or adjacent to the area, whereas the same cannot be said of the Story/Sprague or Yellow Creek areas. Thus, North Ridge would appear best suited as a temporal control site for comparison to other developed winter ranges within the Piceance Basin and may also serve as a geographic control for the Crooked Wash deer population segment located immediately north and adjacent to the Piceance Basin. The Story/Willow Creek and Yellow Creek deer may provide spatial controls for the Magnolia and Ryan Gulch deer population segments, respectively, but future development potential in these areas is unknown. If these areas become developed in the future (either for oil shale or natural gas), they would provide BACI (Before-AfterControl-Impact) type comparisons strengthening our inference of development impacts on mule deer population performance. Magnolia, Crooked Wash, and Ryan Gulch deer areas have historically received relatively high development activity and currently exhibit moderate-high development, and appear likely to be developed extensively in the future based on the gas development layers currently available (Colorado Oil and Gas Conservation Commission). Pretreatment data in these areas will be represented by parameters associated with developed sites and the measured response will be in the form of habitat treatments and/or differing development practices, which will be measured in comparison to the control sites. We propose including 3 control sites (1 temporal/spatial control and 2 spatial controls) and 3 treatment sites to investigate mule deer response to habitat and/or development treatments (e.g., directional versus non-directional drilling, piping versus trucking condensate, etc.) across a range of deer densities (Table 1). We would strive to split high intensity extraction study sites into 2 halves with one half serving as the ‘control’ [standard development] and one half serving as the ‘treatment’ [improved development approach or improved habitat]. The above scenario addresses the potential for establishing control and treatment sites for evaluating mule deer population response to habitat treatments and/or development treatments, and may allow larger scale mule deer responses from energy development to be addressed by comparing control site parameters to developed site parameters; smaller scale inference would require collection of pretreatment data at developed sites (e.g., similar to mitigation treatments in the proposed design) and may not be possible unless the Yellow Creek or Story/Willow Creek areas are developed in the future. Modified versions of the proposed design could be implemented depending on 105 �the level of funding available and the degree to which industry willing to collaborate with this effort. We consider 3 study sites, likely North Ridge, Magnolia, and Crooked Wash, as the minimum number of study sites necessary to adequately address the objectives of this project; the additional proposed study areas will allow increased flexibility in the questions that are addressed and increase our inference relative to mule deer responses to habitat treatments and modifications of development practices. Furthermore, if we are not able to evaluate potential mitigating industrial operation and/or habitat improvements, this study would likely only have the potential to document negative impacts of intense energy extraction practices on mule deer. RESPONSE VARIABLES To allow for competing hypotheses in regards to potential development and mitigation effects, 4 primary response variables will be measured including (1) overwinter fawn survival, (2) deer density, (3) habitat use patterns, and (4) adult female body condition. (1) To determine if mitigation and/or development treatments elicit a chronic survival response with a long-term population level effect, we will measure over-winter fawn survival in all experimental units. Based on past research (White and Bartmann 1998), treatment effects of 15% change in survival appear biologically significant. (2) To determine if habitat treatments or development practices elicit a brief survival response with a long-term population level effect, we will estimate deer density to determine if there is a difference in carrying capacity between treatment and control experimental units. Because mule deer may respond to development or mitigation at variable rates, we may not be able to detect differences in fawn survival, but estimating deer density will still allow us to determine if development or mitigation efforts have a population level effect. (3) To determine if habitat treatments or development practices elicit a shift in habitat use patterns, we will examine changes in Resource Selection Probability Functions (RSPF; Sawyer et al. 2006) pre- and post-habitat treatments, between areas exhibiting development practices, and compare RSPFs between developed and non-developed sites. We will infer population level impacts if fawn survival and/or deer densities differ relative to changes or differences in habitat use patterns. (4) To determine if adult female mule deer respond positively to habitat treatments and/or changes in development practices, percent body fat and loin depth will be measured annually during late winter (Bishop et al. 2005, Bergman et al. 2005). We would expect a relatively rapid response in body condition following habitat or development treatments, indicating that treatments are having the intended positive effect. PROJECT EXPENSES Estimating fawn survival, deer density, deer behavioral responses, female body condition, and implementing small scale habitat improvements are costly endeavors involving the purchase of numerous standard VHF radio-collars, specialized GPS radio-collars, helicopter flight hours for deer capture/collaring and aerial surveys, machinery to physically alter the habitat, and personnel to adequately perform day-to-day data collection. If large scale habitat treatments are needed or desired, funding in addition to the estimates below will be required as habitat treatments cost $300 to $1,000/acre depending on the most appropriate treatment for a locale. Minimum cost estimates to design, implement, and evaluate responses of mule deer to habitat mitigation options range form $580,500 to $1,161,00 (most preferred design) per year depending on project design (Table 2). 106 �LITERATURE CITED BISHOP, C. J., G. C. WHITE, D. J. FREDDY, and B. E. WATKINS. 2005. Effect of nutrition on mule deer recruitment and survival rates. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins. USA. BERGMAN, E. J., C. J. BISHOP, D. J. FREDDY, and G. C. WHITE. 2005. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Study Plan, Colorado Division of Wildlife, Fort Collins, USA. SAWYER, H., R. M. NIELSON, F. LINDZEY, and L. L. MCDONALD. 2006. Winter habitat selection of mule deer before and during development of a natural gas field. Journal of Wildlife Management 70:396-403. WHITE, G. C., and R. M. BARTMANN. 1998. Effect of density reduction on overwinter survival of freeranging mule deer fawns. Journal of Wildlife Management 62:214-225. Prepared by ___________________________________ Charles R. Anderson, Wildlife Researcher Table 1. Relative density of natural gas wells and mule deer and experimental designation for potential study sites in the Piceance Basin, Colorado, for addressing mule deer response to natural gas development practices and habitat mitigation. Relative density Experimental Study area Inactive wells Active wells Mule deer designation North Ridge Very low None High Temporal/spatial control Crooked Wash High High High Treatment Story/Willow Creek Low Low Moderate Spatial control Magnolia High High Moderate Treatment Yellow Creek Moderate Low Low Spatial control Ryan Gulch High Moderate Low Treatment 107 �Table 2. Estimated costs for CDOW to conduct desired mule deer research in the Piceance Basin to assess impacts of natural gas extraction on mule deer and evaluate approaches to mitigate habitat impacts. Project should be conducted for 10 years to allow for adequate time to measure biological responses, 2008-2018. Cost Estimates Per Year Per Study Site (2008 dollars) Piceance Basin Mule Deer Research Telemetry collars & equipment $70,000 Helicopter Deer Capture & Surveys $68,500 Other Field Operations & Equipment $15,000 12 months TFTE Personnel (Tech I) $30,000 Vehicle Yearly Lease Plus Mileage (4x4 PU, & 45,000miles) Total cost Per Study Site/Yr Minimum Study One Control Site & Two Treatment Sites Acceptable Two Control Sites & Two Treatment Sites Best Three Control Sites & Three Treatment Sites Cost Per Year (2008 dollars) Cost Per Year (2008 dollars) Cost Per Year (2008 dollars) $580,500 $774,00 $1,161,000 $20,000 $193,500 108 �Figure 1. Proposed mule deer study sites relative to natural gas development in the Piceance Basin, Colorado, July 2007. Crooked Wash Yellow Creek North Ridge Magnolia Ryan Gulch Story/Willow Creek 109 Piceance Basin Research Areas + Active Wells + Inactive Wells + Drilling Permits �Figure 2. Proposed mule deer study sites relative to the primary energy companies controlling natural gas leases in the Piceance Basin, Colorado, July 2007. Crooked Wash Piceance Basin Yellow Creek North Ridge Magnolia Ryan Gulch Story/Willow Creek 110 Research Areas + Gas Lease Ownership �Colorado Division of Wildlife July 2006 – June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3003 1 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Predatory Mammals Conservation : Puma Population Structure and Vital Rates on the Uncompahgre Plateau : Period covered: August 1, 2006―July 30, 2007 Author: K. A. Logan. Personnel: K. Logan, B. Bavin, B. Dunne, J. Mannas, S. Waters, K. Crane, T. Mathieson, M. Caddy, and T. Bonacquista of CDOW; S. Young, and J. McNamara of U.S.D.A. Wildlife Services; volunteers and cooperators including: private landowners, U.S. Forest Service, Bureau of Land Management, and Colorado State Parks with financial support received from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Research continued on puma population characteristics and dynamics on the Uncompahgre Plateau. Puma capture efforts resulted in a total of 54 puma captures (9-10 adult females [1 female captured twice], 7 adult males [1 male probably captured 3 times, and another captured twice], 1 subadult female, 0-1 other subadults, and 30 cubs [4 captured twice each]). Efforts to capture, sample, and mark pumas with the use of trained dogs extended from November 13, 2006 to May 11, 2007. This resulted in 22 puma captures, including 1 adult female, 1 adult male, 2 adult males, and 2 male cubs captured and processed for the first time. One female (adult or subadult) and 2 cubs were not handled for safety reasons. Capture efforts with ungulate carcasses and cage traps resulted in 8 puma captures, including 4 adult females, 2 adult males, 1 subadult female, and 1 female cub. Of those animals, 1 adult female, 1 adult male, the subadult female, and the female cub were captured for the first time. Capture efforts during November 2006 through May 2007 enabled us to estimate a minimum count of 24 independent pumas detected on the Uncompahgre Plateau study area during that time. The count included 16 females and 8 males. We captured, sampled, and marked 26 puma cubs produced by 10 females. Twenty-three of the cubs were examined at 8 nurseries when the cubs were 29 to 41 days old. Since the start of this study, 38 cubs from 13 litters aged 29 to 42 days old had a sex ratio of 21 males:17 females. The mean (±SD) and extremes of litter sizes were 2.84 (±0.99), 1 to 4. Eight birth intervals for 7 different females averaged 14.99 months (SD = 3.40), and ranged from 11.7 to 20.5 months. Four gestation periods averaged 92.0 days (SD = 1.68). Of 9 adult males and 12 adult females radio-monitored to quantify survival and agentspecific mortality rates, 1 male and 1 female are known to have died from natural causes. Of 6 subadult pumas monitored via radio-telemetry, none died. Thirty-nine puma cubs (20 males, 19 females) have been monitored by radiotelemetry for varying durations. Among those, 12 deaths were documented, including 7 from intra-species strife, 1 killed by coyotes, 1 killed by a vehicle, and 3 died due to research activities. 111 �Twenty adult pumas (7 males, 13 females) fit with GPS collars since field research began in December 2004 have yielded 113 to 2,759 locations per individual puma. Winter activity areas were estimated for 12 (9 female, 3 male) GPS-collared adult pumas. As an index to the vulnerability of puma mothers to sportharvest we monitored mother-cub distances from an airplane during November to March. Puma mothers were ≥520 m from their cubs during 16.3% of the observations (mean distance = 1,120 m, SD = 1,214.40, range = 616 to 4,101). These results were similar to our results the previous winter (15.2%). A collaborative effort to investigate puma use of ungulates on the Uncompahgre Plateau resumed. GPS clusters were investigated for 13 GPS-collared adult pumas (8 female, 5 male). A total of 257 clusters were investigated. Mule deer and elk were about equally important to pumas as food. Preliminary comparisons between our current puma research on the Uncompahgre Plateau (31 months duration) and results of the Anderson et al. (1992) puma research on the plateau (7 years duration 1981-1988) were made where appropriate. Proposed work includes: continuing investigations of puma use of ungulates, developing and testing methods and models to estimate puma abundance, and collaborating with colleagues to assess puma health. In addition, we will consider how research of pumas on developed areas on the Uncompahgre Plateau can contribute to the CDOW’s efforts to study puma-human interactions on the Colorado Front Range. 112 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates― all to improve the Colorado Division of Wildlife’s (CDOW) model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. 5. Continue gathering data on puma population sex and age structure. Continue gathering data for estimates of puma reproduction rates. Continue gathering data to estimate puma sex and age-stage survival rates. Continue gathering data to estimate agent-specific mortality rates. Continue gathering data on puma movements for the development of sampling methods for markresight or recapture population estimates that might involve sampling puma DNA-genotypes, trail cameras, or direct observations. 6. Begin gathering data on spatial relationships of puma mothers to their cubs during the Colorado puma hunting season as a preliminary assessment of the vulnerability of puma mothers to sport-hunting harvest. 7. Evaluate other data sources that could come from this research that can be developed into other puma research relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing puma while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): 113 �Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field experiments. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared puma. Those objectives include: 1. Describe and quantify puma population sex and age structure. 2. Estimate puma population vital rates, including: birth rates, age-stage-specific survival rates, emigration rates, immigration rates. 3. Estimate agent-specific mortality rates. 4. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of population abundance (i.e., numbers and density) and attendant annual population growth rates, such as, direct capture-resight, and DNA genotype capture-recapture. TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 114 �1. Recreational puma hunting management in Colorado Game Management Units (GMUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are deemed to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e., λ = 1.15) for the adult and subadult puma population (J. Apker, Carnivore Management Specialist, CDOW, Monte Vista). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). The key assumption is that the CDOW can manage puma population growth through recreational hunting: for a stable puma population hunting removes the annual increment of population growth (i.e., as estimated from estimates of population density, structure, and λ); for a declining population, hunting removes more than the annual increment of population growth. Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, agespecific natality, sex- and age-specific survival, immigration and emigration. A descriptive study will ascertain these population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. The treatment period will involve the use of controlled recreational hunting to manage the puma population into a decline phase. H1a: Population parameters measured during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15, which is currently assumed in the CDOW’s model-based management. H1aA: Population parameters measured during a 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will be substantially lower (i.e., ≥50% lower, λ ≤1.075) than the assumed λ = 1.15. H1b: Population parameters during a 5-year treatment period (controlled puma hunting) will differ substantially from those measured during the preceding 5-year reference period (hunting closure) and will yield an estimated annual adult plus subadult population growth rate that will be approximately λ = 0.8 for at least the first 2 years of the treatment period. Hunting-caused mortality will be strongly additive, and will require removal of the annual growth increment (of adults plus subadults) plus 20% (e.g., assume λ = 1.15, so, 0.15 × 0.2 + 0.15 = 0.18; 0.18 × 100 = 18% annual harvest of adults plus subadults). H1bA: Population parameters during a 5-year treatment period (controlled puma hunting) will not differ substantially from those measured during the preceding 5-year reference period (hunting closure), and the adult plus subadult population will not decline on average as a result of hunting mortality. Hunting-caused mortality, reproduction, immigration, and emigration might be compensatory. 2. Considering limitations (i.e., methods, number of years, assumption violations) to the Coloradospecific studies on puma densities cited above (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those 115 �quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973, Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0―4.6 puma/100 km2 to extrapolate to Data Analysis Units to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using capture, mark, re-capture techniques developed and refined during the study to estimate the puma population, the following will be tested: H2a: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 3. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H2b: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent puma will cause an older age structure in harvest-age puma (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. H2c: As hunting is re-instated in the treatment period, the age structure of harvested puma and the harvest-age puma in the population will vary as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters useful for estimating puma population abundance, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help those managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for estimating puma abundance (capture-mark-recapture) of known reliability will allow managers to “ground truth” modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will require development of reliable monitoring techniques based on capture-mark-recapture methods and models. Potential methods include direct and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and when we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties, Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded 116 �by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinon-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing summer residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Experimental Treatment Periods This research is structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period is expected to cause a population increase phase. The treatment period will be managed to cause a population decline phase. In both phases, puma population structure, and vital rates will be quantified, and some management assumptions and hypotheses regarding population dynamics will be tested. Contingent upon results of pilot studies, we will also estimate puma numbers, population growth rates, evaluate enumeration methods, and test other hypotheses (Logan 2004). The reference period, without recreational puma hunting as a major limiting factor, is consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000―12,000 years (Culver et al. 2000) that enable puma to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma evolution in western North America for the past 100 years. Hence, the reference period, years 1―5, will provide conditions where individual puma in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factors will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before the treatment (i.e., controlled recreational hunting). In the reference period, all puma in the study area will be protected, except for individual puma that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged puma that range in a buffer zone, that includes the northern halves of GMUs 61 and 62, will be protected from recreational hunting. The reference period will allow researchers to quantify baseline demographic data on the puma population to estimate parameters for the CDOW’s model-based approach to puma management. Moreover, it will allow researchers to develop and test puma enumeration methods when population growth is known to be in one direction― increasing. Without the hunting closure, pilot data for enumeration methods could be confounded by not knowing if the population was increasing, declining, or stable. The reference period will also facilitate other operational needs (because hunters will not be killing the animals) including the marking of a large proportion of the puma population for capture-markrecapture estimates, and the gathering of movement data from GPS-collared puma to help formalize exact sampling designs for enumeration methods. During the treatment period, years 6―10, experimentally structured recreational puma hunting will occur on the same study area with the intent of causing a decline phase in the puma population by using management prescriptions structured from information learned during previous years. Using 117 �recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or population suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, puma survival will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared puma. The portion of adults and subadults in the population will be reduced by approximately 20% in year 6 and 20% more in year 7. The 20% change was identified by Division managers that requested enumeration tools that might detect 20% changes in puma populations. For managers, detecting the magnitude of puma population decline phases is probably more important that detecting the magnitude of population increase phases. This will also allow quantification of puma population characteristics and vital rates and initial tests of enumeration methods during a decline phase. Additional reductions may be made to test enumeration methods and other hypotheses that may be related to effects of hunting (i.e.,: relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting) and puma―prey interactions (i.e., lines of research identified in the Colorado Research Program, Fig. 1). Those decisions can be made later in project development and as late as years 8―10. The killing of tagged and collared puma during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a large majority of independent puma in the population will be marked, and sampling schemes will be formalized. Puma on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW of Wildlife if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that puma live at low densities and capturing puma is difficult, as a starting point, our logistical aim will be to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim is to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of puma might represent the large majority of the puma population on the study area, and will provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration rates, and movement data pertinent to sampling designs for various projects. Assuming that the puma population density on the study area is relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio is equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might be 22 adults, 11 males and 11 females. Also assuming that the total population contains 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might be 4 subadults and 13 cubs with equal sex ratios in a total population of 39 puma. If we achieve our logistical aim in the first 1―2 years (recognizing that the population might grow), then we should be able to quantify population characteristics and vital rates for a majority of the puma population in those years and build upon the tagged number in each subsequent year. Thus, our inferences will pertain to the large majority of the puma population, if not the population on the study area, instead of a relatively small sample of it. We anticipate it may take 2 years to mark the large majority of puma in the population. In addition, the study area is large and will require some time to learn to access it efficiently. Puma capture and handling procedures have been approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured puma will be examined thoroughly to ascertain sex and describe 118 �physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses; disease screening; hair (from various body regions) and fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Puma will be captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, walking, and possibly horse- or mule-back. When puma tracks ≤1 day old are detected, trained dogs will be released to pursue puma to capture. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent will be delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2005). Efficiency of the trap might be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Manchester, NH). A cage trap will be set only if a target puma scavenges on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers will continuously monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized puma will be restrained and monitored as described above. If non-target animals are caught in the cage trap, we will open the door and allow the animal to leave the trap. Foot-hold snares will be used to capture adults, subadults, and large cubs only when safe snare sites at puma kills can be located as described by Logan et al. (1999). Snares set at puma kills will be monitored continuously with VHF beacons on the snares from about 1 km distance. We will not set snares at sites where tracks indicate that other mammals (e.g., deer, elk, bear, bighorn sheep, livestock) are also active. Puma will be immobilized with Telazol injected into the caudal thigh with a pole syringe. Vital signs will be monitored during the handling procedures. Efficiency of snares might also be enhanced with the use of an automated call box with puma or prey vocalizations. Small cubs (≤10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are 119 �away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual puma is essential to a number of project objectives, including estimating vital rates and gathering movement data on puma to formalize designs for developing and testing enumeration methods. Adult, subadult, and cub puma will be marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna is permanent and cannot be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) will be inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old will be eartagged in only one pinna. Locations of GPS- and VHF-collared puma will be fixed about once per week from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using ArcGIS software. Adult and subadult female pumas will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada). Initially, GPS-collars will be programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for puma will provide precise, quantitative data on puma movements mainly to provide data to formalize study designs, to test assumptions for capture-mark-recapture methods for this project, and to assess the relevance of puma DAU boundaries. The GPS-collars also will provide basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and predation frequency on mule deer and elk. Subadult male pumas will be fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male puma reach adulthood on the study area, we will recapture them and fit them with GPS collars. VHF radio transmitters on GPS collars will enable researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters on GPS- and VHF-collars will have a mortality mode set to alert researchers when puma have been immobile for at least 3 hours so that dead puma can be found to quantify survival rates and agent-specific mortality rates by gender and age. We will attempt to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar (~100g, MOD 210, Telonics, Inc., Mesa, Arizona) when cubs weigh 2.3―11 kg (5―25 lb). Cubs with mass ≥11 kg can still wear these small expandable collars until they are about 12 months old. Cubs approaching the age of independence (~11―14 mo. old) may be fit with Lotek LMRT-3 VHF 120 �collars (~400 g) with expansion links. Cubs will be recaptured to replace collars as necessary. Monitoring radioed cubs allow quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Capture-Mark-Recapture: Capture-mark-recapture methods will be evaluated initially as a pilot study. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during capture-recapture occasions needed for population estimation. Therefore, we will capture and mark pumas prior to performing capture-recapture or re-sight occasions using using methods such as houndsmen teams or trail cameras. In addition, by marking puma before capture-recapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked on the study area. After cubs are weaned, the mothers’ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Capture-recapture occasions to estimate the population of independent puma may not begin until the end of the second winter or the third winter when we have a large majority of the puma population sampled and marked. Occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, performance of field methods (e.g., detection differences by sex or life stage as revealed by GPS data on collared puma), and precision of capture-recapture models used to estimate the puma population. Analytical Methods Population Characteristics: Population characteristics each year will be tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allow, age categories may be further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates will be estimated for GPS- and VHF-collared female puma directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male puma (Murphy et al. 1998). Methods will be tested in Dr. M. Douglas’s Laboratory (Colorado State University, Department of Fishery and Wildlife Biology). Survival and Agent-specific Mortality Rates: Radio-collared puma will provide known fate data which can be used to estimate survival rates for each age stage using the binomial survival model (Williams et al. 2001:343-344) or analyzed in program MARK (White and Burnham 1999, Cooch and White 2004). Agent-specific mortality rates can be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will be plotted with survival rate on age in months (Logan and Sweanor 2001:119). Population Estimates: Capture-recapture models will be evaluated initially as a pilot study to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of adult and subadult puma present in the survey area) and puma density (i.e., number of independent puma/100 km2) each winter― December through March― when snow facilitates detection and capture of puma, provided that we meet model assumptions. The December―March period also corresponds with Colorado’s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma that can be legally killed by recreational hunters. Furthermore, adults comprise the breeding segment of the population and subadults are non-breeders that are potential recruits into the adult population in ≤1 year. Thus, the sampling unit is the individual independent puma (~≥1 yr. old). 121 �General assumptions for closed capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). The robust design is a combination of closed and open models; thus, assumptions are a combination of the assumptions for closed and open population methods (Kendall 2001). To analyze capture-recapture data, closed, open, and the robust design models are available in program MARK. Akaike’s Information Criterion will be used to select the most parsimonious models based on AICc score ranks and the difference in AIC (∆AIC) between models (Burnham and Anderson 1998). MARK results also include estimates of abundance. Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of at least 0.5 for each animal per capture occasion. Capture simulations using MARK software (Cooch and White 2004) indicate that greater capture probabilities and more capture occasions yield more precise estimates. The capture probability for the simplest closed model [M(o)], which assumes that every member of the population has the same probability of capture (p) for each sampling period, suggest that for a population of 30 animals (i.e., adults plus subadult puma, which might be present by the end of year 2, see Puma Capture above) p must equal 0.5 for 3 capture occasions to attain a coefficient of variation (V) of 0.1. If 6 capture occasions are used, then a p of 0.3 might yield a V of 0.09. In addition, behavior, movements, survival and mortality of GPS- and VHF-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we might expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models and the robust design would be more appropriate (Pollock et al. 1990, Williams et al. 2001). Collared puma will allow us to determine the number of marked puma present in the search area each capture-recapture occasion. Furthermore, GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information, too. ArcView geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frames. Rate of Population Increase: Finite rates of increase (λ = Nt+1/Nt) between consecutive years and average annual rates of increase (r) for 3- to 5-year periods and levels of precision will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. Functional Relationships: Graphical methods will be used to examine functional relationships between puma density and vital rates, relationships between puma density estimated with direct capturerecapture methods (i.e., houndsmen teams) and possibly later (depending upon funding) by using estimates from DNA genotype or other mark- recapture methods. Linear regression procedures and coefficients of determination can be used to assess these functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not 122 �linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, can also be used to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Statistical analyses will be performed using SYSTAT and SAS software. The risk of committing a type I error (i.e., rejecting a null hypothesis that is actually true) will be controlled at alpha = 0.10 because we will normally have small population sizes (typical of studies of large obligate carnivores). The higher alpha level will increase the probability of detecting a change and reduce the risk of a type II error (i.e., failing to reject a null hypothesis that is false). For managers, the risk of a type II error is probably more important. RESULTS AND DISCUSSION Segment Objective 1 Field research to quantify puma population structure, vital rates, and causes of mortality for this report extended from August 2006 to July 2007. Our searches to detect puma presence covered the entire study area. We allocated most of our effort in areas where we consistently found tracks that we thought were of unmarked pumas, particularly in the northeast and southwest areas where we found little or no evidence of pumas during the previous 2 years. We made 54 puma captures during the period (9-10 adult females [1 adult female captured twice], 7 adult males [1 adult male probably captured 3 times, another captured twice], 1 subadult female, 0-1 other subadults, and 30 cubs [4 of them captured twice each]). As our main method to capture, sample, and mark adult and subadult pumas, we used trained dogs from November 13, 2006 to May 11, 2007. Those efforts resulted in 78 search days, 177-178 puma tracks detected, 45-47 pursuits, and 22 puma captures (Table 1). Puma capture efforts (i.e., search days) with dogs in this period was similar to our efforts in the 2 previous efforts (Table 2). But, the frequency of pursuits and puma captures has increased over the 2 previous periods. In addition, the number of adult and subadult pumas captured for the first time declined from 11 (Oct. 2005 to Apr. 2006) to 6 (this period). This included 1 adult female or subadult puma that could not be handled for safety reasons (see Tables 3 and 4). Of the pumas we captured, but could not handle, it is probable that we captured and marked 1 adult male (M51) and 1 adult female (F50) in subsequent capture efforts. Our puma capture efforts using ungulate carcasses and cage traps extended from August 2006 to July 2007. We used 64 road-killed mule deer, 7 road-killed elk, 3 puma-killed mule deer, and 1 puma killed elk at 26 sites to capture pumas 8 times (Tables 5). Pumas scavenged 16 of 71 (22.5%) of the roadkilled ungulate carcasses used for bait. This was similar to the results last years (16 of 80, 20%). Five pumas were captured, sampled, and marked for the first time by using dogs and cage traps, (Table 3). Fifteen recaptures of 13 marked pumas were made with the use of dogs and cage traps; GPS/VHF collars were replaced as needed (Table 6). We captured, sampled, and marked 26 cubs in 10 litters that were captured by hand at nurseries (Table 7). Search efforts throughout the study area also revealed the presence of at least 4 other independent females and 1 independent male. The tracks we found of those animals were too old to pursue (i.e., probability of capture with the dogs was negligible). We could separate the activity of those pumas from the GPS- and VHF- collared pumas in time and space. In addition, 2 of the females were in association with cubs. One female was followed by 2 cubs about 5 to 6 months old in December and January, when we captured but could not handle 1 or 2 of the cubs (Table 4). Another female was followed by 1 large cub (probably a male) likely 10 or more months old. And another female on the southwest portion of the 123 �study area might have been an adult if it were associated with a female cub (~6 mo. old) that was hit and killed by a vehicle on highway 62 on January 28, 2007. Our search and capture efforts during November 2006 through May 2007 enabled us to estimate a minimum count of 24 independent pumas detected on the Uncompahgre Plateau study area. The count included 16 females and 8 males. Of those, 12 adult females and 7 adult males were probably marked animals (79% of independent pumas detected). Of the remainder, 2 females were adults because they were followed by cubs, and 2 females and 1 male were of unknown independent status (i.e., either subadult or adult). Figure 2 indicates the estimated use areas of those independent pumas. Some of the animals range outside the borders of the study area, as indicated by movements of GPS- and VHFcollared pumas. There appears to be variation in puma numbers on the west and east slopes of the study area. The west slope count includes 8 independent pumas (5 females― 4 marked, 1 unmarked; 3 males― 2 marked, 1 unmarked). The east slope count includes 16 independent pumas (11 females― 8 marked, 3 unmarked; 5 males― all marked). Female home ranges overlap other female home ranges extensively, and are overlapped by male home ranges. Male home ranges overlap multiple female home ranges, and overlap other male home ranges somewhat. Anderson et al. (1992) studied pumas on the east slope of the Uncompahgre Plateau (i.e., GMU 62) during 1981 to 1988. Sport-hunting was banned during that study as it is in this study Reference Period. As our current effort results in larger samples and progresses in time through the Reference and Treatment periods, similarities and differences in results of the 2 research efforts, now separated by more than 15 years, should illuminate reliable knowledge for puma management in Colorado. Our current puma research on the Uncompahgre Plateau has been underway for 2.7 years (compared to 7 years of Anderson et al. 1992). Our data analysis at this stage of the research is not by any means exhaustive or complete, yet, our data set enables some preliminary comparisons with Anderson’s completed work (Anderson et al. 1992). In the Anderson et al. (1992) study, the average capture effort with dogs was 91.1 days per winter (range = 32 to 136, n = 7) resulting in an average capture effort of 13.9 days per puma. Of 189 pursuits of pumas, 110 (58%) were successful (either of radio-collared or non-collared animals). They captured 47 pumas for an average capture rate of 13.9 days per puma. Eight other pumas, all female cubs ≤7 months old, were caught in steel leg-hold traps by trappers, and were added to the study animal population. So far, in our 3 winters, the average effort is 79.3 days (range = 78 to 82). Of 123 pursuits, 50 (41%) were successful. We captured and GPS- or VHF-collared 25 pumas for the first time, yielding a capture rate of 10.0 days per capture. Other capture efforts and results between the 2 studies are not comparable, because Anderson et al. (1992) did not routinely attempt to capture pumas using cage traps or at nurseries like we are. In their effort, Anderson et al. (1992) captured 57 pumas, of which 49 were radio-collared. In our current effort, we captured, sampled, and marked 68 pumas, of which 61 were radio-collared. Puma mass recorded by Anderson et al. (1992:86) for pumas having an estimated age ≥24 months, averaged 61.6 kg for 8 males, (SD = 5.7, range = 51.8 to 70.8) and 44.5 kg for 14 females (SD = 3.6, range = 38.5 to 49.9). So far in our current study, mass for pumas ≥24 months old averaged 59.8 kg for 9 males (SD = 8.1, range 40 to 68 kg) and 38.4 kg for 11 females (SD = 4.9, range = 31 to 46). Sexual dimorphism has been described for puma throughout the species range (Young and Goldman 1946) and has been explained as a potential result of sexual selection (Logan and Sweanor 2001:109). Segment Objective 2 We captured, sampled, and marked 26 puma cubs produced by 10 females (Table 7). Twentythree of the cubs were examined at 8 nurseries when the cubs were 29 to 41 days old. The sexes were 17 124 �males and 6 females. Four other cubs, including 2 males and 2 females, were caught when they were about 158 to 215 day old. In addition to those offspring, 2 cubs, about 152 to 183 days old, were detected in association with an unmarked female that we pursued. One or 2 of those cubs were captured in different events; the female sex was determined for one of the cubs. But, neither cub could be handled safely for further sampling. The estimated birth month for the 10 litters were April (1), May (1), July (5), August (2), and September (1). During the past 27 months of this work we compiled data on puma reproduction that was heretofore not available for Colorado. We examined 38 cubs from 13 litters aged 29 to 42 days old where we were reasonably sure that we examined all the cubs at the nurseries. The sex ratio of the observed cubs was 21 males:17 females. The mean (±SD) and extremes of litter sizes were 2.84 (±0.99), 1 to 4. The distribution of puma births by month indicate puma births extending from March into September, with 18 of 20 births occurring May to September (Fig. 3). In addition, 8 birth intervals for 7 different female pumas averaged 14.99 months (SD = 3.40), and ranged from 11.7 to 20.5 months (Table 8). Based on observations (from GPS data) of associations between 4 mothers and putative sires, 4 gestation periods averaged 92.0 days (SD = 1.68), which is consistent with average puma gestation reported in literature (i.e., mean ± SD = 91.9 ± 4.1, Anderson 1983:33, mean = 91.5 ± 4.0 Logan and Sweanor 2001:414). Anderson et al. (1992:47) reported of “17 postnatal litters about 10-240 days in estimated age from 12 individual females, the mean (±SD) and extremes of litter sizes were 2.41 ± 0.8, 1-4”. “Because most postnatal young were not handled, their sex ratio is unknown” (Anderson et al (1992:48). In addition, because cubs were first observed at older ages, it is likely that some post-natal mortality had occurred. This is one explanation for smaller litters observed by Anderson et al. (1992). Anderson et al. (1992:47-48) found that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. Data on our 20 litters adds to Anderson’s data (Fig. 3), and indicates puma births in Colorado occurring in every month except January and November (so far). Our data suggests that the majority of puma breeding activity occurs February through June. Anderson’s observation of two 12-month birth intervals for one female (Anderson et al. 1992:48) is at the low range of our observations (above). Segment Objective 3 & 4 From December 2, 2004 (start of our research) to July 31, 2007, we radio-monitored 9 adult male and 12 adult female pumas to quantify survival and agent-specific mortality rates (Table 9). One adult male is known to have died. M4 was about 37 to 45 months old when he was killed by an unidentified male puma along the southeast boundary of the study area. We lost contact with 3 adult males apparently due to GPS/VHF collar failure (M1, M6, M27). Evidence in the field suggests that all 3 males might still be alive. One adult female is known to have died. F50 was about 29 to 31 months old when she apparently died of natural causes (exact agent could not be identified). We have radio-monitored 6 subadult pumas (Table 10). None of those died while we were monitoring them. F23 has become a breeding adult on the study area. M5 dispersed from his natal area and the study area at about 13 months old and went to the northwest slope of the Uncompahgre Plateau where he has apparently established an adult territory. M49 was orphaned at 9 months old when his mother F50 died. He has since dispersed from his natal area and the study area to the northeast slope of the Uncompahgre Plateau. We continue to monitor his status. On the other hand, we have lost contact with 2 subadult males and 1 subadult female. Puma M11 became a subadult at 13 months old and dispersed from his natal area at 14 months old. He was last located in the Dolores River valley between Stapletone and Stoner, Colorado, on December 14, 2006. F52 dispersed from the study area before we lost track of her in the area of the Black Canyon of the Gunnison in mid-May 2007. We lost track of M31 seven days after he was captured. He might have dispersed from the study area. Efforts to locate him by 125 �flying over and around the study area have not been successful. Dispersal rates and distances will be reported after we have compiled more complete data. In addition to the subadults discussed above, a nonmarked female puma about 18 to 24 months old was killed by a vehicle November 4, 2006 on highway 550, which forms the southeast boundary of our study area. The female appeared to be in good health (41 kg), was not pregnant, and was not lactating. Anderson et al. (1992) found that all 9 radio-collared male pumas dispersed from their natal areas, and 2 of 6 radio-collared females did not disperse from their natal areas (A. E. Anderson, Sep. 1993, errata for Anderson et al. 1992:61). Mean ± SD and range of dispersal distances (km) for 8 males, aged 10 to 13 months old at dispersal, were 86.2 ± 51.3, 23 to 151. For 4 females, aged 11 to 31 months old at dispersal, mean ± SD and range of dispersal distances (km) were 37.0 ± 15.3, 17 to 54 (Anderson et al. 1992:63). The current closure on sport-hunting on the study area and protection of marked pumas from sport-harvest on the buffer area on the northern portion of the Uncompahgre Plateau for the Reference Period appears to be operating, so far. None of the adult or subadult pumas wearing functional GPS- or VHF- collars have died due to human causes. This reference condition enables us to quantify puma survival rates and agent-specific mortality rates of adult and subadult pumas (i.e., harvest-age pumas) in the absence of direct human-caused mortality factors related to sport-hunting. So far, survival of radiomonitored adult and subadult pumas in the study and buffer areas appears to be high. In addition, the population sex and age structure can be examined in this reference condition. As indicated in Figure 4, the adult age structure appears to be indicative of high survival rates during the past 3 winters without sporthunting mortality. These data will be valuable in comparisons of sex and age structure during the Treatment Period and with the structure of harvested pumas in other regions of Colorado. But, we will wait for greater sample sizes (i.e., greater numbers of radio-monitored pumas and duration) before we develop more quantitative analyses of survival rates and agent-specific mortality rates and attendant inferences. Thirty-nine puma cubs (20 males, 19 females) have been monitored by radiotelemetry for varying durations (Table 11). Three males (M5, M11, M49) are known to have survived to the subadult or adult stages (Table 10). Seven cubs (F13, F18, M22, F33, F34, F36, and M37) were killed and eaten by other pumas. At least 4 of those were subjects of male-induced infanticide. Sex of the puma involved in each of the other cases could not be determined. In addition, cub F45 was apparently killed by coyotes when she was 280 to 283 days old. F45 was separated from her adopted mother, F2, and also appeared to be emaciated at the time of her death. Cub F17 was killed by a vehicle on highway 550 when she was about 330 days old. She was not radio-collared at the time, but GPS data from her mother, F16, showed her in the vicinity of her offspring. Thus, F17 was probably still dependent on F16. Three cub deaths were due to our research activities, namely problems with the expandable radiocollars. F35 died at 37 days old probably as a result of starvation caused when the transmitter box got caught in her mouth. M42 died at 106 days old apparently from complications of septicemia caused by an infection at the axis of the right foreleg. The cub put his right foreleg through the expandable collar and the collar material lacerated the right underarm as the animal grew, enabling the infection. M60 died at 49 days old, apparently from starvation. He apparently could not keep up with the movements of his mother, because he had put his right foreleg through the expandable collar, restricting his mobility. In addition to these deaths, 1 unmarked female cub (~6 mo. old) was killed by a vehicle on highway 62 on the southwest boundary of the study area on January 28, 2007 (mentioned earlier). We lost contact with a number of cubs because they shed their expandable radiocollars (Table 11). As this study proceeds, some cubs with which we have lost contact will be re-captured, re-observed, or harvested, and thus, provide more complete survival information. 126 �Clearly, data on cub survival and mortality are still preliminary. At this time, we can say that a minimum of 12 deaths occurred in 39 radio-collared cubs that we monitored for varying periods of time. This represents a minimum 0.31 mortality rate (12/39), including research-related causes. Subtracting the 3 research-related deaths, the minimum mortality rate is 0.25 (9/36). The main cause of death is being killed by another puma (0.78, 7/9). These rates should be interpreted as only rudimentary information. More complete data on cub survival and mortality will be forthcoming as our efforts continue. Anderson et al. (1992:50) reported on the fates of 21 radio-collared pumas (11 <24 months old, 10 ≥24 months old) from a total of 49 in the previous study where pumas were not hunted. Yet, 19 of those pumas died due to human causes, attributed to: legal kill outside the study area (7), capture-related (6), predator management (3), illegal kill (2), and suspected predacide (1). Other causes of mortality included, intraspecies strife (1) and disease (1). Actual age-stage and annual survival rates and agentspecific survival rates from our current effort will be compared with the Anderson et al. (1992) data set at a later date when we have greater samples, duration in research time, and more complete fate data (i.e., pumas currently without functional collars) to make such comparisons meaningful. Differences might be illuminated. For example, research of a puma population in New Mexico that was not hunted for 10 years indicated that the major cause of death for both sexes and all age stages of pumas was intraspecifies strife, and male-induced infanticide (Logan and Sweanor 2001). Although we have observed 3 male pumas disperse from natal areas, and no females disperse, our current research is too short in duration and samples too small yet to make meaningful comparisons with Anderson’s earlier effort, particularly regarding offspring dispersal rates, distances moved, and philopatry. Dispersal and philopatry have been explained as life history strategies in pumas that assist gene flow, colonization, population maintenance, and individual survival and reproductive success (Logan and Sweanor 2001). Thus, such strategies would be expected to be conserved, and expressed in puma populations at different times and different locations. In addition, because puma emigration and immigration (i.e., via dispersal) have been shown to be important processes in puma population dynamics (Sweanor et al. 2000), we need larger samples and longer research duration in this study to estimate those parameters. Segment Objective 5 Twenty adult pumas (7 males, 13 females) were fit with Lotek 4400S GPS collars since field research began in December 2004. The collars are programmed to fix 4 locations per day (00:00, 06:00, 12:00, and 19:00). The number of GPS locations per individual puma ranged from 113 to 2,759 (Table 12). Winter activity areas for GPS-collared pumas were estimated (Table 13) with fixed kernel and minimum convex polygon home range estimators (ArcView 3.2 Animal Movement Extension). These estimates are intended for use in developing the sampling frame for the puma population estimation pilot project (see Introduction). In addition, 5 adult and subadult pumas have been monitored with VHF radiocollars (Table 14). Anderson et al. (1992) provided an exhaustive analysis of seasonal puma home ranges and movements using data collected from VHF-collared animals during 1982 to 1988. We have not yet conducted an exhaustive analysis of adult puma home ranges and movements with the GPS data from our current puma research efforts. Instead, we provide only limited descriptive information in Tables 13, 14 and Fig. 2. Given the different types of location data and analytical methods, only broad descriptive comparisons might be made between the 2 studies at this time. Elemental similarities in home range attributes of pumas in the Anderson et al. (1992) research and our current effort, include: current home ranges of some puma overlap extensively with home ranges of puma documented by Anderson et al (1992), home ranges of male and female pumas are large, male home ranges are larger than female home ranges, male home ranges overlap multiple female home ranges, female home ranges overlap other female home ranges sometimes extensively, male home ranges overlap other male home ranges to a lesser 127 �extent than female home ranges. These characteristics are generally similar for pumas in other populations that have been studied with adequate intensity and duration (Beier and Barrett 1993, Logan and Sweanor 2001), and reflect behavioral strategies of male and female pumas that seem to contribute to individual survival and reproductive success (Logan and Sweanor 2001). Segment Objective 6 To investigate the potential that puma hunters might detect puma mothers away from their cubs, we continued gathering data on spatial associations of puma mothers and their cubs during the puma hunting season, which extends from November through March each winter in Colorado. Female pumas are fair game in Colorado, unless they are accompanied by 1 or more cubs. Mothers that are caught away from their cubs could be legally harvested. Such incidents would result in cubs being orphaned. Orphaned cubs that ≤6 months old could have a survival rate (to the subadult stage) of <0.05. Orphaned cubs 7 to 12 months old might have a survival rate (to the subadult stage) of about 0.7 (K. Logan, unpublished data). From November 7, 2006 to March 22, 2007 we located 1 to 4 radio-collared families of puma mothers and cubs from an airplane 49 times (Table 15).To assess whether mothers were apart or in close association with cubs, we needed to consider error in aerial locations. We recovered 7 puma radiocollars that we located from the airplane and fixed with GPS and then fixed the actual locations of collars on the ground with GPS. Range of location error was 20 to 520 m (mean = 282.86, SD = 164.75). We decided to use distances greater than the extreme high range of location error (520 m) as the metric to decide if puma mothers might be detected away from their cubs by hunters. Forty-one (83.7%) of observations located mothers and cubs ≤500 m apart, within the extreme margin of location error. Mothers were ≥520 m from their cubs during 8 (16.3%) of the observations (mean distance = 1,120 m, SD = 1,214.40, range = 616 to 4,101). The results for last winter were similar to our results the previous winter (15.2% and 16.3%, Table 15). Anderson et al. (1992:70-71) recorded 69 instances of simultaneous aerial locations of 7 pairs of puma mothers and dependent young. They reported that mothers and young were together in 21 (30.4%) of those instances, and they were 1 to 2.2 km apart in 48 (69.6%) of those instances. Segment Objective 7 Intensive effort to quantify puma use rates on ungulates by investigating puma GPS clusters continued during this period as an expansion of our pilot effort in the first research year (Logan 2005). That work proved the reliability of the GPS technology to allow us to gather quantitative information on ungulate prey use rates by pumas. In summary, 7 GPS-collared adult pumas (3 males, 4 females) used 61 mule deer, 48 elk, 2 porcupines, and 1 beaver found at 139 puma GPS clusters we investigated. The current work is a collaborative effort among CDOW Mammals Researchers (M. Alldredge, E. Bergman, C. Bishop, D. Freddy, and K. Logan). This was another pilot effort because it involved the development and testing of clustering parameters, clustering routine, associated computer programs, and field investigation protocols. Here we report only the general summary of the pilot field investigations of puma GPS clusters from October 2006 to April 2007. Five types of puma GPS clusters (Bergman et al. 2006) were investigated for 13 GPS-collared adult pumas (8 female, 5 male). The sample unit was the individual puma. The field effort focused on investigating a sample of randomly chosen clusters from each cluster type. In addition, when other non-random S1 clusters (i.e., clusters with the highest probability of ungulate use detection) were conveniently located to random clusters targeted for investigation, field personnel would attempt to investigate those clusters, too. A total of 257 clusters were investigated, including 63 non-random S1 clusters, and 173 random clusters (S1, S2, S3, S4, S5). Mule deer and elk were about equally important to pumas as food (Tables 16, 17, 18). Other mammals were rarely found. The next step in this investigation involves examining the performance of all aspects of the GPS cluster investigations and modifying cluster parameters and field protocols to maximize the 128 �efficiency and reliability of our continuing efforts to quantify ungulate use by pumas on the Uncompahgre Plateau. We will make further progress to designing and implementing a pilot project to investigate puma population estimation methods on the Uncompahgre Plateau. CDOW personnel Mat Alldredge, Chad Bishop, Ken Logan (Mammals Research) and Paul Lukacs (Terrestrial) met with Dr. Gary White (Colorado State University) June 21, 2007 to discuss possible approaches to estimating puma numbers by using capture-recapture methods and models. Another method we will explore, with the collaboration Mammals Researcher Chuck Anderson, is helicopter-based puma track probability sampling. We will evaluate the potential for collaborative research on puma-human relationships on the Uncompahgre Plateau with the developing CDOW puma-human research on the Colorado Front Range. To date, we have gathered location data on 10 (7 adult females, 3 adult males) GPS-collared pumas with activity areas on the developed southeast portion of our study area, which includes: Fairway Pines, Loghill Village, and Fisher Creek subdivisions, numerous other private homes, Fairway Pines golf course and driving range, all adjacent to Ridgeway State Park (Fig. 2). In addition, 2 new subdivisions and golf courses are underdevelopment on the southeast quarter of the Uncompahgre Plateau. This is the same area that Anderson et al. (1992:80) received 17 useable questionnaires on puma observations from residents, and also had some radio-collared pumas frequenting these same developments. Linking puma-human research on the Uncompahgre Plateau and Front Range provides opportunities for increasing sample size (i.e., puma numbers, study sites) and observing variation in puma-human relationships. We collaborated with Dr. Sue VandeWoude (CSU) to develop a pilot study titled: Puma concolor immune health― Relationship to management paradigms and disease. Tissue samples (i.e., blood, saliva, feces) from pumas we capture are collected and shipped to her laboratory for analyses. That project will be expanded to The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids. A description of that project and preliminary results on infectious disease surveillance on 21 pumas (13 female, 8 male) sampled on the Uncompahgre Plateau are presented in Appendix I. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 31 months of effort, 68 pumas have been captured, sampled, marked, and released. Of those 61 were radio-collared. Age stages we have monitored have included 21 adults, 6 subadults, and 46 cubs. Data from the marked animals are used to quantify vital rates and puma population dynamics in a reference situation (i.e., without sport-hunting off-take). Data on research efforts and puma capture, fates, reproduction, and activity areas are presented. During November 2006 through May 2007 a minimum count of 24 independent pumas were detected on the Uncompahgre Plateau study area. The count included 16 females and 8 males. Of those, 12 adult females and 7 adult males were probably marked animals (79% of independent pumas detected). Our efforts to quantify reproduction are yielding reliable data for Colorado on puma litter sizes, offspring sex ratios, and birth intervals. In this reference period, survival of adult and subadult pumas appears to be high. So far, the main cause of death in puma cubs is infanticide by males. Twenty adult pumas (13 females, 7 males) have been fitted with GPS collars, yielding 113 to 2,759 locations per puma. Our evaluations on the frequency that puma mothers on the Uncompahgre Plateau are away from their cubs >520 meters during the Colorado hunting season is low (15.2 to 16.3%). Intensive efforts to quantify puma use of ungulates on the Uncompahgre Plateau continued. Mule deer and elk appeared to be about equally important as puma food. 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Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. OTT, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. PIERCE, B. K., V. C. BLEICH, AND R. T. BOWYER. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. POLLOCK, K. H., S. R. WINTERSTEIN, C. M. BUNCK, AND P. D. CURTIS. 1989a. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. _____, S. R. WINTERSTEIN, AND M. J. CONROY. 1989b. Estimation and analysis of survival distributions for radio tagged animals. Biometrics 45:99-109. _____, J. D. NICHOLS, C. BROWNIE, AND J. E. HINES. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs 107:1-97. POJAR, T. M., AND D. C. BOWDEN. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. ROSS, P. I., AND M. G. JALKOTZY. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. STONER, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. SWEANOR, L. L., K. A. LOGAN, AND M. G. HORNOCKER. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. _____, L. L., K. A. LOGAN, J. W. BAUER, W. M. BOYCE, AND B. MILSAP. 2006 in review. Puma-human relationships in a California, USA state park. Biological Conservation. VAN BALLENBERGHE, V. 1983. Rate of increase of white-tailed deer on the George Reserve: a reevaluation. Journal of Wildlife Management 47:1245-1247. WATKINS, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. WILLIAMS, B. K., J. D. NICHOLS, AND M. J. CONROY. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. WHITE, G. C., D. R. ANDERSON, K. P. BURNHAM, AND D. L. OTIS. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. WORTON, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. YOUNG, S. P. AND E. A. GOLDMAN. 1946. The puma: mysterious American cat. The Wildlife Institute, Washington, D. C. Prepared by: __________________________________ Kenneth A. Logan, Wildlife Researcher 131 �Table 1. Summary of puma capture efforts with dogs from November 13, 2006 to May 11, 2007, Uncompahgre Plateau, Colorado. No. & type of No. & type of No. & I.D. or type of pumas Month No. puma tracks pumas pursued captured Search founda Days November 8 12 tracks: 3 male, 7 pursuits: 1 3 pumas captured 4 times: 1 male 7 female, 2 cub male, 4 females, (not handledb), F3 twice (not 2 cubs handled once), cub M42 (died) December 16 49 tracks: 7-8 13 pursuits: 3 5 pumas captured 6 times: 1 male male, 19-20 males, 4-5 (not handled), F50, 1 female or female, 22-23 females, 5-6 cubs subadult puma (not handled), cub cub M49 captured twice (not handled once), 1 cub (not handled) 3 pumas captured: 9-10 pursuits: 3 January 19 56-58 tracks: 19 males, 3 females, 1 male (not handled), M51, 1 male, 30 female, female cub (not handled) 3-4 cubs 7-9 cub February 8 4 tracks: 1 male, 3 pursuits: 1 2 pumas captured: 1 female, 2 cub female, 2 cubs cubs M44 & M56 March 14 31-33 tracks: 8 12 pursuits: 4 7 pumas captured: M29, F7, F23 male, 13 female, male, 5 females, (not handled), F24 (not handled), 10-12 cub 3 cubs cubs M43 (not handled), M56 (not handled), & 1 unmarked female cub (not handled) 1 pursuit: 1 male 0 puma captured April 11 23 tracks: 13-16 male, 5-8 female, 2 cub May 2 2 tracks: 2 female 1 pursuit: 1 0 pumas captured female 78 177-178 tracks: 45-47 pursuits: 22 captures of 16 individuals: 7 TOTALS 51-55 male, 7712 males, 18-19 pumas captured for the 1st time81 female, 45-50 females, 15-17 M49, F50, M51, M56, & 1 female cub cubs or subadult (not handled) & 2 female cubs (not handled), 1 adult male caught twice (not handled), 12 marked pumas were recaptured 15 times (including 4 caught for the 1st time this year). a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female. b Pumas are not handled for a variety of safety reasons: tree to dangerous to climb for researchers, puma treed near river, creek or cliff, puma might fall from tree after drug induction. 132 �Table 2. Summary of puma capture efforts with dogs, December 2004 to May 2007, Uncompahgre Plateau, Colorado. Pursuit effort Puma capture Effort to capture a puma for Period Track effort the first time detection effort Dec. 2, 109/78 = 1.40 35/78 = 0.45 14/78 = 0.18 11 pumas captured for first 2004 tracks/day pursuit/day capture/day time (minus M1, F3, & large to female) May 12, 78/35 = 2.23 78/14 = 5.57 11/78 = 0.14 capture/day 2005 day/pursuit day/capture 78/11 = 7.09 day/capture 7 pumas captured for first time 14/82 = 0.17 149/82 = 1.82 43/82 = 0.52 Nov. 21, 7/82 = 0.08 capture/day capture/day tracks/day pursuit/day 2005 to 82/7 = 11.71 day/capture 82/14 = 5.86 82/43 = 1.91 May 26, day/capture day/pursuit 2006 7 pumas captured for first time 22/78 = 0.28 45/78 to 47/78 177/78 to Nov. 13, 7/78 = 0.09 capture/day capture/day = 0.58-0.60 182/78 = 2.272006 pursuit/day 2.33 to tracks/day May 11, 78/7 = 11.14 day/capture 78/22 = 3.54 78/47 to 78/45 2007 day/capture = 1.66-1.73 day/pursuit Table 3. Adult and subadult pumas captured for the first time, sampled, tagged, and released from December 2006 to January 2007, Uncompahgre Plateau, Colorado. Puma Sex Estimated Mass Capture Capture Location I.D. Age (mo.) (kg) date method F50 F 25-27 31 12-14-06 Dogs West Fork Dry Creek M51 M 44-49 61 01-07-07 Dogs Lindsay Canyon F52 F 18-20 38 01-10-07 Cage trap Paco-Chu-Puk Campground, Ridgway State Park F54 F 30 36 01-12-07 Cage trap Pleasant View, Pleasant Valley M55 M 24-36 62 01-21-07 Cage trap Dallas Creek, Pleasant Valley 133 �Table 4. Pumas that were captured with aid of dogs, but were not handled and marked at that time for either safety reasons or they escaped, November 2006 to May 2007, Uncompahgre Plateau, Colorado. Puma Age Capture Location Comments sex stage date Male adult 11-13-06 East Fork Unmarked puma climbed difficult spruce tree beside Dry Creek creek. This puma is probably M51 (captured & marked 01-07-07, identified with distinguishing notch in margin of right pinna). Female, adult 11-21-07 Dry Creek Puma F3 climbed dangerous tree adjacent to creek. F3 Basin Unknown cub 12-02-06 Dry Creek Unmarked cub was bayed on edge of high cliff. This sex Basin cub was member of family comprised of an adult female & 2 cubs, which was probably pursued again on 01-25-07. Unknown subadult 12-05-06 Dry Creek This unmarked puma was treed on the same day that Basin we captured & handled cub M49. This puma could sex male or have been M49’s mother or a subadult puma (sex female, uncertain). or adult female Male adult 12-18-06 Lower Unmarked puma climbed difficult fir tree on steep East Fork slope. This puma was probably M51 (captured & Dry Creek marked 01-07-07, identified with distinguishing notch in margin of right pinna). Female cub 01-25-07 Piney Unmarked cub climbed tree. Anesthesia was Creek attempted with pole syringe. Cub jumped from tree, apparently with subcutaneous injection. Cub was pursued unsuccessfully by researchers on foot. Dogs were not released on partially sedated cub for safety reasons. This cub was member of family comprised of an adult female & 2 cubs, which was initially pursued on 12-02-06. Female cub 03-01-07 Dolores Unmarked cub associated with puma F2; was Canyon probably her unmarked cub, sibling of M38. Cub climbed difficult spruce tree adjacent to creek. Female, adult 03-07-07 San Puma F23 climbed a cottonwood tree close to the F23 Miguel San Miguel River. We did not attempt to anesthetize River at F23 to replace her non-functional GPS collar for Pinyon safety reasons. 134 �Table 5. Summary of puma capture efforts with ungulate road-kill baits, puma kills, and cage traps from August 2, 2006 to July 26, 2007, Uncompahgre Plateau, Colorado.a Month No. of Puma activity & capture effort resultsb Sites August 5 Puma scavenged a mule deer carcass on 08-07-06. Cage trap set. Black bear caught & released. Puma F16 was in the area. Puma did not return. September 4 No puma activity detected. October 10 Male puma scavenged a mule deer carcass 10-27-06. Cage trap set & monitored 10-27 to 28-06. Puma did not return. November 12 Male puma scavenged a mule deer carcass on 11-06-06. Set & monitored cage trap 11-06 to 10-06. Puma F16 walked around cage trap, but did not enter on 11-09-06. January 3 Subadult female F52 captured at adult female mule deer she killed 01-10-07, Ridgway State Park. Adult female F54 and her cub F53 were captured at an adult female mule deer kill 01-12-07, Pleasant Valley. Adult male puma M55 was captured at a mule deer fawn kill 01-21-07, Dallas Creek. March 7 Adult male puma M29 was temporarily caught in cage trap set on an adult elk cow he had killed 03-15-07. But, M29 escaped out of back of the trap as researchers arrived. An ear-tagged male cub of puma F3 was observed feeding on a mule deer carcass 03-26-07; F3’s family was in the vicinity. Female puma scavenged on a mule deer carcass 03-29-07. Cage trap was set. Puma F30 was recaptured, and her VHF collar was changed to a GPS collar. April 7 Male puma, probably M29, scavenged a mule deer carcass ~04-01-07. Female puma walked by same carcass (as above) on ~04-02-07, but did not feed. During ~04-05 to 08-07 a puma completely scavenged the same mule deer carcass. Puma F3 and her cubs consumed a mule deer carcass 04-06 to 10-07. Puma F30 consumed a mule deer fawn carcass 04-08-07. Puma F30 consumed a mule deer carcass 04-24-07. Male puma scavenged on mule deer carcass 04-10-07. Cage trap set. Male puma M55 walked up to cage trap (GPS data), but did not enter. Pumas F30 & M55 fed on a mule deer carcass 04-17 to 20-07. Female puma scavenged a mule deer carcass 0423-07. Cage trap set. Puma F8 was recaptured; her non-functional GPS collar was replaced with a VHF collar. Male puma M55 scavenged a mule deer carcass 04-30-07. Female puma scavenged a mule deer carcass. 04-27-07. Cage trap set. Puma F16 recaptured, and her GPS collar was changed with a new GPS collar. May 6 Male puma M55 scavenged on a mule deer carcass 05-08-07. Female puma killed a mule deer doe 05-10-07. Cage trap set. Puma did not return or did not enter the trap. Male puma M55 scavenged a mule deer carcass 05-22-07. June 5 Male puma M55 scavenged on an elk carcass 06-06-07. July 4 No puma activity detected. a We used 64 road-killed mule deer, 7 road-killed elk, 3 puma-killed mule deer, and 1 puma-killed elk at 26 different sites. Of the road-killed ungulate baits, 16 of 71 (22.5%) were scavenged by pumas. b Eight pumas were captured, including: 2 adult males (M29, M55), 4 adult females (F54, F30, F8, F16), 1 subadult female (F52), and 1 female cub (F53). 135 �Table 6. Pumas recaptured with dogs and cage traps, November 2006 to April 2007, Uncompahgre Plateau, Colorado. Puma I.D. F3 F3 M42 Recapture date 11-21-06 11-22-06 11-27-06 M49 M44 M43 M56 F7 F23 M29 F24 M29 F30 F8 F16 Mass kg Observed 41 4.8 Estimated Age (mo.) 63 63 3.5 Capture Method Dogs Dogs Dogs 12-12-06 02-14-07 03-01-07 03-01-07 03-03-07 03-07-07 03-05-07 03-22-07 03-27-07 03-29-07 Observed Observed Observed Observed 33 Observed Observed Observed 60 37 5 6 6.5 6.5 88 31 91 71 91 44 Dogs Dogs Dogs Dogs Dogs Dogs Cage trap Dogs Dogs Cage trap 04-23-07 04-28-07 37 48 46 51 Cage trap Cage trap Process None Changed GPS collar Cub died due to infection & stress None None None None Changed GPS collar None None None Changed GPS collar Changed VHF collar to GPS collar Changed GPS collar Changed GPS collar Table 7. Puma cubs sampled July 2006 to August 2007 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M38 M July 29, 2006 41 2.9 F2 67 Unm.b F “ 215 Observed “ “ M39 M August 13, 2006 29 1.9 F8 37 F40 F “ “ 1.8 “ “ F41 F “ “ 1.3 “ “ M42 M “ “ 1.5 “ “ M43 M August 13, 2006 33 2.4 F7 82 M44 M “ “ 2.5 “ “ F45 F “ “ 1.7 “ “ M56c M “ 185 9.6 “ “ M46 M September 17, 2006 31 2.2 F3 61 M47 M “ “ 2.2 “ “ M48 M “ “ 2.5 “ “ M49c M July 1, 2006 158 10.0 F50 21 c F53 F July 1, 2006 196 15.0 F54 24 F57 F April 16, 2007 35 2.3 F25 94 M58 M May 24, 2007 34 2.3 F16 52 F59 F “ “ 2.2 “ “ M60 M “ “ 2.0 “ “ M61 M “ “ 1.7 “ “ M62 M July 14, 2007 34 1.8 F24 75 M63 M “ “ 2.1 “ “ M64 M “ “ 1.7 “ “ M65 M “ “ 1.9 “ “ F66 F July 17, 2007 37 2.1 F30 48 M67 M “ “ 3.0 “ “ M68 M “ “ 3.3 “ “ a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location foci for mothers at nurseries. b This unmarked female cub was captured on 03-01-07 in association with adult female puma F2. This cub could be the sibling of cub M38, offspring of F2, which we were not able to capture previously with M38 (its tracks were observed). c Estimated ages of M49 and F53 were based on morphometric comparisons with known-age cubs (Logan and Sweanor 2001, and unpublished data). 136 �Table 8. Puma reproduction, Uncompahgre Plateau, Colorado, 2004-2007. Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) Dates pairs consortedb Estimated birth datec Estimated birth interval (mo.) Estimated gestation Observed number of cubsd F2 53 05/28/05 3 F2 67 07/29/06 14.0 2 F3 36 08/01/04 1 F3 50 M6 37 06/22-24/05 09/26/05 13.8 93-95 2 F3 62 09/17/06 11.7 3 F7 67 05/19/05 2 F7 82 08/13/06 14.9 4 F8 24 06/26/05 2 F8 37 08/13/06 13.4 4 F16 32 09/22/05 4 F16 52 05/24/07 19.9 4 F23 21 05/30/06 3 F24 75 M29 92 04/12-15/07 07/14/07 90-93 4 F25 74 08/01/05 1 F25 94 04/16/07 20.5 1 F28 36 06/09/06 2 F28 48 M29 88 12/27-29/06 03/30/07 11.7 92-93 ≥2 tracks F30 48 M55 34 04/16-20/07 07/17/07 88-92 3 F50 21 07/01/06 1 F54 24 07/01/06 1 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data. c Estimated birth dates were indicated by GPS data of mothers at nurseries. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 6 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. 137 �Table 9. Summary for individual adult puma survival and mortality, December 2004 to July 2007, Uncompahgre Plateau, Colorado. Puma I.D. M1 M4 M5 M6 M27 M29 M32 M51 M55 F2 F3 F7 F8 F16 F23 F24 F25 F28 F30 F50 F54 Monitoring span 12-08-04 to 08-1606 01-28-05 to 12-2805 08-01-06 to 07-3107 02-18-05 to 02-2206 03-10-06 to 07-0506 04-14-06 to 07-3107 04-26-06 to 07-3107 01-07-07 to 07-3107 01-21-07 to 07-3107 01-07-05 to 07-3107 01-21-05 to 07-3107 02-24-05 to 07-3107 03-21-05 to 07-3107 10-11-05 to 07-3107 02-05-06 to 03-0707 01-17-06 to 07-3107 02-08-06 to 07-3107 03-23-06 to 07-3107 04-15-06 to 07-3107 12-14-06 to 03-2607 01-12-07 to 07-3107 No. days 616 333 365 369 117 Status: Alive/Lost contact/Dead; Cause of death Lost contact― failed GPS/VHF collar. M1 ranged principally north of the study area. Dead; killed by a male puma. Estimated age at death 37―45 months. Alive. Born on study area; offspring of F3. He was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months. Lost contact― failed GPS/VHF collar. 473 Lost contact― failed GPS/VHF collar. M27 ranged principally north of the study area. Alive. 461 Alive. 205 Alive. 191 Alive. 935 Alive. 921 Alive. 887 Alive. 862 Alive. 658 Alive. 396 Lost contact― failed GPS/VHF collar. 560 Alive. 538 Alive. 495 Alive. 472 Alive. 102 Died of natural causes; exact agent unknown. 200 Alive. 138 �Table 10. Summary of subadult puma survival and mortality, December 2004 to June 2006, Uncompahgre Plateau, Colorado. Puma Monitoring No. days Status: Alive/Survived to adult stage/ Lost contact/Dead; I.D. span Cause of death M5 09-16-05 to 308 Alive; independent and dispersed from natal area at 13 06-30-06 months old. Established adult territory on northwest slope of Uncompahgre Plateau. M11 06-21-06 to 176 Lost contact. Independent at 13 months old. Dispersed from 12-14-06 natal area at 14 months old. Last location in Dolores River valley Dec. 14, 2006. F23 01-04-06 to 31 Alive; survived to adult stage; gave birth to first litter at ~21 02-04-06 months old. M31 04-19-06 to 7 Lost contact. Probable disperser. M31’s estimated age at 04-26-06 capture was 25 months, at the lower margin of puberty for puma. He may have been a dispersing subadult, and could have moved away from the study area. M49 03-26-07 to 127 M49 was orphaned at about 9 months old, when his mother 07-31-07 F50 died of natural causes. He dispersed from his natal area at about 10 months old and has been ranging on the northeast slope of the Uncompahgre Plateau. F52 01-10-07 to 125 Lost contact. Dispersed from study area as a subadult. F52’s 05-15-07 last location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon. 139 �Table 11. Summary for individual puma cub survival and mortality, December 2004 to 2007, Uncompahgre Plateau, Colorado. Status: Alive/Survived to subadult stage/ Lost Estimated survival Age to last Puma Estimated contact/Disappeared/ Dead; Cause of death span from 1st monitor date I.D. Age at alive or at capture capture to fate or death (days) (days) last monitor date Mother I.D. M5 183 02-04-05 to 07-31-07 907 F3 F9 F10 31 31 329 207-246 M11 31 06-27-05 to 4-19-06 06-27-05 to 11-2005― 12-29-05 06-27-05 to 12-14-06 F12 42 07-01-05 to 12-0805― 01-26-06 245-294 F13 F14 42 26 07-01-05 to 08-28-05 07-22-05 to 02-0706― 03-10-06 100 226-257 M15 F17 26 34 07-22-05 to 06-06-06 10-26-05 to 08-18-06 345 330 F18 34 301-308 M19 M20 F21 M22 34 34 37 37 M26 183 10-26-05 to 0720―27-06 10-26-05 to 07-27-06 10-26-05 to 05-24-06 11-02-05 to 06-30-06 11-02-05 to 12-2105― 12-22-05 02-08-06 to 03-21-06 306 244 277 86-87 Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old . Lost contact― shed radiocollar 04-19-06―04-26-06. Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 12-30-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Lost contact― shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 12-08-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Dead; killed and eaten by a puma (sex unspecified). Lost contact― shed radiocollar 01-20-06―01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 0207-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-06-06―06-14-06. Dead. Lost contact― shed radiocollar 06-06-06―06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Dead; probably killed by another puma. Multiple bite wounds to skull. 10 mo. old. Born 9/22/05 Lost contact― shed radiocollar 07-27-06―08-02-06. Lost contact― shed radiocollar 05-24-06―05-25-06. Alive. Dead; killed and eaten by male puma 12-21-05―12-22-05. F16 F16 F3 F3 224 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 535 140 F2 F2 F2 F7 F7 F8 F8 F16 F16 �Puma I.D. Estimated Age at capture (days) Estimated survival span from 1st capture to fate or last monitor date Age to last monitor date alive or at death (days) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death F33 31 06-30-06 to 07-31-06 62 F34 31 06-30-06 to 07-31-06 62 F35 F36 31 29 06-30-06 to 07-07-06 07-08-06 to 07-28-06 38 74 M37 29 07-08-06 to 07-28-06 74 M38 M39 41 29 165 9 226 M40 29 9 226 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 F41 29 09-08-06 to 02-20-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. 24 F8 M42 M43 M44 29 33 33 09-11-06 to 11-27-06 09-15-06 to 03-01-07 09-15-06 to 02-14-07 77 167 152 F45 33 09-15-06 to 5-20 to 23-07 280-283 M46 31 10-18-06 to 12-15-06 58 M47 31 10-18-06 to 12-15-06 58 M48 31 10-18-06 to 12-15-06 58 Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 10-13-06 (collar found). Dead; research-related fatality.b Treed, visually observed 03-01-07. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 20-06. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. 141 Mother I.D. F23 F23 F23 F28 F28 F2 F8 F8 F7 F7 F7 F3 F3 F3 �Puma I.D. Estimated Age at capture (days) Estimated survival span from 1st capture to fate or last monitor date Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Age to last monitor date alive or at death (days) Mother I.D. M49 153 12-05-06 to 07-31-07 238 M49 was orphaned when his mother died on about 03-26-07. F50 F53 183 01-12-07 to 02-23-07 42 Lost contact― shed radiocollar 2-23-07. F54 M56c 183 02-14-07 to03-01-07 15 Lost contact― shed radiocollar 2-27-07. M56 observed 03-01-07. F7 (?) F57 35 05-21-07 to 06-06-07 16 Lost contact― shed radiocollar 06-07-07. Live mode 06-06-07. F25 M58 34 06-27-07 Not radio-collared. F16 F59 34 06-27-07 to 08-21-07 55 Alive. F16 M60 34 06-27-07 to 07-11-07 14 Dead; research-related mortality.d F16 F61 34 06-27-07 to 06-29-07 2 Radiocollar malfunction. F16 M62 34 08-17-07 Not radio-collared. F24 M63 34 08-17-07 Not radio-collared. F24 M64 34 08-17-07 Not radio-collared. F24 M65 34 08-17-07 Not radio-collared. F24 F66 37 08-23-07 Radio-collared. F30 M67 37 08-23-07 Not radio-collared. F30 M68 37 08-23-07 Not radio-collared. F30 a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, possibly restricting movement. 142 �Table 12. Numbers of GPS locations for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to July 2007. Puma I.D. M1 M4 M6 M27 M29 M51 M55 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a No. locations M M M M M M M F F F F F F F24 F25 F28 F30 F50 F52 F54 F F F F F F F adult adult adult adult adult adult adult adult adult adult adult adult subadult, adult adult adult adult adult adult subadult adult 12-08-04 to 07-20-06 01-28-05 to 12-28-05 02-18-05 to 11-23-05 03-11-06 to 06-21-06 04-14-06 to 07-30-07 01-07-07 to 07-30-07 01-21-07 to 07-22-07 01-07-05 to 07-11-07 01-21-05 to 07-30-07 02-24-05 to 07-30-07 03-21-05 to 10-04-06 10-12-05 to 06-12-07 01-04-06 to 02-04-06 02-05-06 to 07-17-06 01-17-06 to 07-25-07 02-09-06 to 07-02-07 03-24-06 to 07-11-07 03-30-07 to 07-25-07 12-14-06 to 03-26-07 01-10-07 to 05-08-07 01-12-07 to 07-20-07 1,864 910 926 316 1,165 630 558 2,759 2,474 2,401 1,516 1,797 113 511 1,816 1,408 1,394 381 361 383 615 a Acquisition rate average, range, nb 76, 69―84, 14 70, 57―84, 10 84, 73―93, 9 77, 67―84, 3 69, 56―81,13 76, 66―87, 6 79, 68―91, 6 75, 43―91, 30 78, 55―90, 24 68, 26―92, 27 67, 41―81, 17 73, 41―90, 23 79, 45―92, 6 82, 65―93, 18 69, 55―87, 16 74, 53―89, 16 83, 58―94, 4 87, 76―94, 4 83, 70―92, 3 82, 77―86, 6 GPS collars on pumas are remotely downloaded at approximately 1-month intervals. The last date in Dates monitored includes last location from the last GPS data download for an individual puma in this report. b n = number of remote downloads. Table 13. Estimated use areas of GPS-collared pumas during November through March, Uncompahgre Plateau, Colorado.a Puma I.D. No. locations Time span No. months 95% Fixed kernel (km2) 50% Fixed kernel (km2) F2 F3 F7 F8 F16 F24 F25 F28 F50 M1 M29 M51 151 130 114 147 144 150 147 146 103 149 97 85 11-01-06 to 03-31-07 11-22-06 to 03-31-07 11-01-06 to 03-31-07 11-01-05 to 03-31-06 11-01-06 to 03-31-07 11-01-06 to 03-31-07 11-01-06 to 03-31-07 11-01-06 to 03-31-07 12-14-06 to 03-26-07 11-01-05 to 03-31-06 11-01-06 to 03-31-07 01-07-07 to 03-31-07 5 4.3 3.9b 5 5 5 5 5 3.4 5 3.4c 2.8 78.6 138.9 66.7 33.7 53.6 117.7 52.0 61.8 70.0 1,132.7 349.1 231.0 13.3 12.2 10.6 5.4 7.0 18.9 6.5 6.3 15.8 302.3 25.0 31.0 a 100% Minimum convex polygon (km2) 102.3 164.0 66.8 43.3 59.9 148.9 79.8 105.4 91.2 779.8 379.0 281.2 Use areas were estimated by using the Animal Movement extension in ArcView 3.2. One location per day was randomly chosen from up to 4 locations fixed per day per puma to reduce autocorrelation. b Due to GPS collar failure, GPS locations were not fixed for F7 from 01-30 to 03-02-07. C Due to GPS collar failure, GPS locations were not fixed for M29 from 02-09 to 03-26-07. 143 �Table 14. VHF-radio-collared independent pumas on the Uncompahgre Plateau, Colorado, 2007. Puma I.D. M5 Sex Age stage Dates monitored No. locations M F8 F30 M31 M32 F F M M Subadult Adult Adult Adult Subadult Adult 09-16-05 to 07-31-06 08-01-06 to 07-30-07 04-23-07 to 07-30-07 04-15-06 to 03-29-07 04-09-06 to 04-26-06 04-26-06 to 07-30-07 36 37 14 43 2 50 Table 15. Summary of puma mother and cub associations by distance (m) during airplane flights, November through March each winter. Monitoring period Month Nov. 9, 2005 to March 29, 2006 Nov. Dec. Jan. Feb. Mar. Nov. 7, 2006 to March 22, 2007 Nov. Dec. Jan. Feb. Mar. Totals a Totals No. flights No. puma familiesa Ages of cubs (mo.) No. observations with mothers & cubs ≤520 m apart 3 4 5 4 2 18 4 4 5 4 3 20 4 4 4 5 5 4―5 4 4 3 4 1 1―4 2―6 3―7 4―8 5―9 6―10 2―10 2―3 2―5 4―6 5―7 8 2―8 10 16 16 16 9 67 10 11 9 9 2 41 No. observations with mothers & cubs >520 m apart 2 4 4 2 0 12b 1 1 3 2 1 8c All puma mothers wore GPS-radiocollars. At least 1 cub in the litter wore a VHF radiocollar. b Mean = 1,060 m, SD = 325.99, range = 650―1,600. C Mean = 1,120 m, SD = 1,214.40, range = 616―4,101. Table 16. General results of puma GPS cluster investigations pilot project, October 2006 to April 2007, Uncompahgre Plateau, Colorado. Cluster Types Investigated S1 Non-random S1 Random S2 Random S3 Random S4 Random S5 Random Totals No. 63 84 11 29 30 40 257 Animals found at all clusters Mule deer Elk Beaver Coyote Total 144 No. 63 58 1 2 124 Animals found at random clusters Mule deer Elk Coyote Total No. 33 31 2 66 �Table 17. Sex and age classes of mule deer found at puma GPS cluster investigations, October 2006 to April 2007, Uncompahgre Plateau, Colorado. Sex & age of mule deer Fawn Yearling 2+ year Unknown age 1+ yr. Unknown age Totals Female 0 1 6 1 0 8 All clusters Male Unknown 1 18 6 3 6 1 1 6 0 13 14 41 Female 0 1 5 1 0 7 Random clusters Male Unknown 1 10 3 2 1 1 1 4 0 3 6 20 Table 18. Sex and age classes of elk found at puma GPS cluster investigations, October 2006 to April 2007, Uncompahgre Plateau, Colorado. All clusters Random clusters Sex & age of elk Female Male Unknown Female Male Unknown Calf 3 1 18 1 0 10 Yearling 13 2 3 7 1 3 2+ year 4 3 4 1 2 3 Unknown age 1+ yr. 0 0 4 0 0 2 Unknown age 0 0 3 0 0 1 Totals 20 6 32 9 3 19 145 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Estimation Methods for Monitoring Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Habitat Maps Puma―Prey Relationships Models Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this report for the puma management goal (at top). 146 �! ( ! ( ! ( ! ( ! ( Clifton County Boundary Highways Study Area ! ( ! ( ! ( ! ( ! ( Delta ! ( M1 ! ( UF UF M32 F50 ! ( UF Montrose F8 M27 M51 F3 F23 M29 ! ( ! ( F7 F28 F2 F24 F30 M6 M55 F16 F25 F54 ! ( Norwood ! ( Ridgeway UF ! ( UM ! ( 0 5 10 20 30 40 Kilometers ! ( Figure 2. Schematic of home ranges of GPS-collared (polygons) and non-collared (ellipses) independent pumas (adults and subadults), intended to show the minimum count and location of independent pumas detected on the study area during November to May period, 2006-2007, Uncompahgre Plateau, Colorado. M & F signify male & female, followed by the identification number of the puma. UF and UM signify uncollared and unsampled female and male pumas, respectively. 147 �5 No. Litters 4 3 2 1 Ja n. Fe b. M ar . Ap r. M ay Ju ne Ju ly Au g. Se p. O ct . No v. De c. 0 Births 2005-07 Births 1983-87 Figure 3. Puma births (n = 20 litters) detected by month during the current research effort, 2005 to 2007, and during the earlier effort by Anderson et al. (1992), 1983 to 1987 (n = 10 litters). Age structure of adult pumas captured and sampled on the Uncompahgre Plateau, Colorado, to March 31, 2007. No. Puma 4 3 Female 2 Male 1 0 2 to 3 >3 to >4 to >5 to >6 to >7 to >8 to >9 to 10+ 4 5 6 7 8 9 10 Age (Years) Figure 4. Age structure of adult pumas captured and sampled on the Uncompahgre Plateau, Colorado, on March 31, 2007, after 3 winters (Nov. through Mar., 2004-05 to 2006-07) of protection from sporthunting mortality. In addition, no other human-caused mortalities have been documented in the GPS/radio-collared sample of adults. This age structure assumes that puma M1, M6, and M27 (which had non-functional GPS collars) were alive. Evidence was found on the ground that indicated that all 3 of those males were alive. Pumas M1, M5, and M27 range north of the study area and were protected from legal sport-harvest. Mean ± SD of adult female and adult male ages, respectively: 4.90 ± 1.80 yr. (58.82 ± 21.62 mo.), 4.76 ± 1.62 yr. (57.12 ± 19.39 mo.). 148 �APPENDIX I COLLABORATIVE PROJECT ON DISEASE SURVEILLANCE IN WILD FELIDS. College of Veterinary Medicine and Biomedical Sciences Department of Microbiology, Immunology & Pathology 1619 Campus Delivery Fort Collins, CO 80523-1619 970-491-6144 (voice) 970-491-0603 (fax) TO: Ken Logan, Mammals Researcher, Colorado Division of Wildlife, Montrose, CO. FROM: Sue VandeWoude, DVM, Associate Professor, DMIP RE: Disease Seroprevalence in UP Pumas DATE: August 26, 2007 Attached please find the consolidated report on infectious disease surveillance for the mountain lion samples you have provided to our laboratory as an adjunct to your CDOW ongoing studies. Our laboratory has performed puma-lentivirus (PLV) antibody screening using a sensitive western blot assay developed in our laboratory and found 13 of 18 samples conclusively positive (72%), with two additional samples inconclusive and one not tested. Dr. Michael Lappin, a veterinary internal medicine specialist with expertise in feline infectious disease has tested a subset of 6 samples for antibodies to Feline Calicivirus (FCV), Feline Herpes Virus (FHV), Feline parvovirus (FPV), Toxoplasma gondii (IgM, indicating recent infection, IgG indicating past exposure), and Bartonella hensalae (the agent associated with cat scratch disease). At least one of six animals tested has been positive for each of these agents. Further results are pending from the remaining samples you have provided for these 5 assays. In addition, Dr. Martin Scriefer at Fort Collins CDC has also tested 6 animals for evidence of antibodies to the agent responsible for plague (Yersinia pestis). Interestingly, 3 of 6 animals demonstrate significant exposure to this agent as well. These specific agents were selected for analysis in order to provide a variety of types of agents (viruses: PLV, FCV, FHV, FPV; bacteria: Bartonella henselae and Yersinia pestis; and coccidian: T. gondii), a variety of modes of transmission (direct intra-specific contact, PLV; direct contact with domestic cats, FCV, FHV, FPV; arthropod transmission, B. henselae, Y. pestis; prey ingestion, T. gondii, Y. pestis). Further, at least three of these agents (PLV, FCV, B. henselae) result in chronic infections, allowing the possibility of determining genetic relatedness among organisms isolated from different individuals, and three of these agents (B. henselae, Y. pestis, T. gondii) are also potential zoonotic agents. As you are aware, our laboratory has recently been awarded a 5 year NSF Ecology of Infectious Disease grant entitled, “The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids”, with co-PI Dr. Kevin Crooks, an associate professor in the Warner College of Natural Resources at CSU. The aims of this grant are to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in large carnivore species as described on the following page. The letter of support provided by you and Dave Freddy were pivotal in demonstrating a large cohort of capable and active field collaborators willing to provide samples to support our studies. The mountain lion field work being led by your team, and the newly initiated studies by your colleague, Dr. Mat Alldredge, have provided us with renewed enthusiasm for developing our collaborations to support the goals of our study. We foresee the opportunity to interact in a mutually beneficial partnership to further the goals of all of our studies, and to maximize the information that can be gleaned about these important and ecologically significant species. We anticipate that the data we are generating will be useful for comparative seroprevalence of different geographic populations of bobcats and pumas, and for genetic phenotyping of pathogens to compare relationships among diseases spread by arthropod vectors, domestic cats, feral rodents, and inter-specific contacts. As we discussed during your recent visit to CSU, these samples are most valuable to us if we can receive them directly as quickly as possible after collection. I have provided an SOP providing information about the types of samples that 149 �will be most valuable, and a draft of a ‘permissions’ document that you can use with each sample submission to provide us with guidance for any testing that is permissible on the materials we receive. This latter document will be filed and recorded electronically. We will continue to provide annual updates and communications about any publications that utilize the data resulting from your samples. Again thank you for providing these extremely valuable samples, and we look forward to our continued collaborations. Sincerely, Sue VandeWoude THE EFFECTS OF URBAN FRAGMENTATION AND LANDSCAPE CONNECTIVITY ON DISEASE PREVALENCE AND TRANSMISSION IN NORTH AMERICAN FELIDS PROJECT SUMMARY Sue VandeWoude (co-PI), Kevin Crooks (co-PI), Michael Lappin, Mo Salman, Walter Boyce, Ken Logan, Mat Alldredge, Carolyn Krumm, Don Hunter, Lisa Lyren, Seth Riley, Jennifer Troyer The objective of this study is to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in large carnivore species--ecologically pivotal organisms that are sensitive to human disturbances. Bobcats, puma, and domestic cats will be evaluated simultaneously in three divergent ecosystems: high mountain desert (Colorado), everglades (Florida), and Mediterranean scrub habitat (California). The research will: 1) assess the relationship between habitat fragmentation and prevalence of viral, bacterial, and parasitic pathogens across a gradient of urbanization, 2) use transmission dynamics of selected disease agents as markers of connectivity of fragmented populations, and 3) evaluate the effect of urbanization on the incidence of cross-species disease transmission. The results of this research will give wildlife managers a better understanding of how urbanization affects their local wildlife and assist them in future disease management planning. The combination of a uniquely qualified, broadly based research team with an extensive dataset on large carnivores from across the country presents an unprecedented opportunity to investigate the disease dynamics in these rare and difficult to study species. The research efforts of each regional team will support and provide new insights for all of the regions involved, not simply their own. Training of graduate students in ecology, infectious disease, and epidemiology will be emphasized, as will training for pre- and post-doctoral veterinarians. Results will be made widely available to other scientists, conservation practitioners, and the general public. This research has a tremendous capacity to broadly impact areas of public and post-graduate education, career development for new investigators and persons from underrepresented groups, and to enhance understanding of complex infectious disease ecological problems using extensive multidisciplinary collaborations. 150 �Table 1. Appendix I. Preliminary results of infectious disease surveillance for puma, Uncompahgre Plateau, Colorado. Puma ID UPCO 3 UPCO 7 UPCO 7 UPCO 7 UPCO 8 UPCO 4 UPCO 5 UPCO 6 UPCO 25 UPCO 28 UPCO 29 UPCO 31 UPCO 23 UPCO 27 UPCO 30 UPCO 50 UPCO 51 UPCO 52 UPCO 54 UPCO 55 UPCO 24 a T.g.e IgG B.h. Y.p. FPV T.g. e IgM + + - + - ++ + - - - + - +++ + Ph P P P P P P 13S, 247645, 4246097 Ih P P P P P P P 3/21/2005 12S, 727808, 4239029 I - - - - + - ++ M 1/28/2005 13S, 257565, 4239606 + - - - - + + I M 2/4/2005 13S, 240577, 4251037 - - + + - + - I M 2/18/2005 13S, 247399, 4254006 + - - - - + - I F 2/8/2006 13S, 258374, 4230480 + P P P P P P P F 3/23/2006 12S, 722868, 4240115 + P P P P P P P M 4/14/2006 12S, 723458, 4242340 + P P P P P P P M 4/19/2006 12S, 746919, 4225441 + P P P P P P P F 1/4/2006 12S, 730188, 4234861 - P P P P P P P M 3/10/2006 12S, 722339, 4245212 - P P P P P P P F 4/15/2006 13S, 248551, 4242095 - P P P P P P P F 12/14/2006 12S, 753639, 4260149 + P P P P P P P M 1/7/2007 13S, 238783, 4252390 + P P P P P P P F 1/10/2007 13S, 258058, 4236260 I P P P P P P P F 1/12/2007 13S, 252688, 4228050 + P P P P P P P M 1/21/2007 13S, 258133, 4228691 + P P P P P P P F 1/17/2006 12S, 737151, 4233273 % Seroprevalance = No. animals positive/Total animals tested * 100 + P P P P P P P 72 33 33 33 0 100 17 50 Sex Capture Date GPS NAD27 U.T.M.: Zone, E, N PLV FCV FHV F 1/21/2005 13S, 241606, 4251510 - +h F 2/24/2005 13S, 246328, 4244230 + F 3/30/2006 13S, 245901, 4247627 F 3/3/2007 F a b PLV is Puma Lentivirus. b FCV is Feline Calicivirus. c FHV is Feline Herpesvirus. d FPV is Feline Panleukopenia Virus e T. g. is Toxoplasma gondii. f B. h. is Bartonella hensalae. g Y. p. is Yersinia pestis. h Results: + (positive result), P (Pending result), I (Inconclusive result). 151 c d f g �152 �Colorado Division of Wildlife July 2006 - June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3003 2 Federal Aid Project: N/A : Division of Wildlife : Mammals Research : Predatory Mammals Conservation : Cougar Demographics and Human Interactions Along the Urban-Exurban Front Range of Colorado : Period Covered: July 1, 2006 - June 30, 2007 Author: M.W. Alldredge Personnel: K. Griffin, D. Kilpatrick, M. Miller, F. Quartarone, M. Sirochman, L. Wolfe, D. Freddy CDOW; B. Posthumus, Jeffco Open Space; S. Oyler-McCance, USGS. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Projects were undertaken to evaluate genetic techniques and examine statewide genetic population structure for cougars and bears. Genetic techniques were developed for both cougars and bears for both microsatellite and mitochondrial DNA. Using 50 samples each from cougars and bears, an initial attempt was made to determine genetic population structure for the state. Based on these data, the concept of a megapopulation is a more realistic representation of the cougar and bear populations, as opposed to ideas of subpopulations within the state. Further investigation is warranted to increase the power of these tests and to make management recommendations. In addition to genetics, a pilot field study was initiated to determine the feasibility of conducting a long-term front-range cougar-human interaction study. With considerable time and effort, research agreements were achieved with Jefferson County, Boulder County, and Boulder City open-space agencies. Internal CDOW protocols were also developed that outlined the working relationship between research and management personnel in regards to dealing with various levels of cougar-human conflict. During this year, 2 cougars were caught and one adult male was fitted with a GPS transmitter. The GPS transmitter is working adequately, with an approximate 56% acquisition success rate. Given this success rate we will keep the daily number of acquisitions high, currently set at 8 per day. Based on the interagency agreements, trapping operations, and GPS data, we recommend proceeding with the full scale cougar-human interaction study on the front-range of Colorado. 153 �WILDLIFE RESEARCH REPORT COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBANEXURBAN FRONT RANGE OF COLORADO MATHEW W. ALLDREDGE P.N. OBJECTIVE 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban front-range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus) and estimating population densities of cougars for the state of Colorado. SEGMENT OBJECTIVES 1. Determine the efficacy of using microsatellites or mtDNA to delineate female cougar and black bear subpopulations across the state of Colorado. 2. Evaluate differences in DNA quantity from either a cougar scat surface collection or a cross-sectional collection. 3. Evaluate differences in DNA quantity from successive cougar feces depositions to determine the variation in quantities of genetic material in scats. Quantify differences in epithelial shedding rates. 4. Evaluate temporal, environmental, and seasonal effects on cougar DNA quantity and quality for both controlled and uncontrolled conditions. 5. Determine the effectiveness of cage traps and hounds for capturing cougars on the Front-Range of Colorado. 6. Determine functionality and suitability of GPS collars on cougars in Front-Range habitats. 7. Implement cougar-human risk protocols and communications within CDOW and among public entities and determine if modifications are necessary. 8. Determine the feasibility of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets. 9. Evaluate political/social response to cougar research activities. INTRODUCTION Cougar management is a growing concern for the Colorado Division of Wildlife (CDOW). Cougar conservation and the maintenance of viable populations is a statewide issue as CDOW is charged with the management of cougars. However, the nexus between cougar conservation and human health and safety is becoming a high priority issue within the urban and exurban areas of the state. Cougar conflicts (livestock depredation, pet depredation, and direct human interaction) within urban and exurban areas appear to be increasing as humans continue to encroach on historical cougar habitats. Because of the diversity of cougar management issues across the state, cougar research has focused on statewide issues of cougar population structure and methods of estimating population demographics, and on urban/exurban issues of cougar/human interaction. Genetic techniques for monitoring or research of rare, elusive, and wide ranging species are of particular interest as other techniques are either impractical or financially prohibitive. Genetic techniques for monitoring and research of cougars in Colorado may be invaluable as alternative techniques are expensive and in many situations may not be possible. Capture and handling of cougars is expensive, time consuming, and may not give representative samples of the population. Large dispersal distances of 154 �cougars, especially males, will require impractically large study areas in order to understand demographic patterns that are affected by immigration. Capture may not even be possible in suburban and exurban areas of Colorado as logistical constraints associated with private land owners will likely prohibit the use of many capture techniques. Noninvasive genetic sampling (Hoss et al. 1992, Taberlet and Bouvet 1992) has the potential to provide a realistic method of sampling a population of interest. Noninvasive sampling techniques include the use of hair snares, and scat collections (Harrison et al. 2004, Smith et al. 2005). The use of scats for sampling cougar populations may be particularly useful and provide a representative sample of the population. Scat collections can either be done by searching transects with human observers (Harrison et al. 2004) or with trained dogs (Smith et al. 2005). Scats could also be collected from kill sites. Kill sites would probably need to be based on mortalities of radio-collared ungulate populations. Data from noninvasive sampling techniques are useful in describing dispersal patterns and estimating population size. Noninvasive genetic data are error prone, which in many cases is because of the quantity and quality of genetic material relative to the collection of noninvasive samples. Therefore, one objective over the last year has been to develop a study to evaluate degradation rates of DNA in fecal samples with respect to time and temperature. Use of genetic data for other purposes, such as delineating subpopulations, is also very useful for managing cougar and bear populations in the state. In these cases the goal is to examine local characteristics of the genetic data and determine if it is different among areas (subpopulation structure) or is similar across all areas (panmictic population). Nuclear DNA is inherited from both the mother and the father and therefore is less likely to describe sex-linked population structure. Male cougars and bears generally disperse over greater distances than females and therefore a female population substructure may be easier to detect than male population substructure. Examination of cougar and bear population structure has been examined using nuclear DNA but few studies have examined cougar population structure using mitochondrial DNA (mtDNA). Mitochondrial DNA is only inherited from the female in mammals and therefore lends itself to delineating female cougar population substructures. A second objective has been to determine if any genetic population structure can be identified for cougars and bears across the state by examining nuclear and mtDNA from statewide female cougar and bear harvest. At the local scale efforts have been made to initiate a cougar/human interaction study on the Front-Range of Colorado. Given that cougars currently coexist with humans within urban/exurban areas along Colorado’s Front-Range, varying levels of cougar-human interaction are inevitable. The CDOW is charged with the management of cougar, with management options ranging from minimal cougar population management, to dealing only with direct cougar-human incidents, to attempted extermination of cougars along the human/cougar spatial interface. Inaction and extermination are management starategies that are not practical nor acceptable to the majority of the human population. In the 2005 survey of public opinions and perceptions of cougar issues, 96% of the respondents agreed that it was important to know cougars exist in Colorado, and 93% thought it was important that they exist for future generations (CDOW, unpublished data). There is a growing voice from the public that CDOW do more to mitigate potential conflicts, and the Director of CDOW has requested that research efforts be conducted to help minimize future human/cougar conflicts. In order to meet these goals CDOW believes we need to directly test management prescriptions in terms of desired cougar population and individual levels of responses. Long-term study objectives for the Front-Range Cougar Research project will involve directly testing management responses of cougars at various levels of human interaction, as well as collecting basic information about demographics, movement, habitat use, and prey selection. The CMGWG (2005) recommend that part of determining the level of interaction or risk between cougars and humans is to 155 �evaluate cougar behavior on a spectrum from natural, to habituated, to overly familiar, to nuisance, to dangerous. The CMGWG (2005) clearly state that there is no scientific evidence to indicate that cougar habituation to humans affects the risk of attack. Studying individual and population level responses of cougars will require capturing and radiocollaring cougars, as well as standardizing responses of CDOW personnel to human/cougar interactions. Therefore, in this initial year, we need to test various cougar capture techniques in urban/exurban areas of interest for effectiveness and public acceptance and to assess the reliability of GPS collars as monitoring tools to assess cougar responses to management prescriptions. More importantly, clearly defined protocols have been developed within CDOW (APPENDIX II-B, sub-appendix I) to direct how researchers and field managers should deal with various levels of risk to human health and safety, and these protocols need to be tested and evaluated in the field. A large portion of the Front-Range is a mosaic of private, city, county, State, and Federal public lands. An assessment of capture techniques will allow future assessments of research feasibility and limitations that might be imposed by various land ownerships. Testing capture techniques and potential management actions will also allow for an assessment of the receptiveness of future research within the various political/social environments. STUDY AREA GENETICS Identifying population structure for cougars and bears is a statewide effort. The initial effort for cougars is based on the entire female segment of harvested cougars for the state. The female harvest for bears is much larger, so the sample involved a group of bears from each of the northwest, northeast, southwest, and southeast state regional portions of bear habitat, in an attempt to capture the greatest genetic diversity for the state through spatial separation of sample areas. The genetic degradation study will be conducted at the Foothills Wildlife Research Facility, located in Fort Collins, Colorado. This is the facility where 3 sibling cougars have been raised in captivity and are part of other ongoing research efforts. COUGAR/HUMAN INTERACTION The pilot field study is being conducted in Boulder and Jefferson counties, in an area from near Interstate 70 north to approximately Lyons, Colorado, which is also a likely area for addressing long-term research objectives (see Study Plan APPENDIX II-B, Figure 1). This area is comprised of many land ownerships, including private, Boulder City, Boulder County, Jefferson County, and State and Federal owned lands. Therefore, we have been directly involved with Boulder City and Boulder and Jefferson county governments to obtain agreements from these entities on conduct of research and protocols for dealing with potential human/cougar interactions prior to conducting any research efforts. METHODS GENETICS Genetic samples for the statewide population structure were obtained from statewide voluntary tooth collections from harvested cougars and bears. DNA was extracted from teeth using the DNeasy Blood and Tissue Kit (see Study Plan APPENDIX I-A, sub-appendix I). Following extraction, samples were sent to Sara Oyler-McCance at the Rocky Mountain Center for Conservation Genetics and Systematics, for PCR and sequencing (again, see sub-appendix I for specific methods). A major effort for this year was for the laboratory to develop and test primers for both cougar and bear genetic work. All 156 �future work with this laboratory will not incur these upfront costs of initial setup for these species. The cougar genetic degradation portion of the genetic study will be initiated in fall 2007. COUGAR/HUMAN INTERACTION A major effort involved coordinating access and research agreements with Boulder City, and Boulder and Jefferson counties. These agreements were essentially achieved after several meetings with these entities to discuss the research and also involved public meetings with Boulder city and county advisory boards. Final, signed working agreements among these entities and CDOW were not entirely finalized until late August 2007. Through August 2007, cougar capture efforts only occurred on Jefferson County open space lands (White Ranch and Lacy properties) because a signed agreement had only been achieved with Jefferson County. Capture efforts with hounds occurred during April and May 2007. Baiting, using deer and elk carcasses, has been conducted regularly during April-August 2007. Bait sites are monitored using digital trail cameras to determine bait site activity. Cage traps were generally used for capture when cougars removed the bait and cached it. Captured cougars were anesthetized, monitored for vital signs, aged, measured, and ear-tagged. Adults were fitted with GPS collars. Subadults were released without collars because of dispersal potential and difficulty fitting a static collar to a young cougar that may grow substantially. For detailed capture and handling procedures see the study plan APPENDIX II-B. RESULTS AND DISCUSSION Two project study plans were completed in anticipation of long-term research efforts to improve the management of cougars in Colorado: 1) Evaluating genetic techniques for application to cougar population studies (see study plan APPENDIX I-A), and 2) Pilot Study--Front-Range cougar-human interactions: Feasibility assessment of techniques and protocols (see study plan APPENDIX II-B). Additionally, considerable effort was focused on developing CDOW internal protocols for dealing with intra-agency coordination between research and management of conflict cougars involved in the research project. A working document was approved and signed by the CDOW Director defining internal CDOW protocols for dealing with research cougars in urban areas that outlined procedures, involvement, and communication between research and field management personnel based on perceived risk to public safety (see APPENDIX II-B, sub-appendix I). Standardized protocols are needed to maintain requisite levels of consistency within study populations. These protocols will also focus liability, political, and social pressures on CDOW as a whole, and not on individuals or sections within CDOW. One objective of this pilot year field study was to test the management and communication protocols and modify protocols as needed prior to conducting large scale research studies requiring larger commitments of time and resources. GENETICS Using 6 samples each for cougars and bears, the Rocky Mountain Center for Conservation Genetics and Systematics laboratory was successfully able to develop primers and successfully sequence nuclear DNA for both species. The laboratory was also successful in developing methods to analyze mtDNA for bears. Analysis of mtDNA for cougars has been difficult due to the transposition of mtDNA into the nuclear DNA for cougars. DNA was extracted from all 308 bear teeth collected from harvested bears during 2006. Of those, 49 females were selected for genetic sequencing, representing 4 distinct spatial groups across the state (Figure 1). Using 8 microsatellite loci, all 49 female bears were genotyped. Using program STRUCTURE (2007), the data indicate that bears in Colorado function as one megapopulation, rather than as distinct subpopulations (Figure 2). Examination of control region mtDNA haplotypes revealed 157 �minimal spatial structure as well (Figure 3). Given this data further examination of both microsatellite and mtDNA is warranted for conclusive evidence of the true population structure of bears within the state. DNA was extracted from all 128 cougar teeth collected from harvested cougars during 20062007. Additionally, DNA was extracted from samples taken from the Uncompahgre Plateau cougar study (Logan 2006), and from samples taken in the northern Front Range as part of C. Krumm’s research project (Krumm, unpublished data). All female samples from the harvest plus additional samples from the other research projects were selected for genetic sequencing for a total of 54 samples across the state. Given the limited sample size for females, spatially distinct groups were not available. Using 15 microsatellite loci, all 54 samples were genotyped. The data revealed almost no population structure for cougars across the state (Figure 4). Again, we do feel that, for completeness, additional samples should be analyzed with regard to population structure in order to have conclusive evidence about the lack of population substructure for cougars within the state. COUGAR/HUMAN INTERACTION During 2006-07, several internal CDOW meetings were held to discuss the interaction between research and field management personnel operations when dealing with Front-Range cougars. These meetings resulted in the development of the “Colorado Division of Wildlife Protocols for Front-Range Cougar Pilot Research Project,” which outlines how cougars at various levels of human interaction will be handled with regard to research and management issues of human health and safety. This document also outlines the personnel which will be involved in decisions about cougars, and internal and external communication about the project. In March, 2007, the director of CDOW signed the document, accepting the protocols as operationally feasible (APPENDIX II-B, sub-appendix I). On January 25, 2007, CDOW held a meeting with Jefferson County, Boulder City, and Boulder County open space administrations to discuss the Front-Range cougar program. All entities supported the project. On February 16, 2007, CDOW received a signed research agreement from Jefferson County Open Space (JCOS) approving access and research activities on their properties. Meetings with Boulder county Parks and Open Space Advisory Committee (POSAC) were held in March and April, 2007. The POSAC board recommended support for the project, by unanimous vote, following the April 2007 meeting. On May 22, 2007, CDOW presented the project to the Boulder county commissioners, whom approved the project. Similar meetings were held with Boulder City Open Space and Mountain Parks board of trustees. At the final meeting on March 28, 2007, the board recommended approving the project and allowing access to Boulder city open space lands. Research agreement letters for both Boulder county and city had final signature authority by late August, 2007. In May, 2007, cougar capture efforts commenced on the White Ranch and Lacy properties, which are owned and managed by JCOS. During May, 8 capture days were spent using hounds, resulting in 2 unsuccessful chases of cougars, 2 successful chases of bears, and 4 days with no chases. The 2 cougar chases were initiated from cougars identified at bait sites set-up on the White Ranch property. From May 2 through August 31, 2007, 165 bait nights (one bait night equals one active bait site per night) were conducted, resulting in 10 visits by cougars. Only 2 of these 10 visits by cougars resulted in a cougar taking the bait and providing a trapping opportunity. On both of these occasions a cage trap was set. On June 14, 2007, a subadult male cougar was caught on the Lacy property, ear-tagged and released without a collar because of the likelihood of dispersal out of the area. On July 14, 2007, an adult male cougar (AM04) was caught on the White Ranch property, and was fitted with a GPS collar. Other than cougars, skunks, fox, and bears visited bait sites frequently. From July 18 to August 31, bears took the bait from bait sites on 14 occasions. 158 �On August 17, 2007, the GPS collar on cougar AM04 was downloaded. Acquisition success rate was 56% of 288 total attempts. Most of the acquired locations were “good” locations with dop ratings < 10. Failed acquisitions were generally grouped together, indicating the cougar was in a location with poor GPS coverage for some period of time. The successful GPS locations indicate that cougar AM04 uses an area extending from the capture site on White Ranch, north to the city of Boulder (Figure 5). Some of the locations are in urban/exurban areas, but use of these areas is limited and appears to be random. SUMMARY The Rocky Mountain Center for Conservation Genetics and Systematics laboratory is now prepared to perform nuclear and mitochondrial genetic work on cougars and black bears. Based on sample sizes of approximately 50 individuals each, nuclear or mitochondrial DNA are suggesting that bears and cougars each represent a megapopulation within the state of Colorado. However, we feel further investigation is warranted to increase the strength of evidence. Initiating the Front-Range cougar project was also successful, as working agreements have been implemented with all 3 municipal open space entities within our study area. We have also demonstrated the limited success of baiting and cage trapping to capture cougars, at least during summer months. We were successful in capturing 2 cougars and were able to GPS collar one adult male. Location acquisition success for the GPS collar is low (56%) but with 8 acquisitions per day, valuable information is still attainable from the GPS collars. LITERATURE CITED COUGAR MANAGEMENT GUIDELINES WORKING GROUP. 2005. Cougar Management Guidelines, 1st ed. WildFutures, Bainbridge Island, Washington, USA. HARRISON, R. L., P. B. S. CLARKE, AND C. M. CLARKE. 2004. Indexing swift fox populations in New Mexico using scats. American Midland Naturalist 151:42-49. HOSS, M., M. KOHN, S. PAABO, F. KNAUER, AND W. SCHRODER. 1992. Excrement analysis by PCR. Nature 359:199. SMITH, D. A., K. RALLS, B. L. CYPHER, AND J. E. MALDONADO. 2005. Assessment of scat-detection dog surveys to determine kit fox distribution. Wildlife Society Bulletin 33:897-904. TABERLET, P., AND J. BOUVET. 1992. Bear conservation genetics. Nature 358:197. Prepared by Mathew W. Alldredge, Wildlife Researcher 159 �Figure 1. Locations of 308 bears harvested in Colorado during the 2006 hunting season. Locations for the 49 female bears from four distinct locations for genetic identification of population structure are highlighted. 160 �Figure 2. Cluster diagram of microsatellite data identifying little evidence of population substructure for bears across the state of Colorado based on 49 individual females harvested in 2006 from four distinct spatial locations representing the northeastern, northwestern, southwestern, and southeastern portions of Colorado. 4490000 4440000 4390000 Northing 4340000 4290000 4240000 4190000 4140000 4090000 105000 205000 305000 405000 505000 605000 Easting CC1 CC2 CC3 CC4 CC5 CC6 CC7 CC8 Figure 3. Mitochondrial DNA haplotypes for bears plotted by harvest location for 49 bears harvested in the 2006 hunting season. Although there are 8 haplotypes represented in the data, only 3 occur frequently. 161 �Figure 4. Cluster diagram of microsatellite data identifying little evidence of population substructure for cougars across the state of Colorado based on 54 individual females. Figure 5. GPS locations for cougar AM04 from July 14, 2007 (date of capture) to August 17, 2007. 162 �APPENDIX I-A PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2006-07 State of Cost Center Work Package Task No. Colorado 3430 3003 : Division of Wildlife : Mammals Research : Predatory Mammals Conservation : Evaluating Genetic Techniques for Application to Cougar Population Studies EVALUATING GENETIC TECHNIQUES FOR APPLICATION TO COUGAR POPULATION STUDIES Principal Investigators Mathew W. Alldredge, Wildlife Researcher, Mammals Research Paul Lukacs, Biometrician Sara Oyler-McCance, Rocky Mountain Center for Conservation Genetics and Systematics, USGS David J. Freddy, Wildlife Research Leader, Mammals Research Cooperators Michael Miller, Lisa Wolfe, Karen Griffin, Jerry Apker, Ken Logan Others STUDY PLAN APPROVAL Prepared by: Mathew Alldredge Date: Submitted by: Mathew Alldredge Date: 4/18/2007 Reviewed by: Mike Phillips Date: 5/7/2007 Eric Bergman Date: 5/24/2007 Date: Reviewed by: Paul Lukacs Biometrician Date: 6/25/07 Approved by: Dave Freddy Mammals Research Leader Date: 6/25/07 163 �PROGRAM NARRATIVE STUDY PLAN FY 2006-07 EVALUATING GENETIC TECHNIQUES FOR APPLICATION TO COUGAR POPULATION STUDIES A study proposal submitted by: Mathew W. Alldredge, Wildlife Researcher, Mammals Research Paul Lukacs, Biometrician Sara Oyler-McCance, Rocky Mountain Center for Conservation Genetics and Systematics, USGS David J. Freddy, Wildlife Research Leader, Mammals Research NEED The use of genetic techniques for wildlife research is becoming increasingly common. Genetic information can be used for species identification, evaluation of diets, gender identification, maternal and paternal lineage, and individual identification. This information, in turn, can then be used to describe population demographics, such as sex ratios, population size, dispersal patterns, and local subpopulations. Genetic techniques for monitoring or research of rare, elusive, and wide ranging species are of particular interest as other techniques are either impractical or financially prohibitive. Genetic techniques for monitoring and research of cougars in Colorado may be invaluable as alternative techniques are expensive and in many situations may not be possible. Capture and handling of cougars is expensive, time consuming, and may not give representative samples of the population. Large dispersal distances of cougars, especially males, will require impractically large study areas in order to understand demographic patterns that are affected by immigration. Capture may not even be possible in suburban and exurban areas of Colorado as logistical constraints associated with private land owners will likely prohibit the use of many capture techniques. Genetic samples can be obtained from tissue samples from harvested lions or other removals associated with depredation or human conflict. Samples from these sources may not be representative of the cougar population, however, as harvest is not truly random but is affected by harvest pressure and vulnerability of various sex and age classes. Juvenile males may be most vulnerable to harvest as they are very mobile and may not have established home ranges. Adult females, especially those with cubs, are likely the least vulnerable to harvest, except at high harvest levels (Anderson and Lindzey 2005). Hunter selectivity and sex biased harvest quotas will also influence the composition of the harvested population. These data are still important but other data are necessary for specific demographic questions, such as population estimation. Noninvasive genetic sampling (Hoss et al. 1992, Taberlet and Bouvet 1992) has the potential to provide a realistic method of sampling a population of interest. Noninvasive sampling techniques include the use of hair snares, and scat collections (Harrison et al. 2004, Smith et al. 2005). The use of scats for sampling cougar populations may be particularly useful and provide a representative sample of the population. Scat collections can either be done by searching transects with human observers (Harrison et al. 2004) or with trained dogs (Smith et al. 2005). Scats could also be collected from kill sites. Kill sites would probably need to be based on mortalities of radio-collared ungulate populations. Data from noninvasive sampling techniques are useful in describing dispersal patterns and estimating population size. Noninvasive genetic data are error prone, which in many cases is because of the quantity and quality of genetic material relative to the collection of noninvasive samples (Study plan A—Degradation of Genetic Markers from Fecal Samples). 164 �Use of genetic data for other purposes, such as delineating subpopulations, is also very useful for managing cougar populations in the state but do not require the amount of randomization of sampled individuals that is required for population estimates. In these cases the goal is to examine local characteristics of the genetic data and determine if it is different among areas (subpopulation structure) or is similar across all areas (panmictic population). Nuclear DNA is inherited from both the mother and the father and therefore is less likely to describe sex-linked population structure. Male cougars generally disperse over greater distances than females and therefore a female population substructure may exist, which has not been described in previous studies. Examination of cougar population structure has been examined using nuclear DNA but few studies have examined cougar population structure using mitochondrial DNA (mtDNA). Mitochondrial DNA is only inherited from the female in mammals and therefore lends itself to delineating female cougar population substructures (Study plan B—An Assessment of female cougar population substructure using mitochondrial DNA). LITERATURE CITED ANDERSON, C. R., JR., AND F. G. LINDZEY. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. HARRISON, R. L., P. B. S. CLARKE, AND C. M. CLARKE. 2004. Indexing swift fox populations in New Mexico using scats. American Midland Naturalist 151:42-49. HOSS, M., M. KOHN, S. PAABO, F. KNAUER, AND W. SCHRODER. 1992. Excrement analysis by PCR. Nature 359:199. SMITH, D. A., K. RALLS, B. L. CYPHER, AND J. E. MALDONADO. 2005. Assessment of scat-detection dog surveys to determine kit fox distribution. Wildlife Society Bulletin 33:897-904. TABERLET, P., AND J. BOUVET. 1992. Bear conservation genetics. Nature 358:197. 165 �PROGRAM NARRATIVE STUDY PLAN PART A FY 2006-07 DEGRADATION RATES OF GENETIC MARKERS FROM FECAL SAMPLES A study proposal submitted by: Mathew W. Alldredge, Wildlife Researcher, Mammals Research Paul Lukacs, Biometrician Sara Oyler-McCance, Rocky Mountain Center for Conservation Genetics and Systematics, USGS David J. Freddy, Wildlife Research Leader, Mammals Research NEED Noninvasive genetic sampling of cougars may prove to be a useful method to estimate population size of cougars across the state, which is something that has not been successfully done using traditional methods. The use of hair is probably not an effective method for felids because of the amount of shedding, which limits the number of samples that actually produce DNA. Scats however, should provide a useful method of collecting genetic material as epithelial cells are shed from the intestinal track and appear in the feces. Using species specific primers, DNA from the epithelial cells are amplified during PCR. Important considerations that must be made are the timing of collections and the method of sampling in order to make valid inferences about population size. Defining a sampling scheme for the collection of scats is critical to obtaining unbiased estimates of population size. Using radio-collared or captured cats and invasively collected genetic samples could be used as a means of identifying cats or producing the initial marking event but resampling must be done independently of knowledge about cat locations. Potentially transects could be searched for cougar scats but this is likely to be inefficient and yield low sample sizes. The use of scat-searching dogs may also be possible but efficiency may still be low, especially in large areas where access may be limited. Another option would be to use hunter harvest as the resampling event. Concerns with this would be sex and age bias in the harvest, but stratification may overcome these issues. A final potential approach would be to mark prey and locate scats from known kill sites. The only potential bias with this would be if marking prey affected how cats selected prey. This approach would benefit from the short time span between scat deposition and collection. Other considerations when using scat are the quantity and quality of genetic material that can be obtained from the sample, which are factors of time since deposition and environmental conditions. Extrinsic factors, such as season, diet, and sample age, can cause variation in genotyping error rates (Lucchini et al. 2002, Murphy et al. 2002, Piggott 2004). Piggot (2004) found that red fox and rockwallaby samples collected during the summer in Australia produced fewer genetic errors than samples collected during the winter. They attribute this to warm-dry summers compared to rainy-moist winters. Lucchini et al. (2002) found that wolf feces collected in the western Italian Alps during the winter produced higher quality genetic samples than samples collected during the spring and summer, and fresh samples were better than older samples. Winter samples collected in this study were found on snow, indicating that the samples were likely frozen for the majority of the time following deposition. Both of these studies indicate that fresher samples have lower genetic error rates than older samples. Potential weaknesses with noninvasive genetic sampling are low success rates, contamination concerns, and high genotyping error rates (Taberlet et al. 1999, Waits and Leberg 2000). Even small genotyping errors (< 1%) cause reasonably large overestimation of population size (Waits and Leberg 2000). Some of these errors include allelic dropout (alleles fail to amplify) and false alleles (spurious 166 �amplification of an allele that does not exist for a given individual) (Flagstad et al. 2004, Piggott 2004). Lucchini et al. (2002) only used wolf scats less than 2 weeks old and found that, of the 130 samples analyzed, 64% successfully sexed and 53% successfully genotyped an individual. Inaccurate genotyping due to allelic dropout occurred in 18% of the PCR samples and amplification of false alleles was negligible. Piggot (2004), using captive red fox found that 6 month old feces did not amplify and amplification rates decreased significantly over time. This study also demonstrated that allelic dropout occurred more rapidly than amplification of false alleles. Similar problems have been documented for genetic work on cougar. Ernest et al. (2000) document 17 of 32 fecal samples collected in Yosemite Valley, California, did not amplify because samples were either of nonfelid origin, DNA was degraded, or fecal compounds inhibited detection. In a similar study of cougar in the Peninsular Ranges of California, it was found that only 77% of scats that provided DNA (63% of the samples) also provided the resolution to identify an individual (Ernest et al. 2002). Paetkau (2003), in a review of 21 population inventory studies, states that it is unclear what the frequencies of errors are for different types of errors in relation to the type and quality of the samples being collected and suggests that use of noninvasive sampling will be limited unless evidence is provided to support the reliability of the data. It is also evident that siblings or closely related individuals provide the greatest challenge to genetically distinguishing individuals. A marker system with the power to distinguish a small number of closely related individuals will also have sufficient power to distinguish among a large number of unrelated individuals (Waits et al. 2001). Noninvasive genetic sampling of cougar using feces is one of the few methods available that may provide realistic estimates of cougar populations in Colorado, which is important because these populations are being exploited. Before genetic sampling can be conducted an assessment of potential genetic error rates must be made in order to appropriately design the sampling protocols and determine if such a method can provide reliable estimates. Currently there are 3 sibling cougar in captivity at the CDOW Wildlife Health Lab, which can be used to produce known age feces. These scat samples can be subjected to both controlled and uncontrolled environmental conditions in order to accurately asses the magnitude of error rates that may be expected if scats are used for noninvasive population estimation of cougar. In addition to these captive cougar, there are also numerous cougar that are currently being monitored using GPS collars. Invasive genetic samples have been collected from all of these monitored cougar. Current efforts to identify kill sites of these cougar based on GPS clusters could also be used to collect cougar scats with a known age of within a few days. These scats could be marked and genetic samples could be collected at various time intervals and assessed for error rates for these scats, which are subject to different environmental conditions. OBJECTIVES 1. Evaluate differences in DNA quantity from either a scat surface collection or a crosssectional collection. 2. Evaluate differences in DNA quantity from successive feces depositions to determine the variation in quantities of genetic material in scats. Quantify differences in epithelial shedding rates. 3. Evaluate temporal, environmental, and seasonal effects on DNA quantity and quality for both controlled and uncontrolled conditions. 167 �EXPECTED RESULTS OR BENEFITS Cougar in Colorado provide hunting opportunities across the majority of their current range, and the Colorado Division of Wildlife is responsible for setting reasonable harvest quotas in order to reach management objectives. This is an inherently difficult task, especially when realistic estimates of population size are not attainable. This study will provide basic information on degradation rates with respect to time, environmental condition, and season, which can then be used to design sampling protocols for noninvasive genetic sampling for the purpose of population estimation. This study will also provide estimates of genotyping error rates which can be incorporated in population estimation models to account for misidentification of individuals. APPROACH Working Hypothesis 1: In this investigation we will first test if the quantity of DNA sample is affected by whether the sample is taken along the surface of the scat or if it is taken as a cross-section of the scat. Quantity of DNA in feces can be low and therefore, it will be beneficial to sample scats in order to maximize DNA quantity in the sample. It may also be that genetic degradation due to some environmental factors is greater on the exposed surface of scats, which may indicate benefits of a crosssectional sampling approach if genetic yield is sufficient. In the case of how to sample scats to maximize genetic quantity, we are only interested in large differences between the proposed collection methods. Small differences will be of little biological significance. Therefore, we will collect paired samples from 20 scats, within 12 hours of deposition. A longitudinal sample along the surface of the scat, and a cross-sectional sample, including the surface, will be collected from each of the 20 scats. DNA will be extracted from the samples and DNA quantity will be measured using real time PCR. Scat will be collected from three sibling cougars that are in captivity at the Foothills Wildlife Research Center in Fort Collins, Colorado. Scats will be collected from a known individual, and within six hours of deposition. Upon collection a 100 mg sample will be collected longitudinally along the surface and a 100 mg sample will be collected as a cross-section of the scat. Each scat will be assigned a sample number and each collection will be given the sample number and identified as to the collection method so that samples can remain paired. Samples will then be frozen at -20 C, until DNA extraction. DNA extraction will be done using QIAamp® DNA Stool Mini Kit (Appendix I), a commonly used method for extraction. Following extraction, DNA quantity will be measured using real time PCR(Appendix I). DNA quantity could vary due to many factors, however, pairing samples should account for sources of variation other than collection method. A paired t-test will be used to test for significant differences in DNA quantity associated with collection method. Working Hypothesis 2: We will also test the variability in DNA quantity over successive depositions of feces. It is likely that the amount of epithelial cells shed varies over time, which will affect the quantity of DNA in feces. Understanding this variability will be important in sorting out other sources of variation in this study and will also help to determine if multiple scats should be collected from a single individual, if possible. For example, if DNA quantities can be extremely low in some scats, then this will be a potential reason for amplification failures. The variable of interest is, again, DNA quantity. In some respects the only real interest is the minimum amount of DNA that appears in feces. If minimum levels are low enough so that DNA amplification is a concern then the proportion of time that these low levels occur is also of interest. 168 �Therefore, we will collect samples from all feces over a 20 day period from the 3 captive cougars located at the Foothills Wildlife Research Center. From this we will determine the general form of the distribution of DNA quantity within cougar scats and basic descriptive statistics, including the minimum observed quantities of DNA. It will also be possible to determine if variation in DNA quantity varies with respect to a temporal pattern, since we are working with captive cougar. The captive cougars will be maintained so that feces can be associated with the individual (possibly using orally fed fluorescent markers) and the time series of collections will be tracked. From this we will be able to determine if there is any temporal pattern in DNA quantity. This information may assist in methods of collecting feces from kill sites located in the field where there may be multiple scats from an individual cougar. Scat will be collected from three sibling cougar that are in captivity at the Foothills Wildlife Research Center in Fort Collins, Colorado. Scats will be collected from all individuals, and within 12 hours of deposition over a 20 day period. Two of the captive cougars will be fed a fluorescent marker, so that scats can be associated with an individual cougar. Upon collection, a 100 mg sample will be collected longitudinally along the surface of the scat. Each scat will be assigned a sample number and each collection will be given the sample number, which will identify the time of deposition as well. Samples will then be frozen at -20 C, until DNA extraction. DNA extraction will be done using the QIAamp® DNA Stool Mini Kit (Appendix I). Following extraction, DNA quantity will be measured using real time PCR (Appendix I). Of primary interest will be basic statistics to determine the range (min, max), mean, and variability of DNA quantity in scat samples. We will also determine the general shape of the distribution and the minimum sufficient statistics necessary to describe the distribution. We will also examine the data for predictable patterns in changes in DNA quantity over time using a time series analysis or curve fitting routine. Working Hypothesis 3, part A: Our final hypothesis that we are testing is the rate of genetic degradation that occurs temporally, under various environmental conditions. Some of these experiments will be done under controlled conditions, so that a relationship can be determined for the rate of degradation with respect to a specific factor (part A). Other analyses will involve scats that are subjected to more naturally occurring environmental conditions to help develop a better understanding of reasonable time frames following deposition that scats should be collected given particular environmental conditions (part B). Scats will be collected from three sibling cougars that are in captivity at the Foothills Wildlife Research Center in Fort Collins, Colorado. Scats will be collected from all individuals, and within six hours of deposition. Two of the captive cougars will be fed a fluorescent marker, so that scats can be associated with an individual cougar. Each scat collected will be assigned a collection number that identifies the time of deposition. Scats from each individual will then be randomly assigned to one of the three treatment groups (-5 C, +5 C, and +15 C), such that 20 scats from each individual will be in each temperature regime. Scats will be sub-sampled by removing a 200 mg longitudinal sample at 2 weeks, and 1, 2, 3, 4, and 6 months post deposition. After collection, each sample will be frozen at -20 C, until DNA extraction. DNA will then be extracted using QIAamp® DNA Stool Mini Kit extraction kits. Response variables that will be measured are number of incorrect identifications, allelic dropout rates (actual number of alleles that dropout in any given sample), and number of false alleles. The primary analysis will be a logistic regression on the dichotomous identification variable, treating the three temperature regimes as covariates. Additional analyses will summarize the rate at which alleles dropout and the occurrence of false alleles. 169 �A total of 60 scats will be collected and sub-sampled at each time period. Based on simulating data under a logistic model and assumed error structure, the probability of detecting that the error rate is larger than 5% when the true error is 10%, is approximately 0.63. It is likely however, that genetic degradation will occur over a short time interval, which will render the logistic model less effective. In this case data will be pooled into pre- and post-degradation groups and misidentification rates compared between the groups. In this case the power of the comparison will be greater than that for the logistic analysis. Additionally samples will be analyzed by time period, and once misidentification rates are greater than 50% for a time period, no sequencing will be conducted on scats at larger time periods. PCR and DNA sequencing will be done in the Rocky Mountain Center for Conservation Genetics and Systematics laboratory. Individual cougars will be screened and genotyped using 9 -12 nuclear microsatellite loci isolated from domestic cat (Menotti-Raymond and O’Brien 1995, Menotti-Raymond et al. 1999). Three recent studies have used sets of these primers successfully on mountain lion (Ernest et al. 2000, Sinclair et al. 2001, Anderson et al. 2004). We will choose a set of these primers for our work. PCRs will be performed using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). Each 12.5μl reaction will contain 125μM each dNTP, 1X Taq buffer (Kahn et al. 1998), 0.034μM M13tailed forward primer, 0.5μM non-tailed reverse primer, 0.5μM M13 dye-labeled primer with Beckman Coulter dyes D2, D3 or D4 (Proligo), and 0.31U Taq polymerase (Promega). The thermal profile for both the forward dye-labeled and the M13 dye-labeled reactions will be as follows with the appropriate annealing temperature varying by locus: preheat at 94°C for 1 min, denature at 94 ºC for 1 min, anneal for 1 min, and extend at 72 ºC for 1 min for 35 cycles. The PCR products will be diluted and run on the CEQ8000 XL DNA Analysis System (Beckman Coulter). All loci will be run with the S400 size standard (Beckman Coulter) and analyzed using the Frag 3 default method. Working Hypothesis 3, part B: The second experiment within Hypothesis 3 is to test the rate of genetic degradation that occurs with respect to time under more natural environmental conditions. This phase of the study will be conducted in the second year and data from the first year’s degradation study will be used to refine the design of this second phase. Therefore, sample sizes and timing of collections are speculative. Part of this experiment will involve repeated freeze-thaw cycles to determine the number of freeze-thaw cycles that can occur before genetic material is unusable. The second part will be to expose scats from known individuals to natural environmental conditions in order to assess degradation rates that will be encountered in field situations. Scat will be collected from three sibling cougar that are in captivity at the Foothills Wildlife Research Center in Fort Collins, Colorado for the freeze-thaw experiment. A total of 40 scats will be collected within six hours of deposition utilizing all three cougars. Two of the captive cougars will be fed a fluorescent marker, so that scats can be associated with an individual cougar. Each scat collected will be assigned a collection number that identifies the time of deposition. Scats will then be subjected to 3 freeze-thaw cycles per week (-5 C to +5 C). Scats will be sub-sampled by removing a 200 mg longitudinal sample following 5, 10, 15, 20, and 25 freeze-thaw cycles. DNA will then be extracted using the QIAamp® DNA Stool Mini Kit and then DNA amplification and sequencing will be conducted as described above. Treating each level of freeze-thaw cycle as a treatment group with a binomial response variable of correctly identifying an individual, the probability of detecting an error rate >0.05 when the true error rate is 0.1 is 0.047. Response variables that will be measured are number of incorrect identifications, allelic dropout rates (actual number of alleles that dropout in any given sample), and number of false alleles. The primary analysis will be a binomial analysis of correct identification rates at each level of freeze-thaw cycles. Additional analyses will summarize the rate of allelic dropout and the occurrence of false alleles. 170 �As part of ongoing research projects, cougars are being captured and monitored with GPS collars, as well as individually genetically identified from tissue samples. Kill or feeding sites are being identified and investigated based, on these GPS locations, which provides the opportunity to locate cougar scat exposed to natural environmental conditions with an approximate known date of deposition. Exposure times range from 2 weeks to 8 weeks post-deposition, based on current field protocols for kill site investigation. As scats are found during these field investigations, a 200 mg longitudinal sample will be collected. Following the above procedures for extraction, amplification and sequencing, the individual will be identified based on DNA and compared to the assumed known individual’s genetic identification. The target sample size for this will be 200, which will give us an adequate sample to determine an approximate time frame post-deposition at which genetic identification error rates will increase to unacceptable levels for mark-recapture population analyses. LOCATION OF WORK The captive cougar are located at the Wildlife Health Laboratory in Fort Collins Colorado, which is also where DNA extraction will be done. Free-ranging cougars currently involved in research projects are located in the front-range of Colorado and on the Uncompahgre Plateau, in western Colorado. Genetic analyses will be conducted at the Rocky Mountain Center for Conservation Genetics and Systematics, located at Denver University, Denver, Colorado. SCHEDULE OF WORK Time April 2007 April-June 2007 April-Nov 2007 Nov-Dec 2007 Jan 2008 Jan-Feb 2008 Jan-April 2008 Mar 2007-May2008 Mar 2007-May2008 Jan-June 2008 June-September Activity Study Plan Approval Part A—scat collections from sibling cougar DNA extraction and sequencing Statistical Analysis Preliminary report—Decision on implementation of Part B Scat collections from sibling cougar (freeze-thaw) DNA extraction and sequencing Scat collection from free-ranging cougars DNA extraction DNA sequencing Final analyses and report ESTIMATED COSTS Activity/category Part A Supplies (extraction kits) DNA sequencing (1200 samples at $50 per sample) Part B Supplies (extraction kits) DNA sequencing (400 samples at $50 per sample) Total 171 2006-2007 2007-2008 $500 $1,000 $60,000 $500 $500 $20,000 $85,000 �LITERATURE CITED ANDERSON, C. R., F. G. LINDZEY, AND D. B. MCDONALD. 2004. Genetic structure of cougar populations across the Wyoming Basin: metapopulation or megapopulation. 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Chromosome-specific intron size differences in the avian CHD gene provide an efficient method for sex identification in birds. Auk 115:1074-1078. LUCCHINI, V., E. FABBRI, F. MARUCCO, S. RICCI, L. BOITANI, AND E. RANDI. 2002. Noninvasive molecular tracking of colonizing wolf (Canis lupus) packs in the western Italian Alps. Molecular Ecology 11:857-868. MENOTTI-RAYMOND, M. AND S. J. O’BRIEN. 1995. Evolutionary conservation of ten microsatellite loci in four species of Felidae. Journal of Heredity 86:319-322. MENOTTI-RAYMOND, M., V. A. DAVID, L. A. LYONS, A. A. SHCAFFER, J. F. TOMLIN, M. K. HUTTON, AND S. J. O’BRIEN. 1999. A genetic linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57:9-23. MURPHY, M. A., L. P. WAITS, K. C. KENDALL, S. K. WASSER, J. A. HIGBEE, AND R. BOGDEN. 2002. An evaluation of long-term preservation methods for brown bear (Ursus arctos) faecal samples. Conservation Genetics 3:435-440. PAETKAU, D. 2003. An empirical exploration of data quality in DNA-based population inventories. Molecular Ecology 12:1375-1387. PIGGOTT, M. P. 2004. Effect of sample age and season of collection on the reliability of microsatellite genotyping of faecal DNA. Wildlife Research 31:485-493. SINCLAIR, E. A., E. L. SWENSON, M. L. WOLFE, D. C. CHOATE, B. BATES, AND K. A. CRANDALL. 2001. Gene flow estimates in Utah’s cougars imply management beyond Utah. Animal Conservation 4:257-264. TABERLET, P. L., L. P. WAITS, AND G. LUIKART. 1999. Noninvasive genetic sampling: look before you leap. Trends in Ecology and Evolution 14:323-327. WAITS, J. L., AND P. L. LEBERG. 2000. Biases associated with population estimation using molecular tagging. Animal Conservation 3:191-199. WAITS, L. P, G. LUIKART, AND P. TABERLET. 2001 Estimating the probability of identity among genotypes in natural populations: cautions and guidelines. Molecular Ecology 10:249-256. 172 �PROGRAM NARRATIVE STUDY PLAN PART B FY 2006-07 AN ASSESSMENT OF COUGAR AND BLACK BEAR POPULATION SUBSTRUCTURES USING MITOCHONDRIAL AND NUCLEAR DNA. A study proposal submitted by: Mathew W. Alldredge, Wildlife Researcher, Mammals Research Paul Lukacs, Biometrician Sara Oyler-McCance, Rocky Mountain Center for Conservation Genetics and Systematics, USGS Jerry Apker, Kenneth A. Logan, Wildlife Researcher, Mammals Research David J. Freddy, Wildlife Research Leader, Mammals Research NEED Understanding population structure provides important information for management strategies. A clear example is applying different management strategies to adjacent game management units (GMU’s). If a single population is represented across both GMU’s, then it is not possible to evaluate either management strategy because the effects are on the population and thus, are confounded across the unit boundaries. Metapopulation structure of cougar populations in California were demonstrated using telemetry and the structure was attributed to small isolated habitat patches created through increased human development (Beier 1993). Logan and Sweanor (2001) suggest that a source-sink population dynamic existed for populations in southern New Mexico cougar populations. Cougar habitats in southern New Mexico are relatively small and are separated by areas of non-habitat, which is typical for population structuring of populations for a species that is capable of dispersing across the areas of non-habitat. However, Logan and Sweanor (2001) claim that the high dispersal rates documented in southern New Mexico make it unlikely that any genetic subdivision exists among cougar subpopulations. The idea of managing cougar populations relative to source-sink areas is also promoted in the “Cougar Management Guidelines” (Cougar Management Guidelines Working Group 2005). However, this does not specify that source-sink populations exist naturally or if they are artificially created. In many situations it is likely that the source-sink dynamic is artificially created through hunting pressure in more accessible areas and along the human interface in rural areas to avoid conflict. Understanding whether the source-sink dynamic is part of a natural population structure or is artificially created within a spatially intact population has important management considerations. Genetic analysis of cougar populations is one method that has been successfully used to identify population substructures for cougars in California (Ernest et al. 2003), Wolverine (Tomasik and Cook 2005), and feral pigs (Hampton et al. 2004). In the case of feral pigs, sink areas were artificially created through control efforts and source areas were identified using genetic techniques. Genetic population structure for cougar populations throughout the west, has been evaluated extensively, but generally through the use of microsatellite markers. In California, genetic subdivision of cougar populations was defined and was associated with geographic boundaries and isolation by distance (Ernest et al. 2003). McRae et al. (2005) also found some genetic substructuring for cougar populations in southern New Mexico and Arizona and similarly attributed this to geographic barriers and distance. However, genetic substructuring has not been identified across several other western states based on 173 �microsatellite markers. Analysis of microsatellite markers have shown single large panmictic populations for Utah (Sinclair et al. 2001), Southwestern Colorado, Wyoming, and western South Dakota (Anderson et al. 2004), and northern New Mexico, northern Arizona, Utah, and Colorado (McRae et al. 2005). Culver et al. (2000) using an mtDNA analysis actually suggest that the entire North American population is a single homogeneous population coming from a late Pleistocene recolonization. Little analysis of cougar population substructuring has been attempted using mtDNA, which is especially well suited to studying mammal populations with male-biased dispersal (DeYoung and Honeycutt 2005). Tomasik and Cook (2005) were able to describe three distinct populations of wolverine using mtDNA, which were not well defined in other studies that used nuclear markers. However, neither mtDNA nor microsatellite markers were able to differentiate population structure that was identified through radiotelemetry, indicating gene flow between the subpopulations is mediated by both sexes (Cronin et al. 2006). Because mtDNA has the potential to provide an inexpensive method for assessing cougar population substructure across the state of Colorado, it should be evaluated for its efficacy. Given the evidence against such substructuring across the state using microsatellite markers this should be pursued as a pilot study to first determine if any differences can be detected in mtDNA across the state. If differences are detected, then a more intensive sampling scheme can be used to actually delineate potential subpopulations. Because many of the same large carnivore population management issues could be associated with black bears in Colorado, we propose to opportunistically include samples from harvested black bears to assess evidence for population structuring across the state during this initial effort (C. Anderson, personal comm.). OBJECTIVES Determine the efficacy of using mtDNA to delineate female cougar and black bear subpopulations across the state of Colorado. EXPECTED RESULTS OR BENEFITS In order to manage cougar and black bear populations it is important to understand the population dynamic affecting local and regional populations. Identification of female substructuring of the population across Colorado would influence how management strategies are implemented in the state. Evaluating the use of mtDNA and nuclear DNA as a potential method to delineate populations will help determine whether future efforts are warranted. APPROACH The general hypothesis for this pilot study is that mtDNA and/or nuclear DNA can be used to delineate subpopulations of cougars and black bears across the state of Colorado. Given recent genetic studies using microsatellite markers to investigate substructuring in cougar populations, which included Colorado populations, and documented dispersal distances, we expect limited results from mtDNA as well. Investigation of mtDNA as a method to investigate the existence of subpopulations within the state is warranted given speculation about source-sink dynamics of cougar populations within Colorado. Tissue or blood samples will be obtained from cougars distributed across all available cougar habitat within the state of Colorado. Currently, approximately 70 tissue samples have been collected across the state for law enforcement purposes. About 40 additional tissue or blood samples have been collected along the northern front-range of Colorado and are stored at the Wildlife Health Lab. The 174 �majority of these samples will be used for this pilot study. Tissue samples have also been collected as part of the Uncompahgre Plateau, cougar research study, which should also be available for analysis. Starting in 2006, voluntary tooth collection was initiated for all harvested bears and cougars in the state of Colorado to determine age structures in the harvest. DNA will be collected from all teeth collected from harvested bears and cougars. As of January, 2007, approximately 300 teeth have been collected from harvested bears and DNA has been extracted. This sampling effort provides genetic samples from bears and cougars across the state and will provide some areas with more intensive sampling efforts. This will allow for the use of genetic clustering algorithms to be used as well as direct comparisons among intensively sampled areas. An initial analysis will be conducted by analyzing genetic samples from 10 to 15 female bears and cougars within each of 4 geographically distant areas across the state. Based on these genetic samples we will determine if nuclear or mtDNA can be used to identify differences among these 4 distinct groups. If no differences appear to exist, then analyses of remaining samples will not be done and we will conclude that genetic substructure in the bear or cougar population across Colorado does not exist. If differences are found among these four groups, then the remaining samples will be analyzed and substructures of the Colorado bear or cougar population will be identified. DNA will be extracted using the DNeasy Blood and Tissue Kit, from collected tissues and teeth, following the procedures outlined in appendix I. We will attempt to amplify and sequence approximately half of the black bear mitochondrial control region using primers developed previously (Shields and Kocher 1991, Ward et al. 1991). Amplification will be accomplished using our standard 25μl polymerase chain reaction (PCR) as in St. John et al. (2005) [125μM each dNTP, 1X Taq buffer (67mM Tris-HCl pH 8.0, 6.7 mM MgSO4, 16.6mM NH4SO4 10mM β-mercaptoethanol; Kahn et al. 1998), 0.5μM each primer and 0.625U Taq polymerase (Promega)]. PCR products will be cleaned with shrimp alkaline phosphatase and exonuclease 1 (USB) followed by dye terminator cycle sequencing reactions performed with the Beckman-Coulter Quick Start Sequencing Kit according to the manufacturer’s protocol. These will be precipitated according to the manufacturer’s specifications, resuspended in 30 μL of formamide and run on a CEQ 8000 XL Data Analysis System using method LFR-b (Beckman-Coulter). Individuals will be screened and genotyped using 9 -12 nuclear microsatellite loci isolated from various related mammals (Paetkau and Stobeck 1994, Paetkau et al. 1995, Taberlet et al. 1997, Paetkau et al. 1998). Two recent studies have used sets of these primers successfully in black bear molecular studies (Woods et al. 1999, Boersen et al. 2003). We will choose a set of these primers for our work. PCRs will be performed using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). Each 12.5μl reaction will contain 125μM each dNTP, 1X Taq buffer (Kahn et al. 1998), 0.034μM M13-tailed forward primer, 0.5μM non-tailed reverse primer, 0.5μM M13 dye-labeled primer with Beckman Coulter dyes D2, D3 or D4 (Proligo), and 0.31U Taq polymerase (Promega). The thermal profile for both the forward dye-labeled and the M13 dye-labeled reactions will be as follows with the appropriate annealing temperature varying by locus: preheat at 94°C for 1 min, denature at 94 ºC for 1 min, anneal for 1 min, and extend at 72 ºC for 1 min for 35 cycles. The PCR products will be diluted and run on the CEQ8000 XL DNA Analysis System (Beckman Coulter). All loci will be run with the S400 size standard (Beckman Coulter) and analyzed using the Frag 3 default method. We will attempt to amplify and sequence approximately half of the mitochondrial control region using primers that we will design from published sequences in related species (Freeman et al. 2001). Amplification will be accomplished using our standard 25μl polymerase chain reaction (PCR) as in St. John et al. (2005) [125μM each dNTP, 1X Taq buffer (67mM Tris-HCl pH 8.0, 6.7 mM MgSO4, 16.6mM 175 �NH4SO4 10mM β-mercaptoethanol; Kahn et al. 1998), 0.5μM each primer and 0.625U Taq polymerase (Promega)]. PCR products will be cleaned with shrimp alkaline phosphatase and exonuclease 1 (USB) followed by dye terminator cycle sequencing reactions performed with the Beckman-Coulter Quick Start Sequencing Kit according to the manufacturer’s protocol. These will be precipitated according to the manufacturer’s specifications, resuspended in 30 μL of formamide and run on a CEQ 8000 XL Data Analysis System using method LFR-b (Beckman-Coulter). Individuals will be screened and genotyped using 9 -12 nuclear microsatellite loci isolated from domestic cat (Menotti-Raymond and O’Brien 1995, Menotti-Raymond et al. 1999). Three recent studies have used sets of these primers successfully on mountain lion (Ernest et al. 2000, Sinclair et al. 2001, Anderson et al. 2004). We will choose a set of these primers for our work. PCRs will be performed using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). Each 12.5μl reaction will contain 125μM each dNTP, 1X Taq buffer (Kahn et al. 1998), 0.034μM M13-tailed forward primer, 0.5μM non-tailed reverse primer, 0.5μM M13 dye-labeled primer with Beckman Coulter dyes D2, D3 or D4 (Proligo), and 0.31U Taq polymerase (Promega). The thermal profile for both the forward dye-labeled and the M13 dye-labeled reactions will be as follows with the appropriate annealing temperature varying by locus: preheat at 94°C for 1 min, denature at 94 ºC for 1 min, anneal for 1 min, and extend at 72 ºC for 1 min for 35 cycles. The PCR products will be diluted and run on the CEQ8000 XL DNA Analysis System (Beckman Coulter). All loci will be run with the S400 size standard (Beckman-Coulter) and analyzed using the Frag 3 default method. LOCATION This study will be conducted statewide. Project headquarters will be in the Fort Collins office. DNA extraction will be done at the Wildlife Health Lab. SCHEDULE OF WORK Time Jan 2007 Sept 2006-Mar 2007 Jan 2006-May 2007 Feb-July 2007 Aug-Sept 2007 Oct 2007 Nov-Dec 2007 Jan-April 2008 Activity Submit study plan for CDOW review Collection of samples—primarily from hunter harvest DNA extraction Genetic Sequencing (first 50 samples) Analysis of sequence data Prepare final report Genetic Sequencing of remaining samples (if necessary) Final report on genetic structure across the state 176 �ESTIMATED COSTS: Budget for each Species—Includes Genetics Laboratory Setup and Calibration 2006-2007 2007-2008 Category Personnel Co-investigators DNA extraction (Karen Griffin) $200.00 Sequencing (Rocky Mountain Center for Conservation Genetics and Systematics) Initial Startup (8 samples) Salary with fringe $3850.00 Primers $300.00 Microsatellite Sequencing $307.20 mtDNA sequencing $142.08 Other supplies, equipment $689.89 Indirect $793.38 Total $6082.55 Analysis of 50 teeth (Estimated cost of $58.44 per tooth) Sequencing $444.00 Microsatellite analysis $640.00 Salary with fringe $1150.00 Other supplies, equipment $306.98 Indirect $381.15 Total $2922.13 Analysis of remaining teeth (approximately 250 @ $58.44 /sample) $14,610.00 Total $9404.68 $14,610.00 Related Federal Projects: N/A LITERATURE CITED ANDERSON, C. R., JR., F. G. LINDZEY, AND D. B. MCDONALD. 2004. Genetic structure of cougar populations across the Wyoming basin: metapopulation or megapopulation. Journal of Mammalogy 85:1207-1214. BEIER, P. 1993. Determining minimum habitat areas and habitat corridors for cougars. Conservation Biology 7:94-108. BOERSEN, M. R., J. D. CLARK, AND T. L. KING. 2003. Estimating black bear population density and genetic diversity at Tensas River, Louisiana using microsatellite DNA markers. Wildlife Society Bulletin 31:197-207. BOUTIN-GANACHE, I., M. RAPOSO, M. RAYMOND, AND C. F. DESCHEPPER. 2001. M13-tailed primers improve the readability and usability of microsatellite analyses performed with two different allele-sizing methods. Biotechniques 31:25-28. COUGAR MANAGEMENT GUIDELINES WORKING GROUP. 2005. Cougar management guidelines—first edition.WildFutures, Bainbridge Island, Washington, USA. CRONIN, M. A., S. C. AMSTRUP, AND K. T. SCRIBNER. 2006. Microsatellite DNA and mitochondrial DNA variation in polar bears (Ursus maritimus) from the Beaufort and Chukchi seas, Alaska. Canadian Journal of Zoology 84:655-660. CULVER, M., W. E. JOHNSON, J. PECON-SLATTERY, AND S. J. O’BRIEN. 2000. Genomic ancestry of the American cougar (Cougar concolor). The Journal of Heredity 91:186-197. 177 �DEYOUNG, R. W., AND R. L. HONEYCUTT. 2005. The molecular toolbox: genetic techniques in wildlife ecology and management. Journal of Wildlife Management 69:1362-1384. ERNEST, H. B., M. C. T. PENEDO, B. P. MAY, M. SYVANEN, AND W. M. BOYCE. 2000. Molecular tracking of mountain lions in the Yosemite Valley region in California: genetic analysis using microsatellites and faecal DNA. Molecular Ecology 9:433-441. ERNEST, H. B., W. M. BOYCE, V. C. BLEICH, B. MAY, S. J. STIVER, AND S. G. TORRES. 2003. Genetic structure of mountain lion (Cougar concolor) populations in California. Conservation Genetics 4:353-366. FREEMAN, A. R., D. E. MACHUGH, S. MCKEOWN, C. WALZER, D. J. MCCONNELL, AND D. G. BRAdley. 2001. Sequence variation in the mitochondrial DNA control region of wild African cheetahs (Acinonyx jubatus). Heredity 86:355-362. HAMPTON, J. O., P. B. S. SPENCER, D. L. ALPERS, L. E. TWIGG, A. P. WOOLNOUGH, J. DOUST, T. HIGGS, AND J. PLUSKE. 2004. Molecular techniques, wildlife management and the importance of genetic population structure and dispersal: a case study with feral pigs. Journal of Applied Ecology 41:735-743. KAHN, N.W., J. ST JOHN, AND T. W. QUINN. 1998. Chromosome-specific intron size differences in the avian CHD gene provide an efficient method for sex identification in birds. Auk 115:1074-1078. LOGAN, K. A., AND L. L. SWEANOR. 2001. Desert cougar: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C., USA. MCRAE, B. H., P. BEIER, L. E. DEWALD, L. Y. HUYNH, AND P. KEIM. 2005. Habitat barriers limit gene flow and illuminate historical events in a wide-ranging carnivore, the American cougar. Molecular Ecology 14:1965-1977. MENOTTI-RAYMOND, M. AND S. J. O’BRIEN. 1995. Evolutionary conservation of ten microsatellite loci in four species of Felidae. Journal of Heredity 86:319-322. MENOTTI-RAYMOND, M., V. A. DAVID, L. A. LYONS, A. A. SHCAFFER, J. F. TOMLIN, M. K. HUTTON, AND S. J. O’BRIEN. 1999. A genetic linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57:9-23. PAETKAU, D. AND C. STROBECK. 1994. Microsatellite Analysis of genetic variation in black bear populations. Molecular Ecology 3:489-495. PAETKAU, D., W. CALVERT, I. STIRLING, AND C. STROBECK. 1995. Microsatellite analysis of population structure in Canadian polar bears. Molecular Ecology 4:347-354. PAETKAU, D., G. F. SHIELDS, AND C. STROBECK. 1998. Gene flow between insular, coastal and interior populations of brown bears in Alaska. Molecular Ecology 7:1283-1292. SHIELDS, G. F. AND T. D. KOCHER. 1991. Phylogenetic relationships of North American Ursids based on analysis of mitochondrial DNA. Evolution 45:218-221. SINCLAIR, E. A., E. L. SWENSON, M. L. WOLFE, D. C. CHOATE, B. BATES, AND K. A. CRANDALL. 2001. Estimating gene flow in Utah’s mountain lions. Animal Conservation 4:257-264. ST JOHN, J., J. P. COTTER, AND T. W. QUINN. 2005. A recent chicken repeat 1 retrotransposition confirms the Coscoroba-Cape Barren goose clade. Molecular Phylogenetics and Evolution 37:83-90. TABERLET, P., J. J. CAMARRA, S. GRIFFIN, E. UHRES, O. HANOTTE. L. P. WAITS, C. BUBOIS-PAGANON, T. BURKE, AND J. BOUVET. 1997. Noninvasive genetic tracking of the endangered Pyrenean brown bear population. Molecular Ecology 6:869-876. TOMASIK, E. AND J. A. COOK. 2005. Mitochondrial phylogeography and conservation genetics of wolverine (Gulo gulo) of northwestern North America. Journal of Mammalogy 86:386-396. WARD, R. H., B. L. FRAZIER, K. DEW-JAGER, AND S. PAABO. 1991. Extensive mitochondrial diversity within a single Amerindian tribe. Proceedings of the National Academy of Sciences, USA 88:8720-8724. WOODS. J. G., D. PAETKAU, D. LEWIS, B. N. MCLELLAN, M. PROCTOR, AND C. STROBECK. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. 178 �APPENDIX I EXTRACTION OF DNA Extraction from animal tissue: Using the DNeasy Blood and Tissue Kit Procedure is based on the Protocol: Purification of Total DNA from Animal Tissues (SpinColumn Protocol), from the DNeasy Blood and Tissue HandBook (Qiagen, 2006) PROCEDURE 1. Cut up to 25 mg tissue into small pieces, and place in a 1.5 ml microcentrifuge tube. Add 180 µl Buffer ATL. 2. Add 20 µl proteinase K. Mix thoroughly by vortexing, and incubate at 56۫C until the tissue is completely lysed. Vortex occasionally during incubation to disperse the sample. 3. Vortex for 15 s. Add 200 µl Buller AL to the sample, and mix thoroughly by vortexing. Then add 200 µl ethanol (96-100%), and mix again thoroughly by vortexing. 4. Pipet the mixture from step 3 (including any precipitate) into the DNeasy Mini spin column placed in a 2 ml collection tube. Centrifuge at > 6000 x g (8000 rpm) for 1 min. Discard flowthrough and collection tube. 5. Place the DNeasy Mini spin column in a new 2 ml collection tube, add 500 µl Buffer AW1, and centrifuge for 1 min. at > 6000 x g (8000 rpm). Discard flow-through and collection tube. 6. Place the DNeasy Mini spin column in a new 2 ml collection tube, add 500 µl Buffer AW2, and centrifuge for 3 min at 20,000 x g (14,000 rpm) to dry the DNeasy membrane. Discard flowthrough and collection tube. 7. Place the DNeasy Mini spin column in a clean 1.5 ml or 2 ml microcentrifuge tube, and pipet 200 µl Buffer AE directly onto the DNeasy membrane. Incubate at room temperature for 1 min. and then centrifuge for 1 min. at > 6000 x g (8000 rpm) to elute. 8. Recommended: for maximum DNA yield, repeat elution once as described in step 7. Following DNA extraction, sample should be divided into at least two aliquots for storage or further analysis. Extraction from animal teeth: Using the DNeasy Blood and Tissue Kit 1. Place whole pre-molar tooth into a 1.5 ml microcentrifuge tube containing glass beads. 2. Add 180 ul Buffer ATL and 20ul proteinase K. Mix thoroughly by vortexing. 3. Incubate at 56C for approximately 3 hours. Vortex occasionally during incubation to disperse the sample. 4. Follow DNeasy Blood & Tissue kit protocol, starting with step 3 in protocol (see above). Extraction from animal feces: Using the QIAamp® DNA Stool Mini Kit Procedure is based on the protocol: Protocol for DNA Isolation from Larger Amounts of Stool and Protocol using Stool Tubes for Isolation of DNA from Stool for Human DNA Analysis, from the QIAamp® DNA Stool Mini Kit Handbook (Qiagen 2001). 1. Weigh the stool sample (we will use ~500 mg) and add 10 volumes of Buffer ASL (e.g. add 5 ml Buffer ASL to 500 mg stool). Vortex vigorously for 1 min or until the stool sample is thoroughly homogenized. 2. Pipet 2 ml of lysate into a labeled 2 ml microcentrifuge tube. 3. Go to step 4 of Protocol using Stool Tubes for Isolation of DNA from Stool for Human DNA Analysis. 4. Centrifuge sample at full speed for 1 min to pellet stool particles. 179 �5. Pipet 1.4 ml of the supernatant into a new 2 ml microcentrifuge tube and discard the pellet. 6. Add 1 InhibitEX tablet to each sample and vortex immediately and continuously for 1 min or until the tablet is completely suspended. Incubate suspension for 1 min at room temperature to allow inhibitors to adsorb to the InhibitEX matrix. 7. Centrifuge sample at full speed for 3 min to pellet stool particles and inhibitors bound to InhibitEX. 8. Immediately after the centrifuge stops, pipet all of the supernatant completely into a new 1.5 microcentrifuge tube and discard pellet. Centrifuge the sample at full speed for 3 min. 9. Pipet 25 µl Proteinase K into a new 2 ml microcentrifuge tube. 10. Pipet 600 µl supernatant from step 8 into the 2 ml microcentrifuge tube containing Proteinase K. 11. Add 600 µl Buffer AL and vortex for 15 s. 12. Incubate at 70۫C for 10 min. 13. Add 600 µl of ethanol (96-100%) to the lysate, and mix by vortexing. 14. Label the lid of the QIAamp spin columns provided in a 2 ml collection tube. Carefully apply 600 µl lysate from step 13 to the QIAamp spin column without moistening the rim. Close the cap and centrifuge at full speed for 1 min. Place the QIAamp spin column in a new 2 ml collection tube, and discard the tube containing the filtrate. 15. Carefully open the QIAamp spin column, apply a second aliquot of 600 µl lysate and centrifuge at full speed for 1 min. Place the QIAamp spin column in a new 2 ml collection tube, and discard the tube containing the filtrate. 16. Repeat step 15 to load the third aliquot of lysate onto the spin column. 17. Carefully open the QIAamp spin column and add 500 µl Buffer AW1. Centrifuge at full speed for 1 min. Place the QIAamp spin column in a new 2 ml collection tube, and discard the collection tube containing the filtrate. 18. Carefully open the QIAamp spin column and add 500 µl Buffer AW2. Centrifuge at full speed for 3 min. Discard the collection tube containing the filtrate. REAL TIME PCR Because we are interested in quantifying the amount of cougar DNA that is extracted from feces collected under differing conditions, merely using an estimate of DNA quantity from a spectrophotometer is problematic. This is because the DNA extracted from feces is likely comprised of DNA from prey and/or bacteria in addition to DNA from the mountain lion itself. To address this issue, we will attempt a new technique known as real time PCR to quantify the amount of target (i.e. mountain lion) DNA in the extraction. Real time or quantitative PCR detects products during the exponential phase of the reaction allowing for a more precise measurement of starting material since a direct relationship between quantity of target and product exists during this phase. An absolute quantitation method would be used so that different reactions can be compared. Three to four hydrolysis probes (such as TaqMan® probes) complementary to target species will be utilized in conjunction with dilutions of the DNA extractions. 180 �APPENDIX II-B PROGRAM NARRATIVE PILOT STUDY PLAN FOR MAMMALS RESEARCH FY 2006-07 State of Cost Center Work Package Task No. Colorado 3430 3003 : Division of Wildlife : Mammals Research : Predatory Mammals Conservation : Front-Range Cougar-Human Interactions: Feasibility Assessment of Techniques and Protocols FRONT RANGE COUGAR-HUMAN INTERACTIONS PILOT STUDY: FEASIBILITY ASSESSMENT OF FIELD TECHNIQUES AND PROTOCOLS Principal Investigators Mathew W. Alldredge, Wildlife Researcher, Mammals Research David J. Freddy, Mammals Research Leader Cooperators Scott Hoover, NE Regional Manager Mark Leslie, Dave Clarkson, Liza Hunholz, Reid DeWalt, NE Area Wildlife Managers Janet George, NE Senior Terrestrial Biologist Pilot Study Plan Approval Prepared by: Mathew W. Alldredge Date: 12/2006 Submitted by: Mathew W. Alldredge Date: 1/25/2007 Reviewed by: Brent Bibles Date: 2/15/2007 Date: Date: Reviewed by: Paul Lukacs Biometrician Date: 1/31/2007 Approved by: Dave Freddy Mammals Research Leader Date: 3/2/2007 181 �PROGRAM NARRATIVE PILOT STUDY PLAN FY 2006-07 FRONT RANGE COUGAR-HUMAN INTERACTIONS PILOT STUDY; FEASIBILITY ASSESSMENT OF FIELD TECHNIQUES AND PROTOCOLS A pilot study proposal submitted by: Mathew W. Alldredge, Wildlife Researcher, Mammals Research David J. Freddy, Mammals Research Leader NEED Animals have two choices as human populations encroach on wildlife habitats: they can leave the area or coexist with humans in altered habitats. When large animals choose to coexist, there are bound to be interactions between animals and humans. This is especially true for cougars in many areas across the United States, including the front-range of Colorado. Torres et al. (1996) found that cougar depredation on pets was strongly associated with new housing developments in California from 1979 to 1993. Cougar-human conflicts are inevitable in urban/exurban areas if viable cougar populations are to be maintained in these areas (Cougar Management Guidelines Working Group (CMGWG) 2005). Cougars are territorial, which implies they are space limited, and are also obligate carnivores on large ungulates, specifically deer and elk. Therefore, the options for cougars to relocate in response to human encroachment are limited. Potential prey for cougars also coexist with humans in relatively large numbers, which maintains these urban/exurban areas as effective cougar habitat. Although cougar attacks on humans are rare (CMGWG 2005), they have increased in recent decades. From 1890 to 1990 there were a documented 9 fatal attacks and 54 non-fatal attacks on humans in the United States and Canada (Beier 1991, Fitzhugh et al. 2003). Seven fatal and 38 non-fatal attacks on humans occurred following Beier’s 1991 publication and Fitzhugh et al.’s 2003 publication. Cougar attack rates on the front-range of Colorado have been estimated at one in every 2.2 million person-days. The increase in attacks also corresponds to a large increase in human-cougar incidents, which are likely due to habitat reduction, human encroachment, increased human recreational activities, and possible increases in cougar populations (CMGWG 2005). Torres et al. (1996) found no differences associated with gender in the likelihood of a cougar attack on humans. However, Ruth (1991) did find that subadults were the age group most likely to interact with humans. The CMGWG (2005) found that a combination of inexperience and unfamiliarity with their environment, as well as hunger, may cause young cougars to have more negative interactions with humans. Given that cougars currently coexist with humans within urban/exurban areas along Colorado’s front-range, varying levels of cougar-human interaction are inevitable. The Colorado Division of Wildlife (CDOW) is charged with the management of cougar, with management options ranging from minimal cougar population management, to dealing only with direct cougar-human incidents, to attempted extermination of cougars along the human/cougar spatial interface. Neither, inaction or extermination are practical options nor would they be agreeable to the majority of the human population. In the 2005 survey of public opinions and perceptions of cougar issues, 96% of the respondents agreed that it was important to know cougars exist in Colorado, and 93% thought it was important that they exist for future generations (CDOW, unpublished data). CDOW wildlife managers are faced with decisions about how to manage cougar populations and individual cougars in order to maintain viable populations and maintain acceptable levels of human safety. Defining acceptable levels of human safety is difficult because people’s perceptions are different 182 �when interactions do not directly affect them. In the 2005 public opinions survey, only 44% of respondents felt it acceptable to destroy a cougar that attacks and injures or kills a person that is recreating in cougar habitat, while 49% found eliminating the cougar unacceptable (CDOW, unpublished data). Other difficulties associated with managing cougar populations in areas with high levels of human interaction are caused by the limited amount of information that is currently known about cougars in these exurban situations and responses of cougars to management prescriptions (CMGWG 2005). There is a growing voice from the public that CDOW do more to mitigate potential conflicts (CMGWG 2005), and the Director of CDOW has requested that research efforts be conducted to help minimize future human/cougar conflicts. In order to meet these goals CDOW believes we need to directly test management prescriptions in terms of desired cougar population and individual levels of responses. Long-term study objectives for the Front-Range Cougar Research project will involve directly testing management responses of cougars at various levels of human interaction. The CMGWG (2005) recommend that part of determining the level of interaction or risk between cougars and humans is to evaluate cougar behavior on a spectrum from natural, to habituated, to overly familiar, to nuisance, to dangerous. These categories are defined as (CMGWG 2005): Habituated—frequent use of developed area and cougars appear comfortable in the presence of humans. Overly familiar—a cougar purposefully approaches a human, or allows a human to approach it after the cougar has seen the human. Nuisance—cougar exhibits overly familiar behaviors more than once. Dangerous—displayed non-defensive aggression towards humans (postures, vocalizations, and actions communicating an intent to harm). Note that aggressive behaviors could also be defensive if the cougar perceives the human as a threat to itself, its young, or a food source, or if the cougar is surprised or harassed by humans. The CMGWG (2005) describes cougar behaviors and the level of risk to humans as perceived by the authors (Appendix I, Table 1). We have added an additional column that categorizes the level of risk, which will be used to determine management treatments that will be applied during research efforts. Although cougars may habituate to human developments and activities (Ruth 1991), both habituated and nonhabituated cougars may experiment with humans as potential prey (Aune 1991). The CMGWG (2005) clearly state that there is no scientific evidence to indicate that cougar habituation to humans affects the risk of attack. Clearly, cougars representing a danger to human health and safety should be removed, but the appropriate response to cougars that are overly familiar or habituated to humans is unclear. There have been no studies confirming the effectiveness of aversive conditioning (CMGWG 2005). There is also a paucity of information on relocation success. The information that does exist suggests that relocation distances should be large (Ruth et al. 1998) and that survival may be low (Ross and Jalkotzy 1995, Ruth et al. 1998) Studying individual and population level responses of cougars will require capturing and radiocollaring cougars, as well as standardizing responses of CDOW personnel to human/cougar interactions. Therefore, in this initial year, we need to test various cougar capture techniques in urban/exurban areas of interest for effectiveness and public acceptance and to assess the reliability of GPS collars as monitoring 183 �tools to assess cougar responses to management prescriptions. More importantly, clearly defined protocols have been developed within CDOW (Appendix I) to direct how researchers and field managers should deal with various levels of risk to human health and safety, and these protocols need to be tested and evaluated in the field. A large portion of the front-range is a mosaic of private, and city or county owned public lands. An assessment of capture techniques will allow future assessments of research feasibility and limitations that might be imposed by various land ownerships. Testing capture techniques and potential management actions will also allow for an assessment of the receptiveness of future research within the various political/social environments. A working document has been developed, defining internal CDOW protocols for dealing with cougar in urban areas that outline procedures, involvement, and communication between research and field management personnel based on perceived risk to public safety (Appendix I). Standardized protocols are needed to maintain requisite levels of consistency within study populations. These protocols will also focus liability, political, and social pressures on CDOW as a whole, and not on individuals or sections within CDOW. One objective of this pilot year study is to test management and communication protocols and modify protocols as needed prior to conducting large scale research studies requiring larger commitments of time and resources. OBJECTIVES 1. Determine the effectiveness of cage traps and hounds for capturing cougars on the FrontRange of Colorado. 2. Determine functionality and suitability of GPS collars in front-range habitats. 3. Implement cougar-human risk protocols and communications within CDOW and among public entities and determine if modifications are necessary. 4. Determine the feasibility of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and rubber bullets. 5. Evaluate political/social response to cougar research activities. EXPECTED BENEFITS Information obtained from this pilot study will be valuable in designing future studies in terms of logistical and social limitations. Determining the effectiveness of capture methods as well as GPS collars will define the limitations of future studies and realistic objectives. Testing cougar-human risk protocols is also essential in order to construct research projects that will fit within CDOW operational constraints and avoid liability issues with the public. Finally, assessing public support and reactions to research efforts during this pilot study is important so that the possibilities of losing support during longer term research efforts is minimized or at least understood. APPROACH Long-term research efforts will test the working hypothesis that specific management actions can affect the distribution, behavior or population structure of cougars in order to minimize negative cougar/human interactions. In order to successfully test such hypotheses we will need to capture, GPS collar, VHF collar, and monitor cougars along the front-range and maintain control over other external anthropogenic factors. A pilot study will be initiated in January 2007 to test the logistical, social, and political constraints that will govern the conduct of cougar research along the front-range. As these constraints are understood, long-term research studies will be designed and implemented to test the efficacy of particular management prescriptions. 184 �The pilot study will be conducted in Boulder and Jefferson counties, in an area from near Interstate 70 north to approximately Lyons, Colorado, which is also a likely area for addressing long-term research objectives. This area is comprised of many land ownerships, including private, Boulder city, Boulder county, Jefferson county, and state and federally owned lands. Therefore, we will be directly involved with Boulder city and Boulder and Jefferson county governments and will obtain agreements from these entities on conduct of research and protocols for dealing with potential human/cougar interactions prior to conducting any capture efforts. These entities will also be informed when research efforts are being conducted on their respective properties. Prior to conducting this pilot study, management treatments addressing human/cougar interactions that may take place with individual collared cougars will be agreed upon. This agreement will be among the local DWM’s, AWM’s, biologists and research staff, and will be within the “Internal Colorado Division of Wildlife Protocols for the Front-Range Cougar Research Project,” developed and approved by CDOW. Agreements will include information transfer among CDOW research, management, and external entities, as well as management actions to be tested on cougars at various levels of human interaction. We will attempt to capture 2 cougars in 3 areas; Boulder city open space on the south side of Boulder, Boulder county open space to the north of Boulder, and Jefferson county open space to the south of Boulder. Two to four cougars will be captured using cage traps baited with deer carcasses. Deer carcasses will either be from known cougar cache sites or from road kill. An additional two to four cougars will be captured using hounds to tree individual cougars. Hounds used will be experienced in capturing cougar and may be provided by USDA APHIS-Wildlife Services under the auspices of a working agreement existing between Wildlife Services and CDOW. With complex land ownerships, hounds may be used in small numbers and on leashes as part of a cooperative effort with Wildlife Services to evaluate the effectiveness of leashed hounds. A leash will be necessary to prevent hounds from following cougars onto private lands where we lack permission for pursuit and capture. All captured cougars will be fitted with Lotek 4400S GPS collars. Additionally, cougars will be ear-tagged in each ear with uniquely identifiable numbers, tattooed if required by directive W-20, and a genetic sample collected using an ear-punch. Sex, approximate age from tooth wear, weight and morphometric measurements will be recorded. Vital signs will also be monitored during handling of cougars. See Appendix II for a detailed description of capture and handling protocols. In order to develop an understanding of how cougars are using habitats during normal activity periods, responding to human activity diurnally, and to optimize battery life for GPS collars, location acquisition will occur eight times per day and information downloads will occur once per month. Additional monitoring may be done using the VHF signal from the collars. If aversive conditioning is being considered for an individual the collar may be downloaded more frequently to determine the timing and effectiveness of aversive conditioning. Additionally, if an individual cougar is thought to be a risk to human safety more frequent downloads may be required. Capture efforts will be assessed based on the number of successes versus the number of attempts and the amount of effort per success. Also a descriptive assessment of feasibility for the various methods will be made. Similarly, acquisition rates will be determined for the GPS collars, accounting for time of day and other temporal fluctuations to determine if these collars will provide the desired data for cougars along the front-range. Responses of collared cougars to aversive conditioning or other management actions will also be monitored and summarized descriptively, which will provide information for designing future studies. At this time, we consider aversive conditioning treatments on cougars to potentially be: multiple captures and handling of cougars, single or multiple treatments using rubber 185 �buckshot fired from a shotgun, and single or multiple chases using hounds, and potential combinations of capture, hound chases, and rubber buckshot. During the pilot project all cougars will be potential candidates for aversive conditioning in order to evaluate methods of implementing these techniques in a preventative manner. Protocols for managing cougars at various levels of human interaction and for internal and external communication will also be evaluated and modified throughout this pilot study phase. Periodic assessments will be made by all individuals directly involved with the pilot work to determine if the protocols are sufficient to provide the structure to conduct more intensive research efforts. Public response to research efforts, including capture methods, aversive conditioning, and monitoring, in terms of public complaint, will also be evaluated and assessed in relation to future research efforts. Protocols will be assessed via internal CDOW discussions and in discussions with other cooperating agencies. Public attitudes will be assessed via media articles or coverage of the project and via interviews or limited surveys/interviews of individual citizens. The above information will then be used to design future research efforts specifically developed to directly assess management prescriptions. The logistical, social, and political information obtained from this pilot effort will define the limits of what can be done, where the project can be conducted, and possibly add direction to initial efforts of studying the human-cougar interface. Long-term studies will begin by 2008, and previously collared cougars will likely be integrated into these studies. LOCATION OF WORK The pilot study will be conducted in Boulder and Jefferson counties, in an area from Interstate 70 north to approximately Lyons, Colorado, which is also a likely area for addressing long-term research objectives (Figure 1). SCHEDULE OF WORK Time Jan-Feb 2007 Jan-Feb 2007 Mar-April 2007 Mar-Dec 2007 April-Dec 2007 Activity Study Plan/ACUC Approval Open Space entities approval/access Capture effort Monitoring Aversive conditioning 186 �ESTIMATED COSTS Category Personnel Field Technician(s) (6 months) Operating Expenses Cage Traps (2) Field/Capture Equipment Lotek GPS collars (6) & download receiver (purchased in 2005 budget year) Telemetry Receivers & Antennas Aphis (houndsmen) Travel Total 2006-2007 $14050 $5000 $4000 ($32,000) $1900 $7000 $1,000 32,950 RELATED PROJECTS Uncompahgre cougar research project near Montrose, CO conducted by CDOW and cougar project being conducted in and around Rocky Mountain National Park by NPS-USGS. LITERATURE CITED AUNE, K. E. 1991. Increasing cougar populations and human-cougar interactions in Montana. Pages 86-94 in C. E. Braun, editor. Cougar-human interactions: Symposium and Workshop. Colorado Division of Wildlife, Denver, Colorado, USA. BEIER, P. 1991. Cougar attacks on humans in the United States and Canada. Wildlife Society Bulletin 19:403-412. COUGAR MANAGEMENT GUIDELINES WORKING GROUP. 2005. Cougar Management Guidelines, 1st edn. WildFutures, Bainbridge Island, Washington, USA. FITHZUGH, E. L., M. W. KENYON, AND K. ETLING. 2003 Lessening the impact of a cougar attack on a human in Proceedings of the Seventh Cougar Workshop, Jackson, Wyoming, USA. ROSS, P. I. AND M. G. JALKOTZY. 1995. Fates of translocated cougars, Felis concolor, in Alberta. Canadian Field-Naturalist 109:475-476. RUTH, T. K. 1991. Cougar use in an area of high recreational development in Big Bend Natinal Park, Texas. Thesis, Texas A&M University, College Station, Texas, USA. RUTH, T. K., K. A. LOGAN, L. L. SWEANOR, M. G. HORNOCKER, AND L. J. TEMPLE. 1998. Evaluating cougar translocation in New Mexico. Journal of Wildlife Management 62:1264-1275 TORRES, S. G., T. M. MANSFIELD, J. E. FOLEY, T. LUPO, AND A. BRINKHAUS. 1996. Mountain lion and human activity in California: testing speculations. Wildlife Society Bulletin 24:451-460. 187 �Figure 1. Initial study area 2007. 188 �APPENDIX I COLORADO DIVISION OF WILDLIFE PROTOCOLS FOR FRONT RANGE COUGAR PILOT RESEARCH PROJECT Public safety will be the fundamental issue guiding decisions on how to respond to and manage human interactions involving cougars radio-collared for the Colorado Division of Wildlife (CDOW) Front-Range cougar research project. CDOW Administrative Directive W-20 will serve as a basic guideline for managing cougar incidents. These protocols amend Administrative Directive W-20 and provide guidance specific to the Front-Range cougar research project. Human safety will not be compromised for research purposes; original guidelines in Directive W-20 will be explicitly followed for cougar-human interactions defined as ‘Level D-Attack’ in W-20. These amendments allow additional flexibility and options for managing lower level cougar-human interactions as part of the research and management evaluation process. Under the management guidelines of Directive W-20, section C, it is specified that any cougar that is tranquilized, handled and released by the Division under the authority of W-20 will be ear-tagged with the appropriate color tag for that region, and will be tattooed on the inside of the ear prior to release. All cougars captured for research purposes will also be ear-tagged with the appropriate color for the region using a tag code starting with an R followed by a three digit number. Cougars will only be tattooed on the inside of the ear if they would have been tranquilized, handled and released by the division under the authority of W-20 regardless of the associated research project. If tattooing does occur, the tattoo will match the code used on the ear-tag. The purpose of the Front Range cougar project is to expand our understanding of how to better manage cougar-human interactions within the expanding suburban-rural human environment so that we can sustain both the existence of cougars and ensure public safety. For this study to succeed we must capture and radio-collar cougars that live in or near the suburban-rural environment to acquire basic information on cougar movements and prey selection and the potential for cougars to interact with humans. An inherent risk is that some radio-collared cougars will, at some point in time, likely interact to some degree with humans. These management protocols will provide CDOW managers and researchers an initial menu of choices to consistently guide decisions involving interactions between radio-collared cougars and humans. Cougars will be radio-collared by capturing cougars during planned and systematic efforts or opportunistically during low-level human-interaction circumstances. Protocols address 5 major topics: A) radio-collared cougars, B) project communications, C) research data, D) external media, and E) cooperators awareness of ongoing proposed project protocols and study plan. These protocols will be a ‘living document’ that will evolve as the research project progresses with the input of field managers and researchers. Changes to the protocols will occur through informed discussions among CDOW managers and scheduled as needed as the research project unfolds or objectives are modified. 189 �A. INTERNAL CDOW PROTOCOLS FOR MANAGING FRONT RANGE RESEARCH RADIOCOLLARED COUGARS a. Cougar-Human Interaction Levels Interactions involving radio-collared cougars and humans will span a potential range from benign to dangerous as depicted in the diagram below (Levels I – V). I..Cougar not seen, or detected, by public, nor near human dwellings or infrastructure. II. Cougar sighted by public or passes near human infrastructure but no level of interaction between cougar and humans and not perceived as a safety concern. III. Cougar seen by public or passes near human infrastructure with some low level of interaction between cougar and humans but no threatening behavior documented. V. Cougar seen by public or passes near human infrastructure with a level of interaction between cougar and humans considered to be dangerous to humans. IV. Cougar seen by public or passes near human infrastructure with a level of interaction between cougar and humans reasonably considered to be threatening to humans. Defining the risk to humans that could be associated with observed cougar behaviors is difficult. We relied on the interpretations of cougar behavior as outlined in the Cougar Management Guidelines and adapted these interpreted levels of risk to our cougar-human interaction Levels 1 -5 (Table 1). Interpretations of cougar behavior would be highly dependent on the observer’s skills and experience and the skills and experience of CDOW personnel who would interview the person who had the interaction with the cougar. In threatening or dangerous interactions (Levels 4 and 5), investigating personnel would attempt to determine whether the cougar was defending an animal carcass, kill site, den site, or young. 190 �Table 1. Interpretations of cougar behaviors occurring during cougar-human interactions in order of increasing risk to humans. Columns 1-3, except for ‘Attack” behavior, were copied from the ‘Cougar Management Guidelines Working Group, 2005, Wild Futures Press’ while column 4 represents Levels of Interaction as defined for these Front Range Cougar project protocols. Human Observation of Cougar Behavior Cougar opportunistically viewed at a distance Cougar flight or hiding Cougar lack of attention, various movements not directed towards person. Cougar has various body positions, ears up, may be shifting positions, intent attention, following behavior Intense staring, following and hiding behavior Hissing, snarling, vocalization Crouching, tail twitching, intense staring, ears flattened like wings, body low to ground, head may be up Ears flat, fur out, tail twitching, body and head low to ground, rear legs “pumping” Cougar attempts to or actually strikes, claws, or physically comes into contact with human. Interpretation of Cougar Behavior Secretive Level of Likely Human Risk Low Avoidance Low Indifference or actively avoiding inducing aggression Curiosity Low Front-Range Cougar Risk Category Non-threatening, Level 2 Non-threatening, Level 2 or 3 Non-threatening, Level 2 or 3 Low, provided human response is appropriate Non-threatening to threatening, Level 3 or 4 Assessing success of attack Defensive behaviors, attack may be imminent Pre-attack Moderate Threatening, Level 4 Moderate depending on distance between human and cougar High Threatening, Level 4 Imminent attack Very High and Immediate Dangerous, Level 5 Attack Extremely High Dangerous, Level 5 Dangerous, Level 5 An indirect interaction between humans and cougars involves cougars and domestic pets or livestock and such interactions do occur along the Front Range. There is the possibility that pet-cougar interactions may be a signal that a cougar may be inclined to eventually become involved in a cougarhuman interaction. Similar to cougar-human interactions, we propose a gradient of cougar-pet/livestock interactions that would be assessed relative to the risk of these cougar behaviors to humans (Table 2). Key distinctions among cougar-pet/livestock interactions are whether the incident happened in an open space area and ‘off-leash’, within a confined area such as a fenced yard, within animal/livestock holding pen, or while the pet/livestock was on leash/halter and accompanied by a human. Definitions of domestic pet and domestic livestock will follow guidelines established for W-20. 191 �Table 2. Interpretations of cougar behaviors occurring during cougar-pet/livestock interactions in order of increasing risk to humans. Human Observation of Cougar Behavior Associated with Pet or Livestock Cougar seen in proximity to domestic pet/livestock Cougar displays flight or hiding Cougar approaches pet/livestock, displays various body positions, ears up, intent attention, following behavior Hissing, snarling, vocalizations Crouching, tail twitching, intense staring, body near or low to ground, rear legs may be ‘pumping’ Cougar kills or injures pet Cougar kills or injures livestock Interpretation of Cougar Behavior Front-Range Cougar Risk Category when Occurs in Open Space or Similar Areas away from Dwellings Front-Range Cougar Risk Category When Occurs in Confined Area or On Leash Accompanied by Human Secretive or possibly Curious Non-threatening, Level 1 Non-threatening, Level 2 Avoidance Non-threatening, Level 1 Non-threatening, Level 2 Curiosity or possibly assessing success of attack Non-threatening, Level 2 Non-threatening, Level 3, providing human response is appropriate. Defensive behavior, or possible attack Pre-attack or Imminent Attack Non-threatening, Level 2 Non-threatening, Level 3, or Threatening Level 4 if pet closely accompanied by a human Non-threatening Level 3, or Threatening Level 4 if pet closely accompanied by a human Attack Occurred Level 3 Attack Occurred Level 3 Non-threatening, Level 3 Threatening Level 4, or Dangerous Level 5 if pet closely accompanied by a human Threatening Level 4, or Dangerous Level 5 if livestock closely accompanied by a human b. Decision Process for Evaluating Responses to Cougar-Human Interactions Abbreviations in this section used in reference to CDOW personnel positions are: District Wildlife Manager (DWM), Area Wildlife Manager, (AWM), Regional Manager (RM), Wildlife Researcher (WR), Wildlife Research Leader (RL), Terrestrial Section Manager (TSM). At any level of cougar-human interaction, the minimum Decision Response Team will consist of the primary WR, the area DWM, and the appropriate area AWM, unless immediate action is needed to benefit public safety whereby the AWM could act independently of the Decision Response Team. Input and options provided by all 3 of these persons will be assessed by the group which will attempt to reach a consensus decision. The Decision Response Team will objectively weigh the options available for each interaction/situation and make the most appropriate decision that considers the objectives of the research project while maintaining public safety. The decision will be a process of informed judgment. The AWM, or AWM designee, will be the official CDOW representative for the final decision. If the Decision Response Team cannot reach a decision of consensus, then the AWM will engage the RM, RL, and TSM in the decision process. At any level of response, any member of the response team may opt to consult with appropriate adjoining AWMs, RM, RL and TSM. The AWM will be responsible for forwarding situational and decision information to appropriate field personnel via internal email, phone, 192 �or via the Public Information Specialist. The CDOW Regional Public Information Specialist will be responsible for providing information to the CDOW Denver Public Information Specialist and the media. As the level of cougar-human interaction increases from Level 1 to Level 5, the decision rationale shall shift and become more weighted towards public safety and preventing further cougarhuman interactions as opposed to assessing or moderating cougar behavior. Decisions would therefore shift towards reducing imminent risks to humans. Examples of Cougar-Human Interaction Decision Options: Example situations representing radio-collared cougar interaction Levels 1-5 and possible response decision options for responding to the interaction situation are presented below. The known history/behavior of a cougar in relation to levels of human interaction will weigh heavily on research/management decision options. We emphasize that the situations described below are not all encompassing. Furthermore, there may be rare situations where cougar-human interactions occur that prevent responsive management options because of extraneous factors such as access, snow conditions, or proper identification of the interacting cougar. Level 1. A radio-collared cougar is known to remain in open space lands, utilize natural prey, and utilize areas near public trails based on radio-telemetry information but is not known to have been seen by the public or involved in any level of interaction. Research/Management Options: a. No management prescriptions are applied to the cougar. b. 'Cougar In Area' signs may or may not posted on nearby public trails. c. Aversive conditioning tactics are applied to the cougar consistent with the research study design. Level 2. A radio-collared cougar is known to remain primarily in open space lands and utilize natural prey but is seen by the public near a public trail or is seen or is otherwise documented to occasionally be near human residences or businesses. Additionally, a cougar not previously radio-collared is seen by the public near a public trail or is seen or is otherwise documented to occasionally be near human residences or businesses Research/Management Options: a. No management prescriptions are applied to the radio-collared cougar. b. The cougar is captured and radio-collared and subjected to management prescriptions consistent with the research study design. c. “Cougar In Area” signs may or may not be posted on nearby public trails. d. “Cougar In Area” signs are posted near human infrastructure. Persons living or working within affected human infrastructure are directly contacted by CDOW. e. Aversive conditioning tactics are applied to the cougar consistent with the research study design. Aversive conditioning tactics may include; pursuing cougar with trained hounds, pepper spray application to cougar, or impacting cougar with rubber pellets fired from a shotgun. f. Cougar is captured for the first time, or recaptured and relocated to an appropriate area of natural habitat consistent with the research study design. Relocation distances shall not be constrained by Directive W-20. Level 3. A radio-collared cougar is known to use open space lands and areas having considerable human infrastructure. The cougar has been, or is likely to have been seen by the public on more than 1 occasion near human residences, businesses, or schools and there is reasonable concern for public safety but the 193 �cougar has not been perceived as exhibiting any current or past level of threatening behavior. Additionally, a cougar not previously radio-collared is known or likely seen by the public on more than 1 occasion near human residences, businesses, or schools and there is reasonable concern for public safety because of proximity, but the cougar has not been observed as exhibiting any current or past level of threatening behavior. Research/Management Options: a. No management prescriptions are applied to the radio-collared cougar but monitoring of cougar behavior is intensified by obtaining multiple telemetry locations per day and attempting multiple visual monitoring sessions per day. b. The non-collared cougar is captured and radio-collared, subsequent behavior is closely monitored by obtaining multiple telemetry locations per day and attempting multiple visual monitoring sessions per day. c. Warnings are posted or communicated to the appropriate public using signs or other media. d. Newly collared or previously collared cougars could be subjected to management prescriptions consistent with the research study design. e. Aversive conditioning tactics are applied to the cougar consistent with the research study design. f. Cougar is recaptured and relocated to an appropriate area of natural habitat consistent with the research study design. g. Cougar is recaptured, additional aversive conditioning tactics are applied to the cougar, and the cougar is relocated to an appropriate area of natural habitat consistent with the research study design. Level 4. A radio-collared cougar is known to use open space lands and areas having considerable human infrastructure. The cougar has been or is likely to have been seen by the public on several occasions near human residences, businesses, or schools, or there is 1 documented interaction where the behavior of the cougar was reasonably considered to be somewhat threatening to humans but there was no evidence of attacking humans (such as cougar defending an animal carcass, kill site, den site, or young as demonstrated by snarling and vocalizing without stalking). Additionally, a cougar not previously radiocollared is known or likely seen by the public on several occasions near human residences, businesses, or schools, or there is 1 documented interaction where the behavior of the cougar was reasonably considered to be somewhat threatening to humans but there was no evidence of attacking humans (such as cougar defending an animal carcass, kill site, den site, or young as demonstrated by snarling and vocalizing without stalking). Research/Management Options: a. Warnings are posted or communicated to the appropriate public using signs or other media, and, b. The non-collared cougar is captured and radio-collared, or if involving a previously radiocollared cougar, the subsequent behavior of either cougar is closely monitored by obtaining multiple telemetry locations per day and attempting multiple visual monitoring sessions per day. c. Aversive conditioning tactics are applied to the cougar consistent with the research study design. d. Cougar is initially captured and radio-collared, or recaptured, additional aversive conditioning tactics are applied to the cougar, and the cougar is relocated to an appropriate area of natural habitat consistent with the research study design. e. If a cougar is involved in 1, Level 4 interaction and subsequently becomes involved in another Level 4 interaction, the cougar is euthanized. f. Cougar is captured and euthanized. 194 �Level 5. A cougar, whether previously radio-collared or non-collared, is involved in 1 interaction where the behavior of the cougar was highly threatening to humans or an attack of a human occurred. Research/Management Options: a. Actions follow protocols outlined in W-20, Level D-Attack. Attempts are made to capture the cougar and likely euthanize the cougar. Cougars that must be euthanized will be necropsied by the Colorado State University pathology laboratory with reports provided to the Area Wildlife Manager, primary Wildlife Researcher, and the CDOW Wildlife Health Section. Remains of the cougar, such as head, hide, and tissue will be disposed of based on existing CDOW Regional guidelines with decisions the responsibility of the appropriate AWM. B. INTERNAL CDOW PROTOCOLS MANAGING FRONT RANGE COUGAR RESEARCH COMMUNICATIONS This research project will demand frequent and routine communication between Research, Terrestrial biologists, Area Field Operations personnel, and CDOW Regional and Denver Public Information Specialists. Timing of routine field activities such as baiting, trapping, capturing, and handling of cougars and monitoring of radio-collared cougars will be communicated frequently via email or phone in order to achieve coordinated success of such activities and to maintain informed local knowledge of radio-collared cougar behavior and whereabouts. For cougar-human interaction concerns, the minimum communication tree will be the WR, DWM, AWM, RL, and Senior Terrestrial biologist responsible for the geographic area(s) containing the field research activities and/or inhabited by the radio-collared cougar. Communication should be by cell phone, communications radio, or email as needed for appropriate expediency. Frequency of communication will be decided mutually among these 5 persons. Behavior of individual cougars, and especially changes in behavior of cougars, may necessitate changes in frequency of communication. As the potential for a cougar-human interaction increases from Level 1 to Level 5 as judged by the Decision Response Team based on acute or cumulated changes in cougar behavior or cougar location, communication frequency will increase, and ultimately communications will be a part of and dictated by the Decision Response Team. At any time the AWM or RL can expand the communications tree to include the TSM, RM, or other CDOW representatives but will also be responsible for sending the communications to these additional levels. The AWM will be responsible for disseminating appropriate information to other appropriate agencies or entities. The AWM will communicate with the Regional Public Information Specialist who will be responsible for coordinating activities with and providing information to the Denver Public Information specialist and the media. C. INTERNAL CDOW PROTOCOLS FOR MANAGING FRONT RANGE COUGAR RESEARCH DATA Because the cougar project will be high in profile and involves human safety issues, there will be a constant demand for information because of the perceived ‘need to know’ both by internal CDOW staff and the public. Finding the correct balance between the time spent obtaining information and the time spent distributing information, and to whom, will be a learning process and there will be real costs involved in personnel time. Furthermore, what information is distributed and to whom will be a learning 195 �process. The Decision Response Team shall clearly state that no 'real-time' data of cougar activity will be released, primarily because 'real-time' data capabilities will not be possible within the scope of the project. Under current CORA guidelines, subject to legal interpretation, the raw, non-summarized data obtained during an on-going research project is protected from being obtained by the public via CORA. Examples of raw data would be the actual latitude-longitude or UTM coordinates of cougar locations or locations of critical den sites or kill-caches. Our intent is that this raw data would not be released to the public at-large, not only to protect the cougars as individuals, but also to protect our copyright on the data the agency has obtained. The current lynx reintroduction project sets a precedent for this approach with the caveat that lynx are a threatened species. As part of the internal-only communication process and internal agency ‘knowledge gathering’ the WR will, once per month, provide the appropriate DWM, AWM, RL, and Senior Terrestrial biologist with e-maps (jpeg files) showing the distribution of radio-collared cougars in relation to important topographic and cultural features, so that these CDOW individuals are adequately aware of cougar locations and movement patterns. If cougar behavior changes such as to increase the likelihood of cougar-human interactions, monitoring of the cougar using VHF telemetry will be increased and frequency of internal communications will increase appropriately. The AWM and WR will work together to provide a reasonable frequency of ‘internal-only’ information transfer with both individuals cognizant of the trade-offs between study objectives and needs and human safety issues. Cooperating public landuse agencies will be provided the same information on the same established schedule so as to keep these entities similarly informed. The AWM, WR, RL, and the Regional Public Information Specialist will cooperatively discuss what type of information is released to the public and when such releases occur. However, as the public learns that CDOW has gained information about cougars in suburban-rural areas because CDOW radiocollared cougars and employed GPS collars and can map detailed cougar locations, post-event, CDOW can expect a variety of demands for information that will need to be addressed and a rising challenge as to how often and in what detail information is provided. The WR will provide a written report by 1 October summarizing the progress of the research project on an annual basis to Area and Regional personnel. This report will be available to the public through our standard Wildlife Research Report distribution process. D. EXTERNAL COMMUNICATIONS The Front Range cougar research project will attract the interest, curiosity, and involvement of the media such as newspapers, magazines, radio, and television. Appropriately interacting with the media will be important to maintaining credibility with the public and with providing educational opportunities to the public. Requests by the media for involvement with the research project should be assessed as consistently and appropriately as possible by the Decision Response Team. The Decision Response Team shall clearly state that no 'real-time' data of cougar activity will be released, primarily because 'real-time' data capabilities will not be possible within the scope of the project. We propose that requests be assessed as a dichotomy of cougar-human 'non-incident' and 'incident' requests (Table 3). 196 �Table 3. Guidelines for responding to requests from the media. Media Involvement Request Field Trip on Project Activities Filming or Photographing Project Activities Interview of Project Personnel Request Associated with Non-Interaction Cougar-Human Activity Media schedules time with CDOW Field Personnel; Activity will not jeopardize key field activities such as capturing & handling cougars or create unnecessary safety issues. Researcher identifies most appropriate time for activity to the Decision Response Team. Decision Response Team will notify Regional Public Information Specialist. Filming/photography to be done by CDOW information specialists who will provide footage/photos to media for media use. Filming coordinated by Decision Response Team. CDOW retains right to review all footage/photos prior to release whether provided by CDOW or private media. Decision Response Team will notify Regional Public Information Specialist. Requests for interviews of project personnel will be relayed to the Decision Response Team whenever possible. Interviews will occur to minimize interrupting routine project activities. As a minimum, the RL and the AWM will be notified of the request to conduct the interview. Decision Response Team will notify Regional Public Information Specialist. Request Associated with Cougar-Human Interaction Likely Not Appropriate, Follow W-20 Guidelines- Follow W-20 Guidelines Follow W-20 Guidelines with the exception that questions pertaining to research project objectives, research results, and research protocols will be deferred to the Decision Response Team for accurate answers. E. DOCUMENT COOPERATORS AWARENESS OF FRONT-RANGE COUGAR RESEARCH PROJECT We recommend that representatives of cooperating entities, such as, Boulder County Parks and Open Space, Jefferson County Open Space, and City of Boulder Open Space and Mountain Parks be made aware of these protocols and the CDOW approved research study plan that will guide this project. Bruce L. McCloskey, Director Colorado Division of Wildlife Approval to Implement These Protocols for Front Range Cougar Research Project Date 197 �APPENDIX II CAPTURING AND HANDLING PROCEDURES FOR FREE-RANGING COUGARS Modified by MWA on 1/18/2007: Puma changed to cougar and schedule for monitoring cage traps modified after consultation with CDOW veterinarian L. Wolfe. Delivery of anesthetic drugs via projectile syringe or jab pole, cage traps, or foot snare may be used to capture cougars. All of these techniques have proven effective and safe for capturing cougars under field conditions commonly encountered in Colorado. This document is intended to serve as a comprehensive reference for future cougar studies to avoid unnecessary complexity in study protocols submitted for ACUC review. CAPTURE TECHNIQUES Trained hound pursuit As described in Shaw (1979), an experienced houndsman with trained dogs is used to track and tree or bay each cougar. Field anesthesia is determined under the supervision of the attending veterinarian. Anesthetic drugs will be administered intramuscularly (preferably the caudal thigh) via projectile syringe using a gas-powered projector. For capture, cougars will be anesthetized with Telazol® (6-9 mg/kg) and xylazine HCl (1.8-2 mg/kg) or ketamine (10-11mg/kg) and xylazine HCl (1.8-2mg/kg) or ketamine (2 mg/kg) and medetomidine (0.075 mg/kg) (Shaw 1979, Logan et al. 1986, Kreeger 1996). See drug dosages below (Table 1, Appendix II). If the cougar is treed, then people and dogs should be removed from the immediate area to give the animal a chance to descend before becoming completely anesthetized. If the cougar remains in the tree until almost completely anesthetized, then someone wearing climbing gear will climb to the cougar and attach either a chest harness (preferred) or hind leg noose (e.g. bovine hobbles) to 2 legs and quickly lower the animal to the ground. If possible, other personnel will hold a taunt net, 3 by 3 meters square, below to break the cougar’s fall should it slip before a harness or rope can be secured. If there aren’t enough people to hold the net, anchor the net about 2 m above the ground and on adjacent trees or branches using ropes & carabiners. Occasionally cougars will jump from the tree immediately after being darted. If there is snow cover, the cougar should be tracked with the dogs on leads. Attention should be given to changes to the cougar’s gait and direction of travel. When anesthesia is effective, the cougar’s tracks will weave and show signs of stumbling. Usually the cougar can be found laying or sitting on top of the snow. If after 15 minutes, it appears that the cougar is traveling normally, then dogs can be released on the cougar’s tracks again to encourage it to tree. If the ground is bare, then at least one non-aggressive dog can be released on the cougar’s trail to drive it to bay. If the cougar is radio-collared, radio-telemetry can be used to track the cougar. Upon first approach of an apparently anesthetized cougar, a 4-5 foot stick will be used to gently prod the paws and muzzle of the animal; if there is no response (i.e. snarling or biting), then assume anesthesia is sufficient for handling. Once anesthetized apply an antibiotic or mineral oil based eye ointment and a blindfold to reduce visual stimuli and protect the eyes from bright sun light and debris. Vital signs should be monitored in the anesthetized cougar. Normal signs: pulse ≈ 70―80 bpm, respiration ≈ 20 bpm, capillary refill time ≤2 sec., rectal temperature ≈ 101oF average, range = 95―104oF (Wildlife Restraint Handbook, 1996, California Dep. of Fish and Game, Wildlife Investigation Laboratory, Sacramento, Kreeger et al. 2002). In temperatures near or at sub-freezing wrap the 198 �anesthetized cougar in a thermal blanket. In hot temperatures, the cougar should be treated with water on the head, abdomen, and inguinal area. Cougars that receive lacerations during capture will be given antibiotics. When the cougar is being sampled it should be moved from one side to the other or in sternal recumbency about every 10 minutes to prevent hypostasis in the downside lung. When sampling procedures are completed, the blind-fold and leg restraints (e.g. hobbles or snare cable) will be quickly removed, and the cougar will be allowed to recover from the sedation either naturally or with the aid of an antagonist. When prescribed, yohimbine HCl (0.125 mg/kg IV) will be used to antagonize xylazine sedation and atipamezole (0.3 mg/kg) will be used to antagonize medetomidine sedation. Cage trapping A cage-type trap for live capture of bears was developed by Beck (1993). The trap measures 1.8m long and 1.0m high and wide. The frame is constructed of angle iron, and all side and top panels are wire mesh of 1.9cm mesh size. The floor is 16-gauge steel. A spring-powered, solid aluminum door is mounted on a full-length hinge at one end. A full-length latching mechanism holds the door closed. The door is triggered via a treadle pedal mounted on the floor 1.0m from the door. A standard garage door coil spring provides the closing power. Along one side of the trap is a hinged panel measuring 1.8m by 0.3m. Vertical bars placed on 0.3m centers behind this panel. Swinging the window up allows access through the barred area for administering immobilizing drugs by jabpole. Each trap weighs approximately 236kg. In the first study in which these traps were used, there was only one injury to a bear in 134 captures. An adult male broke a canine tooth while in the trap. Of the limited number of times these trap have been used for cougars, no known injuries have occurred to date (T. Beck, pers. comm.). A cage trap designed specifically for the capture of cougar has been used to manage cougar human conflicts in California since the late 1980s (Shuler 1992). A similar cage trap was used to safely capture cougar for research on cougar human interactions in San Diego County, California (Sweanor et al. in prep.). The cage trap for that study measured 48 in. tall, 40 in. wide, and 10 ft. long. It was built on a frame of 1 ½ in. angle iron with 2 in. by 4 in. grid horse panel made of 3/16 in. welded steel rod for the walls, floor, door, and roof. It weighed about 250 lb (113kg). A cage trap was designed by Don Hunter (USGS) and Colorado State University’s Mechanical Engineering Department. The trap was designed to be smaller, lighter, collapsible, and safer than what was previously available. A counter-weighted door drops closed slowly and quietly so as not to injure any members of a family group caught in the doorway. In addition, there are air-pressured cylinders that slow the door even further and a rubber bumper along the edge in case a tail is caught in the way of the closing door. The trap is 3.5 ft. tall, 3.5 ft. wide and 6 ft. long, constructed of 2 in. by 4 in. grid pattern steel horse panel with 0.225 in. rod. A cage trap will be baited with a deer carcass that will be tied to the end mesh panel opposite the door of the trap. The trap will be checked as early as possible the following morning or immediately after a capture occurs if fitted with a transmitter to be triggered upon closing of the door. The researchers should monitor the trap as soon as possible after sunrise every morning to minimize time in the trap and to avoid human interference from recreational activities. Normally, when a cougar has claimed a bait at a cage trap, it is caught fairly soon after night-fall. Researchers can work the cougar with a spot-light, head lamps, and lantern. Cougars will be immobilized with a jabpole or syringe as described above. Drug dosages and animal handling will be as described above. 199 �Foothold Snares Foot-hold snares are an effective, relatively safe technique for capturing cougars particularly in areas not conducive to using trained hounds (Logan et al. 1999). The snares are constructed to minimize injuries to the cougar. The snare, also called the Aldrich foot snare, was originally designed for the capture of bears. It has been modified to use for cougars. The spring activated snare secures a 3/16 inch steel cable around the foot of the cougar, closing tight with the action of a small piece of angle iron fashioned into a sliding lock mechanism. The snares have been modified considerably over the years for cougars by incorporating a large spring to diminish force applied to the foot and a shock absorption device into the cable. The inside of the loop is wrapped with duct tape to minimize the surface abrasion on the skin of the foot. An in-line swivel is placed in the cable to avoid torsion of the foot and potential bone fracture. A short lead is attached to the snare to further minimize stress to the leg. The lead is then secured to a multi-branched flexible bush with a double off-set hook drag made of 5/8 in. rebar steel. It can also be secured to a tree 4 inches or greater in diameter with 3/16 in. or ¼ in. steel cable clamped and stapled to the base of the tree so the cougar can not climb the tree with the snare. Branches of the tree are lopped of with a saw or an axe about 8 ft. up the tree so the cougar can not hang itself from a branch by the snare cable. An area of 5 meters or more is cleared around the snare site to eliminate potential leg fractures resulting from a fulcrum situation in conjunction to an adjacent tree (Duggins Wroe, pers. comm.) or torque on the leg bones caused by revolutionary twisting of the cable when the swivel is isolated by the foot-loop cable becoming wrapped around stout vegetation. Details on how to safely structure the snare and to choose and prepare snare sites are in Logan et al. 1999. Modifications have been made to avoid capturing non-target animals. The concealed 10 inch loop of cable is positioned over the trigger of the spring. The trigger has a 4 inch plastic trap pan adhered to the top surface. The pan and trigger are positioned over a hole dug in the ground and filled with a 12x12x4 inch piece of high density foam. This foam prevents smaller animals from triggering the snare. Large branches are angled over the snare to force ungulates to step over or go around the snare. The duct tape on the loop keeps it from closing too tightly and usually allows smaller-footed animals such as ungulates, coyotes and bobcats to slip free. The loop size is set smaller than for a black bear, there is, however, a possibility of catching a smaller-footed black bear (Duggins Wroe, pers. comm.). Bears will be drugged and released if caught. Any other non-target animals caught will be examined and treated for injuries and released with snare poles. Preferred sites will have limber bushes with multiple basal stems to securely anchor the snare drag, and a safety area with a circumference 5 m or more around the anchor point. The snares will not be set near cliff or water, and potentially dangerous vegetation will be cleared from the safety area. Snares will be checked as quickly as possible after sunrise every morning to reduce stress and possibility of hyperthermia. Snares will be checked at least twice a day and will not be reset on extremely hot days (Logan et al. 1999, Logan and Sweanor 2001). Logan et al. (1999) found snaring to be a relatively safe technique for capturing cougars. Life-threatening injuries occurred in 5 of 209 captures. The majority of these injuries were fractures to ulna and/or radius of the snared leg. Adult cougars will be immobilized with anesthetics delivered by jabpole or CO2 pistol and projectile syringe as described above. Capture operations will be halted if ambient temperature falls below 0°F or rises above 90°F. Delivery of anesthetic drugs via projectile syringe In situations where pursuit by hounds is not possible and snaring or trapping is difficult due to the high abundance of non-target animals, a lure may be used to bring a cougar in close proximity to dart with a projectile syringe using a gas-powered projector. Lures may include a fresh kill made by the target animal, a deer carcass placed out as bait, or a predator call. A hound on a lead will be available to track the animal once it has been darted. The caudal thigh is the preferred target for the dart. The anesthetic choice is at the discretion of the attending veterinarian. 200 �Hand capture of cubs Nursling cougar cubs can be safely captured by hand or with a catch-pole at nurseries when they are 4 to 10 weeks old (Logan and Sweanor 2001). Cubs usually weigh less than 10 kg, and can be examined and tagged without the need for anesthetics. Nurseries can be located when VHF-collared mothers are present, or by using GPS data from GPS-collared mothers. Wait for a time when the mother is away from the nursery, as determined by VHF-radio-telemetry, in order to capture the cubs. Cubs should be handled with clean leather gloves. They can be picked up by the nape of the neck. A catch-pole may be necessary to extract cubs from holes and crevices. Cubs should be contained together, or in pairs, in new burlap bags to allow ample air circulation. The cubs should be moved about 100 m from the nursery to minimize human activity, disturbance, and odors at the nursery. Individual cubs that are being examined can be held in a separate burlap bag. Once the cubs are processed, they should be returned to the exact nursery, and the researchers should leave the area immediately. Throughout this process a receiver tuned to the frequency of the radio-collared mother should be constantly monitored. If it appears that the mother is returning, the cubs should be put back in the nursery immediately, and researchers should vacate the area. INJURIES AND EUTHANASIA If an animal is seriously injured (e.g. fractured or broken appendage, vertebrae, pelvis, or jaw, severe dislocation, laceration or any other injury that compromises its ability to survive and/or causes severe pain or distress) during capture or recovery, then it will be quickly and humanely euthanized. Cougar will be deeply anesthetized with ketamine or Telazol® and xylazine (IV or IM) and euthanized via rapid IV KCl administration (400-800 mEq). Alternatively, if an injured cougar cannot be handled then euthanasia will be a gunshot to the head or neck with a 0.22 caliber magnum rifle or pistol. LITERATURE CITED BECK, T, D. I. 1993. Development of black bear inventory techniques; job progress report. Project number W-153-R-6 KREEGER, T. J., J. M. ARNEMO, AND J. P. RAATH. 2002. Handbook of wildlife chemical immobilization, International edition. Wildlife Pharmaceuticals, Inc., Ft. Collins, Colorado. LOGAN, K. A., E. T. THORNE, L. L. IRWIN, AND R. SKINNER. 1986. Immobilizing wild cougars (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases 22:97-103. LOGAN, K. A., L. L. SWEANOR, J. F. SMITH, AND M. G. HORNOCKER. 1999. Capturing cougars with foothold snares. Wildlife Society Bulletin 27:201-208. LOGAN, K.A., AND L.L SWEANOR. 2001. Desert Cougar, evolutionary ecology and conservation of an enduring carnivore. Washington: Island Press. SHAW, H.G. 1979. Cougar field guide. Fourth edition. Arizona Game and Fish, Phoenix, Arizona, USA. SHULER, J. D. 1992. A cage trap for live-trapping cougars. Proceedings of the Fifteenth Vertebrate Pest Conference. Newport Beach, California, March 3-5, 1992. SWEANOR, L. L., K. A. LOGAN, J. W. BAUER, B. MILSAP, AND W. M. BOYCE. In prep. Cougar-human relationships in Cuyamaca Rancho State Park, California. 201 �DRUG DOSAGE FOR COUGARS Table 1: Drug dosage by weight for cougars as recommended by CDOW veterinarian L. Wolfe. Dosage Conc Cougar Dose (ml) by animal weight (kg) mg/kg mg/ml 10 20 30 40 50 60 70 80 ANTIBIOTICS Oxytetracycline 3 200 0.2 0.3 0.5 0.6 0.8 0.9 1.1 1.2 Penicillin G SID 20000 300000 0.7 1.3 2.0 2.7 3.3 4.0 4.7 5.3 PAINKILLERS Ketoprofen SID 2 100 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 ANESTHETICS ketamine (+ med) 200 2 200 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 medatomidine 20 0.1 20 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 tolazoline 4 100 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 atipamazole 0.3 5 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8 Dopram 1 20 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Atropine 0.03 0.5 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8 MISC fluids maint ml/ day 60 1 600.0 1200.0 1800.0 2400.0 3000.0 3600.0 4200.0 4800.0 202 100 110 1.5 6.7 1.7 7.3 2.0 2.2 1.0 0.5 4.0 6.0 5.0 6.0 1.1 0.6 4.4 6.6 5.5 6.6 6000.0 6600.0 �Colorado Division of Wildlife July 2006 – June 2007 WILDLIFE RESEARCH REPORT State of Cost Center Work Package No. Task No. Colorado 3430 7210 1 : Division of Wildlife : Mammals Research : Customer Services/Research Support : Library Services Federal Aid Project: N/A : Period Covered: July 1, 2006 – June 30, 2007 Author: D. J. Freddy Personnel: J. A. Boss. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT After providing 17 years of professional library services for the entire Colorado Division of Wildlife, research librarian Jackie Boss retired in April 2007. Consequently, the standard detailed listing of accomplishments, publications, and services provided by the library was not available for this FY 0607 report. We anticipate hiring a replacement librarian in Fall 2007 to continue and expand the services provided by the research library to the entire Colorado Division of Wildlife. 203 �WILDLIFE RESEARCH REPORT COLORADO DIVISION OF WILDLIFE RESEARCH LIBRARY SERVICES D. J. FREDDY, J. A. BOSS P.N. OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Division of Wildlife (CDOW) employees, cooperators, wildlife educators, and the public. SEGMENT OBJECTIVES 1. Continue to improve and modernize library services by implementing the SirsiDynix Horizon library automation system via an Application Service Provider (ASP) model (project began in June 2002). By joining the Automation System Colorado Consortium (ASCC) we were able to take advantage of a LSTA grant written by the Colorado State Library staff, which facilitated the implementation of this system. 2. Continue to develop, improve, and implement the CDOW Research Center Library web-site (started in June 2004) by implementing the SirsiDynix horizon system online to serve broader spectrum of patrons of the CDOW Research Center Library. 3. Continue to attend ASCC meetings and participate in SirsiDynix Horizon online classes to enhance utilization of the SirsiDynix system. SUMMARY OF LIBRARY SERVICES The library continued to provide the following services: Maintain and Build Electronic Catalogs of all Research Library Holdings Acquire Publications for the Research Center Library Receive Publications Donated to the Research Center Library Acquire AV Materials for the Research Center Library Acquire Theses, Dissertations, Documents and Books through Interlibrary Loan Conduct Literature Searches and Deliver Information to Employees Archive CDOW Published Manuscripts Prepared by ________________________________________ D. J. Freddy, for Jacqueline A. Boss, Librarian 204 � https://cpw.cvlcollections.org/files/original/7fbebacf3d018b7d0735478e0ef3ef4c.pdf 80fe5d7da992d7358de777231f4ee2e7 PDF Text Text MAMMALS - JULY 2008 �i �WILDLIFE RESEARCH REPORTS JULY 2007 – JUNE 2008 MAMMALS PROGRAM COLORADO DIVISION OF WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). ii �STATE OF COLORADO Bill Ritter, Governor DEPARTMENT OF NATURAL RESOURCES Harris Sherman, Executive Director WILDLIFE COMMISSION Tom Burke, Chair ……………………………………….…………...………….…........…Grand Junction Claire M. O‘Neal, Vice Chair…………..………………………...…………….…………………Holyoke Robert Bray, Secretary ……………………………….................................................................…Redvale Dennis Buechler…………………………………………………………….………….………...Centennial Brad Coors…………………………………………………………………………………………..Denver Jeffrey Crawford, Chair …………………………………………………………………….…..… Denver Tim Glenn…………………………………………………………….………..…………………......Salida Roy McAnally………………………………………………..…………….………..………………...Craig Richard Ray ………………………………………………………………………………...Pagosa Springs Harris Sherman, Executive Director, Ex-officio………….…………………...…………….…….....Denver John Stulp, Dept. of Agriculture, Ex-officio….………………………………..…………………Lakewood DIRECTOR’S STAFF Thomas Remington, Director Mark Konishi, Deputy Director John Bredehoft, Assistant Director-Field Operations Marilyn Salazar, Assistant Director-Support Services Jeff Ver Steeg, Assistant Director-Wildlife Programs Steve Cassin, Chief Financial Officer MAMMALS RESEARCH STAFF Dave Freddy, Mammals Research Leader Mat Alldredge, Wildlife Researcher Chuck Anderson, Wildlife Researcher Eric Bergman, Wildlife Researcher Chad Bishop, Wildlife Researcher Ken Logan, Wildlife Researcher Tanya Shenk, Wildlife Researcher Margie Michaels, Program Assistant iii �Colorado Division of Wildlife July 2007 – June 2008 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS LYNX CONSERVATION WP 0670 POST-RELEASE MONITORING OF LYNX REINTRODUCED TO COLORADO by T. Shenk………………………………………………………………………….…….1 DEER CONSERVATION WP 3001 EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES by C. Bishop………..…………...39 WP 3001 EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER by E. Bergman…………………………………………………………………………...53 WP 3001 POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION – STAGE I, OBJECTIVE 5; PATTERNS OF MULE DEER DISTRIBUTION AND MOVEMENTS by C. Anderson…………………………………………………………63 WP 3001 PILOT EVALUATION OF PREDATOR-PREY DYNAMICS ON THE UNCOMPAHGRE PLATEAU by M. Alldredge, E. Bergman, C. Bishop, K. Logan, and D. Freddy……………….. …87 PREDATORY MAMMALS CONSERVATION WP 3003 PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU by K. Logan………………….……………………....105 WP 3003 COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBAN-EXURBAN FRONT RANGE OF COLORADO by M. Alldredge………...155 SUPPORT SERVICES WP 7210 LIBRARY SERVICES by D. Freddy……………..………………………………….189 iv �v �Colorado Division of Wildlife July 2007- June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Lynx Conservation Post-Release Monitoring of Lynx Reintroduced to Colorado Period Covered: July 1, 2007 - June 30, 2008 Author: T. M. Shenk Personnel: L. Baeten, B. Diamond, R. Dickman, D. Freddy, L. Gepfert, J. Ivan, R. Kahn, A. Keith, G. Merrill, B. Smith, T. Spraker, S. Wait, S. Waters, L. Wolfe All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to establish a viable population of Canada lynx (Lynx canadensis) in Colorado, the Colorado Division of Wildlife (CDOW) initiated a reintroduction effort in 1997 with the first lynx released in February 1999. From 1999-2007, 218 wild-caught lynx from Canada and Alaska were released in Colorado. We documented survival, movement patterns, reproduction, and landscape habitatuse through aerial (n = 10,935) and satellite (n = 26,082) tracking. Most lynx remained near the core release area in southwestern Colorado. From 1999-August 2008, there were 112 mortalities of released adult lynx. Approximately 30.4% were either human-induced or likely human-induced through either collisions with vehicles or gunshot. Starvation and disease/illness accounted for 18.8% of the deaths while 36.6% of the deaths were from unknown causes. Of these mortalities, 26.8% occurred outside of Colorado. Monthly mortality rate was lower inside the study area than outside, and slightly higher for male than for female lynx, although 95% confidence intervals for sexes overlapped. Mortality was higher immediately after release (first month = 0.0368 [SE = 0.0140] inside the study area, and 0.1012 [SE = 0.0359] outside the study area), and then decreased according to a quadratic trend over time. Reproductive females had the smallest 90% utilization distribution home ranges ( x = 75.2 km2, SE = 15.9 km2), followed by attending males ( x = 102.5 km2, SE = 39.7 km2) and non-reproductive animals ( x = 653.8 km2, SE = 145.4 km2). Reproduction was first documented in 2003 with subsequent successful reproduction in 2004, 2005 and 2006. No dens were documented in 2007 or 2008. From snow-tracking, the primary winter prey species (n = 548 kills) were snowshoe hare (Lepus americanus, annual x = 73.3%, SE = 4.7, n = 10) and red squirrel (Tamiasciurus hudsonicus, annual x = 18.2%, SE = 4.2, n = 10); other mammals and birds formed a minor part of the winter diet. Lynx use-density surfaces were generated to illustrate relative use of areas throughout Colorado. Within the areas of high use in southwestern Colorado, site-scale habitat use, documented through snow-tracking, supports mature 1 �Engelmann spruce (Picea engelmannii)-subalpine fir (Abies lasiocarpa) forest stands with 42-65% canopy cover and 15-20% conifer understory cover as the most commonly used areas in southwestern Colorado. Little difference in aspect (slight preference for north-facing slopes), slope ( x = 15.7°) or elevation ( x = 3173 m) were detected for long beds, travel and kill sites (n = 1841). Den sites (n = 37) however, were located at higher elevations ( x = 3354 m, SE = 31 m) on steeper ( x = 30°, SE = 2°) and more commonly north-facing slopes with a dense understory of coarse woody debris. Two years of a study to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands have been completed in 2006-2008 and will continue through 2009 (see Appendix I of this report). Results to date have demonstrated that CDOW has developed lynx release protocols that ensure high initial post-release survival followed by high long-term survival, site fidelity, reproduction and recruitment of Colorado-born lynx into the Colorado breeding population. What is yet to be demonstrated is whether Colorado can support sufficient recruitment to offset annual mortality for a viable lynx population over time. Monitoring continues in an effort to document such viability. 2 �WILDLIFE RESEARCH REPORT POST RELEASE MONITORING OF LYNX (LYNX CANADENSIS) REINTRODUCED TO COLORADO TANYA M. SHENK P. N. OBJECTIVE The initial post-release monitoring of Canada lynx (Lynx canadensis) reintroduced into Colorado will emphasize 5 primary objectives: 1. Assess and modify release protocols to ensure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival of lynx reintroduced to Colorado. 5. Estimate reproduction of lynx reintroduced to Colorado. Three additional objectives will be emphasized after lynx display site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of lynx conservation strategies in the southern Rocky Mountains. SEGMENT OBJECTIVES 1. Complete winter 2007-08 field data collection on lynx habitat use at the landscape scale, hunting behavior, diet, mortalities, and movement patterns. 2. Complete winter 2007-08 lynx trapping field season to collar Colorado born lynx and re-collar adult lynx. 3. Complete spring 2008 field data on lynx reproduction. 4. Summarize and analyze data and publish information as Progress Reports, peer-reviewed manuscripts for appropriate scientific journals, or CDOW technical publications. 5. Complete the second year of field work to evaluate snowshoe hare (Lepus americanus) densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands (see Appendix I). INTRODUCTION The Canada lynx occurs throughout the boreal forests of northern North America. Colorado represents the southern-most historical distribution of lynx, where the species occupied the higher elevation, montane forests in the state. Little was known about the population dynamics or habitat use of this species in their southern distribution. Lynx were extirpated or reduced to a few animals in the state by the late 1970‘s due, most likely, to predator control efforts such as poisoning and trapping. Given the isolation of Colorado to the nearest northern populations, the CDOW considered reintroduction as the only option to attempt to reestablish the species in the state. 3 �A reintroduction effort was begun in 1997, with the first lynx released in Colorado in 1999. To date, 218 wild-caught lynx from Alaska and Canada have been released in southwestern Colorado. The goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of lynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing if the reintroduction effort is progressing towards success. There are 7 critical criteria for achieving a viable population: 1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, 2) long-term survival of lynx in Colorado, 3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, 4) reintroduced lynx must breed, 5) breeding must lead to reproduction of surviving kittens 6) lynx born in Colorado must reach breeding age and reproduce successfully, and 7) recruitment must equal or be greater than mortality over an extended period of time. The post-release monitoring program for the reintroduced lynx has 2 primary goals. The first goal is to determine how many lynx remain in Colorado and their locations relative to each other. Given this information and knowing the sex of each individual, we can assess whether these lynx can form a breeding core from which a viable population might be established. From these data we can also describe general movement patterns and habitat use. The second primary goal of the monitoring program is to estimate survival of the reintroduced lynx and, where possible, determine causes of mortality for reintroduced lynx. Such information will help in assessing and modifying release protocols and management of lynx once they have been released to ensure their highest probability of survival. Additional goals of the post-release monitoring program for lynx reintroduced to the southern Rocky Mountains included refining descriptions of habitat use and movement patterns and describing successful hunting habitat once lynx established home ranges that encompassed their preferred habitat. Specific objectives for the site-scale habitat data collection include: 1) describe and quantify site-scale habitat use by lynx reintroduced to Colorado, 2) compare site-scale habitat use among types of sites (e.g., kills vs. long-duration beds), and 3) compare habitat features at successful and unsuccessful snowshoe hare chases. Documenting reproduction is critical to the success of the program and lynx are monitored intensively to document breeding, births, survival and recruitment of lynx born in Colorado. Site-scale habitat descriptions of den sites are also collected and compared to other sites used by lynx. The program will also investigate the ecology of snowshoe hare in Colorado. A study comparing snowshoe hare densities among mature stands of Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), lodgepole pine (Pinus contorta) and Ponderosa pine (Pinus ponderosa) was completed in 2004 with highest hare densities found in Engelmann spruce/subalpine fir stands and no hares found in Ponderosa pine stands. A study to evaluate the importance of young, regenerating lodgepole pine and mature Engelmann spruce/subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each was initiated in 2005 and will continue through 2009 (see Appendix I). Lynx is listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.)(U. S. Fish and Wildlife Service 2000). Colorado is included in the federal listing as lynx habitat. Thus, an additional objective of the post-release monitoring program is to develop conservation strategies relevant to lynx in Colorado. To develop these conservation strategies, information specific to the ecology of the lynx in its southern Rocky Mountain range, such as habitat use, movement patterns, mortality factors, survival, and reproduction in Colorado is needed. 4 �STUDY AREA Byrne (1998) evaluated five areas within Colorado as potential lynx habitat based on (1) relative snowshoe hare densities (Bartmann and Byrne 2001), (2) road density, (3) size of area, (4) juxtaposition of habitats within the area, (5) historical records of lynx observations, and (6) public issues. Based on results from this analysis, the San Juan Mountains of southwestern Colorado were selected as the core reintroduction area, and where all lynx were reintroduced. Wild Canada lynx captured in Alaska, British Columbia, Manitoba, Quebec and Yukon were transported to Colorado and held at The Frisco Creek Wildlife Rehabilitation Center located within the reintroduction area prior to release. Post-release monitoring efforts were focused in a 20,684 km2 study area which included the core reintroduction area, release sites and surrounding high elevation sites (> 2,591 m). The area encompassed the southwest quadrant of Colorado and was bounded on the south by New Mexico, on the west by Utah, on the north by interstate highway 70, and on the east by the Sangre de Cristo Mountains (Figure 1). Southwestern Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4,200 m. Engelmann spruce/subalpine fir is the most widely distributed coniferous forest type within the study area. The lynx-established core area is roughly bounded by areas used by lynx in the Taylor Park/Collegiate Peak areas in central Colorado and includes areas of continuous use by lynx, including areas used during breeding and denning (Figure 1). METHODS REINTRODUCTION Effort Wild Canada lynx were captured in Alaska, British Columbia, Manitoba, Quebec and Yukon and transported to Colorado where they were held at the Frisco Creek Wildlife Rehabilitation Center prior to release. All lynx releases were conducted under the protocols found to maximize survival (see Shenk 2001). Estimated age, sex and body condition were ascertained and recorded for each lynx prior to release (see Wild 1999). Lynx were transported from the rehabilitation facility to their release site in individual cages. Specific release site locations were recorded in Universal Transverse Mercator (UTM) coordinates and identification of all lynx released at the same location, on the same day, was recorded. Behavior of the lynx on release and movement away from the release site were documented. Movement, Distribution and Relative Use of Areas by Lynx To monitor lynx movements and thus determine distribution and relative use of areas all released lynx were fitted with radio collars. All lynx released in 1999 were fitted with TelonicsTM radio-collars. All lynx released since 1999, with the exception of 5 males released in spring 2000, were fitted with SirtrackTM dual satellite/VHF radio-collars. These collars have a mortality indicator switch that operated on both the satellite and VHF mode. The satellite component of each collar was programmed to be active for 12 hours per week. The 12-hour active periods for individual collars were staggered throughout the week. Signals from the collars allowed for locations of the animals to be made via Argos, NASA, and NOAA satellites. The location information was processed by ServiceArgos and distributed to the CDOW through e-mail messages. Datasets.-- To determine recent (post-reintroduction) movement and distribution of lynx reintroduced, born or initially trapped in Colorado and relative use of areas by these lynx, regular locations of lynx were collected through a combination of aerial and satellite tracking. Locations were recorded and general habitat descriptions for each aerial location was recorded. The first dataset of lynx locations included all locations obtained from daytime flights conducted with a Cessna 185 or similar aircraft to locate lynx by their VHF collar transmitters (hereafter aerial locations). VHF transmitters have been used on lynx since the first lynx were released in February 1999. The second type of lynx location 5 �data was collected via satellite from the satellite collar transmitters placed on the lynx (hereafter satellite locations). Satellite transmitter collars were first used for lynx in April 2000. These satellite collars also contained a VHF transmitter which also allowed locating lynx from the air or ground. All locations were recorded in Universal Transverse Mercator (UTM) coordinates using the CONUS NAD27 datum. Flights to obtain lynx aerial locations were typically conducted on a weekly basis throughout most summer and winter months and twice a week during the den search field season (May 15 – June 30), depending on weather and availability of planes and pilots. Flights were typically concentrated in the high elevation (> 2700 m) southwest quadrant of Colorado which encompasses the core lynx release and research area (Figure 1). Flights during the den seasons were conducted to obtain locations on all female lynx within the state wearing an active VHF transmitter. VHF transmitters were outfitted with sufficient batteries to last 60 months. The satellite transmitters were designed to provide locations on a weekly basis with sufficient batteries to last for 18 months. Lynx may not be exhibiting typical behavior or habitat use within the first few months after their release in Colorado. Therefore, a subset of each of the aerial and satellite datasets was created that eliminated the first 180 days (approximately 6 months) of locations obtained for each lynx immediately after their initial release. As a result, the truncated aerial location dataset contained lynx locations from September 1999 through March 2007 while the truncated satellite location dataset began October 2000 and extended through March 2007. Accuracy of both aerial and satellite locations varied with the environmental conditions at the time the location was obtained. Accuracy of aerial locations was influenced by weather with accuracy ranging from 50 - 500 meters. Satellite location accuracy was also influenced by atmospheric conditions and position of the satellites. Satellite location accuracy ranged from 150 meters -10 km. Movement and Distribution.-- To document all known lynx locations maps were generated with all aerial and satellite locations displayed. Due to lynx movements outside of Colorado, particularly into the states of New Mexico, Utah and Wyoming we further evaluated lynx use throughout those three states, as well as the data would allow. All individual lynx located at least once in these 3 states (nontruncated datasets) were identified and tallied for each year. To document consistency and known use of these states after the initial effect of being reintroduced was minimized (i.e., 180 days post-release), each individual lynx located at least once in these states from the truncated datasets were identified and tallied. Relative Use.-- To document relative use of areas by lynx, 90% kernel use-density surfaces were calculated for truncated satellite and aerial lynx locations using the ArcGIS Spatial Analyst Kernel Density Tool. Due to differences in data collection frequency and accuracy between datasets, the truncated satellite and truncated aerial data were analyzed separately for generating the lynx use-density surfaces. These use-density surfaces fit a smoothly curved surface over each lynx location. The surface value was highest at the location of the point and diminished with increasing distance from the point. A fixed kernel was used with a smoothing parameter of 5 km, reaching 0 at the search radius distance from the point. Only a circular neighborhood was possible. The volume under the surface equaled the total value for the point. The use-density at each output GIS raster cell was calculated by adding the values of all the kernel surfaces from all the lynx point locations that overlaid each raster cell center. The kernel function was based on the quadratic kernel function described in Silverman (1986, p. 76, equation 4.5). The use-density surfaces were calculated at 100 m resolution. To enhance graphic displays of higher usedensity areas, density values representing single locations were not displayed. 6 �Home Range Annual home ranges were calculated as a 95% utilization distribution using a kernel home-range estimator for each lynx we had at least 30 locations for within a year. A year was defined as March 15 – March 14 of the following year. Locations used in the analyses were collected from September 1999 – January 2006 and all locations obtained for an individual during the first six months after its release were eliminated from any home range analyses as it was assumed movements of lynx initially post-release may not be representative of normal habitat use. Locations were obtained either through aerial VHF surveys or locations or the midpoint (ArcView Movement Extension) of all high quality (accuracy rating of 01km) satellite locations obtained within a single 24-hour period. All locations used within a single home range analysis were taken a minimum of 24 hours apart. Home range estimates were classified as being for a reproductive or non-reproductive animal. A reproductive female was defined as one that had kittens with her; a reproductive male was defined as a male whose movement patterns overlapped that of a reproductive female. If a litter was lost within the defined year a home range described for a reproductive animal were estimated using only locations obtained while the kittens were still with the female. Survival Multi-state mark-recapture models were used to estimate monthly mortality rates and described in detail in Devineau et al. 2008 (in review). This approach accommodated missing data and allowed exploration of factors possibly affecting lynx survival such as sex, time spent in pre-release captivity, movement patterns, and origin. Mortality Factors When a mortality signal (75 beats per minute [bpm] vs. 50 bpm for the Telonics™ VHF transmitters, 20 bpm vs. 40 bpm for the Sirtrack™ VHF transmitters, 0 activity for Sirtrack™ PTT) was heard during either satellite, aerial or ground surveys, the location (UTM coordinates) was recorded. Ground crews then located and retrieved the carcass as soon as possible. The immediate area was searched for evidence of other predators and the carcass photographed in place before removal. Additionally, the mortality site was described and habitat associations and exact location were recorded. Any scat found near the dead lynx that appeared to be from the lynx was collected. All carcasses were transported to the Colorado State University Veterinary Teaching Hospital (CSUVTH) for a post mortem exam to 1) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, and 3) archive samples for future reference (research or forensic). The gross necropsy and histology were performed by, or under the lead and direct supervision of a board certified veterinary pathologist. At least one research personnel from the CDOW involved with the lynx program was also present. The protocol followed standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing (see Shenk 1999 for details). Some additional data/samples were routinely collected for research, forensics, and archiving. Other data/samples were collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). From 1999–2004 the CDOW retained all samples and carcass remains with the exception of tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, and other diagnostic samples. Since 2005 carcasses are disposed of at the CSUVTH with the exception of the lower canine, fecal samples, stomach content samples and tissue or bone marrow samples to be delivered by CDOW to the Center for Disease control for plague testing. The lower canine, from all carcasses, is sent to Matson Labs (Missoula, Montana) for aging and the fecal and stomach content samples are evaluated for diet. 7 �Reproduction Females were monitored for proximity to males during each breeding season. We defined a possible mating pair as any male and female documented within at least 1 km of each other in breeding season through either flight data or snow-tracking data. Females were then monitored for site fidelity to a given area during each denning period of May and June. Each female that exhibited stationary movement patterns in May or June were closely monitored to locate possible dens. Dens were found when field crews walked in on females that exhibited virtually no movement for at least 10 days from both aerial and ground telemetry. Kittens found at den sites were weighed, sexed and photographed. Each kitten was uniquely marked by inserting a sterile passive integrated transponder (PIT, Biomark, Inc., Boise, Idaho, USA) tag subcutaneously between the shoulder blades. Time spent at the den was minimized to ensure the least amount of disturbance to the female and the kittens. Weight, PIT-tag number, sex and any distinguishing characteristics of each kitten was also recorded. Beginning in 2005, blood and saliva samples were collected and archived for genetic identification. During the den site visits, den site location was recorded as UTM coordinates. General vegetation characteristics, elevation, weather, field personnel, time at the den, and behavioral responses of the kittens and female were also recorded. Once the females moved the kittens from the natal den area, den sites were visited again and site-specific habitat data were collected (see Habitat Use section below). Captures Captures were attempted for either lynx that were in poor body condition or lynx that needed to have their radio-collars replaced due to failed or failing batteries or to radio-collar kittens born in Colorado once they reached at least 10-months of age when they were nearly adult size. Methods of recapture included 1) trapping using a Tomahawk™ live trap baited with a rabbit and visual and scent lures, 2) calling in and darting lynx using a Dan-Inject CO2 rifle, 3) custom box-traps modified from those designed by other lynx researchers (Kolbe et al. 2003) and 4) hounds trained to pursue felids were also used to tree lynx and then the lynx was darted while treed. Lynx were immobilized either with Telazol (3 mg/kg; modified from Poole et al. 1993 as recommended by M. Wild, DVM) or medetomidine (0.09mg/kg) and ketamine (3 mg/kg; as recommended by L. Wolfe, DVM)) administered intramuscularly (IM) with either an extendible pole-syringe or a pressurized syringe-dart fired from a Dan-Inject air rifle. Immobilized lynx were monitored continuously for decreased respiration or hypothermia. If a lynx exhibited decreased respiration 2mg/kg of Dopram was administered under the tongue; if respiration was severely decreased, the animal was ventilated with a resuscitation bag. If medetomidine/ketamine were the immobilization drugs, the antagonist Atipamezole hydrochloride (Antisedan) was administered. Hypothermic (body temperature < 95o F) animals were warmed with hand warmers and blankets. While immobilized, lynx were fitted with replacement SirtrackTM VHF/satellite collar and blood and hair samples were collected. Once an animal was processed, recovery was expedited by injecting the equivalent amount of the antagonist Antisedan IM as the amount of medetomidine given, if medetomodine/ketemine was used for immobilization. Lynx were then monitored while confined in the box-trap until they were sufficiently recovered to move safely on their own. No antagonist is available for Telezol so lynx anesthetized with this drug were monitored until the animal recovered on its own in the box-trap and then released. If captured and in poor body condition, lynx were anesthetized with either Telezol (2 mg/kg) or medetomodine/ketemine and returned to the Frisco Creek Wildlife Rehabilitation Center for treatment. HABITAT USE Gross habitat use was documented by recording canopy vegetation at aerial locations. More 8 �refined descriptions of habitat use by reintroduced lynx were obtained through following lynx tracks in the snow (i.e., snow-tracking) and site-scale habitat data collection conducted at sites found through this method to be used by lynx. See Shenk (2006) for detailed methodologies. DIET AND HUNTING BEHAVIOR Winter diet of reintroduced lynx was estimated by documenting successful kills through snowtracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. Scat samples were collected wherever found and labeled with location and individual lynx identification. Only part of the scat was collected (approximately 75%); the remainder was left in place in the event that the scat was being used by the animal as a territory mark. Site-scale habitat data collected for successful and unsuccessful snowshoe hare kills were compared. SNOWSHOE HARE ECOLOGY To further our understanding of snowshoe hare ecology in Colorado, a study was conducted comparing snowshoe hare densities among mature stands of Engelmann spruce/subalpine fir, lodgepole pine (Pinus contorta) and Ponderosa pine (Pinus ponderosa). The highest hare densities were found in Engelmann spruce/subalpine fir stands and no hares found in Ponderosa pine stands (Zahratka and Shenk 2008). A second study was initiated in 2005 to evaluate the importance of young, regenerating lodgepole pine and mature Engelmann spruce / subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each (Ivan 2005). Specifically, this study was designed to evaluate small and medium lodgepole pine stands and large spruce/fir stands where the classes ―small‖, ―medium‖, and ―large‖ refer to the diameter at breast height (dbh) of overstory trees as defined in the United States Forest Service R2VEG Database (small = 2.54 12.69 cm dbh, medium = 12.70 22.85 cm, and large = 22.86 40.64 cm dbh; J. Varner, United States Forest Service, personal communication). The study design was also developed to identify which of the numerous hare density-estimation procedures available perform accurately and consistently using an innovative, telemetry augmentation approach as a baseline. In addition, movement patterns and seasonal use of deciduous cover types such as riparian willow were assessed. Finally, the study was designed to further expound on the relationship between density, demography, and stand-type by examining how snowshoe hare density and demographic rates vary with specific vegetation, physical, and landscape characteristics of a stand. RESULTS REINTRODUCTION Effort From 1999 through 2006, 218 wild-caught lynx were reintroduced into southwestern Colorado (Table 1). No lynx were released in 2007 or 2008. All lynx were released with either VHF or dual VHF/satellite radio collars so they could be monitored for movement, reproduction and survival. The CDOW does not plan to release any additional lynx in 2009. Movement Patterns and Distribution Numerous travel corridors were used repeatedly by more than one lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-SilvertonLizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast through the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. 9 �A total of 10,935 aerial and 26,082 satellite locations were obtained from the 218 reintroduced lynx, radio-collared Colorado kittens (n = 14) and unmarked lynx captured in Colorado (n = 2) as of August 27, 2008. The majority of these locations were in Colorado (Figure 2). Some reintroduced lynx dispersed outside of Colorado into Arizona, Idaho, Iowa, Kansas, Montana, Nebraska, Nevada, New Mexico, South Dakota, Utah and Wyoming (Figure 2). The majority of surviving lynx from the reintroduction effort currently continue to use high elevation (> 2900 m), forested terrain in an area bounded on the south by New Mexico north to Independence Pass, west as far as Taylor Mesa and east to Monarch Pass. Most movements away from the Core Release Area were to the north. Relative Use The lynx use-density surfaces resulting from the fixed kernel analyses provided relative probabilities of finding lynx in areas throughout their distribution. A single use-density surface was calculated separately for both the aerial (n = 8058) and satellite truncated datasets (n = 16240). All 218 lynx released in Colorado, all radio-collared kittens and 2 captured unmarked adults were located at least once in Colorado. The majority of these lynx remained in Colorado. The use-density surfaces within Colorado were displayed separately for both the aerial (Figure 3) and satellite truncated datasets (Figure 4). Of the total locations available in the truncated datasets used to generate the usedensity surfaces, 7953 of the aerial locations and 13,241 of the satellite locations were in Colorado. Aerial and satellite use-density surfaces indicated similar high use-density areas. Satellite locations indicated broader spatial use by lynx because satellite collars provided more locations than flights. The use-density surface for lynx use in Colorado indicates two primary areas of use. The first is the Core Research Area (see Figure 1) and a secondary core centered in the Collegiate Peaks Wilderness (Figures 1, 3 and 4). High use is also documented for 1) the area east of Dillon, on both the north and south sides of I70 and 2) the area north of Hwy 50 centered around Gunnison and then north to Crested Butte. These last 2 high use areas are smaller in extent than the 2 core areas. Relative use-density surfaces were also generated for New Mexico, Wyoming and Utah and presented in detail in Shenk (2007). Home Range Reproductive females had the smallest 90% utilization distribution annual home ranges ( x = 75.2 km2, SE = 15.9 km2, n = 19), followed by attending males ( x = 102.5 km2, SE = 39.7 km2, n = 4). Nonreproductive females had the largest annual home ranges ( x = 703.9 km2, SE = 29.8 km2, n = 32) followed by non-reproductive males ( x = 387.0 km2, SE = 73.5 km2, n = 6). Combining all nonreproductive animals yielded a mean annual home range of 653.8 km2 (SE = 145.4 km2, n = 38). Survival Detailed analyses of lynx mortality was completed and described in Devineau et al. 2008 (in review). Monthly mortality rate was lower inside the study area than outside, and slightly higher for male than for female lynx, although 95% confidence intervals for sexes overlapped. Mortality was higher immediately after release (first month = 0.0368 [SE = 0.0140] inside the study area, and 0.1012 [SE = 0.0359] outside the study area), and then decreased according to a quadratic trend over time. As of August 27, 2008, CDOW was actively monitoring/tracking 45 of the 106 lynx still possibly alive (Table 2). There are 62 lynx that we have not heard signals on since at least August 27, 2007 and these animals are classified as ‗missing‘ (Table 2). One of these missing lynx is a mortality of unknown identity, thus only 61 are truly missing. Possible reasons for not locating these missing lynx include 1) 10 �long distance dispersal, beyond the areas currently being searched, 2) radio failure, or 3) destruction of the radio (e.g., run over by car). CDOW continues to search for all missing lynx during both aerial and ground searches. Two of the missing lynx released in 2000 are thought to have slipped their collars. Mortality Factors Of the total 218 adult lynx released, we have 112 known mortalities as of August 27, 2008 (Table 2). Starvation was a significant cause of mortality in the first year of releases only. The primary known causes of death included 30.4% human-induced deaths which were confirmed or probably caused by collisions with vehicles or gunshot (Table 3). Malnutrition and disease/illness accounted for 18.8% of the deaths. An additional 36.6% of known mortalities were from unknown causes. Mortalities occurred throughout the areas through which lynx moved, with 26.8% occurring outside of Colorado. The out of state mortalities included 14 in New Mexico, 4 in Wyoming, Utah and Nebraska, and 1 each in Arizona, Kansas, Iowa and Montana (Figure 2, Table 4). Reproduction Reproduction was first documented in 2003 when 6 dens and a total of 16 kittens were found in the lynx Core Release Area in southwestern Colorado. Reproduction was also documented in 2004, 2005 and 2006. No dens were found in 2007 or 2008 (Table 5). Field crews weighed, photographed, PIT-tagged the kittens and checked body condition. Beginning in 2005, we also collected blood samples from the kittens for genetic work in an attempt to confirm paternity Kittens were processed as quickly as possible (11-32 minutes) to minimize the time the kittens were without their mother. While working with the kittens the females remained nearby, often making themselves visible to the field crews. The females generally continued a low growling vocalization the entire time personnel were at the den. In all cases, the female returned to the den site once field crews left the area. At all dens the females appeared in excellent condition, as did the kittens. The kittens weighed from 270-500 grams. Lynx kittens weigh approximately 200 grams at birth and do not open their eyes until they are 10-17 days old. The percent of tracked females found with litters in 2006 was lower (0.095) than in the 3 previous years (0.413, SE = 0.032, Table 5). However, all demographic and habitat characteristics measured at the 4 dens that were found in 2006 were comparable to all other dens found. Mean number of kittens per litter from 2003-2006 was 2.78 (SE = 0.05) and sex ratio of females to males was equal ( x = 1.14, SE = 0.14). More details of reproduction in 2003-06 were presented in Shenk (2007). Den Sites.-- A total of 37 dens were found from 2003-2006. All of the dens except one have been scattered throughout the high elevation areas of Colorado, south of I-70. In 2004, 1 den was found in southeastern Wyoming, near the Colorado border. Dens were located on steep ( x slope = 30o , SE=2o), north-facing, high elevation ( x = 3354 m, SE = 31 m) slopes. The dens were typically in Engelmann spruce/subalpine fir forests in areas of extensive downfall of coarse woody debris (Shenk 2006). All dens were located within the winter use areas used by the females. No dens were found in either 2007 or 2008 even though up to 34 adult females were monitored intensively during the denning period (Table 5). Captures Two adult lynx were captured in 2001 for collar replacement. One lynx was captured in a tomahawk live-trap, the other was treed by hounds and then anesthetized using a jab pole. Five adult lynx were captured in 2002; 3 were treed by hounds and 2 were captured in padded leghold traps. In 2004, 1 lynx was captured with a Belisle snare and 6 adult lynx were captured in box-traps. Trapping effort was substantially increased in winter and spring 2005 and 12 adult lynx were captured and re-collared. Eight 11 �reintroduced lynx were captured in winter and spring 2006. In 2007, 11 reintroduced adult lynx were captured and re-collared and an additional 10 in 2008. All lynx captured in Colorado from 2005-2008 were caught in box-traps. In addition, as part of the collaring trapping effort, 14 Colorado-born kittens were captured and collared at approximately 10-months of age. Seven 2004-born kittens were collared in spring 2005, and 7, 2005-born kittens were collared in spring 2006. We were not successful at capturing and collaring any kittens born in 2006 in winter 2006-07. We did however, capture 2 adults (approximate age 2 years old) in winter 2006-07 that had no PIT-tags or radio collars. We assume these 2 lynx were from litters born in Colorado that were never found at dens (i.e., why there were no PIT-tags). All lynx captured for collaring or re-collaring were fitted with new Sirtrack TM dual VHF/satellite collars and re-released at their capture locations. Seven adult lynx were captured from March 1999-August 27, 2008 because they were in poor body condition (Table 6). Five of these lynx were successfully treated at the Frisco Creek Rehabilitation Center and re-released in the Core Release Area. One lynx, BC00F07, died from starvation and hypothermia within 1 day of capture at the rehabilitation center. Lynx QU04M07 died 3 days after capture at the rehabilitation center. Necropsy results documented starvation as the cause of death for this lynx that was precipitated by hydrocephalus and bronchopneumonia (unpublished data T. Spraker, CSUVTH). Seven lynx were captured (either by CDOW personnel or conservation personnel in other states) because they were in atypical habitat outside the state of Colorado (Table 6). They were held at Frisco Creek Rehabilitation Center for a minimum of 3 weeks, fitted with new Sirtrack TM dual VHF/satellite collars and re-released in the Core Release Area in Colorado. Five of these 7 lynx were still alive 6 months post-re-release but 3 had already dispersed out of Colorado and 1 stayed in Colorado through August 27, 2008. Two of these lynx died within 6 months of re-release: 1 died of starvation in Colorado and the other died of unknown causes in Nebraska. One lynx captured out of state and re-released currently remains in Colorado. HABITAT USE Landscape-scale daytime habitat use was documented from 9496 aerial locations of lynx collected from February 1999-June 30, 2007. Throughout the year Engelmann spruce - subalpine fir was the dominant cover used by lynx. A mix of Engelmann spruce, subalpine fir and aspen (Populus tremuloides) was the second most common cover type used throughout the year. Various riparian and riparian-mix areas were the third most common cover type where lynx were found during the daytime flights. Use of Engelmann spruce-subalpine fir forests and Engelmann spruce-subalpine fir-aspen forests was similar throughout the year. There was a trend in increased use of riparian areas beginning in July, peaking in November, and dropping off December through June. Site-scale habitat data collected from snow-tracking efforts indicate Engelmann spruce and subalpine fir were also the most common forest stands used by lynx for all activities during winter in southwestern Colorado. Comparisons were made among sites used for long beds, dens, travel and where they made kills. Little difference in aspect, mean slope and mean elevation were detected for 3 of the 4 site types including long beds, travel and kills where lynx typically use gentler slopes ( x = 15.7o ) at an mean elevation of 3173 m, and varying aspects with a slight preference for north-facing slopes. See Shenk (2006) for more detailed analyses of habitat use. 12 �DIET AND HUNTING BEHAVIOR Winter diet of lynx was documented through detection of kills found through snow-tracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. A total of 548 kills were located from February 1999-April 2008. We collected over 950 scat samples from February 1999-April 2008 that will be analyzed for content. In each winter, the most common prey item was snowshoe hare, followed by red squirrel (Tamiusciurus hudsonicus; Table 7). The percent of snowshoe hare kills found however, varied annually from a low of 55.56% in 1999 to a high of 90.77% in winter 2002-2003. An annual mean of 73.29% (SE = 4.67) snowshoe hare kills in the diet has been documented. A comparison of percent overstory for successful and unsuccessful snowshoe hare chases indicated lynx were more successful at sites with slightly higher percent overstory, if the overstory species were Englemann spruce, subalpine fir or willow. Lynx were slightly less successful in areas of greater aspen overstory. This trend was repeated for percent understory at all 3 height categories except that higher aspen understory improved hunting success. Higher density of Engelmann spruce and subalpine fir increased hunting success while increased aspen density decreased hunting success. SNOWSHOE HARE ECOLOGY Two years of a 3-year study to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands have been completed and preliminary results presented (see Appendix I). DISCUSSION In an effort to establish a viable population of lynx in Colorado, CDOW initiated a reintroduction effort in 1997 with the first lynx released in winter 1999. From 1999 through spring 2007, 218 lynx were released in the Core Release Area. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns and to detect mortalities. Most lynx remain in the high elevation, forested areas in southwestern Colorado. The use-density surfaces for lynx use in Colorado indicate two primary areas of use. The first is the Core Research Area (see Figure 1) and a secondary core centered in the Collegiate Peaks Wilderness (Figures 1, 3, 4). High use is also documented for 1) the area east of Dillon, on both the north and south sides of I70 and 2) the area north of Hwy 50 centered around Gunnison and then north to Crested Butte. These last 2 high use areas are smaller in extent than the 2 core areas. Dispersal movement patterns for lynx released in 2000 and subsequent years were similar to those of lynx released in 1999 (Shenk 2000). However, more animals released in 2000 and subsequent years remained within the Core Release Area than those released in 1999. This increased site fidelity may have been due to the presence of con-specifics in the area on release. Numerous travel corridors within Colorado have been used repeatedly by more than 1 lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-Silverton-Lizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast to the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. Reproductive females had the smallest 90% utilization distribution home ranges ( x = 75.2 km2, SE = 15.9 km2), followed by attending males ( x = 102.5 km2, SE = 39.7 km2) and non-reproductive animals ( x = 653.8 km2, SE = 145.4 km2). Most lynx currently being tracked are within the Core Release Area. During the summer months, lynx were documented to 13 �make extensive movements away from their winter use areas. Extensive summer movements away from areas used throughout the rest of the year have been documented in native lynx in Wyoming and Montana (Squires and Laurion 1999). Current data collection methods used for the Colorado lynx reintroduction program were not specifically designed to address the reintroduced lynx movements or use of areas in other states. In particular, the core research and release area were in Colorado. Therefore, the number of aerial locations obtained would be far fewer in other states than in Colorado which would bias low the number of lynx and intensity of lynx use documented outside the state. In contrast, obtaining satellite locations is not biased by the location of the lynx. Satellite locations are, however, biased by the shorter time the satellite transmitters function, approximately 18 months versus 60 months for the VHF transmitters used to obtain the aerial locations. However, data collected to meet objectives of the lynx reintroduction program were used to provide information to help address the question of lynx use outside of Colorado. Due to the rarity of flights conducted outside Colorado, only use-density surfaces generated from satellite locations were used to document relative lynx use of areas in New Mexico, Utah and Wyoming. New Mexico and Wyoming have been used continuously by lynx since the first year lynx were released in Colorado (1999) to the present. Lynx reintroduced in Colorado were first documented in Utah in 2000 and are still being documented there to date. In addition, all levels of lynx use-density documented throughout Colorado are also represented in New Mexico, Utah and Wyoming from none to the highest level of use (Shenk 2007). One den was found in Wyoming. Although no reproduction has been documented in New Mexico or Utah to date, documenting areas of the highest intensity of use and the continuous presence of lynx within these states for over six years does suggest the potential for yearround residency of lynx and reproduction in those states. From 1999-August 2008, there were 112 mortalities of released adult lynx. Human-caused mortality factors are currently the highest causes of death with approximately 30.4% attributed to collisions with vehicles or gunshot. Starvation and disease/illness accounted for 18.8% of the deaths while 36.6% of the deaths were from unknown causes. Lynx mortalities were documented throughout all areas lynx used, including 30 (26.8%) occurring in other states (Figure 2, Table 3). Nearly half (14 of 30) of the out-of-state mortalities were documented in New Mexico. Monthly mortality rate was lower inside the study area than outside, and slightly higher for male than for female lynx, although 95% confidence intervals for sexes overlapped. Mortality was higher immediately after release (first month = 0.0368 [SE = 0.0140] inside the study area, and 0.1012 [SE = 0.0359] outside the study area), and then decreased according to a quadratic trend over time. Reproduction is critical to achieving a self-sustaining viable population of lynx in Colorado. Reproduction was first documented from the 2003 reproduction season and again in 2004, 2005 and 2006. Lower reproduction occurred in 2006 (Table 5) but did include a Colorado-born female giving birth to 2 kittens, documenting the first recruitment of Colorado-born lynx into the Colorado breeding population. No reproduction was documented in 2007 or 2008. The cause of the decreased reproduction from 2006 08 is unknown. One possible explanation would be a decrease in prey abundance. Additional reproduction is likely to have occurred in all years from females we were no longer tracking, and from Colorado-born lynx that have not been collared. The dens we find are more representative of the minimum number of litters and kittens in a reproduction season. To achieve a viable population of lynx, enough kittens need to be recruited into the population to offset the mortality that occurs in that year and hopefully even exceed the mortality rate to achieve an increasing population. The use-density surfaces depict intensity of use by location. Why certain areas would be used more intensively than others should be explained by the quality of the habitat in those areas. 14 �Characteristics of areas used by lynx, as documented through aerial locations and snow-tracking of lynx in the Colorado core research area, include mature Engelmann spruce-subalpine fir forest stands with 4265% canopy cover and 15-20% conifer understory cover (Shenk 2006). Within these forest stand types, lynx appear to have a slight preference for north-facing, moderate slopes ( x = 15.7°) at high elevations ( x = 3173 m; Shenk 2006). Snow-tracking of released lynx also provided information on hunting behavior and diet through documentation of kills, food caches, chases, and diet composition estimated through prey remains. The primary winter prey species (n = 548) were snowshoe hare (Table 7) with an annual x = 73.3% (SE = 4.7, n = 10) and red squirrel (annual x = 18.2%, SE = 4.2, n = 10). Thus, areas of good habitat must also support populations of snowshoe hare and red squirrel. In winter, lynx reintroduced to Colorado appear to be feeding on their preferred prey species, snowshoe hare and red squirrel in similar proportions as those reported for northern lynx during lows in the snowshoe hare cycle (Aubry et al. 1999). Environmental conditions in the springs and summers of 2003 and 2006 resulted in high cone crops during their following winters based on field observations, resulting in increased red squirrel abundance. This may partially explain the higher percent of red squirrel kills, and thus a lower percent of snowshoe hare kills, found in winters 2003-04 and 2006-07 (Table 7). Caution must be used in interpreting the proportion of identified kills. Such a proportion ignores other food items that are consumed in their entirety and thus are biased towards larger prey and may not accurately represent the proportion of smaller prey items, such as microtines, in lynx winter diet. Through snow-tracking we have evidence that lynx are mousing and several of the fresh carcasses have yielded small mammals in the gut on necropsy. The summer diet of lynx has been documented to include less snowshoe hare and more alternative prey than in winter (Mowat et al., 1999). All evidence suggests reintroduced lynx are finding adequate food resources to survive. Mowat et al. (1999) suggest lynx and snowshoe hare select similar habitats except that hares select more dense stands than lynx. Very dense understory limits hunting success of the lynx and provides refugia for hares. Given the high proportion of snowshoe hare in the lynx diet in Colorado, we might then assume the habitats used by reintroduced lynx also depict areas where snowshoes hare are abundant and available for capture by lynx in Colorado. From both aerial locations taken throughout the year and from the site-scale habitat data collected in winter, the most common areas used by lynx are in stands of Engelmann spruce and subalpine fir. This is in contrast to adjacent areas of Ponderosa pine, pinyon juniper, aspen and oakbrush. The lack of lodgepole pine in the areas used by the lynx may be more reflective of the limited amount of lodgepole pine in southwestern Colorado, the Core Release Area, rather than avoidance of this tree species. Hodges (1999) summarized habitats used by snowshoe hare from 15 studies as areas of dense understory cover from shrubs, stands that are densely stocked, and stands at ages where branches have more lateral cover. Species composition and stand age appears to be less correlated with hare habitat use than is understory structure (Hodges 1999). The stands need to be old enough to provide dense cover and browse for the hares and cover for the lynx. In winter, the cover/browse needs to be tall enough to still provide browse and cover in average snow depths. Hares also use riparian areas and mature forests with understory. Site-scale habitat use documented for lynx in Colorado indicate lynx are most commonly using areas with Engelmann spruce understory present from the snow line to at least 1.5 m above the snow. The mean percent understory cover within the habitat plots is typically less than 15% regardless of understory species. However, if the understory species is willow, percent understory cover is typically double that, with mean number of shrubs per plot approximately 80, far greater than for any other understory species. 15 �In winter, hares browse on small diameter woody stems (<0.25"), bark and needles. In summer, hares shift their diet to include forbs, grasses, and other succulents as well as continuing to browse on woody stems. This shift in diet may express itself in seasonal shifts in habitat use, using more or denser coniferous cover in winter than in summer. The increased use of riparian areas by lynx in Colorado from July to November may reflect a seasonal shift in hare habitat use in Colorado. Major (1989) suggested lynx hunted the edge of dense riparian willow stands. The use of these edge habitats may allow lynx to hunt hares that live in habitats normally too dense to hunt effectively. The use of riparian areas and riparian-Engelmann spruce-subalpine fir and riparian-aspen mixes documented in Colorado may stem from a similar hunting strategy. However, too little is known about habitat use by hares in Colorado to test this hypothesis at this time. Lynx also require sufficient denning habitat. Denning habitat has been described by Koehler (1990) and Mowat et al. (1999) as areas having dense downed trees, roots, or dense live vegetation. We found this to be in true in Colorado as well (Shenk 2006). In addition, the dens used by reintroduced lynx were at high elevations and on steep north-facing slopes. All females that were documented with kittens denned in areas within their winter-use area. SUMMARY From results to date it can be concluded that CDOW developed release protocols that ensure high initial post-release survival of lynx, and on an individual level, lynx demonstrated they can survive longterm in areas of Colorado. We also documented that reintroduced lynx exhibited site fidelity, engaged in breeding behavior and produced kittens that were recruited into the Colorado breeding population. What is yet to be demonstrated is whether current conditions in Colorado can support the recruitment necessary to offset annual mortality in order to sustain the population. Monitoring of reintroduced lynx will continue in an effort to document such viability. ACKNOWLEDGMENTS The lynx reintroduction program involves the efforts of literally hundreds of people across North America, in Canada and USA. Any attempt to properly acknowledge all the people who played a role in this effort is at risk of missing many people. The following list should be considered to be incomplete. CDOW CLAWS Team (1998-2001): Bill Andree, Tom Beck, Gene Byrne, Bruce Gill, Mike Grode, Rick Kahn (Program Leader), Dave Kenvin, Todd Malmsbury, Jim Olterman, Dale Reed, John Seidel, Scott Wait, Margaret Wild. CDOW: John Mumma (Director 1996-2000), Russell George (Director 2001-2003), Bruce McCloskey (Director 2004-2007), Conrad Albert, Jerry Apker, Laurie Baeten, Cary Carron, Don Crane, Larry DeClaire, Phil Ehrlich, Lee Flores, Delana Friedrich, Dave Gallegos, Juanita Garcia, Drayton Harrison, Jon Kindler, Ann Mangusso, Jerrie McKee, Gary Miller, Melody Miller, Mike Miller, Kirk Navo, Robin Olterman, Jerry Pacheo, Mike Reid, Tom Remington, Ellen Salem, Eric Schaller, Mike Sherman, Jennie Slater, Steve Steinert, Kip Stransky, Suzanne Tracey, Anne Trainor, Scott Wait, Brad Weinmeister, Nancy Wild, Perry Will, Lisa Wolfe, Brent Woodward, Kelly Woods, Kevin Wright. Lynx Advisory Team (1998-2001): Steve Buskirk, Jeff Copeland, Dave Kenny, John Krebs, Brian Miller (Co-Leader), Mike Phillips, Kim Poole, Rich Reading (Co-Leader), Rob Ramey, John Weaver. U. S. Forest Service: Kit Buell, Joan Friedlander, Dale Gomez, Jerry Mastel, John Squires, Fred Wahl, Nancy Warren. U. S. Fish and Wildlife Service: Lee Carlson, Gary Patton (1998-2000), Kurt Broderdorp. 16 �State Agencies: Alaska: ADF&G: Cathie Harms, Mark Mcnay, Dan Reed (Regional Manager), Wayne Reglin (Director), Ken Taylor (Assist. Director), Ken Whitten, Randy Zarnke, Other:Ron Perkins (trapper), Dr. Cort Zachel (veterinarian). Washington: Gary Koehler. National Park Service: Steve King. Colorado State University: Alan Franklin, Gary White. Colorado Natural Heritage Program: Rob Schorr, Mike Wunder. Canada: British Columbia: Dr. Gary Armstrong (veterinarian), Mike Badry (government), Paul Blackwell (trapper coordinator), Trappers: Dennis Brown, Ken Graham, Tom Sbo, Terry Stocks, Ron Teppema, Matt Ounpuu. Yukon: Government: Arthur Hoole (Director), Harvey Jessup, Brian Pelchat, Helen Slama, Trappers: Roger Alfred, Ron Chamber, Raymond Craft, Lance Goodwin, Jerry Kruse, Elizabeth Hofer, Jurg Hofer, Guenther Mueller (YK Trapper‘s Association), Ken Reeder, Rene Rivard (Trapper coordinator), Russ Rose, Gilbert Tulk, Dave Young. Alberta: Al Cook. Northwest Territories: Albert Bourque, Robert Mulders (Furbearer Biologist), Doug Steward (Director NWT Renewable Res.), Fort Providence Native People. Quebec: Luc Farrell, Pierre Fornier. Colorado Holding Facility: Herman and Susan Dieterich, Kate Goshorn, Loree Harvey, Rachel Riling. Pilots: Dell Dhabolt, Larry Gepfert, Al Keith, Jim Olterman, Matt Secor, Brian Smith, Whitey Wannamaker, Steve Waters, Dave Younkin. Field Crews (1999-2007): Steve Abele, Brandon Barr, Bryce Bateman, Todd Bayless, Nathan Berg, Ryan Besser, Jessica Bolis, Mandi Brandt, Brad Buckley. Patrick Burke, Braden Burkholder, Paula Capece, Stacey Ciancone, Doug Clark, John DePue, Shana Dunkley, Tim Hanks, Carla Hanson, Dan Haskell, Nick Hatch, Matt Holmes, Andy Jennings, Susan Johnson, Paul Keenlance, Patrick Kolar, Tony Lavictoire, Jenny Lord, Clay Miller, Denny Morris, Kieran O‘Donovan, Gene Orth, Chris Parmater, Jake Powell, Jeremy Rockweit, Jenny Shrum, Josh Smith, Heather Stricker, Adam Strong, Dave Unger, David Waltz, Andy Wastell, Mike Watrobka, Lyle Willmarth, Leslie Witter, Kei Yasuda, Jennifer Zahratka. Research Associates: Bob Dickman, Grant Merrill. Data Analysts: Karin Eichhoff, Joanne Stewart, Anne Trainor. Data Entry: Charlie Blackburn, Patrick Burke, Rebecca Grote, Angela Hill, Mindy Paulek. Mary Schuette and Dave Theobald provided assistance with the GIS analysis and M. Schuette generated the maps used in this report Photographs: Tom Beck, Bruce Gill, Mary Lloyd, Rich Reading, Rick Thompson. Funding: CDOW, Great Outdoors Colorado (GOCO), Turner Foundation, U.S.D.A. Forest Service, Vail Associates, Colorado Wildlife Heritage Foundation. LITERATURE CITED Aubry, K. B., G. M. Koehler, J. R. Squires. 1999. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Bartmann, R. M., and Byrne, G. (2001) Analysis and critique of the 1998 snowshoe hare pellet survey. Colorado Division of Wildlife Report No. 20. Fort Collins, Colorado. Byrne, G. 1998. Core area release site selection and considerations for a Canada lynx reintroduction in Colorado. Report for the Colorado Division of Wildlife. Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2008. Estimating mortality for a widely dispersing reintroduced carnivore, the Canada lynx (Lynx canadensis). Ecology (in review). Hodges, K. E. 1999. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires editors. Ecology and Conservation of Lynx in the United States. General 17 �Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Koehler, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. Kolbe, J. A., J. R. Squires, T. W. Parker. 2003. An effective box trap for capturing lynx. Journal of Wildlife Management 31:980-985. Major, A. R. 1989. Lynx, Lynx canadensis canadensis (Kerr) predation patterns and habitat use in the Yukon Territory, Canada. M. S. Thesis, State University of New York, Syracuse. Mowat, G., K. G. Poole, and M. O‘Donoghue. 1999. Ecology of lynx in northern Canada and Alaska. Pages 265-306 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Poole, K. G., G. Mowat, and B. G. Slough. 1993. Chemical immobilization of lynx. Wildlife Society Bulletin 21:136-140. Shenk, T. M. 1999. Program Narrative Study Plan: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2001. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 7- 34. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2006. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 1-45. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 1-57. Colorado Division of Wildlife, Fort Collins, Colorado. Silverman, B.W. 1986. Density Estimation for Statistics and Data Analysis. Chapman and Hall. New York, New York, USA. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. Wild, M. A. 1999. Lynx veterinary services and diagnostics. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. Zahratka, J. L. and T. M. Shenk. 2008. Population estimates of snowshoe hares in the southern Rocky Mountains. Journal of Wildlife Management 72: 906-912. Prepared by ___________________________________ Tanya M. Shenk, Wildlife Researcher 18 �Table 1. Number of wild-caught male (M) and female (F) Canada lynx (Lynx canadensis) from Alaska (AK) and Canada (BC = British Columbia, MB = Manitoba, QU = Quebec and YK = Yukon) released in southwestern Colorado per year from 1999–2006. State / Province of Origin Total Year %Released Sex AK BC MB QU YK 1999 19 2000 25 2003 15 2004 17 2005 17 2006 6 Total F 13 5 4 22 M 7 6 6 19 F 6 9 20 35 M 4 9 7 20 F 10 7 17 M 10 5 16 F 7 10 17 M 13 7 20 F 4 M 9 F M 30 1 3 8 3 18 8 3 20 4 3 7 5 2 7 48 218 91 4 45 Table 2. Status of adult Canada lynx (Lynx canadensis) reintroduced to Colorado as of August 27, 2008. Females Lynx Males Unknown TOTALS Released 115 103 218 Known Dead 62 49 1 112 Possible Alive 53 54 106 Missing 27 35 61a Monitoring/tracking 26 19 45 a 1 is unknown mortality Table 3. Causes of death for all Canada lynx (Lynx canadensis) released into southwestern Colorado 1999-2006 as of August 27, 2008. Mortalities Cause of Death Total (%) In Colorado (%) Outside Colorado (%) Unknown 41 (36.6) 27 (32.91) 14 (46.7) Gunshot 15 (13.4) 9 (11.0) 6 (20.0) Hit by Vehicle 14 (12.5) 9 (11.0) 5 (16.7) Starvation 11 (9.8) 10 (12.2) 1 (3.3) Other Trauma 8 (7.1) 7 (8.5) 1 (3.3) Plague 7 (6.3) 7 (8.5) 0 (0) Probable Gunshot 5 (4.5) 4 (4.9) 1 (3.3) Predation 5 (4.5) 5 (6.1) 0 (0) Probable Predation 3 (2.7) 2 (2.4) 1 (3.3) Illness 3 (2.7) 2 (2.4) 1 (3.3) Total Mortalities 112 82 (73.2) 30 (26.8) 19 �Table 4. Known lynx mortalities (n = 30) and causes of death documented by state outside of Colorado from February 1999 – August 27, 2008. Lynx ID AK99F8 Unknown AK99M11 YK99M06 AK99F13 YK00F04 BC99M04 QU05M01 QU04F05 QU03F07 BC00M04 YK06F01 BC03M08 BC06F07 AK99M06 AK99M01 QU05M08 MB05F02 BC00F14 QU04F07 BC06M10 QU04F02 AK00M03 QU05M03 YK06M01 YK00F07 YK99F01 YK00M03 YK05M03 YK05M02 State Date Mortality Recorded Cause of Death New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico Nebraska Nebraska Nebraska Nebraska Wyoming Wyoming Wyoming Wyoming Utah Utah Utah Utah Arizona Kansas Montana Iowa 7/30/1999 2000 1/27/2000 6/19/2000 6/22/2000 4/20/2001 6/7/2002 8/22/2005 8/26/2005 9/15/2005 7/19/2006 10/19/2006 10/19/2006 1/8/2007 11/16/1999 1/11/2005 10/1/2006 2/13/2007 7/28/2004 9/21/2004 8/15/2006 3/14/2007 7/2/2001 10/26/2005 12/4/2006 8/6/2007 9/15/2005 9/30/2005 11/8/2005 8/6/2007 Starvation Hit by Vehicle Unknown Probable Gunshot Unknown Gunshot Gunshot Unknown Hit by Vehicle Unknown Unknown Unknown Unknown Gunshot Gunshot Snared (Other Trauma) Unknown Gunshot Unknown Unknown Vehicle Collision Unknown Unknown Unknown Unknown Unknown Gunshot Vehicle Collision Unknown Vehicle Collision Table 5. Lynx reproduction summary statistics for 1999-2008. No reproduction was expected in 1999 because it was the first year of lynx releases and most animals were released after breeding season. Year Females Tracked 2000 2001 2002 2003 2004 2005 2006 2007 2008 TOTAL 9 25 21 17 26 40 42 34 28 Dens Found in May/June 0 0 0 6 11 17 4 0 0 Percent Tracked Females with Kittens 0.0 0.0 0.0 0.353 0.462 0.425 0.095 0.0 0.0 Additional Litters Found in Winter 0 0 0 0 2 1 0 0 0 20 Mean Kittens/Litte r (SE) 2.67 (0.33) 2.83 (0.24) 2.88 (0.18) 2.75 (0.47) Total Kittens Found Sex Ratio M/F (SE) 0 0 0 16 39 50 11 1.0 1.5 0.8 1.2 0 0 116 1.14 (0.14) �Table 6. Lynx captured because they were in poor body condition or were in atypical habitat and their fates 6 months post re-release and as of August 28, 2008. Lynx ID BC99F6 Date of Capture 3/25/1999 State Where Captured Colorado Reason For Capture Poor body condition Date of Re-release 5/28/1999 Status 6 Months Post Re-release Dead AK99M9 3/24/2000 Colorado 5/3/2000 Missing AK99F2 4/18/2000 Colorado 5/22/2000 BC00F7 2/11/2001 Colorado Alive in Colorado Dead BC00M13 3/21/2001 Wyoming BC03M08 9/5/2003 Colorado QU04M07 2/2/2006 Colorado Poor body condition Poor body condition Poor body condition Poor body condition Poor body condition Poor body condition BC04M01 11/5/2004 Utah QU04F02 4/10/2005 Nebraska QU05M08 11/25/2005 Wyoming QU04M04 12/5/2006 Utah YK00F07 12/12/2006 Utah YK05M02 1/1/2007 Kansas BC04M08 1/22/2007 Wyoming N/A 4/24/2001 1/1/2004 N/A Alive in Colorado Alive in Colorado Dead Atypical habitat Atypical habitat 12/5/2004 Atypical habitat Atypical habitat Atypical habitat Atypical habitat Atypical habitat 4/18/2006 Dead 1/20/2007 1/20/2007 Dead in Colorado Alive in Utah 2/2/2007 Alive in Iowa 2/15/2007 Alive in Colorado 5/7/2005 Alive in Colorado Alive in Wyoming Current Status Died 7/19/1999 in Colorado from vehicle collision Last located 5/3/2000, collar failure Last located 7/30/2003 in Colorado Died at Rehab Center on 2/12/2001 Last located 10/26/2004 in Colorado Died in New Mexico of unknown causes 10/19/06 Died at Rehab Center on 2/5/2006 from hydrocephalous and pneumonia In Colorado as of 8/27/2008 Died 3/14/2007 in Wyoming (good habitat) of unknown causes Died of unknown causes in Nebraska 10/1/2006 Died of starvation in Colorado, found 3/19/07 Died in Utah of unknown causes 8/6/2007 Died in Iowa from vehicle collision 8/6/2007 Died in Colorado from gunshot 1/4/2008 Table 7. Number of kills found each winter field season through snow-tracking of lynx and percent composition of kills of the three primary prey species. Field Season 1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007 2007-2008 Total/Mean n 9 83 89 54 65 37 78 50 41 42 548 Snowshoe Hare 55.56 67.47 67.42 90.74 90.77 67.57 83.33 90.00 61.00 59.00 73.29 (SE=4.7) Prey (%) Red Squirrel Cottontail 22.22 0 19.28 1.20 19.10 8.99 5.56 0 6.15 0 27.03 2.70 10.26 0 0.08 0 39.0 0 33.3 0 18.2 (SE=4.2) 1.29 (SE=0.95) 21 Other 22.22 12.05 4.49 3.70 3.08 2.70 6.41 0.02 0 7.4 6.21 (SE=2.22) �Figure 1. Lynx are monitored throughout Colorado and by satellite throughout the western United States. The lynx core release area, where all lynx were released, is located in southwestern Colorado. A lynx-established core use area has developed in the Taylor Park and Collegiate Peak area in central Colorado. 22 �Figure 2. All documented lynx locations (non-truncated datasets) obtained from either aerial (red circles) or satellite (yellow circles) tracking from February 1999 through August 27, 2008. All known lynx mortality locations (n = 112) are displayed as black stars. 23 �Figure 3. Use-density surface for lynx aerial locations (truncated dataset) in Colorado from September 1999-March 2007. 24 �Figure 4. Use-density surface for lynx satellite locations (truncated dataset) in Colorado from September 1999-March 2007. 25 �APPENDIX I Colorado Division of Wildlife July 2007 - June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 2 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Lynx Conservation Density, Demography, and Seasonal Movements Of Snowshoe Hare in Colorado Period Covered: July 1, 2007- June 30, 2008 Author: J. S. Ivan, Ph.D. Candidate, Colorado State University Personnel: Dr. T. Shenk of CDOW and Dr. G. C. White of Colorado State University. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A program to reintroduce the threatened Canada lynx (Lynx canadensis) into Colorado was initiated in 1997. Analysis of scat collected from winter snow tracking indicates that snowshoe hares (Lepus americanus) comprise 65–90% of the winter diet of reintroduced lynx. Thus, existence of lynx in Colorado and success of the reintroduction hinge at least partly on maintaining adequate and widespread hare populations. Beginning in July 2006, I initiated a study to assess the relative value of 3 stand types for providing hare habitat in Colorado. These types include mature, uneven-aged spruce/fir forests, sapling lodgepole pine forests (―small lodgepole‖), and pole-sized lodgepole pine forests (―medium lodgepole‖). Estimates and comparisons of survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each stand will provide the metrics for assessing these stands. Thus far, snowshoe hare densities on the study area are low compared to densities reported elsewhere. Within the study area, hare densities during summer were highest in small lodgepole stands, followed by mature spruce/fir and medium lodgepole, respectively. This pattern was consistent through the first 2 summers of this project, although absolute hare densities declined considerably in summer 2007. Hare density in small and medium lodgepole stands equalized during both winters of the project. However, as with summer, overall density was much lower during the second winter compared to the first. Hare survival from summer to winter has been relatively high. However the single winter to summer estimate I have to date is quite low. Extension of this time series will help determine whether low winter to summer survival is typical or somehow related to the decline in density. 26 �WILDIFE RESEARCH REPORT DENSITY, DEMOGRAPHY, AND SEASONAL MOVEMENTS OF SNOWSHOE HARES IN COLORADO JACOB S. IVAN P. N. OBJECTIVE Assess the relative value of 3 stand types (mature spruce/fir, sapling lodgepole, pole-sized lodgepole) that purportedly provide high quality hare habitat by estimating survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each type. SEGMENT OBJECTIVES 1. Complete mark-recapture work across all replicate stands during late summer (mid-July through midSeptember) and winter (mid-January through March). 2. Obtain daily telemetry locations on radio-tagged hares for 10 days immediately after capture periods, as well as monthly between primary trapping sessions. 3. Locate, retrieve, and refurbish radio tags as mortalities occur. 4. Summarize initial sampling efforts and provide initial density estimates for Progress Reports for Colorado Division of Wildlife (CDOW). INTRODUCTION NEED A program to reintroduce the threatened Canada lynx (Lynx canadensis) into Colorado was initiated in 1997. Since that time, 218 lynx have been released in the state, and an extensive effort to determine their movements, habitat use, reproductive success, and food habits has ensued (Shenk 2005, Shenk 2007). Analysis of scat collected from winter snow tracking indicates that snowshoe hares (Lepus americanus) comprise 65–90% of the winter diet of reintroduced lynx (T. Shenk, Colorado Division of Wildlife, unpublished data). Thus, as in the far north where the intimate relationship between lynx and snowshoe hares has captured the attention of ecologists for decades, it appears that the existence of lynx in Colorado and success of the reintroduction effort may hinge on maintaining adequate and widespread populations of hares. Colorado represents the extreme southern range limit for both lynx and snowshoe hares (Hodges 2000). At this latitude, habitat for each species is less widespread and more fragmented compared to the continuous expanse of boreal forest at the heart of lynx and hare ranges. Neither exhibits dramatic cycles as occur farther north, and typical lynx ( 2 3 lynx/100km2; Aubry et al. 2000) and hare ( 1 2 hares/ha; Hodges 2000) densities in the southern part of their range correspond to cyclic lows form northern populations (2-30 lynx/100 km2, 1 16 hares/ha; Aubry et al. 2000, Hodges 2000, Hodges et al. 2001). Whereas extensive research on lynx-hare ecology has occurred in the boreal forests of Canada, literature regarding the ecology of these species in the southern portion of their range is relatively sparse. This scientific uncertainty is acknowledged in the ―Canada Lynx Conservation Assessment and Strategy,‖ a formal agreement between federal agencies intended to provide a consistent approach to lynx conservation on public lands in the lower 48 states (Ruediger et al. 2000). In fact, one of the explicit guiding principles of this document is to ―retain future options…until more conclusive information concerning lynx management is developed.‖ Thus, management recommendations in this agreement are decidedly conservative, especially with respect to timber management, and are applied broadly to cover 27 �all habitats thought to be of possible value to lynx and hare. Accurate identification and detailed description of lynx-hare habitat in the southern Rocky Mountains would permit more informed and refined management recommendations. A commonality throughout the snowshoe hare literature, regardless of geographic location, is that hares are associated with dense understory vegetation that provides both browse and protection from elements and predators (Wolfe et al. 1982, Litvaitis et al. 1985, Hodges 2000, Homyack et al. 2003, Miller 2005). In western mountains, this understory can be provided by relatively young conifer stands regenerating after stand-replacing fires or timber harvest (Sullivan and Sullivan 1988, Koehler 1990a, Koehler 1990b, Bull et al. 2005) as well as mature, uneven-aged stands (Beauvais 1997, Griffin 2004). Hares may also take advantage of seasonally abundant browse and cover provided by deciduous, open habitats (e.g., riparian willow [Salix spp.], aspen [Populus tremuloides]; Wolff 1980, Miller 2005). In drier portions of hare range, such as Colorado, regenerating stands can be relatively sparse, and hares may be more associated with mesic, late-seral forest and/or riparian areas than with young stands (Ruggiero et al. 2000). Numerous investigators have sought to determine the relative importance of these distinctly different habitat types with regards to snowshoe hare ecology. Most previous evaluations were based on hare density or abundance (Bull et al. 2005), indices to hare density and abundance (Wolfe et al. 1982, Koehler 1990a, Beauvais 1997, Miller 2005), survival (Bull et al. 2005), and/or habitat use (Dolbeer and Clark 1975). Each of these approaches provides insight into hare ecology, but taken singly, none provide a complete picture and may even be misleading. For example, extensive use of a particular habitat type may not accurately reflect the fitness it imparts on individuals, and density can be high even in ―sink‖ habitats (Van Horne 1983). A more informative approach would be to measure density, survival, and habitat use simultaneously in addition to recruitment and population growth rate through time. Griffin (2004) employed such an approach and found that summer hare densities were consistently highest in young, dense stands. However, he also noted that only dense mature stands held as many hares in winter as in summer. Furthermore hare survival seemed to be higher in dense mature stands, and only dense mature stands were predicted (by matrix projection) to impart a mean positive population growth rate on hares. Griffin‘s (2004) study occurred in the relatively moist forests of Montana, which share many similarities but also many notable differences with Colorado forests including levels of fragmentation, species composition, elevation, and annual precipitation. Density estimation is a key component in assessing the value of a particular stand type and is the common currency by which hare populations are compared across time and space. However, it can be a difficult metric to estimate accurately. Abundance estimation based on capture-recapture methods is a well-developed field (Otis et al. 1978, White et al. 1982), but is often too costly and labor intensive to be implemented on scales necessary to effectively monitor density over a biologically meaningful area. Also, density can be difficult to assess from grid-trapping efforts because it is often unclear how much area was effectively sampled by the grid (Williams et al. 2002:314). Alternate approaches can produce density estimates that differ by an order of magnitude even when calculated from the same data (Zahratka 2004). Indices such as pellet plot counts and distance sampling of pellet groups can be used to estimate density, but each of these has limitations as well (Krebs et al. 1987, Eriksson 2006). The study outlined below is designed principally to evaluate the importance of young, regenerating lodgepole pine (Pinus contorta) and mature Engelmann spruce (Picea engelmannii)/ subalpine fir (Abies lasiocarpa) stands in Colorado by examining density and demography of snowshoe hares that reside in each. Secondarily, I intend to quantify movement between these stands and other seasonally available types (e.g., willow). My hope is that information gathered from this research will be drawn upon as managers make routine decisions, leading to landscapes that include stands capable of 28 �supporting abundant populations of hares. I assume that if management agencies focus on providing habitat, hares will persist. I will use mark-recapture techniques as data from such an approach can provide information on both density and demography. In the future, I will address the ―effective trapping area‖ issue using a new approach that augments mark-recapture data with telemetry locations of animals using the grid. However, for this report I used one of the more popular, traditional techniques. I determined that 2 classes of young, regenerating lodgepole stands could both provide adequate hare habitat. Thus, in addition to older spruce/fir forests, I am sampling ―small‖ (2.54-12.69 cm dbh) and ―medium‖ (12.70-22.85 cm dbh) stands regenerating from clearcutting that took place 20 and 40 years ago, respectively (Figure 1). Additionally, medium lodgepole stands were pre-commercially thinned 20 years ago; small lodgepole stands have not yet been thinned. Hypotheses 1) In general, snowshoe hare density in Colorado will be relatively low ( 0.5 hares/ha) compared to densities reported in northern boreal forests, even immediately post-breeding when an influx of juveniles will bolster hare numbers. 2) Snowshoe hare density will be consistently highest in small lodgepole pine stands, followed by large spruce/fir and medium lodgepole pine, respectively. 3) Survival will generally be highest in mature (large) spruce/fir stands followed by small and medium lodgepole pine, respectively. 4) Finite population growth rate will be consistently at or above 1.0 in mature spruce/fir stands with survival contributing most significantly to the growth rate. Finite growth rates for the lodgepole pine stands will be more variable. 5) Snowshoe hares will significantly shift their home ranges to make use of abundant food and cover provided by riparian willow (and/or aspen) habitats in summer. 6) Snowshoe hare density, survival, and recruitment will be highly correlated with understory cover and stem density. STUDY AREA The study area stretches from Taylor Park to Pitkin in central Colorado (Figure 2). Elevation ranges from 2700 m to 4000 m. Sagebrush (Artemisia spp.) dominates broad, low-lying valleys. Most montane areas are covered by even-aged, large-diameter lodgepole pine forests with sparse understory. Moist, north-facing slopes and areas near tree line are dominated by large-diameter Engelmann spruce/subalpine fir. Interspersed along streams and rivers are corridors of willow. Patches of aspen occur sporadically on southern exposures. This area was chosen over other potential study areas in the state because 1) it contained numerous examples of the 3 stand types of interest (more southern regions lack naturally occurring stands of lodgepole pine), 2) it was not subject to confounding effects of largescale mountain pine beetle outbreak as were more northern stands, and 3) an adequate number of radio frequencies were available to support a large study with hundreds of radio-tagged individuals. Within the study area I selected sample stands based on the following: Potential replicate stands were required to be 1) close enough geographically to minimize differences due to climate, weather, and topography, but are far enough apart to be considered independent, 2) adjacent to one or more riparian willow corridors, 3) within 1 km of an access road for logistical purposes, 4) of suitable size and shape to admit a 16.5-ha trapping grid, and 5) consistent in their management history (i.e., replicate lodgepole pine stands were clear-cut and/or thinned within 1-2 years of each other). I queried the U.S. Forest Service R2VEG GIS database using the criteria listed above to initially develop a suite of potential sample stands. I further narrowed this suite after obtaining updated standlevel information from local USFS personnel (Art Haines, Silviculturalist, USFS Gunnison Ranger 29 �District, personal communication). Finally, I ground-truthed potential stands and qualitatively assessed their representativeness and similarity to other potential replicates. Given the numerous constraints imposed, very few stands met all criteria. Thus, I was unable to randomly select sample stands from a population of suitable stands. Rather, I subjectively chose the ―best‖ stands from among the handful that met my criteria. Small lodgepole stands rarely occur on the landscape in patches large enough to fit a full trapping grid. To accommodate this, I sampled 6 replicate small lodgepole stands (rather than 3) using half-sized trapping grids. METHODS Experimental Design/Procedures Variables.--The response variables of interest for this project include stand-specific snowshoe hare density (D), apparent survival ( ), recruitment (f), finite population growth rate (λ), and a metric of seasonal movement. Density is the number of hares per unit area and is estimated using a conventional techniques in this report. The stand-specific demographic parameters will be estimated primarily from capture-mark-recapture methods. As such, apparent survival is defined as the probability that a marked animal alive and in the population at time i survives and is in the population at time i + 1. Apparent survival encompasses losses due to both death and emigration. Estimates of recruitment, population growth, and seasonal movement are forthcoming and not provided in this report. Potential explanatory variables for snowshoe hare density, demographics, and movement include general species composition and structural stage of each stand in which response variables are measured. Additionally, stem density, horizontal cover, and canopy cover (to a lesser extent) are highly correlated with snowshoe hare abundance and habitat use (Wolfe et al. 1982, Litvaitis et al. 1985, Hodges 2000, Zahratka 2004, Miller 2005). Thus, I further characterized vegetation in each stand by measuring stem density by size class (1-7 cm, 7.1-10 cm, and >10 cm), percent canopy cover, percent horizontal cover of understory and basal area. Basal area is an easily obtainable metric that may be correlated with the other variables and is recorded routinely during timber cruises, whereas the others are not. Thus, it might prove a useful link for biologists designing management strategies for snowshoe hare. Additionally, I recorded physical covariates such as ambient temperature, precipitation, and snow depth at each stand during sampling. These metrics were not included in the current preliminary analyses, but will be used as covariates in future models. Sampling.--All trapping and handling procedures have been approved by the Colorado State University Animal Care and Use Committee and filed with the Colorado Division of Wildlife. Snowshoe hares breed synchronously and generally exhibit 2 birth pulses in Colorado (although in some years, some individuals may have 3 litters), with the first pulse terminating approximately June 5 20 and the second approximately July 15–25 (Dolbeer 1972). To obtain a maximum density estimate, I began data collection on the first suite of sites immediately following the second birth pulse in late July. Along with a crew of 5 technicians, I deployed one 7 12 trapping grid (50-m spacing between traps; grid covers 16.5 ha) in the large spruce/fir and medium lodgepole stands within the first suite, along with 2 6 7 grids in 2 small lodgepole stands. Grid set up and trap deployment followed Griffin (2004) and Zahratka (2004). Grid locations and orientation within each stand were chosen subjectively to accommodate logistical constraints and to ensure that hares using the grid had ample opportunity to use adjacent riparian willow zones. As traps were deployed, they were locked open and ―pre-baited‖ with apple slices, hay cubes, and commercial rabbit chow. Traps were pre-baited in this manner for a total of 3 nights to maximize capture rates when trapping began. This minimized the number of trap-nights needed to capture the desired number of animals which in turn minimized trap-related injuries and minimized problems with predators keying into trap lines. During pilot work in winter 2005, I observed low but increasing capture rates (<0.20) during the first 3 nights of trapping, with higher, more stable capture 30 �probabilities after 3 days (approximately 0.35–0.45). Thus 3 days of pre-baiting seemed reasonable. Traps were set on the afternoon of the 4th day and checked early each morning and again in the evening on days 5–9. By checking traps in both morning and evening I prevented hares from being entrapped >13 hours, which should minimize capture stress. A crew of 2 people worked together on each grid to check traps and process captures as quickly as possible. All captured hares were coaxed out of the trap and into a dark handling bag by blowing quick shots of air on them from behind. Hares remained in the handling bag, physically restrained with their eyes covered, for the entire handling process. Each individual was aged, sexed, marked with a passive integrated transponder (PIT) tag and temporary ear mark (to track PIT tag retention), then released. Aging consisted of assigning each individual as either juvenile (<1 year old, <1000 g) or adult ( 1 year old, 1000 g) based on weight. This criterion is accurate through the end of September at which point juveniles are difficult to distinguish from adults (K. Hodges, University of British Columbia; P. Griffin, University of Montana, personal communication). After the first day of trapping, all captured hares were scanned for a PIT tag prior to any handling and those already marked were recorded and immediately released. Traps and bait were completely removed from the grid on day 10. In addition to PIT tags and ear marks, I radio collared up to 10 hares captured on each grid with a 28-g mortality-sensing transmitter (BioTrack, LTD) to facilitate unbiased density estimation as well as assessment of seasonal movements. I expected heterogeneity in snowshoe hare movements and use of the grid area, with potential bias surfacing due to location at which a hare is captured (e.g., hares captured on the edge of a grid may use the grid area differently than those captured at the center), and differential behavioral responses to trapping (e.g., young individuals may have lower capture probabilities and thus may be more likely to be captured on later occasions). To guard against the first potential bias, I randomly selected a starting trap location each morning and ran the grid systematically from that point. Thus, the first several hares encountered (and collared) were as likely to be from the inner part of the grid as from the edge. To protect against the second potential source of bias, I refrained from deploying the final 3 collars until days 4 and 5 of the trapping session. Immediately following the removal of traps, the field crew began work locating each radiocollared hare 1–2 times per day for 10 days. Most locations were obtained by triangulation from relatively close proximity, but some were obtained by ―homing‖ on a signal (Samuel and Fuller 1996, Griffin 2004) taking care not to push hares while approaching them. Because hares are largely nocturnal (Keith 1964, Mech et al. 1966, Foresman and Pearson 1999), I made an effort to conduct telemetry work at various times of the night (safety and logistics permitting) and day to gather a representative sample of locations for each hare. Crews gathered telemetry locations for radio-collared hares on the initial suite of sites for 10 days. Then the 10 day trapping procedure and 8 to 10 day telemetry work were repeated on the grids comprising suites 2 and 3(Figure 3). The entire process was repeated during the winter when densities should have been at a minimum. Thus, during the period covered by this report, sampling occurred from July 16 – September 14 and from January 20 – March 24, 2008. Sampling occurred across similar dates during FY06/07 and will continue during FY08/09. During the interim between intensive trapping and telemetry work, monthly telemetry checks were conducted from the air to track mortalities and facilitate retrieval of collars from dead hares. Telemetry work also occurred during ―pre-baiting‖ days after the initial summer sampling session to determine which hares were still alive and immediately available to be sampled by the grid during the ensuing trapping period. Vegetation sampling at each stand commenced in June 2008 and is nearly finished. I followed protocols established through previous snowshoe hare and lynx work in Colorado (Zahratka 2004, T. 31 �Shenk, Colorado Division of Wildlife, personal communication). Specifically, on each of the 12 livetrapping grids, I laid out 5 5 grids (3-m spacing) of vegetation sampling points centered on 15 of the 84 trap locations (Figure 4; 9 points were sampled on each of the ½-sized small lodgepole stands). At each of the 25 vegetation sampling points, I recorded canopy cover (present or absent) using a densitometer. I quantified downed coarse wood along the center transect of the 25-point grid following Brown (1974). From the centerpoint (i.e., trap location) I measured 1) distance to the nearest woody stem 1.0 7.0 cm, 7.1 10.0 cm, and >10.0 cm in diameter at heights of 0.1 m and 1.0 m above the ground (to capture both summer and winter stem density; Barbour et al. 1999), 2) horizontal cover in 0.5-m increments above the ground up to 2 m (Nudds 1977), 3) basal area, and 4) slope. Data Analysis Density, Survival, and Population Growth.--I analyzed mark-recapture data in a robust design framework (Williams et al. 2002:523-554) treating summer and winter sampling occasions as primary periods, and the 5-day trapping sessions within each as secondary periods. As such, I assumed hare populations were demographically and geographically closed during the short 5-day mark-recapture sampling periods, but were open to immigration, emigration, births, and deaths between these occasions. I specified the Pradel Robust Design data type in Program MARK (White and Burnham 1999) and chose the Huggins closed capture model (Huggins 1989, 1991) to obtain abundance estimates for each grid from the secondary periods. I obtained estimates of apparent survival ( ˆ i ) between each primary period. I employed a technique known as ½ Mean Maxmimum Distance Moved (MMDM; Wilson and Anderson 1985) to calculate the effective area trapped and obtain a density estimate for each grid from each secondary period. Future density analyses will employ a new estimator that employs telemetry data to correct for bias (Ivan 2005). I used Akaike‘s Information Criterion corrected for small sample size (AICc; Burnham and Anderson 1998) to select appropriate models from alternatives that included all 8 closed capture models (Otis et al. 1978) in combination with models that allowed survival to be constant, vary with time, and/or vary with stand type. RESULTS AND DISCUSSION I captured 30 hares 73 times during July-September 2007. I captured 48 hares 71 times during January-March 2008. During summer, density estimates have thus far followed hypotheses 1) and 2) above (Figure 5). Specifically, hare densities were clearly highest in small lodgepole stands and quite low in medium lodgepole stands. Spruce/fir was intermediate in density. This pattern remained consistent between summer 2006 to summer 2007, although the absolute density of hares dropped considerably during summer 2007. Why this decline occurred is unclear, although disease outbreak, natural population cycles, and response to increased predation due to lynx reintroduction are possibilities. Note that even the highest densities recorded here correspond to low estimates observed in other parts of hare range (Hodges 2000). Hare densities tend to equalize in lodgepole stands during winter (Figure 5). I submit that the interplay between food, cover, and snow depth provides a plausible explanation for this pattern. Medium lodgepole stands apparently provide very little forage/cover for hares during summer as the canopy in these stands is generally ≥1 meter off the ground. However, in winter, accumulated snow may make that canopy available again to hares. Conversely, small lodgepole stands provide abundant food and cover during summer, but accumulated snow during winter brings hares closer to the crowns of the young trees, which then provide less cover. Spruce/fir stands probably provide adequate access to both food and cover during both summer and winter due to their uneven-aged, multi-layered structure. Like the summer estimates, density during the second winter was much lower than during the first winter. 32 �Hare survival from the first sampling season into the first winter was relatively high (Figure 6). However, survival from the first winter to the second summer declined drastically. Survival from the second summer to the second winter was again quite high. Whether this pattern is typical is unclear. Survival from winter to summer is commonly lower than from summer to winter. However, the low survival from the first winter to second summer is coincident with the dramatic decline in hare density observed on spruce/fir and small lodgepole grids. Thus, low survival for this period is possibly reflective of, or maybe even a driver for, the decline in density. Extension of the time series and a breakdown of survival by stand type should provide more evidence for one or the other of these explanations. SUMMARY Snowshoe hare densities on my study sites appear to be relatively low compared to densities reported elsewhere. Densities during summer were highest in small lodgepole stands, followed by spruce/fir and medium lodgepole. During winter, densities equalize in lodgepole stands, possibly due to the interplay between snow depth and canopy height in small and medium lodgepole pine. Hare density declined considerably beginning in summer 2007. Summer to winter hare survival has been consistently high thus far in the study, but the lone winter to summer survival estimate is quite low. It is unclear whether winter to summer survival is typically this low or whether that estimate is related to coincident drop in density. ACKNOWLEDGMENTS Ken Wilson (CSU), Bill Romme (CSU), Paul Doherty (CSU), Dave Freddy (CDOW), Chad Bishop (CDOW), and Paul Lukacs (CDOW) provided helpful insight on the design of this study. We appreciate the invaluable logistical support provided by Mike Jackson (USFS), Art Haines (USFS), Jake Spritzer (USFS), Kerry Spetter (USFS), Margie Michaels (CDOW), Gabriele Engler (USGS), Dana Winkelman (USGS), Brandon Diamond (CDOW), Chris Parmeter (CDOW), Kathaleen Crane (CDOW), Lisa Wolfe (CDOW), and Laurie Baeten (CDOW). Jim Gammonley (CDOW), Dave Freddy (CDOW), Chad Bishop (CDOW), Jack Vayhinger (CDOW), Brandon Diamond (CDOW) assisted with trucks and equipment. The following hardy individuals collected the hard-won data presented in this report: Braden Burkholder, Matt Cuzzocreo, Brian Gerber, Belita Marine, Adam Behney, Pete Lundberg, Katie Yale, Britta Shielke, Cory VanStratt, Mike Watrobka, Meredith Goss, Sidra Blake, Keith Rutz, Rob Saltmarsh, Jennie Sinclair, Evan Wilson, Mat Levine, Matt Strauser, Greg Davidson, Leah Yandow, Renae Sattler, and Caylen Cummins. Funding was provided by the Colorado Division of Wildlife. LITERATURE CITED Aubry, K. B., G. M. Koehler, and J. R. Squires. 2000. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA. Barbour, M. G., J. H. Burk, W. E. Pitts, F. S. Gilliam, and M. W. Schwartz. 1999. Terrestrial plant ecology, Addison Wesley Longman, Inc., Menlo Park, California, USA. Beauvais, G. P. 1997. Mammals in fragmented forests in the Rocky Mountains: community structure, habitat selection, and individual fitness. Dissertation, University of Wyoming, Laramie, Wyoming, USA. Brown, J. K. 1974. Handbook for inventorying downed woody material. U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report 33 �INT-16. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. Bull, E. L., T. W. Heater, A. A. Clark, J. F. Shepherd, and A. K. Blumton. 2005. Influence of precommercial thinning on snowshoe hares. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, General Technical Report PNW-RP-562. Dolbeer, R. A. and W. R. Clark. 1975. Population ecology of snowshoe hares in the central Rocky Mountains. Journal of Wildlife Management 39:535-549. Dolbeer, R. A. 1972. Population dynamics of snowshoe hare in Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. Eriksson, H. M. 2006. Snowshoe hare densities in post-fire vegetation. Thesis, University of Alaska Fairbanks, Fairbanks, Alaska, USA. Foresman, K. R. and D. E. Pearson. 1999. Activity patterns of American martens, Martes americana, snowshoe hares, Lepus americanus, and red squirrels, Tamiasciurus hudsonicus, in westcentral Montana. The Canadian Field-Naturalist 113:386-389. Griffin, P. C. 2004. Landscape ecology of snowshoe hares in Montana. Dissertation, University of Montana, Missoula, Montana, USA. Hodges, K. E. 2000. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163-206 in Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. Hodges, K. E., C. J. Krebs, D. S. Hik, C. I. Stefan, E. A. Gillis, and C. E. Doyle. 2001. Snowshoe hare demography. Pages 141-178 in Krebs, C. J., S. Boutin, and R. Boonstra, editors. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. Homyack, J. A., D. J. Harrison, and W. B. Krohn. 2003. Effects of precommercial thinning on select wildlife species in northern Maine, with special emphasis on snowshoe hare. Maine Cooperative Fish and Wildlife Research Unit, Orono, Maine, USA. Huggins, R. M. 1989. On the statistical analysis of capture-recapture experiments. Biometrika 76:133140. Huggins, R. M. 1991. Some practical aspects of a conditional likelihood approach to capture experiments. Biometrics 47:725-732. Ivan, J. S. 2006. Density, demography, and seasonal movements of snowshoe hares in Colorado. Program narrative study plan for mammals research. Pages 27-45 in T.M. Shenk. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 1-45. Colorado Division of Wildlife, Fort Collins, Colorado, USA. Keith, L. B. 1964. Daily activity pattern of snowshoe hares. Journal of Mammalogy 45:626-627. Koehler, G. M. 1990a. Snowshoe hare, Lepus americanus, use of forest successional stages and population changes during 1985-1989 in North-central Washington. Canadian Field-Naturalist 105:291-293. Koehler, G. M. 1990b. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. Krebs, C. J., B. Scott Gilbert, S. Boutin, and e. al. R. Boonstra. 1987. Estimation of snowshoe hare population density from turd transects. Canadian Journal of Zoology 65:565-567. Litvaitis, J. A., J. A. Sherburne, and J. A. Bissonette. 1985. Influence of understory characteristics on snowshoe hare habitat use and density. Journal of Wildlife Management 49:866-873. Mech, L. D., K. L. Heezen, and D. B. Siniff. 1966. Onset and cessation of activity in cottontail rabbit and snowshoe hares in relation to sunset and sunrise. Animal Behaviour 14:410-413. Miller, M. A. 2005. Snowshoe hare habitat relationships in northwest Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Nudds, T. D. 1977. Quantifying the vegetative structure of wildlife cover. Wildlife Society Bulletin 34 �5:113-117. Otis, D. L., K. P. Burnham, G. C. White, and D. R. Anderson. 1978. Statisical inference from capture data on closed animal populations. Wildlife Monographs 62: Ruediger, B., J. Claar, S. Gniadek, B. Holt, Lewis Lyle, S. Mighton, B. Naney, G. Patton , T. Rinaldi, J. Trick, A. Vendehey, F. Wahl, N. Warren, D. Wenger, and A. Williamson. 2000. Canada lynx conservation assessment and strategy. U.S. Department of Agriculture, Forest Service, U.S. Department of Interior, Fish and Wildlife Service, Bureau of Land Management, National Park Service R1-00-53 U.S. Department of Agriculture, Forest Service, U.S. Department of Interior, Fish and Wildlife Service, Bureau of Land Management, National Park Service, Missoula, Montana, USA. Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires. 2000. The scientific basis for lynx conservation: qualified insights. Pages 443-454 in Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA. Samuel, M. D. and M. R. Fuller. 1996. Wildlife radiotelemetry. Pages 370-418 in Bookhout, T. A., editors. Research and Management Techniques for Wildlife and Habitats. Allen Press, Inc., Lawrence, Kansas, USA. Shenk, T. M. 2005. General locations of lynx (Lynx canadensis) reintroduced to southwestern Colorado from February 4, 1999 through February 1, 2005. Colorado Division of Wildlife Colorado Division of Wildlife, Fort Collins, Colorado, USA. Shenk, T. M. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 1-57. Colorado Division of Wildlife, Fort Collins, Colorado USA. Sullivan, T. P. and D. S. Sullivan. 1988. Influence of stand thinning on snowshoe hare population dynamics and feeding damage in lodgepole pine forest. Journal of Applied Ecology 25:791-805. Van Horne, B. 1983. Density as a misleading indicator of habitat quality. Journal of Wildlife Management 47:893-901. White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory, Los Alamos, New Mexico, USA. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2002. Analysis and management of animal populations, Academic Press, San Diego, California, USA. Wilson, K. R. and D. R. Anderson. 1985. Evaluation of two density estimators of small mammal population size. Journal of Mammalogy 66:13-21. Wolfe, M. L., N. V. Debyle, C. S. Winchell, and T. R. McCabe. 1982. Snowshoe hare cover relationships in northern Utah. Journal of Wildlife Management 46:662-670. Wolff, J. O. 1980. The role of habitat patchiness in the population dynamics of snowshoe hares. Ecological Monographs 50:111-130. Zahratka, J. L. 2004. The population and habitat ecology of snowshoe hares (Lepus americanus) in the southern Rocky Mountains. Thesis, The University of Wyoming, Laramie, Wyoming, USA. Prepared by _________________________________________________ Jacob S. Ivan, Graduate Student, Colorado State University 35 �Figure 1. Purported high quality snowshoe hare habitat in Colorado. From left to right: small lodgepole pine, medium lodgepole pine, and large Engelmann spruce/subalpine fir. Figure 2. Study area near Taylor Park and Pitkin, Colorado including medium lodgepole (squares), small lodgepole (circles), and spruce/fir (triangles) stands selected for mark-recapture sampling. 36 �Jul Aug Sep 1 Jan 1 2 3 4 2 3 4 5 6 7 8 5 6 7 8 9 10 11 9 10 11 12 13 14 15 12 13 14 15 16 17 18 16 17 18 19 20 21 22 19 20 21 22 23 24 25 23 24 25 26 27 28 29 26 27 28 29 30 31 1 30 31 1 2 3 4 5 2 3 4 5 6 7 8 6 7 8 9 10 11 12 9 10 11 12 13 14 15 13 14 15 16 17 18 19 16 17 18 19 20 21 22 20 21 22 23 24 25 26 23 24 25 26 27 28 1 27 28 29 30 31 1 2 2 3 4 5 6 7 8 Feb Mar 3 4 5 6 7 8 9 9 10 11 12 13 14 15 10 11 12 13 14 15 16 16 17 18 19 20 21 22 17 18 19 20 21 22 23 23 24 25 26 27 28 29 24 25 26 27 28 29 30 30 31 Figure 3. Approximate annual data collection schedule for trapping () and telemetry (). Dates and weeks changed depending on calendar year and pay schedule. During telemetry work, the 6-person crew was divided into 2 teams, only one of which worked at any given time. Monthly locations on radiocollared hares were also collected in the interim between the intensive sampling periods indicated here. Figure 4. 15 trap locations ( ) on 7 12 trapping grid where vegetation was sampled by measuring stem density, horizontal cover, downed woody material, and basal area. Additionally, the 25-point grid superimposed on each of the 15 trap locations (inset) was used to quantify canopy covert). 37 �Figure 5. Snowshoe hare density and 95% confidence intervals in 3 types of stands in central Colorado as determined by ½ mean maximum distance moved, summer 2006 through winter 2008. Figure 6. Snowshoe hare survival and 95% confidence intervals across summer (S) and winter (W) sampling seasons in central Colorado as determined by mark-recapture, 2006-2008. 38 �Colorado Division of Wildlife July 2007 June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R Period Covered: July 1, 2007 : : : : : Division of Wildlife Mammals Research Deer Conservation Effect of Nutrition and Habitat Enhancements On Mule Deer Recruitment and Survival Rates June 30, 2008 Authors: C. J. Bishop, G. C. White, D. J. Freddy, and B. E. Watkins All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We measured mule deer (Odocoileus hemionus) population parameters in response to a nutrition enhancement treatment to evaluate the relative importance of habitat quality as a limiting factor of mule deer in western Colorado during November 2000 – January 2005. The nutrition enhancement treatment increased survival of fetuses to the yearling age class by 0.14 0.20 depending on year and fawn sex; 95% confidence intervals slightly overlapped 0. Averaged across sexes and years, survival of treatment fetuses to the yearling age class was 0.447 (SE = 0.0519), whereas survival of control fetuses to the yearling age class was 0.271 (SE = 0.0418). The treatment caused fetal to yearling survival to increase by 0.177 (SE = 0.0818, 95% CI: 0.0163, 0.3370). The nutrition treatment also had a positive effect on annual adult female survival. Survival of adult females receiving the treatment (Ŝ = 0.879, SE = 0.0206) was higher than survival of control adult females (Ŝ = 0.833, SE = 0.0253). Our estimate of the population rate of change, ˆ , was 1.165 (SE = 0.0358) for treatment deer and 1.033 (SE = 0.0380) for control deer. The nutrition treatment caused ˆ to increase by 0.133 (SE = 0.0428). We documented food limitation in the Uncompahgre deer population because survival of fawns and adult females increased considerably in response to enhanced nutrition. Our results provide a foundation for focusing deer management efforts on improving habitat quality in western Colorado pinyon-juniper (Pinus edulis-Juniperus osteosperma) ecosystems with corresponding research efforts to quantify the effects of habitat manipulations on deer performance. During 2007 08, we published one paper from this research in the Journal of Wildlife Management (JWM 72(5):1085 1093), we had another paper accepted for publication in Journal of Wildlife Management, and we had one paper accepted for publication in Wildlife Monographs pending suitable revision. The lead principal investigator published a Dissertation to complete requirements for a Ph.D. at Colorado State University. We previously published a manuscript on the effectiveness of vaginal implant transmitters (VITs) for capturing newborn fawns from specific adult females (Bishop et al. 2007). As a follow-up to this component of our research, we worked with Advanced Telemetry Systems (ATS, Isanti, MN) to develop a VIT with modified retention wings. The modified VIT will be ready for fieldtesting in 2009. 39 �WILDLIFE RESEARCH REPORT EFFECT OF NUTRITION AND HABITAT ENHANCEMENTS ON MULE DEER RECRUITMENT AND SURVIVAL RATES CHAD J. BISHOP, GARY C. WHITE, DAVID J. FREDDY, AND BRUCE E. WATKINS P. N. OBJECTIVE To determine experimentally whether enhancing mule deer nutrition during winter and early spring via supplementation increases fetal survival, neonatal survival, overwinter fawn survival, or ultimately, population productivity. SEGMENT OBJECTIVES 1. Publish manuscripts in peer-reviewed scientific journals. 2. Publish dissertation as part of Ph.D. requirements at Colorado State University INTRODUCTION Mule deer (Odocoileus hemionus) numbers apparently declined during the 1990s throughout much of the West, and have clearly decreased since the peak population levels documented during the 1940s 1960s (Unsworth et al. 1999, Gill et al. 2001). Biologists and sportsmen alike have concerns as to what factors may be responsible for declining population trends. Although previous and current research indicates multiple interacting factors are responsible, habitat and predation have typically received the focus of attention. A number of studies have evaluated whether predator control increases deer survival, yet results are highly variable (Connolly 1981, Ballard et al. 2001). Together, predator control studies with adequate rigor and statistical power indicate predation effects on mule deer are variable as a result of time-specific and site-specific factors. Studies which have demonstrated deer population responses to predator control treatments have failed to determine whether predation is ultimately more limiting than habitat when considering long term population changes. Numerous research studies have evaluated mule deer habitat quality, but virtually no studies have documented population responses to habitat improvements. In many areas where declining deer numbers are of concern, predation is common yet habitat quality appears to have declined. The question remains as to whether predation, habitat, or some other factor is more limiting to mule deer in these situations, and whether habitat quality can be improved for the benefit of deer. It may also be that no single factor is responsible for observed deer declines, and a more comprehensive understanding of multi-factor interactions is needed. We designed and implemented a field experiment where we measured deer population responses to a nutrition enhancement treatment to further understand the causative factors underlying observed deer population dynamics. We conducted the study on the Uncompahgre Plateau in southwest Colorado, where several predator species were present in abundant numbers: coyotes (Canis latrans), mountain lions (Felis concolor), and bears (Ursus americanus). In addition to predation, myriad diseases in combination have proximately affected survival of the Uncompahgre deer population (Pojar and Bowden 2004, B. E. Watkins, Colorado Division of Wildlife, unpublished data). Predator numbers were not manipulated in any manner during the course of the study. All factors were left constant with the exception of deer nutrition. Deer nutrition was enhanced by providing supplemental feed to deer occupying a treatment area during winter. We measured December fawn recruitment and overwinter fawn survival in response to the treatment to determine whether deer nutrition was ultimately more limiting 40 �than predation or disease. A second phase of research was initiated in 2005 to quantify deer population parameters in response to manipulations of pinyon-juniper (Pinus edulis-Juniperus osteosperma) habitat (Bergman et al. 2007). The objective of this research is to determine whether habitat can be effectively improved for mule deer by introducing disturbance into late-seral pinyon-juniper stands. STUDY AREA We non-randomly selected two experimental units (A B) within mule deer winter range on the Uncompahgre Plateau (Figure 1) to facilitate a cross-over experimental design for evaluating the effects of enhanced deer nutrition during winter on annual population performance. Unit A received a nutrition enhancement treatment during the first 2 winters of research (2000 – 2002) while Unit B served as a control unit. During winters 2002 03 and 2003 04, Unit B received the treatment while Unit A served as the control. In late April and May, prior to fawning, deer from the winter range experimental units migrated to summer range. We defined the summer range study area by movements of the radio-collared deer captured on winter range; summer range encompassed >1000 mi2 covering the southern portion of the Uncompahgre Plateau and adjacent San Juan Mountains (Figure 2). Winter range elevations ranged from 1830 m (6000 ft) in Shavano Valley to 2318 m (7600 ft) adjacent to the Dry Creek Rim above Shavano Valley. Winter range habitat was dominated by pinyon-juniper with interspersed sagebrush adjacent to agricultural fields in the Shavano and Uncompahgre Valleys. Summer range elevations occupied by deer ranged from 1891 m (6200 ft) in the Uncompahgre Valley to 3538 m (11,600 ft) in Imogene Basin southwest of Ouray, CO. Summer range habitats were dominated by spruce-subalpine fir (Picea spp.-Abies lasiocarpa), aspen (Populus tremuloides), sagebrush, ponderosa pine (Pinus ponderosa), Gambel oak (Quercus gambelii), and to a lesser extent, pinyon-juniper at lower elevations. Bishop et al. (2005) provide a detailed study area description. METHODS Refer to Bishop et al. (2005) or Bishop (2007) for field methodology employed during 2000 2005. During fiscal year 2007 08, we had 1 paper published and 2 papers accepted for publication in peer-reviewed scientific journals. Thus, our primary research efforts were focused on preparation of manuscripts for publication. We completed and published a paper in Journal of Wildlife Management focused on mule deer sibling dependence in context of fetal and neonatal survival analyses. In this paper, we also presented a likelihood function for estimating fetal survival when the fates of some fetuses are unknown. We spent much of the year preparing and submitting a manuscript to Wildlife Monographs. This particular publication documents the effect of enhanced nutrition on all aspects of mule deer productivity, survival, and population rate of change. Finally, we prepared and submitted a manuscript documenting the utility of serum thyroid hormone concentrations for evaluating mule deer body condition in late winter with this manuscript accepted for publication following two substantive revisions. The principal investigator also published his Ph.D. dissertation. A component of this project was an evaluation of vaginal implant transmitters (VITs) as a tool for locating neonatal mule deer fawns from targeted adult females (Bishop et al. 2007). To build on this research, we worked with Advanced Telemetry Systems (ATS, Isanti, MN) to develop a VIT with modified retention wings during 2007 08. We intend to evaluate the modified VIT in conjunction with ongoing mule deer energy development research in northwest Colorado. RESULTS AND DISCUSSION A comprehensive presentation and discussion of all results from this study is provided by Bishop (2007) and is not repeated here. These results and conclusions are being systematically published in peer- 41 �reviewed journals. The following manuscripts were published in 2007 and 2008 (abstracts are provided in Appendix I): Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945 954. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085 1093. Schultheiss, P. C., H. Van Campen, T. R. Spraker, C. J. Bishop, L. L. Wolfe, and B. Podell. 2007. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer in Colorado. Journal of Wildlife Diseases 43:533 537. The following manuscripts were accepted for publication in 2008 and will most likely be published in 2009 (abstracts are provided in Appendix II): Bishop, C. J., B. E. Watkins, L. L. Wolfe, D. J. Freddy, and G. C. White. 2009. Evaluating mule deer body condition using serum thyroid hormone concentrations. Journal of Wildlife Management: In press. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs: in review. (Manuscript has been tentatively accepted pending suitable revision). We intend to pursue several additional manuscripts as time allows, listed below in order of priority. 1. Evaluating dependence of fates among mule deer siblings in Colorado, Idaho, and Montana. Journal of Wildlife Management. 2. Bovine viral diarrhea isolation and seroprevalence in a free-ranging mule deer (Odocoileus hemionus) population in southwest Colorado. Journal of Wildlife Diseases. 3. Spatial patterns in mortality causes of neonatal mule deer across a land use gradient in southwest Colorado. Journal of Wildlife Management. 4. Evaluation of mule deer age and sex ratios as a response variable in field research. Journal of Wildlife Management. SUMMARY Enhanced winter nutrition of free-ranging deer caused an increase in both fetus-neonate survival and overwinter fawn survival, resulting in higher yearling recruitment. Overwinter adult female survival increased as a result of the nutrition treatment, and therefore annual survival was higher among treatment than control adult females. Combining all parameter estimates into a deterministic population model, the treatment population indicated an exceptionally high rate of increase while the control population was stable and indicative of the overall Uncompahgre deer population during 2000 2004. The nutrition enhancement treatment was artificial in the sense that we applied it only to test whether habitat quality was ultimately more limiting than predation or other factors. Our results to do not provide support for managing deer populations with nutrition supplements because our treatment delivery approach could not 42 �be applied to a large number of animals over a large area. Rather, our results provide a foundation for focusing deer management efforts on improving habitat quality in western Colorado pinyon-juniper ecosystems with corresponding research efforts to quantify the effects of habitat manipulations on deer. LITERATURE CITED Ballard, W. B., D. Lutz, T. W. Keegan, L. H. Carpenter, and J. C. DeVos, Jr. 2001. Deer-predator relationships: a review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin 29:99 115. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2007. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report July: 73-96. Colorado Division of Wildlife, Fort Collins, USA. Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945 954. Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2005. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Wildlife Research Report July: 3766. Colorado Division of Wildlife, Fort Collins, USA. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245 285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. Gill, R. B., T. D. I. Beck, C. J. Bishop, D. J. Freddy, N. T. Hobbs, R. H. Kahn, M. W. Miller, T. M. Pojar, And G. C. White. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Fort Collins, USA. Pojar, T. M., And D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550 560. Unsworth, J. W., D. F. Pac, G. C. White, And R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315 326. Prepared by _______________________ Chad J. Bishop, Wildlife Researcher 43 �Year Unit A Unit B 2000-01 Treatment Control 2001-02 Treatment Control 2002-03 Control Treatment 2003-04 Control Treatment Figure 1. Schematic representation of experimental units and nutrition enhancement treatment allocation. Units A and B were located in winter range habitat on the Uncompahgre Plateau in southwest Colorado. The nutrition enhancement cross-over design encompassed 4 years. Uncompahgre Plateau Mesa County GRAND JUNCTION Delta County U nc GMU 62 Gunnison County DELTA Winter Range Exp. Units om pa hg re ea at Pl GMU 61 u Montrose County Sanmiguel County Shavano E.U. MONTROSE Colona Montrose County Summer Range E.U. Ouray County Figure 2. Location of Colona and Shavano (Units A and B) experimental units on the Uncompahgre Plateau, southwest Colorado; and location of the summer range study area encompassing the southern Uncompahgre Plateau and adjacent San Juan Mountains. 44 �APPENDIX I – PUBLISHED PROJECT PAPERS The following Colorado State University dissertation (referenced here by Abstract) was published in 2007. EFFECT OF ENHANCED NUTRITION DURING WINTER ON THE UNCOMPAHGRE PLATEAU MULE DEER POPULATION CHAD J. BISHOP ABSTRACT Mule deer (Odocoileus hemionus) populations declined across much of the West during the 1990s, prompting state wildlife agencies to explore mule deer limiting factors. The greatest concern of agencies and sportsmen was whether declining habitat quality, predation, or both were responsible for the observed declines. In Colorado, the Uncompahgre Plateau mule deer population received the most attention because of a steep population decline from the 1980s through the late 1990s. Biologists hypothesized that poor quality of the pinyon (Pinus edulis) and juniper (Juniperus osteosperma) winter range was the primary cause of the observed decline. In contrast, many of the Colorado Division of Wildlife‘s (CDOW) constituents hypothesized that high predation rates were keeping the mule deer herd below nutritional carrying capacity. These hypotheses represented very different paradigms of population limitation. Perhaps more importantly, the competing views suggested that CDOW should pursue one of two very different management strategies: 1) implement habitat improvements in the pinyon-juniper winter range, or 2) implement efforts to reduce predator populations, particularly coyote (Canis latrans) populations. Information was needed to guide the decision process. I therefore evaluated the effect of enhanced nutrition during winter on the Uncompahgre deer population as a way to evaluate the importance of habitat quality versus that of predation. I conducted a field study incorporating a crossover experimental design to quantify the effect of enhanced nutrition on fetal, neonatal, overwinter fawn, and annual adult doe survival rates. I captured and radio-collared samples of deer in 2 experimental units (EUs) on winter range. I delivered the nutrition treatment to deer occupying one EU (treatment) and did not administer the treatment to deer in the other EU (control). Established field techniques were not sufficient to allow me to quantify the effect of the treatment on fetal and neonatal survival. I therefore pursued an exploration of vaginal implant transmitters as a mechanism to capture necessary samples of newborn fawns on summer range exclusively from radio-collared does that occupied the winter range EUs (Chapter 1). This effort allowed me to estimate fetal and neonatal survival as a function of the treatment. In broad terms, I demonstrated that direct estimates of fetal and neonatal survival may be obtained from previously marked female mule deer in free-ranging populations, thus expanding opportunities for conducting field experiments. I encountered additional challenges with estimation of fetal and neonatal survival. First, I was unable to determine the fate of all fetuses that I documented in utero. I therefore developed a likelihood function for estimating fetal survival when the fates of some fetuses are unknown (Chapter 2). Second, a majority of my fetal and neonatal samples were comprised of siblings, indicating my data were potentially overdispersed. Overdispersion causes sample variances to be underestimated and requires a variance inflation factor, c. To estimate c, I compared theoretical variance estimates with empirical variance estimates obtained from bootstrap analyses of the data (Chapter 2). I found little evidence of overdispersion in my fetal survival data, and I found modest overdispersion in my neonatal sample data (ĉ = 1.25). Although some overdispersion was detected, my results indicated that fates of sibling mule deer neonates may often be independent even though they have the same dam and use the environment similarly. I discuss reasons for this in Chapter 2. 45 �After resolving issues with fetal and neonatal survival estimation, I quantified the effect of the nutrition enhancement treatment on fetal, neonatal, overwinter fawn, and annual adult doe survival (Chapter 3). I then used these parameter estimates, along with estimated fecundity rates, in an agestructured, deterministic population model to estimate the effect of the treatment on the population rate of change, ˆ . The treatment caused ˆ to increase by an average of 0.133 (SD = 0.0168) during the 3 years of my study. I documented density dependence in the Uncompahgre deer population because survival of fawns and does increased considerably in response to enhanced nutrition. I found strong evidence that coyote predation of ≥6-month-old fawns and adult does was compensatory. Finally, I found that winter range habitat quality was a limiting factor of the Uncompahgre Plateau deer population. I completed my principal study objectives in the first 3 chapters of the dissertation. However, my research afforded the opportunity to evaluate the utility of serum thyroid hormones in mule deer as an index to body condition (Chapter 4). Concentrations of total thyroxine (T4) and free T4 (FT4) were substantially higher in treatment deer than control deer. I also found that serum thyroid hormones were highly correlated with estimated body fat in mule deer during late winter. Concentrations of T4 and FT4 could be useful for evaluating relative condition of different deer groups or populations, and for roughly estimating body fat of individual animals during late winter. In summary, I demonstrated that winter range habitat quality was ultimately limiting the Uncompahgre mule deer population. Observed predation was primarily compensatory, particularly of ≥6month-old fawns and adult does. My findings indicate that CDOW should evaluate habitat treatments in late-seral pinyon-juniper habitat as a means to increase habitat productivity for mule deer. Citation: Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. 46 �The following manuscript (referenced here by Abstract) was published in the Journal of Wildlife Management in 2007. USING VAGINAL IMPLANT TRANSMITTERS TO AID IN CAPTURE OF MULE DEER NEONATES CHAD J. BISHOP, DAVID J. FREDDY, GARY C. WHITE, BRUCE E. WATKINS, THOMAS R. STEPHENSON, AND LISA L. WOLFE ABSTRACT Estimating survival of the offspring of marked female ungulates has proven difficult in freeranging populations yet could improve our understanding of factors that limit populations. We evaluated the feasibility and efficiency of capturing large samples (i.e., >80/year) of neonate mule deer (Odocoileus hemionus) exclusively from free-ranging, marked adult does using vaginal implant transmitters (VITs, n = 154) and repeated locations of radio-collared does without VITs. We also evaluated the effectiveness of VITs, when used in conjunction with in utero fetal counts, for obtaining direct estimates of fetal survival. During 2003 and 2004, after we placed VIT batteries on a 12-hour duty cycle to lower electronic failure rates, the proportion that shed 3 days prepartum or during parturition was 0.623 (SE = 0.0456), and the proportion of VITs shed only during parturition was 0.447 (SE = 0.0468). Our neonate capture success rate was 0.880 (SE = 0.0359) from does with VITs shed 3 days prepartum or during parturition and 0.307 (SE = 0.0235) from radio-collared does without VITs or whose implants failed to function properly. Using a combination of techniques, we captured 275 neonates and found 21 stillborns during 2002 2004. We accounted for all fetuses at birth (i.e., live or stillborn) from 78 of the 147 does (0.531, SE = 0.0413) having winter fetal counts, and this rate was heavily dependent on VIT retention success. Deer that shed VITs prepartum were larger than deer that retained VITs to parturition, indicating a need to develop variable-sized VITs that may be fitted individually to deer in the field. We demonstrated that direct estimates of fetal and neonatal survival may be obtained from previously marked female mule deer in free-ranging populations, thus expanding opportunities for conducting field experiments. Survival estimates using VITs lacked bias that is typically associated with other neonate capture techniques. However, current vaginal implant failure rates, and overall expense, limit broad applicability of the technique. Citation: Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945 954. 47 �The following manuscript (referenced here by Abstract) was published in the Journal of Wildlife Management in 2008. EVALUATING DEPENDENCE AMONG MULE DEER SIBLINGS IN FETAL AND NEONATAL SURVIVAL ANALYSES CHAD J. BISHOP, GARY C. WHITE, AND PAUL M. LUKACS ABSTRACT The assumption of independent sample units is potentially violated in survival analyses where siblings comprise a high proportion of the sample. Violation of the independence assumption causes sample data to be overdispersed relative to a binomial model, which leads to underestimates of sampling variances. A variance inflation factor, c, is therefore required to obtain appropriate estimates of variances. We evaluated overdispersion in fetal and neonatal mule deer (Odocoileus hemionus) datasets where more than half of the sample units were comprised of siblings. We developed a likelihood function for estimating fetal survival when the fates of some fetuses are unknown, and we used several variations of the binomial model to estimate neonatal survival. We compared theoretical variance estimates obtained from these analyses with empirical variance estimates obtained from data bootstrap analyses to estimate the overdisperion parameter, c. Our estimates of c for fetal survival ranged from 0.678 to 1.118, which indicate little to no evidence of overdispersion. For neonatal survival, 3 different models indicated that ĉ ranged from 1.1 to 1.4 and averaged 1.24 1.26, providing evidence of limited overdispersion (i.e., limited sibling dependence). Our results indicate that fates of sibling mule deer fetuses and neonates may often be independent even though they have the same dam. Predation tends to act independently on sibling neonates because of dam-neonate behavioral adaptations. The effect of maternal characteristics on sibling fate dependence is less straightforward and may vary by circumstance. We recommend that future neonatal survival studies incorporate additional sampling intensity to accommodate modest overdispersion (i.e., ĉ = 1.25), which would facilitate a corresponding ĉ adjustment in a model selection analysis using quasi-likelihood without a reduction in power. Our computational approach could be used to evaluate sample unit dependence in other studies where fates of individually marked siblings are monitored. Citation: Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085 1093. 48 �The following manuscript (referenced here by Abstract) was published in the Journal of Wildlife Diseases in 2007: MALIGNANT CATARRHAL FEVER ASSOCIATED WITH OVINE HERPESVIRUS-2 IN FREE-RANGING MULE DEER IN COLORADO PATRICIA C. SCHULTHEISS, HANA VAN CAMPEN, TERRY R. SPRAKER, CHAD J. BISHOP, LISA L. WOLFE, AND BRENDAN PODELL ABSTRACT Malignant catarrhal fever (MCF) was diagnosed in 4 free-ranging mule deer (Odocoileus hemionus) in January and February of 2003. Diagnosis was based on typical histologic lesions of lymphocytic vasculitis and PCR identification of ovine herpesvirus-2 (OHV-2) viral genetic sequences in formalin fixed tissues. The animals were from the Uncompahgre Plateau of southwestern Colorado. Deer from these herds occasionally resided in close proximity to domestic sheep (Ovis aries), the reservoir host of OHV-2, in agricultural valleys adjacent to their winter range. These cases indicate that fatal OHV-2 associated MCF can occur in free-ranging mule deer exposed to domestic sheep that overlap their range. Citation: Schultheiss, P. C., H. Van Campen, T. R. Spraker, C. J. Bishop, L. L. Wolfe, and B. Podell. 2007. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer in Colorado. Journal of Wildlife Diseases 43:533 537. 49 �APPENDIX II PROJECT PAPERS ACCEPTED FOR PUBLICATION The following manuscript (referenced here by Abstract) was accepted for publication by the Journal of Wildlife Management during 2008 but has not yet been published. EVALUATING MULE DEER BODY CONDITION USING SERUM THYROID HORMONE CONCENTRATIONS CHAD J. BISHOP, BRUCE E. WATKINS, LISA L. WOLFE, D. J. FREDDY, AND GARY C. WHITE ABSTRACT Body condition of ungulates is a determinant of fecundity and survival rates. Ultrasonography and body condition scoring techniques allow reliable estimation of body fat but may not be feasible to employ in some circumstances. A reliable blood chemistry index for assessing relative condition of different ungulate populations or groups would be useful in ongoing population monitoring programs. We provided a nutrition supplement (treatment) to a group of free-ranging mule deer (Odocoileus hemionus) during 2 consecutive winters in southwest Colorado. In late February each year, we evaluated whether percent body fat and serum concentrations of total thyroxine (T4), total triiodothyronine (T3), free T4 (FT4), and free T3 (FT3) were higher among treatment deer than an adjacent group of deer that did not receive the treatment (control). As a corroborative analysis, we modeled body fat as a function of thyroid hormone concentrations and morphometric variables. Estimated body fat of treatment deer averaged 12.3% (SE = 0.327), whereas estimated body fat of control deer averaged 7.0% (SE = 0.333), during the 2 winters of study. Concentrations of T4 and FT4 averaged 48.07 nmol/l (SE = 3.80) and 12.61 pmol/l (SE = 1.04) higher, respectively, in treatment deer than control deer. Our optimal model of estimated body fat included T4, T42, FT4, and deer chest girth (%Fât = –4.8015 – 0.0946 T4 + 0.000603 T42 + 0.1474 FT4 + 0.1426 chest girth, R2 = 0.609). Serum thyroid hormones effectively discerned treatment deer from control deer and were related to estimated body fat. Ultrasound and body condition scoring should be used to estimate body fat whenever possible. However, in cases where only a blood sample can be obtained, we documented potential utility of T4 and FT4 during late winter for evaluating relative body condition of mule deer. 50 �The following manuscript (referenced here by Abstract) was tentatively accepted for publication by Wildlife Monographs during 2008 and is still in the revision stage. EFFECT OF ENHANCED NUTRITION ON MULE DEER POPULATION RATE OF CHANGE CHAD J. BISHOP, GARY C. WHITE, DAVID J. FREDDY, BRUCE E. WATKINS, AND THOMAS R. STEPHENSON ABSTRACT Concerns over declining mule deer (Odocoileus hemionus) populations during the 1990s prompted research efforts to identify and understand key limiting factors of deer. Similar to past deer decline incidents, a top priority of state wildlife agencies was to evaluate the relative importance of habitat and predation. We therefore evaluated the effect of enhanced nutrition of deer during winter and spring on fecundity and survival rates using a life table response experiment involving free-ranging mule deer on the Uncompahgre Plateau in southwest Colorado. The nutrition enhancement treatment represented an instantaneous increase in nutritional carrying capacity of a pinyon (Pinus edulis) and Utah juniper (Juniperus osteosperma) winter range, and was intended to simulate optimum habitat quality. Prior studies on the Uncompahgre Plateau indicated predation and disease were the most common proximate causes of deer mortality. By manipulating nutrition and leaving natural predation unaltered, we determined whether habitat quality was ultimately a critical factor limiting the deer population. We measured fetal, neonatal, and overwinter fawn survival, and annual adult female survival, which we then used to estimate population rate of change as a function of enhanced nutrition. Pregnancy and fetal rates were high for all deer, regardless of the nutrition treatment. Fetal and neonatal survival rates were higher among deer that received the nutrition enhancement treatment than deer that served as experimental controls. Overwinter fawn survival increased for treatment deer by 0.16 0.31 depending on year and fawn sex, and none of the 95% confidence intervals associated with the effect overlapped 0. Nutrition enhancement increased survival of fetuses to the yearling age class by 0.14 0.20 depending on year and fawn sex, although 95% confidence intervals slightly overlapped 0. Annual survival of adult females receiving the treatment (Ŝ = 0.879, SE = 0.0206) was higher than survival of control adult females (Ŝ = 0.833, SE = 0.0253). Our estimate of the population rate of change, ˆ , was 1.165 (SE = 0.0358) for treatment deer and 1.033 (SE = 0.0380) for control deer. The nutrition treatment caused ˆ to increase by 0.133 (SE = 0.0428). We documented density dependence in the Uncompahgre deer population because survival of fawns and adult females increased considerably in response to enhanced nutrition. We found strong evidence that coyote (Canis latrans) predation of ≥6-month-old fawns and adult females was compensatory. Our results demonstrate that observed coyote predation, by itself, is not useful for evaluating whether coyotes are negatively impacting a deer population. We also found evidence that mountain lion (Puma concolor) predation was compensatory. Disease mortality was not compensatory among adult females. We found that winter range habitat quality was a limiting factor of the Uncompahgre Plateau mule deer population. Therefore, we recommend evaluating habitat treatments for deer that are designed to set-back succession and increase productivity of late-seral pinyon-juniper habitats that presently dominate the winter range. 51 �52 �Colorado Division of Wildlife July 2007 – June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 2 Federal Aid Project No. W-185-R : : : : Division of Wildlife Mammals Research Deer Conservation Evaluation of Winter Range Habitat Treatments On Over-winter Survival and Body Condition of Mule Deer Period Covered: July 1, 2007 - June 30, 2008 Author: E.J. Bergman; project cooperators, C.J. Bishop, D.J. Freddy and G.C. White Personnel: C. Anderson, L. Baeten, D. Baker, B. Banulis, J. Boss, A. Cline, D. Coven, M. Cowardin, K. Crane, R. Del Piccolo, B. deVergie, B. Diamond, K. Duckett, S. Duckett, J. Garner, D. Hale, C. Harty, A. Holland, E. Joyce, D. Kowalski, B. Lamont, R. Lockwood, S. Lockwood, D. Lucchesi, D. Masden, J. McMillan, M. Michaels, G. Miller, Mike Miller, Melody Miller, M. Sirochman, T. Sirochman, M. Stenson, R. Swygman, C. Tucker, D. Walsh, S. Waters, B. Watkins, P. Will, L. Wolfe, V. Yavovich, K. Yeager, M. Zeaman CDOW, L. Carpenter - Wildlife Management Institute, D. Felix, L. Felix - Olathe Spray Service, P. Johnston, M. Keech, R. Swisher, S. Swisher - Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We completed the third year of a multi-year, multi-area study to assess the impacts of landscape level winter range habitat improvement efforts on mule deer population performance. This study is occurring on the Uncompahgre Plateau and in adjacent valleys in southwestern Colorado. Data collection and analysis for this third year were consistent with that of the pilot study and first two years of the study. We measured over-winter fawn survival and total deer density on 4 annual study areas, as well as on a fifth variable area that had previously not been involved in the study. Additionally, on 2 of the study areas we estimated body condition of does. Compared to results from other research throughout the west, as well as on the Uncompahgre Plateau, survival estimates for 6-month old mule deer fawns were highly variable between areas, but tended to be above published long term averages (mean survival rate of 0.63 (0.04 SE)). However, survival rates for the third year of the study were lower than all previous years, which were consistent with observed patterns throughout the state, likely stemming from harsher winter conditions. Preliminary evidence continues to suggest that areas that have received habitat treatments have higher fawn survival. However, based on estimates of total body fat for adult female deer, there was no apparent distinction between treatment and reference study areas. Point estimates of deer density on the 5 study areas during the winter of 2007-2008 varied from estimates colleted during the winters of 2005-2006 and 2006-2007. However, general mule deer density estimates have followed a consistent trend between all winters of the study with no major annual change observed. 53 �WILDLIFE RESEARCH REPORT EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER ERIC J. BERGMAN P.N. OBJECTIVE To experimentally assess whether mechanical/chemical treatments of native habitat vegetation will increase over-winter mule deer fawn survival, adult doe body condition, and localized deer densities on the Uncompahgre Plateau in southwest Colorado. SEGMENT OBJECTIVES 1. Capture and radio-collar the minimum necessary sample (n=25) of 6 month-old fawns between November and early-January in each of 5 study areas. 2. Measure over-winter fawn survival from mid-December through mid-June. 3. Estimate late-winter deer densities in each study area via helicopter resighting of marked deer. 4. Capture and sample a minimum number of adult female deer (n=30) to estimate late-winter body condition in 2 study areas. INTRODUCTION A common trend among many terrestrial, mammalian systems is a tendency to cycle between population highs and lows (Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001, Clutton-Brock and Pemberton 2004). While the true cause of these cycles is likely a merger of habitat quality, weather, disease, predation, sport hunting, competition and community population dynamics, it is often necessary or intriguing for wildlife managers and ecologists to identify the primary limiting factor to population growth. Without exception, mule deer populations have also demonstrated a tendency to show large fluctuations. Several dramatic declines have been observed since the turn of the 19th century (Connolly 1981, Gill 2001, Hurley and Zager 2004). However, only one period of increase, a general trend during the 1940's and 1950's, has been noted. The most recent and pressing decline took place during the 1990's (Unsworth et al. 1999). Colorado has not escaped these tendencies, with certain parts of the state experiencing population declines by as much as 50% between the 1960's and present time (Gill 2001, B. Watkins personal communication). Primarily due to the value of mule deer as a big game hunting species, wildlife managers' challenges are two-fold: understanding the underlying causes of mule deer population change and managing populations to dampen the effects of these fluctuations. In Colorado, the role of habitat as the limiting factor for mule deer populations was recently tested. Specifically, the role of forage quality and quantity on over-winter fawn survival was tested using a treatment/reference cross-over design with ad libitum pelleted food supplements as a substitute for instantaneous high quality habitat improvements (Bishop 2007). The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e. if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the primary limiting factor on populations. As such, preliminary evidence suggests that nutrition enhancement treatments increased fawn survival by as much as 20% (C.J. Bishop, personal communication). This research effectively identified some of the underlying processes in mule deer population regulation, but did not test the effectiveness of acceptable habitat management techniques. Due to the undesirable effects of feeding wildlife (e.g. artificially elevating density, increased 54 �potential for disease transmission and cost), a more appropriate technique for achieving a high quality nutrition enhancement needs to be assessed. Based on this past research and the above mentioned objectives, we designed and initiated a multi-year, multi-area study to assess the impacts of landscape level winter range treatments on mule deer population performance. This study is being conducted on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado. Due to the active habitat treatment history in this area, the Uncompahgre Plateau stood out as the most opportune place for addressing these issues. Additionally, there are several tracts from 2 state wildlife areas that are located in key locations, thereby allowing additional habitat treatments to occur on the level and schedule necessary of this project. To assess the impacts of habitat treatments on mule deer in these areas, we are measuring over-winter fawn survival, mule deer density and late winter body condition. In addition to the above mentioned objectives, the opportunity to explore deer/elk interactions, as well as predator-prey dynamics is available in our study areas. As part of a pilot study to assess these interactions, we distributed elk GPS collars across the south end of the Uncompahgre Plateau where the density of radio-marked deer and mountain lions is highest (Alldredge et al. 2008). Preliminary data will give basic information regarding elk distribution throughout the year, which can then be compared to similar data for deer and the spatial distribution of mountain lion kill sites. STUDY AREA At the onset of this study (Bergman et al. 2005), we identified 2 pairs of treatment/reference study areas, stratified into historically known high and low deer density areas. The selection process for these pairs of experimental units followed several strict guidelines: 1) Treatment/reference units could not be further than 10km apart, but needed to have adequate buffer to minimize the movement of animals between the treatment and reference areas. 2) Reference study areas could not have received any mechanical treatment during the past 30 years. 3) Strata were defined by winter range type (all experimental units had to be in pinyon/juniper winter range) and deer density. 4) Treatment units needed to have received mechanical treatment in the past, but also had to be capable of receiving further treatments during the study period. Each winter a 5th study area is added to increase the level of inference that can be drawn from this study. For each of the 4 winters that will cover the study period, this 5th study area shifts between 4 randomly selected areas. The treatment history on each of these additional study areas varies, but is representative of what can be expected of typical winter-range treatments. During the second winter of this study, this 5th study area fell on the Colona Tract (~5km2) of Billy Creek State Wildlife Area (approximately 15km south of Montrose, CO). The treatment history of Colona Tract is primarily composed of brush mowing and chemical control of weeds and dry land fertilization of preferred species. The high density treatment area is located on the Billy Creek tract of Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). The high density reference area is located around Beaton Creek (approximately 15km south of Montrose, CO and approximately 5km north of Billy Creek State Wildlife Area). Both of the high density study areas are located in GMU 65 (DAU D-40). The low density treatment area is located on Peach Orchard Point, on/near Escalante State Wildlife Area (approximately 25km southwest of Delta, CO). The low density reference area is located on Sowbelly and Tatum draws (approximately 25km west of Delta, CO and approximately 8km from Peach Orchard Point). Both of the low density study areas are located in GMU 62 (DAU D-19). Shavano Valley was also located in GMU 62 (DAU D-19) to the west of Montrose, CO. 55 �METHODS Twenty-five mule deer fawns were captured and radio-collared in each of the 5 study areas. Fawns were captured via baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) and helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) between mid-November and lateDecember. Ten adult female elk were captured via helicopter net-gunning during this same period. Fawns were fitted with radio collars made of vinyl belting and equipped with mortality sensors, which after remaining motionless for 4 hours, increase the pulse rate of received signals. To make fawn collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars after approximately 6 months. Elk were collared with either permanent VHF collars or temporary GPS collars that were fitted with timed blow-off devices. On a daily basis, from December through May, we monitored the radioed fawns in order to document live/death status. This allowed us to determine accurately the date of death and estimate the proximate cause of death. Daily monitoring was done from the ground to maximize efficient collection of mortalities and assessment of cause specific mortality. Weekly aerial telemetry flights were conducted to insure that all deer were heard at least once a week, allowing weekly survival estimates for each study area. Additionally, throughout the winter field season and as part of a related pilot field study, investigations of mountain lion GPS clusters were conducted (see Alldredge et al. 2008). To estimate body composition, an additional 30 adult female deer were captured via helicopter net-gunning and fitted with temporary radio-collars, also having mortality sensors, in late-February within each of the 2 high density study areas. For body condition work, we relied on methods that employed the use of ultrasonography to estimate total body fat (Stephenson et al. 1998, Cook 2000, Stephenson et al. 2002). Blood samples were also collected for endocrinology and pregnancy tests. During late winter (early-March) we estimated deer density on each of our study areas. Helicopter based mark-resight techniques were used for density estimation (Gill 1969, Bartmann et al. 1986, Kufeld et al. 1980, Freddy et al. 2004). Preliminary survival analyses were conducted on the first two years of data. In addition to including individual covariates (fawn sex and mass), we explored the role of habitat treatment history on survival. Due to the preliminary nature of these analyses and the ongoing status of the habitat treatment work, we did not attempt to rank individual study areas. Rather, our analyses were conducted such that areas were included and compared using three different approaches. With the first approach, areas were included individually and a unique survival rate was calculated for each area. The second approach allowed for 3 levels of habitat treatment intensity (untreated, single treatment or ongoing treatments). The final approach did not attempt to segregate treated areas by treatment history. Rather, any area with any treatment history was treated similarly, resulting in a unique survival rates being calculated for untreated (reference) areas and a different, unique survival rate being calculated for all other areas. All survival models were conducted in program MARK (White and Burnham 1999). Known-fate models were tested using the logit link function. All models are compared using Akaike's Information Criterion corrected for small sample size (Burnham and Anderson 2003). RESULTS AND DISCUSSION With the exception of one study area, minimum desired sample sizes were met in all study areas for all components of this research (n = 25 fawns per area for survival work, n = 30 adult females in two 56 �areas for body condition assessment). Minimum desired sample size for fawn survival was not met in one study area (McKenzie Buttes) due to radio-collar failure. Capture related mortalities occurred on 2 of 183 occasions (1.01%, 2 adult females). Four fawns died of unknown causes within 1week of capture and were censored from the survival analysis. Mean mass of all fawns was 35.8 kg and the observed sex ratio for the sample was 54 males to 68 females (Table. 1). The sex of one fawn was inadvertently not recorded. Estimates of fawn survival collected during this study have been above average compared to results from other research throughout the west, as well as on the Uncompahgre Plateau. Across our 5 study areas, estimated survival rates ranged between 0.36 (0.13 SE) and 0.79 (0.08 SE), with a mean survival rate of 0.63 (0.04 SE) (Table 2). While these rates are lower than those measured during previous winters, they remain higher than long term averages reported in the literature (Unsworth et al. 1999). Of note, winter conditions across the state of Colorado were harsher than those observed over the past decade and survival rates are expected to have been negatively affected throughout the state. During the previous years of this study, survival rates in our low-density study areas have been higher than expected. While rates in those areas continued to be higher than those observed in our high-density areas, they also appeared to have been negatively affected by harsher winter conditions. Preliminary survival models indicate that the individual parameter most influencing over-winter fawn survival continues to be fawn mass (Table 3). Fawn sex did not appear to add much additional strength or support to any given model. Of particular interest to this study is that models incorporating study area treatment level were among the top performing models for the entire suite of models run. However, the most supported model did not take treatment history into account. At this time, we speculate that deviation from the previous year‘s best performing model is primarily driven by a single study area (McKenzie Butte) where observed survival rates were quite low, despite being classified as a treatment area. The average elevation for this particular study area was higher than that of nearby study areas, likely exacerbating that harsher winter conditions observed across all areas. When run with a yearly effect, survival models were not improved and consistently under-performed less complex models. The variable nature of model results between years highlights the preliminary nature of these analyses and is ultimately linked to not having collected all of the necessary data. As the study progresses and more study areas are included, a treatment intensity effect is likely to be detected if it exists. Late winter body condition estimates for adult females during the winter of 2007-2008 were again higher than those collected during previous winters on the Uncompahgre Plateau (Bishop 2007 and C.J. Bishop, personal communication). In light of the harsher winter that was observed this past year, this result was counter intuitive. While point estimates of total percent body fat were higher in the treatment area (Billy Creek) than in the reference area (Buckhorn), there was no apparent statistical distinction between our study areas. This lack of distinction was also observed in the levels of the T3 hormone, but not in the T4 hormone (nmol/l) (Table 4). Of particular note, pregnancy rates, based on PSPB, were numerically lower than those observed in earlier years. Past rates ranged between 90% and 95%, whereas rates for this past winter were 80% (Buckhorn) and 87% (Billy Creek). Of note, body condition estimates were collected in the Sowbelly study areas during the first year of the study, but were later replaced by estimates in the Buckhorn study area as estimates from Buckhorn were deemed to be a more realistic and practical comparison to those that have been continuously collected in the Billy Creek study area. Density estimates were collected during March for all five study areas (Figure 1). No major modifications were made to the methodology, although the total number of marked animals in Billy Creek and Buckhorn increased. As such, the precision of estimates for these two areas improved. No major shifts in deer density were observed in Billy Creek, Peach Orchard or Sowbelly. The total number of deer observed and the overall estimated density for Buckhorn showed a marked increase. This shift was likely due to annual variation in deer distribution with deer having shifted down in elevation due to harsher 57 �conditions at the upper end of winter range. However, under this scenario, a similar shift in distribution would have been expected to occur in the Billy Creek study area as winter conditions between these two study areas were very similar. SUMMARY Survival rates for mule deer fawns across our study areas averaged 63% with a measured high of 79% and measured low of 36%. Overall body condition parameter estimates for late-winter adult female deer were moderate to high, which did not coincide with the harsher winter conditions that were observed throughout deer winter range in Colorado. However, pregnancy rates did appear to be lower, which may be explained by winter conditions. Evidence of higher deer survival in treatment areas was observed, but we do not have enough data to draw strong conclusions at this preliminary stage. Estimates of total deer density across our study areas continue to be in line with historical estimates. Precision of density estimates have improved with modification to techniques and additional years of data collection will be needed to determine if habitat treatment effects can potentially be detected. LITERATURE CITED Alldredge, M.W., E.J. Bergman, C.J. Bishop, K. A. Logan, and D.J. Freddy. 2008. Pilot evaluation of predator-prey dynamics on the Uncompahgre Plateau. Wildlife Research Report July:In press. Colorado Division of Wildlife, Fort Collins, USA. Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M., L.H. Carpenter, R.A. Garrott, and D.C. Bowden. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. —————, G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. Bergman, E.J., C.J. Bishop, D.J. Freddy, G.C. White. 2005. Pilot evaluation of winter range habitat treatments of mule deer fawn over-winter survival. Wildlife Research Report July: 23-35. Colorado Division of Wildlife, Fort Collins, USA. Bishop, C.J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Burnham, K.P. and D.R. Anderson. 2003. Model selection and multi-model inference. Springer, New York, USA. Clutton-Brock, T., and J. Pemberton, editors. 2004. Soay sheep: dynamics and selection in an island population. Cambridge University Press, UK. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. Cook, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain Elk. Thesis, University of Idaho, Moscow, USA. Freddy, D.J., G.C. White, M.C. Kneeland, R.H. Kahn, J.W. Unsworth, W.J. DeVergie, V.K. Graham, J.H. Ellenberger, and C.H. Wagner. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. Gill, R.B. 1969. A quadrat count system for estimating game populations. Colorado Division of Game, Fish and Parks, Game Information Leaflet 76. Fort Collins, USA. ————— 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Hurley, M., and P. Zager. 2004. Southeast mule deer ecology - Study I: Influence of predators on mule deer populations. Progress Report, Idaho Department of Fish and Game, Boise, USA. 58 �Jedrzejewska, B., and W. Jedrzejewski. 1998. Predation in Vertebrate Communities: the Białowieża Primeval Forest as a case study. Springer-Verlag, Berlin, Germany. Krebs, C.J., S. Boutin, and R. Boonstra, editors. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. Kufeld, R.C., J.H. Olterman, AND D.C. Bowden. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. Ramsey, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. Schmidt, R.L., W.H. Rutherford, and F.M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. Stephenson, T.R., V.C. Bleich, B.M. Pierce, and G.P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. ————— , T. R., K. J. Hundertmark, C. C. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717722. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G.C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Prepared by Eric J. Bergman, Wildlife Researcher 59 �Table 1. Mean mass (n) and sex of mule deer fawns captured on the Uncompahgre Plateau from lateNovember through early-January of each year, 2005-2006, 2006-2007 and 2007-2008. All fawns were captured by baited drop-nets or helicopter net-gunning. Mass is reported in kg. Area Billy Creek Buckhorn Shavano Peach Orchard Sowbelly Billy Creek Buckhorn Colona Peach Orchard Sowbelly Billy Creek Buckhorn McKenzie Peach Orchard Sowbelly Year 2005 2005 2005 2005 2005 2006 2006 2006 2006 2006 2007 2007 2007 2007 2007 Males 37.1 (14) 37.4 (11) 39.4 (11) 37.0 (11) 37.1 (16) 38.3 (12) 36.7 (10) 38.1 (12) 37.0 (13) 44.3 ( 8) 36.0 (13) 37.8 ( 6) 36.8 (15) 37.3 ( 9) 38.6 (11) Females 32.0 (11) 35.0 (15) 37.2 (14) 35.3 (14) 34.2 (9) 34.4 (12) 34.7 (15) 32.5 (12) 35.5 (12) 35.5 (15) 36.3 (12) 34.8 (18) 34.3 ( 8) 33.5 (16) 35.1 (14) Total 34.9 (25) 36.0 (26) 38.2 (25) 36.1 (25) 36.1 (25) 36.5 (25) 35.5(25) 35.4 (24) 36.3 (25) 38.7 (25) 36.1 (25) 35.5 (25) 36.0 (23) 34.9 (25) 36.7 (25) Table 2. Over-winter mule deer fawn survival rates for study areas across the Uncompahgre Plateau, for the first three winters of the study. Billy Creek, Peach Orchard, Colona, Shavano and McKenzie Buttes represent treatment areas. Buckhorn and Sowbelly are reference areas. Peach Orchard and Sowbelly are considered low-density study areas. Deer reflected by the category ‗Other‘ represent deer that were captured on transition range, with the hope that they would migrate onto the Sowbelly study area, but alternatively migrated into an area not formally designated as a study area. Area Billy Creek Buckhorn Colona Shavano McKenzie Buttes Peach Orchard Sowbelly Other 2005-2006 Ŝ (S.E.) 0.83 (0.76) 0.76 (0.88) N.A. 0.76 (0.85) N.A. 0.88 (0.65) 1.00 (0.00) 0.83 (1.08) 2006-2007 Ŝ (S.E.) 0.72 (0.09) 0.63 (0.10) 0.68 (0.09) N.A. N.A. 0.92 (0.05) 0.88 (0.07) N.A. 60 2007-2008 Ŝ (S.E.) 0.71 (0.09) 0.59 (0.10) N.A. N.A. 0.61 (0.11) 0.79 (0.08) 0.70 (0.19) 0.36 (0.13) �Table 3. Preliminary survival model results for radio collared fawns on the Uncompahgre Plateau for the winters of 2005-2006, 2006-2007 and 2007-2008. Model Area + Mass Treatment Type + Mass Area + Mass + Sex Treatment/Reference + Mass Treatment Type + Mass + Sex Treatment/Reference + Sex + Mass Area Area + Sex Treatment Type Constant Treatment Type + Sex Treatment/Reference Treatment/Reference + Sex + Mass AICc 811.953 812.781 813.926 814.576 814.619 816.276 822.177 823.065 826.542 826.768 827.363 828.525 829.661 ∆AICc 0.000 0.827 1.972 2.623 2.665 4.322 10.224 11.112 14.589 14.815 15.410 16.571 17.708 ωi 0.371 0.245 0.138 0.100 0.098 0.043 0.002 0.001 0.000 0.000 0.000 0.000 0.000 Table 4. Late-winter body condition estimates for female adult mule deer on the Uncompahgre Plateau in 2 study areas each year, 2005-2006 and 2006-2007. Sample sizes were 30 does in each area. Mean T3 and T4 samples are reported in nmol/l. Parameters marked with an asterisk designate a significant difference between areas at the 0.05 level. Year 2005-2006 2006-2007 2007-2008 Parameter % Body Fat T3* T4 % Body Fat T3 T4 % Body Fat T3 T4* Billy Creek 8.80% (2.02) 1.12 (0.28) 70.69 (20.94) 7.61% (1.94) 1.55 (0.53) 88.23 (19.53) 8.09% (1.10) 1.17 (0.28) 94.30 (20.7) 61 Buckhorn N.A. N.A. N.A. 7.03% (1.80) 1.42 (0.31) 78.07 (22.34) 7.20% (1.69) 1.17 (0.56) 56.20 (23.30) Sowbelly 9.81% (2.88) 1.41 (0.51) 79.97 (15.80) N.A. N.A. N.A. N.A. N.A. N.A. �Figure 1. Mule deer density estimates for the 4 permanent study areas. Clear boxes reflect data from the 2005-2006 winter, light grey boxes reflect data from the 2006-2007 winter and dark grey boxes reflect data from the 2007-2008 winter. Error bars represent the 95% confidence intervals for density estimates. 62 �Colorado Division of Wildlife July 2007 June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 6 Federal Aid Project No. W-185-R Period Covered: July 1, 2007 : : : : : Division of Wildlife Mammals Research Deer Conservation Population Performance of Piceance Basin Mule Deer in Response to Natural Gas Resource Extraction and Mitigation Efforts to Address Human Activity and Habitat Degradation – Stage I, Objective 5; Patterns of Mule Deer Distribution and Movements June 30, 2008 Authors: C. R. Anderson and D. J. Freddy Personnel: J. Broderick, B. deVergie, D. Finley, L. Gepfert, C. Harty, K. Kaal, L. Kelly, S. Lockwood, R. Velarde, CDOW; R. Swisher, Quicksilver Air, Inc. Project support received from Federal Aid in Wildlife Restoration, Colorado Mule Deer Association, Colorado Oil and Gas Conservation Commission, Williams Production LMT Co., EnCana Corp., and Shell Petroleum. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We propose to experimentally evaluate habitat treatments that may rehabilitate the landscape to benefit mule deer (Odocoileus hemionus) and to evaluate human-activity management alternatives to reduce the disturbance of energy development impacts on mule deer. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas within the state. Assessments of potential study areas, resource inventory maps, and tentative study plan outlines were presented to potential agency and industry cooperators. Sufficient funding was secured to initiate a pilot study allowing refinement of study area selection based on distribution of GPS collared deer, address logistics of deer captures and collaring efforts, and begin addressing one of the six proposed objectives by monitoring deer movements from GPS locations in 5 study areas representing varying levels of energy development. We attached GPS collars collecting 5 fixes/day to 75 adult female mule deer (15/study area) in January, 2008 to document deer movements and habitat use patterns among 5 deer winter ranges exposed to varying levels of energy development. Over-winter survival of adult females was 90% (64 of 71) and typical for adult female mule deer in the western US. Data analyses of mule deer habitat use patterns will begin once GPS collars are recovered in February, 2009. These data will provide deer behavior information under existing conditions and serve as pre-treatment comparisons to future 63 �conditions following habitat treatments and/or improved development practices. Additional funding has become available to initiate the full study proposal (see Appendix I) beginning November 2008, which will provide for evaluation of changes in body condition, fawn survival, and deer densities relative to improved habitat treatments and energy development practices. This project will require additional funding commitments and cooperative agreements beyond spring 2010 from private industry, the BLM, and the CDOW to assess if sustainable mule deer populations can persist within a highly disturbed landscape following implementation of beneficial habitat treatments and development practices. 64 �WILDLIFE RESEARCH REPORT POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION STAGE I, OBJECTIVE 5: PATTERNS OF MULE DEER DISTRIBUTION & MOVEMENTS CHARLES R. ANDERSON, JR. AND DAVID J. FREDDY P. N. OBJECTIVES 1. To determine experimentally whether enhancing mule deer habitat conditions on winter and/or transition range elicits behavioral responses, improves body condition, increases overwinter fawn survival, or ultimately, population density on mule deer winter ranges exposed to extensive energy development. 2. To determine experimentally to what extent modification of energy development practices enhance habitat selection, body condition, over-winter fawn survival, and winter range mule deer densities. SEGMENT OBJECTIVES 3. Assess the logistics capturing and collaring mule deer via helicopter net-gunning in 5 winter herd segments of the Piceance Basin, Colorado. 4. Improve delineation and identify degree of separation of winter range study sites based on deer distribution and movements from GPS collars collecting 5 fixes/day. 5. Monitor survival of adult female mule deer by daily ground tracking and bi-weekly aerial tracking. 6. Summarize data and present information in an annual Job Progress Report. INTRODUCTION Anderson and Freddy (2007) in their long-term research proposal identified 6 primary study objectives to assess measures to offset impacts of energy extraction on mule deer population performance. Much of the rationale for conducting the long-term research is presented in Appendix I. However, this progress report, beginning as of January 2008, focuses only on Objective 5 of the research proposal (Appendix I): monitoring distribution, movements, and habitat selection patterns of adult female mule deer on 5 potential segments of winter range in relation to varying levels of natural gas development, experimental modifications in energy developmental practices, and potential habitat improvement treatments. Long-term funding and support had not been secured to simultaneously address all 6 proposed study objectives on 5 potential winter range segments, but preliminary funding and support had been established to begin to address mule deer movement patterns relative to current natural gas development activities in the Piceance Basin. This initial effort during FY07-08 provided key information to 1) document movement patterns and degree of spatial separation of deer among potential experimental control and treatment sites, 2) help refine study area boundaries, 3) begin documenting deer spatial use in proposed experimental control and treatment areas prior to implementing habitat or development improvements, and 4) provide an assessment of deer capture logistics and operational success of improved versions of GPS and VHF radio-telemetry collars. Monitoring spatial use patterns of 65 �deer is planned for at least 5 years as part of the forthcoming major study so that this first year of data acquisition establishes the foundation for long-term data acquisition process. Once longer term financial and administrative commitments have been established, we will incorporate the additional objectives into a revised study plan to achieve our overall goal of developing approaches to provide for energy extraction in a manner that maintains viable mule deer populations for future recreational and ecological purposes. We recently acquired the necessary funding to allow for the complete study proposal to be initiated by fall 2008 and continue through spring 2010. STUDY AREA The Piceance Basin in northwest Colorado was selected as the project area due to its ecological importance as one of the largest migratory mule deer populations in North America and also exhibits one of the highest natural gas reserves in North America (Fig. 1). Historically, mule deer numbers on winter range were estimated between 15,000-22,000 (Bartmann 1975), and the current number of well pads (Appendix I: Fig.1) and projected number of gas wells in the Piceance Basin over the next 20 years is about 400 and 15,000, respectively. Mule deer winter range in the Piceance Basin is predominantly characterized as a topographically diverse pinion pine (Pinus edulis)-Utah juniper (Juniperus osteosperma; pinion-juniper) shrubland complex ranging from 1675 m to 2285 m in elevation (Bartmann and Steinert 1981). Pinion-juniper are the dominant overstory species and major shrub species include Utah serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), big sagebrush (Artemisia tridentata), Gamble‘s oak (Quercus gambelii), mountain snowberry Symphoricarpos oreophilus), and rabbitbrush (Crysothamnus spp.; Bartmann et al. 1992). The Piceance Basin is segmented by numerous drainages characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainages having been converted to mixed-grass hay fields. Grasses and forbs common to the area consist of wheatgrass (Agropyron spp.), blue grama (Bouteloua gracilis), needle and thread (Stipa comata), Indian rice grass (Oryzopsis hymenoides), arrowleaf balsamroot (Balsamorhiza sagittata), broom snakeweed (Gutierrezia sarothreae), pinnate tansymustard (Descurainia pinnata), milkvetch (Astragalus spp.), Lewis flax (Linum lewisii), evening primrose (Oenothera spp.), skyrocket gilia (Gilia aggregata), buckwheat (Erigonum spp.), Indian paintbrush (Castilleja spp.), and penstemon (Penstemon spp.; Gibbs 1978). The climate of the Piceance Basin is characterized by warm dry summers and cold winters with most of the annual moisture coming from spring snow melt. In our initial proposal, we outlined 6 potential study sites exhibiting varying winter deer densities and varying levels of energy development activity to provide control and treatment experimental units for evaluating improved habitat and development treatments (Appendix I: Table 1, Fig. 2). Ultimately, 1 of the 6 proposed study sites was omitted partly due to funding limitations and ultimately because the omitted area (Crooked Wash) offered limited opportunity to examine habitat improvements due to dry moisture conditions inhibiting success of habitat treatments and future energy development in the area appeared unlikely due to extensive previous development precluding evaluations of improved development practices. The remaining 5 areas were maintained and North Ridge will serve as a temporal control area offering evaluations of annual variation in parameter estimates due to non-development factors from an undeveloped area, and Story/Sprague Gulch (formerly referred to as Story/Willow Creek) and Yellow Creek will serve as spatial control areas to the 2 treatment areas (Magnolia and Ryan Gulch, respectively), providing spatial comparisons from geographically and vegetatively similar areas exposed to minor levels of energy development compared to extensively developed areas receiving improved habitat and/or development treatments. Because the progression and extent of energy development in the future is currently unknown (to CDOW, at least), North Ridge may also serve as a spatial control area to Magnolia or possibly Ryan Gulch should the Story/Sprague Gulch or Yellow Creek study areas become developed in the future. 66 �METHODS Tasks addressed this fiscal year included deer capture and collaring efforts, monitoring adult female mule deer survival, and downloading and plotting GPS location data monthly from a segment of the sample fitted with downloadable GPS collars (24 of 75 deer total). We employed helicopter netgunning techniques (Barrett et al. 1982, van Reenen 1982) to capture 15 adult female mule deer in each of 5 study areas (75 deer total). Once netted, deer were hobbled, blind folded, fitted with GPS collars, and released. Five deer in 4 of the 5 study areas and 4 deer in the Yellow Creek study area were fitted with remotely downloadable GPS collars (GPS-4400S; Lotek Wireless, Newmarket, Ontario, Canada) and the remaining deer in each area were fitted with store-on-board GPS collars (G2110B; Advanced Telemetry Systems, Isanti, MN, USA). To insure GPS fixes for at least 1 year, both collar types were programmed to attempt a fix every 5 hours and the fix schedule for store-on-board collars was reduced to attempt a fix every 23 hours July-October. Mule deer mortality monitoring consisted of ground tracking deer daily and aerial monitoring deer approximately every 2 weeks from fixed-wing aircraft. Once a mortality signal was detected, deer were located and necropsied to attempt determination of cause of death. We collected GPS locations from the 24 downloadable collars monthly via ground tracking, if possible, or using fixedwing aircraft. RESULTS AND DISSCUSSION Deer Captures We captured and GPS collared 4 yearling and 71 adult female mule deer (15 deer/study area) from January 10-12, 2008 (Fig. 2). No significant injuries were noted during captures. In planning future capture efforts for adult female mule deer, we will anticipate about 25 captures/day/helicopter. Deer Mortalities We identified 1 yearling and 7 adult female mule deer mortalities from January-June, 2008 (Table 1). Although winter severity was relatively high this past winter, adult female survival (90%, n = 71) was typical of mule deer populations under normal winter conditions in the western US (Unsworth et al. 1999). Cause of mortality was determined for 4 of the 8 mortalities documented and varied between coyote predation, malnutrition, and vehicle collision (Table 1). Although the other 4 mortalities were undetermined due to timing of carcass inspection, winter severity was likely a factor given 3 of the 4 mortalities occurred during late May (Table 1). GPS Data Collection and Deer Distribution GPS data downloads and collars retrieved from mortalities suggested collars were generally functioning as expected, but a few issues were noted that may warrant future attention. GPS location acquisition rates were high (>90%) for all collars except 1 where intermittent acquisition failures were common (Lotek GPS_4400S; 58% acquisition rate). The single collar exhibiting a low acquisition rate is acceptable relative to the 31 other collars exhibiting high acquisition rates, but the malfunctioning collar will be returned for evaluation once retrieved to potentially enhance collar performance in the future. We noted that false mortality signals (a mortality signal for an active deer) occurred for short durations (1 to a few days) on several occasions during winter monitoring, and we will increase the inactive time period to activate the mortality switch from 4 to 8 hours for future collar orders to try to address this problem. In addition, consultation with collar manufacturers will be conducted in an attempt to address the problem of inactive mortality signals occurring while deer are active. Another, more significant problem was noted when we unsuccessfully attempted to remotely detonate drop-off mechanisms on a few occasions (Lotek collars). The 20 Lotek collars currently in use will require remote detonation for retrieval in February, 2009, but the apparent unreliability of this device may require additional efforts to successfully retrieve the collars. We should consider the feasibility of using helicopter net-gunning to retrieve Lotek collars 67 �during capture efforts scheduled for late February, 2009, assuming attempts to remotely detonate drop-off mechanisms fail. Monthly downloads and collars retrieved from mortalities yielded GPS movement and distribution data from 32 individuals during winter (Fig. 3), 28 during the spring transition period (Fig. 4), and 24 during early summer (Fig. 5). Observed winter deer distribution (Fig. 3) reasonably followed apriori expectations (Appendix I; Fig. 2) with minor differences in study area boundaries, as defined by deer use, except for the Story/Sprague study area, where wintering deer were distributed farther east than expected (see Bartmann et al. 1992); this change in distribution may be due to changes in habitat conditions and/or potential increases in other ungulate populations (e.g., elk). Of the 32 deer monitored during winter, no interchange between winter herd segments was noted, but a few individuals traveled beyond areas of interest relative to control and treatment experimental units addressing energy development (Fig. 3B). These movements can be addressed by either censoring those data or applying a covariate to the analyses. Based on the winter deer distribution data documented since January and the level of energy development activity present in April, 2008, we provide preliminary study area boundaries (Fig. 3) for future monitoring efforts to address experimental control (North Ridge, Yellow Creek, and Story/Sprague Gulch) and treatment (Ryan Gulch and Magnolia) areas addressing mule deer responses to beneficial habitat treatments and/or development activities. More specific boundaries will be assigned once data are analyzed from the remaining 43 collars scheduled for retrieval in February, 2009. During the spring transition period, deer from North Ridge and the northern half of Magnolia generally moved east, deer from southern Magnolia, Yellow Creek, and Ryan Gulch moved south, and the Story/Sprague Gulch deer moved relatively short distances south and east (Fig. 4). As expected, summer deer distribution was more widely scattered than during winter with deer distributions radiating from the Piceance Basin to the northeast, east, southeast, and south generally following wintering deer from North Ridge, Magnolia-north, Story/Sprague Gulch, and Magnolia-south, Ryan Gulch, Yellow Creek. FUTURE PLANS Funding has been recently secured to initiate the complete study proposal (Appendix I) beginning fall 2008 and continuing spring 2010. To address the other 5 study objectives outlined in Appendix I, we will attach VHF collars to 50 fawns/study area, increase our GPS sample to 20 GPS collared does/study area, measure body condition of 30 does/study area, and add 10 VHF collared does/study area to enhance mark-resight estimates. The period covered will represent existing development conditions or the pretreatment period and allow estimates of mule deer population parameters relative to current development practices and habitat conditions. Additional funding and cooperative agreements will be necessary to manipulate habitat conditions to benefit mule deer and modify development practices to enhance mule deer condition and survival on winter ranges exposed to energy development. We optimistically anticipate the opportunity to work cooperatively toward developing solutions for allowing the nation‘s energy reserves to be developed in a manner that benefits wildlife and the people who value both the wildlife and energy resources of Colorado. LITERATURE CITED Anderson, C. R., Jr., and D. J. Freddy. 2007. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Draft Study Proposal, Colorado Division of Wildlife, Fort Collins, USA. Bartmann, R. M. 1975. Piceance deer study—population density and structure. Job Progress Report, Colorado Division of Wildlife, Fort Collins, Colorado, USA. Bartmann, R. B., and S. F. Steinert. 1981. Distribution and movements of mule deer in the White River Drainage, Colorado. Special Report No. 51. Colorado Division of Wildlife, Fort Collins, USA. 68 �Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monograph No. 121. Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Gibbs, H. D. 1978. Nutritional quality of mule deer foods, Piceance Basin, Colorado. Thesis, Colorado State University, Fort Collins, USA. Unsworth, J. W., D. F. Pack, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Prepared by ________________________ Charles R. Anderson, Wildlife Researcher Table 1. Mortalities of GPS collared yearling and adult female mule deer in the Piceance Basin, Colorado, January-June, 2008. Deer ID Study area Mortality date Age class Apparent cause 150.194 150.235 219.159 150.094 219.149 150.275 216.706 217.615 Story/Sprague Gulch Magnolia Ryan Gulch North Ridge Story/Sprague Gulch Ryan Gulch North Ridge Magnolia 1/19/08 4/9/08 4/25/08 5/4/08 5/23/08 5/24/08 5/25/08 5/28/08 Young adult Young adult Yearling Young adult Old adult Young adult Old adult Young adult Undetermined Coyote predation Vehicle collision Coyote predation Malnutrition Undetermined Undetermined Undetermined 69 �Figure 1. Piceance Basin project area (dashed line) relative to mule deer winter range, oil and gas fields, and the oil and gas basin. Figure 2. Capture locations by study area (solid lines) of GPS collared adult female mule deer in the Piceance Basin, Colorado, January 10-12, 2008. 70 �Figure 3. Mule deer GPS locations by preliminary study area boundary (solid lines) excluding (top) and including (bottom) active will pads and energy development facilities (as of April, 2008) in the Piceance Basin, Colorado, January—April, 2008. 71 �Figure 4. GPS locations of Piceance Basin mule deer during the spring transition period (April—May, 2008). Capture study site: circles = North Ridge, stars = Magnolia, triangles = Story/Sprague Gulch, diamonds = Ryan Gulch, pluses = Yellow Creek. Figure 5. Summer range GPS locations of Piceance Basin mule deer, June—July, 2008. Capture study site: circles = North Ridge, stars = Magnolia, triangles = Story/Sprague Gulch, diamonds = Ryan Gulch, pluses = Yellow Creek. 72 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2007-08 – FY 2012-13 POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION STAGE I, OBJECTIVE 5: PATTERNS OF MULE DEER DISTRIBUTION & MOVEMENTS A Research Study Plan submitted by: C.R. Anderson, Wildlife Researcher, Mammals Research, Colorado Division of Wildlife D.J. Freddy, Mammals Research Leader, Colorado Division of Wildlife A. Need Extraction of natural gas from areas throughout western Colorado has raised concerns among many public stakeholders and the Colorado Division of Wildlife that the cumulative impacts associated with this intense industrialization will dramatically and negatively affect the wildlife resources of the region. Concern is especially high for mule deer due to their recreational and economic importance as a principal game species and their ecological importance as one of the primary herbivores of the Colorado Plateau Ecoregion. Extraction of natural gas will directly affect the potential suitability of the landscape used by mule deer by converting native habitat vegetation to drill pads, roads, or noxious weeds, by fragmenting habitat because of drill pads and roads, by increasing noise levels via compressor stations and vehicle traffic, and by increasing the year-round presence of human activities. Extraction will indirectly affect deer by increasing the human work-force population of the region and the subsequent need for developing additional landscape for human housing, supporting businesses, and upgraded road/transportation infrastructure. Additionally, increased traffic on rural roads will raise the potential for vehicle-animal collisions and additive direct mortality to deer populations. Thus, research documenting these impacts and evaluating the most effective strategies for minimizing and mitigating these activities will greatly enhance future management efforts to sustain mule deer populations for future recreational and ecological values. The Piceance Basin in northwest Colorado supports one of the largest migratory mule deer populations in North America and also exhibits one of the highest natural gas reserves in North America. Projected energy development throughout northwest Colorado within the next 20 years is projected to be about 15,000 wells, many of which will occur in the Piceance Basin. The Piceance Basin (including the White River gas field immediately to the north) currently supports about 400 active gas well pads, 250 permits for development within the next year, and 200 energy development facilities (Colorado Oil and Gas Conservation Commission; Fig. 1). Wintering mule deer population segments in or immediately adjacent to the Piceance Basin include: Crooked Wash along the White River on the north edge of the Basin, North Ridge between Dry Fork of Piceance Creek and the White River in the northeastern portion of the Basin, Yellow Creek along Yellow Creek in the western portion of the Basin, Ryan Gulch between Ryan Gulch and Dry Gulch in the southwestern portion of the Basin, Magnolia north and east of Piceance Creek in the central portion of the Basin, and Story/Willow Creek between Willow Creek and Story Gulch in the southern portion of the Basin. Each of these wintering population segments has received varying levels of development, from little-no development in Story/Willow Creek and North Ridge, light development in Yellow Creek, and relatively high development in Ryan Gulch, Crooked Wash, and 73 �Magnolia segments (Fig. 2). Due to advances in resource extraction technology and the increased demand for natural gas, future development and extraction activities will likely focus on natural gas fields previously developed and expand into adjacent areas where previously identified oil shale reserves and natural gas basins provide additional resource extraction opportunities. Because of the variation in the geology relative to gas reserves in the area and the juxtaposition of differing mule deer winter herd segments, several opportunities are available to address different, but related, questions relative to natural gas extraction methods and mitigation efforts relative to mule deer habitat use patterns. Past Research The Piceance Basin has been the location of numerous research investigations conducted by the Colorado Division of Wildlife, Colorado State University, and others which addressed various aspects of mule deer ecology and management beginning in the 1970s and continuing through the mid 1990s. Previous investigations of Piceance Basin mule deer addressed food habits (Hansen and Dearden 1975, Hubbard and Hansen 1976, Gibbs 1978, Bartmann 1983), physiology (Bartmann 1986, Torbit et al. 1988), development of management techniques (Freddy and Bowden 1983b, Garrott and White 1984a, Lee et al. 1985, White and Bartmann 1994), efficacy of population sampling methods (Freddy and Bowden 1983a, Bartmann et al. 1986, 1987, White et al. 1989), and population dynamics (White and Bartmann 1983, 1998, Garrott and White 1984b, Lee 1984, Garrott et al. 1987, White et al. 1987, Bartmann et al. 1992). Previous investigations of mule deer habitat use patterns in the Piceance Basin (Garrott et al. 1987) suggested fall migration consistently occurred during November, but spring migration varied likely due to winter severity and body condition, where rapid migration was evident when deer were leaving winter range in good condition and delayed migration was indicative of deer transitioning from winter range in relatively poor condition. Garrott et al. (1987) also noted strong fidelity to seasonal ranges, that deer shifted from north to south slopes as winter severity increased, and that irrigated and fertilized hay meadows served as important transition areas during fall and spring migration periods. Bartmann et al. (1992) manipulated deer densities to demonstrate compensatory mortality in the Piceance Basin mule deer population, where overwinter fawn survival varied inversely with density and adult female survival remained relatively constant; fawn mortality rather than reproduction appeared to be the major process driving the density-dependent mechanism. White and Bartmann (1998) reduced deer densities by 75% in their treatment area and reported 16% higher overwinter fawn survival and fawn body mass averaging 0.8 kg higher than the control area, whereas adult female survival was comparable between areas supporting previous findings (Bartmann et al. 1992). Empirical evidence of mule deer population response to habitat manipulations is currently limited, largely due to the logistical and financial difficulty in conducting long-term research sufficient to address this relationship. Density dependent relationships have been demonstrated (e.g., Bartmann et al. 1992) and habitat quality rather than proximate mortality factors (e.g., predation) appear to be the driving factor (Bartmann et al. 1992, Hurley and Zager 2004, Bishop et al. 2005). Bishop et al. (2005), however, demonstrated enhanced population performance in supplementally fed, free-ranging deer to simulate high quality habitat, and reported 18% higher fawn survival (fetus to yearling; fetus-neonate = 0.127, overwinter = 0.240) and adult females averaged 5.5% more body fat, but reproduction and adult female survival were similar between treatment and control groups. Bergman et al. (2005, 2006) are currently investigating mule deer population response to habitat treatments in western Colorado, which will likely provide insight into our approach of addressing habitat treatments in response to energy development as this study progresses. Currently, research addressing mule deer activity in response to natural gas development is limited to one study from the Pinedale anticline in Wyoming (Sawyer et al. 2006). Sawyer et al. (2006) examined changes in distribution before and during development of a natural gas field, and observed shifts in mule deer habitat use away from well pads (2.7-3.7 km) within 1 year of development which continued throughout the study, suggesting indirect habitat loss may be substantially larger than direct 74 �habitat loss and presumably results in deer using lower quality habitats that may ultimately lead to population decline. Mule deer habitat in Pinedale was much less topographically and vegetatively diverse than the Piceance Basin, however, and mule deer may respond differently where the habitat affords a higher degree of security cover. Mule Deer Response to Habitat Treatments and Changes in Development Practices Our primary goal of this study is to develop approaches to provide for energy extraction in a manner that maintains viable mule deer populations for future recreational and ecological purposes. This may be accomplished by restoring or enhancing habitat conditions on or adjacent to disturbed sites and by modifying development practices. Mitigating developed sites following disturbance requires reseeding or planting native vegetation, control of noxious weeds, and demonstrating success of mitigation efforts. Because mule deer are primarily browsers, shrub establishment will be essential, but shrub establishment is difficult and takes time for reemergence. Mule deer response to winter range mitigation efforts on disturbed sites will require relatively long-term monitoring to determine success of habitat treatments. More rapid habitat, and thus mule deer, responses can be expected from treating mule deer habitat adjacent to developed areas and by irrigating and fertilizing hay meadows adjacent to winter ranges (Garrott et al. 1987). Improving habitat conditions for or reverting succession of shrub communities using roller-chopping, hydro-axing, or fire can improve forage quality, and increasing forage quality and quantity by irrigating and fertilizing hay fields can improve mule deer body condition at critical times when transitioning to and from winter range. In addition to habitat treatments, mule deer may also benefit from modification in development practices that reduce human disturbance. Development practices that concentrate activities and/or minimize human disturbance will most likely minimize detrimental impacts to mule deer populations. Energy development practices that may be informative to investigate include directional versus non-directional drilling, piping versus trucking condensate from well pads, remotely versus directly monitoring gas wells, closing access roads following development, shifting from noisy diesel to quieter natural gas motors, and phased/clustered development where sections of deer winter range are developed while others remain undisturbed until development and mitigation are completed in developed sections. Determining the response of mule deer to specific development practices will require collaboration with the developer, and the specific conditions of the site being developed will dictate which development practices can feasibly be evaluated. Encana and Exxon-Mobile are the primary energy companies controlling natural gas development in the Piceance Basin (Fig. 3). Mule Deer Response to Energy Development Mule deer may negatively respond to energy development from direct reduction in forage availability from development activities, from indirect reduction of forage quality and quantity by shifting their distribution away from development activity to less preferred habitats, from negative physiological responses where deer maintain fidelity in areas exposed to development activities or from a combination of these factors. Depending on the extent and concentration of development, deer may also be able to adjust to development activities without population level impacts, and other factors (e.g., winter severity, drought, habitat succession, predation) also contribute to fluctuations in population performance/trajectory over time. Ultimately, reproduction and survival drive population performance and, based on past research, focusing on fawn survival and recruitment appear to be the most influential parameters given the density dependent nature of these factors versus the apparent density independent nature of adult female survival and reproduction. Documenting proximate factors influencing fawn survival will also be useful and thus changes in distribution, deer density, body condition, and specific mortality factors should also be monitored. Comparing changes in mule deer population parameters relative to energy development will require that undeveloped control areas are monitored and predevelopment data are collected to determine whether or not and to what extent development versus environmental factors may be contributing. This will be challenging given development already in place and the unpredictability of future development that may occur. Large scale impacts from energy development may be detectable by comparing mule deer population parameters from undeveloped sites to 75 �developed sites, but natural variation due to geographic differences will be unaccounted for and add error to comparisons. Our ability to examine mule deer response to habitat mitigation and/or beneficial development practices will be better suited for demonstrating cause-effect relationships by allowing controlled experimental designs where habitat manipulation or modifying human behavior (i.e., development practices) provide the treatments for examining positive responses in mule deer population parameters. B. Objective The primary objectives for the long-term research proposal are as follows: 1. Determine if winter range and riparian vegetation responds positively to habitat treatments; 2. Determine if fawn and yearling survival is positively influenced by winter range habitat treatments; 3. Determine if fawn and yearling survival is positively influenced by irrigating and fertilizing hay meadows adjacent to winter ranges; 4. Determine if modification of development practices positively influences mule deer population performance; 5. Determine if habitat treatments, changes in development practices, or natural gas development results in distributional shifts on mule deer winter range; 6. Determine if habitat treatments, changes in development practices, or natural gas development results in changing mule deer densities on winter range. The specific objective of this study plan is to address objective 5: Determine if habitat treatments, changes in development practices, or natural gas development result in distributional shifts on mule deer winter range in the Piceance Basin. The primary working hypotheses for the long-term research proposal are as follows: a. Landscape level habitat treatments do not influence forage quantity and quality; b. Fawn and yearling survival are not influenced by winter range habitat treatments; c. Fawn and yearling survival are not influenced by modification of development practices; d. Mid-winter deer density does not fluctuate in response to habitat treatments, changes in development practices, or natural gas development; e. Mule deer habitat selection does not change in response to habitat treatments, changes in development practices, or natural gas development. The specific working hypothesis of this study plan is: Mule deer habitat selection does not change in response to habitat treatments, changes in development practices, or natural gas development. C. Expected Results Due to the extensive energy development that is projected to occur over the next 20 years throughout much of the mule deer winter range in the northern Rocky Mountains of the western US, innovative approaches to energy development and mitigation methods are essential to sustain viable mule deer populations in the region. Impacts from development and conversely success of mitigation efforts are often assumed but rarely demonstrated, and these assumptions can only be confirmed by application of well designed research efforts conducted over sufficiently long time periods to measure responses. As a first step toward this effort, we propose to address mule deer habitat selection patterns relative to varying levels natural gas development and associated human activity and ultimately address mule distributional responses to habitat and development modifications anticipated to be beneficial to mule deer. This project will require coordination and cooperation between Colorado Division of Wildlife, land management agencies, and the major energy companies developing the Piceance Basin. We anticipate this partnership will benefit mule deer populations and foster the evolution of wildlife management and 76 �energy development practices that are compatible with other wildlife and human values associated with maintaining functional ecosystems over the long term. D. Approach 1. Experimental Approach a. Experimental Units Because of the varying levels of development and deer densities relative to differing winter population segments in the Piceance Basin, different experimental areas (i.e., mule deer winter ranges) are uniquely suited for addressing mule deer habitat selection patterns relative to varying levels of energy development. Experimental designs monitoring mule deer responses to treatment (e.g., habitat mitigation, modified development practices) and control areas are necessary to differentiate cause-effect relationships from development versus environmental factors. Suitable control areas require that little or no previous development has occurred and that no development occurs during the experimental time frame. Ideally, both temporal and spatial control areas would be monitored to make valid comparisons to developed and subsequently mitigated sites; temporal controls provide measures of natural variability in mule deer population parameters over time and spatial controls provide measures of variability due to differences in geography. Once spatial and temporal variation is accounted for, inferences can be made relative to development disturbance or mitigation effects on mule deer. The North Ridge, Story/Willow Creek, and Yellow Creek deer population segment areas (Fig. 2) currently exhibit little to no development, but it is currently unknown whether or not these areas will be developed in the future; there is potential for future oil shale development in the Story/Willow Creek and Yellow Creek deer areas. North Ridge appears least likely to be developed because it is outside of the current oil shale lease area and only a few natural gas wells have historically been drilled on or adjacent to the area, whereas some development is currently occurring and likely to increase in the Story/Willow Creek and Yellow Creek areas. Thus, North Ridge would appear best suited as a temporal control site for comparison to other developed winter ranges within the Piceance Basin and may also serve as a geographic control for the Crooked Wash deer population segment located immediately north and adjacent to the Piceance Basin (as of Dec. 2007, the Crooked Wash site ranks 6th in study priority and will not be sampled in the initial year due to limited funding). The Story/Willow Creek and Yellow Creek deer may provide spatial controls for the Magnolia and Ryan Gulch deer population segments, respectively, but future development potential in these areas is unknown. If these areas become developed in the future (either for oil shale or natural gas), they would provide BACI (Before-AfterControl-Impact) type comparisons strengthening our inference of development impacts on mule deer habitat selection patterns. Magnolia, Crooked Wash, and Ryan Gulch deer areas have historically received relatively high development activity and currently exhibit moderate-high development, and appear likely to be developed extensively in the future based on the gas development layers currently available (Colorado Oil and Gas Conservation Commission; Fig. 1). Pretreatment data in these areas will be represented by parameters associated with developed sites and the measured response will be in the form of habitat treatments and/or differing development practices, which will be measured in comparison to the control sites. We propose including 3 control sites (1 temporal/spatial control and 2 spatial controls) and 3 treatment sites to investigate mule deer response to habitat and/or development treatments (e.g., directional versus non-directional drilling, piping versus trucking condensate, etc.) across a range of deer densities (Table 1). We would strive to split high intensity extraction study sites into 2 halves with one half serving as the ‗control‘ [standard development] and one half serving as the ‗treatment‘ [improved development approach or improved habitat] (e.g., see Magnolia in Fig. 2). The above scenario addresses the potential for establishing control and treatment sites for evaluating shifts in mule deer habitat use patterns in response to habitat treatments and/or development treatments, and may allow larger scale 77 �comparisons in mule deer habitat use patterns relative to varying levels of energy development to be compared among experimental areas. Modified versions of the proposed design could be implemented depending on the level of funding available and the degree to which industry is willing to collaborate with this effort. We consider 3 study sites, likely North Ridge, Magnolia, and Ryan Gulch, as the minimum number of study sites necessary to adequately address the objectives of this project; the additional proposed study areas will allow increased flexibility in the questions that are addressed and increase our inference relative to mule deer responses to habitat treatments and modifications of development practices. Furthermore, if we are not able to evaluate potential for mitigating industrial operation and/or habitat improvements, this study would likely only have the potential to document negative impacts of intense energy extraction practices on mule deer. Table 1. Relative density of natural gas wells and mule deer and experimental designation for potential study sites in the Piceanace Basin, Colorado, for addressing mule deer response to natural gas development practices and habitat mitigation. Relative density Experimental Study area Inactive wells Active wells Mule deer designation North Ridge Very low None High Temporal/spatial control Crooked Washa High High High Treatment Story/Willow Creek Low Low Moderate Spatial control Magnolia High High Moderate Treatment Yellow Creek Moderate Low Low Spatial control Ryan Gulch High Moderate Low Treatment a As of Dec. 2007, for the initial research effort, the Crooked Wash study site ranks 6th in priority and will not be sampled due to limited funding. b. Response Variables To determine if habitat treatments or development practices elicit a shift in habitat use patterns, we will examine changes in Resource Selection Probability Functions (RSPF; Sawyer et al. 2006) preand post-habitat treatments, between areas exhibiting differing development practices, and compare RSPFs between developed and non-developed sites. Population level models for each study area will be compared to assess similarities and differences in habitat selection patterns relative to differing levels of energy development. We suggest relevant habitat attributes associated with mule deer response to habitat treatments and development practices include slope, aspect, elevation, habitat type, road density, distance to well pad, and development activity. Definition for development activity would vary depending on the development treatment investigated. For example, if the development treatment were applied to examine 78 �fluid collection systems, the variable would be coded 1 or 0 depending on whether they were present or absent and the RSPF would be estimated relative to this effect. In another example, well pad visitation rate may be the variable of interest and the RSPF would be estimated for a continuous effect of increasing road traffic to well pads. 2. Sample Size / Power Calculations We anticipate 20 GPS collars per experimental area will be sufficient to provide population level inference based on similar studies with ungulates (Millspaugh and Marzluff 2001) for addressing adult female mule deer habitat selection patterns for each study site. 3. Procedures a). Capture and Handling Methods A total of 120 adult female mule deer will be captured and GPS-collared (20/study area assuming 6 study sites, 100 deer during initial FY07-08 for 5 study sites). Helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) will be used to complete the necessary sample in January 2008 and a combination of helicopter net-gunning and drop netting will be used during March of subsequent years. b). Monitoring Habitat Use Patterns Habitat use patterns on treatment and control sites will be evaluated applying the Resource Selection Probability Function (RSPF) approach of Sawyer et al. (2006), where resource selection is estimated using the relative frequency or absolute probability of use as a function of the predictor variables. This approach will consists of 5 basic steps including (1) estimate the relative frequency of use (an empirical estimate of probability of use) for a large number of sampling units for each GPS collared deer (20/study area), (2) use the relative frequency as the response variable in a multiple regression analysis to model the probability of use for each deer as a function of predictor variables, (3) develop a population level model from the individual deer models for each experimental area, (4) map predictions from each model annually to examine changes in habitat use patterns over time relative to treatment effects, and (5) compare population level model coefficients between treatment and control sites to examine differences in resource selection among non-developed, developed, and mitigated sites. Relative frequency of use for each deer will be estimated by counting the number of deer locations that occur within 100-m radii circular sampling units (representing habitat attributes) systematically sampled throughout each study area; 200-m-wide sample unit should be small enough to detect changes in deer movements and large enough to provide multiple locations for estimating use probability functions. c). Habitat Manipulations The purpose of habitat manipulation would be 2-fold: 1) replace forage lost directly to surface destruction associated with gas pad/road/infrastructure development through rehabilitation of these areas, and 2) enhance suitable undisturbed vegetation. In both situations, the goal would be to provide habitats/vegetation having enhanced nutritional value to mule deer during fall (pre-winter) and spring (post-winter) migrations and during the critical winter period in order to improve body condition of deer and enhance their probability of survival. Placement of such habitat treatments would need to be evaluated and planned based on identification of priority areas within the Piceance Basin, in general, and specifically within experimental study sites. Opportunities within study sites would, in part, be dependent on cooperation of Energy Corporations, BLM, and private land owners, and site specific potentials that realistically can only be specifically determined after commitments are made in choosing experimental sites. We envision the potential to utilize a full-suite of habitat improvement options. These could include: enhancing existing sagebrush areas using combinations of herbicide, nitrogen fertilizer, chopping-mowing, reseeding with grasses-forbs, and in some cases reseeding with suitable sagebrush species; enhancing mountain brush habitats through burning, hydroaxing, and reseeding; enhancing 79 �pinyon-juniper habitats through hydroaxing, burning, and reseeding. Site specific situations could require using advanced mulching, seeding, and irrigation options to effectively rehabilitate sites. In all cases, we would attempt to layout experimental habitat improvements to facilitate evaluation of success both from the standpoint of vegetation rehabilitation and use by mule deer. Past research and monitoring of radio-collared mule deer in the Piceance Basin documented the high use and importance of cultivated hay fields along Piceance Creek. We envision considerable potential to improve management of hayfields to specifically address the needs of deer, especially during post-fall and pre-spring migrations of deer into and out of the Piceance Basin. The potential to manage hayfields for deer will be dependent on options to own or lease fee-title property and water rights. There may be nearly 10,000 acres of suitable hayfields located along Piceance, Ryan, Black Sulphur and Yellow creeks. In general, we believe that hayfields using more efficient irrigation practices and planted with suitable varieties of alfalfa developed to be grazed more so than for traditional hay production and suitable to alkaline soils would offer high potential to enhance nutrition of deer at key periods of the year. We also could see potential to establish hayfields with appropriate varieties of cool-season grasses (bluegrass for example) that could be managed for high nutritional quality through annual burning, mowing, grazing, and irrigation practices. Such cool season grass fields could provide ‗green‘ forage for deer both during spring ‗green-up‘ and fall ‗re-green‘ periods, especially if limited irrigation could be applied. The specific design and layout of reformed hayfield management would require considerable planning involving the expertise of NRCS or University Extension programs and considerable cost (potentially millions of dollars) for fee title ownership of land and water rights, mechanical preparation of hayfields and irrigation systems, and annual management practices once fields were established. d) Evaluation of Development Practices We anticipate options for industry to alter extraction practices that would reduce and/or concentrate human activity and benefit deer by increasing the relative ‗security‘ of existing or improved habitats for deer. Options could include: multi-well versus single-well drilling platforms to reduce well pad density; piping instead of trucking well-condensate; road closures that minimize where traffic occurs; time of day restrictions; remote well-monitoring, or other options that industry may be able to offer. The key to evaluating any of these industrial-human activity options would be to create experimental comparisons using ‗control‘ areas [current practices] versus ‗treatment‘ areas [improved practices]. Which alternative practices are tested and in which potential study sites involved will depend upon cooperation from industry. Ideally, energy corporations would cooperate among themselves, the BLM, and with Division of Wildlife to help develop the best possible experimental design among extraction lease areas. e). Statistical Analyses Following Sawyer et al. (2006) for estimating Resource Selection Probability Functions, we will obtain population–level models for each experimental area by first estimating coefficients for each GPScollared deer. A negative binomial distribution will be used to fit the following general linear model (GLM): ln(E[ri]) = ln(total) + β0 + β1X1 +…+ βpXp, where ri is the number of locations for a GPS-collared deer within sampling unit i (i = 1, 2, …, r), total is the total number of locations for that deer within each experimental unit, βo is the intercept term, β1,…,βp are unknown coefficients for habitat variables X1,...,Xp, and E[.] denotes the expected value. We will estimate coefficients for the population–level model for each experimental unit following: ˆ k 1 n ˆ kj , n j1 80 �ˆ where kj is the estimate of coefficient k for individual j (j = 1,…,n) and the variance will be estimated applying the variation among individual model coefficients. To compare habitat use patterns between areas and over treatment effects, we will map predicted probabilities of use for each study area by season. Differences (P < 0.05) between population level model coefficients will be compared between study areas using a t-test. 4. Project Schedule FY2007-08 FY2008-09 FY2009-10 FY2010-11 FY2011-12 FY2012-13 FY2013-14 FY2014-15 FY2015-16 FY2016-17 FY2017-18 FY2018-19 Pretreatment/Revised Program Narrative Study Plan Pretreatment/Progress Report (PR) Habitat and/or Development Treatments/PR Habitat-and/or Development Treatments/PR Monitor Deer Response/Progress Report Project Status Evaluation Monitor Deer Response/Progress Report Monitor Deer Response/Progress Report Monitor Deer Response/Progress Report Project Status Evaluation Monitor Deer Response/Progress Report Monitor Deer Response/Progress Report Monitor Deer Response/Completion Report Prepare and submit peer-reviewed publications 9/1/2007 8/1/2008 8/1/2009 8/1/2010 8/1/2011 8/1/2012 8/1/2013 8/1/2014 8/1/2015 8/1/2016 8/1/2017 8/1/2018 5. Annual Cost Estimates Estimating mule deer resource selection probability functions and implementing small scale habitat improvements are costly endeavors involving the purchase of specialized GPS radio-collars, helicopter flight hours for deer capture/collaring, machinery to physically alter the habitat, and personnel to adequately perform day-to-day data collection. If large scale habitat treatments are needed or desired, funding in addition to the estimates below will be required as habitat treatments cost $300 to $1,000/acre depending on the most appropriate treatment for a locale. Key to evaluating mule deer responses to habitat and/or development treatments will be sufficient and steady funding over a time horizon (minimum of 5-year commitments over the 10 year study period) that allows for meaningful biological responses to occur and be measured. Cost estimates per year (2007 dollars for objective #5): GPS Equipment Costs: $200,000 Helicopter Capture Costs: $ 70,000 12 months TFTE: $ 30,000 Vehicle support: $ 20,000 Other field operations and equipment: $ 15,000 Total: $335,000 6. Personnel Charles R. Anderson, Jr., Wildlife Researcher, Project Leader, Colorado Division of Wildlife David J. Freddy, Mammals Research Leader, Colorado Division of Wildlife E. Location of Work The proposed research will take place in or adjacent to the Piceance Basin of northwest Colorado, primarily within Game Management Unit 22 of the White River mule deer DAU D-7, west and southwest of Meeker, Colorado (Fig. 2). 81 �F. Literature Cited Anderson, C. R., Jr., and D. J. Freddy. 2007. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Draft Study Proposal, Colorado Division of Wildlife, Fort Collins, USA. Bartmann, R. M. 1983. 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Thesis, Colorado State University, Fort Collins, USA. Lee, J. E., G. C. White, R. A. Garrott, R. M. Bartmann, and A. W. Alldredge. 1985. Assessing accuracy of a radiotelemetry system for estimating animal locations. Journal of Wildlife Management 49:658-663. Millspuagh, J. J. and J. M. Marzluff. 2001. Radio tracking and animal populations. Academic Press, San Diego, USA. Ramsey, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. Sawyer, H., R. M. Nielson, F. Lindzey, and L. L. McDonald. 2006. Winter habitat selection of mule deer before and during development of a natural gas field. Journal of Wildlife Management 70:396403. Schmidt, R.L., W.H. Rutherford, and F.M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. Stephenshon, T.R., V.C. Bleich, B.M. Pierce, and G.P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. Stephenshon, T.R., T.R., K.J. Hundertmark, C.C. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717722. Torbit, S. C., L. H. Carpenter, R. M. Bartmann, A. W. Alldredge, and G. C. White. 1988. Calibration of carcass fat indicies in wintering mule deer. Journal of Wildlife Management 52:582-588. Unsworth, J. W., D. F. Pack, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G. C. 1996. NOREMARK: Population estimation from mark-resighting surveys. Wildlife Society Bulletin 24:50-52. White, G. C., and R. M. Bartmann. 1983. Estimation of survival rates from band recoveries of mule deer in Colorado. Journal of Wildlife Management 47:506-511. White, G. C., R. A. Garrott, R. M. Bartmann, L. H. Carpenter, and A. W. Alldredge. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Management 51:852-859. White, G. C., R. M. Bartmann, L. H. Carpenter, and R. A. Garrott. 1989. Evaluation of aerial line transects for estimating mule deer densities. Journal of Wildlife Management 53:625-635. White, G. C., and R. M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. White, G. C., and R. M. Bartmann. 1998. Effect of density reduction on overwinter survival of freeranging mule deer fawns. Journal of Wildlife Management 62:214-225. 83 �Piceance Basin Gas Fields + Gas Basin + Active Wells + Inactive Wells + Permitted Wells Figure 1. Natural gas development in the Piceance Basin, Colorado, July 2007. 84 �Crooked Wash Yellow Creek Piceance Basin North Ridge Magnolia Ryan Gulch Story/Willow Creek Research Areas + Active Wells + Inactive Wells + Drilling Permits Figure 2. Proposed mule deer study sites relative to natural gas development in the Piceance Basin, Colorado, July 2007. 85 �Crooked Wash Yellow Creek North Ridge Magnolia Ryan Gulch Piceance Basin Research Areas + Gas Lease Ownership Story/Willow Creek Figure 3. Proposed mule deer study sites relative to the primary energy companies controlling natural gas leases in the Piceance Basin, Colorado, July 2007. 86 �Colorado Division of Wildlife July 2007 – June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 3 Federal Aid Project No. W-185-R : : : : Division of Wildlife Mammals Research Deer Conservation Pilot Evaluation of Predator-Prey Dynamics On the Uncompahgre Plateau Period Covered: July 1, 2007 - June 30, 2008 Authors: M.W. Alldredge, E.J. Bergman, C.J. Bishop, K.A. Logan, D.J. Freddy Personnel: B. Dunne, V. Yovovich, E. Phillips, M. Schuette All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an attempt to address predator-prey dynamics, we initiated a pilot study to evaluate cougar predation relative to prey distribution across the southern half of the Uncompahgre Plateau in southwestern Colorado. As part of ongoing mule deer and cougar research in this area, we estimated cougar kill rates and prey selection by sampling different sized clusters of cougar GPS locations across the landscape. Cluster size ranged from 1 location to >30 locations/cluster. In the vicinity of each sampled cluster, we searched for cougar prey items to determine whether a kill had occurred and to classify prey by species and age. This field effort was primarily focused in areas with extensive historical mule deer population and winter range distribution data. Simultaneously, a pilot effort to collect distribution and movement data of elk over this same geographic area was conducted. As predicted, cougar kill sites were associated with deer and elk distribution. The greatest density of kill sites occurred across mid-upper elevation deer winter range where overlap of wintering elk and deer was greatest. We investigated 462 clusters during this pilot study. Kill probability increased as cluster size increased ( ˆ = 0.353, SE = 0.0706). Kill probability exceeded 0.9 with ≥ 10 locations/cluster and approached 1 with ≥ 15 locations/cluster. The probability of a kill was high if a cougar spent >2 days in the same general area, and a kill was essentially certain if a cougar spent >3 days in the same general area. There was some probability of a kill at clusters that comprised only 1 location, indicating that isolated cougar locations may periodically be associated with kills and should not be ruled out when using GPS location data to address cougar prey utilization. Our estimates of kill probability are conservative because the estimates assume detection probability was 1, which is unlikely. Cougars killed adult deer, fawn deer, adult elk, and calf elk in roughly equal proportions. Each prey class comprised 0.22 0.24 of the total kill. Kill composition varied as a function of percent vegetative cover and elevation. Future research should evaluate detection probability, which underlies the interpretation of cougar kill rates. 87 �WILDLIFE RESEARCH REPORT PILOT EVALUATION OF PREDATOR-PREY DYNAMICS ON THE UNCOMPAHGRE PLATEAU MATHEW W. ALLDREDGE, ERIC J. BERGMAN, CHAD J. BISHOP, KENNETH A. LOGAN, AND DAVID J. FREDDY P.N. OBJECTIVE To assess if a sampling based approach to collecting cougar predation data can efficiently result in unbiased data. To make a pilot assessment of how cougar kills are spatially distributed over prey winter range. SEGMENT OBJECTIVES 1. Use and evaluate the efficiency of a GPS collar, GIS and statistical sampling based approach to investigate potential cougar kill sites. 2. Estimate mule deer density on three study areas and extrapolate results onto surrounding mule deer range. 3. Overlay locations of 5 elk, collected via GPS collars, on mule deer winter range boundaries to gain preliminary information as to how much spatial overlap occurs between the species and to determine where cougar kills occur in relation to the mule deer and elk space use. INTRODUCTION Predator prey interactions have always been a topic of interest for wildlife managers and ecologists. However, due to the complexities of studying natural systems, behavioral theories pertaining to the subject are often developed in invertebrate, aquatic or small mammal systems, often under controlled laboratory conditions (Mathews et al. 2006, Schmitz 2006, Werner and Peacor 2006). Similarly, many models are developed within theoretical frameworks (Keeling et al. 2000, Mitchell and Lima 2002). While developing theories under these conditions is almost inherently necessary, their subsequent transition to free ranging systems is not frequent (Ryall and Fahrig 2006). Of the free ranging systems where theories are developed and tested, most deal with avian species (Lima and Bednekoff 1999, Roth et al. 2006), where as application to large mammalian systems is less frequent. Of the mammalian predator prey systems that have been studied, most have been conducted in preservation/park settings that largely exclude human influence (Kunkel and Pletscher 1999, Kunkel et al. 1999, Krebs et al. 2001, Creel and Creel 2002, Mao et al. 2005, Wilmers et al. 2006,). Additionally, due to the small number of large scale studies that have been conducted, the ability of managers to draw inference to separate systems (i.e. different species or different ecosystems) is limited. While this existing body of work is invaluable, extrapolation of theories to large mammalian systems could be limited and basing wildlife management decisions on this information may be tenuous. Due to the value of mule deer, elk and cougars as recreationally hunted species in Colorado, there is much interest in understanding the nature and relationship between the population dynamics of these species. However, resulting from the dearth of information pertaining to the interactions of these 3 species, a vast array of opinions and theories pertaining to their impacts on each other have been propagated. As a management agency, the Colorado Division of Wildlife is responsible for supporting or refuting claims with biological data that were collected in a scientifically unbiased manner. To date, these data are largely unavailable. 88 �Currently, the opportunity to develop a predator prey study exists on the Uncompahgre Plateau in southwestern Colorado. Two large scale research programs, independently studying cougar and mule deer, are underway in the same geographic area. Thus, the initial framework to study a top carnivore, and what are thought to be its primary prey species, is in place. However, to date there is little or no information pertaining to elk distribution or population dynamics in this area. The addition of elk spatial data will allow us to assess the feasibility of developing a full study addressing the influence and interactions of cougars, mule deer, and elk. STUDY AREA This pilot study was conducted on the southern half of the Uncompahgre Plateau in southwestern Colorado, near Montrose, Colorado (Figure 1). The study area was defined by the existing boundary for the ongoing cougar research project with prey populations being monitored only in the eastern half of the cougar study area. METHODS Capture and Handling Methods As part of completed, as well as ongoing mule deer research, approximately 75 adult female mule deer were marked with VHF radio collars in the area of interest (Bishop et al. 2005). Additionally, 25 mule deer fawns were captured and radio-collared within the eastern portion of the study area between late-November and late-December 2006 as part of the ongoing mule deer research (Bergman et al. 2005; capture protocols previously approved by CDOW ACUC). All mule deer were captured with baited dropnets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) or via helicopter net-gunning (Barrett et al. 1982, van Reenen 1982). As part of the ongoing cougar research project, 19 cougars (15 female, 4 male) were outfitted with GPS collars that allowed on-demand data download interaction with researchers. Cougars were captured primarily via pursuit by dogs as well as in live traps (Logan 2005, capture protocols previously approved by CDOW ACUC). As part of this pilot study, adult female elk (9) were captured via helicopter net-gunning during late-December/January 2006-07 with 5 adult females fitted with drop-off GPS/VHF collars and 4 adult females fitted with VHF permanent collars. Elk were captured on the eastern portion of the study area, directly overlapping areas including radio collared mule deer and cougar. Sample sizes for elk reflected an estimate of what we believed to be an adequate number of elk to provide an initial estimation of elk spatial use in the study area. Ungulate Survival and Location Monitoring On a daily basis, from December through May, we monitored radioed fawns and adult female deer and elk in order to document live/death status. This allowed us to determine accurately the date of death and estimate the proximate cause of death. For animals not heard from the ground, we conducted weekly flights to assess live/death status. Detailed locations of GPS collared elk became available when self-actuating mechanisms caused the GPS collars to drop-off elk in September 2007. Elk GPS collars collected locations every 30 minutes. Identification of Cougar GPS Location Clusters Characteristics of clusters of GPS locations representing cougar-killed ungulate sites (Anderson and Lindzey 2003, Logan 2005) were used to develop a standard algorithm to group GPS points together, to provide a sound sampling frame from which statistical inference could be made about clusters that are not physically investigated. GPS collars collected locations 4 times/day to reflect time periods when cougars are both active and inactive (00:00, 6:00, 12:00 and 19:00). The clustering routine was designed to identify clusters in five unique selection sets in order to identify clusters containing two or more points, those that contained missing GPS locations, and those that were represented by single points. The clustering algorithm was written in Visual Basic and was 89 �designed to run within ARCGIS (Alldredge and Schuette, CDOW unpubl. data 2006). The widths of the spatial and temporal sampling windows were user specified, in order to meet multiple applications and research needs. This also enabled adjustment of the sampling frames to improve cluster specifications as needed. The initial step was to prepare data files for ARCGIS. The main priority was to number all downloaded GPS lat-long location records consecutively to provide a time stamp that could be used in the program. Failed locations were numbered within the data files to maintain the proper time step (i.e. two locations that were separated by a missing location were time stamped in such a way that the clustering algorithm recognized that a missing location existed between the records). At this point data files were imported to ARCGIS and coordinates converted to UTMs. The initial selection set of clusters (S1) were based on clusters consisting of two or more points within a specified distance and time interval. Working with temporal and spatial variables simultaneously is difficult, so we chose to create an association matrix of the combined variables. The units for time were based on GPS locations so that the time between consecutive downloads was one. Cougar locations are attempted 4 times a day, so that one day consisted of 4 time-steps. The association matrix was then constructed as 1 Aij d max e 1 dij ti tj tmax where Aij was the association in time and space between points i and j, dmax was the maximum distance between two points to be considered a cluster, dij was the distance between points i and j, tmax was the maximum number of time steps between points to be considered in a cluster, and ti and tj were the times for locations i and j. This formula weighted the distance between two locations heavier than the time between two locations. It also caused the association Aij to be negative for any locations that were outside the temporal window (separated by more time-steps than tmax). The association between two locations within the specified time interval was greatest for those locations that were spatially closer together. So, the largest value in the association matrix corresponded to the 2 points that were spatially the closest and within the time interval. Initially, dmax was set at 200 m and tmax was set at 16 time steps [4 DAYS] . The initial cluster was selected by choosing the 2 points with the largest association value from the association matrix. The distance was checked to verify that the points were within the specified maximum distance, dmax, and if so, the centroid of the two points was calculated. An association vector Ac was made by calculating the association among the centroid and all other points using the above formula. If all values in Ac were negative, then no points were within the specified time interval, so no additional points were added to the cluster. Then the greatest association value Acmax was selected from Ac and the distance from the centroid to the point corresponding to Acmax was compared to dmax. If the distance was less than dmax then the point was added to the cluster and a new centroid was calculated using all cluster points and a new vector Ac was constructed using the new centroid. This procedure was repeated until no additional points were added to the cluster because either no points were within the specified time interval or the distance from the centroid to all points was greater than dmax. After each cluster was constructed these points were omitted from the association matrix and a new cluster was started by again selecting the greatest value from the matrix and verifying that the distance between points was less than dmax. Points were again added to this cluster as previously described. This entire procedure was repeated until no 2 locations met the temporal or spatial criteria. 90 �All clusters were given a unique identifier, which was based on the animal identification and the Julian date. This completed the selection set for clusters with two or more locations, which were likely to have a high probability of being a kill site. Additional selection sets were constructed from the remaining points as single location clusters. However, not all locations are equal, so the remaining selection sets were created based on whether points were associated with missing locations and based on distance between consecutive locations. The second selection set (S2) of clusters was created from any 2 points that were within a distance dmiss, and were separated by 1 or more missing locations. The cluster was considered to be the area within the distance dmax of each of the known locations (2 areas make up the cluster, and dmiss was initially set at 500 m). The final 2 cluster selection sets consisted of consecutive points that were within the ranges dmax to d2 (S3) and d2 to d3 (S4). To construct these selection sets, the distance between consecutive points was examined and if the distance was within the range dmax to d2 (500 m) then the initial point was added as a cluster to the set S3, or if the distance was within the range d2 to d3 (1000 m) then the initial point was added as a cluster to the set S4. These single-point clusters were assumed to have radius dmax. Points not used in selection sets S1 through S4 were then used in a final selection set S5. These points represented larger movements between consecutive locations and thus were thought to have low probabilities of being associated with a kill site, although these points could be associated with use of small prey items, or kill sites where a cougar was physically disturbed away from a kill site. These single-point clusters were also assumed to have radius dmax. Sampling of Cougar GPS Location Clusters A primary objective of the pilot study was to determine the probability that a given cluster represented a cougar feeding site. Specifically, to evaluate cougar feeding sites as a function of the cluster association matrix. Using the clustering algorithm described above, we attempt to classify each sampled cluster as a cougar feeding site (1) or not a feeding site (0). We expected a high proportion of S1 clusters to represent cougar feeding sites. Conversely, we expected a moderate proportion of S2 and S3 clusters, and a low proportion of S4 and S5 clusters, to represent cougar feeding sites. A secondary objective of the pilot study was to gather preliminary biological data regarding cougar prey utilization, primarily with respect to deer and elk. The secondary objective was most efficiently accomplished by sampling S1 clusters with greater intensity than other clusters. We therefore structured our sampling approach to allow adequate estimation of the proportion of clusters that were cougar feeding sites for each cluster set, while more intensively sampling S1 clusters than all others. With no previous evidence to indicate similarities among individuals based on sex, age, or parental status, sampling was stratified by each individual cougar. GPS collars were downloaded once a month for each cougar and data were analyzed through the clustering algorithm. Clusters within 2 weeks of the download date were selected for the sampling frame, making the maximum time between the predation event and sampling about 1 month by the time field technicians could get to and assess evidence at each cluster site. Clusters were randomly chosen from each selection set for each individual cougar every month in the following manner: S1 = 2 clusters, S2 = 1 cluster, S3 = 1 cluster, and S4 and S5 = 1 cluster on alternating months. Five clusters were sampled each month for each cougar, for a total of 30 clusters per cougar from 1 November 2006, to 15 July 2008. As time allowed, additional clusters were sampled from the selection sets. Our approach forced constant sampling of each cluster set over time regardless of the frequency of clusters within a given set. This prevented a scenario where nearly all sampled clusters in a given month were from sets, S3, S4 and/or S5 (i.e., low probability of finding feeding sites). Our assessment of prey utilization depended on relatively constant detection of cougar feeding sites over time to avoid bias. 91 �However, for each cluster set, the true proportion of clusters representing feeding sites may possibly change over time corresponding to changes in cougar use of feeding sites. If the GPS download data indicated major changes in set-specific cluster frequencies over the sampling period, we maintained the ability to use a proportional-allocation sampling approach if needed. Assuming a binomial distribution and 0.90 of S1 clusters represented cougar feeding sites, our approach enabled us to estimate the true proportion with a 95% confidence interval of +/ 0.07. Assuming 0.5 of S2 clusters represented cougar feeding sites, we were able to estimate the true proportion with a 95% confidence interval of +/ 0.17. Assuming 0.3 of S3 clusters represented feeding sites, we were be able to estimate the true proportion with a 95% confidence interval of +/ 0.15. Finally, assuming 0.1 of S4 and S5 clusters represented feeding sites, we were able to estimate the true proportion with a 95% confidence interval of +/ 0.10. These precision levels were deemed acceptable for the pilot study, and should facilitate development of an optimal sampling scheme in future years for evaluating cougar prey utilization from GPS cluster-location data. Finally, regarding our secondary objective of collecting preliminary prey use data, we were able to estimate the overall proportion of kill sites represented by deer (or the proportion of kill sites represented by elk) with a 95% confidence interval of +/ 0.05 (Anderson and Lindzey 2003, Logan 2005). We used the following protocol to investigate cougar GPS clusters in the field. For S1 clusters, we investigated each cougar GPS location in the cluster by spiraling out a minimum of 20 m from the GPS waypoint while using the GPS unit as a guide, and visually inspecting overlapping view fields in the area for prey remains. Normally, this was sufficient to detect prey remains and other cougar sign (e.g., tracks, beds, toilets) associated with cougar. If prey remains were not detected within 20 m radius of the cluster waypoints, then we expanded our searches to a minimum of 50 m radius around each waypoint. The 20 m and 50 m radius search areas resulted in overlapping view fields of individual waypoints, and took up to 7 hours to complete, depending upon the number of waypoints, topography, and vegetation type and density associated with a cluster. For S2 through S5 clusters, we went to each cougar GPS location and spiraled out 50 m around each waypoint, while using the GPS unit as a guide. Depending on the number of locations, topography, and vegetation type and density, we spent a minimum of 1 hour and up to 3 hours per cluster to judge whether the cluster was a kill site. Estimating Deer, Elk, and Cougar Distributions We examine locations, movements, and kernel home ranges of mule deer, elk, and cougars for spatial overlap and time synchrony using ArcGIS. Our initial analyses are descriptive and should provide insight into patterns of cougar movements and feeding sites in relation to major ungulate species. Based on past observations, we did not expect deer distributions to fluctuate greatly during the winter. However, we did expect elk distributions to fluctuate depending on weather and time. We anticipated being able to generate correlations between species of prey killed by cougars and the relative presence of prey within cougar home ranges. Cougar GPS Cluster Analysis We estimated the probability of locating cougar prey items (i.e., cougar kills) at GPS location clusters using logistic regression in SAS (PROC LOGISTIC; SAS Institute, Cary, NC). We modeled cougar kills as a function of cluster type (S1, S2,…, S5), cluster size (no. locations/cluster), cougar status (adult female with cubs, adult female without cubs, adult male), and season when cluster was investigated (winter, spring, summer, fall). We then analyzed kill composition using a generalized logits model (i.e., multinomial logistic regression) in SAS (PROC LOGISTIC). For this analysis, we used only clusters where prey items were found (i.e., kills). Kill composition was divided into 5 categories: adult deer, fawn deer, adult elk, calf elk, and other (i.e., porcupine, coyote, turkey, unknown). We modeled kill composition as a function of cluster type, cluster size, cougar status, season when kill occurred, elevation, 92 �and percent vegetative cover. We used Akaike‘s information criterion adjusted for sample size (AICc) to select among candidate models in both modeling analyses (Burnham and Anderson 2002). Hypothesis Testing Our preliminary sampling effort of cougar clusters and ungulate distributions provided estimates of cougar kill rates and proportions of deer and elk killed. As data collection continues, we intend to address whether 1) cougar prey mass is positively related to cougar mass (i.e., male cougars kill larger prey than female cougars), 2) cougars prey on deer and elk in proportion to availability (i.e., no selection for prey species), 3) cougars prey on sex or ages of deer or elk populations in proportion to availability (i.e., no selection for prey age classes), 4) cougars alter their use of prey among seasons of the year (i.e., prey-switch between deer and elk, or between juvenile and adult), and 5) maternal cougar home ranges include the highest available densities of ungulate prey. RESULTS AND DISCUSSION Mule Deer Distribution As expected, over the course of the winter, mule deer movements occurred at too fine of spatial and temporal scales to be detected without more intense repeated sampling. However, as they relate to the pilot study, the data gathered are adequate for making basic summaries. Mule deer density appeared to be highly variable across a gradient of winter range (density estimates ranged between 19 and 109 deer/km2 , Figure 1) (Bergman et al. 2008). Relative to the entire Uncompahgre Plateau, the estimates tended to be high, confirming historical information and further justifying the decision to conduct pilot work in this area. Of particular interest in regards to spatial overlap between cougar kill sites and mule deer winter range, the majority of located kill sites were higher in elevation than the greatest concentrations of mule deer. The exception to this trend occurred on the southern most portion of deer winter range where the majority of kill sites were composed of mule deer. As discussed below, an apparent explanation for this may be linked to elk distribution as this area also appeared to be the area of greatest overlap between mule deer and elk. To improve future efforts, several key steps would need to be taken. Mule deer density estimates are relatively course for the majority of winter range included in this pilot study. With the exception of three polygons, deer density estimates were extrapolated from surrounding areas. Furthermore, estimates of deer density for the 3 areas were not collected during the same year and therefore include annual variation. To accurately reflect the conditions, albeit still at a course level, encountered by cougars as they move across mule deer winter range, density estimates should minimally be collected on all segments of winter range on an annual basis. While fine scale movements of deer (i.e. daily movements within winter range) were not incorporated in this study, such data likely would not be hugely beneficial. Fine scale data would be of greatest interest if the focus of the study were shifted to analyze/describe fine scale hunting behavior of individual cougars. Elk Movement and Distribution Elk GPS collar data confirmed our initial expectations that elk movements during winter months were more dynamic than those of deer. The four elk collared with VHF collars left the study area of interest after 7 months and collecting repeated aerial locations was not deemed worthwhile as they were not in areas with radio marked deer or cougar. However, elk did appear to be highly individualistic in regards to space use and movement during winter months. Two elk appeared to concentrate locations over a relatively large geographic area (>75 km2) during the winter months, but restricted movements to stay within these areas. The other 3 elk appeared to utilize relatively small spatial areas (9-10 km2) for 12 week periods before making slightly longer movements (10+ km) to new concentration areas. Plotting known locations for cougar kill sites on elk spatial data suggested that cougar kill sites had a strong correlation to elk distribution (Fig. 2). Based on the more dynamic nature of elk movement during winter, 93 �future efforts to map elk distributions and densities would be better met by saturating the area of interest with GPS collared elk. Annual density estimates, collected via helicopter, would likely only be valid for a relatively short time period (2-4 weeks) due to elk movement and thus making it difficult to track cougar space use and predation patterns in a realistic prey context. By outfitting a large number of elk with GPS collars, resource selection functions for the elk in the area of interest could be built around habitat and elevation selection patterns. Due the large amount of data collected by GPS collars, resource selection functions could justifiably be built at 2-4 week intervals. Kill Probability Associated with Cougar GPS Clusters We investigated 462 clusters during this pilot study (195 S1 clusters, 33 S2 clusters, 71 S3 clusters, 73 S4 clusters, 90 S5 clusters). The probability of locating cougar kills at GPS location clusters varied as a function of cluster type, cluster size, cougar status, and season (Table 1). As expected, S1 clusters were far more likely to be associated with cougar kills than S2 S5 clusters (Figure 3). The probability of a kill at an S1 cluster was 0.505 (95% CI: 0.435, 0.575), whereas kill probability was ≤ 0.12 at all other cluster types. There was some probability of a kill at S4 and S5 clusters, indicating that isolated cougar locations may periodically be associated with kills and should not be ruled out when using GPS location data to address cougar prey utilization. Kill probability increased as cluster size increased ( ˆ = 0.353, SE = 0.0706). Kill probability exceeded 0.9 with ≥ 10 locations/cluster and approached 1 with ≥ 15 locations/cluster (Figure 4). Thus, the probability of a kill was high if a cougar spent >2 days in the same general area, and a kill was essentially certain if a cougar spent >3 days in the same general area. Models receiving the most weight also provided evidence of interactions between cluster size and cougar status and between cluster size and season. The cluster size × cougar status interaction occurred because smaller cluster sizes were more likely to be associated with kills for female cougars than male cougars (Figure 5). For example, female cougars with ≥ 10 locations/cluster indicated a near-certain kill, whereas male cougars with 10 locations/cluster indicated only 0.571 probability of a kill (95% CI: 0.267, 0.830). Adult males were more likely to spend multiple days in an area without a kill than were adult females. The cluster size × season interaction occurred because larger cluster sizes during summer were less likely to indicate a kill than during other seasons (Figure 6). Perhaps cougars were more likely to remain sedentary without a kill nearby during summer months when energetic demands were lower. This result should be interpreted with caution, however, because we collected less data during summer than during other seasons. Our primary reason for including season in the analysis was to evaluate possible differences in detection probability. We expected kills to be difficult to detect during winter and possibly spring months when carcasses and sign would be periodically covered by snow. However, our results did not support this hypothesis, but instead suggested that kills may have been the most difficult to detect during summer. Kills may be difficult to detect in summer range habitats because of extensive foliage or increases in scavenging by bears and/or coyotes. Regardless, carcass detection probability is a significant issue that underlies our entire analysis. That is, it is difficult to fully interpret our findings above without an adequate understanding of detection probability. For example, our summer results could reflect reduced carcass detection probability during summer, or they could reflect changes in cougar behavior during summer as compared to other months. A key point is that our estimates of kill probability for different cluster types and sizes are minimum estimates because these estimates assume detection probability was 1, which is unlikely. Detection probability should be addressed in subsequent research. Cougar Kill Composition Cougars killed adult deer, fawn deer, adult elk, and calf elk in nearly equal proportions (Figure 7). Each prey class comprised 0.22 0.24 of the total kill. Kill composition varied as a function of percent vegetative cover and elevation (Table 2). Adult elk were more likely to be killed in areas with little cover whereas calf elk, adult deer, and other species were more likely to be taken in habitats with heavier cover 94 �(Figure 8). Adult elk and adult deer were more likely to be killed at lower elevations whereas calf elk and other species were more likely to be killed at higher elevations (Figure 9). Unexpectedly, kill composition did not vary in response to cluster type or cluster size (Figure 10). Kill composition could be biased if S1 clusters, or larger cluster sizes, were associated with larger prey items, because it would suggest that larger prey may be more easily detected. However, given that kills of different sized prey occurred in roughly equal probabilities across all cluster sizes, restricting sampling to larger clusters would not necessarily bias kill composition estimates, at least for ungulates. Efficiency would be gained in the field by sampling larger clusters because they are more likely to be associated with kills. Additional data collection will be necessary to determine whether this preliminary finding is valid. Also, we urge caution interpreting this result because it is not biologically intuitive and would lead to biased kill composition data if proven incorrect. SUMMARY Over the past 2 years we have collected data on elk and deer distributions in conjunction with cougar predation data across the southern half of the Uncompahgre Plateau. Part of this effort included the development and implementation of a sampling based approach to estimate cougar kill rates and prey selection from GPS location data. Based on this effort we were able to randomly sample clusters of cougar GPS locations in relation to cluster type/size, which presumably correlates to prey selection and handling time. Mule deer and elk distributions on winter range were as expected with mule deer utilizing lower elevations and elk utilizing both lower and higher elevations with an area of overlap between the two species across deer winter range. Interestingly, cougar kill sites for mule deer generally occurred at midelevations within the range of overlap for deer and elk. Cougar kill sites for elk occurred at all elevations characteristic of elk distribution. As expected, cougar clusters with a large number of points had a high probability of being associated with a predation event and those with few points had a lower probability, especially single point clusters that are spatially distinct from other points. However, evidence of predation was identified at some of the spatially distinct single point clusters, indicating that these types of clusters are important in accurately describing cougar diet composition and predator/prey interactions. The association between cluster size and the probability of a cougar kill was related to season and cougar sex, with larger clusters being less predictive of a kill during summer and for males. Cougars killed elk and deer in approximately equal proportions and killed fawns/calves in equal proportion to adults for both deer and elk. Other prey items that could be detected at GPS locations comprised less than 10% of cougar diets. LITERATURE CITED Anderson, C. R., Jr., and F. G. Lindzey. 2003. Estimating cougar predation rates from GPS location clusters. Journal of Wildlife Management 67:307-316. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M. 1983. Composition and quality of mule deer diets on pinyon-juniper winter range, Colorado. Journal of Range Management 36:534-541. Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. Bergman, E.J., C.J. Bishop, D.J. Freddy and G.C. White. 2005. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, July: 23-35. Colorado Division of Wildlife, Fort Collins, USA. 95 �Bergman, E.J., C.J. Bishop, D.J. Freddy and G.C. White. 2008. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, July: In Press. Colorado Division of Wildlife, Fort Collins, USA. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second Edition. Springer-Verlag, New York, New York, USA. Creel, S. and N.M. Creel. 2002. The African wild dog: behavior, ecology and conservation. Princeton University Press, New Jersey, USA. Keeling, M.J., H.B. Wilson and S.W. Pacala. 2000. Reinterpreting space, time-lags, and functional responses in ecological models. Science 290:1758-1761. Krebs, C.J., S. Boutin and R. Boonstra, eds. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, USA. Kunkel, K. E., and D. H. Pletscher. 1999. Species-specific population dynamics of cervids in a multipredator ecosystem. Journal of Wildlife Management 63:1082-1093. Kunkel, K. E., T. K. Ruth, D. H. Pletscher, and M. G. Hornocker. 1999. Winter prey selection by wolves and cougars in and near Glacier National Park, Montana. Journal of Wildlife Management 63:901-910. Lima, S.L. and P.A. Bednekoff. 1999. Back to the basics of antipredatory vigilance: Can nonvigilant animals detect attack? Animal Behaviour 58:537-543. Logan, K.A. 2005. Cougar population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report, July: 105-126. Colorado Division of Wildlife, Fort Collins, USA. Mathews, C.G., J.A. Lesku, S.L. Lima and C.J. Amlaner. 2006. Asynchronous eye closure as an antipredator behavior in the western fence lizard (Sceloporus occidentalis). Ethology 112:286-292. Mao, J.S., M.S. Boyce, D.W. Smith, F.J. Singer, D.J. Vales, J.M. Vore and E.H. Merrill. 2006. Habitat selection by elk before and after wolf reintroduction in Yellowstone National Park. Journal of Wildlife Management 69:1691-1707. Mitchell, W.A., and S.L. Lima. 2002. Predator-prey shell games: large-scale movement and its implications for decision making by prey. Oikos 99:249-259. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. Roth, T.C., II, S.L. Lima and W.E. Vetter. 2006. Determinants of predation risk in small wintering birds: the hawk's perspective. Behavioral Ecology and Sociobiology 60:195-204. Ryall, K.L. and L. Fahrig. 2006. Response of predators to loss and fragmentation of prey habitat: a review of theory. Ecology 87:1086-1093. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. Schmitz, O.J. 2006. Predators have large effects on ecosystem properties by changing plant diversity, not plant biomass. Ecology 87:1432-1437. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. Werner, E.E. and S.D. Peacor. 2006. Lethal and nonlethal predator effects on an herbivore guild mediated by system productivity. Ecology 87:347-361. Wilmers, C.C., E. Post, R.O. Peterson and J.A. Vucetich. 2006. Predator disease out-break modulates top-down, bottom-up and climatic effects on herbivore population dynamics. Ecology Letters 9:383-389. Prepared by Mathew W. Alldredge, Eric J. Bergman and Chad J. Bishop, Wildlife Researchers 96 �Table 1. Model selection results, based on Akaike‘s Information Criterion with small sample size correction (AICc), of an analysis evaluating the probability of locating cougar prey items (i.e., cougar kills) at GPS location clusters. We modeled cougar kills as a function of cluster type (type; S1, S2,…, S5), cluster size (size; no. GPS locations/cluster), cougar age and sex status (status), and season when cluster was investigated (season; spring, summer, fall, winter). Model Type size season size×season Type size status season size×status size×season Type size status season size×season Type size Type size season Size status season size×status size×season Size season size×season Type size status season Size status season size×season Size status size×status No. Parameters AICc Delta AICc Model Weight 12 16 14 6 9 12 8 11 10 6 365.61 367.84 369.68 370.75 371.80 373.04 374.80 375.71 378.87 380.07 0.00 2.22 4.07 5.13 6.19 7.42 9.19 10.10 13.25 14.46 0.615 0.202 0.081 0.047 0.028 0.015 0.006 0.004 0.001 0.000 Table 2. Model selection results, based on Akaike‘s Information Criterion with small sample size correction (AICc), of an analysis evaluating cougar kill composition at GPS location clusters. We modeled kill composition as a function of cluster type (type; S1, S2,…, S5), cluster size (size; no. GPS locations/cluster), cougar age and sex status (status), season when kill occurred (season; spring, summer, fall, winter), elevation (elev), and percent vegetative cover (cover). Model Elevation cover Elevation cover status Cover Elevation Size elevation Status Status season size elevation cover Size Season Status season size elevation No. Parameters AICc Delta AICc Model Weight 12 20 8 8 12 12 36 8 16 32 347.81 353.25 356.35 366.44 371.41 385.84 386.30 386.47 389.36 399.07 0.00 5.45 8.54 18.64 23.60 38.04 38.49 38.67 41.55 51.27 0.926 0.061 0.013 0.000 0.000 0.000 0.000 0.000 0.000 0.000 97 �Figure 1. Location of pilot predator-prey research on the Uncompahgre Plateau, southwest Colorado. Ongoing deer research study areas are reflected by red and blue polygons with hash marks, as well as by solid yellow polygons. The ongoing lion research study area is designated by the large red polygon. Figure 2. Distribution of cougar kill sites (red circles) in relation to mule deer winter range on the southeast portion of the Uncompahgre Plateau, Colorado. Black polygons represent segments of mule deer winter range where density estimates were either estimated or extrapolated to by surrounding areas on which estimates were measured. Gray lines represent Game Management Unit boundaries as designated by the Colorado Division of Wildlife. 98 �Figure 3. Distribution of cougar kill sites (red circles) in relation to GPS collar locations for 5 elk (black circles) on the southeast portion of the Uncompahgre Plateau, Colorado. Gray lines represent Game Management Unit boundaries as designated by the Colorado Division of Wildlife. Figure 4. Probability of a cougar kill at different types of GPS location clusters (with 95% CIs), Uncompahgre Plateau, Colorado, 2006 2008. Refer to the Methods section for a detailed explanation of cluster types. 99 �Figure 5. Probability of a cougar kill as a function of the number of locations in a GPS cluster (with 95% CI), Uncompahgre Plateau, Colorado, 2006 2008. Figure 6. Probability of a cougar kill at GPS location clusters relative to sex and reproduction status (with 95% CIs), Uncompahgre Plateau, Colorado, 2006 2008. Cougar status was defined as single adult female (AdFemSingle), adult female with cubs (AdFemCubs), or adult male (AdMale). 100 �Figure 7. Probability of a cougar kill at GPS location clusters by season (with 95% CIs), Uncompahgre Plateau, Colorado, 2006 2008. Figure 8. Prey composition of cougar kills (with 95% CIs) on the Uncompahgre Plateau, Colorado, 2006 2008. Prey items included adult deer (AdDeer), ≥ 6-month-old fawn deer (FwnDeer), adult elk (AdElk), calf elk (CalfElk), and other species (e.g., porcupine, turkey, coyote). 101 �Predicted probabilities Percent cover Figure 9. Predicted prey composition of cougar kills as a function of vegetative cover (with 95% CIs), Uncompahgre Plateau, Colorado, 2006 2008. 102 �Predicted probabilities Elevation Figure 10. Predicted prey composition of cougar kills as a function of elevation (m) (with 95% CIs), Uncompahgre Plateau, Colorado, 2006 2008. 103 �Predicted probabilities No. locations/cluster Figure 11. Predicted prey composition of cougar kills as a function of the number of locations comprising a GPS location cluster (with 95% CIs), Uncompahgre Plateau, Colorado, 2006 2008. 104 �Colorado Division of Wildlife July 2007 −June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Predatory Mammals Conservation Puma Population Structure and Vital Rates On the Uncompahgre Plateau Period covered: July 1, 2007−June 30, 2008 Author: K. A. Logan. Personnel: K. Logan, B. Bavin, B. Dunne, J. Timmer, V. Yovovich, S. Waters, K. Crane, T. Mathieson, M. Caddy, and T. Bonacquista of CDOW; S. Young, and J. McNamara of U.S.D.A. Wildlife Services; volunteers and cooperators including: private landowners, Bureau of Land Management, Colorado State Parks, Colorado State University and U.S. Forest Service, with supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Research continued on puma population characteristics and dynamics on the Uncompahgre Plateau. All capture efforts in 2007-08 resulted in a total of 41 puma captures (9 adult females [1 adult female captured 3 times], 6 adult males [1 adult male captured 2 times], 1 subadult male, and 21 cubs [4 of them captured twice each]). Two adults, 4 subadults, and 16 cubs were captured for the first time. As of July 2008, there were 18 adults, 1 subadult, and 4 cubs marked with active radio-collars. Efforts to capture, sample, and mark pumas with the use of trained dogs extended from November 19, 2007 to April 24, 2008. Those efforts resulted in 77 search days, 217-218 puma tracks detected, 49 pursuits, and 20 puma captures. In 2007-08, capture efforts with ungulate carcasses and cage traps resulted in 1 adult male being captured twice. One cub was captured for the first time with dogs, and 15 cubs were caught the first time by hand. Capture and search efforts from November 2007 through March 2008 enabled us to estimate a minimum of 33 independent pumas detected on the Uncompahgre Plateau study area during that time, including 21 females and 12 males. Preliminary puma population parameters estimated during the past 3.7 years of research, included: population sex and age structure, reproduction rates, and survival rates. Data on puma reproduction rates included: average litter size = 2.810 ± 0.9808 SD, n = 21; average birth interval (mo.) = 17.969 ± 4.748 SD, n = 13; average proportion of adult females producing cubs each year = 0.65 ± 0.0586 SD, n = 12-13 females for 3 yr.; secondary sex ratio = 33:26, consistent with 1:1; and average gestation length (day) = 91.188 ± 2.3443 SD. Puma births occurred March through September. Survival rates for both adult and subadult pumas in this reference period appear to be high, and might reflect the relatively small samples of individual pumas in each age-stage and sex and years. Cub survival ranged from 0.50 (Kaplan-Meier procedure) to 0.56 (binomial model). The main cause of 105 �mortality in the adults and cubs is caused by male pumas. A puma population model was developed for researchers and wildlife managers to assess scenarios of puma harvest management strategies. Results from a set of scenarios and attendant models are presented. Only 1 puma family with a radio-collared mother and cub could be monitored during the winter to assess association distances during aerial locations. The aggregate data gathered during the past 3 winters generally indicate that mothers were usually within 520 m of their cubs during the day. Preliminary comparisons between our current puma research on the Uncompahgre Plateau (3.7 years duration) and results of the Anderson et al. (1992) puma research on the plateau (7 years duration 1981-1988) were made where appropriate. Proposed work includes: continuing to quantify puma population characteristics and vital rates, with an emphasis on increasing sample sizes on radio-monitored adults, subadults, and cubs, and developing a study plan for the next 6 years of research, which will include the treatment period. We will collaborate with colleagues to assess puma health and model and map puma habitat. 106 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates; begin puma population modeling process; and plan for the remaining 6 years of the Uncompahgre Plateau Puma Project― all to improve the Colorado Division of Wildlife‘s (CDOW) model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. 5. Continue gathering data on puma population sex and age structure. Continue gathering data for estimates of puma reproduction rates. Continue gathering data to estimate puma sex and age-stage survival rates. Continue gathering data to estimate agent-specific mortality rates. Develop a puma population model and parameter estimates useful for guiding decisions about the hunting treatment phase of this project, and for the Data Analysis Unit puma management planning process performed by CDOW biologists and managers. 6. Gather data on spatial relationships of puma mothers to their cubs during the Colorado puma hunting season as a preliminary assessment of the vulnerability of puma mothers to sport-hunting harvest. 7. Develop a study plan for remaining 6 years of puma population research on the Uncompahgre Plateau Study Area. 8. Evaluate other data sources that could come from this research that can be developed into other puma research relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing puma while ―achieving healthy, self-sustaining populations‖(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW‘s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CDOW staff and public stakeholders form the basis of Colorado‘s puma research program, with multiple lines of inquiry (i.e., projects): 107 �Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field experiments. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared pumas. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage-specific survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CDOW‘s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of population abundance (i.e., numbers and density) and attendant annual population growth rates, such as, direct mark-recapture, and DNA genotype capture-recapture. A descriptive study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. The treatment period will involve the use of controlled recreational hunting to manage the puma population. 108 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Recreational puma hunting management in Colorado Data Analysis Units (DAUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft LDAU Plans, 2004, CDOW 2007). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,  for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing  include population density, sex and age structure, female age-at-first-breeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H1: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed = 1.15. 2. The key assumption is that the CDOW can manage puma population growth through recreational hunting: for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). H2: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a decline of the harvest-age segment of the population by the beginning of the next hunting season. 3. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H3: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a decline in the abundance of harvest-age pumas (i.e., adults and subadults). Considering limitations (i.e., methods, number of years, assumption violations) to the Colorado-specific studies on puma densities cited above (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973, Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0―4.6 puma/100 km2 to extrapolate to DAUs to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using capture, mark, re-capture techniques developed and refined during the study to estimate the puma population, the following will be tested: 109 �H4: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0―4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help those managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for estimating puma abundance (e.g., capture-mark-recapture) of known reliability will allow managers to ―ground truth‖ modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will require development of reliable monitoring techniques based on capture-mark-recapture methods and models. Potential methods include direct and DNA genotype capture-recapture, and assessments of harvest sex and age structure. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties. The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinon-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and 110 �domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Experimental Treatment Periods This research is structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period is expected to cause a population increase phase. The treatment period will involve structured puma management strategies. In both phases, puma population structure, and vital rates will be quantified, and some management assumptions and hypotheses regarding population dynamics and effects of harvest will be tested. Contingent upon results of pilot studies, we will also estimate puma numbers, population growth rates, evaluate enumeration methods, and test other hypotheses (Logan 2004). The reference period, without recreational puma hunting as a major limiting factor, is consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000―12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma evolution in western North America for the past 100 years. Hence, the reference period, years 1―5, will provide conditions where individual puma in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factors will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before the treatment (i.e., controlled recreational hunting). In the reference period, all puma in the study area will be protected, except for individual puma that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged puma that range in a buffer zone, that includes the northern halves of GMUs 61 and 62, will be protected from recreational hunting. The reference period will allow researchers to quantify baseline demographic data on the puma population to estimate parameters for the CDOW‘s model-based approach to puma management. Moreover, it will allow researchers to develop and test puma enumeration methods when population growth is known to be in one direction― increasing. Without the hunting closure, pilot data for enumeration methods could be confounded by not knowing if the population was increasing, declining, or stable. The reference period will also facilitate other operational needs (because hunters will not be killing the animals) including the marking of a large proportion of the puma population for capture-markrecapture estimates, and the gathering of movement data from GPS-collared puma to help formalize exact sampling designs for enumeration methods. During the treatment period, years 6―10, experimentally structured recreational puma hunting will occur on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW‘s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase and population suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, puma survival will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared puma. For managers, demonstrating that they can manage puma populations with hunting and achieve the CDOW strategic objective of managing for a healthy, self- sustainable puma population state-wide is important. Dynamics of the puma population may be manipulated (i.e., increase and decline phases) to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative 111 �vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting), enumeration methods, and puma―prey interactions (i.e., lines of research identified in the Colorado Research Program, Fig. 1). The killing of tagged and collared puma during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a large majority of independent puma in the population will be marked, and sampling schemes will be formalized. Puma on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared puma have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that puma live at low densities and capturing puma is difficult, as a starting point, our logistical aim will be to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim is to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of puma might represent the large majority of the puma population on the study area, and will provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration rates, and movement data pertinent to sampling designs for various projects. Assuming that the puma population density on the study area is relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio is equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might be 22 adults, 11 males and 11 females. Also assuming that the total population contains 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might be 4 subadults and 13 cubs with equal sex ratios in a total population of 39 puma. If we achieve our logistical aim in the first 1―2 years (recognizing that the population might grow), then we should be able to quantify population characteristics and vital rates for a majority of the puma population in those years and build upon the tagged number in each subsequent year. Thus, our inferences will pertain to the large majority of the puma population, if not the population on the study area, instead of a relatively small sample of it. We anticipate it may take 2 years to mark the large majority of puma in the population. In addition, the study area is large and will require some time to learn to access it efficiently. Puma capture and handling procedures have been approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured puma will be examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Age of adult puma will be estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub puma will be estimated initially based on dental and physical characteristics of known-age puma (Logan and Sweanor unpubl. data). Body measurements recorded for each puma will include at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections will include: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags) and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) and fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma will be fixed via Global Positioning System (GPS, North American Datum 27). Puma will be captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs will be conducted mainly during the winter when 112 �snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area will be searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, walking, and possibly horse- or mule-back. When puma tracks ≤1 day old are detected, trained dogs will be released to pursue puma to capture. Puma usually climb trees to take refuge from the dogs. Adult and subadult puma captured for the first time or requiring a change in telemetry collar will be immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent will be delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net will be deployed beneath the puma to catch it in case it falls from the tree. A researcher will climb the tree, fix a Y-rope to two legs of the puma and lower the cat to the ground with an attached climbing rope. Once the puma is on the ground, its head will be covered, its legs tethered, and vital signs monitored (Logan et al. 1986). (Normal signs: pulse ~70―80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95―104oF) (Kreeger 1996). A cage trap will be used to capture adults, subadults, and large cubs when puma can be lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). Efficiency of the trap might be enhanced by using an automated digital call box that emits puma vocalizations (Wildlife Technologies, Manchester, NH). A cage trap will be set only if a target puma scavenges on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers will continuously monitor the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allows researchers to be at the cage to handle captured puma within 30 minutes. Puma will be immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized puma will be restrained and monitored as described above. If non-target animals are caught in the cage trap, we will open the door and allow the animal to leave the trap. Foot-hold snares will be used to capture adults, subadults, and large cubs only when safe snare sites at puma kills can be located as described by Logan et al. (1999). Snares set at puma kills will be monitored continuously with VHF beacons on the snares from about 1 km distance. We will not set snares at sites where tracks indicate that other mammals (e.g., deer, elk, bear, bighorn sheep, livestock) are also active. Puma will be immobilized with Telazol injected into the caudal thigh with a pole syringe. Vital signs will be monitored during the handling procedures. Efficiency of snares might also be enhanced with the use of an automated call box with puma or prey vocalizations. Small cubs (≤10 weeks old) will be captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs will be restrained inside new burlap bags during the handling process and will not be administered immobilizing drugs. Cubs at nurseries will be approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries will be removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes are complete, cubs will be returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Puma do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual puma is essential to a number of project objectives, including estimating vital rates and gathering movement data on puma to formalize designs for developing and testing enumeration methods. Adult, subadult, and cub puma will be marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna is permanent and cannot be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) will be inserted into each 113 �pinna to facilitate individual identification during direct recaptures. Cubs 10 weeks old will be eartagged in only one pinna. Locations of GPS- and VHF-collared puma will be fixed about once per week (as flight schedules and weather allow) from light fixed-wing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). This monitoring will enable researchers to find GPS-collared puma to acquire remote GPS location reports from the ground, monitor the status (i.e., live or dead) of individual puma, and to recover carcasses for necropsy. It will also provide simultaneous location data on mothers and cubs. GPS- and VHF-collared puma will be located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals will be mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations will be plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes will be recorded on standard forms. GPS locations will be mapped using GIS software. Adult and subadult female pumas will be fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada). Initially, GPS-collars will be programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for puma will provide precise, quantitative data on puma movements mainly to provide data to formalize study designs, to test assumptions for capture-mark-recapture methods for this project, and to assess the relevance of puma DAU boundaries. The GPS-collars also will provide basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and predation frequency on mule deer and elk. Subadult male pumas will be fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male puma reach adulthood on the study area, we will recapture them and fit them with GPS collars. VHF radio transmitters on GPS collars will enable researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and physical status. VHF transmitters on GPS- and VHF-collars will have a mortality mode set to alert researchers when puma have been immobile for 3 to 24 hours so that dead puma can be found to quantify survival rates and agent-specific mortality rates by gender and age. We will attempt to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar (Wildlife Materials, Murphysboro, Illinois, HLPM-2160, ~50g, or Telonics, Inc., Mesa, Arizona MOD 210, ~100g,) when cubs weigh 2.3―11 kg (5―25 lb). Cubs with mass ≥11 kg can still wear these small expandable collars until they are about 12 months old. Cubs approaching the age of independence (~11―14 mo. old) may be fit with Lotek LMRT-3 VHF collars (~400 g) with expansion links. Cubs will be recaptured to replace collars as necessary. Monitoring radio-collared cubs allow quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Capture-Mark-Recapture: Capture-mark-recapture methods will be evaluated initially as a pilot study. Capturing and marking puma is time consuming, and would lengthen the time to thoroughly search the study area for capturing and marking puma during capture-recapture occasions needed for population estimation. Therefore, we will capture and mark pumas prior to performing capture-recapture or re-sight occasions using methods such as houndsmen teams. In addition, by marking puma before capturerecapture occasions begin, we will have opportunities to capture female puma at different stages of their reproductive status, and thus reduce the chance that mothers in a stage with suckling cubs and small activity areas are not detected and marked on the study area. After cubs are weaned, the mothers‘ activity area expands (Logan and Sweanor 2001). The probability of females having suckling cubs in winter is 114 �naturally small; that season exhibits the lowest rate of births (Logan and Sweanor 2001). Capturerecapture occasions to estimate the population of independent puma may not begin until we have a large majority of the puma population sampled and marked. Occasions performed at that time will be viewed as a pilot study allowing us to examine the logistics of the field methods, the extent to which model assumptions are met, performance of field methods (e.g., detection differences by sex or life stage as revealed by GPS data on collared puma), and precision of capture-recapture models used to estimate the puma population. Analytical Methods Population Characteristics: Population characteristics each year will be tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allow, age categories may be further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates will be estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male puma (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared puma will provide known fate data which can be used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989), binomial survival model (Williams et al. 2001:343-344), or analyzed in program MARK (White and Burnham 1999, Cooch and White 2004). Agent-specific mortality rates can be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Cub survival curves for each gender will be plotted with survival rate on age in months (Logan and Sweanor 2001:119). Population Estimates: Capture-recapture models will be evaluated initially as a pilot study to estimate the parameters of primary interest― absolute numbers of independent puma (i.e., number of adult and subadult puma present in the survey area) and puma density (i.e., number of independent puma/100 km2) each winter― December through March― when snow facilitates detection and capture of puma, provided that we meet model assumptions. The December―March period also corresponds with Colorado‘s puma hunting season. The population of interest is independent puma (i.e., adults and subadults) because those are the puma that can be legally killed by recreational hunters. Furthermore, adults comprise the breeding segment of the population and subadults are non-breeders that are potential recruits into the adult population in ≤1 year. Thus, the sampling unit is the individual independent puma (~≥1 yr. old). Basic assumptions for closed capture-recapture models are: (1) the population is closed; (2) animals do not lose their marks during the interval; (3) all marks are correctly noted and recorded at each trapping occasion; (4) each animal has a constant and equal probability of capture on each capture occasion. Open population models allow the assumption of closure to be relaxed (Otis et al. 1978, White et al. 1982, Pollock et al. 1990). The robust design is a combination of closed and open models; thus, assumptions are a combination of the assumptions for closed and open population methods (Kendall 2001). To analyze capture-recapture data, closed, open, and the robust design models are available in program MARK. Akaike‘s Information Criterion will be used to select the most parsimonious models based on AICc score ranks and the difference in AIC (∆AIC) between models (Burnham and Anderson 1998). MARK results also include estimates of abundance. 115 �Because the precision of estimates for small populations is sensitive to the probability of capture (White et al. 1982, Pollock et al. 1990), our operational goal will be to achieve capture probabilities of ≥0.4 for each animal per capture occasion (see Results and Discussion, Segment Objective 7). In addition, behavior, movements, survival and mortality of GPS- and VHF-collared puma will allow direct biological examinations of assumptions of geographic and demographic closure (White et al. 1982) and variation in capture probability of individual puma and puma classes (i.e., adult females, adult males, subadult females, subadult males). If capture probabilities vary by puma class, we will examine if data stratification is necessary or possible (depending upon sample size). For example, we might expect the larger home ranges of male puma to expose them to more search routes, thus, this may increase their probability of capture. If the assumption of demographic closure cannot be satisfied, then open population models and the robust design would be more appropriate (Pollock et al. 1990, Williams et al. 2001). Collared puma will allow us to determine the number of marked puma present in the search area each capture-recapture occasion. Furthermore, GPS locations (4 fixes/day) on individual puma will provide data on the probability that puma may temporarily move out of and back into the survey area between capture occasions. Unmarked puma that are subsequently GPS-collared should provide such information, too. ArcView geographic information system software will be used to map and analyze puma locations, movements, and home ranges. It will also be used to map and quantify attributes of the study area and sampling frames. Rate of Population Increase: Finite rates of increase ( Nt+1/Nt) between consecutive years and average annual rates of increase (r) for 3- to 5-year periods and levels of precision will be calculated (Caughley 1978, Van Ballenberghe 1983) and plotted. Functional Relationships: Graphical methods will be used to examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination can be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman‘s rank correlation coefficient, can also be used to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Statistical analyses will be performed using SYSTAT and SAS software. RESULTS AND DISCUSSION Segment Objective 1 Field research to quantify puma population structure, vital rates, and causes of mortality for this report extended from August 2007 to July 2008. Our searches to detect puma presence covered the entire study area. We made 41 puma captures during the period (9 adult females [1 adult female captured 3 times], 6 adult males [1 adult male captured 2 times], 1 subadult male, and 21 cubs [4 of them captured twice each]), resulting in 2 adults (1 female, 1 male), 4 subadults (2 females, 2 males), and 16 cubs (7 females, 9 males) captured for the first time in 2007-08. Trained dogs were used as our main method to capture, sample, and mark adult and subadult pumas from November 19, 2007 to April 24, 2008. Those efforts resulted in 77 search days, 217-218 puma tracks detected, 49 pursuits, and 20 puma captures (Table 1). Puma capture efforts (i.e., search days) with dogs in this period was similar to our efforts in the 3 previous winters (Table 2). But, the frequency of tracks encountered and pursuits increased over the 3 previous periods. Our capture rate 116 �declined slightly probably due to our ability to identify radio-collared pumas associated with tracks (see later), thus, negating the need to capture the pumas directly with dogs. Seven adult and subadult pumas were captured for the first time (Table 3). This includes 1 adult female puma that could not be handled for safety reasons (Tables 4). One large cub, and 1 adult female were each recaptured twice, but could not be handled for safety reasons. One GPS-collared male puma was visually observed in association with an adult female puma we recaptured with dogs, but the male puma was not be bayed by the dogs (Table 4). The age structure of independent pumas captured for the first time continues to suggest that we have been studying a relatively young age-structured puma population that is increasing in the current reference period (Figure 2). Our puma capture efforts using ungulate carcasses and cage traps extended from August 7, 2007 to July 15, 2008. We used 59 road-killed mule deer, 1 road-killed elk, and 1 puma-killed mule deer as bait at 15 different sites to capture one adult male puma 2 times (Tables 5). The puma-killed deer was used as bait at another site after puma F30 abandoned the carcass after we set a camera trap at her cache to obtain photos of the number of marked cubs in her family to confirm survival data. Pumas scavenged 11 of 60 (18.3%) of the ungulate carcasses used for bait. This was slightly lower than results of the last 2 years (i.e., 20%, 22.5%). Other carnivores that used the ungulate baits included: black bear, coyote, and bobcat. Recaptures of 11 to 12 individual marked pumas were made 17 times with the use of dogs and cage traps; GPS/VHF collars were replaced as needed (Table 6). This included puma M27 (which wore a non-functional GPS collar) that was treed twice north of the study area by a puma hunter (Stan Garvey, Nucla) using dogs. The hunter reported the observation of the tagged animal (including, ear-tag number, and a visible hole in the GPS unit battery box), dates, and locations to principal investigator K. Logan. One recapture was of puma cub M44 (offspring of F7) made by Wildlife Services personnel responding to puma depredation on domestic sheep on the study area. The Wildlife Service houndsman released dogs on the puma tracks, and subsequently treed M44 and shot him to control the depredation. In another instance, a researcher visually observed a GPS-collared male puma in association with puma F23 as we pursued both pumas with dogs. Neither of the pumas had functioning GPS collars at the time. The GPS-collared male puma was either M27 or M29, as those 2 adult males were the only GPS-collared males that ranged in that area. The dogs treed F23, but they did not bay the male puma to enable us to obtain exact identity. We also captured 16 cubs (9 male:7 female) for the first time (Table 7). Seven cubs were radiocollared, including zero to 2 cubs collared in each of 7 litters (Appendix A). One 18 kg female cub was treed by our trained dogs, and immobilized with a pole syringe for safe handling. The other 15 cubs were handled without anesthetics at their nurseries when they were 28 to 40 days old. The litters were produced in May (3), June (2), and July (2). In addition to our direct puma captures, we identified 11 previously marked adult pumas that we detected 34 times initially by snow-tracking (Table 8). Upon detecting puma tracks that were roughly aged at 1 to 2 days old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be < 1 km from the tracks and in direction of travel of the tracks. GPS data from pumas with functional GPS collars provided confirmatory information about movements of pumas. If GPS data indicated that the puma moved through the area at the time the tracks were made in snow, then we ruled the data were confirmatory. A large majority (i.e., 70%) of confirmatory data is a combination of radio-telemetry and GPS data. One snow track was assigned to a male puma only using GPS data, apparently because he had moved sufficiently far enough away so we did not receive radio signals at the time we found his tracks. If the GPS data did not indicate movement through the area, but the puma probably had sufficient time between fixes to foray to the tracks from proximate GPS locations, then we decided the GPS data were inconclusive. None of the GPS data clearly indicated that an individual puma could not have been the one we initially identified by radio-telemetry. 117 �In one instance, principal investigator K. Logan visually observed puma F25 attack a mule deer after following up her tracks with radio-telemetry. If we could not identify a collared puma in association with 1-day-old puma tracks, then we released the dogs in attempt to capture the puma. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with non-functioning radio- or GPS-collars. This approach would also be useful in a rigorous mark-recapture effort where radio-collared pumas are available. Our search efforts throughout the study area also revealed the presence of at least 9 other independent females and 1 independent male. We could separate the activity of these pumas from the GPS- and VHF- collared pumas in time and space. Moreover, females in association with cubs of different counts and sizes enabled us to separate 5 adult females followed by 1 to 3 medium-to-large-size cubs. One adult female with 1 large dependent cub was treed, but could not be handled safely. She initially treed, which provided us with an excellent visual observation; but, she left the tree and escaped into a system of sink holes that were too unstable (i.e., dangerous) for researchers to enter. Another adult female with 2 medium-size cubs was pursued with dogs, but was not captured. It was the same situation with another adult female with 2 to 3 medium-size cubs in a different area. The tracks we found of the other pumas were too old to pursue (i.e., probability of capture with the dogs was negligible). Our search and capture efforts during November 2007 through April 2008 enabled us to estimate a minimum count of 33 independent pumas detected on the Uncompahgre Plateau study area, up from a minimum count of 24 independent pumas during the November 2006 to May 2007 period. This estimate was based on the number of known radio-collared pumas, the observation of one non-collared puma, and detection of tracks of suspected non-collared pumas on the study area (explained previously). In addition to the independent pumas, we also counted a minimum of 20 to 21 cubs. The sex and age structure of the minimum puma count is in Table 9. Of the 33 independent pumas, 23−24 (70−73%) were marked and 9−10 (27−30%) were assumed to be unmarked animals. Of the expected unmarked pumas, 8−9 were females and 1 was male, which might reflect lower detection rates of females. There appears to be variation in puma numbers on the west and east slopes of the study area. The west slope count includes 12 independent pumas (8 females, 4 males). The east slope count includes 21 independent pumas (13 females, 8 males). We used the minimum puma count and population structure in an effort to develop puma population models to simulate expected puma population dynamics in the remainder of the reference period and expected results of harvest management for the treatment period on the Uncompahgre Plateau Puma Project. Moreover, the models can be used by CODOW wildlife managers and biologists as a tool to explore expected outcomes of puma harvest management strategies in Colorado (see Segment Objective 5). Anderson et al. (1992) studied pumas on the east slope of the Uncompahgre Plateau (i.e., GMU 62) during 1981 to 1988. Sport-hunting was banned during that study to investigate an ―unexploited‖ puma population (Anderson et al. 1992:5). As our current effort results in larger samples and progresses in time through the reference and treatment periods, similarities and differences in results of the 2 research efforts, now separated by more than 15 years, should illuminate reliable knowledge for puma management in Colorado. Our current puma research on the Uncompahgre Plateau has been underway for 3.7 years (compared to 7 years of Anderson et al. 1992). Our data analysis at this stage of the research is not by any means exhaustive or complete because we are still in the intensive data-gathering phase, yet, our data allows some preliminary comparisons with Anderson‘s (1992) completed work. In the Anderson et al. (1992) study, the average capture effort with dogs was 91.1 days per winter (range = 32 to 136, n = 7) resulting in an average capture effort of 13.9 days per puma. Of 189 pursuits of pumas, 110 (58%) were successful (either of radio-collared or non-collared animals). Anderson et al. (1992) focused on capturing pumas >27 kg in body mass while avoiding pumas <27 kg in mass. They captured 47 pumas with dogs for an average capture rate of 13.9 days per puma. Eight other pumas, all 118 �female cubs ≤ 7 months old, were caught in steel leg-hold traps by trappers, and were added to the study animal population. Two other cubs were killed by the dogs. In total, Anderson et al. (1992) captured 57 pumas, of which 49 were radio-collared. So far, in our 4 winters, the average effort to capture pumas with dogs is 78.8 days (range = 77 to 82). Of 172 pursuits, 70 (41%) were successful. We captured 38 individual pumas their first time with dogs (i.e., does not include dog-aided recaptures), yielding an average capture rate of 8.3 days per capture (i.e., 315 days/38 captures). Other capture efforts and results between the 2 studies are not comparable, because Anderson et al. (1992) did not routinely attempt to capture pumas using cage traps or capture cubs at nurseries like we are. In our current effort, we captured, sampled, and marked 90 pumas. Of those animals, 74 were radio-collared, allowing us to monitor fates of pumas in all sexes and age stages, including: 15 adult females, 11 adult males, 2 subadult females, 5 subadult males, 25 female cubs, 22 male cubs (some individuals occur in more than one age-stage). To date, this represents the largest number of individual pumas sampled for population data in Colorado. Mass recorded by Anderson et al. (1992:86) for pumas having an estimated age ≥24 months, averaged 61.6 kg for 8 males, (SD = 5.7, range = 51.8 to 70.8) and 44.5 kg for 14 females (SD = 3.6, range = 38.5 to 49.9). So far in our current study, mass for pumas ≥24 months old averaged 59.4 kg for 11 males (SD = 7.42, range 40 to 68 kg) and 38.4 kg for 14 females (SD = 4.29, range = 31 to 46). Sexual dimorphism is evident in pumas, and has been described for the species throughout its range (Young and Goldman 1946). Sexual dimorphism in puma has been explained as a potential result of sexual selection (Logan and Sweanor 2001:109). Segment Objective 2 During the past 3.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado. We examined 59 cubs from 21 litters aged 29 to 42 days old where we were reasonably sure that we counted all the cubs at the nurseries (Appendix A). The distribution of puma births by month indicate puma births extending from March into September, with 26 of 28 births occurring May through September (Fig. 3).The secondary sex ratio was 33:26 for 21 litters where all the cubs were sexed. This ratio was not significantly different from 1:1, (X2 = 0.8305 < 3.841, α = 0.05, 1 d.f.). An equal sex ratio at birth is characteristic of other puma populations in North America (Robinette et al. 1961, Logan and Sweanor 2001:69-70). The mean (±SD) and extremes of litter sizes were 2.810 (±0.9808), 1−4 (Table 10). In addition, 13 birth intervals for 8 different female pumas averaged 17.969 months (SD = 4.748), and ranged from 11.7 to 23.9 months (Table 10). During the past 3 biological years (i.e., 2005-06 to 2007-08) when we radio-monitored 12, 13, and 12 adult female pumas respectively, the proportion of adult females that produced cubs each year were 0.67, 0.69, and 0.58, with a mean ± SD of 0.65 ± 0.0586. Based on observations (from GPS and radio-telemetry data) of associations between 7 mothers and putative sires, 8 estimated gestation periods averaged 91.188 days (SD = 2.3443), which is consistent with average puma gestation reported in the technical literature on puma (i.e., mean ± SD = 91.9 ± 4.1, Anderson 1983:33, mean = 91.5 ± 4.0 Logan and Sweanor 2001:414). Anderson et al. (1992:47) reported of ―17 postnatal litters about 10-240 days in estimated age from 12 individual females, the mean (±SD) and extremes of litter sizes were 2.41 ± 0.8, 1-4‖. ―Because most postnatal young were not handled, their sex ratio is unknown‖ (Anderson et al.1992:48). In addition, because cubs were first observed at older ages, it is likely that some post-natal mortality had occurred. This is one explanation for smaller litters observed by Anderson et al. (1992). Anderson et al. (1992:47-48) found that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. Data on our 28 litters adds to Anderson‘s data (Fig. 2), and indicates puma births in Colorado occurring in every 119 �month except January and November (so far). Our data suggests that the majority of puma breeding activity occurs February through June. Anderson‘s observation of two 12-month birth intervals for one female (Anderson et al. 1992:48) is at the low range of our observations (see previously). Segment Objective 3 & 4 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2008, we radio-monitored 11 adult male and 15 adult female pumas to quantify survival and agent-specific mortality rates (Table 11). One adult male is known to have died. M4 was about 37 to 45 months old when he was killed by an unidentified male puma along the southeast boundary of the study area. We lost contact with 3 adult males apparently due to GPS/VHF collar failure: M1, M27, and M29. Direct observations in the field during January 2008 indicated that M27 was alive, and M29 might also be alive. Three adult females are known to have died. F50 was about 29 to 31 months old when she died apparently of natural causes (exact agent could not be identified). Two adult females, F54 and F30, were killed by other pumas. F54 was killed at about 49 months old by a male puma on the southern boundary of the study area while apparently in direct competition for a fawn mule deer. F30 was apparently killed by a puma of unknown sex and for unknown circumstances when she was about 60 months old. Both females died as a result of fatal bites to the head. Preliminary estimates of adult puma survival rates indicate relatively high survival in this reference period (i.e., with no sport-hunting) (Table 12). Survival rates were estimated using the KaplanMeier procedure to staggered entry of animals (Pollock et al. 1989) for the past 2 annual and hunting season periods when samples were ≥ 5 animals in each sex category. The survival rates reflect zero male deaths, and all 3 adult females that occurred in those periods. We need to increase the number of radiomonitored adult males to obtain more realistic survival rates (i.e., other than 1.0). The adult age structure, as indicated in Figure 4, is indicative of high survival rates during the past 4 winters without sporthunting mortality. Research in New Mexico on a non-hunted puma population also indicated higher survival rates for adult male than adult female pumas, with the major cause of death being aggression by male pumas (n = 8 years; Logan and Sweanor 2001:127-138). We have radio-monitored 7 subadult pumas, 5 males and 2 females (Table 13). None of those died while we were monitoring them in the subadult age stage. F23 has become a breeding adult on the study area. M5 dispersed from his natal area and the study area at about 13 months old and went to the northwest slope of the Uncompahgre Plateau where he established an adult territory. M49 was orphaned at 9 months old when his mother F50 died. He dispersed from his natal area and the study area to the northeast slope of the Uncompahgre Plateau, but shed his expandable radio-collar at a fresh elk kill when he was about 15 months old. Puma M11 became a subadult at 13 months old and dispersed from his natal area at 14 months old. He moved to the Dolores River valley between Stapletone and Stoner, Colorado by December 14, 2006. He was legally killed by a puma hunter on December 12, 2007 when he was 30 months old, in the adult age-stage. We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire more realistic estimates of their survival (i.e., other than 1.0). Contact was lost with 2 subadult males and 1 subadult female. F52 dispersed from the study area before we lost track of her in the area of the Black Canyon of the Gunnison in mid-May 2007. We lost track of M31 seven days after he was captured in April 2006. He might have dispersed from the study area. Efforts to locate him by flying over and around the study area have not been successful. M69 emigrated from the study area in spring 2008 when he was about 16 to 20 months old. We monitored him in the Beaton Creek area east of the Uncompahgre River for awhile until we lost contact with him in April 2008. In addition to the subadults discussed previously, a non-marked female puma about 18 to 24 months old was killed by a vehicle November 4, 2006 on highway 550 (between Colona and Ridgway), 120 �which forms the southeast boundary of our study area. The female appeared to be in good health (41 kg), was not pregnant, and was not lactating. Anderson et al. (1992) found that all 9 radio-collared male pumas dispersed from their natal areas, and 2 of 6 radio-collared females did not disperse from their natal areas (A. E. Anderson, Sep. 1993, errata for Anderson et al. 1992:61). Mean ± SD and range of dispersal distances (km) for 8 males, aged 10 to 13 months old at dispersal, were 86.2 ± 51.3, 23 to 151. For 4 females, aged 11 to 31 months old at dispersal, mean ± SD and range of dispersal distances (km) were 37.0 ± 15.3, 17 to 54 (Anderson et al. 1992:63). Although we have observed 3 male pumas disperse from natal areas, and no females disperse, our current research is too short in duration and samples too small yet to make meaningful comparisons with Anderson‘s earlier effort, particularly regarding offspring dispersal rates, distances moved, and philopatry. Dispersal and philopatry have been explained as life history strategies in pumas that assist gene flow, colonization, population maintenance, and individual survival and reproductive success (Logan and Sweanor 2001). Thus, such strategies would be expected to be conserved, and expressed in puma populations in different locations and at different times. In addition, because puma emigration and immigration (i.e., via dispersal) have been shown to be important processes in puma population dynamics (Sweanor et al. 2000), we need larger samples and longer research duration in this study to estimate those parameters. A preliminary estimate of puma cub survival was made with 38 cubs (21 males, 17 females) that we marked (n = 31 were radio-collared) at nurseries when they were 26 to 42 days old. Only cubs that died of natural causes were used (i.e., 3 capture-related deaths were excluded). All cubs were born from May 2005 to July 2007. Cubs that died included 13 that were radio-collared at nurseries and 3 noncollared cubs that apparently disappeared from families because they were not subsequently observed or track counts indicated attrition in cubs. For the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989), the maximum survival period was assumed to be 365 days (i.e., 12 months) to coincide with the time that puma cubs would usually be expected to become independent from their mothers (Logan and Sweanor 2001). Otherwise, cubs were right censored if they reached independence, or we lost contact before then. Dates that bracketed the deaths or disappearances of cubs were used to estimate minim and maximum survival rates. Maximum estimated cub survival using the Kaplan-Meier procedure was 0.4998 (SE = 0.2499). The estimated minimum survival rate was practically the same, 0.4993 (SE = 0.2498). Cub survival estimated with a binomial model (Williams et al. 2001) was 0.5789 ± 0.1570 (95% C.I.). In order to improve the reliability of puma cub survival data, we will make an effort to increase the number of radio-collared cubs that are monitored. The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by male pumas (Appendix A). Male-caused infanticide and cannibalism, along with aggression-caused mortality in adult (indicated previously) and subadult pumas (Logan and Sweanor 2001) has also been a dominant mortality factor in other puma populations in North America (Logan and Sweanor 2001:115-136). Such male puma behavior has been theorized for being a strong selective force in shaping the evolution of behavioral tactics and life history strategies in pumas (Logan and Sweanor 2001). The current closure on sport-hunting on the study area and protection of marked pumas from sport-harvest on the buffer area on the northern portion of the Uncompahgre Plateau for the reference period appears to be operating, so far. None of the adult or subadult pumas wearing functional GPS- or VHF-collars have died due to human causes. This reference condition enables us to quantify puma population structure, survival rates, and agent-specific mortality rates of pumas in the absence of direct 121 �human-caused mortality factors related to sport-hunting, and allow comparisons with the treatment period when hunting of pumas on the study area resumes. Anderson et al. (1992:50) reported on the fates of 21 radio-collared pumas (11 < 24 months old, 10 ≥ 24 months old) from a total of 49 in his previous study which was intended to ―assess the effects of sport-hunting on an unexploited population‖ (Anderson et al. 1992:5). They found 19 (90%) of those pumas died due to human causes, attributed to: legal kill outside the study area (7), capture-related (6), predator management (3), illegal kill (2), and suspected predacide (1). Other causes of mortality included, intraspecies strife (1) and disease (1). Actual age-stage and annual survival rates and agent-specific mortality rates from our current effort cannot be clearly compared with the Anderson et al. (1992:53) data set because they pooled data for male and female pumas in seemingly arbitrary age stages that overlapped puma life history stages (i.e., cubs, subadults, adults). The Anderson et al. (1992:53) estimated survival rates with the Kaplan-Meier procedure (Pollock et al. 1989) for 20 male and 22 female pumas were: 1224 month old = 0.642; 24-36 months old = 0.692, 36 to 48 months old = 0.917, and 48-60 months old = 0.800. Actual sample sizes within each age-stage were not given. There were no quantitative data allowing estimation of survival and agent-specific mortality for cubs less than 12 months old. Segment Objective 5 Cumulative data gathered during the past 3.7 years on the Uncompahgre Plateau Puma Project allowed a minimum count of pumas on the Uncompahgre Plateau Study area, and attendant estimates of population structure, reproduction rates, and survival rates. Those data positioned this project to begin puma population modeling efforts. Such modeling processes are useful for CDOW Mammals Researchers to design the treatment phase of this research project and provide CDOW wildlife biologists and managers with tools to assess current puma harvest management assumptions (previously in Testing Assumptions and Hypotheses) and other conceptual and proposed puma management approaches. A deterministic, discrete time model was developed and created on Excel (Microsoft Office software 2007) by principal investigator K. Logan and CDOW Biometrician P. Lukacs. The model structure has 3 age stages recognized in puma population biology (Logan and Sweanor 2001)− adult, subadult, and juvenile− and which are consistent with parameters we are estimating in this research and available in the technical literature on puma populations: Adult: NAFt+1 = (SF*NAFt + SSF*NSFt)(1-HAFt+1) NAMt+1 = (SM*NAMt + SSM*NSMt)(1-HAMt+1) Subadult: NSFt+1 = ((rSJF*NJt)(1-HSFt+1))PIF/EF NSMt+1 = (((1-r)SJM*NJt)(1-HSMt+1))PIM/EM Juvenile: NJt+1 = RNAFt+1 The model terms are: NAFt+1 = Number of adult females at year t+1. NAMt+1 = Number of adult males at year t+1. NSFt+1 = Number of subadult females at year t+1. NSMt+1 = Number of subadult males at year t+1. NJt+1 = Number of juveniles at year t+1. S = Survival rate for each specified sex and age stage. H = Proportion of the harvest rate comprised by each sex and age stage (e.g., 0.28 harvest rate * 0.40 adult females). PI/E = Ratio of progeny + immigrants/emigrants. R = Reproductive rate for adult females (i.e., average number of cubs per female per year). 122 �r = Proportion of the subadult population that is female (e.g., 0.5; 1-0.5 = proportion of males). These basic assumptions pertain to the use of this model. Expected puma population projections and annual rates of increase (i.e., lambda) generated by the model are conditional on the assigned puma population structure and demographic estimates that parameterize the model. The model structure does not include density dependence, and thus, should not be used to project population trends beyond 10 years. In reality, density dependence probably operates in puma population dynamics, with competition for food expected to regulate independent (i.e., adults and subadults) female density and competition for mates expected to regulate independent male density (Logan and Sweanor 2001). The model structure also assumes that puma harvest is strongly additive mortality, an assumption that is consistent with the current observed adult and subadult (i.e., harvest-age pumas) puma survival rates in the reference period and for adult pumas in other non-hunted puma populations (Logan and Sweanor 2001). We used this model to simulate puma population dynamics to examine a set of scenarios that pertain to current CDOW puma management assumptions and to consider the puma research and management direction for the treatment period. Furthermore, we modeled the potential population impact of the historical puma harvest on the study area prior to the current puma research (i.e., 1994-2003). We parameterized the model with data gathered on the pumas on the study area during the past 3.7 years. The starting population was the minimum count of pumas and attendant estimated sex and age structure made during November 2007 to March 2008 (Table 9). We assumed that all individuals were present in the population during that entire period. No mortalities of independent pumas were detected. But, one radiocollared subadult male emigrated by March 19, 2008. Population parameters included: estimated rates of reproduction and sex and age-stage specific survival, which included data to July 2008 (Table 14). Some sex and age-stage specific estimates of survival (i.e., adult male, subadult male, subadult female) came from the literature (Table 14), because our current sample sizes (i.e., number of individuals and years) were not adequate for realistic estimates (i.e., estimates from our data were 1.0 for adult males and subadults). We did not use actual rates in the literature where estimates involved the pooling of data on sexes and age stages, and where sample sizes for age stages were not presented (e.g., Anderson et al. 1992). In addition, the ratio of progeny and immigrant recruits to emigrants as a model input was from the literature, because such data is scarce and does not exist for Colorado (all references in Table 14). We preferred using the population characteristics and parameter estimates gathered in the current study, because this is the puma population we intend to manipulate in the treatment period to test CDOW puma management strategies. Results of our modeling efforts are presented in Appendix B. This constitutes the first time that current CDOW puma harvest assumptions have been evaluated by using Colorado-specific population data, and thus, is considered to be preliminary. Expected estimates of population growth were generally consistent with the CDOW puma harvest management assumptions that were previously developed from data in the puma population literature to manage for a stable-to-increasing population and for a declining puma population. The results demonstrated the importance of female survival to population dynamics. As more quantitative population data is gathered and the puma population is manipulated during the treatment period, population dynamics can be evaluated further. Results from the model evaluating the historical puma mortality on the study area during 1994 to 2003 indicate the expected outcome is that the puma population on the study area would decline during the treatment years. Segment Objective 6 To investigate the potential that puma hunters might detect puma mothers away from their cubs, we continued gathering data on spatial associations of puma mothers and their cubs during the puma hunting season, which extends from November through March each winter in Colorado. Female pumas are fair game in Colorado, unless they are accompanied by 1 or more cubs. Mothers that are caught away 123 �from their cubs could be legally harvested. Such incidents would result in cubs being orphaned. Orphaned cubs that 6 months old could have a survival rate (to the subadult stage) of < 0.05. Orphaned cubs 7 to 12 months old might have a survival rate (to the subadult stage) of about 0.7 (K. Logan, unpublished data). We monitored only 1 puma family with a radio-collared mother and cub from November 13, 2007 to February 14, 2008 during 8 airplane flights (Table 16).To assess whether mothers were apart or in close association with cubs, we considered error in aerial locations. We recovered 7 puma radiocollars that we located from the airplane and then fixed the actual locations of collars on the ground with GPS. Range of location error was 20 to 520 m (mean = 282.86, SD = 164.75). We decided to use distances greater than the extreme high range of location error (520 m) as the metric to decide if puma mothers might be detected away from their cubs by hunters. Five of 8 (62%) of the observations located the mother and cub 500 m apart, within the extreme margin of location error. In aggregate, the data for the past 3 winters include 136 observations for 1−5 families per winter (Table 15), and generally indicate that puma mothers are more likely to be within 520 m of their cubs during the day in winter. An effort will be made to increase the number of radio-collared family members in subsequent winters. In addition, we will examine variation in mother-cub association distances on an individual female basis. Anderson et al. (1992:70-71) recorded 69 instances of simultaneous aerial locations of 7 pairs of puma mothers and dependent young. They reported that mothers and young were together in 21 (30.4%) of those instances, and they were 1 to 2.2 km apart in 48 (69.6%) of those instances. Segment Objective 7 Principal investigator K. Logan developed 6 drafts study plans pertaining to the next 6 years of puma research on the Uncompahgre Plateau. Three of the drafts were circulated for internal review to obtain comments from CDOW Mammals Research Leader D. Freddy, Carnivore Biologist J. Apker, Area 18 Biologist B. Banulis, Southwest Regional Biologist S. Wait, and Area 18 Wildlife Manager R. Del Piccolo. The planning process involved modeling puma population scenarios (previously in Segment Objective 5) and modeling mark-recapture scenarios in MARK (Cooch and White 2004) with CDOW Biometrician P. Lukacs. The mark-recapture modeling process enabled consideration of effects of puma population size and individual detection rates on the ability to detect changes in puma population abundance that might result from the hunting treatment. Results of the MARK simulations applied to a scenario with 3 capture occasions and puma population abundances that varied from 25 to 50 animals indicated that individual detection rates would need to be 0.4 or greater to be able to detect changes in puma abundance (Table 16). The study plan is expected to be completed in September 2008, with a decision on a course to proceed with the remainder of the research soon thereafter. Segment Objective 8 Data from 23 (7 male, 23 female) GPS-collared pumas, totaling over 31 thousand GPS locations (Table 17) are currently being used in a collaborative study of puma prey use on the Uncompahgre Plateau, carried out by CDOW Mammals Research staff. Plans to use these and other data subsequently gathered, include habitat modeling and mapping for pumas in the western U.S. in collaboration with colleagues at Colorado State University (CSU), and descriptive information on puma behavior in relation to human development on the Uncompahgre Plateau. We are currently collaborating with Dr. Sue VandeWoude and Dr. Kevin Crooks, and postdoctoral and graduate students at CSU to develop a pilot study titled: Puma concolor immune health― Relationship to management paradigms and disease. Tissue samples (i.e., blood, saliva, feces) from pumas we capture are collected and shipped to the Department of Microbiology, Immunology, and Pathology at CSU for analyses. That project will be expanded to The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids. A description of 124 �that project and incomplete results on infectious disease surveillance on 27 pumas (16 female, 11 male) sampled on the Uncompahgre Plateau are presented in Appendix C. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 3.7 years of effort, 90 pumas have been captured, sampled, marked, and released. Of those, 74 pumas were radiocollared, allowing us to monitor fates of pumas in sexes and age stages, including: 15 adult females, 11 adult males, 2 subadult females, 5 subadult males, 25 female cubs, 22 male cubs. As of July 2008, we were monitoring 18 adults, 1 subadult, and 4 cubs with active radio-collars. Data from the marked animals are used to quantify puma population characteristics and vital rates in a reference situation (i.e., without sport-hunting off-take). During November 2007 through March 2008 a minimum estimate of 33 independent pumas were detected on the Uncompahgre Plateau study area, up from 24 the previous winter, with estimates of sex and age structure. Our efforts to quantify puma population characteristics and vital rates positioned us to begin puma population model development, and to use modeling scenarios to assess potential directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools useful to CDOW wildlife biologists and managers for assessing effects of puma harvest strategies. A study plan for the remainder of the research has been in development and should be completed in September 2008. To improve data on puma population vital rates, attention will be given to increasing sample sizes on radio-collared adult males, subadults, and cubs. Furthermore, data from 23 GPS –collared pumas, totaling over 31 thousand GPS locations enables collaboration on investigations of puma use of prey, puma-human relations on the Uncompahgre Plateau, and puma habitat modeling and mapping with colleagues. All of these efforts should enhance the Colorado puma research and management programs. LITERATURE CITED Anderson, A. E. 1983. A critical review of literature on puma (Felis concolor). Colorado Division of Wildlife Special Report No. 54. _____, D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. 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Irwin, and R. Skinner. 1986. Immobilizing wild mountain lions (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases. 22:97-103. _____, L. L. Sweanor, J. F. Smith, and M. G. Hornocker. 1999. Capturing pumas with foot-hold snares. Wildlife Society Bulletin 27:201-208. _____, and L. L. Sweanor. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. _____. 2004. Colorado puma research and development program: population characteristics and vital rates study plan. Colorado Division of Wildlife, Ft. Collins Research Center, Ft. Collins. _____. 2005. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. July: 105-126, Colorado Division of Wildlife, Fort Collins. Murphy, K., M. Culver, M. Menotti-Raymond, V. David, M. G. Hornocker, and S. J. O‘Brien. 1998. Cougar reproductive success in the Northern Yellowstone Ecosystem. 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Nichols, C. Brownie, and J. E. Hines. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs 107:1-97. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. 126 �Sweanor, L. L., K. A. Logan, and M. G. Hornocker. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. _____, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:1076-1084. Van Ballenberghe, V. 1983. Rate of increase of white-tailed deer on the George Reserve: a re-evaluation. Journal of Wildlife Management 47:1245-1247. Watkins, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. Worton, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. Young, S. P. and E. A. Goldman. 1946. The puma: mysterious American cat. The Wildlife Institute, Washington, D. C. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 127 �Table 1. Summary of puma capture efforts with dogs from November 19, 2007 to April 24, 2008, Uncompahgre Plateau, Colorado. Month November No. Search Days 5 December 18 January 18 69 tracks: 23-27 male, 22-26 female, 20 cub 5 pursuits: 2 males, 3 females February 20 64-65 tracks: 14-15 male, 30-31 female, 19-20 cub 21 pursuits: 9 males, 9 females, 3 cubs March 11 17 tracks: 5-6 male, 9-10 female, 2 cub April 5 15 tracks: 1 male, 6 female, 8 cub 217-218 tracks: 6573 male, 85-93 female, 59-60 cub 11 pursuits: 3-4 males, 4-5 females, 3 cubs 6 pursuits: 2 females, 4 cubs 49 pursuits: 16-17 males, 20-21 females, 12 cubs No. & type of pumas pursued 1 pursuit: 1 male 5 pursuits: 1 male, 2 females, 2 cubs No. & I.D. or type of pumas captured 1 puma recaptured: M55 (not handled). 4 pumas captured 5 times: M32 recaptured (not handled), F25 recaptured (faulty GPS collar changed), cub F57 recaptured twice (not handled), cub M44 recaptured by Wildlife Services & killed for depredation on domestic sheep. 5 pumas captured: M69 & M71 (handled & marked for the first time), F16 recaptured (faulty GPS collar changed), F2 recaptured (faulty GPS collar changed), F70 (handled & marked for the first time). 5 pumas captured 7 times: M73 (handled & marked for the first time), F23 recaptured 3 times (could not be handled safely first 2 times, faulty GPS collar changed the 3rd time), F72 (handled & marked for the first time), 1 radio-collared male puma was visually observed in association with F23 while pursuing a female & male puma with dogs on 2-25-08, but he could not be treed to handle (either M27 or M29, both with non-functional GPS collars), 1 unmarked adult female captured (could not be handled safely). 2 pumas captured: F74 (handled & marked for the first time), F75 (handled & marked for the first time). 0 pumas captured 20 captures of 17 individuals: 7 independent pumas and 1 cub were captured for the 1st time- M69, F70, M71, F72, M73, cub F74, F75, & 1 unmarked adult female (not handled). a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; 50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Pumas are not handled for a variety of safety reasons: tree to dangerous to climb for researchers, puma treed near river, creek or cliff, puma might fall from tree after drug induction. TOTALS 77 No. & type of puma tracks founda 20 tracks: 9 male, 8 female, 3 cub 32 tracks: 13-15 male, 10-12 female, 7 cub 128 �Table 2. Summary of puma capture efforts with dogs, December 2004 to April 2008, Uncompahgre Plateau, Colorado. Period Track detection effort 109/78 = 1.40 tracks/day Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 77/49 = 1.57 day/pursuit 77/20 = 3.85 day/capture 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day Table 3. Adult and subadult pumas captured for the first time, sampled, tagged, and released from January 2008 to March 2008, Uncompahgre Plateau, Colorado. Puma I.D. M69 F70 M71 F72 M73 F74 F75 Sex M F M F M F F Estimated Age (mo.) 14-18 33 24 24 49 8-9 41 Mass (kg) 42 39 55 43 60 18 39 Capture date 01-11-08 01-14-08 01-29-08 02-12-08 02-21-08 03-12-08 03-26-08 Capture method Dogs Dogs Dogs Dogs Dogs Dogs Dogs 129 Location Dolores Creek Dolores Creek East Fork Dry Creek Loghill Mesa North fork Cottonwood Creek North fork Cottonwood Creek Cottonwood Creek �Table 4. Pumas that were captured and observed with aid of dogs, but were not handled at that time for safety or other reasons, December 2007 to February 2008, Uncompahgre Plateau, Colorado. Puma sex Capture date Location Comments F57 Age stage or months 7 12-03-07 Caterwauler Canyon F57 8 12-19-07 Loghill Mesa Female adult 02-01-08 Cottonwood Canyon F23 49 02-19-08 F23 49 02-20-08 Big Bucktail Canyon San Miguel Canyon M27 or M29 78 107 02-25-08 F57 was previously marked at the nursery when about 35 days old; born ~April 16, 2007. F57 was recaptured high in a tree, too dangerous to attempt to handle her to fit an expandable radio-collar. F57 was recaptured in a tree that did not allow safe immobilization to handle her to fit an expandable radio-collar. Unmarked female was bayed high in a tree out of range of dart gun. The puma left the tree, but escaped into deep system of sink holes too unstable for any research team member to enter. F23 was recaptured in a tree too dangerous to handle her to change the non-functioning GPS collar she wore. F23 was recaptured again in a tree too dangerous to handle her to change the non-functioning GPS collar she wore. She was safely recaptured and handled on 02-25-08, and was fit with a new GPS collar. A radio-collared male puma was visually observed in association with puma F23 when she & a male puma were pursued with dogs. The male puma was either M27 or M29, both of which had over-lapping home ranges in that area, and both had non-functional GPS collars. But, the male puma could not be treed for absolute identity or for handling. Big Bucktail Canyon Table 5. Summary of puma capture efforts with ungulate road-kill baits, puma kills, and cage traps from August 7, 2007 to July 15, 2008, Uncompahgre Plateau, Colorado.a Carnivore activity & capture effort resultsb No puma activity detected. One deer carcass scavenged by a black bear. No puma activity detected. Deer carcasses scavenged by skunk, bobcat, & black bear. Deer carcasses scavenged by male pumas M55 (10-2 to 3-07) and M29 (10-19 to 22-07). Puma M51 walked ~4 m from a deer carcass, but did not feed. An unknown female puma scavenged on a deer carcass 10-16-07; two cage traps were set and monitored for 2 days, but puma did not return. Deer carcasses were also scavenged by bobcat, coyote, and black bear. November 3 An unknown female puma walked past a deer carcass on 11-1&2-07, but did not feed. An unknown female puma walked past another deer carcass on 11-4-07, but did not feed. An unknown male puma walked past a deer carcass on 11-14-07, but did not feed. Deer carcasses were scavenged by bobcat and coyote. December 2 No puma activity detected. March 3 Unknown male puma scavenged a deer carcass 3-15 to 17-08; two cage traps set and monitored 3-18 &19-08, but puma did not return. Unknown male puma (possibly same as above) scavenged deer carcass 3-23 to 24-08; cage trap set and monitored 3-25 to 27-08, but puma did not return. April 5 Male puma M6 recaptured 4-12-08. He had shed his non-functional GPS collar; we fit him with a new one. An unknown female puma scavenged a deer carcass on ~4-10-08, but did not return. A deer carcass was visited by unknown male & a female pumas; one or both scavenged 4-16-08. Two cage traps were set and monitored 4-17 to 19-08, but the pumas did not return. An unknown male puma scavenged a deer carcass 4-19 or 20-08. Cage trap set and monitored 4-21 to 25-08, but the puma did not return. An unknown female puma scavenged a deer carcass 4-23-08. Cage trap was set and monitored 4-23 to 25-08, but the puma did not return. Another unknown female puma walked past a deer carcass without feeding. July 1 Puma M6 was recaptured 7-15-08; his non-functional GPS collar was replaced with a VHF collar. This was the same bait site and cage trap where we recaptured M6 on 4-8-08. a We used 59 road-killed mule deer, 1 road-killed elk, and 1 puma-killed mule deer (abandoned by F30 and used as bait) at 15 different sites. Of the road-killed ungulate baits, 11 of 60 (18.3%) were scavenged by pumas. b One adult male puma, M6, was recaptured twice. Month August September October No. of Sites 3 4 12 130 �Table 6. Pumas recaptured with dogs, cage traps, or visually observed, November 2007 to July 2008, Uncompahgre Plateau, Colorado. Puma I.D. Recapture Date Estimated Age (mo.) 42 76 Capture Method Process 11-28-07 12-02-07 Mass (kg) Observed Observed M55 M27 Dogs Dogs F25 F57 M44 12-03-07 12-03-07 12-05-07 45 Observed 50 102 7.5 15.5 Dogs Dogs Dogs M32 F57 F16 F2 M27 12-12-07 12-19-07 01-01-08 01-08-08 01-22-08 Observed Observed 43 42 Observed 76 8 59 85 77 Dogs Dogs Dogs Dogs Dogs F25 01-26-08 Observed 103 F23 F23 F23 M27 or M29 02-19-08 02-20-08 02-25-08 02-25-08 Observed Observed Observed Observed 42 42 42 78 107 M6 M6 04-12-08 07-15-08 67 63 74 77 Visual observation of F25 attacking a mule deer after detecting tracks on snow, then snow& radio-tracking Dogs Dogs Dogs Visually observed while pursued by dogs Cage Cage None None, treed in E. fork Tabeguache Cr. by outfitter Stan Garvey, Nucla, CO Changed GPS collar None Shot by Wildlife Services for depredation on domestic sheep None None Changed GPS collar Changed GPS collar None, treed in Johnson Cr. by outfitter Stan Garvey, Nucla, CO None None None Changed GPS collar None GPS collar VHF collar Table 7. Puma cubs sampled June 2007 to August 2008 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) F74b F June 1, 2007 267 18 F75 32 M76 M May 19, 2008 30 2.0 F2 89 M77 M ― ― 2.3 ― ― F78 F ― ― 1.2 ― ― M79 M ― ― 2.2 ― ― F80 F May 23, 2008 40 1.1 F23 45 F81 F ― ― 2.8 ― ― M82 M May 29, 2008 37 2.8 F8 58 M83 M ― ― 2.5 ― ― M84 M June 5, 2008 36 2.6 F70 38 F85 F ― ― 1.8 ― ― F86 F ― ― 2.0 ― ― M87 M July 3, 2008 28 1.9 F3 83 M88 M ― ― 1.8 ― ― F89 F ― ― 1.7 ― ― M90 M July 9, 2008 36 2.1 F72 29 a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs with mother only with radio-telemetry. b This unmarked female cub was captured on 03-12-08 in association with an unmarked adult female puma. The adult female puma, F75, was captured and marked 03-26-08 with cub F74 in association. 131 �Table 8. Pumas detected by tracks and identified by radio-telemetry, GPS-collar fixes, and visual observation. Puma I.D.a Date detected Estimated Age of Tracks on Snow (days) Type of IdentificationRadio-telemetry (VHF) and/or GPS fixes, Visual Observation M55 12/2/07 2 GPS M51 12/3/07 1 VHF & GPS F3 12/6/07 1 VHF & GPS M55 12/15/07 1 VHF & GPS M55 12/18/07 1 VHF (GPS inconclusive) F7 12/28/07 1 VHF & GPS M51 12/28/07 1 VHF & GPS M51 1/3/08 1 VHF M51 1/10/08 1 VHF & GPS F2 1/11/08 1 VHF & GPS F16 & cubs 1/15/08 2 VHF & GPS M51 1/17/08 1 VHF & GPS F16 1/17/08 2 VHF & GPS F25 1/17/08 2 VHF & GPS F16 & cubs 1/18/08 1 VHF & GPS F25 & cub F57 1/18/08 1 VHF & GPS F16 & cubs 1/22/08 1 VHF & GPS F16 & cubs 1/24/08 1 VHF & GPS F25 & cub F57 1/26/08 1 VHF & GPS & visual of F25 F16 & cubs 1/26/08 1 VHF & GPS M55 1/26/08 1 VHF & GPS M32 & Unk.F 1/31/08 1 VHF (GPS NA)b M32 2/6/08 1 VHF (GPS NA) F25 & cub F57 2/12/08 2 VHF & GPS F16 & cubs 2/13/08 1 VHF & GPS F16 2/14/08 1 VHF & GPS F16 & 3 cubs 2/15/08 1 VHF & GPS F8 2/21/08 2 VHF (GPS NA) F23 2/28/08 1 VHF & GPS F23 3/12/08 2 VHF & GPS F8 3/12/08 1 VHF (GPS NA) F25 & cub F57 4/12/08 1 VHF (GPS inconclusive) F16 & 3 cubs 4/12/08 1 VHF (GPS inconclusive) F24 & 2 cubs 4/24/08 1 VHF (GPS NA) a Eleven individual adult radio- and/or GPS-collared pumas were first detected by tracks on snow, then identified by radio- and GPS data, including one visual observation, a total of 34 times. b GPS NA means the GPS instrument was non-functional, but the VHF beacon was working. 132 �Table 9. Minimum puma population estimate based on numbers of known radio-collared pumas and track counts of suspected unmarked pumas on Uncompahgre Plateau study area, Colorado, November 2007 to March 2008. Adults Subadults Cubs Female Male Female Male Female Male Unknown sex 10 4 3 4 4 4 7 6 4 2 0 1 2 2-3 16 8 5 4 5 6 9-10 Total Independent Pumas = 33a,b a Of the total, 23−24 (70−73%) independent pumas were marked and 9-10 (27−30%) were assumed to be unmarked. b The unmarked independent pumas included: 1adult female with 2 large cubs in Happy Canyon, 1 adult female with 1 large cub in Potter Creek and 25-mile Mesa, 1 adult female with 2 large cubs in Monitor Creek, 1 adult female with 2 medium-size cubs in Potter Creek, 1 adult female with 2-3 cubs in San Miguel Canyon, and 1 female or F28 with a non-functional collar Big Bucktail Creek to San Miguel Canyon. Region East slope West slope Totals Table 10. Puma reproduction, Uncompahgre Plateau, Colorado, 2005-2008. Consort pairs and estimated agesa Female Age Male Age (mo.) (mo.) F2 F2 F2 F3 F3 F3 F3 F7 F7 F7 F8*e F8 F8 F16 F16 F23* F23 53 67 89 36 50 62 83 67 82 106 24 37 58 32 52 21 45 Dates pairs consortedb M6 37 06/22-24/05 M51 60 03/31/08 M73 M27 or M29f M29 49 78 02/28-29/08 02/19-25/08 Estimated birth datec 05/28/05 07/29/06 05/19/08 08/01/04 09/26/05 09/17/06 07/03/08 05/19/05 08/13/06 07/10/08 06/26/05 08/13/06 05/29/08 09/22/05 05/24/07 05/30/06 05/23/08 Estimated birth interval (mo.) Estimated gestation (days) 14.0 22.0 13.8 11.7 21.5 93-95 94 14.9 23.9 13.4 22.5 90-91 19.9 23.8 87-93 Observed number of cubsd 3 2 4 1 2 3 3 2 4 3 2 4 2 4 4 3 2 107 F24 75 92 04/12-15/07 06/14/07 90-93 4 F25 74 08/01/05 1 F25 94 04/16/07 20.5 1 F28* 36 06/09/06 2 F28 48 M29 88 12/27-29/06 03/30/07 11.7 92-93 ≥2 tracks F30* 48 M55 34 04/16-20/07 07/17/07 88-92 3 F50 21 07/01/06 1 F54 24 07/01/06 1 F70* 38 M51 60 03/10/08 06/05/08 87 3 F72* 29 07/09/08 1 F75 32 06/01/07 1 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS and radio-telemetry data. c Estimated birth dates were indicated by GPS and radio-telemetry data of mothers at nurseries. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 6 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. 133 �Table 11. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2008, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 No. days 616 M4 M5 01-28-05 to 12-28-05 08-01-06 to 07-31-08 333 730 M6 M27 02-18-05 to 07-31-08 03-10-06 to 01-22-08 1259 683 M29 04-14-06 to 01-11-08 637 M32 M51 M55 M71 M73 F2 F3 F7 F8 F16 F23 F24 F25 F28 F30 04-26-06 to 07-31-08 01-07-07 to 07-31-08 01-21-07 to 07-31-08 01-29-08 to 07-31-08 02-21-08 to 07-31-08 01-07-05 to 07-31-08 01-21-05 to 07-31-08 02-24-05 to 07-31-08 03-21-05 to 07-31-08 10-11-05 to 07-31-08 02-05-06 to 07-31-08 01-17-06 to 07-31-08 02-08-06 to 07-31-08 03-23-06 to 09-25-07 04-15-06 to 07-29-08 827 571 557 184 161 1301 1287 1253 1228 1024 907 926 904 551 836 F50 12-14-06 to 03-26-07 102 F54 01-12-07 to 08-18-07 218 F70 F72 F75 01-14-08 to 07-31-08 02-12-08 to 07-31-08 03-26-08 to 07-31-08 199 170 127 Status: Alive/Lost contact/Dead; Cause of death Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area. Dead; killed by a male puma. Estimated age at death 37−45 months. Alive. Born on study area; offspring of F3. He was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months. Alive. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-2208 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Alive. Lost contact− failed GPS/VHF collar. Died; killed by another puma (sex of puma unknown). Estimated age at death 60 months. Died of natural causes; exact agent unknown. Estimated age at death 30 months. Died; killed by a male puma while in direct competition for prey (i.e., mule deer fawn). Estimated age at death 49 months. Alive. Alive. Alive. Table 12. Preliminary estimated survival rates (S) of adult-age pumas during the reference period (i.e., the study area is closed to puma hunting), Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31) and the hunting season period (November 1 through March 31). Survival rates were estimated only for periods when n ≥ 5 individuals. Period of interest Annual 8/1/2006 to 7/31/2007 Annual 8/1/2007 to 7/31/2008 Hunting season 11/1/2006 to 3/31/2007 Hunting season 11/1/2007 to 3/31/2008 S 0.909 Females SE 0.0867 n 11 S 1.000 Males SE 0.0000 n 5 0.825 0.1041 13 1.000 0.0000 9 0.909 0.0867 11 1.000 0.0000 5 1.000 0.0000 12 1.000 0.0000 9 134 �Table 13. Summary of subadult puma survival and mortality, December 2004 to June 2008, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span No. days 09-16-05 to 06-3006 308 M11 06-21-06 to 12-0207 529 F23 01-04-06 to 02-0406 04-19-06 to 04-2606 31 M49 03-26-07 to 10-0107 189 F52 01-10-07 to 05-1507 125 M69 01-11-08 to 04-0708 87 M31 7 Status: Alive/Survived to adult stage/ Lost contact/Dead; Cause of death Alive; independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau. Dead. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by Dec. 14, 2006. Killed by a puma hunter Dec. 12, 2007 when 30 months old. Alive. Captured on the study area when ~17 months old. Survived to adult stage; gave birth to first litter at ~21 months old. Lost contact. Probable disperser. M31‘s estimated age at capture was 25 months, at the lower margin of puberty for puma. He may have been a dispersing subadult, and could have moved away from the study area. Lost contact. M49 was orphaned at about 9 months old, when his mother F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was ~15 months old, he shed his expandable radio-collar on ~10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. Lost contact. Dispersed from study area as a subadult by Jan. 16, 2007. F52‘s last location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon. Lost contact. Captured on the study area when ~14-18 months old. Emigrated from the study area as subadult by Mar. 19, 2008. Last location was in Beaton Creek, east side of Uncompahgre River valley. 135 �Table 14. Summary of preliminary puma population model parameter estimates obtained from the Uncompahgre Plateau Puma Project and from the published literature on puma. Survival Sex and age stage Adult Female Estimate 0.87 Adult Male 0.91 Subadult Female 0.80 Subadult Male 0.60 Cub 0.50 0.90 Reference Estimated average annual survival rate (n = 2 years) for 11−13 adult females on Uncompahgre Plateau study area. Estimated average annual survival rate (n = 8 years) for adult males in a nonhunted New Mexico puma population (Logan and Sweanor 2001:127-128). Estimated annual survival rate (n = 2 years) for 5−9 adult males on Uncompahgre Plateau study area was 1.00. Estimated subadult female survival in New Mexico (0.88, n = 16; Logan and Sweanor 2001:122) adjusted downward for potential lower survival for pumas 12-24 months old on Uncompahgre Plateau (0.642, n = 14 females and 10 males combined, life stages not known or described in Anderson et al. 1992:53). Survival of 7 radio-collared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated subadult male survival in New Mexico (i.e., 0.56, n = 9; Logan and Sweanor 2001:122) adjusted upward for potential slightly higher survival for pumas 12-24 months old (i.e., 0.642) on Uncompahgre Plateau (Anderson et al. 1992:53). Survival of 7 radio-collared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated cub survival rate (n = 38 cubs combined sexes), on Uncompahgre Plateau study area. This survival rate is applied to the model starting with the expected number of cubs from birth in RY5. Estimated cub survival for cubs ≥7 months old, and is applied to RY4 cubs only, because the minimum count of pumas in RY4 was tallied when most cub mortality had already occurred. Survival of cubs ≥7 months old in the literature is about 0.95 (Logan and Sweanor 2001). Here, a more conservative 0.90 is used in this model. Reproduction Parameter Adult age Estimate 2+ years Litter size 2.81 Secondary sex ratio observed at nurseries 1:1 Proportion of adult females producing new litters each year 0.65 Parameter Subadult female Estimated Ratio 1.02 Subadult male 0.94 Reference Assume all females 2 years old and older are adults (Logan and Sweanor 2001: 93-94). Average litter size for 21 litters on the Uncompahgre Plateau study area = 2.810 ± 0.9808SD; litters were examined when the cubs were 26 to 42 days old. Secondary sex ratio was 33:26 for 21 litters examined at 29 to 42 days old on the Uncompahgre Plateau study area (not significantly different from 1:1, (X2 = 0.8305 < 3.841, α = 0.05, 1 d.f.). Also see Robinette et al. 1961, Logan and Sweanor 2001:69-70. Proportion of adult females giving birth each year (n = 3 years for ns = 12, 13, 12 females), Uncompahgre Plateau study area. Proportion for a non-hunted puma population in New Mexico was 0.50 (Logan and Sweanor 2001:98). Progeny + Immigrant Recruits /Emigration Ratio Reference No data for pumas in Colorado exists. Assume the ratio of female immigrants to emigrants = 1.02. This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). No data for pumas in Colorado exists. Assume the ratio of male immigrants to emigrants = 0.94, (i.e., male immigration is half of emigration). This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). 136 �Table 15. Summary of puma mother and cub associations by distance (m) during airplane flights, each winter, Uncompahgre Plateau, Colorado. Monitoring period Month No. flights No. puma familiesa Ages of cubs (mo.) No. observations with mothers & cubs 520 m apart Nov. 9, 2005 to Nov. 3 4 2−6 10 Mar. 29, 2006 Dec. 4 4 3−7 16 Jan. 5 4 4−8 16 Feb. 4 5 5−9 16 Mar. 2 5 6−10 9 Totals 18 4−5 2−10 67 Nov. 7, 2006 to Nov. 4 4 2−3 10 Mar. 22, 2007 Dec. 4 4 2−5 11 Jan. 5 3 4−6 9 Feb. 4 4 5−7 9 Mar. 3 1 8 2 Totals 20 1−4 2−8 41 Nov. 13, 2007 to Nov. 2 1 6 1 Feb. 14, 2008 Dec. 0 1 7 NA Jan. 3 1 8 2 Feb. 3 1 9 2 Totals 8 1 6−9 5 a All puma mothers wore GPS-radiocollars. At least 1 cub in the litter wore a VHF radiocollar. b Mean = 1,060 m, SD = 325.99, range = 650−1,600. c Mean = 1,120 m, SD = 1,214.40, range = 616−4,101. d Mean = 1,317 m, SD = 530, range = 750−1,800. No. observations with mothers & cubs >520 m apart 2 4 4 2 0 12b 1 1 3 2 1 8c 1 NA 1 1 3d Table 16. Results of MARK (Cooch and White 2004) simulations to investigate precision as a function of individual capture probabilities and population size. Expected Standard Error Capture Probability (p) 0.2 0.3 0.4 0.5 Large Population (n = 50) 21 9.6 5.5 3.5 Small Population (n = 25) 13 7.8 4.2 2.5 Confidence Interval width Large Population (n = 50) 84 38.4 22 14 137 Small Population (n = 25) 52 31.2 16.8 10 Large Pop. Lower Bound Small Pop. Upper Bound 8 31 39 43 32 29 27 26 �Table 17. Numbers of GPS locations and spans of monitoring for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to July 2008. Puma I.D. M1 M4 M6 M27 M29 M51 M55 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a M M M M M M M F F F F F F No. locations adult 12-08-04 to 07-20-06 1,797 adult 01-28-05 to 01-14-06 958 adult 02-18-05 to 05-14-08 1,035 adult 03-12-06 to 06-21-06 313 adult 04-14-06 to 01-01-08 1,599 adult 01-07-07 to 05-17-08 1,464 adult 01-21-07 to 05-01-08 1,334 adult 01-07-05 to 05-07-08 3,239 adult 01-21-05 to 04-01-08 3,205 adult 02-24-05 to 07-30-07 2,401 adult 03-21-05 to 10-10-06 1,541 adult 10-12-05 to 04-01-08 2,089 subadult, 01-04-06 to 02-04-06 113 adult 02-05-06 to 05-07-08 746 F24 F adult 01-17-06 to 07-25-07 1,812 F25 F adult 02-09-06 to 04-07-08 1,854 F28 F adult 03-24-06 to 08-15-07 1,499 F30 F adult 03-30-07 to 02-22-08 1,057 F50 F adult 12-14-06 to 03-26-07 352 F52 F subadult 01-10-07 to 05-08-07 383 F54 F adult 01-12-07 to 08-01-08 686 F70 F adult 01-14-08 to 07-31-08 685 F72 F adult 02-12-08 to 07-31-08 737 F75 F adult 03-26-08 to 07-02-08 287 a GPS collars on pumas are remotely downloaded at approximately 1-month intervals. The last date in Dates monitored includes last location from the last GPS data download acquired for an individual puma in this report period. 138 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Estimation Methods for Monitoring Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 139 �Figure 2. Age structure of independent pumas captured and sampled for the first time on the Uncompahgre Plateau, Colorado, December 2004 to March 2008. Figure 3. Puma births detected by month during the current research effort, 2005 to 2008 (n = 28 litters of 15 females), and during the earlier effort by Anderson et al. (1992; 1983 to 1987, n = 10 litters of 8 females), Uncompahgre Plateau, Colorado. 140 �Figure 4. Age structure of surviving independent pumas captured and sampled on the Uncompahgre Plateau, Colorado, in March 2008, and after protection from sport-hunting mortality since April 2004, which includes 4 hunting seasons (Nov. through Mar., 2004-05 to 2007-08). In addition, no other humancaused mortalities were documented in the radio- and GPS-collared sample of independent pumas. This age structure assumes that puma M27 and M29 were alive on March 31, 2008; they each had nonfunctional GPS collars, and were detected alive on 1-22-08 and 1-11-08, respectively. Pumas M5 and M27 range north of the study area and were protected from legal sport-harvest because they are visually tagged animals. Mean ± SD of adult female and adult male ages, respectively: 5.35 ± 2.11 yr. (64.23 ± 25.36 mo.); 4.79 ± 2.17 yr. (57.50 ± 26.06 mo.). 141 �Appendix A. Summary of individual puma cub survival and mortality, December 2004 to 2008, Uncompahgre Plateau, Colorado. Puma I.D. Est. Birth date Est. survival span from 1st capture to fate or last monitor date M5 Estimated Age at capture (days) 183 ~8-1-04 02-04-05 to 04-07-08 F9 31 5-28-05 F10 31 5-28-05 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 M11 31 5-28-05 06-27-05 to 12-2-07 F12 42 5-19-05 07-01-05 to 12-08-05― 01-26-06 F13 42 5-19-05 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 F21 37 9-26-05 Age to last monitor date alive or at death (days, birth to fate) ~1,345 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Lost contact― shed radiocollar 04-19-06 to 04-26-06. F3 Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 1230-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old Lost contact― shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 12-08-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7‘s tracks. Dead; killed and eaten by a puma (sex unspecified) about 8-28-05. Lost contact― shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-06-06 to 06-14-06. F2 F16 308-314 Dead. Lost contact― shed radiocollar 06-06-06 to 0614-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Dead; probably killed by another puma. Multiple bite wounds to skull. 10 mo. old. Lost contact― shed radiocollar 07-27-06 to 08-02-06. 244-245 Lost contact― shed radiocollar 05-24-06―05-25-06. F16 324 Lost contact; radiocollar quit. Last aerial location 8-1606, live signal. F3 326-333 176-215 918 203-252 101 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 11-02-05 to 08-16-06 301-308 330 142 F2 F2 F7 F7 F8 F8 F16 F16 �Appendix A continued Puma Estimated I.D. Age at capture (days) M22 37 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 9-26-05 M26 183 8-1-05 F33 31 5-30-06 11-02-05 to 12-21-05― 12-22-05 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 F34 31 5-30-06 06-30-06 to 07-31-06 63-65 F35 31 5-30-06 38 F36 29 6-9-06 M37 29 6-9-06 M38 41 7-29-06 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 M39 29 8-13-06 F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 M44 33 8-13-06 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 86-87 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Dead; killed and eaten by male puma 12-21-05―12-2205. F3 ~232-235 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 63-65 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a F23 Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 7/16-17/07 at 352-353 days old. F28 F8 53-61 106 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 0425-07. Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 0425-07. Assumed dead. Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 10-13-06 (collar found); assumed dead. Dead; research-related fatality.b 200 Treed, visually observed 03-01-07. F7 F7 479 Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Killed by Wildlife Services for depredation control on 12/5/07, for killing 4 domestic sheep. 74 74 352-353 9 255 9 255 143 F23 F23 F28 F2 F8 F8 F8 �Appendix A continued Puma Estimated I.D. Age at capture (days) F45 33 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 8-13-06 09-15-06 to 5-20 to 23-07 M46 9-17-06 10-18-06 to 12-15-06 31 Age to last monitor date alive or at death (days, birth to fate) 280-283 89 360 M47 M48 M49 F53 31 31 153 183 9-17-06 9-17-06 7-1-06 7-1-06 M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 89 360 89 360 12-05-06 to 07-31-07 to 01-01-07 01-12-07 to 02-23-07 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 ~456 42 ~428 subad. 200 52 324 434 144 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 1219 to 20-06. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-12-07 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-12-07 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-12-07 in Puma Canyon. M49 was orphaned when his mother died on about 0326-07; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Lost contact― shed radiocollar 2-23-07. F53 visually observed by P. & F. Star, on 9-2-07, when F53 was ~14 months old and an independent subadult. F7 Lost contact― shed radiocollar 2-27-07. M56 observed 03-01-07. Lost contact― shed radiocollar 06-07-07. Live mode 06-06-07. Not radio-collared. Tracks of 3 cubs observed with F16‘s tracks on 04-1208, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F3 F3 F3 F50 F54 F7 (?) F25 F16 �Appendix A continued Puma Estimated I.D. Age at capture (days) F59 34 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 5-24-07 06-27-07 to 08-21-07 Age to last monitor date alive or at death (days, birth to fate) 55 324 434 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 48-49 324 434 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 08-17-07 262 M65 34 7-14-07 08-17-07 262 F66 37 7-17-07 08-23-07 to 5-31 to 6-1-08 M67 37 7-17-07 08-23-07 M68 37 7-17-07 08-23-07 F74 259 6-1-07 M76 M77 30 30 5-19-08 5-19-08 03-12-08 to 07-09-08 06-18-08 06-18-08 282-283 403 145 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Alive. Observed alive 11-20-07 with F16, but without siblings M58 & F61. Tracks of 3 cubs observed with F16‘s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead; research-related mortality.d F16 Radiocollar malfunction. Tracks of 3 cubs observed with F16‘s tracks on 04-1208, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Not radio-collared. Not radio-collared. Not radio-collared. Two out of potential of 4 of F24‘s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Not radio-collared. Two out of potential of 4 of F24‘s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. One male cub might have died or was not observed. Radio-collared. Shed radiocollar between 7-9-08 and 715-08, probably while still dependent on mother F75. Not radio-collared. Not radio-collared. F16 F16 F24 F24 F24 F24 F30 F30 F30 F75 F2 F2 �Appendix A continued Puma Estimated I.D. Age at capture (days) F78 30 M79 30 F80 40 F81 40 M82 37 M83 37 M84 36 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 5-19-08 5-19-08 5-23-08 5-23-08 5-29-08 5-29-08 6-5-08 06-18-08 06-18-08 07-02-08 07-02-08 07-05-08 07-05-08 07-11-08 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Not radio-collared. F2 Not radio-collared. F2 Not radio-collared. F23 Radio-collared. F23 Radio-collared. F8 Not radio-collared. F8 ~69 Radio-collared 7-11-08 to 7-22-08; collar removed F70 because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08; assuming M84 died, he probably died around 8-13-08 when cub F85 was located ~340m south of the eartag in the East fork Dolores Cyn. F85 36 6-5-08 07-11-08 Radio-collared. F70 F86 36 6-5-08 07-11-08 Radio-collared 7-22-08. F70 M87 28 7-3-08 07-31-08 Not radio-collared. F3 M88 28 7-3-08 07-31-08 Not radio-collared. F3 F89 28 7-3-08 07-31-08 Radio-collared F3 M90 36 7-9-08 08-14-08 Radio-collared F72 7MA 28-35 7-10-08 08-08 to 13-08 Examined, but not tagged. F7 7MB 28-35 7-10-08 08-08 to 13-08 Examined, but not tagged. F7 7FC 28-35 7-10-08 08-08 to 13-08 Examined, but not tagged. F7 a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, possibly restricting movement. 146 �Appendix B. Puma population models and simulation results as preliminary assessments of current CDOW puma management assumptions and population manipulations for the treatment period. Modeling Scenarios We modeled a set of scenarios that pertain to current CDOW puma management assumptions and to potential puma research direction on the Uncompahgre Plateau for the treatment period: 1) Puma population dynamics without hunting-caused mortality. 2) Puma harvest that would induce a stable (i.e., no growth) phase to identify a population tipping point induced by harvest mortality. 3) Puma harvest at the upper limit (i.e., 15% of 8-15% range, CDOW 2007) that CDOW assumes would result in a stable to increasing puma population, with harvest apportioned equally among independent males and females. 4) Puma harvest at the upper limit (i.e., 15% of 8-15% range, CDOW 2007) that CDOW assumes would result in a stable to increasing puma population, but with harvest comprised of 40% females and 60% males, which is consistent with the sex composition of puma harvest in Colorado. 5) Puma harvest at the upper limit (i.e., 28% of 16-28% range, CDOW 2007) that CDOW assumes would result in a declining puma population, with harvest apportioned equally among independent males and females. 6) Puma harvest at the upper limit (i.e., 28% of >15-28% range, CDOW 2007) that CDOW assumes would result in a declining puma population, but with harvest comprised of 40% females and 60% males, which is consistent with the sex composition of puma harvest in Colorado. 7) A harvest scenario applied the historic puma harvest on the study area. Puma mortality data for the study area during the 10 years previous (i.e., 1994-2003) to the beginning of the reference period was quantified after carefully geo-referencing mortality locations on the study area (see last table in Appendix B). Model parameters from those data include: mortality rate of 14.3 independent puma mortalities per year (rounded to 14/yr.), and sex proportions of 55% males and 45% females. No other puma population data or parameter estimates were available for the study area at that time. Therefore, the scenario that was modeled pertained to the expected impact of the average annual puma mortality of independent pumas (i.e., adults and subadults) if the hypothetical population was the same as the non-hunted minimum expected puma population in treatment period year 1 (i.e., TY1). A harvest of 14 pumas per year is a 26% harvest rate on the expected TY1 non-hunted minimum independent puma population (i.e., 14/53). Another way of stating this scenario is; what would occur if puma harvest was applied to the puma population on the study area during the treatment period at the average rate of puma mortality that was recorded during 1994 to 2003? Results of Puma Population Simulations The following tables contain the expected minimum population sizes for independent pumas and annual rates of population increase for independent pumas conditional upon the minimum number of independent pumas detected in Reference Year 4 (RY4) and the model input parameters and assumptions (Table 14, this report). Notes below each table explain how results may be interpreted relative to other research results on puma population dynamics and specific CDOW puma management assumptions. The harvest levels for each model are clearly stated in the left column of each table. Simulations involving harvest apply the harvest following reference year 5 (RY5) and starting with treatment year 1 (TY1). 147 �Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 23 14 8 8 42 53 1.14 TY2 27 17 11 10 49 64 1.18 TY3 32 22 12 11 58 77 1.17 TY4 38 27 15 14 69 92 1.17 TY5 44 32 17 16 81 110 1.16 Note: Expected lambda for the modeled non-hunted puma population on the Uncompahgre Plateau approach the high range of observed average annual rates of population increase for a non-hunted puma population in good quality habitat in southern New Mexico (i.e., r = 0.21, n = 4; r = 0.28, n = 4; r = 0.17, n = 4; r = 0.11, n = 7; Logan and Sweanor 2001:169-175). Puma population growth could be higher on the Uncompahgre Plateau because of higher quality habitat (i.e., greater prey biomass), and if puma sources are nearby to the study area. Harvest Level No harvest. Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 19 12 7 6 35 44 0.98 TY2 19 12 8 7 34 45 1.02 TY3 19 13 7 7 34 46 1.01 TY4 19 13 7 7 34 46 1.01 TY5 19 14 7 7 34 46 1.00 Note: The tipping point of population stability and decline is expected to be about 16% harvest of independent male and female pumas, consistent with current CDOW puma harvest assumptions. Harvest Level 16% of independent pumas, sexes are harvested equally; i.e., stable phase model. Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 19 12 7 7 36 45 0.99 TY2 19 12 8 7 35 47 1.03 TY3 19 13 8 7 36 47 1.02 TY4 20 14 8 7 36 48 1.02 TY5 20 14 8 7 36 49 1.01 Note: This result is consistent with the current CDOW puma harvest assumption for a stable-to-increasing population, with very slow growth attributed to equal harvest of females and males. Harvest Level 15% of independent pumas, sexes are harvested equally. 148 �Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 21 11 8 6 38 45 0.99 TY2 22 10 9 7 39 47 1.05 TY3 23 10 9 7 42 50 1.05 TY4 25 11 10 8 45 53 1.05 TY5 26 11 10 8 48 56 1.06 Note: This result is consistent with the current CDOW puma harvest assumption for a stable-to-increasing population, with increased growth due to reduced female mortality. Harvest Level 15% of independent pumas, comprised of 40% females & 60% males. Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 17 10 6 6 30 38 0.81 TY2 14 9 6 5 25 33 0.86 TY3 12 8 5 4 22 29 0.84 TY4 10 7 4 4 18 25 0.84 TY5 9 6 3 3 16 21 0.84 Note: This result is consistent with the current CDOW puma harvest assumption for a declining population. Harvest Level 28% of independent pumas, sexes are harvested equally. Projected Minimum Puma Population Size Independent Pumas Adult Subadult Cub Year Female Male Female Male F&M Total Lambda RY4 16 8 5 4 20 33 RY5 18 10 9 8 33 45 1.27 TY1 19 8 7 4 34 38 0.81 TY2 18 6 7 5 32 35 0.92 TY3 17 5 7 4 31 33 0.93 TY4 16 4 6 4 30 31 0.95 TY5 16 4 6 4 29 30 0.95 Note: This result is consistent with the current CDOW puma harvest assumption for a declining population even with harvest weighted toward males. Harvest Level 28% of independent pumas, comprised of 40% females & 60% males. Projected Minimum Puma Population Size Harvest Independent Pumas Adult Subadult Cub Level Year Female Male Female Male F&M Total Lambda 26% of RY4 16 8 5 4 20 33 independent RY5 18 10 9 8 33 45 1.27 pumas, TY1 18 9 7 6 33 41 0.89 comprised of TY2 17 8 7 6 31 39 0.94 45% females TY3 16 8 7 6 30 36 0.94 & 55% males; TY4 16 7 7 5 28 35 0.95 i.e. historical harvest model TY5 15 7 6 5 27 33 0.95 Note: Results of this model indicate that the expected outcome is that the puma population would decline. 149 �Appendix B (continued). Puma mortality data for portions of Game Management Units (GMUs) 61, 62, 70 that comprise the Uncompahgre Plateau Study Area, 1994-2003. GMU Year Adult Male Subadult Male Adult Female Subadult Female Subtotals 61 2003 4 2 3 0 9 62 2003 1 1 1 3 6 70 2003 0 0 0 0 0 61 2002 1 0 2 0 3 62 2002 0 0 3 1 4 70 2002 1 0 0 0 1 61 2001 4 0 5 0 9 62 2001 2 1 2 1 6 70 2001 1 0 1 0 2 61 2000 5 0 1 2 8 62 2000 0 0 0 0 0 70 2000 0 0 1 1 2 61 1999 3 1 3 0 7 62 1999 2 0 1 0 3 70 1999 2 0 1 0 3 61 1998 3 1 3 1 8 62 1998 3 1 0 0 4 70 1998 1 0 3 0 4 61 1997 5 1 1 0 7 62 1997 2 0 2 1 5 70 1997 1 0 0 0 1 61 1996 3 0 2 0 5 62 1996 2 1 3 0 6 70 1996 1 0 0 0 1 61 1995 6 1 4 0 11 62 1995 9 0 4 0 13 70 1995 1 0 0 0 1 61 1994 2 0 3 0 5 62 1994 3 1 4 0 8 70 1994 0 0 1 0 1 Subtotal 68 11 54 10 143 Total 79 males (55%) 64 females (45%) 14.3/yr. Note: Nine puma records did not designate adult or subadult age stages. Those data were determined with a cointoss for this table, resulting in 6 males designated as 3 adults and 3 subadults, and 3 females designated as 1 adult and 2 subadults. Three mortalities were recorded as ―road-kills‖ (1 subadult male, 2 subadult females). Two adult male deaths were recorded as ―other‖. Two adult male deaths were recorded as ―landowner‖. All other deaths were recorded as ―hunter harvest‖. Source of records: Colorado Division of Wildlife, 6060 Broadway, Denver, CO, and K. Crane, CDOW DWM, Ridgway. 150 �Appendix C. Collaborative project on disease surveillance in wild felids. College of Veterinary Medicine and Biomedical Sciences Department of Microbiology, Immunology & Pathology 1619 Campus Delivery Fort Collins, CO 80523-1619 970-491-6144 (voice) 970-491-0603 (fax) TO: Ken Logan, Mammals Researcher, Colorado Division of Wildlife, Montrose, CO. FROM: Sue VandeWoude, DVM, Associate Professor, DMIP RE: Disease Seroprevalence in UP Pumas DATE: August 26, 2007 Attached please find the consolidated report on infectious disease surveillance for the mountain lion samples you have provided to our laboratory as an adjunct to your CDOW ongoing studies. Our laboratory has performed puma-lentivirus (PLV) antibody screening using a sensitive western blot assay developed in our laboratory and found 13 of 18 samples conclusively positive (72%), with two additional samples inconclusive and one not tested. Dr. Michael Lappin, a veterinary internal medicine specialist with expertise in feline infectious disease has tested a subset of 6 samples for antibodies to Feline Calicivirus (FCV), Feline Herpes Virus (FHV), Feline parvovirus (FPV), Toxoplasma gondii (IgM, indicating recent infection, IgG indicating past exposure), and Bartonella hensalae (the agent associated with cat scratch disease). At least one of six animals tested has been positive for each of these agents. Further results are pending from the remaining samples you have provided for these 5 assays. In addition, Dr. Martin Scriefer at Fort Collins CDC has also tested 6 animals for evidence of antibodies to the agent responsible for plague (Yersinia pestis). Interestingly, 3 of 6 animals demonstrate significant exposure to this agent as well. These specific agents were selected for analysis in order to provide a variety of types of agents (viruses: PLV, FCV, FHV, FPV; bacteria: Bartonella henselae and Yersinia pestis; and coccidian: T. gondii), a variety of modes of transmission (direct intra-specific contact, PLV; direct contact with domestic cats, FCV, FHV, FPV; arthropod transmission, B. henselae, Y. pestis; prey ingestion, T. gondii, Y. pestis). Further, at least three of these agents (PLV, FCV, B. henselae) result in chronic infections, allowing the possibility of determining genetic relatedness among organisms isolated from different individuals, and three of these agents (B. henselae, Y. pestis, T. gondii) are also potential zoonotic agents. As you are aware, our laboratory has recently been awarded a 5 year NSF Ecology of Infectious Disease grant entitled, ―The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids‖, with co-PI Dr. Kevin Crooks, an associate professor in the Warner College of Natural Resources at CSU. The aims of this grant are to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in large carnivore species as described on the following page. The letter of support provided by you and Mr. Dave Freddy were pivotal in demonstrating a large cohort of capable and active field collaborators willing to provide samples to support our studies. The mountain lion field work being led by your team, and the newly initiated studies by your colleague, Dr. Mat Alldredge, have provided us with renewed enthusiasm for developing our collaborations to support the goals of our study. We foresee the opportunity to interact in a mutually beneficial partnership to further the goals of all of our studies, and to maximize the information that can be gleaned about these important and ecologically significant species. 151 �We anticipate that the data we are generating will be useful for comparative seroprevalence of different geographic populations of bobcats and pumas, and for genetic phenotyping of pathogens to compare relationships among diseases spread by arthropod vectors, domestic cats, feral rodents, and inter-specific contacts. As we discussed during your recent visit to CSU, these samples are most valuable to us if we can receive them directly as quickly as possible after collection. I have provided an SOP providing information about the types of samples that will be most valuable, and a draft of a ‗permissions‘ document that you can use with each sample submission to provide us with guidance for any testing that is permissible on the materials we receive. This latter document will be filed and recorded electronically. We will continue to provide annual updates and communications about any publications that utilize the data resulting from your samples. Again thank you for providing these extremely valuable samples, and we look forward to our continued collaborations. Sincerely, Sue VandeWoude The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids Project Summary Sue VandeWoude (co-PI), Kevin Crooks (co-PI), Michael Lappin, Mo Salman, Walter Boyce, Ken Logan, Mat Alldredge, Carolyn Krumm, Don Hunter, Lisa Lyren, Seth Riley, Jennifer Troyer The objective of this study is to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in carnivore species. Bobcats, puma, and domestic cats will be evaluated simultaneously in three divergent ecosystems: high mountain desert (Colorado), everglades (Florida), and Mediterranean scrub habitat (California). The research will: 1) assess the relationship between habitat fragmentation and prevalence of viral, bacterial, and parasitic pathogens across a gradient of urbanization, 2) use transmission dynamics of selected disease agents as markers of connectivity of fragmented populations, and 3) evaluate the effect of urbanization on the incidence of cross-species disease transmission. The results of this research will give wildlife managers a better understanding of how urbanization affects their local wildlife and assist them in future disease management planning. The combination of a uniquely qualified, broadly based research team with an extensive dataset on carnivores from across the country presents an unprecedented opportunity to investigate the disease dynamics in these rare and difficult to study species. The research efforts of each regional team will support and provide new insights for all of the regions involved, not simply their own. Training of graduate students in ecology, infectious disease, and epidemiology will be emphasized, as will training for pre- and post-doctoral veterinarians. Results will be made widely available to other scientists, conservation practitioners, and the general public. This research has a tremendous capacity to broadly impact areas of public and post-graduate education, career development for new investigators and persons from underrepresented groups, and to enhance understanding of complex infectious disease ecological problems using extensive multi-disciplinary collaborations. 152 �Appendix C (continued). Preliminary results of infectious disease surveillance for puma, Uncompahgre Plateau, Colorado, 2005-2008. Puma ID UPCO2 UPCO3 UPCO7 UPCO7 UPCO7 UPCO8 UPCO4 UPCO5 UPCO6 UPCO6 UPCO23 UPCO25 UPCO28 UPCO29 UPCO31 UPCO23 UPCO27 UPCO30 UPCO50 UPCO51 UPCO52 UPCO54 UPCO55 UPCO24 UPCO69 UPCO70 UPCO71 UPCO72 UPCO73 UPCO74 UPCO75 Sex F F F F F F M M M M F F F M M F M F F M F F M F M F M F F F F Capture Date 1/8/2008 1/21/2005 2/24/2005 3/30/2006 3/3/2007 3/21/2005 1/28/2005 2/4/2005 2/18/2005 4/12/2008 2/25/2008 2/8/2006 3/23/2006 4/14/2006 4/19/2006 1/4/2006 3/10/2006 4/15/2006 12/14/2006 1/7/2007 1/10/2007 1/12/2007 1/21/2007 1/17/2006 1/11/2008 1/20/2008 1/29/2008 2/12/2008 2/21/2008 3/12/2008 3/26/2008 GPS NAD27 U.T.M.: Zone, E, N 13S, 245722, 4244166 13S, 241606, 4251510 13S, 246328, 4244230 13S, 245901, 4247627 13S, 247645, 4246097 12S, 727808, 4239029 13S, 257565, 4239606 13S, 240577, 4251037 13S, 247399, 4254006 13S, 257516, 4239696 12S, 723304, 4242231 13S, 258374, 4230480 12S, 722868, 4240115 12S, 723458, 4242340 12S, 746919, 4225441 12S, 730188, 4234861 12S, 722339, 4245212 13S, 248551, 4242095 12S, 753639, 4260149 13S, 238783, 4252390 13S, 258058, 4236260 13S, 252688, 4228050 13S, 258133, 4228691 12S, 737151, 4233273 13S, 248191, 4246810 13S, 247122, 4245760 12S, 754611, 4256842 13S, 258294, 4234597 12S, 728576, 4241799 12S, 729678, 4239555 12S, 732894, 4239423 PLV + + + Ih I + + P P + + + + + + I + + + + + P P P P P a a FCV +h + Ph P P P P P P P P P P P P P P P P + + P P P P P b PLV is Puma Lentivirus. FCV is Feline Calicivirus. c FHV is Feline Herpesvirus. d FPV is Feline Panleukopenia Virus e T. g. is Toxoplasma gondii. f B. h. is Bartonella hensalae. g Y. p. is Yersinia pestis. h Results: + (positive result), P (Pending result), I (Inconclusive result). b 153 FHV + P P + P P P P P P P P P P P P P P P + + P P P P P c FPV + P P + P P P P P P P P P P P P P P P + + P P P P P d T.g. e IgM + P P P P P P P P P P P P P P P P P P P P P P T.g.e IgG + + P P + + + + P P P P P P P P P P P P P P P + + P P P P P B.h. Y.p. f g P P + P P P P P P P P P P P P P P P P P P P P + ++ +++ P P ++ I I I + + P P P P P P P P P P P P P + + + �154 �Colorado Division of Wildlife July 2007 - June 2008 State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 2 Federal Aid Project No. N/A WILDLIFE RESEARCH REPORT : Division of Wildlife : Mammals Research : Predatory Mammals Conservation : Cougar Demographics and Human Interactions : Along the Urban-Exurban Front-range of : Colorado Period Covered: July 1, 2007 - June 30, 2008 Author: M.W. Alldredge Personnel: K. Griffin, D. Kilpatrick, M. Paulek, B. Karabensh, M. Miller, F. Quartarone, M. Sirochman, L. Wolfe, J. Duetsch, C. Solohub, J Koehler, M. Leslie, L. Rogstad, T. Howard, D. Freddy CDOW; B. Posthumus, Jeffco Open Space; D. Hoerath, K. Grady, D. Morris, Boulder County Open Space; S. Oyler-McCance, USGS. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We continued to examine the statewide population structure of both black bears and cougars. Using 75 and 56 samples each from bears and cougars respectively, we examined genetic population structure for the state. Based on these data, the concept of a megapopulation is a more realistic representation of the bear and cougar populations, as opposed to ideas of subpopulations within the state. No evidence for any population sub-structure was seen in the analyses so no further genetic work on this project is recommended. We also began analyzing cougar fecal samples collected from the 3 sibling cougars in captivity at the Foothills Wildlife Research Facility. Feces were stored at controlled temperatures after deposition and sub-sampled at monthly intervals. Genetic material has been found in samples up to 4 months postdeposition, but genotyping error rates have not yet been assessed. Sampling cougar feces in the field may be a feasible non-invasive sampling method to estimate cougar populations. The front-range cougar project began intensive capture efforts during the 2007-2008 year, especially starting in November with the use of hounds. Cougar captures exceeded expectations with a total of 18 cougars being captured during the year. Human caused and natural mortality was high during the year with 5 of the 18 collared cougars dying during the year. We had 5 cougars interact with humans, 4 of which were initially captured in relation to a human interaction. All of these cougars were aversively conditioned following the interaction with humans. The first year of the study was successful, however we are switching to a different GPS/telemetry system as failure rates with the current collar system is unacceptable. 155 �WILDLIFE RESEARCH REPORT COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBANEXURBAN FRONT-RANGE OF COLORADO MATHEW W. ALLDREDGE P.N. OBJECTIVE 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban front-range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus) and estimating population densities of cougars for the state of Colorado. SEGMENT OBJECTIVES 1. Determine the efficacy of using microsatellites or mtDNA to delineate female cougar and black bear subpopulations across the state of Colorado. 2. Evaluate differences in DNA quantity from either a scat surface collection or a cross-sectional collection. 3. Evaluate differences in DNA quantity from successive feces depositions to determine the variation in quantities of genetic material in scats. Quantify differences in epithelial shedding rates. 4. Evaluate temporal, environmental, and seasonal effects on DNA quantity and quality for both controlled and uncontrolled conditions. 5. Determine the effectiveness of cage traps and hounds for capturing cougars on the Front-Range of Colorado. 6. Determine functionality and suitability of GPS collars on cougars in Front-Range habitats. 7. Implement cougar-human risk protocols and communications within CDOW and among public entities and determine if modifications are necessary. 8. Determine the feasibility of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets. 9. Evaluate political/social response to cougar research activities. INTRODUCTION Cougar management is a growing concern for the Colorado Division of Wildlife (CDOW). Cougar conservation and the maintenance of viable populations is a statewide issue as CDOW is charged with the management of cougars. However, the nexus created between cougar conservation and human health and safety is becoming a high priority issue within the urban and exurban areas of the state. Cougar conflicts (livestock depredation, pet depredation, and direct human interaction) within urban and exurban areas appear to be increasing as humans continue to encroach into cougar habitats. Because of the diversity of cougar management issues across the state, cougar research is focused on both statewide issues of cougar population structure and methods of estimating population demographics, and on urban/exurban issues of cougar/human interaction. Genetic techniques for monitoring or research of rare, elusive, and wide ranging species are of particular interest as other techniques are either impractical or financially prohibitive. Genetic techniques for monitoring and research of cougars in Colorado may be invaluable as alternative techniques are expensive and in many situations may not be possible. Capture and handling of cougars is expensive, time consuming, and may not give representative samples of the population. Large dispersal distances of cougars, especially males, will require impractically large study areas in order to understand demographic 156 �patterns that are affected by immigration. Capture may not even be possible in suburban and exurban areas of Colorado as logistical constraints associated with private land owners will likely prohibit the use of many capture techniques. Noninvasive genetic sampling (Hoss et al. 1992, Taberlet and Bouvet 1992) has the potential to provide a realistic method of sampling a population of interest. Noninvasive sampling techniques include the use of hair snares, and scat collections (Harrison et al. 2004, Smith et al. 2005). The use of scats for sampling cougar populations may be particularly useful and provide a representative sample of the population. Scat collections can either be done by searching transects with human observers (Harrison et al. 2004) or with trained dogs (Smith et al. 2005). Scats could also be collected from kill sites. Kill sites would need to be based on mortalities of radio-collared ungulate populations. Data from noninvasive sampling techniques are useful in describing dispersal patterns and estimating population size. Noninvasive genetic data are error prone, which in many cases is because of the quantity and quality of genetic material relative to the collection of noninvasive samples. Therefore, one objective over the last year has been to develop a study to evaluate degradation rates of DNA in fecal samples with respect to time and temperature. Use of genetic data for other purposes, such as delineating subpopulations, is also very useful for managing cougar and bear populations in the state. In these cases the goal is to examine local characteristics of the genetic data and determine if it is different among areas (subpopulation structure) or is similar across all areas (panmictic population). Nuclear DNA is inherited from both the mother and the father and therefore is less likely to describe sex-linked population structure. Male cougars and bears generally disperse over greater distances than females and therefore a female population substructure may be easier to detect than male population substructure. Examination of cougar and bear population structure has been examined using nuclear DNA but few studies have examined cougar population structure using mitochondrial DNA (mtDNA). Mitochondrial DNA is only inherited from the female in mammals and therefore lends itself to delineating female cougar population substructures. A second objective has been to determine if any genetic population structure can be identified for cougars and bears across the state by examining nuclear and mtDNA from statewide female cougar and bear harvest. At the local scale efforts have been made to initiate a cougar/human interaction study on the Front-Range of Colorado. Given that cougars currently coexist with humans within urban/exurban areas along Colorado‘s Front-Range, varying levels of cougar-human interaction are inevitable. The CDOW is charged with the management of cougar, with management options ranging from minimal cougar population management, to dealing only with direct cougar-human incidents, to attempted extermination of cougars along the human/cougar spatial interface. Neither, inaction nor extermination, represent practical options nor would the majority of the human population agree with these strategies. In the 2005 survey of public opinions and perceptions of cougar issues, 96% of the respondents agreed that it was important to know cougars exist in Colorado, and 93% thought it was important that they exist for future generations (CDOW, unpublished data). There is a growing voice from the public that CDOW do more to mitigate potential conflicts, and the Director of CDOW has requested that research efforts be conducted to help minimize future human/cougar conflicts. In order to meet these goals CDOW believes we need to directly test management prescriptions in terms of desired cougar population and individual levels of response. Long-term study objectives for the Front-Range Cougar Research project will involve directly testing management responses of cougars at various levels of human interaction, as well as collecting basic information about demographics, movement, habitat use, and prey selection. The CMGWG (2005) recommend that part of determining the level of interaction or risk between cougars and humans is to evaluate cougar behavior on a spectrum from natural, to habituated, to overly familiar, to nuisance, to 157 �dangerous. The CMGWG (2005) clearly state that there is no scientific evidence to indicate that cougar habituation to humans affects the risk of attack. Studying individual and population level responses of cougars will require capturing and radiocollaring cougars, as well as standardizing responses of CDOW personnel to human/cougar interactions. Therefore, in this initial year, we tested various cougar capture techniques in urban/exurban areas of interest for effectiveness and public acceptance and assessed the reliability of GPS collars as monitoring tools to assess cougar responses to management prescriptions. More importantly, clearly defined protocols have been implemented within CDOW (APPENDIX I, sub-appendix II) to direct how researchers and field managers should deal with various levels of risk to human health and safety, and these protocols were tested and evaluated in the field. A large portion of the Front-Range is a mosaic of private, city, county, State, and Federal public lands. An assessment of capture techniques allows future assessments of research feasibility and limitations that might be imposed by various land ownerships. Testing capture techniques and potential management actions also allows for an assessment of the receptiveness of future research within the various political/social environments. STUDY AREA GENETICS Identifying population structure for cougars and bears is a statewide effort. The initial effort for cougars is based on the entire female segment of harvested cougars for the state. The female harvest for bears is much larger, so the sample involved a group of bears from each of the northwest, northeast, southwest, and southeast state regional portions of bear habitat, in an attempt to capture the greatest genetic diversity for the state through spatial separation of sample areas. The genetic degradation study is being conducted at the Foothills Wildlife Research Facility, located in Fort Collins, Colorado. This is the facility where 3 sibling cougars have been raised in captivity and are part of other ongoing research efforts. COUGAR/HUMAN INTERACTION The pilot field study is being conducted in Boulder and Jefferson counties, in an area from near Interstate 70 north to approximately Lyons, Colorado, which is also a likely area for addressing long-term research objectives (see Figure 1). This area is comprised of many land ownerships, including private, Boulder city, Boulder County, Jefferson County, and state and federally owned lands. Therefore, we have been directly involved with Boulder city and Boulder and Jefferson county governments to obtain agreements from these entities on conduct of research and protocols for dealing with potential human/cougar interactions prior to conducting any research efforts. METHODS GENETICS Genetic samples for the statewide population structure were obtained from statewide voluntary tooth collections from harvested bears and cougars. DNA was extracted from teeth using the DNeasy Blood and Tissue Kit (see Alldredge 2007, Study Plan APPENDIX I-A, sub-appendix I). Following extraction, samples were sent to Sara Oyler-McCance at the Rocky Mountain Center for Conservation Genetics and Systematics, for PCR and sequencing (again, see Alldredge 2007, sub-appendix I for specific methods). 158 �Fecal samples were also collected from the 3 sibling cougars located at the Foothills Wildlife Research Facility. During the year 20 to 30 feces were collected from each cat and samples were placed at random into one of three treatment groups (-5 C, +5 C, and +15 C). Genetic samples were collected from these at the time of initial collection and at 2 weeks, and 1, 2, 3, 4, and 6 months post deposition. DNA was extracted and then stored at -20 C until PCR and genetic sequencing was done at the Rocky Mountain Center for Conservation Genetics and Systematics laboratory. COUGAR/HUMAN INTERACTION Baiting, using deer and elk carcasses, has been conducted regularly beginning in May, 2007. Bait sites are monitored using digital trail cameras to determine bait site activity. Cage traps were generally used for capture when cougars removed the bait and cached it. Beginning in November, 2007 and continuing through April, 2008, hounds were also used several times per week to capture cougars. Captured cougars were anesthetized, monitored for vital signs, aged, measured, and ear-tagged. All independent cougars (> 18 months old) were fitted with GPS collars. For detailed capture and handling procedures see the study plan APPENDIX I. A supplemental study plan was written as a justification for increasing sample size requirements and to specifically address aversive conditioning treatments and implementation (Appendix I). Cougars involved in human interactions that invoke a management response are subject to aversive conditioning treatments and were treated at the time of the incident. Additional cougars were also captured and added to the study because of their interaction with humans. RESULTS AND DISCUSSION GENETICS DNA was extracted from all 568 bear teeth collected from harvested bears during 2007. Of those, 75 females were selected for genetic sequencing, representing 4 distinct regional spatial groups across the state. Using 8 microsatellite loci, all 75 female bears were genotyped. Using program STRUCTURE (2007), the data indicate that bears in Colorado function as one mega-population, rather than as distinct subpopulations (Figure 2). Given this data combined with the previous year‘s data (n = 49 females, Alldredge 2007), the statewide bear population can probably be viewed and managed as a megapopulation. DNA was extracted from all 192 cougar teeth collected from harvested cougars during 20072008. Additionally, DNA was extracted from samples taken from the Uncompahgre Plateau cougar study (Logan 2006), and from samples taken from the front-range cougar study (Alldredge 2007). All female samples from the harvest plus additional samples from the research projects were selected for genetic sequencing for a total of 56 samples across the state. Given the limited sample size for females, spatially distinct regional groups were not available. Using 15 microsatellite loci, all 56 samples were genotyped. The data revealed almost no population structure for cougars across the state (Figure 3). Again, given this data in conjunction with the previous year‘s data (n = 54 females, Alldredge 2007), the statewide cougar population can probably be viewed and managed as a mega-population. Close to 200 genetic samples from the genetic degradation study have been analyzed. This work is still ongoing so an assessment of genotyping error rates cannot be made. However, sufficient genetic material for genotyping has been found in samples up to 4 months old. Therefore, we will continue to collect samples from feces in treatment categories out to 6 months. COUGAR/HUMAN INTERACTION Starting in September, 2007 cougar capture efforts were maintained across the study area on city and county open space properties. From November, 2007 through April, 2008, capture efforts included 159 �the use of hounds on the larger open space properties. Throughout this period there was excellent cooperation with the conduct of the research project among branches within the CDOW and among the CDOW and city and county entities involved with the study. This cooperation included numerous volunteers from these entities to assist with checking bait sites and running hounds. A total of 18 cougars were captured during the 2007-2008 year (Table 1). Hound capture was the most effective with 9 initial captures. Captures from reported cougar kills using cage traps were also effective with 5 total captures. Only 1 initial capture was from a bait site. Cage traps following pet/livestock depredation accounted for 2 captures. The final capture was a cougar that was free-range darted in the city of Boulder. Of the 18 total cougars captured, 10 were males. Of the males, 3 of these were adults. Over half (10 of 18) of the captured cougars were between 1 and 2 years old. Home ranges for collared cougars have been determined using minimum convex polygons (MCP) to depict the general pattern of use (Figure 4). Home ranges are fairly linear in a north-south direction. The two adult male home ranges are the largest with areas of 537 km2 and 233 km2 for AM06 and AM04, respectively. Female home ranges are smaller with areas between 90 and 118 km2. Subadult male home ranges are the smallest with areas between 40 and 50 km2. The home range for AF03 appears large but this is representing a dispersal movement and not a true home range. Mortalities of collared cougars were high with 5 of 18 (28%) dying during the year (Table 1). One of these was a young male (AM02) interacting with an adult male (AM04) and being killed. Two of the mortalities were road kills (AF10 and her kittens, and AM07). AM20 was depredating sheep and was shot by the land-owner as AM20 approached the barn where the sheep were being held. We located AF17 from a mortality beacon, but, aside from some trauma to her front shoulder, cause of death could not be determined. During 2007-2008 there have been 5 cougars that have been aversively conditioned. AM04 provided the first aversive conditioning opportunity after he killed several goats near Eldorado Springs in October, 2007. AM04 was captured near the depredation site, relocated to his original capture location and shot with beanbags. Prior to the aversive conditioning AM04 used this depredation area frequently, but has not used the area much following the treatment (Figure 5). In April, 2008, AM04 was seen in the city of Boulder and had to be darted as a number of onlookers pushed him deeper into the city. At this time he was moved outside the city and shot with beanbags. AM04 entered the city again in August, 2008 and killed a deer in Boulder. He was trapped, relocated to the southwestern edge of his home range and shot with beanbags. Although AM04 uses urban areas, he is rarely seen by people and does not appear to be a threat or habituated to humans. Both AF17 and AM13 were captured and aversively conditioned following depredation events on Sugarloaf, northwest of Boulder. AF17 was captured after killing a dog. She was relocated approximately 2 km to remove her from the urban area and shot with beanbags on release. AM13 was captured after killing a llama on the remote edge of private property. He was released on site because of the remote location and shot with beanbags on release. To date, neither AF17 nor AM13 have had any further human interaction. Both AF12 and AM14 were captured in the city of Boulder and aversively conditioned, but have since been relocated. AF12 killed a deer in Boulder on May 7, 2008 and was captured, relocated about 10 kilometers outside the city and shot with beanbags on release. AM14 was seen in the city on May 15, 2008 and was darted out from under a home-owner‘s deck, relocated about 5 km outside the city and released. AM14 and AF12 returned to the city within 5 and 21 days, respectively, and were captured and relocated more than 40 km from the city and shot with beanbags on release. AF12 has returned to the 160 �Boulder area but has not been captured again. AM14 has remained near his release sight and may have been seen in urban areas near Nederland. Initially the Lotek GPS collars appeared to be performing satisfactorily with an approximate acquisition success rate for locations of 60%. However, several collars have failed after several months in the field and several of the collars recently deployed have failed. These collars are not transmitting the VHF beacon or the beacon has a very weak signal, or the collars are not acquiring any GPS locations. In the coming year we will try Northstar GPS-satellite collars as a more reliable/economical method to track cougars during the study. SUMMARY A total of 75 and 56 black bear and cougar samples, respectively, were used to assess genetic population structure across the state. Analyses suggest that both black bear and cougar populations are panmictic, representing more of a megapopulation than a metapopulation. This is reasonable given the high dispersal rates and large dispersal distances typical for both species. Genetic analysis for cougar feces revealed that DNA is still present in samples after feces have been in controlled temperature environments for up to 4 months. Genotyping error rates still need to be assessed. However, the presence of DNA in these samples suggests that field detection of cougar scats may be a viable non-invasive population sampling technique. A total of 18 independent cougars were captured during 2007-2008 on the front-range cougar pilot study. Both the use of cage traps and hounds proved to be effective methods for capturing cougars, although luring cougars to bait sites has very limited success. Mortalities during the year were high with a total of 5 cougars dying from both natural and human related causes. Aversive conditioning was done on 5 cougars with mixed results. Lotek GPS collars are proving to be unreliable and North Star Satellite collars will be used in the upcoming year. LITERATURE CITED Alldredge, M.W. 2007. Cougar demographics and human interactions along the urban-exurban front range of Colorado. Wildlife Research Report July: 153-202. Colorado Division of Wildlife, Fort Collins, USA. Cougar Management Guidelines Working Group. 2005. Cougar Management Guidelines, 1sted. WildFutures, Bainbridge Island, Washington, USA. Harrison, R. L., P. B. S. Clarke, and C. M. Clarke. 2004. Indexing swift fox populations in New Mexico using scats. American Midland Naturalist 151:42-49. Hoss, M., M. Kohn, S. Paabo, F. Knauer, and W. Schroder. 1992. Excrement analysis by PCR. Nature 359:199. Logan, K.A. 2006. Cougar population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report July:95-122. Colorado Division of Wildlife, Fort Collins, USA. Smith, D. A., K. Ralls, B. L. Cypher, and J. E. Maldonado. 2005. Assessment of scat-detection dog surveys to determine kit fox distribution. Wildlife Society Bulletin 33:897-904. Taberlet, P., and J. Bouvet. 1992. Bear conservation genetics. Nature 358:197. Prepared by Mathew W. Alldredge, Wildlife Researcher 161 �Table 1. Summary of cougars captured during 2007-2008. Ages are based on tooth wear. Capture types are hound captures (hound), free-range darted, (free-range), cage trapping from bait sites (bait), or cage trapping from reported cougar kills (kill). Status indicates a cat that is still alive or indicates the type of mortality. Cougar ID Date Sex Age Capture type Location Status AM02 AM04 AM06 AF03 AF01 AM05 AM07 AF08 AM09 AF10 AF19 AF11 AM20 AF15 AF17 AM13 AF12 AM14 1/10/08 7/14/07 11/21/07 11/29/07 12/17/07 12/19/07 12/26/07 12/26/07 12/28/07 1/15/08 3/4/08 3/5/08 3/6/08 3/18/08 3/29/08 5/8/08 5/8/08 5/15/08 M M M F F M M F M F F F M F F M F M 1.5 7 5 4 2 1.5 1.5 1.5 1.5 7+ 8 1.5 4 6 9 2 2 2 Hound Bait Hound Kill Kill Hound Hound Hound Hound Kill Hound Kill Hound Hound Depredation Depredation Kill Free-range White Ranch White Ranch Heil Valley Flagstaff NCAR White Ranch Heil Valley Heil Valley Heil Valley Apex Heil Valley Table Mesa White Ranch Coffin Top Sugarloaf Sugarloaf Boulder Boulder Intraspecific Alive Alive Alive Alive Alive Road kill Missing Missing Road kill Alive Alive Depredation Alive Unknown Alive Alive Alive Figure 1. Study area for 2007-2008 Front Range cougar pilot study extending from Lyons to Golden. 162 �Figure 2. Cluster diagram of microsatellite data identifying little evidence of population substructure for bears across the state of Colorado based on 75 individual females harvested in 2007 from four distinct spatial locations representing the northeastern, northwestern, southwestern, and southeastern portions of Colorado. Figure 3. Cluster diagram of microsatellite data identifying little evidence of population substructure for cougars across the state of Colorado based on 56 individual females harvested in 2007 and from cougars sampled as part of ongoing research from across Colorado. 163 �Figure 4. Minimum convex polygon home-ranges for cougars captured during the 2007-2008 front-range cougar pilot study. 164 �Figure 5. Home-range maps for cougar AM04 depicting home-range and location from July 14, 2007 until October 17, 2007 (left) and October 18, 2007 until January 5, 2008 (right). Arrows point to Eldorado Springs area where AM04 was captured and aversively conditioned following a goat depredation. The lack of locations in this area following aversive conditioning is evident in the homerange on the right. 165 �APPENDIX I PROGRAM NARRATIVE PILOT STUDY PLAN FOR MAMMALS RESEARCH FY 2007-08 State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 2 Federal Aid Project No. N/A : : : : : : : : Division of Wildlife Mammals Research Predatory Mammals Conservation Front-range Cougar-Human Interaction Pilot Study: Feasibility Assessment of Field Techniques and Protocols, Phase II: Enhancing Assessment of Aversive Conditioning Techniques For Cougar Human Interactions FRONT-RANGE COUGAR-HUMAN INTERACTION PILOT STUDY: FEASIBILITY ASSESSMENT OF FIELD TECHNIQUES AND PROTOCOLS, PHASE II, ENHANCING ASSESSMENT OF AVERSIVE CONDITIONING TECHNIQUES FOR COUGAR-HUMAN INTERACTIONS Phase II January 2008 Principal Investigators Mathew W. Alldredge, Wildlife Researcher, Mammals Research David J. Freddy, Mammals Research Leader Cooperators Kathi Green, NE Assistant Regional Manager Mark Leslie, Liza Hunholz, Reid DeWalt, NE Area Wildlife Managers Janet George, NE Senior Terrestrial Biologist Study Plan Approval Prepared by: Mathew W. Alldredge Date: Submitted by: Mathew W. Alldredge Date: Reviewed by: Chad J. Bishop Date: Date: Date: Reviewed by: Paul Lukacs Biometrician Date: Approved by: Dave Freddy Mammals Research Leader Date: 166 �PROGRAM NARRATIVE PILOT STUDY PLAN FY 2007-08 FRONT-RANGE COUGAR-HUMAN INTERACTION PILOT STUDY: FEASIBILITY ASSESSMENT OF FIELD TECHNIQUES AND PROTOCOLS, PHASE II, ENHANCING ASSESSMENT OF AVERSIVE CONDITIONING TECHNIQUES FOR COUGAR-HUMAN INTERACTIONS Phase II January 2008 A pilot study plan enhancement submitted by: Mathew W. Alldredge, Wildlife Researcher, Mammals Research David J. Freddy, Mammals Research Leader PREFACE Alldredge (2007) in his initial pilot study plan approved in March 2007 listed 5 objectives to begin addressing with the initial capture and radio/GPS-collaring of 6 cougars. This pilot study plan enhancement (Phase II) focuses on expanding efforts to assess objective 4: determine the feasibility of aversive conditioning techniques on cougars within urban/exurban areas. From May through December 2007, project efforts resulted in capturing 6 cougars which have provided valuable information on effectiveness and deployment of capture techniques, effectiveness of GPS collars, cougar movements, and initial but limited information on cougar-human interactions; with all results to date supporting all original objectives 1-5 (see page 4 of this document). We are confident to move forward with radiocollaring more cougars to enhance our abilities to address the feasibility of aversive conditioning both in the short- and long-term and provide our rationale in this document for expanding the number of cougars to be captured during our pilot study phase. Especially important, is maintaining our immediate ability to capture cougars during the winter months of January-February when winter snow conditions are most likely to be optimal for detecting and tracking cougars. Our multi-year, Front-range cougar project study plan, incorporating results of our pilot efforts, will address cougar-human interactions over an expanded geographic area and will utilize all cougars captured and collared during the pilot phases of this project. We anticipate the multi-year study plan will be completed and approved by April 2008. In the interim, this enhanced plan will allow us to expand our capture effort from the original 6 cougars, which was the absolute minimum to start the project, to 20 additional cougars. All original pilot study plan objectives will be enhanced by this additional capture effort. NEED Although cougar attacks on humans are rare (CMGWG 2005), they have increased in recent decades. From 1890 to 1990 there were a documented 9 fatal attacks and 54 non-fatal attacks on humans in the United States and Canada (Beier 1991, Fitzhugh et al. 2003). Seven fatal and 38 non-fatal attacks on humans occurred following Beier‘s 1991 publication and Fitzhugh et al.‘s 2003 publication. Cougar attack rates on the front-range of Colorado have been estimated at one in every 2.2 million person-days. The increase in attacks also corresponds to a large increase in human-cougar incidents, which are likely due to habitat reduction, human encroachment, increased human recreational activities, and possible increases in cougar populations (CMGWG 2005). Torres et al. (1996) found no differences associated with gender in the likelihood of a cougar attack on humans. However, Ruth (1991) did find that subadults were the age group most likely to interact with humans. The CMGWG (2005) found that a combination of inexperience and unfamiliarity with their environment, as well as hunger, may cause young cougars to have more negative interactions with humans. 167 �CDOW wildlife managers are faced with decisions about how to manage cougar populations and individual cougars in order to maintain viable populations and maintain acceptable levels of human safety. Defining acceptable levels of human safety is difficult because people‘s perceptions are different when interactions do not directly affect them. In the 2005 public opinions survey, only 44% of respondents felt it acceptable to destroy a cougar that attacks and injures or kills a person that is recreating in cougar habitat, while 49% found eliminating the cougar unacceptable (CDOW, unpublished data). Other difficulties associated with managing cougar populations in areas with high levels of human interaction are caused by the limited amount of information that is currently known about cougars in these exurban situations and responses of cougars to management prescriptions (CMGWG 2005). There is a growing voice from the public that CDOW do more to mitigate potential conflicts (CMGWG 2005), and the Director of CDOW has requested that research efforts be conducted to help minimize future human/cougar conflicts. In order to meet these goals CDOW believes we need to directly test management prescriptions in terms of desired cougar population and individual levels of responses. Long-term study objectives for the Front-Range Cougar Research project will involve directly testing management responses of cougars at various levels of human interaction. The CMGWG (2005) recommend that part of determining the level of interaction or risk between cougars and humans is to evaluate cougar behavior on a spectrum from natural, to habituated, to overly familiar, to nuisance, to dangerous. These categories are defined as (CMGWG 2005): Habituated—frequent use of developed area and cougars appear comfortable in the presence of humans. Overly familiar—a cougar purposefully approaches a human, or allows a human to approach it after the cougar has seen the human. Nuisance—cougar exhibits overly familiar behaviors more than once. Dangerous—displayed non-defensive aggression towards humans (postures, vocalizations, and actions communicating an intent to harm). Note that aggressive behaviors could also be defensive if the cougar perceives the human as a threat to itself, its young, or a food source, or if the cougar is surprised or harassed by humans. The CMGWG (2005) describes cougar behaviors and the level of risk to humans as perceived by the authors (Appendix III, Table 1). We have added an additional column that categorizes the level of risk, which will be used to determine management treatments that will be applied during research efforts. Although cougars may habituate to human developments and activities (Ruth 1991), both habituated and non-habituated cougars may experiment with humans as potential prey (Aune 1991). The CMGWG (2005) clearly state that there is no scientific evidence to indicate that cougar habituation to humans affects the risk of attack. Clearly, cougars representing a danger to human health and safety should be removed, but the appropriate response to cougars that are overly familiar or habituated to humans is unclear. Lethal control is loosing public support (Reiter et al. 1999) so other options need to be examined. Shivik and Martin (2000) emphasize the need to research and determine effective non-lethal control techniques, or managers risk loosing credibility with the public. There have been no studies confirming the effectiveness of aversive conditioning on cougars (CMGWG 2005). Beier (1991) describes two unsuccessful attempts at aversive conditioning (one cougar shot with rock salt, one treed and collared), however, one of these was already exhibiting aggressive 168 �behavior and the other was in poor body condition. McBride et al. (2005), used hound capture, and subsequent hound chases as a form of aversive conditioning on 4 Florida panthers with some degree of success. Studying individual and population level responses of cougars will require capturing and radiocollaring cougars, as well as standardizing responses of CDOW personnel to human/cougar interactions. In doing this we will be able to develop a series of comparable case histories that can demonstrate effective methods for dealing with cougars interacting with humans. A primary objective of this study is to determine the feasibility and effectiveness of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds, rubber bullets, beanbag bullets and pepper spray fired from a shotgun. In conjunction with aversive conditioning, relocation of cougars will generally be part of the treatment as this will be a required management action when the cougar-human incident occurs within neighborhoods. Additionally we do not want to chase a cougar from one neighborhood to another. Treatments will be applied in a manner that is consistent with management options so that wildlife managers in the future will be able to implement these techniques without the aid of cougars being radio-collared. Making this assessment of aversive conditioning techniques will provide crucial information for developing long-term management prescriptions for dealing with cougars interacting with humans and possibly preventing habituation to humans. OBJECTIVES 1. Determine the effectiveness of cage traps and hounds for capturing cougars on the FrontRange of Colorado. 2. Determine functionality and suitability of GPS collars in front-range habitats. 3. Implement cougar-human risk protocols and communications within CDOW and among public entities and determine if modifications are necessary (see Appendix III). 4. Determine the feasibility of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and rubber bullets. a. Assess the effectiveness of various methods of aversive conditioning in terms of decreased use by individual cougars of urban areas and future incident rates. b. Statistically test the effectiveness of the aversive methods in affecting cougar behavior. 5. Evaluate political/social response to cougar research activities. EXPECTED BENEFITS An assessment of aversive conditioning techniques will provide future guidance for wildlife managers in dealing with cougar-human conflicts. Understanding the likely response of a cougar to a management treatment will help managers chose the right response to a particular situation. This will also give us credibility with the public with regard to the management actions chosen for a particular event, because we will have some understanding of the long-term effects on the cougar‘s future behavior and not just a short-term solution to an incident that may be repeated. APPROACH Cougars have been captured during the initial phases of this pilot project (Alldredge 2007) and cougars will continue to be captured on large publicly owned properties, such as city and county openspace. These cougars are captured in their natural environments and we have no knowledge of any interaction with humans among these cougars, although the potential exists. These cougars will be incorporated into the aversive conditioning treatments as they are reported as interacting with humans, or 169 �as they demonstrate selection for urban areas which could be viewed as potential habituation to humans. Radio/GPS-collared cougars that travel through urban areas and/or occasionally kill naturally occurring prey items in urban areas will not be viewed as problem cougars and will not be included in aversive conditioning treatments. See Appendix I for approved capture and handling protocols Additional cougars for aversive conditioning treatments will be obtained from actual reported cougar/human interactions. In general, these will not include cougars that are reported to have killed naturally occurring prey items on private properties resembling the naturally occurring environment. These cougars will be individuals involved in human-interactions that would typically result in management actions, such as hazing or relocation , that resemble aversive conditioning treatments. All such management level cougars will be radio/GPS-collared and treated with aversive conditioning for this portion of the study. At this time, we consider aversive conditioning treatments on cougars to potentially be: multiple captures and handling of cougars, single or multiple treatments using rubber buckshot, beanbags, or pepper spray fired from a shotgun, single or multiple chases using hounds, and potential combinations of capture, hound chases, and rubber buckshot or beanbags or pepper spray (specific application of treatments are outlined in Appendix II). Initially, we want to assess situations and methods that are already being implemented by local wildlife managers. The most likely scenario will involve incidents occurring in neighborhoods, where relocating the cougar is necessary prior to any application of an aversive conditioning treatment. For these situations, all treatments will require the relocation of the offending cougar to an adjacent open-space property or similar area. Following relocation and at the point of release, we will either chase the cougar off using rubber bullets or beanbag rounds, pepper spray, or hounds. For first time offenders we will initially try rubber bullets or beanbag rounds. Second time offenders will be chased with hounds. If rubber bullets or beanbag rounds are not affecting cougar behavior, we will begin using pepper spray on first time offenders. The other potential scenarios that will occur are incidents in areas where a cougar can be directly conditioned or chased from the incident area. We will mimic the above approach as much as possible, and use rubber bullets or beanbag rounds on first time offenders. If possible we will chase individuals with hounds on their second offense, although this may not always be practical. Pepper spray may not be practical either in many situations. As a second level treatment where direct hound chases are not practical, we will attempt to capture, relocate, and aversive condition the individual. At this time, these aversive treatment efforts will be primarily observational. Once we have determined a method that routinely elicits the desired response we will focus on that method to achieve a statistically valid sample size. Response variables would be, future incident rates following aversive conditioning and change in use patterns associated with urban areas. However, this may take several months or years to accomplish. To demonstrate required sample sizes we have run a detailed simulation of the potential human interaction and aversive conditioning phase of the study in order to obtain expected values and standard errors for a hypothetical sample of 20 collared cougars some of which may interact with humans at a level requiring management actions. Very little information exists about human-cougar interaction rates and variability and effectiveness of aversive conditioning; therefore many assumptions must be made to conduct any kind of statistical power analysis. The assumptions are as follows: 1. 80% of all cougars in the study area will interact negatively with humans. 2. All cougars behave and respond the same to the urban environment and aversive conditioning (i.e. no sex or age effects). 170 �3. 25% of cougars that have a negative interaction with humans are not habituated to urban environments and will not interact with humans again. The remaining portion of the population (75%) will have additional negative interactions following the first interaction. 4. Aversive conditioning is 50% effective, so that half of the treatment group (on average) will not interact with humans following the aversive treatment. Based on these assumptions we would expect 16 of the 20 collared cougars to interact negatively with humans. Following the first negative interaction, half of the cougars would be placed in a control group and half in a treatment group, giving an expected 8 cougars in each group. No aversive conditioning would be applied to the control group, while aversive conditioning (chased by hounds and/or shot with bean bags) would be applied to all of the treatment animals. Based on our assumptions we would expect 6 of the control animals to continue to interact negatively with humans and 3 of the treatment animals to continue negative human interactions. Using these assumptions we simulated the aversive conditioning process 1000 times, assuming a binomial process (success-failure) and only 1 aversive conditioning attempt. The average number of control and treatment cougars from the simulations was 8±2 cougars each with a minimum of 4 and a maximum of 10 in each group. The average number of control cougars that continued to have negative human interactions was 5.8±4.06, with a minimum of 1 and a maximum of 10. The average number of treatment animals that continued to have negative interactions was 2.8±3.81, with a minimum of 0 and a maximum of 7. Location of Work: This work will be conducted along Colorado‘s front-range, in Boulder, Jefferson, Gilpin and Larimer counties. The study area is defined by the existing boundary for the ongoing cougar research project. Schedule of Work: Time January 2008, ongoing September 2008, ongoing Activity Capture Cougars/Begin treating cougars involved in human incidents Summary report of findings Estimated Costs: Salaries of permanent employees, as well as many other logistical costs (vehicles and aerial flights) will be covered by existing project funds in the CDOW carnivore research and terrestrial management programs. 2007-2008 Category Personnel Field Technician(s) (6 months) $14,050 Operating Expenses Field/Capture Equipment Lotek GPS collars (14) ATS VHF collars (6) Vehicle Mileage/Lease Total Expenses $ 6,000 $63,000 $ 1,500 $ 8,000 $92,550 171 �LITERATURE CITED Alldredge M. W. 2007. Program Narrative Pilot Study Plan: Front-range cougar-human interaction feasibility assessment of techniques and protocols. Pages 181-202 in Alldredge, M.. 2007. Cougar demographics and human interactions along the urban-exurban Front-range of Colorado. Wildlife Research Report July: 153-202. Colorado Division of Wildlife, Fort Collins, USA. Aune, K. E. 1991. Increasing cougar populations and human-cougar interactions in Montana. Pages 8694 in C. E. Braun, editor. Cougar-human interactions: Symposium and Workshop. Colorado Division of Wildlife, Denver, Colorado, USA. Beier, P. 1991. Cougar attacks on humans in the United States and Canada. Wildlife Society Bulletin 19:403-412. Cougar Management Guidelines Working Group (2005) Cougar Management Guidelines, 1st edn. WildFutures, Bainbridge Island, Washington, USA. Fithzugh, E. L., M. W. Kenyon, and K. Etling. 2003 Lessening the impact of a cougar attack on a human. In Proceedings of the 7th Mountain Lion Workshop, Jackson, Wyoming, USA. McBride, R., D. K. Jansen, R. McBride, and S. R. Schulze. 2005. Aversive conditioning of Florida panthers by combining painful experiences with instinctively threatening sounds. Page 136 In Proceedings of the 8th Mountain Lion Workshop. Leavenworth, Washington, USA. Reiter, D. K., M. W. Brunson, and R. H. Schmidt. 1999. Public attitudes toward wildlife damage management and policy. Wildlife Society Bulletin 27:746-758. Ruth, T. K. 1991. Cougar use in an area of high recreational development in Big BendNatinal Park, Texas. Thesis, Texas A&M University, College Station, Texas, USA. Shivik, J. A. and D. J. Martin. 2000. Aversive and disruptive stimulus applications for managing predation. The 9th Wildlife Damage Management Conference Proceedings 9:111-119. Torres, S. G., T. M. Mansfield, J. E. Foley, T. Lupo, and A. Brinkhaus. 1996. Mountain lion and human activity in California: testing speculations. Wildlife Society Bulletin 24:451-460. 172 �APPENDIX II CAPTURING AND HANDLING PROCEDURES FOR FREE-RANGING COUGARS Modified by MWA on 1/18/2007: Puma changed to cougar and schedule for monitoring cage traps modified after consultation with CDOW veterinarian L. Wolfe. Delivery of anesthetic drugs via projectile syringe or jab pole, cage traps, or foot snare may be used to capture cougars. All of these techniques have proven effective and safe for capturing cougars under field conditions commonly encountered in Colorado. This document is intended to serve as a comprehensive reference for future cougar studies to avoid unnecessary complexity in study protocols submitted for ACUC review. Capture Techniques Trained hound pursuit As described in Shaw (1979), an experienced houndsman with trained dogs is used to track and tree or bay each cougar. Field anesthesia is determined under the supervision of the attending veterinarian. Anesthetic drugs will be administered intramuscularly (preferably the caudal thigh) via projectile syringe using a gas-powered projector. For capture, cougars will be anesthetized with Telazol (6-9 mg/kg) and xylazine HCl (1.8-2 mg/kg) or ketamine (10-11mg/kg) and xylazine HCl (1.8-2mg/kg) or ketamine (2 mg/kg) and medetomidine (0.075 mg/kg) (Shaw 1979, Logan et al. 1986, Kreeger 1996). See drug dosages below (Table 1, Appendix II). If the cougar is treed, then people and dogs should be removed from the immediate area to give the animal a chance to descend before becoming completely anesthetized. If the cougar remains in the tree until almost completely anesthetized, then someone wearing climbing gear will climb to the cougar and attach either a chest harness (preferred) or hind leg noose (e.g. bovine hobbles) to 2 legs and quickly lower the animal to the ground. If possible, other personnel will hold a taunt net, 3 by 3 meters square, below to break the cougar‘s fall should it slip before a harness or rope can be secured. If there aren‘t enough people to hold the net, anchor the net about 2 m above the ground and on adjacent trees or branches using ropes & carabiners. Occasionally cougars will jump from the tree immediately after being darted. If there is snow cover, the cougar should be tracked with the dogs on leads. Attention should be given to changes to the cougar‘s gait and direction of travel. When anesthesia is effective, the cougar‘s tracks will weave and show signs of stumbling. Usually the cougar can be found laying or sitting on top of the snow. If after 15 minutes, it appears that the cougar is traveling normally, then dogs can be released on the cougar‘s tracks again to encourage it to tree. When the ground is bare, at least one non-aggressive dog will be released on the cougar‘s trail to drive the dog to bay. If the cougar is radio-collared, radio-telemetry can be used to track the cougar. Upon first approach of an apparently anesthetized cougar, a 4-5 foot stick will be used to gently prod the paws and muzzle of the animal; if there is no response (i.e. snarling or biting), then assume anesthesia is sufficient for handling. Once anesthetized apply an antibiotic or mineral oil based eye ointment and a blindfold to reduce visual stimuli and protect the eyes from bright sun light and debris. Vital signs should be monitored in the anesthetized cougar. Normal signs: pulse ≈ 70―80 bpm, respiration ≈ 20 bpm, capillary refill time ≤2 sec., rectal temperature ≈ 101oF average, range = 95―104oF (Wildlife Restraint Handbook, 1996, California Dep. of Fish and Game, Wildlife Investigation 173 �Laboratory, Sacramento, Kreeger et al. 2002). In temperatures near or at sub-freezing wrap the anesthetized cougar in a thermal blanket. In hot temperatures, the cougar should be treated with water on the head, abdomen, and inguinal area. Cougars that receive lacerations during capture will be given antibiotics. When the cougar is being sampled it should be moved from one side to the other or in sternal recumbency about every 10 minutes to prevent hypostasis in the downside lung. When sampling procedures are completed, the blind-fold and leg restraints (e.g. hobbles or snare cable) will be quickly removed, and the cougar will be allowed to recover from the sedation either naturally or with the aid of an antagonist. When prescribed, yohimbine HCl (0.125 mg/kg IV) will be used to antagonize xylazine sedation and atipamezole (0.3 mg/kg) will be used to antagonize medetomidine sedation. Cage trapping A cage-type trap for live capture of bears was developed by Beck (1993). The trap measures 1.8m long and 1.0m high and wide. The frame is constructed of angle iron, and all side and top panels are wire mesh of 1.9cm mesh size. The floor is 16-gauge steel. A spring-powered, solid aluminum door is mounted on a full-length hinge at one end. A full-length latching mechanism holds the door closed. The door is triggered via a treadle pedal mounted on the floor 1.0m from the door. A standard garage door coil spring provides the closing power. Along one side of the trap is a hinged panel measuring 1.8m by 0.3m. Vertical bars placed on 0.3m centers behind this panel. Swinging the window up allows access through the barred area for administering immobilizing drugs by jabpole. Each trap weighs approximately 236kg. In the first study in which these traps were used, there was only one injury to a bear in 134 captures. An adult male broke a canine tooth while in the trap. Of the limited number of times these trap have been used for cougars, no known injuries have occurred to date (T. Beck, pers. comm.). A cage trap designed specifically for the capture of cougar has been used to manage cougar human conflicts in California since the late 1980s (Shuler 1992). A similar cage trap was used to safely capture cougar for research on cougar human interactions in San Diego County, California (Sweanor et al. in prep.). The cage trap for that study measured 48 in. tall, 40 in. wide, and 10 ft. long. It was built on a frame of 1 ½ in. angle iron with 2 in. by 4 in. grid horse panel made of 3/16 in. welded steel rod for the walls, floor, door, and roof. It weighed about 250 lb (113kg). A cage trap was designed by Don Hunter (USGS) and Colorado State University‘s Mechanical Engineering Department. The trap was designed to be smaller, lighter, collapsible, and safer than what was previously available. A counter-weighted door drops closed slowly and quietly so as not to injure any members of a family group caught in the doorway. In addition, there are air-pressured cylinders that slow the door even further and a rubber bumper along the edge in case a tail is caught in the way of the closing door. The trap is 3.5 ft. tall, 3.5 ft. wide and 6 ft. long, constructed of 2 in. by 4 in. grid pattern steel horse panel with 0.225 in. rod. A cage trap will be baited with a deer carcass that will be tied to the end mesh panel opposite the door of the trap. The trap will be checked as early as possible the following morning or immediately after a capture occurs if fitted with a transmitter to be triggered upon closing of the door. The researchers should monitor the trap as soon as possible after sunrise every morning to minimize time in the trap and to avoid human interference from recreational activities. Normally, when a cougar has claimed a bait at a cage trap, it is caught fairly soon after night-fall. Researchers can work the cougar with a spot-light, head lamps, and lantern. Cougars will be immobilized with a jab-pole or syringe as described above. Drug dosages and animal handling will be as described above. 174 �Foothold Snares Foot-hold snares are an effective, relatively safe technique for capturing cougars particularly in areas not conducive to using trained hounds (Logan et al. 1999). The snares are constructed to minimize injuries to the cougar. The snare, also called the Aldrich foot snare, was originally designed for the capture of bears. It has been modified to use for cougars. The spring activated snare secures a 3/16 inch steel cable around the foot of the cougar, closing tight with the action of a small piece of angle iron fashioned into a sliding lock mechanism. The snares have been modified considerably over the years for cougars by incorporating a large spring to diminish force applied to the foot and a shock absorption device into the cable. The inside of the loop is wrapped with duct tape to minimize the surface abrasion on the skin of the foot. An in-line swivel is placed in the cable to avoid torsion of the foot and potential bone fracture. A short lead is attached to the snare to further minimize stress to the leg. The lead is then secured to a multi-branched flexible bush with a double off-set hook drag made of 5/8 in. rebar steel. It can also be secured to a tree 4 inches or greater in diameter with 3/16 in. or ¼ in. steel cable clamped and stapled to the base of the tree so the cougar can not climb the tree with the snare. Branches of the tree are lopped of with a saw or an axe about 8 ft. up the tree so the cougar can not hang itself from a branch by the snare cable. An area of 5 meters or more is cleared around the snare site to eliminate potential leg fractures resulting from a fulcrum situation in conjunction to an adjacent tree (Duggins Wroe, pers. comm.) or torque on the leg bones caused by revolutionary twisting of the cable when the swivel is isolated by the foot-loop cable becoming wrapped around stout vegetation. Details on how to safely structure the snare and to choose and prepare snare sites are in Logan et al. 1999. Modifications have been made to avoid capturing non-target animals. The concealed 10 inch loop of cable is positioned over the trigger of the spring. The trigger has a 4 inch plastic trap pan adhered to the top surface. The pan and trigger are positioned over a hole dug in the ground and filled with a 12x12x4 inch piece of high density foam. This foam prevents smaller animals from triggering the snare. Large branches are angled over the snare to force ungulates to step over or go around the snare. The duct tape on the loop keeps it from closing too tightly and usually allows smaller-footed animals such as ungulates, coyotes and bobcats to slip free. The loop size is set smaller than for a black bear, there is, however, a possibility of catching a smaller-footed black bear (Duggins Wroe, pers. comm.). Bears will be drugged and released if caught. Any other non-target animals caught will be examined and treated for injuries and released with snare poles. Preferred sites will have limber bushes with multiple basal stems to securely anchor the snare drag, and a safety area with a circumference 5 m or more around the anchor point. The snares will not be set near cliff or water, and potentially dangerous vegetation will be cleared from the safety area. Snares will be checked as quickly as possible after sunrise every morning to reduce stress and possibility of hyperthermia. Snares will be checked at least twice a day and will not be reset on extremely hot days (Logan et al. 1999, Logan and Sweanor 2001). Logan et al. (1999) found snaring to be a relatively safe technique for capturing cougars. Life-threatening injuries occurred in 5 of 209 captures. The majority of these injuries were fractures to ulna and/or radius of the snared leg. Adult cougars will be immobilized with anesthetics delivered by jab-pole or CO2 pistol and projectile syringe as described above. Capture operations will be halted if ambient temperature falls below 0 F or rises above 90 F. Delivery of anesthetic drugs via projectile syringe: In situations where pursuit by hounds is not possible and snaring or trapping is difficult due to the high abundance of non-target animals, a lure may be used to bring a cougar in close proximity to dart with a projectile syringe using a gas-powered projector. Lures may include a fresh kill made by the target animal, a deer carcass placed out as bait, or a predator call. A hound on a lead will be 175 �available to track the animal once it has been darted. The caudal thigh is the preferred target for the dart. The anesthetic choice is at the discretion of the attending veterinarian. Hand capture of cubs Nursing cougar cubs can be safely captured by hand or with a catch-pole at nurseries when they are 4 to 10 weeks old (Logan and Sweanor 2001). Cubs usually weigh less than 10 kg, and can be examined and tagged without the need for anesthetics. Nurseries can be located when VHF-collared mothers are present, or by using GPS data from GPS-collared mothers. Wait for a time when the mother is away from the nursery, as determined by VHF-radio-telemetry, in order to capture the cubs. Cubs should be handled with clean leather gloves. They can be picked up by the nape of the neck. A catch-pole may be necessary to extract cubs from holes and crevices. Cubs should be contained together, or in pairs, in new burlap bags to allow ample air circulation. The cubs should be moved about 100 m from the nursery to minimize human activity, disturbance, and odors at the nursery. Individual cubs that are being examined can be held in a separate burlap bag. Once the cubs are processed, they should be returned to the exact nursery, and the researchers should leave the area immediately. Throughout this process a receiver tuned to the frequency of the radio-collared mother should be constantly monitored. If it appears that the mother is returning, the cubs should be put back in the nursery immediately, and researchers should vacate the area. Injuries and Euthanasia If an animal is seriously injured (e.g. fractured or broken appendage, vertebrae, pelvis, or jaw, severe dislocation, laceration or any other injury that compromises its ability to survive and/or causes severe pain or distress) during capture or recovery, then it will be quickly and humanely euthanized. Cougars will be deeply anesthetized with ketamine or Telazol® and xylazine (IV or IM) and euthanized via rapid IV KCl administration (400-800 mEq). Alternatively, if an injured cougar cannot be handled then euthanasia will be a gunshot to the head or neck with a ≥0.22 caliber magnum rifle or pistol. LITERATURE CITED Beck, T, D. I. 1993. Development of black bear inventory techniques. Job progress report W-153-R-6. Colorado Division of Wildlife, Fort Collins, USA. Kreeger, T. J., J. M. Arnemo, and J. P. Raath. 2002. Handbook of wildlife chemical immobilization, International edition. Wildlife Pharmaceuticals, Inc., Fort Collins, Colorado,USA. Logan, K. A., E. T. Thorne, L. L. Irwin, and R. Skinner. 1986. Immobilizing wild cougars (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases 22:97-103. Logan, K. A., L. L. Sweanor, J. F. Smith, and M. G. Hornocker. 1999. Capturing cougars with foot-hold snares. Wildlife Society Bulletin 27:201-208. Logan, K.A., and L.L Sweanor. 2001. Desert Cougar, evolutionary ecology and conservation of an enduring carnivore. Washington: Island Press. Shaw, H.G. 1979. Cougar field guide. Fourth edition. Arizona Game and Fish, Phoenix, Arizona, USA. Shuler, J. D. 1992. A cage trap for live-trapping cougars. Proceedings of the Fifteenth Vertebrate Pest Conference. Newport Beach, California, March 3-5, 1992. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. In prep. Cougar-human relationships in Cuyamaca Rancho State Park, California. 176 �Table 1: Drug dosage by weight for cougars as recommended by CDOW veterinarian L. Wolfe. Dosage Conc Cougar Dose (ml) by animal weight (kg) mg/kg mg/ml 10 20 30 40 50 60 70 80 ANTIBIOTICS Oxytetracycline 3 200 0.2 0.3 0.5 0.6 0.8 0.9 1.1 1.2 SI Penicillin G D 20000 300000 0.7 1.3 2.0 2.7 3.3 4.0 4.7 5.3 PAINKILLERS SI Ketoprofen D 2 100 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 ANESTHETICS ketamine (+ med) 200 2 200 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 medatomidine 20 0.1 20 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.4 tolazoline 4 100 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 atipamazole 0.3 5 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8 Dopram 1 20 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Atropine 0.03 0.5 0.6 1.2 1.8 2.4 3.0 3.6 4.2 4.8 MISC 600. fluids maint ml/ day 60 1 0 1200.0 1800.0 2400.0 3000.0 3600.0 4200.0 4800.0 177 100 110 1.5 1.7 6.7 7.3 2.0 2.2 1.0 0.5 4.0 6.0 5.0 6.0 1.1 0.6 4.4 6.6 5.5 6.6 6000.0 6600.0 �APPENDIX III APPLICATION OF AVERSIVE CONDITIONING TECHNIQUES TO COUGARS Management options for CDOW managers when dealing with cougar-human interactions include firing rubber bullets or beanbags from a 12 gauge shotgun at the offending cougar, pepper spray, and capturing and relocating offending cougars. Chasing a cougar with hounds as a means of aversive conditioning is also a viable option for treating cougars interacting with humans. Below we describe the application of each of these treatments. Fired Projectiles: There are a wide variety of less than lethal projectiles that are designed to be fired from 12 gauge shotguns to control humans in law enforcement situations. These projectiles are also used by wildlife managers to chase nuisance animals away from areas where these animals are not wanted. These projectiles are designed to strike an individual, which may cause pain, but do not penetrate the skin or cause any permanent injury. Rubber bullets, beanbag rounds, and pepper-spray rounds are three such projectiles that are less than lethal munitions that can be used. Each of these has different designs or ballistics for specific distances. Depending on the type, they can be fired at ranges from 2 yards to over 50 yards. We will use rubber bullets, beanbag rounds, and pepper-spray rounds designed to be fired at distances greater than 5 yards. These rounds will be fired at cougars facing away from the shooter at distances exceeding 10 yards to avoid striking the cougar in the head or facial area. Cougars will be released from capture and while initially fleeing, cougars may be hit with projectiles up to four times within one treatment with only large muscle masses, such as the rump, being targeted. Pepper Spray: Pepper spray may be fired at a cougar from a 12 gauge shotgun or a pepper-ball gun. In these cases the cougar will be hit with the pepper spray in the chest or the ground in front of the animal will be hit in order to get the spray to contact the animal in the face. Such pepper spray rounds are approved for use as less than lethal ammunition and has been used by CDOW for management purposes on bears and cougars. Alternatively, a cougar will be sprayed in the face by hand while the animal is exiting a cage trap. Such action will ensure that the cougar will associate the action with direct human interaction. When this treatment is administered it will be done following the directions provided with pepper spray sold commercially. This will be a one second spray applied directly in the cougars face at a distance of approximately 2 to 4 meters. Hound Chases: Hound chases will be designed to mimic hound capture techniques that are currently being used to capture cougars in open space areas. Cougars will either be chased directly from the property where the incident occurs or will be chased upon release from a cage trap. In either case, hounds will not be released until the cougar is fleeing and is at least 20 m from the hounds. Cougars are faster than hounds, so this approach will avoid any direct contact between the cougar and hounds. Cougars will be chased until treed, by two to five hounds. In general, chases should be short in duration as cougars tend to tree quickly with hounds in immediate pursuit. After being treed, the hounds will be removed on leashes and the cougar will be left in the tree with no further human contact. However, if cougars opt to not become treed, we will terminate the chase after 1-hour and/or when cougar crosses property boundaries where hounds are not allowed. 178 �Relocation: In many situations (i.e. neighborhoods) direct application of aversive conditioning will not be possible to prevent secondary incidents within neighborhoods and management actions will require the relocation of the offending animal. In these situations, the cougar will be drug-captured or cage-trapped and transported to an appropriate open-space location or other large property that represents natural cougar habitat. If the cougar has not been previously captured, it will have to be anesthetized and radiocollared. Cougars that are already radio-collared and do not need new collars will generally not be anesthetized when possible. These cougars will be lifted into the back of a truck in a cage trap and relocated. Cougars that must be anesthetized will be reversed with an antagonist drug and awakened prior to transport. Injuries and Euthanasia: If an animal is seriously injured (e.g. fractured or broken appendage, vertebrae, pelvis, or jaw, severe dislocation, laceration or any other injury that compromises its ability to survive and/or causes severe pain or distress) during capture, recovery, or relocation, then it will be quickly and humanely euthanized. Cougars will be deeply anesthetized with ketamine or Telazol® and xylazine (IV or IM) and euthanized via rapid IV KCl administration (400-800 mEq). Alternatively, if an injured cougar cannot be handled then euthanasia will be a gunshot to the head or neck with a ≥0.22 caliber magnum rifle or pistol. 179 �APPENDIX IV COLORADO DIVISION OF WILDLIFE PROTOCOLS FOR FRONT-RANGE COUGAR PILOT RESEARCH PROJECT Public safety will be the fundamental issue guiding decisions on how to respond to and manage human interactions involving cougars radio-collared for the Colorado Division of Wildlife (CDOW) Front-Range cougar research project. CDOW Administrative Directive W-20 will serve as a basic guideline for managing cougar incidents. These protocols amend Administrative Directive W-20 and provide guidance specific to the Front-Range cougar research project. Human safety will not be compromised for research purposes; original guidelines in Directive W-20 will be explicitly followed for cougar-human interactions defined as ‗Level D-Attack‘ in W-20. These amendments allow additional flexibility and options for managing lower level cougar-human interactions as part of the research and management evaluation process. Under the management guidelines of Directive W-20, section C, it is specified that any cougar that is tranquilized, handled and released by the Division under the authority of W-20 will be ear-tagged with the appropriate color tag for that region, and will be tattooed on the inside of the ear prior to release. All cougars captured for research purposes will also be ear-tagged with the appropriate color for the region using a tag code starting with an R followed by a three digit number. Cougars will only be tattooed on the inside of the ear if they would have been tranquilized, handled and released by the division under the authority of W-20 regardless of the associated research project. If tattooing does occur, the tattoo will match the code used on the ear-tag. The purpose of the Front-range cougar project is to expand our understanding of how to better manage cougar-human interactions within the expanding suburban-rural human environment so that we can sustain both the existence of cougars and ensure public safety. For this study to succeed we must capture and radio-collar cougars that live in or near the suburban-rural environment to acquire basic information on cougar movements and prey selection and the potential for cougars to interact with humans. An inherent risk is that some radio-collared cougars will, at some point in time, likely interact to some degree with humans. These management protocols will provide CDOW managers and researchers an initial menu of choices to consistently guide decisions involving interactions between radio-collared cougars and humans. Cougars will be radio-collared by capturing cougars during planned and systematic efforts or opportunistically during low-level human-interaction circumstances. Protocols address 5 major topics: A) radio-collared cougars, B) project communications, C) research data, D) external media, and E) cooperators awareness of ongoing proposed project protocols and study plan. These protocols will be a ‗living document‘ that will evolve as the research project progresses with the input of field managers and researchers. Changes to the protocols will occur through informed discussions among CDOW managers and scheduled as needed as the research project unfolds or objectives are modified. 180 �A. INTERNAL CDOW PROTOCOLS FOR MANAGING FRONT-RANGE RESEARCH RADIOCOLLARED COUGARS a. Cougar-Human Interaction Levels Interactions involving radio-collared cougars and humans will span a potential range from benign to dangerous as depicted in the diagram below (Levels I – V). I..Cougar not seen, or detected, by public, nor near human dwellings or infrastructure. II. Cougar sighted by public or passes near human infrastructure but no level of interaction between cougar and humans and not perceived as a safety concern. III. Cougar seen by public or passes near human infrastructure with some low level of interaction between cougar and humans but no threatening behavior documented. V. Cougar seen by public or passes near human infrastructure with a level of interaction between cougar and humans considered to be dangerous to humans. IV. Cougar seen by public or passes near human infrastructure with a level of interaction between cougar and humans reasonably considered to be threatening to humans. Defining the risk to humans that could be associated with observed cougar behaviors is difficult. We relied on the interpretations of cougar behavior as outlined in the Cougar Management Guidelines and adapted these interpreted levels of risk to our cougar-human interaction Levels 1 -5 (Table 1). Interpretations of cougar behavior would be highly dependent on the observer‘s skills and experience and the skills and experience of CDOW personnel who would interview the person who had the interaction with the cougar. In threatening or dangerous interactions (Levels 4 and 5), investigating personnel would attempt to determine whether the cougar was defending an animal carcass, kill site, den site, or young. 181 �Table 1. Interpretations of cougar behaviors occurring during cougar-human interactions in order of increasing risk to humans. Columns 1-3, except for ‗Attack‖ behavior, were copied from the ‗Cougar Management Guidelines Working Group, 2005, Wild Futures Press‘ while column 4 represents Levels of Interaction as defined for these Front-range Cougar project protocols. Human Observation of Cougar Behavior Cougar opportunistically viewed at a distance Cougar flight or hiding Interpretation of Cougar Behavior Secretive Level of Likely Human Risk Low Avoidance Low Cougar lack of attention, various movements not directed towards person. Cougar has various body positions, ears up, may be shifting positions, intent attention, following behavior Intense staring, following and hiding behavior Hissing, snarling, vocalization Indifference or actively avoiding inducing aggression Curiosity Low Low, provided human response is appropriate Non-threatening to threatening, Level 3 or 4 Assessing success of attack Defensive behaviors, attack may be imminent Pre-attack Moderate Threatening, Level 4 Moderate depending on distance between human and cougar High Threatening, Level 4 Imminent attack Very High and Immediate Dangerous, Level 5 Attack Extremely High Dangerous, Level 5 Crouching, tail twitching, intense staring, ears flattened like wings, body low to ground, head may be up Ears flat, fur out, tail twitching, body and head low to ground, rear legs ―pumping‖ Cougar attempts to or actually strikes, claws, or physically comes into contact with human. Front-Range Cougar Risk Category Non-threatening, Level 2 Non-threatening, Level 2 or 3 Non-threatening, Level 2 or 3 Dangerous, Level 5 An indirect interaction between humans and cougars involves cougars and domestic pets or livestock and such interactions do occur along the Front-range. There is the possibility that pet-cougar interactions may be a signal that a cougar may be inclined to eventually become involved in a cougarhuman interaction. Similar to cougar-human interactions, we propose a gradient of cougar-pet/livestock interactions that would be assessed relative to the risk of these cougar behaviors to humans (Table 2). Key distinctions among cougar-pet/livestock interactions are whether the incident happened in an open space area and ‗off-leash‘, within a confined area such as a fenced yard, within animal/livestock holding pen, or while the pet/livestock was on leash/halter and accompanied by a human. Definitions of domestic pet and domestic livestock will follow guidelines established for W-20. 182 �Table 2. Interpretations of cougar behaviors occurring during cougar-pet/livestock interactions in order of increasing risk to humans. Human Observation of Cougar Behavior Associated with Pet or Livestock Cougar seen in proximity to domestic pet/livestock Cougar displays flight or hiding Cougar approaches pet/livestock, displays various body positions, ears up, intent attention, following behavior Hissing, snarling, vocalizations Crouching, tail twitching, intense staring, body near or low to ground, rear legs may be ‗pumping‘ Cougar kills or injures pet Cougar kills or injures livestock Interpretation of Cougar Behavior Front-Range Cougar Risk Category when Occurs in Open Space or Similar Areas away from Dwellings Front-Range Cougar Risk Category When Occurs in Confined Area or On Leash Accompanied by Human Secretive or possibly Curious Non-threatening, Level 1 Non-threatening, Level 2 Avoidance Non-threatening, Level 1 Non-threatening, Level 2 Curiosity or possibly assessing success of attack Non-threatening, Level 2 Non-threatening, Level 3, providing human response is appropriate. Defensive behavior, or possible attack Pre-attack or Imminent Attack Non-threatening, Level 2 Non-threatening, Level 3, or Threatening Level 4 if pet closely accompanied by a human Non-threatening Level 3, or Threatening Level 4 if pet closely accompanied by a human Attack Occurred Level 3 Attack Occurred Level 3 Non-threatening, Level 3 Threatening Level 4, or Dangerous Level 5 if pet closely accompanied by a human Threatening Level 4, or Dangerous Level 5 if livestock closely accompanied by a human b. Decision Process for Evaluating Responses to Cougar-Human Interactions Abbreviations in this section used in reference to CDOW personnel positions are: District Wildlife Manager (DWM), Area Wildlife Manager, (AWM), Regional Manager (RM), Wildlife Researcher (WR), Wildlife Research Leader (RL), Terrestrial Section Manager (TSM). At any level of cougar-human interaction, the minimum Decision Response Team will consist of the primary WR, the area DWM, and the appropriate area AWM, unless immediate action is needed to benefit public safety whereby the AWM could act independently of the Decision Response Team. Input and options provided by all 3 of these persons will be assessed by the group which will attempt to reach a consensus decision. The Decision Response Team will objectively weigh the options available for each interaction/situation and make the most appropriate decision that considers the objectives of the research project while maintaining public safety. The decision will be a process of informed judgment. The AWM, or AWM designee, will be the official CDOW representative for the final decision. If the Decision Response Team cannot reach a decision of consensus, then the AWM will engage the RM, RL, and TSM in the decision process. At any level of response, any member of the response team may opt to consult with appropriate adjoining AWMs, RM, RL and TSM. The AWM will be responsible for 183 �forwarding situational and decision information to appropriate field personnel via internal email, phone, or via the Public Information Specialist. The CDOW Regional Public Information Specialist will be responsible for providing information to the CDOW Denver Public Information Specialist and the media. As the level of cougar-human interaction increases from Level 1 to Level 5, the decision rationale shall shift and become more weighted towards public safety and preventing further cougarhuman interactions as opposed to assessing or moderating cougar behavior. Decisions would therefore shift towards reducing imminent risks to humans. Examples of Cougar-Human Interaction Decision Options Example situations representing radio-collared cougar interaction Levels 1-5 and possible response decision options for responding to the interaction situation are presented below. The known history/behavior of a cougar in relation to levels of human interaction will weigh heavily on research/management decision options. We emphasize that the situations described below are not all encompassing. Furthermore, there may be rare situations where cougar-human interactions occur that prevent responsive management options because of extraneous factors such as access, snow conditions, or proper identification of the interacting cougar. Level 1. A radio-collared cougar is known to remain in open space lands, utilize natural prey, and utilize areas near public trails based on radio-telemetry information but is not known to have been seen by the public or involved in any level of interaction. Research/Management Options: a. No management prescriptions are applied to the cougar. b. 'Cougar In Area' signs may or may not posted on nearby public trails. c. Aversive conditioning tactics are applied to the cougar consistent with the research study design. Level 2. A radio-collared cougar is known to remain primarily in open space lands and utilize natural prey but is seen by the public near a public trail or is seen or is otherwise documented to occasionally be near human residences or businesses. Additionally, a cougar not previously radio-collared is seen by the public near a public trail or is seen or is otherwise documented to occasionally be near human residences or businesses Research/Management Options: a. No management prescriptions are applied to the radio-collared cougar. b. The cougar is captured and radio-collared and subjected to management prescriptions consistent with the research study design. c. ―Cougar In Area‖ signs may or may not be posted on nearby public trails. d. ―Cougar In Area‖ signs are posted near human infrastructure. Persons living or working within affected human infrastructure are directly contacted by CDOW. e. Aversive conditioning tactics are applied to the cougar consistent with the research study design. Aversive conditioning tactics may include; pursuing cougar with trained hounds, pepper spray application to cougar, or impacting cougar with rubber pellets fired from a shotgun. f. Cougar is captured for the first time, or recaptured and relocated to an appropriate area of natural habitat consistent with the research study design. Relocation distances shall not be constrained by Directive W-20. Level 3. A radio-collared cougar is known to use open space lands and areas having considerable human infrastructure. The cougar has been, or is likely to have been seen by the public on more than 1 occasion near human residences, businesses, or schools and there is reasonable concern for public safety but the cougar has not been perceived as exhibiting any current or past level of threatening behavior. 184 �Additionally, a cougar not previously radio-collared is known or likely seen by the public on more than 1 occasion near human residences, businesses, or schools and there is reasonable concern for public safety because of proximity, but the cougar has not been observed as exhibiting any current or past level of threatening behavior. Research/Management Options: a. No management prescriptions are applied to the radio-collared cougar but monitoring of cougar behavior is intensified by obtaining multiple telemetry locations per day and attempting multiple visual monitoring sessions per day. b. The non-collared cougar is captured and radio-collared, subsequent behavior is closely monitored by obtaining multiple telemetry locations per day and attempting multiple visual monitoring sessions per day. c. Warnings are posted or communicated to the appropriate public using signs or other media. d. Newly collared or previously collared cougars could be subjected to management prescriptions consistent with the research study design. e. Aversive conditioning tactics are applied to the cougar consistent with the research study design. f. Cougar is recaptured and relocated to an appropriate area of natural habitat consistent with the research study design. g. Cougar is recaptured, additional aversive conditioning tactics are applied to the cougar, and the cougar is relocated to an appropriate area of natural habitat consistent with the research study design. Level 4. A radio-collared cougar is known to use open space lands and areas having considerable human infrastructure. The cougar has been or is likely to have been seen by the public on several occasions near human residences, businesses, or schools, or there is 1 documented interaction where the behavior of the cougar was reasonably considered to be somewhat threatening to humans but there was no evidence of attacking humans (such as cougar defending an animal carcass, kill site, den site, or young as demonstrated by snarling and vocalizing without stalking). Additionally, a cougar not previously radiocollared is known or likely seen by the public on several occasions near human residences, businesses, or schools, or there is 1 documented interaction where the behavior of the cougar was reasonably considered to be somewhat threatening to humans but there was no evidence of attacking humans (such as cougar defending an animal carcass, kill site, den site, or young as demonstrated by snarling and vocalizing without stalking). Research/Management Options: a. Warnings are posted or communicated to the appropriate public using signs or other media, and, b. The non-collared cougar is captured and radio-collared, or if involving a previously radiocollared cougar, the subsequent behavior of either cougar is closely monitored by obtaining multiple telemetry locations per day and attempting multiple visual monitoring sessions per day. c. Aversive conditioning tactics are applied to the cougar consistent with the research study design. d. Cougar is initially captured and radio-collared, or recaptured, additional aversive conditioning tactics are applied to the cougar, and the cougar is relocated to an appropriate area of natural habitat consistent with the research study design. e. If a cougar is involved in 1, Level 4 interaction and subsequently becomes involved in another Level 4 interaction, the cougar is euthanized. f. Cougar is captured and euthanized. Level 5. A cougar, whether previously radio-collared or non-collared, is involved in 1 interaction where the behavior of the cougar was highly threatening to humans or an attack of a human occurred. 185 �Research/Management Options: a. Actions follow protocols outlined in W-20, Level D-Attack. Attempts are made to capture the cougar and likely euthanize the cougar. Cougars that must be euthanized will be necropsied by the Colorado State University pathology laboratory with reports provided to the Area Wildlife Manager, primary Wildlife Researcher, and the CDOW Wildlife Health Section. Remains of the cougar, such as head, hide, and tissue will be disposed of based on existing CDOW Regional guidelines with decisions the responsibility of the appropriate AWM. B. INTERNAL CDOW PROTOCOLS MANAGING FRONT-RANGE COUGAR RESEARCH COMMUNICATIONS This research project will demand frequent and routine communication between Research, Terrestrial biologists, Area Field Operations personnel, and CDOW Regional and Denver Public Information Specialists. Timing of routine field activities such as baiting, trapping, capturing, and handling of cougars and monitoring of radio-collared cougars will be communicated frequently via email or phone in order to achieve coordinated success of such activities and to maintain informed local knowledge of radio-collared cougar behavior and whereabouts. For cougar-human interaction concerns, the minimum communication tree will be the WR, DWM, AWM, RL, and Senior Terrestrial biologist responsible for the geographic area(s) containing the field research activities and/or inhabited by the radio-collared cougar. Communication should be by cell phone, communications radio, or email as needed for appropriate expediency. Frequency of communication will be decided mutually among these 5 persons. Behavior of individual cougars, and especially changes in behavior of cougars, may necessitate changes in frequency of communication. As the potential for a cougar-human interaction increases from Level 1 to Level 5 as judged by the Decision Response Team based on acute or cumulated changes in cougar behavior or cougar location, communication frequency will increase, and ultimately communications will be a part of and dictated by the Decision Response Team. At any time the AWM or RL can expand the communications tree to include the TSM, RM, or other CDOW representatives but will also be responsible for sending the communications to these additional levels. The AWM will be responsible for disseminating appropriate information to other appropriate agencies or entities. The AWM will communicate with the Regional Public Information Specialist who will be responsible for coordinating activities with and providing information to the Denver Public Information specialist and the media. C. INTERNAL CDOW PROTOCOLS FOR MANAGING FRONT-RANGE COUGAR RESEARCH DATA Because the cougar project will be high in profile and involves human safety issues, there will be a constant demand for information because of the perceived ‗need to know‘ both by internal CDOW staff and the public. Finding the correct balance between the time spent obtaining information and the time spent distributing information, and to whom, will be a learning process and there will be real costs involved in personnel time. Furthermore, what information is distributed and to whom will be a learning process. The Decision Response Team shall clearly state that no 'real-time' data of cougar activity will be released, primarily because 'real-time' data capabilities will not be possible within the scope of the project. Under current CORA guidelines, subject to legal interpretation, the raw, non-summarized data obtained during an on-going research project is protected from being obtained by the public via CORA. Examples of raw data would be the actual latitude-longitude or UTM coordinates of cougar locations or 186 �locations of critical den sites or kill-caches. Our intent is that this raw data would not be released to the public at-large, not only to protect the cougars as individuals, but also to protect our copyright on the data the agency has obtained. The current lynx reintroduction project sets a precedent for this approach with the caveat that lynx are a threatened species. As part of the internal-only communication process and internal agency ‗knowledge gathering‘ the WR will, once per month, provide the appropriate DWM, AWM, RL, and Senior Terrestrial biologist with e-maps (jpeg files) showing the distribution of radio-collared cougars in relation to important topographic and cultural features, so that these CDOW individuals are adequately aware of cougar locations and movement patterns. If cougar behavior changes such as to increase the likelihood of cougar-human interactions, monitoring of the cougar using VHF telemetry will be increased and frequency of internal communications will increase appropriately. The AWM and WR will work together to provide a reasonable frequency of ‘internal-only’ information transfer with both individuals cognizant of the trade-offs between study objectives and needs and human safety issues. Cooperating public landuse agencies will be provided the same information on the same established schedule so as to keep these entities similarly informed. The AWM, WR, RL, and the Regional Public Information Specialist will cooperatively discuss what type of information is released to the public and when such releases occur. However, as the public learns that CDOW has gained information about cougars in suburban-rural areas because CDOW radiocollared cougars and employed GPS collars and can map detailed cougar locations, post-event, CDOW can expect a variety of demands for information that will need to be addressed and a rising challenge as to how often and in what detail information is provided. The WR will provide a written report by 1 October summarizing the progress of the research project on an annual basis to Area and Regional personnel. This report will be available to the public through our standard Wildlife Research Report distribution process. D. EXTERNAL COMMUNICATIONS The Front-range cougar research project will attract the interest, curiosity, and involvement of the media such as newspapers, magazines, radio, and television. Appropriately interacting with the media will be important to maintaining credibility with the public and with providing educational opportunities to the public. Requests by the media for involvement with the research project should be assessed as consistently and appropriately as possible by the Decision Response Team. The Decision Response Team shall clearly state that no 'real-time' data of cougar activity will be released, primarily because 'real-time' data capabilities will not be possible within the scope of the project. We propose that requests be assessed as a dichotomy of cougar-human 'non-incident' and 'incident' requests (Table 3). 187 �Table 3. Guidelines for responding to requests from the media. Media Involvement Request Field Trip on Project Activities Filming or Photographing Project Activities Interview of Project Personnel Request Associated with Non-Interaction Cougar-Human Activity Media schedules time with CDOW Field Personnel; Activity will not jeopardize key field activities such as capturing & handling cougars or create unnecessary safety issues. Researcher identifies most appropriate time for activity to the Decision Response Team. Decision Response Team will notify Regional Public Information Specialist. Filming/photography to be done by CDOW information specialists who will provide footage/photos to media for media use. Filming coordinated by Decision Response Team. CDOW retains right to review all footage/photos prior to release whether provided by CDOW or private media. Decision Response Team will notify Regional Public Information Specialist. Requests for interviews of project personnel will be relayed to the Decision Response Team whenever possible. Interviews will occur to minimize interrupting routine project activities. As a minimum, the RL and the AWM will be notified of the request to conduct the interview. Decision Response Team will notify Regional Public Information Specialist. Request Associated with Cougar-Human Interaction Likely Not Appropriate, Follow W-20 Guidelines- Follow W-20 Guidelines Follow W-20 Guidelines with the exception that questions pertaining to research project objectives, research results, and research protocols will be deferred to the Decision Response Team for accurate answers. E. DOCUMENT COOPERATORS AWARENESS OF FRONT-RANGE COUGAR RESEARCH PROJECT We recommend that representatives of cooperating entities, such as, Boulder County Parks and Open Space, Jefferson County Open Space, and City of Boulder Open Space and Mountain Parks be made aware of these protocols and the CDOW approved research study plan that will guide this project. Bruce L. McCloskey, Director Colorado Division of Wildlife Approval to Implement These Protocols for Front-range Cougar Research Project Date 188 �Colorado Division of Wildlife July 2007 – June 2008 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 7210 1 : : : : Division of Wildlife Mammals Research Customer Services/Research Support Library Services N/A Period Covered: July 1, 2007 – June 30, 2008 Author: D. J. Freddy Personnel: D. J. Freddy All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT After providing 17 years of professional library services for the entire Colorado Division of Wildlife, research librarian Jackie Boss retired in April 2007. The permanent position was retained and a formal hiring process was initiated in Fall 2007. In the interim, the library remained closed to all services. In June 2008, Kay Horton Knudsen was hired as the new research librarian and was scheduled to begin employment with the Colorado Division of Wildlife in August 2008. Under the direction of the new librarian, the electronic/digital capabilities of library services will be expanded to the entire Colorado Division of Wildlife. 189 �WILDLIFE RESEARCH REPORT COLORADO DIVISION OF WILDLIFE RESEARCH LIBRARY SERVICES D. J. FREDDY P.N. OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Division of Wildlife (CDOW) employees, cooperators, wildlife educators, and the public. SEGMENT OBJECTIVES 1. Continue to improve and modernize library services. 2. Continue to develop, improve, and implement the CDOW Research Center Library web-site. SUMMARY OF LIBRARY SERVICES The library was closed during most of FY2007-08 because a new permanent librarian was yet to be hired. As such, the following usual services were temporarily halted: Maintain and Build Electronic Catalogs of all Research Library Holdings Acquire Publications for the Research Center Library Receive Publications Donated to the Research Center Library Acquire AV Materials for the Research Center Library Acquire Theses, Dissertations, Documents and Books through Interlibrary Loan Conduct Literature Searches and Deliver Information to Employees Archive CDOW Published Manuscripts Prepared by ___________________________ D. J. Freddy 190 � https://cpw.cvlcollections.org/files/original/4801d4da91d2a1163aca5f1d3398c2b4.pdf 2fb61c87b48bd829e67bee89d2343329 PDF Text Text MAMMALS - JULY 2009 �i �WILDLIFE RESEARCH REPORTS JULY 2008 – JUNE 2009 MAMMALS PROGRAM COLORADO DIVISION OF WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). ii �STATE OF COLORADO Bill Ritter, Governor DEPARTMENT OF NATURAL RESOURCES Harris Sherman, Executive Director WILDLIFE COMMISSION Brad Coors, Chair…………………………………………………………………………………..Golden Tim Glenn, Vice Chair……………………………………………….………..…………………......Salida Dennis Buechler, Secretary……………………………………………….………….….……...Centennial Jeffrey Crawford, ……..………………………………………………………………….….…..…..Denver Dorothea Farris………………………………………………………………………….………Carbondale Roy McAnally………………………………………………..…………….………..…………...…...Craig John Singletary……………………………………………………………………………………Vineland Mike Smith……..…………………………………………………………………………………….Center Robert Streeter………………………………………………….………………………………Fort Collins Harris Sherman, Executive Director, Ex-officio………….…………………...…………….…….....Denver John Stulp, Dept. of Agriculture, Ex-officio….………………………………..…………………Lakewood DIRECTOR’S STAFF Thomas Remington, Director Mark Konishi, Assistant Director-Field Operations Marilyn Salazar, Assistant Director-Support Services Jeff Ver Steeg, Assistant Director-Wildlife Programs Jim Godfrey, Chief Financial Officer MAMMALS RESEARCH STAFF Dave Freddy, Mammals Research Leader, July-December 2008 Michael W. Miller, Acting Mammals Research Leader, January-June 2009 Mat Alldredge, Wildlife Researcher Chuck Anderson, Wildlife Researcher Eric Bergman, Wildlife Researcher Chad Bishop, Wildlife Researcher Ken Logan, Wildlife Researcher Tanya Shenk, Wildlife Researcher Kay Knudsen, Libraian Margie Michaels, Program Assistant iii �Colorado Division of Wildlife July 2008 – June 2009 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS LYNX CONSERVATION WP 0670 POST-RELEASE MONITORING OF LYNX REINTRODUCED TO COLORADO by T. Shenk……………………………….…………………………….1 DEER CONSERVATION WP 3001 DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS by C. Bishop………..…………………………...55 WP 3001 EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER IN MULE DEER by C. Bishop…..…………………………………………………….69 WP 3001 EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVERWINTER SURVIVAL AND BODY CONDITION OF MULE DEER by E. Bergman…………………………………………………………………………101 WP 3001 POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson…………………………………………………………………………111 PREDATORY MAMMALS CONSERVATION WP 3003 PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU by K. Logan………………….……………………....125 WP 3003 COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBAN-EXURBAN FRONT-RANGE OF COLORADO by M. Alldredge………...185 SUPPORT SERVICES WP 7210 LIBRARY SERVICES by K. Knudsen……..……………………………...…………207 iv �v �Colorado Division of Wildlife July 2008- Aug 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Lynx Conservation Post-Release Monitoring of Lynx Reintroduced to Colorado Period Covered: July 1, 2008 – August 31, 2009 Author: T. M. Shenk Personnel: O. Devineau, R. Dickman, P. Doherty, D. Freddy, L. Gepfert, J. Ivan, R. Kahn, A. Keith, P. Lukacs, G. Merrill, B. Smith, T. Spraker, S. Waters, G. White, L. Wolfe All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to establish a viable population of Canada lynx (Lynx canadensis) in Colorado, the Colorado Division of Wildlife (CDOW) initiated a reintroduction effort in 1997 with the first lynx released in February 1999. From 1999-2006, 218 wild-caught lynx from Canada and Alaska were released in Colorado. We documented survival, movement patterns, reproduction, and landscape habitatuse through aerial (n = 11,580) and satellite (n = 29,258) tracking. Most lynx remained near the core release area in southwestern Colorado. From 1999-August 2009, there were 118 mortalities of released adult lynx. Approximately 29.7% were either human-induced or likely human-induced through either collisions with vehicles or shot. Starvation and disease/illness accounted for 18.6% of the deaths while 37.3% of the deaths were from unknown causes. Of these mortalities, 26.3% occurred outside of Colorado. Monthly mortality rate was lower inside the study area than outside, and slightly higher for male than for female lynx, although 95% confidence intervals for sexes overlapped. Mortality was higher immediately after release (first month = 0.0368 [SE = 0.0140] inside the study area, and 0.1012 [SE = 0.0359] outside the study area), and then decreased according to a quadratic trend over time. Reproductive females had the smallest 90% utilization distribution home ranges ( x = 75.2 km2, SE = 15.9 km2), followed by attending males ( x = 102.5 km2, SE = 39.7 km2) and non-reproductive animals ( x = 653.8 km2, SE = 145.4 km2). Reproduction was first documented in 2003 with subsequent successful reproduction in 2004, 2005, 2006 and 2009. No dens were documented in 2007 or 2008. From snow-tracking, the primary winter prey species (n = 604 kills) were snowshoe hare (Lepus americanus, annual x = 69.4%, SE = 5.6, n = 11) and red squirrel (Tamiasciurus hudsonicus, annual x = 22.6%, SE = 5.7, n = 11); other mammals and birds formed a minor part of the winter diet. Lynx usedensity surfaces were generated to illustrate relative use of areas throughout Colorado. Within the areas of high use in southwestern Colorado, site-scale habitat use, documented through snow-tracking, supports 1 �mature Engelmann spruce (Picea engelmannii)-subalpine fir (Abies lasiocarpa) forest stands with 4265% canopy cover and 15-20% conifer understory cover as the most commonly used areas in southwestern Colorado. Little difference in aspect (slight preference for north-facing slopes), slope ( x = 15.7°) or elevation ( x = 3173 m) were detected for long beds, travel and kill sites (n = 1841). Den sites (n = 37) however, were located at higher elevations ( x = 3354 m, SE = 31 m) on steeper ( x = 30°, SE = 2°) and more commonly north-facing slopes with a dense understory of coarse woody debris. Three years of a study to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine (Pinus contorta) stands and mature spruce/fir stands have been completed in 2006-2009 (see Appendix I of this report). A pilot study to evaluate the efficacy of using minimally-invasive monitoring techniques was developed to estimate the extent, stability and potential distribution of lynx throughout Colorado. Results to date have demonstrated that CDOW has developed lynx release protocols that ensure high initial post-release survival followed by high long-term survival, site fidelity, reproduction and recruitment of Colorado-born lynx into the Colorado breeding population. What is yet to be demonstrated is whether Colorado can support sufficient recruitment to offset annual mortality for a viable lynx population over time. Monitoring continues in an effort to document such viability. 2 �WILDLIFE RESEARCH REPORT POST RELEASE MONITORING OF LYNX (LYNX CANADENSIS) REINTRODUCED TO COLORADO TANYA M. SHENK P. N. OBJECTIVE The initial post-release monitoring of Canada lynx (Lynx canadensis) reintroduced into Colorado will emphasize 5 primary objectives: 1. Assess and modify release protocols to ensure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival of lynx reintroduced to Colorado. 5. Estimate reproduction of lynx reintroduced to Colorado. Three additional objectives will be emphasized after lynx display site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of lynx conservation strategies in the southern Rocky Mountains. SEGMENT OBJECTIVES 1. Complete winter 2008-09 field data collection on lynx habitat use at the landscape scale, hunting behavior, diet, mortalities, and movement patterns. 2. Complete winter 2008-09 lynx trapping field season to collar Colorado born lynx and re-collar adult lynx. 3. Complete spring 2009 field data on lynx reproduction. 4. Summarize and analyze data and publish information as Progress Reports, peer-reviewed manuscripts for appropriate scientific journals, or CDOW technical publications. 5. Complete the third and final year of field work to evaluate snowshoe hare (Lepus americanus) densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands (see Appendix I). 6. Complete a pilot study to evaluate the efficacy of using minimally-invasive monitoring techniques to estimate the extent, stability and potential distribution of lynx throughout Colorado (see Appendix II). INTRODUCTION The Canada lynx occurs throughout the boreal forests of northern North America. Colorado represents the southern-most historical distribution of lynx, where the species occupied the higher elevation, montane forests in the state. Little was known about the population dynamics or habitat use of this species in their southern distribution. Lynx were extirpated or reduced to a few animals in the state by the late 1970’s due, most likely, to predator control efforts such as poisoning and trapping. Given the isolation of Colorado to the nearest northern populations, the CDOW considered reintroduction as the only option to attempt to reestablish the species in the state. 3 �A reintroduction effort was begun in 1997, with the first lynx released in Colorado in 1999. To date, 218 wild-caught lynx from Alaska and Canada have been released in southwestern Colorado. The goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of lynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing if the reintroduction effort is progressing towards success. There are 7 critical criteria for achieving a viable population: 1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, 2) long-term survival of lynx in Colorado, 3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, 4) reintroduced lynx must breed, 5) breeding must lead to reproduction of surviving kittens 6) lynx born in Colorado must reach breeding age and reproduce successfully, and 7) recruitment must equal or be greater than mortality over an extended period of time. The post-release monitoring program for the reintroduced lynx has 2 primary goals. The first goal is to determine how many lynx remain in Colorado and their locations relative to each other. Given this information and knowing the sex of each individual, we can assess whether these lynx can form a breeding core from which a viable population might be established. From these data we can also describe general movement patterns and habitat use. The second primary goal of the monitoring program is to estimate survival of the reintroduced lynx and, where possible, determine causes of mortality for reintroduced lynx. Such information will help in assessing and modifying release protocols and management of lynx once they have been released to ensure their highest probability of survival. Documenting reproduction is critical to the success of the program and lynx are monitored intensively to document breeding, births, survival and recruitment of lynx born in Colorado. Site-scale habitat descriptions of den sites are also collected and compared to other sites used by lynx. Lynx populations in Canada and Alaska have long been known to cycle in response to the 10-year snowshoe hare (Lepus americana) cycle (Elton and Nicholson 1942). Northern populations of lynx respond to snowshoe hare lows first through a decline in reproduction followed by an increase in adult mortality; when snowshoe hare populations increase, lynx respond with increased survival and reproduction (O’Donoghue et al. 2001). Therefore, annual survival and reproduction are highly variable but must be sufficient, overall, to result in long-term persistence of the population. It is not known if snowshoe hare populations in Colorado cycle and if so, where in the approximate 10-year cycle we are currently. Given this uncertainty, documenting persistence of lynx in Colorado for a period of at least 1015 years would provide support that a viable population of lynx can be sustained in Colorado even in the event snowshoe hares do cycle in the state. Therefore, to document the continued viability of lynx in Colorado beyond the initial reintroduction period, some form of long-term monitoring must be used to determine whether recruitment exceeds mortality for a period of time long enough to encompass possible snowshoe hare cycles. In addition, a challenge facing CDOW is how efforts should be allocated between focusing on monitoring the persistence of those lynx that have established within the core release area (Shenk 2007, Shenk 2008) and those lynx that may be pioneering and expanding into other portions of the state. Reproduction and known recruitment have been observed to be sporadic in the core area. To continue to document lynx reproduction through den site visits and to document survival of those kittens through tracking the adult females in winter looking for accompanying kittens requires a continued trapping effort to capture and radio-collar adult females. Lynx trapping is typically a time consuming and expensive operation as the lynx are territorial with large home ranges that may be entirely located within or largely comprised of inaccessible areas (e.g., wilderness areas). Alternatively, occupancy modeling using minimally-invasive techniques could be a feasible alternative for ascertaining trends in population status. 4 �Additional goals of the post-release monitoring program for lynx reintroduced to the southern Rocky Mountains included refining descriptions of habitat use and movement patterns and describing successful hunting habitat once lynx established home ranges that encompassed their preferred habitat. Specific objectives for the site-scale habitat data collection include: 1) describe and quantify site-scale habitat use by lynx reintroduced to Colorado, 2) compare site-scale habitat use among types of sites (e.g., kills vs. long-duration beds), and 3) compare habitat features at successful and unsuccessful snowshoe hare chases. The program will also investigate the ecology of snowshoe hare in Colorado. A study comparing snowshoe hare densities among mature stands of Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), lodgepole pine (Pinus contorta) and Ponderosa pine (Pinus ponderosa) was completed in 2004 with highest hare densities found in Engelmann spruce/subalpine fir stands and no hares found in Ponderosa pine stands. A study to evaluate the importance of young, regenerating lodgepole pine and mature Engelmann spruce/subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each was initiated in 2005 and will continue through 2009 (see Appendix I). Lynx is listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.)(U. S. Fish and Wildlife Service 2000). Colorado is included in the federal listing as lynx habitat. Thus, an additional objective of the post-release monitoring program is to develop conservation strategies relevant to lynx in Colorado. To develop these conservation strategies, information specific to the ecology of the lynx in its southern Rocky Mountain range, such as habitat use, movement patterns, mortality factors, survival, and reproduction in Colorado is needed. STUDY AREA Byrne (1998) evaluated five areas within Colorado as potential lynx habitat based on (1) relative snowshoe hare densities (Bartmann and Byrne 2001), (2) road density, (3) size of area, (4) juxtaposition of habitats within the area, (5) historical records of lynx observations, and (6) public issues. Based on results from this analysis, the San Juan Mountains of southwestern Colorado were selected as the core reintroduction area, and where all lynx were reintroduced. Wild Canada lynx captured in Alaska, British Columbia, Manitoba, Quebec and Yukon were transported to Colorado and held at The Frisco Creek Wildlife Rehabilitation Center located within the reintroduction area prior to release. Post-release monitoring efforts were focused in a 20,684 km2 study area which included the core reintroduction area, release sites and surrounding high elevation sites (> 2,591 m). The area encompassed the southwest quadrant of Colorado and was bounded on the south by New Mexico, on the west by Utah, on the north by interstate highway 70, and on the east by the Sangre de Cristo Mountains (Figure 1). Southwestern Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4,200 m. Engelmann spruce/subalpine fir is the most widely distributed coniferous forest type within the study area. The lynx-established core area is roughly bounded by areas used by lynx in the Taylor Park/Collegiate Peak areas in central Colorado and includes areas of continuous use by lynx, including areas used during breeding and denning (Figure 1). METHODS REINTRODUCTION Effort Wild Canada lynx were captured in Alaska, British Columbia, Manitoba, Quebec and Yukon and transported to Colorado where they were held at the Frisco Creek Wildlife Rehabilitation Center prior to release. All lynx releases were conducted under the protocols found to maximize survival (see Shenk 5 �2001). Estimated age, sex and body condition were ascertained and recorded for each lynx prior to release (see Wild 1999). Lynx were transported from the rehabilitation facility to their release site in individual cages. Specific release site locations were recorded in Universal Transverse Mercator (UTM) coordinates and identification of all lynx released at the same location, on the same day, was recorded. Behavior of the lynx on release and movement away from the release site were documented. Movement, Distribution and Relative Use of Areas by Lynx To monitor lynx movements and thus determine distribution and relative use of areas all released lynx were fitted with radio collars. All lynx released in 1999 were fitted with TelonicsTM radio-collars. All lynx released since 1999, with the exception of 5 males released in spring 2000, were fitted with SirtrackTM dual satellite/VHF radio-collars. These collars have a mortality indicator switch that operated on both the satellite and VHF mode. The satellite component of each collar was programmed to be active for 12 hours per week. The 12-hour active periods for individual collars were staggered throughout the week. Signals from the collars allowed for locations of the animals to be made via Argos, NASA, and NOAA satellites. The location information was processed by ServiceArgos and distributed to the CDOW through e-mail messages. Datasets.-- To determine recent (post-reintroduction) movement and distribution of lynx reintroduced, born or initially trapped in Colorado and relative use of areas by these lynx, regular locations of lynx were collected through a combination of aerial and satellite tracking. Locations were recorded and general habitat descriptions for each aerial location was recorded. The first dataset of lynx locations included all locations obtained from daytime flights conducted with a Cessna 185 or similar aircraft to locate lynx by their VHF collar transmitters (hereafter aerial locations). VHF transmitters have been used on lynx since the first lynx were released in February 1999. The second type of lynx location data was collected via satellite from the satellite collar transmitters placed on the lynx (hereafter satellite locations). Satellite transmitter collars were first used for lynx in April 2000. These satellite collars also contained a VHF transmitter which also allowed locating lynx from the air or ground. All locations were recorded in Universal Transverse Mercator (UTM) coordinates using the CONUS NAD27 datum. Flights to obtain lynx aerial locations were typically conducted on a weekly basis throughout most summer and winter months and twice a week during the den search field season (May 15 – June 30), depending on weather and availability of planes and pilots. Flights were typically concentrated in the high elevation (> 2700 m) southwest quadrant of Colorado which encompasses the core lynx release and research area (Figure 1). Flights during the den seasons were conducted to obtain locations on all female lynx within the state wearing an active VHF transmitter. VHF transmitters were outfitted with sufficient batteries to last 60 months. The satellite transmitters were designed to provide locations on a weekly basis with sufficient batteries to last for 18 months. These data collections remain ongoing and all information will be used for future habitat use and survival analyses. Accuracy of both aerial and satellite locations varied with the environmental conditions at the time the location was obtained. Accuracy of aerial locations was influenced by weather with accuracy ranging from 50 - 500 meters. Satellite location accuracy was also influenced by atmospheric conditions and position of the satellites. Satellite location accuracy ranged from 150 meters -10 km. Movement and Distribution.-- To document all known lynx locations maps were generated with all aerial and satellite locations displayed. Due to lynx movements outside of Colorado, particularly into the states of New Mexico, Utah and Wyoming we further evaluated lynx use throughout those three states, as well as the data would allow. All individual lynx located at least once in these 3 states (nontruncated datasets) were identified and tallied for each year. To document consistency and known use of these states after the initial effect of being reintroduced was minimized (i.e., 180 days post-release), each individual lynx located at least once in these states from the truncated datasets were identified and tallied. 6 �Relative Use.-- To document relative use of areas by lynx, 90% kernel use-density surfaces were calculated for truncated satellite and aerial lynx locations using the ArcGIS Spatial Analyst Kernel Density Tool. Lynx may not be exhibiting typical behavior or habitat use within the first few months after their release in Colorado. Therefore, a subset of each of the aerial and satellite datasets was created that eliminated the first 180 days (approximately 6 months) of locations obtained for each lynx immediately after their initial release. As a result, the truncated aerial location dataset contained lynx locations from September 1999 through April 2009 while the truncated satellite location dataset began October 2000 and extended through April 2009. Due to differences in data collection frequency and accuracy between datasets, the truncated satellite and truncated aerial data were analyzed separately for generating the lynx use-density surfaces. These use-density surfaces fit a smoothly curved surface over each lynx location. The surface value was highest at the location of the point and diminished with increasing distance from the point. A fixed kernel was used with a smoothing parameter of 5 km, reaching 0 at the search radius distance from the point. Only a circular neighborhood was possible. The volume under the surface equaled the total value for the point. The use-density at each output GIS raster cell was calculated by adding the values of all the kernel surfaces from all the lynx point locations that overlaid each raster cell center. The kernel function was based on the quadratic kernel function described in Silverman (1986, p. 76, equation 4.5). The use-density surfaces were calculated at 100 m resolution. To enhance graphic displays of higher usedensity areas, density values representing single locations were not displayed. Home Range Preliminary estimates of annual home ranges were calculated as a 95% utilization distribution using a kernel home-range estimator for each lynx we had at least 30 locations for within a year. A year was defined as March 15 – March 14 of the following year. Locations used in the analyses were collected from September 1999 – January 2006 and all locations obtained for an individual during the first six months after its release were eliminated from any home range analyses as it was assumed movements of lynx initially post-release may not be representative of normal habitat use. Locations were obtained either through aerial VHF surveys or locations or the midpoint (ArcView Movement Extension) of all high quality (accuracy rating of 0-1km) satellite locations obtained within a single 24-hour period. All locations used within a single home range analysis were taken a minimum of 24 hours apart. Home range estimates were classified as being for a reproductive or non-reproductive animal. A reproductive female was defined as one that had kittens with her; a reproductive male was defined as a male whose movement patterns overlapped that of a reproductive female. If a litter was lost within the defined year a home range described for a reproductive animal were estimated using only locations obtained while the kittens were still with the female. Final estimates of annual home range size will completed with the addition of data collected through 2009 and in conjunction with current habitat use analyses and publications to be completed in 2009-2010. Survival Multi-state mark-recapture models were used to estimate monthly mortality rates and described in detail in Devineau et al. 2009a (in review) for the first year post-release and for 10 years post-release in Devineau et al. 2009b (in review). This approach accommodated missing data and allowed exploration of factors possibly affecting lynx survival such as sex, time spent in pre-release captivity, movement patterns, and origin. Mortality Factors When a mortality signal (75 beats per minute [bpm] vs. 50 bpm for the Telonics™ VHF transmitters, 20 bpm vs. 40 bpm for the Sirtrack™ VHF transmitters, 0 activity for Sirtrack™ PTT) was heard during either satellite, aerial or ground surveys, the location (UTM coordinates) was recorded. 7 �Ground crews then located and retrieved the carcass as soon as possible. The immediate area was searched for evidence of other predators and the carcass photographed in place before removal. Additionally, the mortality site was described and habitat associations and exact location were recorded. Any scat found near the dead lynx that appeared to be from the lynx was collected. All carcasses were transported to the Colorado State University Veterinary Teaching Hospital (CSUVTH) for a post mortem exam to 1) determine the cause of death and document with evidence, 2) collect samples for a variety of research projects, and 3) archive samples for future reference (research or forensic). The gross necropsy and histology were performed by, or under the lead and direct supervision of a board certified veterinary pathologist. At least one research personnel from the CDOW involved with the lynx program was also present. The protocol followed standard procedures used for thorough post-mortem examination and sample collection for histopathology and diagnostic testing (see Shenk 1999 for details). Some additional data/samples were routinely collected for research, forensics, and archiving. Other data/samples were collected based on the circumstances of the death (e.g., photographs, video, radiographs, bullet recovery, samples for toxicology or other diagnostic tests, etc.). From 1999–2004 the CDOW retained all samples and carcass remains with the exception of tissues in formalin for histopathology, brain for rabies exam, feces for parasitology, external parasites for ID, and other diagnostic samples. Since 2005 carcasses are disposed of at the CSUVTH with the exception of the lower canine, fecal samples, stomach content samples and tissue or bone marrow samples to be delivered by CDOW to the Center for Disease Control for plague testing. The lower canine, from all carcasses, is sent to Matson Labs (Missoula, Montana) for aging and the fecal and stomach content samples are evaluated for diet. Reproduction Females were monitored for proximity to males during each breeding season. We defined a possible mating pair as any male and female documented within at least 1 km of each other in breeding season through either flight data or snow-tracking data. Females were then monitored for site fidelity to a given area during each denning period of May and June. Each female that exhibited stationary movement patterns in May or June were closely monitored to locate possible dens. Dens were found when field crews walked in on females that exhibited virtually no movement for at least 10 days from both aerial and ground telemetry. Kittens found at den sites were weighed, sexed and photographed. Each kitten was uniquely marked by inserting a sterile passive integrated transponder (PIT, Biomark, Inc., Boise, Idaho, USA) tag subcutaneously between the shoulder blades. Time spent at the den was minimized to ensure the least amount of disturbance to the female and the kittens. Weight, PIT-tag number, sex and any distinguishing characteristics of each kitten was also recorded. Beginning in 2005, blood and saliva samples were collected and archived for genetic identification. During the den site visits, den site location was recorded as UTM coordinates. General vegetation characteristics, elevation, weather, field personnel, time at the den, and behavioral responses of the kittens and female were also recorded. Once the females moved the kittens from the natal den area, den sites were visited again and site-specific habitat data were collected (see Habitat Use section below). Captures Captures were attempted for either lynx that were in poor body condition or lynx that needed to have their radio-collars replaced due to failed or failing batteries or to radio-collar kittens born in Colorado once they reached at least 10-months of age when they were nearly adult size. Methods of recapture included 1) trapping using a Tomahawk™ live trap baited with a rabbit and visual and scent lures, 2) calling in and darting lynx using a Dan-Inject CO2 rifle, 3) custom box-traps modified from those 8 �designed by other lynx researchers (Kolbe et al. 2003) and 4) hounds trained to pursue felids were also used to tree lynx and then the lynx was darted while treed. Lynx were immobilized either with Telazol (3 mg/kg; modified from Poole et al. 1993 as recommended by M. Wild, DVM) or medetomidine (0.09mg/kg) and ketamine (3 mg/kg; as recommended by L. Wolfe, DVM)) administered intramuscularly (IM) with either an extendible pole-syringe or a pressurized syringe-dart fired from a Dan-Inject air rifle. Immobilized lynx were monitored continuously for decreased respiration or hypothermia. If a lynx exhibited decreased respiration 2mg/kg of Dopram was administered under the tongue; if respiration was severely decreased, the animal was ventilated with a resuscitation bag. If medetomidine/ketamine were the immobilization drugs, the antagonist Atipamezole hydrochloride (Antisedan) was administered. Hypothermic (body temperature < 95o F) animals were warmed with hand warmers and blankets. While immobilized, lynx were fitted with replacement SirtrackTM VHF/satellite collar and blood and hair samples were collected. Once an animal was processed, recovery was expedited by injecting the equivalent amount of the antagonist Antisedan IM as the amount of medetomidine given, if medetomodine/ketemine was used for immobilization. Lynx were then monitored while confined in the box-trap until they were sufficiently recovered to move safely on their own. No antagonist is available for Telezol so lynx anesthetized with this drug were monitored until the animal recovered on its own in the box-trap and then released. If captured and in poor body condition, lynx were anesthetized with either Telezol (2 mg/kg) or medetomodine/ketemine and returned to the Frisco Creek Wildlife Rehabilitation Center for treatment. HABITAT USE Gross habitat use was documented by recording canopy vegetation at aerial locations. More refined descriptions of habitat use by reintroduced lynx were obtained through following lynx tracks in the snow (i.e., snow-tracking) and site-scale habitat data collection conducted at sites found through this method to be used by lynx. See Shenk (2006) for detailed methodologies. DIET AND HUNTING BEHAVIOR Winter diet of reintroduced lynx was estimated by documenting successful kills through snowtracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. Scat samples were collected wherever found and labeled with location and individual lynx identification. Only part of the scat was collected (approximately 75%); the remainder was left in place in the event that the scat was being used by the animal as a territory mark. Site-scale habitat data collected for successful and unsuccessful snowshoe hare kills were compared. SNOWSHOE HARE ECOLOGY To further our understanding of snowshoe hare ecology in Colorado, a study was conducted comparing snowshoe hare densities among mature stands of Engelmann spruce/subalpine fir, lodgepole pine (Pinus contorta) and Ponderosa pine (Pinus ponderosa). The highest hare densities were found in Engelmann spruce/subalpine fir stands and no hares found in Ponderosa pine stands (Zahratka and Shenk 2008). A second study was initiated in 2005 to evaluate the importance of young, regenerating lodgepole pine and mature Engelmann spruce / subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each (Ivan 2005). Specifically, this study was designed to evaluate small and medium lodgepole pine stands and large spruce/fir stands where the classes “small”, “medium”, and “large” refer to the diameter at breast height (dbh) of overstory trees as defined in the United States Forest Service R2VEG Database (small = 2.54−12.69 cm dbh, medium = 12.70−22.85 cm, and large = 22.86−40.64 cm dbh; J. Varner, United States Forest Service, personal communication). The study design was also developed to identify which 9 �of the numerous hare density-estimation procedures available perform accurately and consistently using an innovative, telemetry augmentation approach as a baseline. In addition, movement patterns and seasonal use of deciduous cover types such as riparian willow were assessed. Finally, the study was designed to further expound on the relationship between density, demography, and stand-type by examining how snowshoe hare density and demographic rates vary with specific vegetation, physical, and landscape characteristics of a stand. RESULTS REINTRODUCTION Effort From 1999 through 2006, 218 wild-caught lynx were reintroduced into southwestern Colorado (Table 1). No lynx were released in 2007, 2008 or 2009. All lynx were released with either VHF or dual VHF/satellite radio collars so they could be monitored for movement, reproduction and survival. The CDOW does not plan to release any additional lynx in 2010. Movement Patterns and Distribution Numerous travel corridors were used repeatedly by more than one lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-SilvertonLizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast through the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. A total of 11,580 aerial and 29,258 satellite locations were obtained from the 218 reintroduced lynx, radio-collared Colorado kittens (n = 16) and unmarked lynx captured in Colorado (n = 3) as of August 31, 2009. The majority of these locations were in Colorado (Figure 2). Some reintroduced lynx dispersed outside of Colorado into Arizona, Idaho, Iowa, Kansas, Montana, Nebraska, Nevada, New Mexico, South Dakota, Utah and Wyoming (Figure 2). The majority of surviving lynx from the reintroduction effort currently continue to use high elevation (> 2900 m), forested terrain in an area bounded on the south by New Mexico north to Independence Pass, west as far as Taylor Mesa and east to Monarch Pass. Most movements away from the Core Release Area were to the north. Relative Use The lynx use-density surfaces resulting from the fixed kernel analyses provided relative probabilities of finding lynx in areas throughout their distribution. All 218 lynx released in Colorado, all radio-collared kittens and 3 captured unmarked adults were located at least once in Colorado. The majority of these lynx remained in Colorado. Single use density surfaces were calculated for both truncated aerial and truncated satellite datasets in Colorado up to March 2007 and presented in Shenk (2008). Relative use-density surfaces were also generated for New Mexico, Wyoming and Utah and presented in detail in Shenk (2007). Aerial and satellite use-density surfaces indicated similar high usedensity areas. Satellite locations indicated broader spatial use by lynx because satellite collars provided more locations than flights. A single use-density surface was calculated for the satellite non-truncated dataset from April 2000-April 2009 (n = 18,240). The use-density surface was displayed for the satellite non-truncated dataset in Colorado (Figure 3) and for all documented use (Figure 4). The use-density surface for lynx use in Colorado indicates two primary areas of use. The first is the Core Research Area (see Figure 1) and a secondary core centered in the Collegiate Peaks Wilderness (Figures 1, 3 and 4). High use is also documented for 1) the area east of Dillon, on both the north and south sides of I70 and 2) the area north of Hwy 50 centered around Gunnison and then north to Crested Butte. These last 2 high use areas are smaller in extent than the 2 core areas. 10 �Home Range Reproductive females had the smallest 90% utilization distribution annual home ranges ( x = 75.2 km2, SE = 15.9 km2, n = 19), followed by attending males ( x = 102.5 km2, SE = 39.7 km2, n = 4). Nonreproductive females had the largest annual home ranges ( x = 703.9 km2, SE = 29.8 km2, n = 32) followed by non-reproductive males ( x = 387.0 km2, SE = 73.5 km2, n = 6). Combining all nonreproductive animals yielded a mean annual home range of 653.8 km2 (SE = 145.4 km2, n = 38). Survival Detailed analysis of lynx mortality was completed and described in Devineau et al. 2009a (in review) to evaluate how the different release protocols used to reintroduce lynx in Colorado (Shenk 2001) affected mortality within the first year post-release. Average monthly mortality in the study area during the first year decreased with time in captivity from 0.205 [95% CI 0.069, 0.475] for lynx having spent up to 7 days in captivity to 0.028 [95% CI 0.012, 0.064] for lynx spending > 45 days in captivity before release (Devineau et al. 2009). The results also suggest that keeping lynx in captivity beyond 5 or 6 weeks accrued little benefit in terms of monthly survival. On a monthly average basis, lynx were as likely to move out (probability = 0.196, SE=0.032) as well as back on (probability = 0.143, SE=0.034) the reintroduction area (i.e., study area) during the first year after release. Mortality was 1.6x greater outside of the reintroduction area. Detailed analysis of lynx mortality over the first 10 years post-reintroduction was completed and described in Devineau et al. 2009b (in review). In summary, monthly mortality rate was lower inside the study area than outside, and slightly higher for male than for female lynx, although 95% confidence intervals for sexes overlapped. Mortality was higher immediately after release (first month = 0.0368 [SE = 0.0140]; inside the study area, and 0.1012 [SE = 0.0359] outside the study area), and then decreased according to a quadratic trend over time. As of August 31, 2009, CDOW was actively monitoring/tracking 37 of the 100 lynx still possibly alive (Table 2). There are 61 lynx that we have not heard signals on since at least August 31, 2008 and these animals are classified as ‘missing’ (Table 2). One of these missing lynx is a mortality of unknown identity, thus only 60 are truly missing. Possible reasons for not locating these missing lynx include 1) long distance dispersal, beyond the areas currently being searched, 2) radio failure, or 3) destruction of the radio (e.g., run over by car). CDOW continues to search for all missing lynx during both aerial and ground searches. Two of the missing lynx released in 2000 are thought to have slipped their collars. Mortality Factors Of the total 218 adult lynx released, we have 118 known mortalities as of August 31, 2009 (Table 2). Starvation was a significant cause of mortality in the first year of releases only. The primary known causes of death included 29.7% human-induced deaths which were confirmed or probably caused by collisions with vehicles or gunshot (Table 3). Malnutrition and disease/illness accounted for 18.6% of the deaths. An additional 37.3% of known mortalities were from unknown causes. Mortalities occurred throughout the areas through which lynx moved, with 26.3% (n=31) occurring outside of Colorado. The out of state mortalities included 14 in New Mexico, 5 in Utah, 4 in Wyoming and Nebraska, and 1 each in Arizona, Kansas, Iowa and Montana (Figure 2, Table 4). 11 �Reproduction Reproduction was first documented in 2003 when 6 dens and a total of 16 kittens were found in the lynx Core Release Area in southwestern Colorado. Reproduction was also documented in 2004, 2005, 2006, and 2009. No dens were found in 2007 or 2008 (Table 5). Field crews weighed, photographed, PIT-tagged the kittens and checked body condition. Beginning in 2005, we also collected blood samples from the kittens for genetic work in an attempt to confirm paternity. Kittens were processed as quickly as possible (11-32 minutes) to minimize the time the kittens were without their mother. While working with the kittens the females remained nearby, often making themselves visible to the field crews. The females generally continued a low growling vocalization the entire time personnel were at the den. In all cases, the female returned to the den site once field crews left the area. At all dens the females appeared in excellent condition, as did the kittens. The kittens weighed from 270-500 grams. Lynx kittens weigh approximately 200 grams at birth and do not open their eyes until they are 10-17 days old. The proportion of tracked females found with litters in 2006 was lower (0.095) than in the 3 previous years (0.413, SE = 0.032, Table 5). However, all demographic and habitat characteristics measured at the 4 dens that were found in 2006 were comparable to all other dens found. Mean number of kittens per litter from 2003-2006 was 2.78 (SE = 0.05) and sex ratio of females to males was equal ( x = 1.14, SE = 0.14). More details of reproduction in 2003-06 were presented in Shenk (2007). No dens were found in either 2007 or 2008, even though up to 34 adult females were monitored intensively during the denning period (Table 5). In 2009, 22.7% of females being monitored (n = 22) had dens. Two kittens were found at each of these 5 dens, a decrease in the mean of 2.78 (SE= 0.05) kittens per litter found in other years. Sex ratio was also more biased towards female kittens in 2009 (0.4 males/females) than found in previous years. Den Sites.-- A total of 42 dens were found from 2003-2009. All of the dens except one have been scattered throughout the high elevation areas of Colorado, south of I-70. In 2004, 1 den was found in southeastern Wyoming, near the Colorado border. Habitat measurements conducted through 2006 (n=37) document that dens were located on steep ( x slope = 30o , SE=2o), north-facing, high elevation ( x = 3354 m, SE = 31 m) slopes. The dens were typically in Engelmann spruce/subalpine fir forests in areas of extensive downfall of coarse woody debris (Shenk 2006). All dens (n = 42) were located within the winter use areas used by the females. Captures Two adult lynx were captured in 2001 for collar replacement. One lynx was captured in a tomahawk live-trap, the other was treed by hounds and then anesthetized using a jab pole. Five adult lynx were captured in 2002; 3 were treed by hounds and 2 were captured in padded leghold traps. In 2004, 1 lynx was captured with a Belisle snare and 6 adult lynx were captured in box-traps. Trapping effort was substantially increased in winter and spring 2005 and 12 adult lynx were captured and re-collared. Eight reintroduced lynx were captured in winter and spring 2006. In 2007, 11 reintroduced adult lynx were captured and re-collared; 10 in 2008 and 11 in 2009. All lynx captured in Colorado from 2005-2009were caught in box-traps. In addition, as part of the collaring trapping effort, 16 Colorado-born kittens were captured and collared at approximately 10-months of age. Seven 2004-born kittens were collared in spring 2005; 7 2005-born kittens were collared in spring 2006; and 1 2004- and 1 2005 born kitten were first captured and collared in 2009. We also captured 3 adults (approximate age 2 years old) in winters 2006-09 that had no PIT-tags or radio collars. We assume these 3 lynx were from litters born in Colorado that were 12 �never found at dens (i.e., why there were no PIT-tags). All lynx captured for collaring or re-collaring were fitted with new Sirtrack TM dual VHF/satellite collars and re-released at their capture locations. Seven adult lynx were captured from March 1999-August 31, 2009 because they were in poor body condition (Table 6). Five of these lynx were successfully treated at the Frisco Creek Rehabilitation Center and re-released in the Core Release Area. One lynx, BC00F07, died from starvation and hypothermia within 1 day of capture at the rehabilitation center. Lynx QU04M07 died 3 days after capture at the rehabilitation center. Necropsy results documented starvation as the cause of death for this lynx that was precipitated by hydrocephalus and bronchopneumonia (unpublished data T. Spraker, CSUVTH). There were no apparent commonalities among these animals. Seven lynx were captured (either by CDOW personnel or conservation personnel in other states) because they were in atypical habitat outside the state of Colorado (Table 6). They were held at Frisco Creek Rehabilitation Center for a minimum of 3 weeks, fitted with new Sirtrack TM dual VHF/satellite collars and re-released in the Core Release Area in Colorado. Five of these 7 lynx were still alive 6 months post-re-release but 3 had already dispersed out of Colorado and 1 stayed in Colorado through August 31, 2009. Two of these lynx died within 6 months of re-release: 1 died of starvation in Colorado and the other died of unknown causes in Nebraska. One lynx captured out of state and re-released currently remains in Colorado. HABITAT USE Landscape-scale daytime habitat use was documented from 9496 aerial locations of lynx collected from February 1999-June 30, 2007. Throughout the year Engelmann spruce - subalpine fir was the dominant cover used by lynx. A mix of Engelmann spruce, subalpine fir and aspen (Populus tremuloides) was the second most common cover type used throughout the year. Various riparian and riparian-mix areas were the third most common cover type where lynx were found during the daytime flights. Use of Engelmann spruce-subalpine fir forests and Engelmann spruce-subalpine fir-aspen forests was similar throughout the year. There was a trend in increased use of riparian areas beginning in July, peaking in November, and dropping off December through June. Site-scale habitat data collected from snow-tracking efforts indicate Engelmann spruce and subalpine fir were also the most common forest stands used by lynx for all activities during winter in southwestern Colorado. Comparisons were made among sites used for long beds, dens, travel and where they made kills. Little difference in aspect, mean slope and mean elevation were detected for 3 of the 4 site types including long beds, travel and kills where lynx typically use gentler slopes ( x = 15.7o ) at a mean elevation of 3173 m, and varying aspects with a slight preference for north-facing slopes. See Shenk (2006) for more detailed analyses of habitat use. DIET AND HUNTING BEHAVIOR Winter diet of lynx was documented through detection of kills found through snow-tracking. Prey species from failed and successful hunting attempts were identified by either tracks or remains. Scat analysis also provided information on foods consumed. A total of 604 kills were located from February 1999-April 2009. We collected over 990 scat samples from February 1999-April 2009 that will be analyzed for content. In each winter, the most common prey item was snowshoe hare, followed by red squirrel (Tamiusciurus hudsonicus; Table 7). The percent of snowshoe hare kills found however, varied annually from a low of 30.4% in 2009 to a high of 90.77% in winter 2002-2003. An annual mean of 69.39% (SE = 5.6) snowshoe hare kills in the diet has been documented. A comparison of percent overstory for successful and unsuccessful snowshoe hare chases indicated lynx were more successful at sites with slightly higher percent overstory, if the overstory 13 �species were Englemann spruce, subalpine fir or willow. Lynx were slightly less successful in areas of greater aspen overstory. This trend was repeated for percent understory at all 3 height categories except that higher aspen understory improved hunting success. Higher density of Engelmann spruce and subalpine fir increased hunting success while increased aspen density decreased hunting success. SNOWSHOE HARE ECOLOGY Three years of a 3-year study to evaluate snowshoe hare densities, demography and seasonal movement patterns among small and medium tree-sized lodgepole pine stands and mature spruce/fir stands have been completed and preliminary results presented (see Appendix I). DISCUSSION In an effort to establish a viable population of lynx in Colorado, CDOW initiated a reintroduction effort in 1997 with the first lynx released in winter 1999. From 1999 through spring 2006, 218 lynx were released in the Core Release Area. Locations of each lynx were collected through aerial- or satellite-tracking to document movement patterns and to detect mortalities. Most lynx remain in the high elevation, forested areas in southwestern Colorado. The use-density surfaces for lynx use in Colorado indicate two primary areas of use. The first is the Core Research Area (see Figure 1) and a secondary core centered in the Collegiate Peaks Wilderness (Figures 1, 3, 4). High use is also documented for 1) the area east of Dillon, on both the north and south sides of I70 and 2) the area north of Hwy 50 centered around Gunnison and then north to Crested Butte. These last 2 high use areas are smaller in extent than the 2 core areas. Dispersal movement patterns for lynx released in 2000 and subsequent years were similar to those of lynx released in 1999 (Shenk 2000). However, more animals released in 2000 and subsequent years remained within the Core Release Area than those released in 1999. This increased site fidelity may have been due to the presence of con-specifics in the area on release. Numerous travel corridors within Colorado have been used repeatedly by more than 1 lynx. These travel corridors include the Cochetopa Hills area for northerly movements, the Rio Grande Reservoir-Silverton-Lizardhead Pass for movements to the west, and southerly movements down the east side of Wolf Creek Pass to the southeast to the Conejos River Valley. Lynx appear to remain faithful to an area during winter months, and exhibit more extensive movements away from these areas in the summer. Reproductive females had the smallest 90% utilization distribution home ranges ( x = 75.2 km2, SE = 15.9 km2), followed by attending males ( x = 102.5 km2, SE = 39.7 km2) and non-reproductive animals ( x = 653.8 km2, SE = 145.4 km2). Most lynx currently being tracked are within the Core Release Area. During the summer months, lynx were documented to make extensive movements away from their winter use areas. Extensive summer movements away from areas used throughout the rest of the year have been documented in native lynx in Wyoming and Montana (Squires and Laurion 1999). Current data collection methods used for the Colorado lynx reintroduction program were not specifically designed to address the reintroduced lynx movements or use of areas in other states. In particular, the core research and release area were in Colorado. Therefore, the number of aerial locations obtained would be far fewer in other states than in Colorado which would bias low the number of lynx and intensity of lynx use documented outside the state. In contrast, obtaining satellite locations is not biased by the location of the lynx. Satellite locations are, however, biased by the shorter time the satellite transmitters function, approximately 18 months versus 60 months for the VHF transmitters used to obtain the aerial locations. However, data collected to meet objectives of the lynx reintroduction program were 14 �used to provide information to help address the question of lynx use outside of Colorado. Due to the rarity of flights conducted outside Colorado, only use-density surfaces generated from satellite locations were used to document relative lynx use of areas in New Mexico, Utah and Wyoming. New Mexico and Wyoming have been used continuously by lynx since the first year lynx were released in Colorado (1999) to the present. Lynx reintroduced in Colorado were first documented in Utah in 2000 and are still being documented there to date. In addition, all levels of lynx use-density documented throughout Colorado are also represented in New Mexico, Utah and Wyoming from none to the highest level of use (Shenk 2007). One den was found in Wyoming. Although no reproduction has been documented in New Mexico or Utah to date, documenting areas of the highest intensity of use and the continuous presence of lynx within these states for over six years does suggest the potential for yearround residency of lynx and reproduction in those states. From 1999-August 2009, there were 118 mortalities of released adult lynx. Human-caused mortality factors are currently the highest causes of death with approximately 29.7% attributed to collisions with vehicles or gunshot. Starvation and disease/illness accounted for 18.6% of the deaths while 37.3% of the deaths were from unknown causes. Lynx mortalities were documented throughout all areas lynx used, including 31 (26.3%) occurring in other states (Figure 2, Table 3). Nearly half (14 of 30) of the out-of-state mortalities were documented in New Mexico. Detailed analysis of lynx mortality was completed and described in Devineau et al. 2009a to evaluate how the different release protocols used to reintroduce lynx in Colorado (Shenk 2002) affected mortality within the first year post-release. Average monthly mortality in the study area during the first year decreased with time in captivity from 0.205 [95% CI 0.069, 0.475] for lynx having spent up to 7 days in captivity to 0.028 [95% CI 0.012, 0.064] for lynx spending > 45 days in captivity before release (Devineau et al. 2009a). The results also suggest that keeping lynx in captivity beyond 5 or 6 weeks accrued little benefit in terms of monthly survival. On a monthly average basis, lynx were as likely to move out (probability = 0.196, SE=0.032) as well as back on (probability = 0.143, SE=0.034) the reintroduction area during the first year after release. Mortality was 1.6x greater outside of the study area suggesting that permanent emigration and differential mortality rates on and off reintroduction areas should be factored into sample size calculations for an effective reintroduction effort. A post-release monitoring plan is critical to providing information to assess aspects of release protocols in order to improve the survival of individuals. Future lynx, as well as other carnivore, reintroductions may use our results to help design reintroduction programs including both their release and post-release monitoring protocols. Over the 10 years of the reintroduction effort, monthly mortality rate was lower inside the study area than outside, and slightly higher for male than for female lynx, although 95% confidence intervals for sexes overlapped (Devineau et al. 2009b). Mortality was higher immediately after release (first month = 0.0368 [SE = 0.0140] inside the study area, and 0.1012 [SE = 0.0359] outside the study area), and then decreased according to a quadratic trend over time (Devineau et al. 2009, in review). Reproduction is critical to achieving a self-sustaining viable population of lynx in Colorado. Reproduction was first documented from the 2003 reproduction season and again in 2004, 2005 and 2006. Lower reproduction occurred in 2006 (Table 5) but did include a Colorado-born female giving birth to 2 kittens, documenting the first recruitment of Colorado-born lynx into the Colorado breeding population. No reproduction was documented in 2007 or 2008. The cause of the decreased reproduction from 2006 08 is unknown. One possible explanation would be a decrease in prey abundance. Reproduction was again observed in 2009 with 5 dens and 10 kittens found in Colorado. Litter size was smaller than previously documented with only2 kittens found in each litter in comparison to a mean of 2.78 found in previous years. In addition, a sex bias towards female kittens was evident in 2009 which was not evident 15 �in prior years. Two litters found in 2009 had both parents born in Colorado, resulting in the first documented third generation Colorado lynx from the reintroduction. Additional reproduction is likely to have occurred in all years from females we were no longer tracking, and from Colorado-born lynx that have not been collared. The dens we find are more representative of the minimum number of litters and kittens in a reproduction season. To achieve a viable population of lynx, enough kittens need to be recruited into the population to offset the mortality that occurs in that year and hopefully even exceed the mortality rate to achieve an increasing population. The use-density surfaces depict intensity of use by location. Why certain areas would be used more intensively than others should be explained by the quality of the habitat in those areas. Characteristics of areas used by lynx, as documented through aerial locations and snow-tracking of lynx in the Colorado core research area, include mature Engelmann spruce-subalpine fir forest stands with 4265% canopy cover and 15-20% conifer understory cover (Shenk 2006). Within these forest stand types, lynx appear to have a slight preference for north-facing, moderate slopes ( x = 15.7°) at high elevations ( x = 3173 m; Shenk 2006). Snow-tracking of released lynx also provided information on hunting behavior and diet through documentation of kills, food caches, chases, and diet composition estimated through prey remains. Primary winter prey species (n = 604) were snowshoe hare and red squirrel (Table 7), which comprised 69.4% (SE = 5.6, n = 11) and 22.6.2% (SE = 5.7, n = 11) of the annual diet, respectively. Thus, areas of good habitat must also support populations of snowshoe hare and red squirrel. In winter, lynx reintroduced to Colorado appear to be feeding on their preferred prey species, snowshoe hare and red squirrel in similar proportions as those reported for northern lynx during lows in the snowshoe hare cycle (Aubry et al. 1999). Environmental conditions in the springs and summers of 2003, 2006 and 2008 resulted in high cone crops during their following winters based on field observations, resulting in increased red squirrel abundance. This may partially explain the higher percent of red squirrel kills, and thus a lower percent of snowshoe hare kills, found in winters 2003-04, 2006-07 and 2008-09 (Table 7). Caution must be used in interpreting the proportion of identified kills. Such a proportion ignores other food items that are consumed in their entirety and thus are biased towards larger prey and may not accurately represent the proportion of smaller prey items, such as microtines, in lynx winter diet. Through snow-tracking we have evidence that lynx are mousing and several of the fresh carcasses have yielded small mammals in the gut on necropsy. The summer diet of lynx has been documented to include less snowshoe hare and more alternative prey than in winter (Mowat et al., 1999). All evidence suggests that most reintroduced lynx are finding adequate food resources to survive. Mowat et al. (1999) suggest lynx and snowshoe hare select similar habitats except that hares select more dense stands than lynx. Very dense understory limits hunting success of the lynx and provides refugia for hares. Given the high proportion of snowshoe hare in the lynx diet in Colorado, we might then assume the habitats used by reintroduced lynx also depict areas where snowshoes hare are abundant and available for capture by lynx in Colorado. From both aerial locations taken throughout the year and from the site-scale habitat data collected in winter, the most common areas used by lynx are in stands of Engelmann spruce and subalpine fir. This is in contrast to adjacent areas of Ponderosa pine, pinyon juniper, aspen and oakbrush. The lack of lodgepole pine in the areas used by the lynx may be more reflective of the limited amount of lodgepole pine in southwestern Colorado, the Core Release Area, rather than avoidance of this tree species. Hodges (1999) summarized habitats used by snowshoe hare from 15 studies as areas of dense understory cover from shrubs, stands that are densely stocked, and stands at ages where branches have 16 �more lateral cover. Species composition and stand age appears to be less correlated with hare habitat use than is understory structure (Hodges 1999). The stands need to be old enough to provide dense cover and browse for the hares and cover for the lynx. In winter, the cover/browse needs to be tall enough to still provide browse and cover in average snow depths. Hares also use riparian areas and mature forests with understory. Site-scale habitat use documented for lynx in Colorado indicate lynx are most commonly using areas with Engelmann spruce understory present from the snow line to at least 1.5 m above the snow. The mean percent understory cover within the habitat plots is typically less than 15% regardless of understory species. However, if the understory species is willow, percent understory cover is typically double that, with mean number of shrubs per plot approximately 80, far greater than for any other understory species. In winter, hares browse on small diameter woody stems (<0.25"), bark and needles. In summer, hares shift their diet to include forbs, grasses, and other succulents as well as continuing to browse on woody stems. This shift in diet may express itself in seasonal shifts in habitat use, using more or denser coniferous cover in winter than in summer. The increased use of riparian areas by lynx in Colorado from July to November may reflect a seasonal shift in hare habitat use in Colorado. Major (1989) suggested lynx hunted the edge of dense riparian willow stands. The use of these edge habitats may allow lynx to hunt hares that live in habitats normally too dense to hunt effectively. The use of riparian areas and riparian-Engelmann spruce-subalpine fir and riparian-aspen mixes documented in Colorado may stem from a similar hunting strategy. However, too little is known about habitat use by hares in Colorado to test this hypothesis at this time. Lynx also require sufficient denning habitat. Denning habitat has been described by Koehler (1990) and Mowat et al. (1999) as areas having dense downed trees, roots, or dense live vegetation. We found this to be in true in Colorado as well (Shenk 2006). In addition, the dens used by reintroduced lynx were at high elevations and on steep north-facing slopes. All females that were documented with kittens denned in areas within their winter-use area. FUTURE STUDIES Monitoring of individuals through telemetry continues in an effort to document the viability of the reintroduced lynx population. However, as time since release increases, battery failure of telemetry collars also increases resulting in fewer released animals having working collars. In addition, few Colorado-born lynx have been captured and fitted with telemetry collars. Although trapping efforts have been conducted in earnest since 2003 to capture and fit animals with working telemetry collars, we have not been able to collar a sufficient number of animals throughout the state to document the status and trends of lynx distribution and demography throughout Colorado from these collared animals. The extent of lynx dispersal and current distribution beyond the Core Research Area and the difficulty of trapping lynx in all areas they inhabit, particularly large tracts of wilderness, requires redesigning our sampling and monitoring efforts to provide valid estimates of lynx distribution. Exploring occupancy modeling using non-invasive techniques may be a feasible alternative for ascertaining trends in population status and forming a basis for a large scale area monitoring program Therefore, we propose that monitoring lynx distribution would consist of 3 potential primary objectives to document the extent, stability and potential distribution of lynx (at the species and individual level) in Colorado. To estimate patterns in lynx distribution in Colorado a monitoring program could be developed that will: 1) annually estimate the spatial distribution of lynx in the core area and assess changes in lynx distribution over time; 2) detect colonization or expansion of lynx into other portions of the state, and 3) determine whether distribution or persistence are associated with habitat features, measured at the landscape-scale (stand age or composition). 17 �In order to design the most efficient statewide monitoring program, however, we will first evaluate the detection probabilities and efficacy of 3 methods of detection. These include snow-tracking, hair snares and camera surveillance. All of these methods can be conducted with minimal (camera surveillance or collection of hair) or non-invasive approaches (collection of scat samples) to individual animals. A pilot study will be conducted first to establish the most valid, efficient method to estimate the distribution and persistence of lynx. (see Appendix II for the detailed study plan). Information from the pilot study will then be used to design the most efficient strategy to meet the objectives of larger-scale monitoring programs to detect changes in lynx persistence and distribution as a foundation for assessing whether lynx have become established and will persist in Colorado. First, a minimally invasive monitoring program will be designed and implemented within the Core Research Area to describe lynx distribution and distribution trends in this area. A statewide plan could then be implemented to describe lynx distribution and distribution trends throughout Colorado. This monitoring protocol could result in the development of a standardized methodology that might be used by multiple entities to monitor the status of lynx throughout their range in North America. SUMMARY From results to date it can be concluded that CDOW developed release protocols that ensure high initial post-release survival of lynx, and on an individual level, lynx demonstrated they can survive longterm in areas of Colorado. We also documented that reintroduced lynx exhibited site fidelity, engaged in breeding behavior and produced kittens that were recruited into the Colorado breeding population. What is yet to be demonstrated is whether current conditions in Colorado can support the recruitment necessary to offset annual mortality in order to sustain the population. Monitoring of reintroduced lynx will continue in an effort to document such viability. ACKNOWLEDGMENTS The lynx reintroduction program involves the efforts of literally hundreds of people across North America, in Canada and USA. Any attempt to properly acknowledge all the people who played a role in this effort is at risk of missing many people. The following list should be considered to be incomplete. CDOW CLAWS Team (1998-2001): Bill Andree, Tom Beck, Gene Byrne, Bruce Gill, Mike Grode, Rick Kahn (Program Leader), Dave Kenvin, Todd Malmsbury, Jim Olterman, Dale Reed, John Seidel, Scott Wait, Margaret Wild. CDOW: John Mumma (Director 1996-2000), Russell George (Director 2001-2003), Bruce McCloskey (Director 2004-2007), Conrad Albert, Jerry Apker, Laurie Baeten, Cary Carron, Don Crane, Larry DeClaire, Phil Ehrlich, Lee Flores, Delana Friedrich, Dave Gallegos, Juanita Garcia, Drayton Harrison, Jon Kindler, Ann Mangusso, Jerrie McKee, Gary Miller, Melody Miller, Mike Miller, Kirk Navo, Robin Olterman, Jerry Pacheo, Mike Reid, Tom Remington, Ellen Salem, Eric Schaller, Mike Sherman, Jennie Slater, Steve Steinert, Kip Stransky, Suzanne Tracey, Anne Trainor, Scott Wait, Brad Weinmeister, Nancy Wild, Perry Will, Lisa Wolfe, Brent Woodward, Kelly Woods, Kevin Wright. Lynx Advisory Team (1998-2001): Steve Buskirk, Jeff Copeland, Dave Kenny, John Krebs, Brian Miller (Co-Leader), Mike Phillips, Kim Poole, Rich Reading (Co-Leader), Rob Ramey, John Weaver. U. S. Forest Service: Kit Buell, Joan Friedlander, Dale Gomez, Jerry Mastel, John Squires, Fred Wahl, Nancy Warren. U. S. Fish and Wildlife Service: Lee Carlson, Gary Patton (1998-2000), Kurt Broderdorp. State Agencies: Alaska: ADF&G: Cathie Harms, Mark Mcnay, Dan Reed (Regional Manager), Wayne Reglin (Director), Ken Taylor (Assist. Director), Ken Whitten, Randy Zarnke, Other:Ron Perkins (trapper), Dr. Cort Zachel (veterinarian). Washington: Gary Koehler. 18 �National Park Service: Steve King. Colorado State University: Alan Franklin, Gary White. Colorado Natural Heritage Program: Rob Schorr, Mike Wunder. Canada: British Columbia: Dr. Gary Armstrong (veterinarian), Mike Badry (government), Paul Blackwell (trapper coordinator), Trappers: Dennis Brown, Ken Graham, Tom Sbo, Terry Stocks, Ron Teppema, Matt Ounpuu. Yukon: Government: Arthur Hoole (Director), Harvey Jessup, Brian Pelchat, Helen Slama, Trappers: Roger Alfred, Ron Chamber, Raymond Craft, Lance Goodwin, Jerry Kruse, Elizabeth Hofer, Jurg Hofer, Guenther Mueller (YK Trapper’s Association), Ken Reeder, Rene Rivard (Trapper coordinator), Russ Rose, Gilbert Tulk, Dave Young. Alberta: Al Cook. Northwest Territories: Albert Bourque, Robert Mulders (Furbearer Biologist), Doug Steward (Director NWT Renewable Res.), Fort Providence Native People. Quebec: Luc Farrell, Pierre Fornier. Colorado Holding Facility: Herman and Susan Dieterich, Kate Goshorn, Loree Harvey, Rachel Riling. Pilots: Dell Dhabolt, Larry Gepfert, Al Keith, Jim Olterman, Matt Secor, Brian Smith, Whitey Wannamaker, Steve Waters, Dave Younkin. Field Crews (1999-2009): Steve Abele, Brandon Barr, Bryce Bateman, Todd Bayless, Nathan Berg, Ryan Besser, Jessica Bolis, Mandi Brandt, Keith Bruno, Brad Buckley. Patrick Burke, Braden Burkholder, Paula Capece, Matthew Chappell, Stacey Ciancone, Doug Clark, John DePue, Shana Dunkley, Brady Dunne, Tim Hanks, Carla Hanson, Dan Haskell, Nick Hatch, Matt Holmes, Allie Hunter, Andy Jennings, Susan Johnson, Paul Keenlance, Darrin Kite, Patrick Kolar, Tony Lavictoire, Jenny Lord, Clay Miller, Denny Morris, Kieran O’Donovan, Gene Orth, Chris Parmater, Bob Peterson, Jake Powell, Jeremy Rockweit, Britta Schielke, Jenny Shrum, Josh Smith, Heather Stricker, Adam Strong, Dave Unger, James Waddell, David Waltz, Andy Wastell, Mike Watrobka, Lyle Willmarth, Leslie Witter, Kei Yasuda, Jennifer Zahratka. Research Associates: Bob Dickman, Grant Merrill. Data Analysts: Karin Eichhoff, Joanne Stewart, Anne Trainor. Data Entry: Charlie Blackburn, Patrick Burke, Rebecca Grote, Angela Hill, Mindy Paulek. Mary Schuette , Dave Theobald and Chris Woodward provided assistance with the GIS analysis. . Funding: CDOW, Great Outdoors Colorado (GOCO), Turner Foundation, U.S.D.A. Forest Service, Vail Associates, Colorado Wildlife Heritage Foundation. LITERATURE CITED Aubry, K. B., G. M. Koehler, J. R. Squires. 1999. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Bartmann, R. M., and Byrne, G. (2001) Analysis and critique of the 1998 snowshoe hare pellet survey. Colorado Division of Wildlife Report No. 20. Fort Collins, Colorado. Byrne, G. 1998. Core area release site selection and considerations for a Canada lynx reintroduction in Colorado. Report for the Colorado Division of Wildlife. Devineau, O., T. M. Shenk, P. F. Doherty Jr., G. C. White, and R. H. Kahn. 2009. Assessing release protocols for the Colorado Canada lynx (Lynx canadensis) reintroduction. Journal of Wildlife Management (in review). Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2009. Estimating mortality for a widely dispersing carnivore, the Canada lynx (Lynx canadensis) reintroduced to Colorado. Journal of Applied Ecology (in review). Elton, C. and M. Nicholson 1942. The ten-year cycle in numbers of lynx in Canada. Journal of Animal Ecology 11: 215-244. Hodges, K. E. 1999. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, 19 �and J. R. Squires editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Koehler, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. Kolbe, J. A., J. R. Squires, T. W. Parker. 2003. An effective box trap for capturing lynx. Journal of Wildlife Management 31:980-985. Major, A. R. 1989. Lynx, Lynx canadensis canadensis (Kerr) predation patterns and habitat use in the Yukon Territory, Canada. M. S. Thesis, State University of New York, Syracuse. Mowat, G., K. G. Poole, and M. O’Donoghue. 1999. Ecology of lynx in northern Canada and Alaska. Pages 265-306 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. O’Donoghue, M, S. Boutin, D. L. Murray, C. J. Krebs, E. J. Hofer, U. Breitenmoser, C. BreitenmoserWuersten, G. Zuleta, C. , C. Doyle, and V. O. Nams. 2001. Mammalian predators: Coyotes and lynx. in Ecosystem Dynamics of the Boreal Forest: The Kluane Project. eds. C. J. Krebs, S. Boutin and R. Boonstra. Oxford University Press, Inc. New York, New York Poole, K. G., G. Mowat, and B. G. Slough. 1993. Chemical immobilization of lynx. Wildlife Society Bulletin 21:136-140. Shenk, T. M. 1999. Program Narrative Study Plan: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2001. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 7- 34. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2006. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 1-45. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 1-57. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2008. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 1-57. Colorado Division of Wildlife, Fort Collins, Colorado Silverman, B.W. 1986. Density Estimation for Statistics and Data Analysis. Chapman and Hall. New York, New York, USA. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. Wild, M. A. 1999. Lynx veterinary services and diagnostics. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. Zahratka, J. L. and T. M. Shenk. 2008. Population estimates of snowshoe hares in the southern Rocky Mountains. Journal of Wildlife Management 72: 906-912. Prepared by ___________________________________ Tanya M. Shenk, Wildlife Researcher 20 �Table 1. Number of wild-caught male (M) and female (F) Canada lynx (Lynx canadensis) from Alaska (AK) and Canada (BC = British Columbia, MB = Manitoba, QU = Quebec and YK = Yukon) released in southwestern Colorado per year from 1999–2006. State / Province of Origin Total Year %Released Sex AK BC MB QU YK 1999 19 2000 25 2003 15 2004 17 2005 17 2006 6 Total F 13 5 4 22 M 7 6 6 19 F 6 9 20 35 M 4 9 7 20 F 10 7 17 M 10 5 16 F 7 10 17 M 13 7 20 F 4 M 9 F M 30 1 3 8 3 18 8 3 20 4 3 7 5 2 7 48 218 91 4 45 Table 2. Status of adult Canada lynx (Lynx canadensis) reintroduced to Colorado as of August 31, 2009. Females Lynx Males Unknown TOTALS Released 115 103 218 Known Dead 65 52 1 118 Possible Alive 50 51 100 Missing 27 35 61a Monitoring/tracking 20 17 37 a 1 is unknown mortality Table 3. Causes of death for all Canada lynx (Lynx canadensis) released into southwestern Colorado 1999-2006 as of August 31, 2009. Mortalities Cause of Death Total (%) In Colorado (%) Outside Colorado (%) Unknown 44 (37.3) 29 (24.6) 15 (12.7) Gunshot 16 (13.6) 10 (8.5) 6 (5.1) Hit by Vehicle 14 (11.9) 9 (7.6) 5 (4.2) Starvation 12 (10.2) 11 (9.3) 1 (0.8) Other Trauma 8 (6.8) 7 (5.9) 1 (0.8) Plague 7 (5.9) 7 (5.9) 0 (0) Predation 6 (5.1) 6 (5.1) 0 (0) Probable Gunshot 5 (4.2) 4 (3.4) 1 (0.8) Probable Predation 3 (2.5) 2 (1.7) 1 (0.8) Illness 3 (2.5) 2 (1.7) 1 (0.8) Total Mortalities 118 87 (73.7) 31 (26.3) 21 �Table 4. Known lynx mortalities (n = 31) and causes of death documented by state outside of Colorado from February 1999 – August 31, 2009. Lynx ID AK99F8 Unknown AK99M11 YK99M06 AK99F13 YK00F04 BC99M04 QU05M01 QU04F05 QU03F07 BC00M04 YK06F01 BC03M08 BC06F07 AK99M06 AK99M01 QU05M08 MB05F02 BC00F14 QU04F07 BC06M10 QU04F02 AK00M03 QU05M03 YK06M01 YK00F07 BC06M13 YK99F01 YK00M03 YK05M03 YK05M02 State Date Mortality Recorded Cause of Death New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico New Mexico Nebraska Nebraska Nebraska Nebraska Wyoming Wyoming Wyoming Wyoming Utah Utah Utah Utah Utah Arizona Kansas Montana Iowa 7/30/1999 2000 1/27/2000 6/19/2000 6/22/2000 4/20/2001 6/7/2002 8/22/2005 8/26/2005 9/15/2005 7/19/2006 10/19/2006 10/19/2006 1/8/2007 11/16/1999 1/11/2005 10/1/2006 2/13/2007 7/28/2004 9/21/2004 8/15/2006 3/14/2007 7/2/2001 10/26/2005 12/4/2006 8/6/2007 12/11/08 9/15/2005 9/30/2005 11/8/2005 8/6/2007 Starvation Hit by Vehicle Unknown Probable Gunshot Unknown Gunshot Gunshot Unknown Hit by Vehicle Unknown Unknown Unknown Unknown Gunshot Gunshot Snared (Other Trauma) Unknown Gunshot Unknown Unknown Vehicle Collision Unknown Unknown Unknown Unknown Unknown Unknown Gunshot Vehicle Collision Unknown Vehicle Collision Table 5. Lynx reproduction summary statistics for 1999-2009. No reproduction was expected in 1999 because it was the first year of lynx releases and most animals were released after breeding season. Year Females Tracked 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 TOTAL /MEAN 9 25 21 17 26 40 42 34 28 22 Dens Found in May/June 0 0 0 6 11 17 4 0 0 5 Percent Tracked Females with Kittens 0.0 0.0 0.0 35.3 46.2 42.5 9.5 0.0 0.0 22.7 Additional Litters Found in Winter 0 0 0 0 2 1 0 0 0 - 22 Total Kittens Found Sex Ratio M/F (SE) 2.67 (0.33) 2.83 (0.24) 2.88 (0.18) 2.75 (0.47) 0 0 0 16 39 50 11 1.0 1.5 0.8 1.2 2.00 (0.00) 0 0 10 0.4 2.63(0.16) 126 0.98 (0.18) Mean Kittens/Litter (SE) �Table 6. Lynx captured because they were in poor body condition or were in atypical habitat and their fates 6 months post re-release as of August 31, 2009. Lynx ID Date of Capture State Where Captured Reason For Capture BC99F6 AK99M9 AK99F2 BC00F7 BC00M13 BC03M08 QU04M07 BC04M01 QU04F02 QU05M08 QU04M04 YK00F07 YK05M02 BC04M08 3/25/1999 3/24/2000 4/18/2000 2/11/2001 3/21/2001 9/5/2003 2/2/2006 11/5/2004 4/10/2005 11/25/2005 12/5/2006 12/12/2006 1/1/2007 1/22/2007 Colorado Colorado Colorado Colorado Wyoming Colorado Colorado Utah Nebraska Wyoming Utah Utah Kansas Wyoming Poor body condition Poor body condition Poor body condition Poor body condition Poor body condition Poor body condition Poor body condition Atypical habitat Atypical habitat Atypical habitat Atypical habitat Atypical habitat Atypical habitat Atypical habitat Date of Re-release 5/28/1999 5/3/2000 5/22/2000 N/A 4/24/2001 1/1/2004 N/A 12/5/2004 5/7/2005 4/18/2006 1/20/2007 1/20/2007 2/2/2007 2/15/2007 Status 6 Months Post Re-release Dead Missing Alive in Colorado Dead Alive in Colorado Alive in Colorado Dead Alive in Colorado Alive in Wyoming Dead Dead in Colorado Alive in Utah Alive in Iowa Alive in Colorado Table 7. Number of kills found each winter field season through snow-tracking of lynx and percent composition of kills of the three primary prey species. Field Season 1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007 2007-2008 2008-2009 Total/Mean n 9 83 89 54 65 37 78 50 41 42 56 604 Snowshoe Hare 55.56 67.47 67.42 90.74 90.77 67.57 83.33 90.00 61.00 59.00 30.4 69.39 (SE=5.6) Prey (%) Red Squirrel Cottontail 22.22 0 19.28 1.20 19.10 8.99 5.56 0 6.15 0 27.03 2.70 10.26 0 0.08 0 39.0 0 33.3 0 66.1 0 22.55 (SE=5.7) 1.17 (SE=0.82) 23 Other 22.22 12.05 4.49 3.70 3.08 2.70 6.41 0.02 0 7.4 3.5 5.96 (SE=1.92) �Figure 1. Lynx are monitored throughout Colorado and by satellite throughout the western United States. The lynx core release area, where all lynx were released, is located in southwestern Colorado (outlines in white). A lynx-established core use area has developed in the Taylor Park and Collegiate Peak area in central Colorado. 24 �Figure 2. All documented lynx locations (non-truncated datasets) obtained from either aerial (red circles) or satellite (yellow circles) tracking from February 1999 through August 31, 2009 All known lynx mortality locations (n = 112) are displayed as black stars. 25 �Figure 3. Use-density surface for lynx satellite locations (non-truncated dataset) in Colorado from April 2000-April 2009. 26 �Figure 4. Use-density surface for lynx satellite locations (non- truncated dataset) in Colorado from April 2000-April 2009 27 �APPENDIX I Colorado Division of Wildlife August 2009 WILDLIFE RESEARCH REPORT State of Colorado Cost Center_______3430 Work Package_____0670 Task No.___________2 : : : : Federal Aid Project: N/A : Division of Wildlife Mammals Research Lynx Reintroduction Density, Demography, and Seasonal Movements of Snowshoe Hare in Colorado Period Covered: July 1, 2008- June 30, 2009 Author: J. S. Ivan, Ph.D. Candidate, Colorado State University Personnel: Dr. T. Shenk of CDOW and Dr. G. C. White of Colorado State University. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A program to reintroduce the threatened Canada lynx (Lynx canadensis) into Colorado was initiated in 1997. Analysis of scat collected from winter snow tracking indicates that snowshoe hares (Lepus americanus) comprise 65–90% of the winter diet of reintroduced lynx in most winters. Thus, existence of lynx in Colorado and success of the reintroduction hinge at least partly on maintaining adequate and widespread hare populations. Beginning in July 2006, I initiated a study to assess the relative value of 3 stand types for providing hare habitat in Colorado. These types include mature, uneven-aged Engelmann spruce (Picea engelmannii)-subalpine fir (Abies lasiocarpa) forests, sapling lodgepole pine (Pinus contorta) forests (“small lodgepole”), and pole-sized lodgepole pine forests (“medium lodgepole”). Estimates and comparisons of survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each stand will provide the metrics for assessing these stands. Snowshoe hare densities on the study area are low compared to densities reported elsewhere. Within the study area, hare densities during summer were generally highest in small lodgepole stands, followed by mature spruce/fir and medium lodgepole, respectively. Absolute hare densities declined considerably in summer 2007 and rebounded only slightly during summer 2008. Hare density in small and medium lodgepole stands equalized during winters. However, as with summer, overall density was much lower during the second winter compared to the first and rebounded somewhat during the last winter. Hare survival from summer to winter was relatively high whereas winter to summer survival is quite low. Survival does not appear to differ between stand types or years, although a much more thorough analysis that will include known-fate telemetry data is forthcoming. This combined analysis will provide a final winter-summer estimate, will bring much more information to bear on the estimation process, and should increase precision of all estimates by a fair amount. 28 �WILDIFE RESEARCH REPORT DENSITY AND SURVIVAL OF SNOWSHOE HARES IN TAYLOR PARK AND PITKIN JACOB S. IVAN P. N. OBJECTIVE Assess the relative value of 3 stand types (mature spruce/fir, sapling lodgepole, pole-sized lodgepole) that purportedly provide high quality hare habitat by estimating survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each type. SEGMENT OBJECTIVES 1. Complete mark-recapture work across all replicate stands during late summer (mid-July through midSeptember) and winter (mid-January through March). 2. Obtain daily telemetry locations on radio-tagged hares for 10 days immediately after capture periods, as well as monthly between primary trapping sessions. 3. Locate, retrieve, and refurbish radio tags as mortalities occur. INTRODUCTION A program to reintroduce the threatened Canada lynx (Lynx canadensis) into Colorado was initiated in 1997. Since that time, 218 lynx have been released in the state, and an extensive effort to determine their movements, habitat use, reproductive success, and food habits has ensued (Shenk 2005). Analysis of scat collected from winter snow tracking indicates that snowshoe hares (Lepus americanus) comprise 65–90% of the winter diet of reintroduced lynx during most winters (T. Shenk, Colorado Division of Wildlife, unpublished data). Thus, as in the far north where the relationship between lynx and snowshoe hares has captured the attention of ecologists for decades, it appears that the existence of lynx in Colorado and success of the reintroduction effort may hinge on maintaining adequate and widespread populations of hares. Colorado represents the extreme southern range limit for both lynx and snowshoe hares (Hodges 2000). At this latitude, habitat for each species is less widespread and more fragmented compared to the continuous expanse of boreal forest at the heart of lynx and hare ranges. Neither exhibits dramatic cycles as occur farther north, and typical lynx (≤2−3 lynx/100km2; Aubry et al. 2000) and hare (≤1−2 hares/ha; Hodges 2000) densities in the southern part of their range correspond to cyclic lows form northern populations (2-30 lynx/100 km2, 1−16 hares/ha; Aubry et al. 2000, Hodges 2000, Hodges et al. 2001). Whereas extensive research on lynx-hare ecology has occurred in the boreal forests of Canada, literature regarding the ecology of these species in the southern portion of their range is relatively sparse. This scientific uncertainty is acknowledged in the “Canada Lynx Conservation Assessment and Strategy,” a formal agreement between federal agencies intended to provide a consistent approach to lynx conservation on public lands in the lower 48 states (Ruediger et al. 2000). In fact, one of the explicit guiding principles of this document is to “retain future options…until more conclusive information concerning lynx management is developed.” Thus, management recommendations in this agreement are decidedly conservative, especially with respect to timber management, and are applied broadly to cover all habitats thought to be of possible value to lynx and hare. Accurate identification and detailed 29 �description of lynx-hare habitat in the southern Rocky Mountains would permit more informed and refined management recommendations. A commonality throughout the snowshoe hare literature, regardless of geographic location, is that hares are associated with dense understory vegetation that provides both browse and cover (Wolfe et al. 1982, Litvaitis et al. 1985, Hodges 2000, Homyack et al. 2003, Miller 2005). In western mountains, this understory can be provided by relatively young conifer stands regenerating after stand-replacing fires or timber harvest (Sullivan and Sullivan 1988, Koehler 1990a, Koehler 1990b, Bull et al. 2005) as well as mature, uneven-aged stands (Beauvais 1997, Griffin 2004). Hares may also take advantage of seasonally abundant browse and cover provided by deciduous shrubs (e.g., riparian willow [Salix spp.], aspen [Populus tremuloides]; Wolff 1980, Miller 2005). In drier portions of hare range, such as Colorado, regenerating stands can be relatively sparse, and hares may be more associated with mesic, late-seral forest and/or riparian areas than with young stands (Ruggiero et al. 2000). Numerous investigators have sought to determine the relative importance of these distinctly different habitat types with regards to snowshoe hare ecology. Most previous evaluations were based on hare density or abundance (Bull et al. 2005), indices to hare density and abundance (Wolfe et al. 1982, Koehler 1990a, Beauvais 1997, Miller 2005), survival (Bull et al. 2005), and/or habitat use (Dolbeer and Clark 1975). Each of these approaches provides insight into hare ecology, but taken singly, none provide a complete picture and may even be misleading. For example, extensive use of a particular habitat type may not accurately reflect the fitness it imparts on individuals, and density can be high even in “sink” habitats (Van Horne 1983). A more informative approach would be to measure density, survival, and habitat use simultaneously in addition to recruitment and population growth rate through time. Griffin (2004) employed such an approach and found that summer hare densities were consistently highest in young, dense stands. However, he also noted that only dense mature stands held as many hares in winter as in summer. Furthermore hare survival seemed to be higher in dense mature stands, and only dense mature stands were predicted (by matrix projection) to impart a mean positive population growth rate on hares. Griffin’s (2004) study occurred in the relatively moist forests of Montana, which share many similarities but also many notable differences with Colorado forests including levels of fragmentation, species composition, elevation, and annual precipitation. The study outlined below is designed principally to evaluate the importance of young, regenerating lodgepole pine (Pinus contorta) and mature Engelmann spruce (Picea engelmannii)/ subalpine fir (Abies lasiocarpa) stands in Colorado by examining density and demography of snowshoe hares that reside in each. I determined that 2 classes of regenerating lodgepole could provide adequate hare habitat. Thus, I sampled both “small” (2.54-12.69 cm dbh) and “medium” (12.70-22.85 cm dbh) stands regenerating from clearcutting 20 and 40 years ago, respectively (Figure 1). Medium lodgepole stands were pre-commercially thinned 20 years ago; small lodgepole stands have not yet been thinned. Density and demography will be estimated primarily from mark-recapture techniques as data from such approaches can simultaneously provide information on both aspects of hare ecology. However, I will augment both density and demographic analyses with telemetry data to improve the accuracy and precision of estimates. The estimates reported here do not yet reflect addition of telemetry information. My hope is that information gathered from this research will be drawn upon as managers make routine decisions, leading to landscapes that include stands capable of supporting abundant populations of hares. I assume that if management agencies focus on providing habitat, hares will persist. 30 �Hypotheses 1) In general, snowshoe hare density in Colorado will be relatively low (≤0.5 hares/ha) compared to densities reported in northern boreal forests, even immediately post-breeding when an influx of juveniles will bolster hare numbers. 2) Snowshoe hare density will be consistently highest in small lodgepole pine stands, followed by large spruce/fir and medium lodgepole pine, respectively. 3) Survival will generally be highest in mature (large) spruce/fir stands followed by small and medium lodgepole pine, respectively. 4) Finite population growth rate will be consistently at or above 1.0 in mature spruce/fir stands with survival contributing most significantly to the growth rate. Finite growth rates for the lodgepole pine stands will be more variable. 5) Snowshoe hares will significantly shift their home ranges to make use of abundant food and cover provided by riparian willow (and/or aspen) habitats in summer. 6) Snowshoe hare density, survival, and recruitment will be highly correlated with understory cover and stem density. STUDY AREA The study area stretches from Taylor Park to Pitkin in central Colorado (Figure 2). Elevation ranges from 2700 m to 4000 m. Sagebrush (Artemisia spp.) dominates broad, low-lying valleys. Most montane areas are covered by even-aged, large-diameter lodgepole pine forests with sparse understory. Moist, north-facing slopes and areas near tree line are dominated by large-diameter Engelmann spruce/subalpine fir. Interspersed along streams and rivers are corridors of willow. Patches of aspen occur sporadically on southern exposures. This area was chosen over other potential study areas in the state because 1) it contained numerous examples of the 3 stand types of interest (more southern regions lack naturally occurring stands of lodgepole pine), 2) it was not subject to confounding effects of largescale mountain pine beetle outbreak as were more northern stands, and 3) an adequate number of radio frequencies were available to support a large study with hundreds of radio-tagged individuals. Within the study area I selected sample stands based on the following: Potential replicate stands were required to be 1) close enough geographically to minimize differences due to climate, weather, and topography, but are far enough apart to be considered independent, 2) adjacent to one or more riparian willow corridors, 3) within 1 km of an access road for logistical purposes, 4) of suitable size and shape to admit a 16.5-ha trapping grid, and 5) consistent in their management history (i.e., replicate lodgepole pine stands were clear-cut and/or thinned within 1-2 years of each other). I queried the U.S. Forest Service R2VEG GIS database using the criteria listed above to initially develop a suite of potential sample stands. I further narrowed this suite after obtaining updated standlevel information from local USFS personnel (Art Haines, Silviculturalist, USFS Gunnison Ranger District, personal communication). Finally, I ground-truthed potential stands and qualitatively assessed their representativeness and similarity to other potential replicates. Given the numerous constraints imposed, very few stands met all criteria. Thus, I was unable to randomly select sample stands from a population of suitable stands. Rather, I subjectively chose the “best” stands from among the handful that met my criteria. Small lodgepole stands rarely occur on the landscape in patches large enough to fit a full trapping grid. To accommodate this, I sampled 6 replicate small lodgepole stands (rather than 3) using half-sized trapping grids. 31 �METHODS Experimental Design/Procedures Variables.--The response variables of interest for this project include stand-specific snowshoe hare density (D), apparent survival (φ), recruitment (f), finite population growth rate (λ), and a metric of seasonal movement. Density is the number of hares per unit area and is estimated using conventional “boundary strip” techniques (Wilson and Anderson 1985) in this report. Stand-specific demographic parameters were estimated primarily from capture-mark-recapture methods. As such, apparent survival was defined as the probability that a marked animal alive and in the population at time i survived and was in the population at time i + 1. Apparent survival encompassed losses due to both death and emigration. Estimates of recruitment, population growth, and seasonal movement are forthcoming and not provided in this report. Potential explanatory variables for snowshoe hare density, demographics, and movement include general species composition and structural stage of each stand in which response variables are measured. Additionally, stem density, horizontal cover, and canopy cover (to a lesser extent) are highly correlated with snowshoe hare abundance and habitat use (Wolfe et al. 1982, Litvaitis et al. 1985, Hodges 2000, Zahratka 2004, Miller 2005). Thus, I further characterized vegetation in each stand by measuring stem density by size class (1-7 cm, 7.1-10 cm, and >10 cm), percent canopy cover, percent horizontal cover of understory and basal area. Basal area is an easily obtainable metric that may be correlated with the other variables and is recorded routinely during timber cruises, whereas the others are not. Thus, it might prove a useful link for biologists designing management strategies for snowshoe hare. Additionally, I recorded physical covariates such as ambient temperature, precipitation, and snow depth at each stand during sampling. These metrics were not included in the current preliminary analyses, but will be used as covariates in future models. Sampling.--All trapping and handling procedures have been approved by the Colorado State University Animal Care and Use Committee and filed with the Colorado Division of Wildlife. Snowshoe hares breed synchronously and generally exhibit 2 birth pulses in Colorado (although in some years, some individuals may have 3 litters), with the first pulse terminating approximately June 5−20 and the second approximately July 15–25 (Dolbeer 1972). To obtain a maximum density estimate, I began data collection on the first suite of sites immediately following the second birth pulse in late July. Along with a crew of 5 technicians, I deployed one 7 × 12 trapping grid (50-m spacing between traps; grid covers 16.5 ha) in the large spruce/fir and medium lodgepole stands within the first suite, along with 2 6 × 7 grids in 2 small lodgepole stands. Grid set up and trap deployment followed Griffin (2004) and Zahratka (2004). Grid locations and orientation within each stand were chosen subjectively to accommodate logistical constraints and to ensure that hares using the grid had ample opportunity to use adjacent riparian willow zones. As traps were deployed, they were locked open and “pre-baited” with apple slices, hay cubes, and commercial rabbit chow. Traps were pre-baited in this manner for a total of 3 nights to maximize capture rates when trapping began. This minimized the number of trap-nights needed to capture the desired number of animals which in turn minimized trap-related injuries and minimized problems with predators keying into trap lines. During pilot work in winter 2005, I observed low but increasing capture rates (<0.20) during the first 3 nights of trapping, with higher, more stable capture probabilities after 3 days (approximately 0.35–0.45). Thus 3 days of pre-baiting seemed reasonable. Traps were set on the afternoon of the 4th day and checked early each morning and re-set again in the evening on days 5–9. By checking traps in both morning and evening I prevented hares from being entrapped >13 hours, which minimized capture stress. A crew of 2 people worked together on each grid to check traps and process captures as quickly as possible. All captured hares were coaxed out of the trap and into a dark handling bag by blowing quick shots of air on them from behind. Hares remained in the 32 �handling bag, physically restrained with their eyes covered, for the entire handling process. Each individual was aged, sexed, marked with a passive integrated transponder (PIT) tag and temporary ear mark (to track PIT tag retention), then released. Aging consisted of assigning each individual as either juvenile (<1 year old, <1000 g) or adult (≥1 year old, ≥1000 g) based on weight and development of genitalia. This criterion is accurate through the end of September at which point juveniles are difficult to distinguish from adults (K. Hodges, University of British Columbia; P. Griffin, University of Montana, personal communication). After the first day of trapping, all captured hares were scanned for a PIT tag prior to any handling and those already marked were recorded and immediately released. Traps and bait were completely removed from the grid on day 10. In addition to PIT tags and ear marks, I radio collared up to 10 hares captured on each grid with a 28-g mortality-sensing transmitter (BioTrack, LTD) to facilitate unbiased density estimation as well as assessment of seasonal movements. I expected heterogeneity in snowshoe hare movements and use of the grid area, with potential bias surfacing due to location at which a hare is captured (e.g., hares captured on the edge of a grid may use the grid area differently than those captured at the center), and differential behavioral responses to trapping (e.g., young individuals may have lower capture probabilities and thus may be more likely to be captured on later occasions). To guard against the first potential bias, I randomly selected a starting trap location each morning and ran the grid systematically from that point. Thus, the first several hares encountered (and collared) were as likely to be from the inner part of the grid as from the edge. To protect against the second potential source of bias, I refrained from deploying the final 3 collars until days 4 and 5 of the trapping session. Immediately following the removal of traps, the field crew began work locating each radiocollared hare 1–2 times per day for 10 days. Most locations were obtained by triangulation from relatively close proximity, but some were obtained by “homing” on a signal (Samuel and Fuller 1996, Griffin 2004) taking care not to push hares while approaching them. Because hares are largely nocturnal (Keith 1964, Mech et al. 1966, Foresman and Pearson 1999), I made an effort to conduct telemetry work at various times of the night (safety and logistics permitting) and day to gather a representative sample of locations for each hare. Crews gathered telemetry locations for radio-collared hares on the initial suite of sites for 10 days. Then the 10−day trapping procedure and 8 to 10−day telemetry work were repeated on the grids comprising suites 2 and 3(Figure 3). The entire process was repeated during the winter when densities should have been at a minimum. Thus, during the period covered by this report, sampling occurred between July 16 – September 22 and between January 20−March 26. Telemetry work also occurred during “pre-baiting” days after the initial summer sampling session to determine which hares were still alive and immediately available to be sampled by the grid during the ensuing trapping period. Vegetation sampling was conducted in June and July 2008. I followed protocols established through previous snowshoe hare and lynx work in Colorado (Zahratka 2004, T. Shenk, Colorado Division of Wildlife, personal communication). Specifically, on each of the 12 live-trapping grids, I laid out 5 × 5 grids (3-m spacing) of vegetation sampling points centered on 15 of the 84 trap locations (Figure 4; 9 points were sampled on each of the ½-sized small lodgepole stands). At each of the 25 vegetation sampling points, I recorded canopy cover (present or absent) using a densitometer. I quantified downed coarse wood along the center transect of the 25-point grid following Brown (1974). From the center point (i.e., trap location) I measured 1) distance to the nearest woody stem 1.0−7.0 cm, 7.1−10.0 cm, and >10.0 cm in diameter at heights of 0.1 m and 1.0 m above the ground (to capture both summer and winter stem density; Barbour et al. 1999), 2) horizontal cover in 0.5-m increments above the ground up to 2 m (Nudds 1977), 3) basal area, and 4) slope. 33 �Data Analysis Density, Survival, and Population Growth.--I analyzed mark-recapture data in a robust design framework (Williams et al. 2002:523-554) treating summer and winter sampling occasions as primary periods, and the 5-day trapping sessions within each as secondary periods. As such, I assumed hare populations were demographically and geographically closed during the short 5-day mark-recapture sampling periods, but were open to immigration, emigration, births, and deaths between these occasions. I specified the Robust Design data type in Program MARK (White and Burnham 1999) and used the Huggins closed capture model (Huggins 1989, 1991) for secondary periods. I obtained estimates of apparent survival ( φˆ i )between each primary period. I followed Wilson and Anderson (1985) to calculate the effective area trapped and obtain a density estimate for each grid from each secondary period. Future density analyses will employ a new estimator that employs telemetry data to correct for bias (Ivan 2005). For this report, I used a relatively simple model where capture probability varied by stand type and season (i.e., winter and summer), while survival was allowed to vary by stand type, season, and time. RESULTS AND DISCUSSION During summer, density estimates followed hypotheses 1) and 2) above (Figure 5). Specifically, hare densities were clearly highest in small lodgepole stands and quite low in medium lodgepole stands. Spruce/fir was generally intermediate in density with the exception of the final summer. Telemetry data collected during this last sampling period suggests that many hares were present on spruce/fir sites, but were never caught. Therefore, I believe spruce/fir densities were much higher than actually measured during the final summer. While the relationship in density between stand types remained fairly constant throughout the study, the absolute density of hares dropped considerably from summer 2006 to summer 2007 and rebounded only slightly during summer 2008. It is unclear why this sharp decline occurred, although disease outbreak, natural population cycles, and response to increased predation due to lynx reintroduction are possibilities. Note that even the highest densities recorded here correspond to low estimates observed in other parts of hare range (Hodges 2000). Hare densities tend to equalize in lodgepole stands during winter (Figure 5). I submit that the interplay between food, cover, and snow depth provides a plausible explanation for this pattern. Medium lodgepole stands apparently provide very little forage/cover for hares during summer as the canopy in these stands is generally ≥1 meter off the ground. However, in winter, accumulated snow may make that canopy available again to hares. Conversely, small lodgepole stands provide abundant food and cover during summer, but accumulated snow during winter brings hares closer to the crowns of the young trees, which then provide less cover. Spruce/fir stands probably provide adequate access to both food and cover during both summer and winter due to their uneven-aged, multi-layered structure. Like the summer estimates, density during the second winter was much lower than during the first winter. Hare survival is quite high from summer to winter but very low from winter to summer (Figure 6). However, survival did not appear to differ between stand types or among years of this study. A deeper analysis of these data will occur over the next several months in which known-fate telemetry data will be combined with the current mark-recapture dataset. This combined analysis will bring significantly more information to bear on the process which should improve precision of estimates and may elucidate differences between stands or years that are not yet apparent. A much larger suite of models will be considered in that analysis. Model selection and model averaging (Burnham and Anderson 2002) will be used to more thoroughly assess survival of hares. Additionally, combining telemetry data with the current dataset will allow for another estimate of survival from winter 2009 to summer 2009. Hare recruitment and finite population growth rate will be estimated as derived parameters following the combined survival analysis. 34 �SUMMARY • • • • Snowshoe hare densities on my study sites appear to be relatively low compared to densities reported elsewhere. Densities during summer were highest in small lodgepole stands, followed by spruce/fir and medium lodgepole. During winter, densities equalize in lodgepole stands, possibly due to the interplay between snow depth and canopy height in small and medium lodgepole pine. Hare density declined considerably from winter to summer 2007 but has recovered somewhat since then. Summer to winter hare survival was consistently high but winter to summer survival is quite low. A more thorough analysis including known-fate survival data is forthcoming. This new analysis should improve precision of estimates and will add a sixth survival estimate to the current time series. ACKNOWLEDGMENTS Ken Wilson (CSU), Bill Romme (CSU), Paul Doherty (CSU), Dave Freddy (CDOW), Chad Bishop (CDOW), and Paul Lukacs (CDOW) provided helpful insight on the design of this study. We appreciate the invaluable logistical support provided by Mike Jackson (USFS), Art Haines (USFS), Jake Spritzer (USFS), Kerry Spetter (USFS), Margie Michaels (CDOW), Gabriele Engler (USGS), Dana Winkelman (USGS), Brandon Diamond (CDOW), Chris Parmeter (CDOW), Kathaleen Crane (CDOW), Lisa Wolfe (CDOW), and Laurie Baeten (CDOW). Jim Gammonley (CDOW), Dave Freddy (CDOW), Chad Bishop (CDOW), Jack Vayhinger (CDOW), Brandon Diamond (CDOW), and Brent Bibles (CDOW) assisted with trucks and equipment. The following hardy individuals collected the hard-won data presented in this report: Braden Burkholder, Matt Cuzzocreo, Brian Gerber, Belita Marine, Adam Behney, Pete Lundberg, Katie Yale, Britta Shielke, Cory VanStratt, Mike Watrobka, Meredith Goss, Sidra Blake, Keith Rutz, Rob Saltmarsh, Jennie Sinclair, Evan Wilson, Mat Levine, Matt Strauser, Greg Davidson, Leah Yandow, Renae Sattler, Caylen Cummins, DeVaughn Fraser, Mark Ratchford, Mike Petriello, Cynthia Soria, Roblyn Stitt, Sarah Ryan, Eric Newkirk, Kyle Heinrick, Matt Strauser, Doug Miles, and Cate Brown. Funding was provided by the Colorado Division of Wildlife. LITERATURE CITED Aubry, K. B., G. M. Koehler, and J. R. Squires. 2000. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA. Barbour, M. G., J. H. Burk, W. E. Pitts, F. S. Gilliam, and M. W. Schwartz. 1999. Terrestrial plant ecology, Addison Wesley Longman, Inc., Menlo Park, California, USA. Beauvais, G. P. 1997. Mammals in fragmented forests in the Rocky Mountains: community structure, habitat selection, and individual fitness. Dissertation, University of Wyoming, Laramie, Wyoming, USA. BROWN, J. K. 1974. Handbook for inventorying downed woody material. U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report INT-16. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. 35 �Bull, E. L., T. W. Heater, A. A. Clark, J. F. Shepherd, and A. K. Blumton. 2005. Influence of precommercial thinning on snowshoe hares. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, General Technical Report PNW-RP-562. Dolbeer, R. A. and W. R. Clark. 1975. Population ecology of snowshoe hares in the central Rocky Mountains. Journal of Wildlife Management 39:535-549. Dolbeer, R. A. 1972. Population dynamics of snowshoe hare in Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. Foresman, K. R. and D. E. Pearson. 1999. Activity patterns of American martens, Martes americana, snowshoe hares, Lepus americanus, and red squirrels, Tamiasciurus hudsonicus, in westcentral Montana. The Canadian Field-Naturalist 113:386-389. Griffin, P. C. 2004. Landscape ecology of snowshoe hares in Montana. Dissertation, University of Montana, Missoula, Montana, USA. Hodges, K. E. 2000. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163-206 in Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. Hodges, K. E., C. J. Krebs, D. S. Hik, C. I. Stefan, E. A. Gillis, and C. E. Doyle. 2001. Snowshoe hare demography. Pages 141-178 in Krebs, C. J., S. Boutin, and R. Boonstra, editors. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. Homyack, J. A., D. J. Harrison, and W. B. Krohn. 2003. Effects of precommercial thinning on select wildlife species in northern Maine, with special emphasis on snowshoe hare. Maine Cooperative Fish and Wildlife Research Unit, Orono, Maine, USA. Huggins, R. M. 1989. On the statistical analysis of capture-recapture experiments. Biometrika 76:133140. Huggins, R. M. 1991. Some practical aspects of a conditional likelihood approach to capture experiments. Biometrics 47:725-732. Ivan, J. S. 2005. Density, demography, and seasonal movements of snowshoe hares in Colorado. Program narrative study plan for mammals research, Colorado Division of Wildlife, Fort Collins, Colorado, USA. Keith, L. B. 1964. Daily activity pattern of snowshoe hares. Journal of Mammalogy 45:626-627. Koehler, G. M. 1990a. Snowshoe hare, Lepus americanus, use of forest successional stages and population changes during 1985-1989 in North-central Washington. Canadian Field-Naturalist 105:291-293. Koehler, G. M. 1990b. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. Litvaitis, J. A., J. A. Sherburne, and J. A. Bissonette. 1985. Influence of understory characteristics on snowshoe hare habitat use and density. Journal of Wildlife Management 49:866-873. Mech, L. D., K. L. Heezen, and D. B. Siniff. 1966. Onset and cessation of activity in cottontail rabbit and snowshoe hares in relation to sunset and sunrise. Animal Behaviour 14:410-413. Miller, M. A. 2005. Snowshoe hare habitat relationships in northwest Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Nudds, T. D. 1977. Quantifying the vegetative structure of wildlife cover. Wildlife Society Bulletin 5:113-117. Ruediger, B., J. Claar, S. Gniadek, B. Holt, Lewis Lyle, S. Mighton, B. Naney, G. Patton , T. Rinaldi, J. Trick, A. Vendehey, F. Wahl, N. Warren, D. Wenger, and A. Williamson. 2000. Canada lynx conservation assessment and strategy. U.S. Department of Agriculture, Forest Service, U.S. Department of Interior, Fish and Wildlife Service, Bureau of Land Management, National Park Service R1-00-53 U.S. Department of Agriculture, Forest Service, U.S. Department of Interior, Fish and Wildlife Service, Bureau of Land Management, National Park Service, Missoula, Montana, USA. 36 �Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires. 2000. The scientific basis for lynx conservation: qualified insights. Pages 443-454 in Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, and J. R. Squires, editors. Ecology and conservation of lynx in the United States. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA. Samuel, M. D. and M. R. Fuller. 1996. Wildlife radiotelemetry. Pages 370-418 in Bookhout, T. A., editors. Research and Management Techniques for Wildlife and Habitats. Allen Press, Inc., Lawrence, Kansas, USA. Shenk, T. M. 2005. General locations of lynx (Lynx canadensis) reintroduced to southwestern Colorado from February 4, 1999 through February 1, 2005. Colorado Division of Wildlife Colorado Division of Wildlife, Fort Collins, Colorado, USA. Sullivan, T. P. and D. S. Sullivan. 1988. Influence of stand thinning on snowshoe hare population dynamics and feeding damage in lodgepole pine forest. Journal of Applied Ecology 25:791-805. Van Horne, B. 1983. Density as a misleading indicator of habitat quality. Journal of Wildlife Management 47:893-901. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2002. Analysis and management of animal populations, Academic Press, San Diego, California, USA. Wilson, K. R. and D. R. Anderson. 1985. Evaluation of two density estimators of small mammal population size. Journal of Mammalogy 66:13-21. Wolfe, M. L., N. V. Debyle, C. S. Winchell, and T. R. McCabe. 1982. Snowshoe hare cover relationships in northern Utah. Journal of Wildlife Management 46:662-670. Wolff, J. O. 1980. The role of habitat patchiness in the population dynamics of snowshoe hares. Ecological Monographs 50:111-130. Zahratka, J. L. 2004. The population and habitat ecology of snowshoe hares (Lepus americanus) in the southern Rocky Mountains. Thesis, The University of Wyoming, Laramie, Wyoming, USA. Prepared by _________________________________________________ Jacob S. Ivan, Graduate Student, Colorado State University 37 �Figure 1. Purported high quality snowshoe hare habitat in Colorado. From left to right: small lodgepole pine, medium lodgepole pine, and large Engelmann spruce/subalpine fir. Figure 2. Study area near Taylor Park and Pitkin, Colorado including medium lodgepole (squares), small lodgepole (circles), and spruce/fir (triangles) stands selected for mark-recapture sampling. 38 �Jul Aug Sep 1 2 3 4 2 3 4 5 6 7 8 1 Jan 5 6 7 8 9 10 11 9 10 11 12 13 14 15 12 13 14 15 16 17 18 16 17 18 19 20 21 22 19 20 21 22 23 24 25 23 24 25 26 27 28 29 26 27 28 29 30 31 1 30 31 1 2 3 4 5 2 3 4 5 6 7 8 6 7 8 9 10 11 12 9 10 11 12 13 14 15 13 14 15 16 17 18 19 16 17 18 19 20 21 22 20 21 22 23 24 25 26 23 24 25 26 27 28 1 27 28 29 30 31 1 2 2 3 4 5 6 7 8 3 4 5 6 7 8 9 9 10 11 12 13 14 15 10 11 12 13 14 15 16 16 17 18 19 20 21 22 17 18 19 20 21 22 23 23 24 25 26 27 28 29 24 25 26 27 28 29 30 30 31 Feb Mar Figure 3. Approximate annual data collection schedule for trapping () and telemetry (). Dates and weeks changed depending on calendar year and pay schedule. During telemetry work, the 6-person crew was divided into 2 teams, only one of which worked at any given time. Monthly locations on radio-collared hares were also collected in the interim between the intensive sampling periods indicated here. Figure 4. 15 trap locations (•) on 7 × 12 trapping grid where vegetation was sampled by measuring stem density, horizontal cover, downed woody material, and basal area. Additionally, the 25-point grid superimposed on each of the 15 trap locations (inset) was used to quantify canopy cover). 39 �Figure 5. Snowshoe hare density and 95% confidence intervals in 3 types of stands in central Colorado as determined by ½ mean maximum distance moved, summer 2006 through winter 2009. Figure 6. Snowshoe hare survival and 95% confidence intervals between summer and winter sampling seasons in 3 types of stands in central Colorado as determined by mark-recapture, 2006-2009. 40 �APPENDIX II PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2009 – 10 State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 3 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Lynx Conservation Estimating Potential Changes in Distribution of Canada Lynx in Colorado: A Pilot Study Plan to Estimate Lynx Detection Probabilities ESTIMATING POTENTIAL CHANGES IN DISTRIBUTION OF CANADA LYNX IN COLORADO; A PILOT STUDY PLAN TO ESTIMATE LYNX DETECTION PROBABILITIES Principal Investigator Tanya M. Shenk, Wildlife Researcher, Mammals Research Cooperators Rick H. Kahn, Terrestrial Management Coordinator, CDOW Paul M. Lukacs, Biometrician, CDOW Grant J. Merrill, Research Associate, CSU Cooperative Research Unit Robert D. Dickman, CDOW Mike Miller, Acting Mammals Research Leader, CDOW STUDY PLAN APPROVAL Prepared by: Date: Submitted by; Date: Reviewed by: Date: Date: Date: Biometrician Review Date: Approved by: Date: Mammals Research Leader 41 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2009-10 ESTIMATING THE EXTENT, STABILITY AND POTENTIAL DISTRIBUTION OF CANADA LYNX (LYNX CANADENSIS) IN COLORADO: A PILOT STUDY TO ESTIMATE LYNX DETECTION PROBABILITIES A Research Proposal Submitted By Tanya M. Shenk, Wildlife Researcher, Mammals Research A. Background: The Canada lynx (Lynx canadensis) occurs throughout the boreal forests of northern North America. While Canada and Alaska support healthy populations of the species, the lynx is currently listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.; U. S. Fish and Wildlife Service 2000) in the coterminous United States. Colorado represents the southern-most historical distribution of naturally occurring lynx, where the species occupied the higher elevation, montane forests in the state (U. S. Fish and Wildlife Service 2000). Thus, Colorado is included in the federal listing as lynx habitat. Lynx were extirpated or reduced to a few animals in Colorado, however, by the late 1970’s (U. S. Fish and Wildlife Service 2000), most likely due to multiple humanassociated factors, including predator control efforts such as poisoning and trapping (Meaney 2002). Given the isolation of and distance from Colorado to the nearest northern populations of lynx, the Colorado Division of Wildlife (CDOW) considered reintroduction as the only option to attempt to reestablish the species in the state. Therefore, a reintroduction effort was begun in 1997, with the first lynx released in Colorado in 1999. To date, 218 wild lynx were captured in Alaska or Canada and released in southwestern Colorado. The goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of lynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing the success of the reintroduction effort. Seven critical criteria were identified that must be met before concluding a viable population had been established: 1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, 2) long-term survival of lynx in Colorado, 3) site fidelity by lynx to areas supporting good habitat and in densities sufficient to breed, 4) reintroduced lynx must breed, 5) breeding must lead to production of surviving kittens, 6) lynx born in Colorado must reach breeding age and reproduce successfully, and 7) recruitment must equal to or be greater than mortality over an extended (~10 year) period of time (Shenk 2006). The fundamental approach taken to evaluate the status of each of these criteria was to PIT-tag and place telemetry collars on every lynx released and as many Colorado-born kittens surviving to adulthood as possible, followed by intensive monitoring of these animals through satellite, aerial and groundtracking. All establishment criteria, except (7) have been achieved. Lynx populations in Canada and Alaska have long been known to cycle in response to the 10-year snowshoe hare (Lepus americana) cycle (Elton and Nicholson 1942). Northern populations of lynx respond to snowshoe hare lows first through a decline in reproduction followed by an increase in adult mortality; when snowshoe hare populations increase, lynx respond with increased survival and reproduction (O’Donoghue et al. 2001). Therefore, annual survival and reproduction are highly variable but must be sufficient, overall, to result in long-term persistence of the population. It is not known if snowshoe hare populations in Colorado cycle and if so, where in the approximate 10-year cycle we are currently. Given this uncertainty, documenting persistence of lynx in Colorado for a period of at least 10- 42 �15 years would provide support that a viable population of lynx can be sustained in Colorado even in the event snowshoe hares do cycle in the state. Therefore, to document viability of the lynx population in Colorado, some form of long-term monitoring must be used to determine whether recruitment exceeds mortality for a period of time long enough to encompass a possible snowshoe hare cycle, and thus, determine the reintroduction a success. A challenge facing CDOW is how efforts should be allocated between focusing on monitoring the persistence of those lynx that have established within the core release area (Shenk 2007, Shenk 2008) and those lynx that may be pioneering and expanding into other portions of the state. Reproduction and known recruitment have been observed to be sporadic in the core area. To continue to document lynx reproduction through den site visits and to document survival of those kittens through tracking the adult females in winter looking for accompanying kittens requires a continued trapping effort to capture and radio-collar adult females. Lynx trapping is typically a time consuming and expensive operation as the lynx are territorial with large home ranges that may be entirely located within or largely comprised of inaccessible areas (e.g., wilderness areas). Alternatively, exploring occupancy modeling using noninvasive techniques may be a feasible alternative for ascertaining trends in population status and forming a basis for a large scale area monitoring program. Monitoring of individuals through telemetry continues in an effort to document the viability of the reintroduced lynx population. However, as time since release increases, battery failure of telemetry collars also increases resulting in fewer released animals having working collars. In addition, few Colorado-born lynx have been captured and fitted with telemetry collars. Although trapping efforts have been conducted in earnest since 2003 to capture and fit animals with working telemetry collars, we have not been able to collar a sufficient number of animals throughout the state to document the status and trends of lynx distribution and demography throughout Colorado from these collared animals. The extent of lynx dispersal and current distribution beyond the Core Research Area and the difficulty of trapping lynx in all areas they inhabit, particularly large tracts of wilderness, requires redesigning our sampling and monitoring efforts to provide valid estimates of lynx distribution. We propose that monitoring lynx distribution would consist of 3 potential primary objectives to document the extent, stability and potential distribution of lynx (at the species and individual level) in Colorado. To estimate patterns in lynx distribution in Colorado a monitoring program could be developed that will: 1) annually estimate the spatial distribution of lynx in the core area and assess changes in lynx distribution over time; 2) detect colonization or expansion of lynx into other portions of the state, and 3) determine whether distribution or persistence are associated with habitat features, measured at the landscape-scale (stand age or composition). A pilot study will be conducted first to establish the most valid, efficient method to estimate the distribution and persistence of lynx. B. Need The primary goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of Canada lynx in Colorado. The approach taken to reach this goal was to initially establish a lynx population within a core reintroduction area in southwestern Colorado. From this core reintroduction area, lynx could disperse on their own throughout the suitable habitat in the state, or additional reintroductions north of the core area could be conducted. The current lynx population in Colorado is comprised of surviving reintroduced adults, lynx born in Colorado from the reintroduced animals and possibly some naturally occurring lynx. Research and monitoring efforts over the last 9 years, since the first lynx were released, have focused primarily on monitoring reintroduced animals through VHF and satellite telemetry and estimating demographic parameters of these animals (e.g., Devineau et al. 2009). However, as more of these animals become unavailable for monitoring due to failed telemetry collars, death or movement out of the Core 43 �Research Area, it becomes more difficult to accurately evaluate the status of the entire lynx population in Colorado, including the Core Research Area. A dual monitoring approach will provide a comprehensive, feasible and valid estimation of the demography of the lynx population throughout the state. The first approach would continue to estimate reproduction within the Core Research Area through the use of telemetry. The second approach would obtain information on the status and trend of the distribution of lynx throughout the high elevation, montane areas of Colorado. Below we first outline the objectives and approach for the statewide distribution study and then propose a pilot study to establish the most valid, efficient methods to estimate the statewide distribution and persistence of lynx. A minimally-invasive monitoring program can be developed to estimate the extent, stability and potential distribution of lynx throughout Colorado. The primary objectives of the monitoring program will be to document the current distribution of lynx throughout Colorado, the stability, growth or shrinkage of this distribution over time, and to identify potential areas lynx may occupy in the future. The proposed goal would be to annually monitor lynx into the long-term future, with regular analyses of change (e.g., every 5 years). The fundamental structure of such a monitoring program will consist of: 1. 2. 3. 4. Creating a sampling frame of all potential lynx home range sized primary sampling units within Colorado. Annually estimating winter site occupancy and persistence within this sampling frame. Measuring key habitat features that have been documented to be important for both snowshoe hare and lynx at the landscape-scale within annually sampled sites. Predicting potential distribution of lynx throughout Colorado based on these habitat relationships. In the past, biologists referred to presence/absence as present/not detected, because absence cannot be absolutely determined. This term, however, confuses the status of being present or not present with the activity of either detecting or not detecting an animal. This monitoring program adopts the term presence/absence with the argument that although absence cannot be determined, it can be estimated statistically using a known or estimated detection probability. The indicator used to determine the distribution of occurrence of lynx is P, the proportion of primary sampling units (PSU’s) (Levy and Lemeshow 1999) with lynx presence. A PSU is a square sampling unit of 75km2, the approximate mean size of a lynx winter home range as estimated by a 90% kernel utilization distribution (Shenk 2007). For the statewide monitoring program, the sampling frame would consist of a grid of PSU’s laid over all areas of Colorado above 2591 meters (8500 feet). We would then estimate P from a random sample of PSU’s, using a sample size that is sufficient for attaining an estimate that is within 10% of the actual frequency 90% of the time (see Table 6.1, pg. 168 in MacKenzie et al. 2006). In order to design the most efficient statewide monitoring program, however, we will first evaluate the detection probabilities and efficacy of 3 methods of detection. These include snow-tracking, hair snares and camera surveillance. All of these methods can be conducted with minimal (camera surveillance or collection of hair) or non-invasive approaches (collection of scat samples) to individual animals. Identification of species will allow us to determine the presence of lynx in a PSU; identifying individual lynx within PSU’s will allow for monitoring individual movement patterns across PSU’s, reproduction, social structure and possibly apparent survival rates. Such non-invasive techniques are widely desirable because they are considered to have a minimal impact on animals and are inexpensive relative to other methods. Methodologies for identifying the species and individual lynx from blood and scat samples has been completed by the USFS Conservation Genetics Laboratory in Missoula, Montana. Thus, development costs have already been expended (by other agencies) and we need only cover the 44 �costs of genetic sample processing and interpretation of results. In order to begin genetic tracking of individual lynx a genetic library should be created from all lynx released in Colorado as part of the Colorado lynx reintroduction program, all documented kittens and lynx of unknown origin captured in Colorado. These samples have already been collected and are currently archived at the CDOW. This genetic library would be used to help determine paternity of Colorado-born kittens for future, detailed reproduction studies, document the dispersal of individuals throughout Colorado and also be available for research conducted on continent-wide studies of Canada lynx (e.g., Schwartz et al. 2002, Schwartz et al. 2003). Collecting scat samples during the pilot study will allow a test of these methodologies for the larger study as well as providing an opportunity to establish the protocols with the conservation genetics lab for collection, transport and analysis of the samples. This pilot study will provide necessary information to (1) identify the most efficient method of detecting lynx in a PSU and (2) provide an estimate of detection probability within a PSU. This detection probability will then be used to design the most efficient strategy to meet the objectives of larger-scale monitoring programs to detect changes in lynx persistence and distribution as a foundation for assessing whether lynx have become established and will persist in Colorado. First, a minimally invasive monitoring program will be designed and implemented within the Core Research Area to describe lynx distribution and distribution trends in this area. A statewide plan could then be implemented to describe lynx distribution and distribution trends throughout Colorado. This monitoring protocol could result in the development of a standardized methodology that might be used by multiple entities to monitor the status of lynx throughout their range in North America. This monitoring design will not provide a means of estimating total population size in the state because detection of a lynx may represent a single territorial animal, a breeding pair or a family unit. To obtain a statewide lynx abundance estimate, further efforts beyond this sampling design would be needed to establish the actual or estimated number of lynx in a PSU. Furthermore, this monitoring program is not designed to provide information on reproductive success or estimate survival. C. Objectives: The primary objectives of this pilot study are to: 1. Provide information needed to estimate the detection probability (p) of 3 different, minimally-invasive methods to detect lynx in a PSU in winter, where lynx are known to occur but in extremely low densities (approximately 1 per 75 km2). 2. Evaluate and compare the efficacy of the 3 methods of lynx detection in winter within a PSU. 3. Develop a standardized, valid methodology for describing various landscape-scale habitat features, including those important to snowshoe hare, within a PSU. D. Expected Results or Benefits: The methodologies developed during this pilot study will be used to develop a valid, non-invasive or minimally invasive inventory and monitoring program to estimate the distribution of Canada lynx in Colorado. The monitoring program will provide information on the annual winter distribution, extent and habitat relationships of these parameters as well as their long-term trend which will be evaluated every 5 years. The protocols developed will be made available to any other agencies or entities that want to monitor lynx. The proposed methodology to estimate and monitor trends in lynx distribution throughout Colorado is designed to make use of technologies (e.g., genetic identification) reliant only on noninvasive or minimally invasive techniques. Such non-invasive techniques are widely desirable because they require minimal impact to the animals and because of their cost efficiencies. 45 �E. Approach The primary objective of the pilot study is to evaluate the efficacy of the proposed sampling techniques for detecting lynx presence. However, the pilot study will also include qualitative evaluation of all design methods that will be employed in a future, larger research area and statewide monitoring efforts, (i.e., the complete sampling frame). Sampling Frame and Primary Sampling Unit Selection The sampling frame will consist of all forested areas in Colorado >2591 m (8500 ft) in elevation. The sampling frame will be randomly overlayed with a contiguous grid of 75 km2 squares. The size of the square reflects a mean annual home range size of a reproducing lynx in Colorado (Shenk 2007) and similar to home range estimates obtained for lynx in Montana (Squires and Laurion 1999). If a grid square is >50% forested it will be identified as a PSU. We will assume the lowest detection probabilities for lynx would occur in a PSU occupied by only 1 lynx. Given that we want to estimate lynx detection probabilities under the worst case scenario, we will eliminate all PSU’s where we know, through VHF or satellite-tracking, there is more than one lynx occupying the area. We will then select 6 PSU’s where we know at least 1 but not likely more than 1 lynx occupies the area. The assumptions that must be met in estimating occupancy are 1) surveyed sites can be occupied by the species of interest throughout the duration of the study, with no sites becoming occupied or unoccupied during the survey period (i.e., the system is closed), 2) species are not falsely detected, but can remain undetected if present, and 3) species detection at a site is assumed to be independent of species detection at other sites (MacKenzie et al. 2006). For this pilot study, there will be 3 different methods of detection (snow-tracking, hair snares and camera surveillance). Snow-tracking and camera surveillance will be evaluated at 2 different levels of effort; hair snares will be evaluated at 3 levels of effort resulting in 7 total detection approaches. In order to meet the assumptions for estimating occupancy and assuming the different detection approaches don’t influence each other, each of the 6 PSU’s will be assigned all detection approaches (except for the higher level of hair-snaring) for 3 weeks, allowing for completing surveys of 2 PSU’s per month. The increased hair snare effort will be conducted on a PSU the month following the initial survey effort (see below). Thus, by the end of four months each PSU will have had each detection approach applied to it. This will result in 6 spatial replications of each of 3 detection approaches applied to a PSU for 3 weeks. Maximum levels of effort will be applied to each PSU and then the data sub-sampled to evaluate lower levels of effort. Field Methods Temporal aspects of the sampling design In order to verify the detection methods being evaluated in this pilot study are effective at detecting lynx when they are present, we need to conduct the study while we have active radio collars on lynx. Currently, we are continuing to monitor and re-collar lynx within the Core Research Area for data on the demography and movement patterns of the reintroduced lynx. Thus, completing this pilot study at the same time that active monitoring is being conducted in the research area eliminates the need for future radio-collaring efforts to conduct this pilot study. All data collection will be conducted from January 1-March 31 (Table 1). This is within the time period (October–April) when lynx typically maintain fidelity to a winter home range and when breeding occurs, the period of interest for document long-term persistence of lynx. 46 �Table 1. Data collection and crew work schedule for the six PSU’s to be sampled. PSU Month Week Crew Activity 1 January 1 I Set-up detection routes and 5 detection stations with hair snares and cameras; Snow-track (2 10-hour days) 2 I Snow-track (4 10-hour days) 3 I Snow-track (4 10-hour days)4 I Snow-track (2 10-hour days); Retrieve cameras and hair snares at the 5 detection stations, place 20 hair snares along the detection route; Travel to next PSU 2 January 1 II Set-up detection routes and stations with hair snares and cameras; Snow-track (2 10-hour days) 2 II Snow-track (4 10-hour days) 3 II Snow-track (4 10-hour days)4 II Snow-track (2 10-hour days); Retrieve cameras and hair snares at the 5 detection stations, place 20 hair snares along the detection route; Travel to next PSU 3 February 1 I Set-up detection routes and stations with hair snares and cameras; Snow-track (2 10-hour days) 2 I Snow-track (4 10-hour days) 3 I Snow-track (4 10-hour days)4 I Snow-track (2 10-hour days); Retrieve cameras and hair snares at the 5 detection stations, place 20 hair snares along the detection route; Travel to next PSU 4 February 1 II Set-up detection routes and stations with hair snares and cameras; Snow-track (2 10-hour days) 2 II Snow-track (4 10-hour days) 3 II Snow-track (4 10-hour days)4 II Snow-track (2 10-hour days); Retrieve cameras and hair snares at the 5 detection stations, place 20 hair snares along the detection route; Travel to next PSU 5 March 1 I Set-up detection routes and stations with hair snares and cameras; Snow-track (2 10-hour days) 2 I Snow-track (4 10-hour days) 3 I Snow-track (4 10-hour days)4 I Snow-track (2 10-hour days); Retrieve cameras and hair snares at the 5 detection stations, place 20 hair snares along the detection route; Travel to next PSU 6 March 1 II Set-up detection routes and stations with hair snares and cameras; Snow-track (2 10-hour days) 2 II Snow-track (4 10-hour days) 3 II Snow-track (4 10-hour days)4 II Snow-track (2 10-hour days); Retrieve cameras and hair snares at the 5 detection stations, place 20 hair snares along the detection route; Travel to next PSU Lynx Detection Data Collection Three methods will be evaluated to determine which is most efficient in detecting the presence of lynx. These methods include 1) documenting the presence of lynx tracks in the snow coupled with a DNA sample collection (hair or scat found through snow-tracking), 2) a photograph of a lynx captured by 47 �a surveillance camera, or 3) documenting the presence of lynx from a hair DNA sample collected on a hair snag at a scent and visual lure station. All methods will be applied to the same stations within a PSU at the same time. Each method will be implemented in the areas within the selected PSU that a lynx would most likely use. Based on lynx habitat use in Colorado (Shenk 2005), this will include areas of mature Engelmann spruce-subalpine fir forest stands with 42-65% canopy cover and 15-20% conifer understory cover, mean slopes of 16° and elevations above 2591 m. In addition, selection of specific detection stations will be based on natural travel routes or the presence of lynx sign (i.e., tracks or scat). Chances of detecting lynx at these locations will be further enhanced by placing scent and visual lures at these sites. Other feline species may be attracted to these same lures, however, the probability will be low as the study will be conducted in winter and the deep snows at these elevations should preclude species such as mountain lion (Puma concolor) and bobcat (Lynx rufus) from using these areas. Different levels of sampling intensity will be evaluated for each method to determine the most efficient sampling design. Establishing Detection Stations & Routes. – To eliminate bias in site selection of detection stations and routes, any known lynx locations in the selected PSU’s will not be made available to the field technicians who will be establishing the detection routes, detection stations and collecting the detection data. Field personnel will be provided information to select routes that are both the most feasible and likely areas to detect lynx within a PSU (see above). Detection stations will be set up in areas along those selected routes in areas of good lynx habitat. Commercial scent lures and visual lures (e.g., CD’s, waterfowl wings) will be used at each detection station to enhance the probability of drawing a lynx into the station. To increase the probability of lynx using the hair snares, the hair snares will be placed on landscape features at the detection station known to be used as scent posts by lynx such as tree stumps, small trees and broken logs protruding from the snow at approximate head height of a lynx (Schmidt and Kowalczyk 2006). Snow-Tracking. –Searches for tracks will be attempted by hiking, driving or snowmobiling detection station routes in the PSU once enough snow has accumulated. Due to the inaccessibility of wilderness and roadless areas after significant snowfall, surveys will be conducted in these areas first, while snow accumulations are great enough to detect tracks but not so great as to preclude human access to the area. Once tracks are observed, personnel will follow the tracks until either lynx hair or scat are found and collected or the distance tracks are followed exceeds 1 km. All hair found in day beds or a single scat will constitute a sample. Because lynx are a federally listed species, which can result in regulatory protection, we will eliminate doubt about the presence of lynx by submitting hair or scat sampled to a conservation genetics lab to confirm species identification (see McKelvey et al. 2006). All hair and fecal samples will be submitted to a conservation genetics lab for identification to species and individual, if possible. The distance a track is followed will be limited to 1 km to increase efficiency in lynx detection within the PSU (i.e., it will be assumed it is quicker to find a new lynx track to follow to locate hair or scat than to pursue a single track for more than 1 km; see McKelvey et al. 2006). Two levels of search effort for lynx tracks will be implemented within a PSU. The first tracking intensity will be 4 consecutive tracking days (although there may be days of no tracking within this period – e.g., days off, cancellation of tracking effort due to weather etc.), the second will be 8 consecutive days of tracking. All PSU’s will be snow-tracked for 12 days (3 week field effort, see Table 1). This will provide 3 replicates of a 4-day tracking session and 2 replicates of an 8-day tracking session (replicating one of the 4-day tracking sessions). Camera Traps. – Digital infrared surveillance cameras (RECONYX RapidFireTM Professional PC85) will be placed at 5 randomly selected detection stations among those that appear the most likely places where lynx would encounter them within the PSU, as defined above. Cameras will be encased in heavy duty 16 gauge steel security enclosure, attached to a tree with a Master Lock TM PythonTM cable lock and powered by 3-volt C-cell lithium batteries. 48 �We will evaluate detection probabilities for 2 levels of camera surveillance, placing either 2 cameras within the grid or 5 cameras. Five cameras will be placed in all PSU’s, a random subset of 2 cameras from these 5 will be selected to evaluate the efficacy of the lesser effort. Cameras will run continuously for the 3.5 week period. We can evaluate the most efficient number of days required to detect a lynx and the interaction between number of cameras and length of time cameras are active. Hair-Snares. - Barbed wire and carpet hair traps, scented with commercial lynx lures as described by McDaniel et al. (2000) will be placed at each of the detection stations within the PSU in areas where lynx would most likely encounter them (see above). A sample will be defined as all hairs from a single hair snare. Each hair sample will be placed in a uniquely numbered paper envelop, and a flame passed under the barbs to remove any genetic material so that the hair snare can be used again without contaminating future samples. All hair samples will be submitted to a conservation genetics lab for identification to species. Hair snares have been shown to be highly reliable for lynx identification to species (Schwartz et al. 2002) but not for individual lynx identification (Lukacs 2005). We will evaluate detection probabilities of lynx for 3 sample intensity levels of hair snares. First, hair snares will be set up within the PSU at each of the 5 detection stations. A the end of the 3.5 week monitoring session of a PSU, 20 hair snares, at least 100 meters apart (McDaniel et al. 2000) will be placed along the detection route (assuming detection routes will be approximately 25 km long) and collected approximately 1 month later (by the crew leader). Both the detection probability for the 20 hair snares and a random subset of 10 hair snares from these 20 will be selected to evaluate the efficacy of the lesser effort. This larger effort of 20 hair snares will be completed in a PSU after the monitoring conducted by snow-tracking and camera traps as the presence of additional scent stations may affect the use of the 5 camera detection stations. Data Analysis We will estimate the probability of detecting a lynx (p) on each of the PSU’s for each of the detection methods and level of effort for each of those methods. Aerial or satellite telemetry will be used to confirm the presence of at least one lynx in each of the six sampled PSU’s. An evaluation of each of the detection methods will be completed to determine the most reliable, efficient (e.g., cost of equipment, labor) and feasible method of detecting a lynx on a PSU when at least one lynx is present. Project Schedule Completed by Dec. 2009 1. Complete sampling frame and selection of primary sampling units. 2. Purchase and test equipment. Jan.–Mar. 2010 1. Set up detection stations. 2. Conduct lynx snow-tracking surveys. 3. Conduct lynx hair snare sampling. 4. Conduct camera surveillance surveys. 5. Process and submit all genetic samples collected during surveys to a genetic conservation lab (e.g., USDAFS Conservation Genetics Lab in Missoula, Montana, USGS Conservation Genetics Lab in Denver, Colorado). Apr.–May 2010 1. Data entry, analyses and complete report. 49 �Personnel: Project Leader: Tanya Shenk, Wildlife Researcher, CDOW Responsibilities: Design study, work with research associate to implement and complete field work and data entry, complete analysis, write report. Crew Leader: Responsibilities: Assist is study design and selection of PSU’s, supervise field technician, complete all data entry, and perform other duties as needed associated with the post-release monitoring program and the reproduction study. Field Technicians Responsibilities. To establish detection routes, detection stations, place hair snags, cameras and conduct all snow-tracking. Data Analysis: Tanya Shenk, Wildlife Researcher, CDOW Paul Lukacs, Biometrician CDOW Gary White, Professor Emeritus, CSU Paul Doherty, Associate Professor, CSU Estimated Annual Budget: January 2009 – April 2010 Salary (Tech III, Jan 2009 –Apr 2010) Salary (4 Field Technicians, Tech II Jan 2010 – Mar 2010) Travel, housing Misc. Supplies/Operating Equipment Repair, maintenance (snowmobiles) Detection cameras (11 @$1,000 each) Processing of genetic samples collected during monitoring Vehicles (3) $ 15,000 $ 36,100 $ 5,000 $ 4,000 $ 5000 $ 11,000 $ 4,000 $ 6,000 TOTAL $86,100 G. Location: Southwestern and central Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce-subalpine fir is the most widely distributed coniferous forest type at elevations most typically used by lynx (2591-3353 m). The Core Reintroduction Research Area is defined as areas >2591 m in elevation within the area bounded by the New Mexico state line to the south, Taylor Mesa to the west and Monarch Pass on the north and east (Figure 1). Project headquarters will at the Fort Collins CDOW Research Center. H. Literature Cited: Aubry, K. B., G. M. Koehler, J. R. Squires. 1999. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. 50 �Byrne, G. 1998. Core area release site selection and considerations for a Canada lynx reintroduction in Colorado. Report for the Colorado Division of Wildlife. Curtis, J. T. 1959. The vegetation of Wisconsin. University of Wisconsin Pres, Madison. Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2008. Estimating mortality for a widely dispersing reintroduced carnivore, the Canada lynx (Lynx canadensis). Ecology (in review). Elton, C. and M. Nicholson 1942. The ten-year cycle in numbers of lynx in Canada. Journal of Animal Ecology 11: 215-244. Hodges, K. E. 1999. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. Koehler, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in north central Washington. Canadian Journal of Zoology 68:845-851. Kolbe, J. A., J. R. Squires, T. W. Parker. 2003. An effective box trap for capturing lynx. Journal of Wildlife Management 31:980-985. Laymon, S. A. 1988. The ecology of the spotted owl in the central Sierra Nevada, California. PhD Dissertation, University of California, Berkeley, California. Lukacs, P. M. 2005. Statistical aspects of using genetic markers for individual identification in capturerecapture studies. PhD Dissertation, Colorado State University, Fort Collins, Colorado. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Elsevier Academic Press. Oxford, UK. Major, A. R. 1989. Lynx, Lynx canadensis canadensis (Kerr) predation patterns and habitat use in the Yukon Territory, Canada. M. S. Thesis, State University of New York, Syracuse. McDaniel, G. W., K. S. McKelvey, J. R. Squires. and L. F. Ruggiero. 2000. Efficacy of lures and hair snares to detect lynx. Wildlife Society Bulletin 28:119-123. McKelvey, K. S., J. von Kienast; K.B. Aubry; G. M. Koehler; B. T. Maletzke; J. R. Squires; E. L. Lindquist; S. Loch; M. K. Schwartz. 2006. DNA analysis of hair and scat collected along snow tracks to document the presence of Canada lynx. Wildlife Society Bulletin 34: 451-455. Meaney C. 2002. A review of Canada lynx (Lynx canadensis) abundance records from Colorado in the first quarter of the 20Th century. Colorado Department of Transportation Report. Mowat, G., K. G. Poole, and M. O’Donoghue. 1999. Ecology of lynx in northern Canada and Alaska. Pages 265-306 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University of Colorado Press, Boulder, Colorado. O’Donoghue, M, S. Boutin, D. L. Murray, C. J. Krebs, E. J. Hofer, U. Breitenmoser, C. BreitenmoserWuersten, G. Zuleta, C. , C. Doyle, and V. O. Nams. 2001. Mammalian predators: Coyotes and lynx. in Ecosystem Dynamics of the Boreal Forest: The Kluane Project. eds. C. J. Krebs, S. Boutin and R. Boonstra. Oxford University Press, Inc. New York, New York. Poole, K. G., G. Mowat, and B. G. Slough. 1993. Chemical immobilization of lynx. Wildlife Society Bulletin 21:136-140. Schmidt, K. and R. Kowalcyzk. 2006. Using scent-marking stations to collect hair samples to monitor Eurasian lynx populations. Wildlife Society Bulletin 34: 462-466. Schwartz, M. K. , L. S. Mills, K. S. McKelvey, L. F. Ruggiero, AND F. W. Allendorf. 2002. DNA reveals high dispersal synchronizing the population dynamics of Canada lynx. Nature 415:520522. Schwartz, M. K., L. S. Mills, Y. Ortega, L. F. Ruggiero, and F. W. Allendorf. 2003. Landscape location affects genetic variation of Canada lynx (Lynx canadensis). Molecular Ecology 12:1807-1816. 51 �Shenk, T. M. 1999. Program narrative Study Plan: Post-release monitoring of reintroduced lynx (Lynx canadensis) to Colorado. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2001. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2006. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado __________. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado Silverman, B.W. 1986. Density Estimation for Statistics and Data Analysis. Chapman and Hall. New York, New York, USA. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. White, G.C. and K. P. Burnham. 1999. Program MARK: Survival estimation from populations of marked animals. Bird Study 46 Supplement, 120-138. Wild, M. A. 1999. Lynx veterinary services and diagnostics. Job Progress Report for the Colorado Division of Wildlife. Fort Collins, Colorado. 52 �Figure 3. Study area depicting the Core Research Area, Lynx-established Core Area and relative lynx use (red is high intensity use, yellow is low intensity use). 53 �54 �Colorado Division of Wildlife July 2008 − June 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2008 − June 30, 2009 Authors: C. J. Bishop, D. P. Walsh, M. W. Alldredge, E. J. Bergman, and C. R. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We initiated an effort to design, produce, and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. A passive collaring device would allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. Such a technique would significantly reduce stress that is typically associated with capture and handling and would eliminate capture-related mortality. We wrote a study plan (Appendix I) and collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University in an attempt to produce a prototype device. We evaluated device components in phases throughout the year using captive deer at the Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado. The students did a good job with the mechanical aspects of the design when developing a prototype, but the electrical controls to run the device were too advanced for them. Although the prototype lacked several key components, we were able to evaluate various aspects of the device to guide further development. We tested the device at FWRF and then conducted a field evaluation with free-ranging deer during April and May, 2009. The latter provided extensive information on how deer interacted with the device. Most importantly, we could have collared free-ranging deer without handling them had the device been fully automated. To produce a fully functional device, we are pursuing a contract with a professional engineering firm capable of meeting our detailed device specifications. 55 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, DANIEL P. WALSH, MATHEW W. ALLDREDGE, ERIC J. BERGMAN, AND CHUCK R. ANDERSON P. N. OBJECTIVE To develop and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. SEGMENT OBJECTIVES 1. Write a study plan to guide development and evaluation of the automated collaring device. 2. Produce a prototype device and conduct a preliminary field evaluation with mule deer. INTRODUCTION The Colorado Division of Wildlife (CDOW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240 deer fawns are captured annually to monitor survival among 4 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CDOW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., $3,000−5,000 ea.) would reduce CDOW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. 56 �A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CDOW’s operating expenses and improve animal welfare. STUDY AREA We conducted all evaluations with captive deer at the FWRF in Fort Collins, Colorado. We conducted limited evaluations with free-ranging deer near Fort Collins in north-central Colorado. We plan to conduct extensive field evaluations in the Piceance Basin in northwest Colorado once a fullyfunctioning device is produced. METHODS We wrote a study plan and identified detailed device specifications to guide development of the automated collaring device (Appendix I). We approached Colorado State University’s Mechanical Engineering Department to discuss their interest in helping design such a device. In result, the collaring device became a senior design project for 6 CSU engineering students during the 2008-09 school year. We met with the students weekly and provided them a materials budget of $10,000 to produce a prototype device. We conducted staged evaluations of device components during the year by working with captive deer at FWRF. We also conducted limited evaluations with free-ranging deer near the end of the year. Field evaluations focused primarily on how deer utilized and interacted with the device to guide subsequent design and development decisions. We documented utilization and interactions using direct observation and motion-sensor digital cameras. We relied exclusively on digital cameras when we were not on-site during an evaluation. Automation of the collaring device was disabled any time we were not present to prevent any potential harm to deer. RESULTS AND DISCUSSION We completed the study plan and detailed device specifications (Appendix I). The student engineers did a good job with the mechanical aspects of the design, but the electrical controls to run the device were too advanced for them. The students therefore approached a private electrical engineering design firm located in Fort Collins – Dynamic Group Circuit Design (DGCD). DGCD donated many hours to the project to help the students produce a prototype. By spring 2009, we were interacting directly with DGCD in an attempt to make the prototype device function. Although the device lacked several key components, a number of aspects were ready for evaluation. We therefore tested the device at FWRF and then conducted a field evaluation with free-ranging deer during April and May, 2009. The latter provided extensive information on how deer interacted with the device. Most importantly, we could have collared free-ranging deer without handling them had the device been fully automated. In order to produce a fully functional device, we are presently pursuing a contract with DGCD because of their capability to incorporate our complete set of design specifications into the device. SUMMARY We made significant progress toward developing an automated collaring device for mule deer. We now depend on services of professional engineers to complete prototype development and evaluation. If we are successful, the automated collaring device would allow biologists and researchers to radio-collar portions of their deer samples with minimal time and expense because no animal handling would be required and deer could be collared at any time. Primary time commitments would include baiting sites, 57 �moving device(s) among sites, and adding collars to the devices. Once design work is completed, the current estimate for producing one fully functional collaring device is $7,000. At the current net-gunning rate of roughly $550/deer, an individual collaring device would be paid off after 13 deer were collared. Over time, as an individual biologist or researcher accumulated several of these devices, it is reasonable to assume they could collar 25-35 deer with a few weeks of limited effort, amounting to a savings of roughly $14,000-$20,000 per study per year once the devices were paid off. The collaring device would also have distinct benefits for studies in urban environments by providing a non-invasive technique for collaring deer. The collaring device would significantly reduce stress that is typically associated with capture and handling and there should be no capture-related mortality. We also have designed the collaring device so that it should be relatively easy to adjust to target adult deer and other ungulate species. Last, the collaring device would have wide applicability for ungulate researchers and managers beyond Colorado. LITERATURE CITED Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108−114. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by Chad J. Bishop, Wildlife Researcher 58 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2008-09 – FY 2009-10 State of: Cost Center: Work Package: Task No. Colorado 3430 3001 8 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS Principal Investigators Chad J. Bishop, Mammals Researcher, Colorado Division of Wildlife Daniel P. Walsh, Wildlife Health Researcher, Colorado Division of Wildlife Eric J. Bergman, Mammals Researcher, Colorado Division of Wildlife Mathew W. Alldredge, Mammals Researcher, Colorado Division of Wildlife Chuck R. Anderson, Mammals Researcher, Colorado Division of Wildlife Cooperators Mechanical Engineering Department, Colorado State University Michael Sirochman, Veterinarian Technician, Colorado Division of Wildlife John Broderick, Senior Terrestrial Biologist, Colorado Division of Wildlife Lisa L. Wolfe, Veterinarian, Colorado Division of Wildlife Michael W. Miller, Wildlife Health Leader, Colorado Division of Wildlife Stewart Breck, Research Wildlife Biologist, National Wildlife Research Center STUDY PLAN APPROVAL Prepared by: Chad J. Bishop Date: Nov 2008 Submitted by: Chad J. Bishop Date: Nov 2008 Reviewed by: Date: Date: Biometrician: Approved by: Date: Michael W. Miller Mammals Research Leader, Acting 59 Date: �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS A Study Plan Proposal Submitted by: Chad J. Bishop, Mammals Researcher, Colorado Division of Wildlife Daniel P. Walsh, Wildlife Health Researcher, Colorado Division of Wildlife Eric J. Bergman, Mammals Researcher, Colorado Division of Wildlife Mathew W. Alldredge, Mammals Researcher, Colorado Division of Wildlife Chuck R. Anderson, Mammals Researcher, Colorado Division of Wildlife A. Need The Colorado Division of Wildlife (CDOW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240 deer fawns are captured annually to monitor survival among 4 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CDOW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., $3,000−5,000 ea.) would reduce CDOW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CDOW’s operating expenses and improve animal welfare. 60 �B. Objectives Our study objective is to develop and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. C. Expected Results or Benefits A passive collaring device, as described above, would allow biologists and researchers to radiocollar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. Such a technique would significantly reduce stress that is typically associated with capture and handling and would eliminate capture-related mortality. We do not expect our collaring device to replace other capture techniques. Rather, we expect the device to provide biologists and researchers with an efficient, cost-effective technique to mark a portion of their targeted fawn samples, thereby keeping helicopter net-gunning requirements and associated costs at viable levels. D. Approach 1. Device Specifications We identified an array of specifications to guide design of the automated collaring device, which we divided into 3 categories: 1) collaring device, 2) radio collar, and 3) controls. Collaring device refers to the overall trap-like device and its various components. Our radio collar specifications reflect 6month-old fawn radio collars that are currently used by CDOW. Our intent was to avoid design of a more costly radio collar and to ensure that biologists and researchers could use radio collars readily available on the market without making substantive changes. If radio collar costs increased significantly, the automated collaring device would fail to be cost-effective and have much less utility to biologists and researchers accustomed to using helicopter net-gunning. We were less concerned about cost of the collaring device because it would be a one-time expense that would support repeated fawn captures. Our third specification category, controls, refers to those aspects of the device requiring automation. Collaring Device 1. Device remotely attaches radio collar around the neck of a ≥6-month-old deer fawn; most ≥6month-old fawns range in size from 50−100 lbs. 2. Device deters adult deer or other larger animals from entering but does not deter entry of fawns. 3. Device allows fawns to easily exit in multiple directions at any time. 4. Device must not cause injury to animals. 5. Device incorporates a place for bait, which will lure the animals to the device. 6. The collapsed device should fit in the back of a typical full-size pickup truck. 7. Device should be of a generalized design that could be modified in the future to target different ages and species of animals (e.g., adult deer, calf elk, adult elk, lamb sheep, adult sheep, etc.) Radio collar 1. Collar accommodates fawn neck sizes ranging from 11 to 16 inches in circumference. 2. Width of collar neckband ranges from 0.5 to 3 inches. 3. Collar sheds from the deer 6−12 months after being placed on the animal using surgical tubing or comparable mechanism that does not increase the overall cost of a radio collar. 4. Use existing radio transmitters that are presently available on the market. Controls 1. Restrict collaring to animals that weigh 47−103 lbs (i.e., guarantee that only fawns receive radio collars). 2. Prevent the same fawn from being collared more than once. 3. Measure and record animal weight. 4. Measure and record animal sex. a. Fawn deer sexing options include: 61 �i. Gonads (most reliable) ii. Antler stubs (less reliable) 5. Obtain photo of captured animal. 2. Device Design Working with engineering students and faculty at Colorado State University, we designed the device in stages using a series of prototypes. For example, we initially constructed the device frame out of cheap material and evaluated it using captive deer at the Foothills Wildlife Research Facility in Fort Collins, CO. We observed deer interactions with the prototype to evaluate device dimensions and placement of the radio collar within the device (Figs. 1, 2). We then modified the prototype accordingly and reevaluated until we were comfortable the dimensions were adequate. Once staged prototype testing was completed, we constructed the various device components using materials we believed were suitable for employing the device in winter field conditions. The device frame was constructed from steel and coated to prevent rust and to lessen wear and tear (Fig. 3). The sides of the device comprise one-gay gates, which prevent entry from outside the device yet allow deer to exit the device at any point they choose. The one-way gates were constructed from aluminum and are being mounted with hinges and springs to allow one-way movement. Deer will enter the device through a 14” x 32” opening in the front of the device; entry dimensions were derived from experience feeding deer fawns in Idaho (G. Scholten, Idaho Department of Fish and Game - retired, personal communication). The radio collar and collaring mechanism will be positioned at the rear of the device and in front of the bait compartment (Fig. 4). To access the bait, a deer will be required to extend its head and neck through an expandable collar in the fully expanded position (Fig. 5). The radio collar was made expandable using springs, which was patterned after an expandable adult buck collar designed by Michael Sirochman (Colorado Division of Wildlife, personal communication). The springs prevent the collar from being too loose on a small fawn while not being too tight on a large fawn. Expandable fawn collars are not a new concept and have been commonly used elsewhere on 6-month-old fawns and are sold by telemetry companies. The floor of the device will comprise a scale to estimate the animal’s weight. The animal’s weight will be correctly recorded no matter where the animal stands within the device. A door will close and prevent access to the collaring mechanism/bait compartment if an animal is heavier than 103 lbs, which will allow us to target fawns and prevent older deer from sticking their head through the expanded collar. To be collared, a deer must extend its head through the collar and nudge a joystick positioned in the center of the bait container. The collar will not release unless an animal is heavier than 43 lbs (and less than 103 lbs), which will prevent small animals that may access the bait from triggering the collar. When the joystick is moved and the animal is in the correct weight range, a solenoid will be activated that causes the collar to release around the deer’s neck (Fig. 5). To prevent double-collaring, radio frequency identification (RFID) tags will be attached to all fawn collars. An antenna will be positioned around the opening of the device and connected to an RFID reader. When a previously collared fawn enters the device, the RFID reader will detect the tag and cause the door to the collaring mechanism/bait compartment to close. Digital cameras will be positioned in several locations in the device to photograph the animal when the collar is released. We are currently in the process of assembling the various device components. Once fully assembled and operational, we will evaluate the device with captive deer at FWRF. As necessary, we will make modifications or adjustments to the device until it meets all of our specifications listed above. 62 �3. Field Testing We will evaluate the device with free-ranging deer after we have confirmed the device is working correctly with captive deer. Initially, we will evaluate the device under close supervision in the Fort Collins area to record deer interactions with the trap and to document any problems we may have failed to anticipate. We will be on-site during this initial field testing and we will secure the device entry to prevent access when we’re not present. This will allow us to directly observe how animals interact with the device and to free any animals if there is a problem. If there is a problem, we will use a pole or rod to simultaneously pull back the bars forming the one-way gates on the sides of the trap to encourage the animal to exit and/or to assist the animal with exiting. In the unlikely event we were to seriously injure an animal or kill an animal, we would cease the field study and go back to the design phase to address the problem that caused the animal harm. Animals will be released from the device with functioning radio collars and will be monitored one week post-collaring and every few weeks thereafter. Collars will have surgical tubing between the transmitter and the springs, thereby allowing the collar to drop-off when the surgical tubing degrades. We are using surgical tubing because it is the standard technique used to collar 6-month-old fawns in Colorado, and thus we want to test deployment of collars that will actually be used with this device. However, we will use a knife to make small cuts in the surgical tubing to cause the collars to shed from the animals within a few months of being deployed. Once we have radio-collared several fawns successively without incident and confirmed the device is working correctly, we will begin more widespread testing. During November-December 2009, we will employ ≥1 devices on mule deer winter range to capture fawns as part of ongoing research (Anderson and Freddy 2008). We will document whether the collars cause any ill effects to fawns during the field evaluations by following up on fawns and evaluating whether any mortalities might be related to collaring. We will record numbers of fawns successfully radio-collared and measured relative to personhours expended setting and moving the device. We will then contrast costs and efficiency with other fawn capture techniques. Finally, we will project the cost-savings over a 10-year period associated with using the device for 3 weeks on each deer research and management study in Colorado. It is highly unlikely that an animal would require euthanasia in this study because we will not restrain animals and animals will be able to readily exit the collaring device in any of 3 directions. However, if a deer were to suffer a broken leg, back, neck, pelvis, or other similar wound, it will be euthanized by deep anesthesia with the drug combination of ketamine or Telazol© and xylazine (IV or IM) with dosage based on estimated weight, followed by intravenous administration of KCl (~350 mg KCl/ml sterile water, dosed at >50 mg KCl/kg estimated body mass). In situations where administration of KCl is not feasible, then euthanasia will be performed via a gunshot to the head. E. Location We will conduct all evaluations with captive deer at the FWRF in Fort Collins, CO. We will conduct limited evaluations with free-ranging deer near Fort Collins in north-central Colorado and extensive field evaluations in the Piceance Basin in northwest Colorado. Anderson and Freddy (2008) provided a detailed description of winter range study sites where 6-month-old fawn mule deer will be captured in the Piceance Basin. 63 �F. Schedule Of Work Activity Date Complete Initial Device Specifications Design and Evaluate Prototypes of Device Components Assemble and Evaluate Prototype Device with Captive Deer Initial Evaluation of Device with Free-Ranging Deer Set up Contract with Professional Engineering Firm Complete Design Requirements and Fabricate Working Device Extensive Evaluation of Device with Free-Ranging Deer Prepare Final Report Submit Manuscript to JWM for Publication Sept 2008 Sept 2008−Feb 2009 Mar 2009 Mar−Apr 2009 July−Aug 2009 Sept−Dec 2009 Dec 2009−Feb 2010 Mar−Apr 2010 May−July 2010 G. Estimated Costs Category Item or Position FY 08-09 FY 09-10 Personnel Chad Bishop 0.06 PFTE 0.06 PFTE Dan Walsh 0.06 PFTE 0.04 PFTE Mat Alldredge 0.03 PFTE 0.01 PFTE Eric Bergman 0.03 PFTE 0.01 PFTE Chuck Anderson 0.00 PFTE 0.03 PFTE Device Design and Fabrication $9,000 $22,000 Field Evaluations $1,000 $3,000 Operating H. Related Federal Projects Our research will be conducted on federal (i.e., BLM, USFS) and state lands. The study does not involve formal collaboration with any federal agencies, nor does the work duplicate any ongoing federal projects. I. Literature Cited Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, USA. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108−114. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. 64 �van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Figure 1. Prototype evaluation of collar and bait placement, and validation that a deer would extend its head and neck through an expanded collar to access the bait. 65 �Figure 2. Prototype evaluation of entrance and cage dimensions with captive deer. Figure 3. Device frame. The sides of the device will comprise one-way gates that prevent entry to the device yet allow animal to easily exit once inside. Animals will be required to enter the device through a 14” x 32” opening in the front. The rear portion of the device is a bait compartment fabricated from steel. A door on the rear of the bait compartment will allow biologists to easily add bait in the field. 66 �Figure 4. The bait compartment. Deer will be required to extend their head and neck through an outstretched expandable radio collar in order to reach the bait. Figure 5. Radio collar in fully expanded position situated at the entry to the bait compartment. Clear plexi-glass will be placed on either side of the collar to prevent deer from accessing the bait from the side yet will allow visibility. When activated, a solenoid positioned at the top of the collaring device pushes a lever that releases the collar. 67 �68 �Colorado Division of Wildlife July 2008 − June 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Effectiveness of a Redesigned Vaginal Implant Transmitter in Mule Deer Period Covered: July 1, 2008 − June 30, 2009 Authors: C. J. Bishop, C. R. Anderson, D. P. Walsh, P. Kuechle, J. Roth, and E. J. Bergman. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Our understanding of factors that limit mule deer populations may be improved by evaluating neonatal survival as a function of dam characteristics under free-ranging conditions, which generally requires that both neonates and dams are radiocollared. The only viable technique facilitating capture of neonates from radiocollared adult females is use of vaginal implant transmitters (VITs). To date, VITs have allowed research opportunities that were not possible previously; however, VITs are often expelled from adult females prepartum, which limits their utility. We redesigned an existing vaginal implant transmitter (VIT) manufactured by Advanced Telemetry Systems (ATS) by lengthening and widening wings used to retain the VIT in an adult female. Our objective was to increase VIT retention rates to increase likelihood of locating birth sites and newborn fawns. We placed VITs with modified wings in 59 adult female mule deer and evaluated probability of retention to parturition and probability of locating newborn fawns. Probability of a VIT being expelled during parturition (i.e., success) was 0.766 (SE = 0.0605) and probability of a VIT being expelled ≤3 days prepartum (i.e., partial success) was 0.128 (SE = 0.0477). Thus, probability of a VIT being at least partially successful was 0.894 (SE = 0.0441). Probability of locating at least 1 neonate from successful or partially successful VITs was 0.952 (SE = 0.0333) and probability of locating both fawns from twin litters was 0.588 (SE = 0.0857). We expended approximately 12 person-hours per detected neonate. Our modifications to VIT wings effectively increased VIT retention in mule deer, allowing more neonate fawns to be located per unit cost and effort. Researchers employing VITs with modified wings should require minimal oversampling to offset failures caused by early expulsion. To aid researchers in planning future studies, we developed an equation for determining VIT sample size necessary to achieve a specified sample size of neonates. Our study expands opportunities for conducting research that links adult female attributes to productivity and offspring survival. 69 �WILDLIFE RESEARCH REPORT EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES CHAD J. BISHOP, CHUCK R. ANDERSON, DANIEL P. WALSH, PETER KUECHLE, JOHN ROTH, AND ERIC J. BERGMAN P. N. OBJECTIVE To redesign vaginal implant transmitters (VITs) and evaluate their retention in free-ranging mule deer. SEGMENT OBJECTIVES 1. Redesign and manufacture the silicone-covered plastic wings used to retain VITs in deer. 2. Evaluate rates of VIT retention to parturition and fawn capture success using the newly-designed wings in free-ranging mule deer. INTRODUCTION Mule deer (Odocoileus hemionus) fawn production and neonatal survival is influenced by dam characteristics (e.g., body condition, disease status, habitat use). To understand fawn-dam relationships, manipulative field studies are needed that allow fawn production and survival to be estimated as a function of treatments applied to adult females. For example, a study evaluating the effectiveness of winter range habitat treatments on subsequent neonatal survival would require the capture of fawns from marked adult females that verifiably used, or did not use, the habitat treatments the previous winter(s). Such studies depend on a technique that enables newborn fawns to be captured from marked adult females. The most promising technique employed to capture neonates from marked adult females is use of vaginal implant transmitters (VITs), which are placed in the vagina of adult females during early to mid gestation. In theory, adult females retain VITs until parturition, at which point VITs are expelled at birth sites along with newborn fawns. Assuming VITs are routinely monitored, researchers can promptly radio-locate shed VITs and capture the newborn fawns. Recent applications of VITs in white-tailed deer (O. hemionus), black-tailed deer (O. hemionus columbianus), and mule deer have been moderately successful (Bowman and Jacobson 1998, Carstensen et al. 2003, Pamplin 2003, Bishop et al. 2007). Vaginal implant transmitters also permit measurement of fetal survival in free-ranging populations, which has important implications in populations where stillborn mortality occurs (Bishop et al. 2007, 2008, 2009). An additional advantage of using VITs to capture neonates may be a reduction in sample bias when compared to capture techniques that rely on opportunistic fawn capture (White et al. 1972, Ballard et al. 1998, Pojar and Bowden 2004). Opportunistic techniques are susceptible to bias because of unequal capture success among vegetation types, road densities, fawn ages, and stages of fawning. When using VITs, neonate captures should be more random as long as VIT signals are monitored with equal intensity during fawning, and assuming the sample of radio-collared does was captured with minimal bias. Thus, VITs could have broad applicability regardless of whether study objectives require that fawns be captured from previously marked adult females. The most significant problem associated with VITs has been premature expulsion and subsequent failure to locate birth sites or newborn fawns (Bowman and Jacobson 1998, Carstensen et al. 2003, Pamplin 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). The VIT has flexible, plastic wings coated with a soft silicone that induce pressure against the vaginal wall to retain the transmitter. The VIT 70 �design facilitates a quick, non-surgical insertion process and is safe for the animal (Johnson et al. 2006), but the current wing design is inadequate with respect to retention. Bishop et al. (2007) found that 43% (SE = 4.7) of VITs in mule deer shed prepartum, although capture success was high when VITs shed only 1−3 days prepartum. More importantly, Bishop et al. (2007) found that 25% (SE = 4.1) of VITs shed >3 days prepartum and that retention probability declined as deer body size increased, indicating the retention wings were too small to be effective in larger deer. Based on these results, considerable oversampling would be required in the design of future projects to achieve a target sample size of fawns. Oversampling is not desirable from an animal care and use perspective or from a cost perspective. Thus, the plastic-silicone retention wings of VITs need to be redesigned to allow maximum retention in deer. To date, the wings used to retain VITs have been purchased from a company in New Zealand (Carter Holt Harvey Plastic Products, Hamilton, New Zealand) that originally produced them for an application in the livestock industry (Bowman and Jacobson 1998). The company manufactured 1 large wing and 1 small wing; the former has been used to produce VITs for bison (Bison bison) and elk (Cervus elaphus) whereas the latter has been used to produce VITs for deer (Advanced Telemetry Systems, Isanti, MN). Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, made an initial effort in 2004 to lengthen the retention wings by adding resin to the wing tips. Using these VITs and with antennas cut to the appropriate length, S. P. Haskell (Texas Tech University, unpublished data) reported that 81% of VITs (n = 21) in deer were retained until parturition. Although retention improved, this aftermarket modification was not ideal. The modified wing tips were hard because of the resin addition and thus not ideal for placement in the vaginal canal. Also, there remained a need to further increase retention rate. We therefore developed a study plan (Appendix A), redesigned retention wings of VITs used in deer and similar-sized ungulates, fabricated a new production mold, and evaluated retention rates of VITs in free-ranging mule deer. STUDY AREA We conducted our research in Piceance Basin and on Roan Plateau in northwest Colorado (Fig. 1). Our winter range study area comprised 4 study units distributed across much of the Piceance Basin. The 4 units ranged in size from 70 to 130 km2 and are referenced as Magnolia, Story-Sprague, Ryan Gulch, and Yellow Creek (Fig. 2). These study units are part of a larger research study evaluating effects of natural gas development and mitigation on mule deer (Anderson and Freddy 2008). Winter range habitat comprised predominantly pinyon pine (Pinus edulis) and Utah juniper (Juniperus osteosperma) and secondarily big sagebrush (Artemisia tridentata), serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), and rabbitbrush (Chrysothamnus spp.). Drainage bottoms were characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainage bottoms having been converted to irrigated, grass hay fields. Elevations ranged from 1860 m at Piceance Creek in Ryan Gulch to 2280 m in Yellow Creek and Story-Sprague. Our summer range study area comprised roughly 1700 km2 across the Roan Plateau and Piceance Basin (Fig. 1). Principal summer range habitat types included aspen (Populus tremuloides), mountain shrub, oakbrush (Quercus gambellii), big sagebrush, and pinyon-juniper. Serviceberry, snowberry (Symphoricarpos spp.), and chokecherry (Prunus virginiana) were common species in mountain shrub communities. Elevation ranged from 2000 m in Piceance Creek at the mouth of Story Gulch to 2600 m on Roan Plateau. 71 �METHODS VIT Modification We worked with ATS personnel to redesign the M3930 VIT presently manufactured by ATS. The existing M3930 has been described in detail elsewhere (Bowman and Jacobson 1998, Carstensen et al. 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). Our redesign included changes to the retention wings and the way in which wings are attached to the transmitter body. Specifically, we extended the length and width of the retention wings and added ridges to the wing surface, both of which were intended to increase probability of retention to parturition (Fig. 3). The wings were made of flexible plastic encased in silicone. We initially produced a small number of the newly-designed wings using a relatively inexpensive prototype mold, which met our target specifications and therefore was deemed acceptable. We then manufactured a production mold, necessary to produce a large number of the wings. We incorporated ejector pins into the VIT design that allow wings to be attached to the VIT transmitter body in the field. In the original design, wings were permanently affixed to the transmitter body during the VIT assembly process. Although we only used one wing size in this study, field-attachment will allow researchers to use more than one wing size or style, without purchasing extra transmitters, if additional production molds are manufactured over time. For each wing design (i.e., production mold), extra wings could be inexpensively purchased and available in the field to affix to the fixed number of transmitter bodies. Researchers could then individually fit VITs to animals in the field much in the same way radiocollars are individually fitted. Deer Capture and VIT Insertion During late February and early March, 2009, we captured 59 adult female deer utilizing helicopter net guns (Barrett et al. 1982, van Reenen 1982) in conjunction with ongoing research addressing other objectives (Anderson and Freddy 2008). We captured 20 deer in Ryan Gulch, 19 deer in Yellow Creek, and 10 deer each in South Magnolia and Story-Sprague study units. Captured deer were hobbled, blind-folded, and ferried ≤5 km by helicopter to a central handling location. For each captured deer, we used transabdominal ultrasonography (SonoVet 2000, Universal Medical Systems, Bedford Hills, NY) to determine pregnancy status and number of fetuses (Stephenson et al. 1995, Bishop et al. 2007, Bishop et al. 2009). We shaved the left caudal abdomen from the last rib and applied lubricant to facilitate transabdominal scanning using a 3-MHz linear transducer. We fitted each pregnant deer with a VIT and a radiocollar equipped with a mortality sensor and store-on-board global position system (GPS). The mortality sensor was programmed to switch signal transmission from a slow pulse to a fast pulse after remaining motionless for 4 hours. We also measured mass, chest girth, and hind foot length of each deer and estimated age by evaluating tooth replacement and wear (Severinghaus 1949, Robinette et al. 1957, Hamlin et al. 2000). We performed the ultrasound and VIT insertion procedures in a wall-frame tent to minimize disturbance from helicopter rotor wash and adverse weather conditions and to create a dim environment to facilitate ultrasonography. We sterilized VITs in a chlorhexidine solution prior to insertion in the field. We inserted VITs using a clear, plastic swine vaginoscope (Jorgensen Laboratories, Inc., Loveland, Colo.) and alligator forceps. The vaginoscope was 15.2 cm long with a 1.59 cm internal diameter and had a smoothed end to minimize vaginal trauma. We placed vaginoscopes and alligator forceps in cold sterilization containers with chlorhexidine solution between each use and used a new pair of surgical gloves to handle the vaginoscope and VIT for each deer, and we applied a lidocaine cream to the deer’s vagina prior to insertion. To insert a VIT, we folded the wings together and placed the VIT into the end of the vaginoscope. We liberally applied sterile KY Jelly to the scope and inserted it into the vaginal canal until the tip of the VIT antenna was approximately flush with the vulva. We used previous field experience to guide insertion distance and antenna length (Bishop et al. 2007). We extended alligator forceps through the vaginoscope to firmly hold the VIT in place while the scope was pulled out from the vagina. Each VIT had a temperature-sensitive switch and a pre-cut antenna (6 cm in length) with antenna 72 �tip encapsulated in a resin bead to eliminate sharp edges. The temperature-sensitive switch caused the VIT to increase pulse rates from 40 pulses to 80 pulses per minute when the temperature dropped below 32° C. A temperature drop below 32° C was indicative of the VIT being expelled from the deer. VIT Monitoring and Success Evaluation We monitored live-dead status and general location of all radiocollared adult females daily from the ground and biweekly from the air during winter and spring. During each morning of June we checked VIT signal status by aerially locating each radio-collared doe having a VIT, weather permitting. We began flights at approximately 0630 hours and completed them by 0900–1100 hours. Early flights were necessary to detect fast signals because temperature sensors of VITs expelled in open habitats and subject to sunlight often exceeded 32° C by mid-day, which caused VITs to switch back to a slow (i.e., prepartum) pulse. When we detected a fast (i.e., postpartum) pulse rate, we used very high frequency (VHF) receivers and directional antennae from the ground to simultaneously locate the VIT and radiocollared doe. We attempted to observe behavior of the collared adult female, establish whether the VIT was shed at a birth site, and search for fawns in the vicinity of the adult female and expelled VIT. In cases where the dam moved away from the VIT (i.e., >200 m), we located the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawn(s) were present and subsequently located the collared dam to search for fawns at her location. We attempted to account for each dam’s fetus(es) as live or stillborn. We typically worked in pairs, which allowed us to effectively partition effort across the study area while maintaining reasonable efficiency when searching for neonates (i.e., two people were more effective locating a hidden neonate than one person). We described effort associated with locating fawns by calculating the number of person-hours per fawn. We also quantified cost per fawn by considering all operating and personnel expenses, including capture and VIT costs for adult females. We assigned the fate of each VIT to one of 4 categories: 1) success (i.e., VIT expelled during parturition), 2) partial success (i.e., VIT expelled ≤3 days prepartum), 3) failure (i.e., VIT expelled >3 days prepartum), or 4) censor. We considered a VIT successful if it was expelled at or near a birth site in conjunction with parturition. For most success events, we located VITs at birth sites and located neonates near the VITs or in close proximity to their dams. In other success cases, we did not locate VITs at birth sites yet we found neonate(s) in close proximity to the dam, sometimes at a birth site a short distance from the expelled VIT. In these cases, we considered a VIT successful if we documented <1-day-old fawn(s) <24 hours after the VIT was expelled. Last, on two occasions, we considered a VIT successful because it was located at an evident birth site even though we could not locate fawns. Birth sites appeared as atypically large deer beds with soil appearing damp and with forbs and grasses flattened and radiating outward, consistent with a deer licking the site clean. On some occasions, fawns and/or placental remains were still present at birth sites when we arrived, providing positive confirmation of birth site characteristics. We considered VITs expelled within 3 days of parturition as partial successes because they provided useful information for locating fawns, consistent with Bishop et al. (2007). We documented such cases by locating a dam’s neonates one or more days after the VIT was expelled and comparing neonate age to VIT expulsion date. We censored VITs when adult females died prior to parturition and when adult females were located on private land that we did not have permission to access. In either case, we were unable to evaluate VIT effectiveness. All females dying prior to parturition were still carrying the VITs upon death. Analysis We modeled VIT success probability using a generalized logits model (i.e., multinomial logistic regression) in PROC LOGISTIC in SAS (SAS Institute, Cary, NC). We considered 3 levels of success consistent with our description above (success, partial success, failure) and we removed all censors from the dataset prior to analysis. We modeled VIT success as a function of adult female age (yr), mass (kg), hind foot length (cm), chest girth (cm), body fat (%), vegetative cover at VIT expulsion site, and study site. The latter two variables were included to evaluate whether locating fawns, and hence VIT success, 73 �was influenced by habitat characteristics. We expressed vegetative cover categorically as low, medium, or high. Low cover class was characterized by limited understory and overstory vegetation with minimal visual obstruction at ground level (e.g., sparsely-vegetated grass, sagebrush, or mountain shrub slopes). Medium cover class was characterized by moderate to heavy vegetative cover within 1 m of the ground but limited cover above 1 m (e.g., typical sagebrush, mountain shrub sites). High cover class comprised moderate to heavy vegetative cover from ground level up to > 1 m with nearly complete visual obstruction (e.g., oakbrush, aspen-mountain shrub, dense serviceberry). We selected among models using Akaike’s information criterion adjusted for sample size (AICc; Burnham and Anderson 2002). We then estimated the probability of locating ≥ 1 fawn, probability of locating both fawns from twin litters, and probability of locating complete litters from adult females with successful or partially successful VITs. Finally, we developed an equation for determining number of VITs necessary to achieve a specified sample of neonates for planning of future neonatal studies. RESULTS AND DISCUSSION We observed 9 adult female mortalities during winter and spring, which was much higher than expected. There was no evidence to suggest VITs were related to the mortality events. Several of the mortalities occurred within 1 week of capture and were likely capture-related. We were unable to groundmonitor 2 other adult females during the fawning period because they were located on private land that we did not have permission to access. One other adult female was inadvertently deleted from the aerial monitoring list due to miscommunication. We censored these 12 deer because they did not permit evaluation of VIT effectiveness, resulting in a sample size of 47 deer. The model of VIT success probability with the lowest AICc included only the intercept (no. parameters = 2, AICc wt = 0.271; Table 1). Probability of a VIT being expelled during parturition (i.e., success) was 0.766 (SE = 0.0605) and probability of a VIT being expelled ≤3 days prepartum (i.e., partial success) was 0.128 (SE = 0.0477). Thus, probability of a VIT being at least partially successful was 0.894 (SE = 0.0441). For comparison, using the original VIT wing design, Bishop et al. (2007) found that probability of VIT expulsion during parturition was 0.447 (SE = 0.0468), and probability of VIT expulsion during parturition or ≤3 days prepartum was 0.623 (SE = 0.0456). We employed the same methodology as Bishop et al. (2007), except for the wing modification. Assuming the 2 studies are comparable, our wing modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). High VIT success probability may largely explain why VIT retention did not vary as a function of any covariates we evaluated. Bishop et al. (2007) found that larger deer were more likely to expel VITs prematurely, which was the basis for modifying VIT wings. Our results suggest the wing modifications effectively reduced premature expulsion in larger deer. We located 58 neonates and 2 stillborns from 42 adult females with successful or partially successful VITs. For these 42 females, probability of locating at least 1 neonate was 0.952 (SE = 0.0333), probability of locating complete litters was 0.667 (SE = 0.0745), and probability of locating both fawns from twin litters was 0.588 (SE = 0.0857). Fawn location success did not differ between successful and partially successful VITs. Our probability estimate of locating twins is conservative because we did not place radio collars on fawns, and therefore, we could not relocate radiocollared fawns to search for their siblings. The technique of relocating a radiocollared fawn to locate its sibling was found to be successful in a previous study in Colorado (Bishop et al. 2009). During this earlier study, when a dam was known to have twin fetuses yet only one fawn was located and radiocollared during the initial capture attempt, the sibling fawn was found 45% of the time (10/22) by relocating the initial radiocollared fawn 1−2 days post-capture (C. J. Bishop, CDOW, unpublished data). Based on this rate, we would expect our probability of locating both fawns from twin litters to be roughly 0.77 had we radiocollared fawns during our study. 74 �On average, we located 1.3 neonates per VIT excluding censors and 1.0 neonate per VIT including censors. Censors need to be considered when planning VIT sample sizes for neonatal studies. Censored VITs represent the reduction in VIT sample size caused by prepartum mortality of adult females or any factor preventing access to adult females during the fawning period. We developed the following equation for determining the expected number of neonates to be encountered from a sample of VITs: , where = targeted neonate sample size. = sample size of adult females with VITs. = probability adult female survives to parturition and is accessible. = probability of VIT retention to within 3 days of parturition. = probability of detecting ≥1 fawn. = probability adult female has twin fetuses. = probability of detecting twin neonates given an adult female has twin fetuses. The purpose of the above equation is to allow determination of VIT sample size once a target neonate sample size has been identified. Thus, it makes more sense to rearrange the equation as: Incorporating our estimates of retention and detection probabilities, we recommend use of the following equation to plan neonatal studies incorporating VITs with our modified wing design: We expended roughly 700 person-hours during the fawning period to locate 58 neonates and 2 stillborns, or approximately 12 person-hours per fawn located. This estimate includes hours spent searching for fawns from adult females with failed VITs, although we were never successful in these attempts. Bishop et al. (2007) expended 7 person-hours per captured fawn from adult females with successful VITs, 16 person-hours per fawn from females with partially successful VITs, and 42 personhours per fawn from females with failed VITs and females not receiving VITs. Given their observed VIT success rates, Bishop et al. (2007) would have required approximately 1,315 person-hours to locate 60 neonates, or 22 person-hours per fawn. Assuming these studies are comparable, increased VIT success associated with our modified wing design resulted in a 45% reduction in labor required to locate a fawn from a radiocollared adult female. We expended $31,000 to net-gun our sample of adult females, $15,000 on VITs, $10,000 on fixed wing monitoring, and $20,000 on personnel. Thus, we expended approximately $1,267 per neonate located. We did not include adult female radio collars in our cost estimate because we used GPS collars to meet other research objectives, yet VHF collars would have sufficed for locating neonates. Assuming VHF collars were used on adult females at a rate of $250 per collar, our cost estimate becomes $1,520 per fawn. The VIT technique is therefore effective but expensive to employ. Actual cost of the technique depends on what costs are already incurred to meet other research objectives. For example, in Colorado and elsewhere, researchers have begun estimating late-winter deer body condition as a response variable to accompany survival estimates. In these cases, adult female capture and radio collar costs are already accounted for in the base study, and thus, incorporation of VITs to facilitate neonate capture becomes much more cost-effective. In our study, where adult female capture and collar costs were covered by ongoing research efforts, the added cost of incorporating VITs and neonate capture was $750 per fawn. 75 �SUMMARY Use of VITs in well-designed field studies will increase our understanding of deer limiting factors and population limitation by allowing investigators to link fawn production and survival to dam characteristics under free-ranging conditions. A primary drawback of VITs in deer has been the failure of many adult females to retain VITs to parturition. We increased VIT retention in mule deer by lengthening and widening wings used to retain a VIT in the vaginal canal. Researchers employing VITs with our modified wing design should require minimal oversampling to offset failures caused by early expulsion, thereby rendering the technique more cost-effective and reliable. Our findings provide explicit guidance for planning a fetal-neonatal deer study involving VITs. Improved VIT effectiveness facilitates increased detection of twins, and therefore, increased likelihood of radio-collaring complete litters. Determining fates of complete litters improves our ecological understanding of fawn production and recruitment and allows assessment of individual reproductive fitness if the same females are captured across years. However, it is not reasonable to assume neonatal twins are independent sample units when analyzing survival. A technique is available to quantify the amount of sibling dependence in a sample of radio-collared fawns comprising siblings to correctly estimate variance of survival rates and to improve understanding of sibling relationships (Bishop et al. 2008). Although we significantly increased VIT retention, we cannot explain why 10% of adult females expelled VITs several days or weeks prepartum. These individuals were not older or larger than other deer in our sample, making it difficult to recommend future VIT modifications to further improve retention. We speculate that individual behavior may largely explain early VIT expulsion in this study. That is, some deer may be more inclined to attempt to remove VITs than others, making it difficult to eliminate prepartum shedding altogether without dramatically changing how VITs are retained. LITERATURE CITED Anderson, C. R., and D. J. Freddy. 2008. 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Evaluating the accuracy of ages obtained by two methods for Montana ungulates. Journal of Wildlife Management 64:441−449. Johnson, B. K., T. McCoy, C. O. Kochanny, and R. C. Cook. 2006. Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134−153. Severinghaus, C. W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195−216. Stephenson, T. R., J. W. Testa, G. P. Adams, R. G. Sasser, C. C. Schwartz, and K. J. Hundertmark. 1995. Diagnosis of pregnancy and twinning in moose by ultrasonography and serum assay. Alces 31:167−172. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, M., F. F. Knowlton, and W. C. Glazener. 1972. Effects of dam-newborn fawn behavior on capture and mortality. Journal of Wildlife Management 36:897−906. Prepared by Chad J. Bishop, Wildlife Researcher 77 �Figure 1. Location of winter and summer range study areas in Piceance Basin and on Roan Plateau, northwest Colorado. 78 �Figure 2. Location of winter range study units where we captured and radio-marked mule deer in Piceance Basin, northwest Colorado. These study units are part of a larger research study evaluating effects of natural gas development and mitigation on mule deer (Anderson and Freddy 2008). 79 �Figure 3. Design and dimensions of a modified retention wing used to retain vaginal implant transmitters in adult female mule deer. The displayed dimensions include a nylon core with an elastomeric overmold that protects deer from any sharp or rigid edges. 80 �APPENDIX A PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2007-08 – FY 2009-10 State of: Cost Center: Work Package: Task No. Colorado 3430 3001 7 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Effectiveness of a Redesigned Vaginal Implant Transmitter in Mule Deer EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES Principal Investigators Chad J. Bishop, Wildlife Researcher, Mammals Research Chuck R. Anderson, Wildlife Researcher, Mammals Research Daniel P. Walsh, Wildlife Researcher, Wildlife Health Eric J. Bergman, Wildlife Researcher, Mammals Research Peter Kuechle, President, Advanced Telemetry Systems John Roth, Product Consultant, Advanced Telemetry Systems David J. Freddy, Wildlife Research Leader, Mammals Research Cooperators Lisa L. Wolfe, Veterinarian, Colorado Division of Wildlife Darby Finley, Terrestrial Biologist, Colorado Division of Wildlife Jamin Grigg, Terrestrial Biologist, Colorado Division of Wildlife STUDY PLAN APPROVAL Prepared by: Chad J. Bishop Date: July 2008 Submitted by: Chad J. Bishop Date: July 2008 Reviewed by: Danny Martin Date: 11/24/2008 Jon Runge Date: 11/13/2008 Date: Biometrician Review: Paul Lukacs Date: 11/4/2008 Approved by: David J. Freddy Date: Dec. 2008 Mammals Research Leader 81 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES. A Study Plan Proposal Submitted by: Chad J. Bishop, Wildlife Researcher, Mammals Research Chuck R. Anderson, Wildlife Researcher, Mammals Research Daniel P. Walsh, Wildlife Researcher, Wildlife Health Eric J. Bergman, Wildlife Researcher, Mammals Research Peter Kuechle, President, Advanced Telemetry Systems John Roth, Product Consultant, Advanced Telemetry Systems David J. Freddy, Wildlife Research Leader, Mammals Research A. Need Mule deer (Odocoileus hemionus) fawn production and neonatal survival is influenced by dam characteristics (e.g., body condition, disease status, habitat use). To understand fawn-dam relationships, manipulative field studies are needed that allow fawn production and survival to be estimated as a function of treatments applied to adult females. For example, a study evaluating the effectiveness of winter range habitat treatments on subsequent neonatal survival would require the capture of fawns from marked adult females that verifiably used, or did not use, the habitat treatments the previous winter(s). Such studies depend on a technique that enables newborn fawns to be captured from marked adult females. The most promising technique employed to capture neonates from marked adult females is use of vaginal implant transmitters (VITs), which are placed in the vagina of adult females during early to mid gestation. In theory, adult females retain VITs until parturition, at which point VITs are expelled at birth sites along with newborn fawns. Assuming VITs are routinely monitored, researchers can promptly radio-locate shed VITs and capture the newborn fawns. Recent applications of VITs in white-tailed deer (O. hemionus), black-tailed deer (O. hemionus columbianus), and mule deer have been moderately successful (Bowman and Jacobson 1998, Carstensen et al. 2003, Pamplin 2003, Bishop et al. 2007). Vaginal implant transmitters also permit measurement of fetal survival in free-ranging populations, which has important implications in populations where stillborn mortality is known to occur (Bishop 2007, Bishop et al. 2007, Bishop et al. 2008). An additional advantage of using VITs to capture neonates may be a reduction in sample bias when compared to capture techniques that rely on opportunistic fawn capture (White et al. 1972, Ballard et al. 1998, Pojar and Bowden 2004). Opportunistic techniques are susceptible to bias because of unequal capture success among vegetation types, road densities, fawn ages, and stages of fawning. When using VITs, neonate captures should be more random as long as VIT signals are monitored with equal intensity during fawning, and assuming the sample of radio-collared does was captured with minimal bias. Thus, VITs could have broad applicability regardless of whether study objectives require that fawns be captured from previously marked does. The most significant problem associated with VITs has been premature expulsion and subsequent failure to locate birth sites or newborn fawns (Bowman and Jacobson 1998, Carstensen et al. 2003, Pamplin 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). The VIT has flexible, plastic wings coated with silicone that induce pressure against the vaginal wall to retain the transmitter. The VIT design facilitates a quick, non-surgical insertion process and is safe for the animal (Johnson et al. 2006), but the current wing design is inadequate with respect to retention. Bishop et al. (2007) found that 43% (SE = 4.7) of VITs in mule deer shed prepartum, although capture success was high when VITs shed only 1−3 days prepartum. More importantly, Bishop et al. (2007) found that 25% (SE = 4.1) of VITs shed >3 82 �days prepartum and that retention probability declined as deer body size increased, indicating the retention wings were too small to be effective in larger deer. Based on these results, considerable oversampling would be required in the design of future projects to achieve a target sample size of fawns. Oversampling is not desirable from an animal care and use perspective or from a cost perspective. Application of VITs in mule deer costs roughly $1,325 per captured fawn given current rates of premature expulsion (Bishop et al. 2007). Thus, the plastic-silicone retention wings of VITs need to be redesigned to allow maximum retention in deer. To date, the wings used to retain VITs have been purchased from a company in New Zealand (Carter Holt Harvey Plastic Products, Hamilton, New Zealand) that originally produced them for an application in the livestock industry (Bowman and Jacobson 1998). The company manufactures 1 large wing and 1 small wing; the former has been used to produce VITs for bison (Bison bison) and elk (Cervus elaphus) whereas the latter has been used to produce VITs for deer (Advanced Telemetry Systems, Isanti, MN). Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, made an initial effort in 2004 to lengthen the retention wings by adding resin to the wing tips. Using these VITs and with antennas cut to the appropriate length, S. P. Haskell (Texas Tech University, unpublished data) reported that 81% of VITs (n = 21) in deer were retained until parturition. Although retention improved, this aftermarket modification is not ideal. The modified wing tips are hard because of the resin addition and thus not ideal for placement in the vaginal canal. Also, we desire a VIT design that will provide >0.9 retention rates to parturition. Ideally, any modification to the VIT wings should be incorporated into the manufacturing process. The silicone-covered plastic wings must be manufactured using a production mold that costs roughly $15,000 to fabricate. To date, this cost has deterred design modifications to VIT wings. There is no economic incentive for a company to fabricate wing production molds exclusively for use in wildlife research given the high manufacturing costs and low anticipated return. However, the opportunity exists to redesign VIT retention wings with suitable funding. We propose to redesign the silicone-covered plastic wings, fabricate a new production mold, and conduct a field evaluation. B. Objectives Our study objectives are to (1) redesign and manufacture the silicone-covered plastic wings used to retain VITs in deer, and (2) evaluate rates of VIT retention to parturition and fawn capture rates using the newly designed wings in free-ranging mule deer. C. Expected Results or Benefits A redesigned VIT allowing high rates of retention to parturition (i.e., >0.9) would enable researchers to cost-effectively address complex problems associated with deer reproductive ecology, population productivity, and disease transmission in field studies. This field technique would then be efficacious and directly applicable to research evaluating effects of energy development and associated mitigation strategies, which is presently the highest priority facing Colorado Division of Wildlife and several other state wildlife agencies in the West. D. Approach 1. Hypotheses 1) Redesigned VITs will be retained until parturition in >90% of adult female mule deer. • Redesigning VITs by lengthening and widening the retention wings is expected to increase retention rates based on past research (Bishop et al. 2007; S. P. Haskell, Texas Tech University, unpublished data). 2) Stillborn or neonatal fawns will be located from >85% of adult female mule deer that receive redesigned VITs. • Bishop et al. (2007) captured fawns from 92% (SE = 3.7) of adult female mule deer that retained VITs to parturition. 83 �2. Experimental Design Our study design requires 2 key elements: 1) a minimum sample size of 60 adult female mule deer to guarantee suitable precision of VIT retention estimates, and 2) capture of adult female deer during mid-late winter to facilitate in utero fetus detection and to ensure VIT batteries will be operational throughout the fawning period (i.e., through early July). We will augment existing research efforts by placing VITs in adult female mule deer that will be captured in the Piceance Basin to meet other study objectives (Anderson and Freddy 2008). During 2009−2010, we will place VITs in 60 adult female mule deer each year during late February through early March in the Piceance Basin in northwest Colorado. The adult females will be captured across the Piceance Basin (Anderson and Freddy 2008) and are expected to cover an extensive area during summer (i.e., roughly 3000−4000 mi2) based on past research in this area (White et al. 1987, Bartmann et al. 1992). Assuming a VIT retention rate of 0.9 (i.e., 90% of VITs shed at birth sites), 60 adult females would allow us to estimate a yearly retention rate with a 95% confidence interval (CI) of 0.79−0.96, or a coefficient of variation (CV) of 4.3%. Following the 2-year study, we will be able to estimate retention rate with a 95% CI of 0.83−0.95 (i.e., CV = 3.1%), if there is no significant year effect. If we observe a year effect, we may be able to identify factor(s) that were potentially responsible and improve our understanding of VIT retention. Also, if we experience a problem in the first year, we may be able to correct it prior to the second year. If we experience high success during the first year (e.g., >0.9 retention to parturition), the second year may become part of a biological study to evaluate effects of energy development on fawn production and neonatal survival. 3. Procedures We worked with ATS personnel to redesign the M3930 VIT presently manufactured by ATS. The existing M3930 has been described in detail elsewhere (Bowman and Jacobson 1998, Carstensen et al. 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). Our redesign included changes to the retention wings and the way in which wings are attached to the transmitter body. Specifically, we extended the length and width of the retention wings and added ridges to the wing surface, both of which should increase probability of retention to parturition (Figs. 1, 2). The wings are made of flexible plastic encased in silicone. We initially produced a small number of the newly-designed wings using a relatively inexpensive prototype mold (i.e., $1,200). The prototype was acceptable. We will therefore manufacture a production mold (i.e., ~$15,000), which will allow a large number of the wings to be produced. The wings will be inexpensive to manufacture once the production mold is available. We will incorporate ejector pins into the VIT design that will allow wings to be attached to the VIT transmitter body in the field. Previously, wings were permanently affixed to the transmitter body during the VIT assembly process. Field-attachment would allow researchers to use more than one wing size or style, without purchasing extra transmitters, if additional production molds are manufactured over time. For each wing design (i.e., production mold), extra wings could be inexpensively purchased and available in the field to affix to the fixed number of transmitter bodies. Researchers could then individually fit VITs to animals in the field much in the same way radiocollars are individually fitted. In late February or early March each year of study, we will capture a total of 60 adult female deer utilizing helicopter net guns (Barrett et al. 1982, van Reenen 1982) in conjunction with ongoing research (Anderson and Freddy 2008). Captured deer will be hobbled, blind-folded, and ferried ≤3.5 km by helicopter to a central handling location. For each captured deer, we will use transabdominal ultrasonography (SonoVet 2000, Universal Medical Systems, Bedford Hills, NY) to determine pregnancy status and number of fetuses (Stephenson et al. 1995, Bishop 2007, Bishop et al. 2007). We will shave the left caudal abdomen from the last rib and apply lubricant to facilitate transabdominal scanning using a 3-MHz linear transducer. We will fit each pregnant deer with a VIT and a radiocollar equipped with a mortality sensor, which will activate after remaining motionless for 4 hours. 84 �We will also measure mass, chest girth, and hind foot length of each deer and estimate age by evaluating tooth replacement and wear (Severinghaus 1949, Robinette et al. 1957, Hamlin et al. 2000). We will perform the ultrasound and VIT insertion procedures in a wall-frame tent or other structure to minimize disturbance from helicopter rotor wash and adverse weather conditions and to create a dim environment to facilitate ultrasonography. We will sterilize VITs in a chlorhexidine solution prior to insertion in the field. We will insert VITs using a clear, plastic swine vaginoscope (Jorgensen Laboratories, Inc., Loveland, Colo.) and alligator forceps. The vaginoscope is 15.2 cm long with a 1.59 cm internal diameter and has a smoothed end to minimize vaginal trauma. We will place vaginoscopes and alligator forceps in cold sterilization containers with chlorhexidine solution between each use and use a new pair of nitrile surgical gloves to handle the vaginoscope and VIT for each deer, and we will apply a lidocaine cream to the deer’s vagina prior to insertion. To insert a VIT, we will fold the silicone wings together and place the VIT into the end of the vaginoscope. We will liberally apply sterile KY Jelly to the scope and insert it into the vaginal canal until the tip of the VIT antenna is approximately flush with the vulva. We will use previous field experience to guide insertion distance and antenna length (Bishop et al. 2007). We will extend alligator forceps through the vaginoscope to firmly hold the VIT in place while the scope is pulled out from the vagina. Each VIT will have a temperature-sensitive switch, pre-cut antenna (~6 cm in length) with antenna tip encapsulated in a resin bead to eliminate sharp edges, and a 12-hour on-off duty cycle to extend battery life (Bishop et al. 2007). The temperature-sensitive switch will cause the VIT to increase pulse rates from 40 pulses to 80 pulses per minute when the temperature drops below 32° C. A temperature drop below 32° C will be indicative of the VIT being expelled from the deer. We will regularly monitor live-dead status and general location of all radiocollared adult females during winter and spring. During each morning of June we will check VIT signal status by aerially locating each radio-collared doe having a VIT, weather permitting. We will begin flights at approximately 0530 hours and complete them by approximately 1000–1100 hours. Early flights will be necessary to detect fast signals because temperature sensors of VITs expelled in open habitats and subject to sunlight often exceed 32° C by mid-day, which will cause VITs to switch back to a slow (i.e., prepartum) pulse (Bishop et al. 2007). When we detect a fast (i.e., postpartum) pulse rate, we will use very high frequency (VHF) receivers and directional antennae from the ground to simultaneously locate the VIT and radiocollared doe. We will attempt to observe behavior of the collared adult female, establish whether the VIT is shed at a birth site, and search for fawns in the vicinity of the adult female and expelled VIT. In cases where the dam moves away from the VIT (i.e., >200 m), we will locate the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawn(s) are present and subsequently locate the collared dam to search for fawns at her location. We will attempt to account for each dam’s fetus(es) as live or stillborn, which is fundamental to estimating fetal survival (Bishop et al. 2007, 2008). We will wear surgical gloves when handling fawns to help minimize transfer of human scent. We will work in pairs and partition the study area into segments, whereby each 2-person team is responsible for one segment. We anticipate needing 4−5 teams given the expanse of the study area (Fig. 3). We will assign the fate of each VIT to one of 6 categories: 1) parturition shed, 2) late prepartum shed (i.e., ≤3 days prepartum), 3) early prepartum shed (i.e., >3 days prepartum), 4) battery or transmitter failure, 5) migration loss, or 6) censor (Bishop et al. 2007). We will identify parturition sheds based on identification of a birth site where the VIT is shed or location of <1-day-old fawn(s) <24 hours after a VIT is shed. The latter criterion is useful because not all birth sites can be positively identified once the dam has cleaned up afterbirth and moved the fawns. Although our primary objective is to quantify the proportion of VITs shed at parturition, the remaining VIT fate categories will be useful for understanding why VITs failed and should aid additional technique refinements. We will distinguish between early 85 �prepartum sheds and late prepartum sheds because the latter provides useful information for capturing fawns. Neonate capture success rate was 0.792 (SE = 0.0847, n = 24) for dams with VITs shed late prepartum on the Uncompahgre Plateau during 2002−2004 (Bishop et al. 2007). We will document battery failures based on the disappearance of a doe’s VIT signal after having consistently heard the signal on a daily basis. Migration losses refer to any VIT signals that disappear during spring migration. These failures are presumably caused by battery failures or early prepartum sheds between winter and summer range, yet the specific cause cannot be determined (Bishop et al. 2007). We will censor VITs associated with prepartum doe mortalities and missing does (i.e., unable to detect radiocollar signal) because these deer will not provide an adequate test of VIT effectiveness (i.e., the failure is independent of VIT technology). We will quantify the proportion of successful fawn captures associated with VITs shed at parturition as well as those shed ≤3 days prepartum. We will also determine whether we account for the entire litter by comparing the number of fawns located in June to the in utero fetal counts obtained in February−March. We will describe effort associated with fawn capture by calculating the number of person-hours per captured fawn. We will also quantify cost per captured fawn by considering all operating and personnel expenses, including capture and transmitter costs for adult does. 4. Data Analysis Procedures We will use a straight-forward binomial model to estimate the probability of VIT retention until parturition in adult female mule deer. We will contrast this estimate with a previous retention probability estimate (0.447, SE = 0.0468, Bishop et al. 2007) to evaluate the likely effect of our VIT modification. The estimates are not directly comparable because they will not have been measured simultaneously. However, the initial retention estimate measured by Bishop et al. (2007) provides a baseline for evaluating whether our VIT modifications had a positive effect. Ultimately, we will evaluate our retention probability estimate relative to our hypothesized retention rate of 0.9. We will model VIT retention as a function of adult female individual covariates (i.e., age, mass, chest girth, hind foot length) using logistic regression in SAS (SAS Institute, Cary, North Carolina) to improve our understanding of factors related to retention, which will be particularly useful if retention is < 0.9. We will select among models using Akaike’s information criterion adjusted for sample size (AICc; Burnham and Anderson 2002). We will also estimate fawn detection probability associated with adult females receiving VITs. Specifically, we will estimate separate detection probabilities for adult females that shed VITs prepartum and adult females that shed VITs at parturition. We will then use the detection probabilities to estimate the probability of capturing the complete litter for different sized litters. E. Location The proposed research will take place in the vicinity of Piceance Basin and the White River National Forest in northwest Colorado (Fig. 3). Anderson and Freddy (2008) provided a detailed description of winter range study sites where adult female mule deer will be captured. The winter range study area is located primarily within CDOW Game Management Unit (GMU) 22. Summer range will be defined by the movements of the radiocollared adult females captured on winter range. We anticipate the summer range study area will include portions of GMUs 11, 211, 12, 22, 23, 24, 31, 32, and 33 (Fig. 3). 86 �F. Schedule Of Work Activity Complete Initial Draft of Study Plan Manufacture VIT Retention Wing Production Mold Finalize Study Plan and Submit to ACUC Order VITs and Purchase Associated Field Equipment Capture Deer and Insert VITs Periodically Monitor Radiocollared Deer Monitor VITs Daily, Locate Shed VITs, and Conduct Fawn Searches Analyze Data and Prepare Progress Report Analyze Data and Prepare Final Report Submit VIT Techniques Manuscript for Publication Date April−May 2008 May−June 2008 August−October 2008 November 2008−2009 February−March 2009−2010 March−May 2009−2010 June 2009−2010 July−August 2009 July−August 2010 December 2010 G. Estimated Costsa Category Item or Position FY 07-08 FY 08-09 FY 09-10 Personnel Chad Bishop 0.20 PFTE 0.40 PFTE 0.40 PFTE Chuck Anderson 0 0.05 PFTE 0.05 PFTE Eric Bergman 0 0.05 PFTE 0.05 PFTE Dan Walsh 0.05 PFTE 0.05 PFTE 0.05 PFTE 0 6.5 Mo. - $17,186 7.0 Mo. - $18,760 VIT Prototype $2,500 0 0 VIT Production Mold $18,500 0 0 Fixed-wing Monitoring (June) 0 $14,875 $15,750 Field Supplies 0 $5,000 $4,000 60 VITs 0 $13,800 $13,800 Telemetry Equipment 0 $3,000 $1,500 TFTE Operating Total Cost $21,000 $53,861 $53,810 a Study costs were minimized by leveraging existing mule deer capture efforts within the ongoing Piceance Basin deer study (Anderson and Freddy 2008). H. Related Federal Projects Our research will be conducted on federal (i.e., BLM, USFS), state, and private lands. The study does not involve formal collaboration with any federal agencies, nor does the work duplicate any ongoing federal projects. I. Literature Cited Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, USA. 87 �Ballard, W. B., H. A. Whitlaw, D. L. Sabine, R. A. Jenkins, S. J. Young, and G. J. Forbes. 1998. Whitetailed deer, Odocoileus virginianus, capture techniques in yarding and non-yarding populations in New Brunswick. Canadian Field-Naturalist 112:254−261. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108−114. Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1−39. Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085−1093. Bowman, J. L., and H. A. Jacobson. 1998. An improved vaginal-implant transmitter for locating whitetailed deer birth sites and fawns. Wildlife Society Bulletin 26:295−298. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Second Edition. Springer-Verlag, New York, New York, USA. Carstensen, M., G. D. DelGiudice, and B. A. Sampson. 2003. Using doe behavior and vaginal-implant transmitters to capture neonate white-tailed deer in north-central Minnesota. Wildlife Society Bulletin 31:634−641. Hamlin, K. L., D. F. Pac, C. A. Sime, R. M. DeSimone, and G. L. Dusek. 2000. Evaluating the accuracy of ages obtained by two methods for Montana ungulates. Journal of Wildlife Management 64:441−449. Johnson, B. K., T. McCoy, C. O. Kochanny, and R. C. Cook. 2006. Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134−153. Severinghaus, C. W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195−216. Stephenson, T. R., J. W. Testa, G. P. Adams, R. G. Sasser, C. C. Schwartz, and K. J. Hundertmark. 1995. Diagnosis of pregnancy and twinning in moose by ultrasonography and serum assay. Alces 31:167−172. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G. C., R. A. Garrott, R. M. Bartmann, L. H. Carpenter, and A. W. Alldredge. 1987. Survival of mule deer in northwest Colorado. Journal of Wildlife Management 51:852−859. White, M., F. F. Knowlton, and W. C. Glazener. 1972. Effects of dam-newborn fawn behavior on capture and mortality. Journal of Wildlife Management 36:897−906. 88 �J. Figures And Tables Figure 1. Modified design of the nylon core of retention wings used to retain vaginal implant transmitters in adult female mule deer. We modified the original design by lengthening and widening the wings and modifying the shape. We also incorporated an ejector pin to facilitate attachment of different-sized wings in the field. 89 �Figure 2. Design and dimensions of a modified retention wing used to retain vaginal implant transmitters in adult female mule deer. The displayed dimensions include the nylon core (Figure 1) with an elastomeric overmold that protects deer from any sharp or rigid edges. 90 �Figure 3. Location of winter range and summer range study areas in the vicinity of Piceance Basin and White River National Forest in northwest Colorado, where we will evaluate the effectiveness of modified vaginal implant transmitters (VITs). Winter and summer range study areas are outlined in white. Mule deer winter range is denoted with dark shading and USFS lands are outlined in black. 91 �K. Appendices APPENDIX I HELICOPTER NET-GUN CAPTURE AND HANDLING PROTOCOL FOR MULE DEER Helicopter net-gunning is a well-established procedure for capturing ungulates (Barrett et al. 1982, van Reenen 1982). Large samples of mule deer and white-tailed deer have been captured using helicopter net-guns with ≤ 1% capture-related mortality (Potvin and Breton 1998, White and Bartmann 1994, Webb et al. 2008). The protocol described below is nearly identical to net-gun protocols approved previously by CDOW’s ACUC (CDOW ACUC Project Protocols 11−2000, 10−2005, 15−2007). Capture-related mortality rates in these projects have ranged from 0 to 3.5%, which includes all animals dying ≤1 week post-capture regardless of cause. A capture mortality rate of 3.5% is higher than the preferred rate of 2% (Spraker 1993) but much lower than what has commonly been experienced in the field using other methods to capture deer (Conner et al. 1987, DelGiudice et al. 2005). The 3.5% capturerelated mortality rate occurred on the Uncompahgre Plateau when large samples of mule deer were captured within small study sites, creating challenging conditions for helicopter net-gunning (Bishop 2007). The overall capture mortality rate in this study was 2% because a majority of deer were captured with drop nets, where capture mortality was 1%. In other recent studies, capture-related mortality rates associated with helicopter net-gunning have been ≤ 2% (Anderson and Freddy 2008; Bergman et al. 2006, 2007, 2008). Net-gunning will be performed by Quicksilver Air, Inc., or other qualified vendor selected by the Colorado Division of Wildlife (CDOW) through a request-for-proposal (RFP) process, which is the required procedure for selecting vendors to conduct helicopter work for CDOW. Quicksilver Air, Inc., has captured large samples of deer in Colorado during the past few years with capture-related mortality rates generally ≤ 2% (Anderson and Freddy 2008; Bergman et al. 2006, 2007, 2008; B. E. Watkins, CDOW, personal communication). Capture and Transport Methods: Wild mule deer will be pursued and netted by the helicopter net-gunning crew. The crew will consist of one pilot, one net-gunner, and ≤2 handlers. Netted animals will immediately be blind-folded and hobbled and transported by the helicopter to a nearby handling site. Deer will be placed inside the helicopter or slung underneath the helicopter during transport. At the handling site, CDOW personnel (i.e., handling crew) will record measurements, affix transmitters, and release each captured deer. Mule deer will be captured within 1−2 miles of the handling site to minimize the distance deer are transported. The handling crew will be ferried to appropriate handling sites by the helicopter pilot if vehicle access is limited in an area. Mule deer will be captured with net-guns in late February or early March in Game Management Unit (GMU) 22 in the Piceance Basin. In Meeker, Colorado, mid-late winter snow depths average roughly 12 cm, and rarely exceed 35 cm, where deer will be captured, and mean daily temperatures during late February have averaged –1 °C (30 °F) during recent decades. Under these conditions, mule deer can be captured safely without undue risk of hyperthermia. Maximum allowable pursuit time, or time necessary to chase and net a target animal, will vary given existing weather conditions and animal behavior. For example, in warmer conditions (e.g. >4°C), pursuit times will be minimized, particularly if unfavorable snow conditions are present. Total pursuit time will not exceed 8−10 minutes regardless of conditions, and will generally be less than 5 minutes. Individual deer will not be repeatedly chased. Large deer groups typically fracture upon the initial pursuit, thereby preventing the need to repeatedly chase the same individuals while still allowing the capture of >1 deer from the initial group. 92 �The helicopter pilot, fuel truck driver, and handling crew will be in radio contact with one another. In the event of an accident, the Meeker CDOW office will be contacted by radio, and necessary emergency services will be sent to the site. The ground crew will have direct radio access to the Rio Blanco County Sheriffs Office, Colorado State Patrol, and other emergency law enforcement channels. Training and Personnel: The helicopter net-gunning crew will be instructed as to procedures for minimizing stress and injury to the animals. Specifically, they will be instructed on pursuit times, transport distances, and safe handling procedures. The handling crew, comprised of CDOW personnel, will be instructed on proper care and handling procedures to minimize stress and risk of injury to the captured deer. Chad Bishop and Chuck Anderson will be ultimately responsible for all animal care and handling during the capture operation. Procedures and Manipulations of Animals: As stated above, netted animals will immediately be blind-folded, hobbled, and transported to the handling site. At the handling site, deer will be removed from the net and/or transport bag if present, and the blind-fold and hobbles will be checked. Deer will be radiocollared and aged by qualitatively evaluating height and wear of incisors and premolars. Radio collars will be of fixed-size and individually fitted to each animal. The following samples will be obtained from each deer: blood, hind foot length, chest girth, and weight. Blood samples will be collected using routine venipuncture for evaluating serum thyroid hormone concentrations and disease serology. Pregnancy status, number of fetuses, and body condition will also be determined using ultrasonography. Please refer to Appendix II for detailed handling procedures (Appendix II. Use of Ultrasonography and Vaginal Implant Transmitters in Adult Female Mule Deer to Capture Neonatal Fawns). If a captured deer suffers a broken leg, back, neck, pelvis, or other similar wound, it will be euthanized by deep anesthesia with the drug combination of ketamine or Telazol© and xylazine (IV or IM) with dosage based on estimated weight, followed by intravenous administration of KCl (~350 mg KCl/ml sterile water, dosed at >50 mg KCl/kg estimated body mass). In situations where administration of KCl is not feasible, then euthanasia will be performed via a gunshot to the head. Radiocollared mule deer will not be handled following capture, although they will be radiomonitored from both the ground and air on a routine basis. Except during the fawning period, deer will not be routinely relocated from the ground using VHF telemetry and therefore will not be regularly disturbed. During fawning in June, deer will be radiomonitored daily to determine when vaginal implant trasmitters are shed (see Appendix II. Use of Ultrasonography and Vaginal Implant Transmitters in Adult Female Mule Deer to Locate Neonatal Fawns). Literature Cited: Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2006. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2007. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. 93 �Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2008. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, USA. Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Conner, M. C., E. C. Soutiere, and R. A. Lancia. 1987. Drop-netting deer: costs and incidence of capture myopathy. Wildlife Society Bulletin 15:434−438. DelGiudice, G. D., B. A. Sampson, D. W. Kuehn, M. Carstensen Powell, and J. Fieberg. 2005. Understanding margins of safe capture, chemical immobilization, and handling of free-ranging white-tailed deer. Wildlife Society Bulletin 33:677−687. Potvin, F., and L. Breton. 1988. Use of a net gun for capturing white-tailed deer Odocoileus virginianus on Anticosti Island, Quebec. The Canadian Field Naturalist 102:697−700. Spraker, T. R. 1993. Stress and capture myopathy in artiodactylids. Pages 481−488 in M. E. Fowler, editor. Zoo and wild animal medicine: current therapy 3. W. B. Saunders, Philadelphia, Pennsylvania, USA. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. White, G. C., and R. M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248−252. 94 �APPENDIX II ULTRASONOGRAPHY AND VAGINAL IMPLANT TRANSMITTER PROTOCOLS FOR ADULT FEMALE MULE DEER AND NEONATAL FAWNS Background: For some time, radio-transmitter implants in the vaginas of deer have been considered as a technique for locating and capturing newborn fawns from radio-collared does immediately following parturition. Early attempts to employ this technique were largely unsuccessful in terms of both effectiveness and animal welfare (Garrott and Bartmann 1984, Giessman and Dalton 1984, Nelson 1984). This early technique used sutures to partially close the vulva in order to retain the transmitter in the vagina. Later, Bowman and Jacobsen (1998) developed and employed a modified vaginal implant transmitter (VIT) for white-tailed deer, with better success. This transmitter had plastic wings encased in silicone to retain the transmitter in the vagina until parturition; thus, no sutures were used. They found no indications that animals were negatively impacted by the newly designed VIT. Recent studies employing VITs have not identified any negative impacts to animals receiving VITs (Carstensen et al. 2003, Pamplin 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007), including a VIT study on elk focused exclusively on animal welfare (Johnson et al. 2006). Also, these studies do not indicate that VITs cause major problems with in utero fetus survival or birthing, particularly given the success of researchers at finding birth sites and fawns, occasionally from the same adult females over consecutive years. Furthermore, farmed deer in New Zealand with vaginal hormone implants with a similar design have not had any major reproduction problems (Asher and Smith 1987, Asher et al. 1988, Mylrea et al. 1992). Although the current VIT design apparently causes no harm to the animal, animals often expel VITs prior to parturition, which greatly reduces their utility. Thus, to achieve target sample sizes of newborn fawns, investigators must oversample adult females, causing excess animals to be captured, handled, and implanted with VITs. To reduce premature VIT expulsion, Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, lengthened the retention wings in 2004 from 58 mm to 68 mm by adding hard resin to the wing tips, which significantly improved VIT retention (S. P. Haskell, Texas Tech University, unpublished data). Since 2004, researchers employing VITs with the longer wings have not documented any ill effects in deer (ATS, unpublished data). Although retention improved and no ill effects have been observed, this aftermarket modification is not ideal. The modified wing tips are hard because of the resin addition and thus not ideal for placement in the vaginal canal. Ideally, any modification to the VIT wings should be incorporated into the manufacturing process. The retention wings must be manufactured using a production mold that costs a minimum of $15,000 to fabricate. We therefore obtained suitable funding and redesigned the VIT production mold. We lengthened the wing mold from 58 mm to 68 mm, consistent with the aftermarket modifications made to VIT wings beginning in 2004. We also widened the wings from 9 mm to 14 mm to increase the contact surface with the vaginal wall. During spring-summer 2008, we placed 6 prototypes of our newly-manufactured VITs in bighorn sheep ewes at the Foothills Wildlife Research Facility in Fort Collins, CO, where the penned sheep could be closely monitored. We documented no ill effects and all pregnant sheep retained their VITs until parturition. We do not anticipate that our VIT design modifications will pose a risk to animal welfare considering our pilot evaluation in sheep and recent deer studies that employed VITs with aftermarket alterations. In fact, the motivation for developing a new production mold was to improve animal welfare by eliminating the need for aftermarket alterations that create particularly hard wing surfaces. We will monitor fetal survival and neonatal production of all adult female deer receiving VITs to help document whether the newly designed VITs cause any negative effects. We will also monitor survival of the adult females and conduct a thorough necropsy of any deer that die. 95 �Aside from the VIT modifications, the protocols described herein are nearly identical to a protocol approved in the past (CDOW ACUC Project Protocol 1−2002). In this earlier study, we did not document any negative effects to deer associated with ultrasonography or VIT procedures. Also, neonatal fawn survival was higher among fawns captured from adult does that received VITs than fawns captured opportunistically from adult does that did not have VITs (Bishop et al. 2007). Vaginal implants allowed us to remotely monitor adult doe birthing status. If a VIT functioned correctly, we were generally able to capture the adult doe’s fawn(s) with only one disturbance event. In the absence of a VIT, when attempting to capture fawns from a targeted adult doe, we typically had to repeatedly locate and disturb the adult doe during the fawning period to capture her fawn(s). Capture and Transport Technique: Adult female mule deer will be captured in late February and/or early March via helicopter netgunning (Barrett et al. 1982, van Reenen 1982). Please refer to Appendix I. for a detailed helicopter netgunning capture protocol (Appendix I. Helicopter Net-gunning Capture and Handling Protocol for Mule Deer). Net-gunned deer will be blind-folded, hobbled, and ferried a short distance to a handling site. Procedures and Manipulations of Animals: We will use ultrasonography to determine pregnancy status (yes/no), fetal count (# fetuses), and body condition (see below). Additionally, we will measure weight, chest girth, hind foot length, and age (based on tooth replacement and wear). We will collect a blood sample using routine venipuncture. If an adult female is pregnant, we will place a nylon radio-collar around the neck and insert a VIT in the vagina posterior to the cervix. Vaginal implant insertion procedures are explained in detail below. Total handling time for an individual deer will typically be ~15 minutes and will not exceed 25 minutes. We will cease manipulations/data collection at any point the welfare of the deer is in question and immediately begin administering fluids, oxygen, or any other warranted procedure under the guidance of CDOW’s attending veterinarian. Ultrasonography: We will use ultrasonography to determine body condition, diagnose pregnancy, and quantify fetal numbers of each mule deer. Body condition will be measured to meet other research objectives (Anderson and Freddy 2008). Body condition methods are briefly repeated here for completeness. We will measure maximum subcutaneous fat thickness on the rump and thickness of the longissimus dorsi muscle of each doe using a SonoVet 2000 portable ultrasound unit (Universal Medical Systems, Bedford Hills, NY) with a 5 MHz linear transducer (Stephenson et al. 1998, 2002; Cook et al. 2001; Bishop 2007). A small area of hair will be plucked at each measurement point and lubricant will be used to enhance contact between the transducer and skin. The 2 plucked areas will be ≤15 cm long by ≤5 cm wide. We will determine a body condition score (BCS) for each deer by palpating the rump (Cook et al. 2001, 2007). We will combine ultrasound measurements with the BCS score to estimate body fat of each deer (Cook et al. 2007). We will quantify reproductive status using a SonoVet 2000 portable ultrasound unit (Universal Medical Systems, Bedford Hills, NY) with a 3 MHz linear transducer. We will shave the left side of the abdomen and apply lubricant to facilitate transabdominal scanning (Stephenson et al. 1995, Bishop 2007, Bishop et al. 2007). Specifically, we will shave an area covering the haired portion of the left ventral abdomen that is 20 cm wide; the area is bounded by the caudal rib cranially, the inguinal fold caudally, and the ventral midline. Both uterine horns will be systematically scanned to identify fetal numbers ranging from 0 to 3. 96 �Vaginal Implant Transmitter (VIT) and Insertion Technique: Refer to the attached study plan for detailed specifications of VITs to be used in this study. Prior to insertion, we will sterilize VITs in a chlorhexidine solution, rinse them with sterile saline solution, allow them to air-dry, and seal them in air- and water-tight pouches. This will guarantee cleanliness of VITs up until the moment they are placed in deer. We will insert VITs using a clear, plastic swine vaginoscope (Jorgensen Laboratories, Inc., Loveland, Colo.) and alligator forceps. The vaginoscope is 15.2 cm long with a 1.59 cm internal diameter and has a smoothed end to minimize vaginal trauma. We will gauge approximate insertion distance from extensive experience gained on the Uncompahgre Plateau (Bishop et al. 2007). We will place vaginoscopes and alligator forceps in cold sterilization containers with chlorhexidine solution between each use and use a new pair of nitrile surgical gloves to handle the vaginoscope and VIT for each deer, and we will apply a lidocaine cream to the deer’s vagina prior to insertion. To insert a VIT, we will fold the silicone wings together and place the VIT into the end of the vaginoscope. We will liberally apply sterile KY Jelly to the scope and insert it into the vaginal canal until the tip of the VIT antenna is approximately flush with the vulva. We will use the alligator forceps, which extend through the vaginoscope, to firmly hold the VIT in place while the scope is pulled out from the vagina. The tip of the antenna, which may protrude up to 1.5 cm past the vulva, is encapsulated is a resin bead to protect the deer from its sharp edge. Post-Implantation Monitoring: From March through May, we will regularly monitor the radio collar and VIT signals of the adult does in our sample. Monitoring will allow us to document any VITs that shed early and the opportunity to perform a necropsy on mortalities. The latter will allow us to evaluate whether VITs caused any tissue irritation or other impact to the adult doe. Fetus Survival and Neonate Capture: During each morning of June we will check VIT signal status by aerially locating each radiocollared doe having a VIT, weather permitting. We will also radiomonitor VIT signals from the ground as logistically feasible. When we detect a fast (i.e., postpartum) pulse rate, we will use VHF receivers and directional antennae from the ground to simultaneously locate the VIT and radio-collared doe, which should be in proximity to one another. We will attempt to observe behavior of the collared doe, establish whether the VIT is shed at a birth site, and search for fawns in the vicinity of the doe and expelled VIT. If the doe has moved away from the VIT (i.e., >200 m), we will locate the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawn(s) were present and subsequently locate the collared doe to search for fawns at her location. We will attempt to account for each doe’s fetus(es) measured in February as live or stillborn fawns. We will not radiocollar or handle newborn fawns. Thus, once a neonate is located, we will back away and leave the neonate undisturbed. If a VIT is shed prior to parturition, we will radiolocate the adult doe no more than once per day on each successive day and search for fawns in an attempt to determine approximately when the doe actually gives birth. This will allow us to determine how many days a VIT shed prematurely. Neonate searches will typically last up to 30−45 minutes and will not exceed 1 hour. Past deer neonatal studies have reported minimal or no abandonment as a result of neonate capture, handling, and marking (Carstensen et al. 2003, Pojar and Bowden 2004, Bishop 2007). Powell et al. (2005) found no evidence of markinginduced abandonment, and they found that handling time and age-at-capture had no impact on neonatal survival. We therefore do not anticipate that our neonate searches will cause any direct or indirect harm to the neonates or their dams, particularly since we will not be handling fawns. 97 �Literature Cited: Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Study Plan, Colorado Division of Wildlife, Fort Collins, USA. Asher, G. W., and J. F. Smith. 1987. Induction of oestrus and ovulation in farmed fallow deer (Dama dama) by using progesterone and PMSG treatment. Journal of Reproduction and Fertility 81:113−118. Asher, G. W., J. L. Adam, R. W. James, and D. Barnes. 1988. Artificial insemination of farmed fallow deer (Dama dama): fixed-time insemination at a synchronized oestrus. Animal Production 47:487−492. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108−114. Bishop, C. J. 2007. Effect of enhanced nutrition during winter on the Uncompahgre Plateau mule deer population. Dissertation, Colorado State University, Fort Collins, USA. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bowman, J. L., and H. A. Jacobson. 1998. An improved vaginal-implant transmitter for locating whitetailed deer birth sites and fawns. Wildlife Society Bulletin 26:295−298. Carstensen, M., G. D. DelGiudice, and B. A. Sampson. 2003. Using doe behavior and vaginal-implant transmitters to capture neonate white-tailed deer in north-central Minnesota. Wildlife Society Bulletin 31:634−641. Cook, R. C., J. G. Cook, D. L. Murray, P. Zager, B. K. Johnson, and M. W. Gratson. 2001. Development of predictive models of nutritional condition for Rocky Mountain Elk. Journal of Wildlife Management 65:973−987. Cook, R. C., T. R. Stephenson, W. L. Myers, J. G. Cook, and L. A. Shipley. 2007. Validating predictive models of nutritional condition for mule deer. Journal of Wildlife Management 71:1934−1943. Garrott, R. A, and R. M. Bartmann. 1984. Evaluation of vaginal implants for mule deer. Journal of Wildlife Management 48:646−648. Giessman, N. F., and C. J. Dalton. 1984. White-tailed deer fawn mortality in the southeastern Missouri Ozarks. Missouri Department of Conservation, Jefferson City, Pittman-Robertson Project W-13R-35. Johnson, B. K., T. McCoy, C. O. Kochanny, and R. C. Cook. 2006. Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Mylrea, G. E., A. W., English, R. C. Mulley, and G. Evans. 1992. Artificial insemination of farmed chital deer. Pages 334−337 in R. D. Brown, editor. The Biology of Deer. Springer-Verlag, New York, New York, USA. Nelson, T. A. 1984. Production and survival of white-tailed deer fawns on Crab Orchard National Wildlife Refuge. Thesis, Southern Illinois University, Carbondale, IL, USA. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Powell, M. C., G. D. DelGiudice, and B. A. Sampson. 2005. Low risk of marking-induced abandonment in free-ranging white-tailed deer neonates. Wildlife Society Bulletin 33:643−655. 98 �Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557−564. Stephenson, T. R., K. J. Hundertmark, C. C. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717−722. Stephenson, T. R., J. W. Testa, G. P. Adams, R. G. Sasser, C. C. Schwartz, and K. J. Hundertmark. 1995. Diagnosis of pregnancy and twinning in moose by ultrasonography and serum assay. Alces 31:167−172. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, Wisconsin, USA. 99 �100 �Colorado Division of Wildlife July 2008 – June 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 2 Federal Aid Project No. W-185-R : : : : Division of Wildlife Mammals Research Deer Conservation Evaluation of Winter Range Habitat Treatments On Over-winter Survival and Body Condition of Mule Deer Period Covered: July 1, 2008 - June 30, 2009 Author: E.J. Bergman; project cooperators, C.J. Bishop, D.J. Freddy and G.C. White Personnel: C. Anderson, L. Baeten, D. Baker, B. Banulis, J. Boss, A. Cline, D. Coven, M. Cowardin, K. Crane, R. Del Piccolo, B. deVergie, B. Diamond, K. Duckett, S. Duckett, J. Garner, D. Hale, C. Harty, A. Holland, E. Joyce, D. Kowalski, B. Lamont, R. Lockwood, S. Lockwood, D. Lucchesi, D. Masden, J. McMillan, M. Michaels, G. Miller, Mike Miller, Melody Miller, C. Santana, M. Sirochman, T. Sirochman, M. Stenson, R. Swygman, C. Tucker, D. Walsh, S. Waters, B. Watkins, P. Will, L. Wolfe, V. Yavovich, K. Yeager, M. Zeaman CDOW, L. Carpenter - Wildlife Management Institute, D. Felix, L. Felix - Olathe Spray Service, P. Johnston, M. Keech, D. Rivers, J. Rowe, L. Shelton, M. Shelton, R. Swisher, S. Swisher - Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We completed the fourth and final year of a multi-year, multi-area study to assess the impacts of landscape level winter range habitat improvement efforts on mule deer population performance. This study took place on the Uncompahgre Plateau and in adjacent valleys in southwestern Colorado. Data collection and analysis for the fourth year were consistent with those of the pilot study and first three years of this study. We measured over-winter fawn survival and total deer density on 4 annual study areas, as well as on a fifth variable area that had previously not been involved in the study. Additionally, on 2 of the study areas we estimated body condition of does. Compared to results from other research throughout the West, as well as on the Uncompahgre Plateau, survival estimates for 6-month old mule deer fawns were highly variable between areas, and tended to be near published long term averages (mean survival rate of 0.59 (0.04 SE)). Survival rates for the fourth year of the study were lower than all previous years, which was surprising given casual observation of winter severity. However, preliminary evidence continues to suggest that areas that have received habitat treatments have higher fawn survival. Based on estimates of total body fat for adult female deer, there was a slight distinction between treatment and reference study areas. Point estimates of deer density on the 5 study areas during the winter of 20082009 varied from estimates collected during other winters, but in general density estimates have shown a consistent trend between all winters of the study. Major fluctuations within density estimates are likely attributable to animal movements. 101 �WILDLIFE RESEARCH REPORT EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER ERIC J. BERGMAN P.N. OBJECTIVE To experimentally assess whether mechanical/chemical treatments of native habitat vegetation will increase over-winter mule deer fawn survival, adult doe body condition, and localized deer densities on the Uncompahgre Plateau in southwest Colorado. SEGMENT OBJECTIVES 1. Capture and radio-collar the minimum necessary sample (n=25) of 6 month-old fawns between November and early-January in each of 5 study areas. 2. Measure over-winter fawn survival from mid-December through mid-June. 3. Estimate late-winter deer densities in each study area via helicopter resighting of marked deer. 4. Capture and sample a minimum number of adult female deer (n=30) to estimate late-winter body condition in 2 study areas. INTRODUCTION A common trend among many terrestrial, mammalian systems is a tendency to cycle between population highs and lows (Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001, Clutton-Brock and Pemberton 2004). While the true cause of these cycles is likely a merger of habitat quality, weather, disease, predation, sport hunting, competition and community population dynamics, it is often necessary or intriguing for wildlife managers and ecologists to identify the primary limiting factor to population growth. Without exception, mule deer populations have also demonstrated a tendency to show large fluctuations. Several dramatic declines have been observed since the turn of the 19th century (Connolly 1981, Gill 2001, Hurley and Zager 2004). However, only one period of increase, a general trend during the 1940's and 1950's, has been noted. The most recent and pressing decline took place during the 1990's (Unsworth et al. 1999). Colorado has not escaped these tendencies, with certain parts of the state experiencing population declines by as much as 50% between the 1960's and present time (Gill 2001, B. Watkins personal communication). Primarily due to the value of mule deer as a big game hunting species, wildlife managers' challenges are two-fold: understanding the underlying causes of mule deer population change and managing populations to dampen the effects of these fluctuations. In Colorado, the role of habitat as the limiting factor for mule deer populations was recently tested. Specifically, the role of forage quality and quantity on over-winter fawn survival was tested using a treatment/reference cross-over design with ad libitum pelleted food supplements as a substitute for instantaneous high quality habitat improvements (Bishop et al. 2009). The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e. if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the primary limiting factor on populations. As such, nutrition enhancement treatments increased fawn survival rate by 0.22 (Bishop et al. 2009). This research effectively identified some of the underlying processes in mule deer population regulation, but did not test the effectiveness of acceptable habitat management techniques. Due to the undesirable effects of feeding wildlife (e.g. artificially elevating density, increased potential for disease transmission and cost), a more appropriate technique for achieving a high quality nutrition enhancement needs to be assessed. 102 �Based on this past research and the above mentioned objectives, we designed and initiated a multi-year, multi-area study to assess the impacts of landscape level winter range treatments on mule deer population performance. This study is being conducted on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado. Due to the active habitat treatment history in this area, the Uncompahgre Plateau stood out as the most opportune place for addressing these issues. Additionally, there are several tracts from 2 state wildlife areas that are located in key locations, thereby allowing additional habitat treatments to occur on the level and schedule necessary of this project. To assess the impacts of habitat treatments on mule deer in these areas, we are measuring over-winter fawn survival, mule deer density and late winter body condition. STUDY AREA At the onset of this study (Bergman et al. 2005), we identified 2 pairs of treatment/reference study areas, stratified into historically known high and low deer density areas. The selection process for these pairs of experimental units followed several strict guidelines: 1) Treatment/reference units could not be further than 10km apart, but needed to have adequate buffer to minimize the movement of animals between the treatment and reference areas. 2) Reference study areas could not have received any mechanical treatment during the past 30 years. 3) Strata were defined by winter range type (all experimental units had to be in pinyon/juniper winter range) and deer density. 4) Treatment units needed to have received mechanical treatment in the past, but also had to be capable of receiving further treatments during the study period. Each winter a 5th study area was added to increase the level of inference that could be drawn from this study. For each of the 4 winters covering the study period, this 5th study area shifted between 4 randomly selected areas. The treatment history on each of these additional study areas varied, but was representative of what can be expected of typical winter-range treatments. During the first winter of this study, this 5th study area fell on Shavano Valley. Treatments on Shavano Valley were primarily composed of roller-chopping and reseeding of browse species in the higher pinyon/juniper range. During the second winter of the study, the 5th study area fell on the Colona Tract (~5km2) of Billy Creek State Wildlife Area (approximately 15km south of Montrose, CO). The treatment history of Colona Tract was primarily composed of brush mowing and chemical control of weeds and dry land fertilization of preferred species. During the third winter of the study, the 5th study area was located at McKenzie Buttes. The treatments at McKenzie Buttes were slightly older (10-15 years) and were also composed of rollerchopping. During the final year of the study, the 5th study area was located at Transfer Road. The treatments available to deer at Transfer were younger (1-2 years) and were composed of hydro-ax and some roller-chopping. The high density treatment area is located on the Billy Creek tract of Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). The high density reference area is located around Beaton Creek (approximately 15km south of Montrose, CO and approximately 5km north of Billy Creek State Wildlife Area). Both of the high density study areas are located in GMU 65 (DAU D-40). The low density treatment area is located on Peach Orchard Point, on/near Escalante State Wildlife Area (approximately 25km southwest of Delta, CO). The low density reference area is located on Sowbelly and Tatum draws (approximately 25km west of Delta, CO and approximately 8km from Peach Orchard Point). Both of the low density study areas are located in GMU 62 (DAU D-19). All of the other study areas, mentioned above, were also located in GMU 62 (DAU D-19) to the west of Montrose, CO. 103 �METHODS Twenty-five mule deer fawns were captured and radio-collared in each of the 5 study areas. Fawns were captured via baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) and helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) between mid-November and lateDecember. To make fawn collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars after approximately 6 months. On a daily basis, from December through May, we monitored the radioed fawns in order to document live/death status. This allowed us to determine accurately the date of death and estimate the proximate cause of death. Daily monitoring was done from the ground to maximize efficient collection of mortalities and assessment of cause specific mortality. Weekly aerial telemetry flights were conducted to insure that all deer were heard at least once a week, allowing weekly survival estimates for each study area. To estimate body condition, an additional 30 adult female deer were captured via helicopter netgunning and fitted with temporary neckbands, in late-February within each of the 2 high density study areas. For body condition work, we relied on methods that employed the use of ultrasonography to estimate total body fat (Stephenson et al. 1998, Cook 2000, Stephenson et al. 2002). Blood samples were also collected for endocrinology and pregnancy tests. During late winter (early-March) we estimated deer density on each of our study areas. Helicopter based mark-resight techniques were used for density estimation (Gill 1969, Bartmann et al. 1986, Kufeld et al. 1980, Freddy et al. 2004). Preliminary survival analyses were conducted on all years of data. In addition to including individual covariates (fawn sex and mass), we explored the role of habitat treatment history on survival. Due to the preliminary nature of these analyses and the ongoing status of the habitat treatment work, we did not attempt to rank individual study areas. Estimating survival for study areas was done in 5 different forms. The simplest form was constant survival where all study areas were pooled and survival was estimated using a single parameter (hereafter “constant”). The second simplest form was to estimate survival for each unique study area (i.e., 8 survival estimates were generated, hereafter “area”). The remaining 3 forms allowed study areas to be partitioned according to treatment history. The simplest of these forms was a comparison between treatment areas and reference study areas in which each study areas was partitioned into one of these two categories (i.e., two survival parameters, hereafter “treatment/reference”). The next simplest of these forms segregated study areas by treatment type. In this form, study areas were either reference areas (no treatment), management treatments (areas that received a typical management treatment at some point during the past 10 years), or repeated treatments (areas that received a typical management treatment but also received additional and repeated efforts in an attempt to force treatment effect). Thus, in this form (hereafter “treatment type”), the number of parameters dedicated to estimating survival rates across all study areas was 3. The final form followed the “treatment type” form, but further partitioned study areas according to a density/treatment gradient. A total of 5 parameters were used to estimate survival (high-density repeated treatment, high-density reference, management treatment, low-density super treatment and low-density reference, hereafter “treatment type by density”). All survival models were evaluated in program MARK using the known-fate model type with logit link function (White and Burnham 1999). All models were compared using Akaike's Information Criterion corrected for small sample size (Burnham and Anderson 2003). 104 �RESULTS AND DISCUSSION Minimum desired sample sizes were met in all study areas for all components of this research (n = 25 fawns per area for survival work, n = 30 adult females in two areas for body condition assessment). With the exception of a single fawn, all deer were captured via helicopter net-gunning during the fourth year of the study. Capture related mortalities occurred on 1 of 184 occasions (0.54%, 1 adult female, spinal injury). Two fawns died of predation within 1week of capture and were censored from the survival analysis due to the potential that effects of capture were still in place. An additional three fawns slipped their radio collars within a week of capture and were also censored. Mean mass of all fawns was 35.1 kg and the observed sex ratio for the sample was 61 males to 64 females (Table 1). Estimates of fawn survival collected during previous years of this study tended to be above average compared to results from other research throughout the West, as well as on the Uncompahgre Plateau. However, survival rates during the fourth year of the study were noticeably lower. Across our 5 study areas, estimated survival rates ranged between 0.38 (0.10 SE) and 0.65 (0.10 SE), with a mean survival rate of 0.59 (0.04 SE) (Table 2). While these rates are lower than those measured during previous winters, they remain higher than long term averages reported in the literature (Unsworth et al. 1999). Of note, winter conditions across the state of Colorado tended to be less harsh than those observed during the previous year and survival rates were expected to have been higher during the 2008-2009 winter. Also of note, survival rates in one of our reference (i.e., non-treated) study areas (Buckhorn) was dramatically lower than in its paired treatment study area (Billy Creek). While this trend has been consistent, during previous years of the study the difference between these two study areas was not so dramatic. Survival rates in our low-density study areas were quite comparable to our high-density study areas. During previous winters, the low-density study areas tended to have higher survival. Preliminary survival models indicate that the individual parameter most influencing over-winter fawn survival continues to be fawn mass (Table 3). Fawn sex did not appear to add much additional strength or support to any given model. Of particular interest to this study is that models incorporating study area treatment level were among the top performing models for the entire suite of models run, and the most supported model took treatment type by density into account. Closely competing with this model was one which estimated a constant survival rate, but thereby benefited by estimating 4 fewer parameters. The strongest model support for the model that estimated survival rates according to the treatment type by density structure lends credence to the study design and will likely become refined with a more complete analysis. Late winter body condition estimates for adult females during the winter of 2008-2009 were consistent with those collected during previous years of this study, but also tended to be higher than those estimates during previous research on the Uncompahgre Plateau (Bishop et al. 2009 and C.J. Bishop, personal communication). The lowest single total percent body fat estimate for this study was recorded during this winter, despite the fact that observations of winter severity indicated that body fat estimates likely should have been higher. For the two study areas where body condition estimates were measured, they did have a tendency to reflect the same trends that were observed in survival estimates. However, as has been the case in the past, there was no apparent statistical distinction in total percent body fat between our study areas. This lack of distinction was also observed in the levels of the T3 hormone, but not in the T4 hormone (nmol/l) (Table 4). Pregnancy rates, based on ultrasonography and/or PSPB, tended to be slightly higher than those observed during the previous year, but not as high as those observed during the first two years of the study. Past rates ranged between 90% and 95%, whereas rates for this past winter were 90% (Buckhorn) and 87% (Billy Creek). During the winter of 2007-2008, pregnancy rates were estimated to be 80% (Buckhorn) and 87% (Billy Creek). 105 �Density estimates were collected during March for all five study areas (Figure 1). No major modifications were made to the methodology, although the number of marked animals in Billy Creek and Buckhorn has decreased since 2007 due to mortality of adult female deer. As such, the precision of estimates for these two was expected to decline. Additionally, during the two week period preceding the density estimation flights, deer in the Buckhorn study area started moving up in elevation into transition range. Similar shifts were not observed in the other study areas, but in Buckhorn it was quantified through relocation of radio-marked animals. Relying on this approach, we estimated that 47% of the deer on Billy Creek had moved off of the study area prior to the density estimation flights, explaining the marked drop in total number of deer on that study area. No major shifts in deer density were observed in Billy Creek, Peach Orchard or Sowbelly. SUMMARY Survival rates for mule deer fawns across our study areas averaged 59% with a measured high of 65% and measured low of 38%. Overall body condition parameter estimates for late-winter adult female deer were moderately low, which did not coincide with the milder winter conditions that were observed throughout deer winter range in Colorado. Pregnancy rates were slightly lower, but still within the long term range of observed data. Estimates of total deer density across our study areas continued to reflect historical estimates, but a dramatic early spring shift in movement was observed on one study area. Overall, a consistent trend of higher survival of fawns was observed in treated study areas, indicating winter range treatments likely have a positive effect on survival. The magnitude and overall population effect of these impacts will be quantified during the next 12-18 months. LITERATURE CITED Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M., L.H. Carpenter, R.A. Garrott, and D.C. Bowden. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. —————, G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. Bergman, E.J., C.J. Bishop, D.J. Freddy, G.C. White. 2005. Pilot evaluation of winter range habitat treatments of mule deer fawn over-winter survival. Wildlife Research Report July: 23-35. Colorado Division of Wildlife, Fort Collins, USA. Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172. Burnham, K.P. and D.R. Anderson. 2003. Model selection and multi-model inference. Springer, New York, USA. Clutton-Brock, T., and J. Pemberton, editors. 2004. Soay sheep: dynamics and selection in an island population. Cambridge University Press, UK. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. Cook, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain Elk. Thesis, University of Idaho, Moscow, USA. Freddy, D.J., G.C. White, M.C. Kneeland, R.H. Kahn, J.W. Unsworth, W.J. DeVergie, V.K. Graham, J.H. Ellenberger, and C.H. Wagner. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. Gill, R.B. 1969. A quadrat count system for estimating game populations. Colorado Division of Game, Fish and Parks, Game Information Leaflet 76. Fort Collins, USA. 106 �————— 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Hurley, M., and P. Zager. 2004. Southeast mule deer ecology - Study I: Influence of predators on mule deer populations. Progress Report, Idaho Department of Fish and Game, Boise, USA. Jedrzejewska, B., and W. Jedrzejewski. 1998. Predation in Vertebrate Communities: the Białowieża Primeval Forest as a case study. Springer-Verlag, Berlin, Germany. Krebs, C.J., S. Boutin, and R. Boonstra, editors. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. Kufeld, R.C., J.H. Olterman, AND D.C. Bowden. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. Ramsey, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. Schmidt, R.L., W.H. Rutherford, and F.M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. Stephenson, T.R., V.C. Bleich, B.M. Pierce, and G.P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. ————— , T. R., K. J. Hundertmark, C. C. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717722. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G.C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Prepared by Eric J. Bergman, Wildlife Researcher 107 �Table 1. Mean mass (n) and sex of mule deer fawns captured on the Uncompahgre Plateau from lateNovember through early-January of each year, 2005-2006, 2006-2007, 2007-2008, and 2008-2009. All fawns were captured by baited drop-nets or helicopter net-gunning. Mass is reported in kg. Area Billy Creek Buckhorn Shavano Peach Orchard Sowbelly Billy Creek Buckhorn Colona Peach Orchard Sowbelly Billy Creek Buckhorn McKenzie Peach Orchard Sowbelly Billy Creek Buckhorn Transfer Peach Orchard Sowbelly Year 2005 2005 2005 2005 2005 2006 2006 2006 2006 2006 2007 2007 2007 2007 2007 2008 2008 2008 2008 2008 Males 37.1 (14) 37.4 (11) 39.4 (11) 37.0 (11) 37.1 (16) 38.3 (12) 36.7 (10) 38.1 (12) 37.0 (13) 44.3 ( 8) 36.0 (13) 37.8 ( 6) 36.8 (15) 37.3 ( 9) 38.6 (11) 37.2 (13) 36.4 (12) 36.8 (13) 37.9 (10) 36.7 (13) Females 32.0 (11) 35.0 (15) 37.2 (14) 35.3 (14) 34.2 (9) 34.4 (12) 34.7 (15) 32.5 (12) 35.5 (12) 35.5 (15) 36.3 (12) 34.8 (18) 34.3 ( 8) 33.5 (16) 35.1 (14) 34.4 (12) 31.7 (13) 32.0 (12) 35.0 (15) 33.2 (12) Total 34.9 (25) 36.0 (26) 38.2 (25) 36.1 (25) 36.1 (25) 36.5 (25) 35.5(25) 35.4 (24) 36.3 (25) 38.7 (25) 36.1 (25) 35.5 (25) 36.0 (23) 34.9 (25) 36.7 (25) 35.9 (25) 34.0 (25) 34.5 (25) 36.2 (25) 35.0 (25) Table 2. Over-winter mule deer fawn survival rates for study areas across the Uncompahgre Plateau during the 4-year study. Billy Creek, Peach Orchard, Colona, Shavano and McKenzie Buttes represent treatment areas. Buckhorn and Sowbelly are reference areas. Peach Orchard and Sowbelly are considered low-density study areas. Deer reflected by the category ‘Other’ represent deer that were captured on transition range, with the hope that they would migrate onto the Sowbelly study area, but alternatively migrated into an area not formally designated as a study area. 2005-2006 2006-2007 2007-2008 2008-2009 Area Ŝ (S.E.) Ŝ (S.E.) Ŝ (S.E.) Ŝ (S.E.) Billy Creek 0.83 (0.76) 0.72 (0.09) 0.71 (0.09) 0.60 (0.10) Buckhorn 0.76 (0.88) 0.63 (0.10) 0.59 (0.10) 0.38 (0.10) Colona N.A. 0.68 (0.09) N.A. N.A. Shavano 0.76 (0.85) N.A. N.A. N.A. McKenzie Buttes N.A. N.A. 0.61 (0.11) N.A. Transfer N.A. N.A. N.A. 0.63 (0.10) Peach Orchard 0.88 (0.65) 0.92 (0.05) 0.79 (0.08) 0.60 (0.11) Sowbelly 1.00 (0.00) 0.88 (0.07) 0.70 (0.19) 0.65 (0.10) Other 0.83 (1.08) N.A. 0.36 (0.13) N.A. 108 �Table 3. Preliminary survival model results for radio collared fawns on the Uncompahgre Plateau for the winters of 2005-2006, 2006-2007 and 2007-2008. Model AICc ∆AICc ωi k ŝ (Treatment Type by Density) + mass 1293.577 0.000 0.255 6 ŝ (Constant) + mass 1294.706 1.129 0.145 2 ŝ (Treatment Type by Density) + sex + mass 1294.712 1.135 0.145 7 ŝ (Treatment/Reference) + mass 1295.336 1.759 0.106 3 ŝ (Treatment Type) + mass 1295.557 1.980 0.095 4 ŝ (Constant) + sex + mass 1295.724 2.147 0.087 3 ŝ (Treatment/Reference) + sex + mass 1296.047 2.470 0.074 4 ŝ (Treatment Type) + sex + mass 1296.457 2.880 0.060 5 ŝ (Area) + mass 1298.547 4.970 0.021 9 ŝ (Area) + sex + mass 1299.686 6.109 0.012 10 ŝ (Treatment Type by Density) 1319.598 26.021 0.000 5 ŝ (Treatment Type by Density) + sex 1320.269 26.693 0.000 6 ŝ (Area) 1323.900 30.324 0.000 8 ŝ (Area) + sex 1324.675 31.098 0.000 9 ŝ (Constant) 1324.726 31.149 0.000 1 ŝ (Treatment Type) 1324.915 31.338 0.000 3 ŝ (Constant) + sex 1325.300 31.723 0.000 2 ŝ (Treatment/Reference) 1325.317 31.741 0.000 2 ŝ (Treatment Type) + sex 1325.545 31.968 0.000 4 ŝ (Treatment/Reference) + sex 1326.176 32.599 0.000 3 Table 4. Late-winter body condition estimates for female adult mule deer on the Uncompahgre Plateau in 2 study areas each year of study, 2005-2009. Sample sizes were 30 does in each area. Mean T3 and T4 samples are reported in nmol/l. Parameters marked with an asterisk designate a significant difference between areas at the 0.05 level. Year 2005-2006 2006-2007 2007-2008 2008-2009 Parameter % Body Fat T3* T4 % Body Fat T3 T4 % Body Fat T3 T4* % Body Fat T3 T4* Billy Creek 8.80% (2.02) 1.12 (0.28) 70.69 (20.94) 7.61% (1.94) 1.55 (0.53) 88.23 (19.53) 8.09% (1.10) 1.17 (0.28) 94.30 (20.7) 7.20% (1.85) 1.22 (0.32) 74.63 (14.61) 109 Buckhorn N.A. N.A. N.A. 7.03% (1.80) 1.42 (0.31) 78.07 (22.34) 7.20% (1.69) 1.17 (0.56) 56.20 (23.30) 6.25% (1.63) 1.26 (0.35) 54.77 (19.34) Sowbelly 9.81% (2.88) 1.41 (0.51) 79.97 (15.80) N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. �Figure 1. Mule deer density estimates for the 4 permanent study areas. Clear boxes reflect data from the 2005-2006 winter, light grey boxes reflect data from the 2006-2007 winter, grey boxes reflect data from the 2007-2008 winter, and dark gray boxes reflect 2008-2009. Error bars represent the 95% confidence intervals for density estimates. 110 �Colorado Division of Wildlife July 2008 − June 2009 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 6 Federal Aid Project: W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Population Performance of Piceance Basin Mule Deer in Response to Natural Gas Resource Extraction and Mitigation Efforts to Address Human Activity and Habitat Degradation : Period Covered: July 1, 2008 − June 30, 2009 Author: C. R. Anderson Personnel: D. Alkire, E. Bergman, C. Bishop, J. Broderick, B. deVergie, D. Finley, C. Flickinger, D. Freddy, L. Gepfert, K. Kaal, L. Kelly, T. Knowles, P. Lendrum, P. Lukacs, B. Marsh, M. Reitz, T. Segal, K. Taylor, R. Velarde, CDOW; E. Hollowed, BLM; S. Monsen, Western Ecological Consulting, Inc.; G. White, Colorado State University; R. Swisher, Quicksilver Air, Inc. Project support received from Federal Aid in Wildlife Restoration, Colorado Mule Deer Association, Colorado Mule Deer Foundation, Colorado Oil and Gas Conservation Commission, Colorado State Severance Tax Fund, EnCana Corp., Shell Petroleum, and Williams Production LMT Co. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT I propose to experimentally evaluate habitat treatments that may improve the landscape to benefit mule deer (Odocoileus hemionus) and evaluate human-activity management alternatives to reduce the disturbance of energy development impacts on mule deer. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas within the state. The data presented here represent the first pretreatment year of a long-term study addressing habitat modifications and improved energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. I selected 5 winter range study areas representing varying levels of development to serve as treatment (Ryan Gulch and Magnolia) and control (Yellow Creek, Story/Sprague, and North Ridge) sites and recorded habitat use and movement patterns using GPS collars (5 locations/day), estimated overwinter fawn and adult female survival, estimated late winter body condition of adult females using ultrasonography, and estimated abundance using helicopter mark-resight surveys. I attached 250 VHF collars (50/study area) to fawns in early December 2008 and 150 VHF (10/study area) and GPS (20/study area) collars to adult female mule deer in late February—early March 2009. In comparing the data among study areas this first year, Story/Sprague deer appear to be in better physical condition than deer from the other winter ranges examined. Migration patterns were similar among 4 of the 5 areas, but Story/Sprague deer traveled shorter distances and spent less time on winter range. Yellow Creek fawns were lighter than 111 �other study areas and exhibited the lowest survival of the areas investigated. North Ridge deer exhibited the highest winter range density and Magnolia and Ryan Gulch deer exhibited the lowest densities. Reasons for these differences are currently unknown, but could be related to several factors including relative habitat conditions, duration on and distance to seasonal ranges, and extent of human activity throughout occupied habitats. Meaningful comparisons will be evident once treatments are implemented and comparisons are possible between areas that are manipulated (treatment areas; Ryan Gulch and Magnolia) and those that are not (control areas: Yellow Creek, Story/Sprague, and North Ridge). This project will require additional funding commitments and cooperative agreements beyond spring 2010 from private industry, the BLM, and the CDOW to assess if sustainable mule deer populations can persist within a highly disturbed landscape following implementation of beneficial habitat treatments and development practices. 112 �WILDLIFE RESEARCH REPORT POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION CHARLES R. ANDERSON, JR. P. N. OBJECTIVES 1. To determine experimentally whether enhancing mule deer habitat conditions on winter and/or transition range elicits behavioral responses, improves body condition, increases overwinter fawn survival, or ultimately, population density on mule deer winter ranges exposed to extensive energy development. To determine experimentally to what extent modification of energy development practices enhance habitat selection, body condition, over-winter fawn survival, and winter range mule deer densities. 2. SEGMENT OBJECTIVES 1. Collect and reattach GPS collars (5 fixes/day) to maintain sample sizes for addressing mule deer 2. 3. 4. 5. habitat use and behavior patterns in 5 study areas experiencing varying levels of energy development of the Piceance Basin, Colorado. Estimate late winter body condition of adult female mule deer in each of the 5 winter herd segments Monitor over-winter survival of fawn and adult female mule deer by daily ground tracking and bi-weekly aerial tracking. Conduct Mark-Resight helicopter surveys to estimate mule deer abundance in each study area. Summarize data and present information in an annual Job Progress Report. INTRODUCTION Extraction of natural gas from areas throughout western Colorado has raised concerns among many public stakeholders and the Colorado Division of Wildlife that the cumulative impacts associated with this intense industrialization will dramatically and negatively affect the wildlife resources of the region. Concern is especially high for mule deer due to their recreational and economic importance as a principal game species and their ecological importance as one of the primary herbivores of the Colorado Plateau Ecoregion. Extraction of natural gas will directly affect the potential suitability of the landscape used by mule deer through conversion of native habitat vegetation with drill pads, roads, or noxious weeds, by fragmenting habitat because of drill pads and roads, by increasing noise levels via compressor stations and vehicle traffic, and by increasing the year-round presence of human activities. Extraction will indirectly affect deer by increasing the human work-force population of the region resulting in the need for additional landscape for human housing, supporting businesses, and upgraded road/transportation infrastructure. Additionally, increased traffic on rural roads will raise the potential for vehicle-animal collisions and additive direct mortality to deer populations. Thus, research documenting these impacts and evaluating the most effective strategies for minimizing and mitigating these activities will greatly enhance future management efforts to sustain mule deer populations for future recreational and ecological values. 113 �The Piceance Basin in northwest Colorado contains one of the largest migratory mule deer populations in North America and also exhibits some of the largest natural gas reserves in North America. Projected energy development throughout northwest Colorado within the next 20 years is about 15,000 wells, many of which will occur in the Piceance Basin, which currently supports over 250 active gas well pads (http://cogcc.state.co.us). Anderson and Freddy (2008a) in their long-term research proposal identified 6 primary study objectives to assess measures to offset impacts of energy extraction on mule deer population performance. This progress report describes the first year of addressing mule deer population performance during the pretreatment phase, which includes monitoring habitat selection and behavior patterns of adult female mule deer, overwinter fawn and adult female survival, estimates of adult female body condition during late winter, and abundance estimates on 5 winter range herd segments in relation to varying levels of natural gas development in control and treatment experimental areas prior to proposed experimental modifications in energy developmental practices and potential habitat improvement treatments. STUDY AREAS The Piceance Basin between the cities of Rangely, Meeker, and Rifle in northwest Colorado was selected as the project area due to its ecological importance as one of the largest migratory mule deer populations in North America and because it exhibits one of the highest natural gas reserves in North America (Fig. 1). Historically, mule deer numbers on winter range were estimated between 15,00022,000 (Bartmann 1975), and the current number of well pads (Fig.1) and projected number of gas wells in the Piceance Basin over the next 20 years is about 250 and 15,000, respectively. Mule deer winter range in the Piceance Basin is predominantly characterized as a topographically diverse pinion pine (Pinus edulis)-Utah juniper (Juniperus osteosperma; pinion-juniper) shrubland complex ranging from 1675 m to 2285 m in elevation (Bartmann and Steinert 1981). Pinion-juniper are the dominant overstory species and major shrub species include Utah serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), big sagebrush (Artemisia tridentata), Gamble’s oak (Quercus gambelii), mountain snowberry Symphoricarpos oreophilus), and rabbitbrush (Chrysothamnus spp.; Bartmann et al. 1992). The Piceance Basin is segmented by numerous drainages characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainages having been converted to mixed-grass hay fields. Grasses and forbs common to the area consist of wheatgrass (Agropyron spp.), blue grama (Bouteloua gracilis), needle and thread (Stipa comata), Indian rice grass (Oryzopsis hymenoides), arrowleaf balsamroot (Balsamorhiza sagittata), broom snakeweed (Gutierrezia sarothreae), pinnate tansymustard (Descurainia pinnata), milkvetch (Astragalus spp.), Lewis flax (Linum lewisii), evening primrose (Oenothera spp.), skyrocket gilia (Gilia aggregata), buckwheat (Erigonum spp.), Indian paintbrush (Castilleja spp.), and penstemon (Penstemon spp.; Gibbs 1978). The climate of the Piceance Basin is characterized by warm dry summers and cold winters with most of the annual moisture coming from spring snow melt. Wintering mule deer population segments in the Piceance Basin include: North Ridge (57 km2) between Dry Fork of Piceance Creek and the White River in the northeastern portion of the Basin, Yellow Creek (70 km2) along Corral Gulch in the western portion of the Basin, Ryan Gulch (130 km2) between Ryan Gulch and Dry Gulch in the southwestern portion of the Basin, Magnolia (130 km2) north and east of Piceance Creek in the central portion of the Basin, and Story/Sprague Gulch (90 km2) between Story Gulch and Sprague Gulch in the southern portion of the Basin (Fig. 1). Each of these wintering population segments has received varying levels of development, from no development in North Ridge, light development in Story/Sprague Gulch and Yellow Creek, and relatively high development in Ryan Gulch and Magnolia segments (Fig. 1). Among the 5 study areas, Yellow Creek and Story/Sprague will serve as spatial controls to Ryan Gulch and Magnolia, respectively, and North Ridge will serve as a temporal control area. Because the progression and extent of energy development in the future is 114 �dynamic and currently unknown, North Ridge may also serve as a spatial control area to Magnolia or possibly Ryan Gulch should the Story/Sprague Gulch or Yellow Creek study areas become developed in the future. METHODS Tasks addressed this fiscal year included mule deer capture and collaring efforts, monitoring overwinter fawn and adult female survival, estimating adult female body condition during late winter using ultrasonography, and estimating mule deer abundance applying helicopter mark-resight surveys. I employed helicopter net-gunning techniques (Barrett et al. 1982, van Reenen 1982) to capture 50 fawns during early December and 30 adult females during late February-early March in each of the 5 study areas (250 fawns and 150 does total). Once netted, all deer were hobbled and blind folded. Fawns were weighed, radio-collared and released on site, and adult females were transported to a handling site for collection of body measurements and were fitted with GPS (20/area; 5 fixes/day; G2110B, Advanced Telemetry Systems, Isanti, MN, USA) or VHF collars (10/area) and released. Fawn collars were spliced and fitted with 2 lengths of rubber surgical tubing to facilitate collar drop during mid-summer—early autumn, adult VHF collars were attached static, and GPS collars were supplied with timed drop-off mechanisms scheduled to release early April, 2010. All radio-collars were equipped with mortality sensing options (i.e., increased pulse rate following 8 hrs of inactivity). Mule Deer Habitat Use and Movements I downloaded and organized data from GPS collars deployed during the pilot study (January 2008; see Anderson and Freddy 2008b) following collar drop and retrieval late February 2009. GPS collars redeployed late February-early March 2009 maintained the same fix schedule of attempting fixes every 5 hours. All well pads and roads present throughout the 5 study areas in spring 2009 were mapped using hand-held GPS units and data were incorporated into ArcGIS 9.2 for resource selection analyses. I plotted deer locations and recorded timing and distance of spring and fall 2008 migrations for each study area. Mule deer resource selection analyses for the first winter of research (January—May 2008) are pending acquisition of information on timing of road and well pad development and completion. Analyses of data from winter 2008-2009 will be conducted following retrieval of GPS collars in April 2010. Over-Winter Survival Mule deer mortality monitoring consisted of daily ground telemetry tracking and aerial monitoring deer approximately every 2 weeks from fixed-wing aircraft. Once a mortality signal was detected, deer were located and necropsied to assess cause of death. I estimated over-winter survival on a weekly basis using the staggered entry Kaplan-Meier procedure (Kaplan and Meier 1958, Pollock et al. 1989). Capture-related mortalities (any mortalities occurring within 10 days of capture) and collar failures were censored from survival rate estimates. I estimated over-winter survival rates beginning 14 December, 2008—20 June, 2009 for adult females and 14 December, 2008—21 March, 2009 for fawns. Premature failure of surgical tubing integrity beginning late March inhibited my ability to reasonably estimate fawn survival beyond late March. Adult Female Body Measurements I applied ultrasonography techniques described by Stephenson et al. (1998, 2002) and Cook et al. (2001) to measure maximum subcutaneous rump fat (mm) and loin depth (longissimus dorsi muscle, mm). I estimated a body condition score (BCS) for each deer by palpating the rump (Cook et al. 2001). I combined ultrasound rump fat measurements with BCS to develop an index (rLIVINDEX; Cook et al. 2001, 2007) of the relative nutritional status of deer from each study area. I examined differences (P < 0.05) in nutritional status among study areas using a two-sample t-test. Other body measurements recorded included pregnancy status (pregnant, barren) via ultrasound, weight (kg), chest girth (cm), and 115 �hind-foot length (cm). Fetal counts were also recorded in 4 of the 5 study areas to assist a Vaginal Implant Transmitter (VIT) evaluation study (see Bishop 2009). Abundance Estimates I conducted 4 (Ryan Gulch) or 5 (the remaining study areas) helicopter mark-resight surveys (2 observers and the pilot) during late March—early April, 2009 to estimate deer abundance in each of the 5 study areas. I delineated each study area from GPS locations during the same period the previous year and aerial telemetry locations of radio-collared deer within 2 weeks of the first survey. The survey boundary of each study area was then extended to the nearest section boundary and study areas were divided into 2.6 km2 sampling blocks. Aerial telemetry surveys were conducted during helicopter surveys to determine which marked deer were within each survey area. Initially, I randomly selected 10 sampling blocks from each study area (total sampling blocks = 22-50/study area) for each survey and surveyed sampling blocks sequentially to minimize flight time. After the first 2—3 surveys, depending on the area, it became apparent that increasing the number of sampling blocks to improve precision could be accomplished without undue expense, and subsequent surveys included all sampling blocks for the smaller areas (North Ridge, Yellow Creek, Story/Sprague) or 40% of the sampling blocks for the larger areas (Ryan Gulch, Magnolia). I delineated flight paths in ArcGIS 9.2 prior to surveys following topographic contours (e.g., drainages, ridges) and approximating 500 m spacing throughout selected survey blocks; flight paths during surveys were followed using GPS navigation in the helicopter. All deer observed within and between sampling blocks within the study area were included in abundance estimates. Two approximately 12 x 12 cm pieces of Ritchey livestock banding material (Ritchey Manufacturing Co., Brighton, CO USA) were uniquely marked using number, symbol combinations and attached to each radio-collar to enhance mark-resight estimates. Each deer observed during surveys was recorded as mark ID#, unmarked, or unidentified mark. I used program MARK (White and Burnham 1999) applying the immigration-emigration mixed logit-normal model (McClintock et al. 2008) to estimate mule deer abundance and confidence intervals. For mark-resight model evaluations, I examined all parameter combinations of varying detection rates with survey occasion or effort (vary P with survey or effort), evaluating population size as equal or varied among surveys (α = 0 or ≠ 0), and whether individual sighting probabilities (i.e., individual heterogeneity) were constant or varied (σ2 = 0 or ≠ 0). Model selection procedures followed the information-theoretic approach of Burnham and Anderson (2002). RESULTS AND DISSCUSSION Deer Captures and Survival The capture crew captured 253 fawns in early December 2008 and 150 does in late February— early March 2009. Three fawn and 0 doe mortalities occurred during capture and 0 fawn and 5 doe mortalities occurred during the myopathy period 10 days post-capture. Fawn survival during mid-December 2008—late March 2009 varied from 0.688 (Yellow Creek) to 0.925 (Ryan Gulch; Fig 2., Table 1). Fawn survival rates differed (P < 0.05) between the Ryan Gulch and Yellow Creek Study areas (Table 1). Adult female survival mid-December 2008—late June 2009 varied from 0.762 (North Ridge) to 0.931 (Magnolia; Fig 1), but were not different (P > 0.05) among study areas (Table 1). Smaller sample sizes for adult females reduced my ability to detect differences relative to fawns, but the apparent lower survival of North Ridge females was partly due to 2 mortalities that occurred during early winter before the March capture effort when only 12-13 marked females were available in each study area. Overall, fawn survival was high during the period examined likely due to the mild winter conditions present through late March, and doe survival was consistent with other mule deer populations experiencing normal winter conditions in the western US (Unsworth et al. 1999). 116 �Seasonal Movement Patterns Mule deer migration patterns during 2008 varied among study areas and within the Magnolia study area. North Ridge and north Magnolia deer migrated east—west typically across US Highway 13; Yellow Creek, Ryan Gulch, and south Magnolia deer migrated south—north summering along the Roan Plateau; and Story/Sprague deer typically migrated relatively short distances south—north (Fig 3.). Although summer and winter ranges differed among study areas, distance and timing of migration was similar among 4 of the 5 study areas. Excluding the Story/Sprague study area, median date of spring migration occurred May 17, 2008 (all 4 study areas) and fall migration occurred from October 17-23, 2008; median straight-line migration distances ranged between 30.6 and 39.4 km among the 4 study areas. I noted unique migration patterns among Story/Sprague deer where median spring and fall migration occurred April 29 and December 17, 2008, respectively, and median migration distance was 9.6 km. Story/Sprague deer generally spent less time on winter range and required shorter migration distances to achieve their seasonal metabolic requirements. Mule Deer Body Measurements Body measurements of adult female mule deer recorded 27 February—6 March 2009 were typically highest from the Story/Sprague and North Ridge study areas and lowest from the Yellow Creek and Magnolia study areas (Table 2). Parameters most related to mule deer nutritional status (rLIVINDEX derived from rump fat and BCS; Cook et al. 2001, 2007) suggested mule deer from the Story/Sprague study area were in the best condition and Yellow Creek deer were in the poorest condition. I observed significantly higher rLIVINDEX values (P < 0.05) among Story/Sprague females than females from the other 4 areas, but differences were not significant (P > 0.05) among the other 4 female groups. Early December fawn weights of males and females averaged 36.4 kg (n = 22, SD = 4.5) and 33.5 kg (n = 27, SD = 3.3) from Ryan Gulch, 33.9 kg (n = 22, SD = 3.6) and 30.5 (n = 28, SD = 4.9) from Yellow Creek, 37.0 kg (n = 24, SD = 3.5) and 33.5 kg (n = 26, SD = 4.0) from Magnolia, 35.8 kg (n = 26, SD = 4.8) and 33.2 kg (n = 24, SD = 3.0) from Story/Sprague, and 35.2 kg (n = 20, SD = 4.3) and 33.9 kg (n = 30, SD = 4.2) from North Ridge. Female fawns from Yellow Creek were significantly lighter (P < 0.05) than female fawns from the other 4 areas and Yellow Creek male fawns were significantly lighter than male fawns from Magnolia (P = 0.010). Mule Deer Population Estimates Mark-resight models that best predicted abundance estimates (lowest AICc; Burnham and Anderson 2002) exhibited constant population size across surveys (i.e., α = 0 suggesting population closure) and homogenous individual sightability (σ2 = 0) for all study areas, and variable sightability (P) across surveys in Ryan Gulch and Magnolia or with survey effort in North Ridge, Story/Sprague, and Yellow Creek. North Ridge exhibited the highest deer density (18.1/km2) and Ryan Gulch and Magnolia exhibited relatively low deer densities (5.6 and 6.6/km2; Table 3). Abundance estimates were similarly precise from 4 of the 5 study areas (mean CV = 0.16—0.18), with Story/Sprague exhibiting the widest CIs (Table 3; mean CV = 0.29). A relatively small number of marked deer were sighted during surveys (Table 3) suggesting improved precision can be accomplished with increased sample sizes or increasing the number of surveys/study area. Increasing the number of marks/study area by 30 can easily be accomplished by extending GPS drop-off dates beyond the March capture period, which wasn’t the case last winter. I also noted that complete coverage of each study area can reasonably be accomplished by increasing flight time by about 20 to 60 minutes/survey depending on the study area and should be more cost effective than increasing number of surveys/area. By increasing the number of marks and complete survey coverage/study area, CVs should improve likely providing detection of <30% change in population size. 117 �SUMMARY AND FUTURE PLANS The goal of this study is to investigate habitat treatments and energy development practices that enhance mule deer populations exposed to extensive energy development activity. The information presented here provide data describing mule deer population parameters from the first pre-treatment year of a long-term study intended to address how mule deer react to landscape scale habitat and human activity modifications. The pretreatment period is intended to continue 1 to 2 more winters to provide baseline data to compare against intended improvements in habitat conditions and concentration/reduction in human development activities, which will be maintained for at least 5 years to provide sufficient time to measure how deer respond to these changes. Based on the data collected thus far, Story/Sprague deer appear to be in better physical condition than deer from the other winter ranges examined. Migration patterns were similar among 4 of the 5 areas, but Story/Sprague deer traveled shorter distances and spent less time on winter range. Yellow Creek fawns were lighter than other study areas and exhibited lowest survival of the areas investigated. North Ridge deer exhibited the highest winter range density and Magnolia and Ryan Gulch deer exhibited the lowest densities. Reasons for these differences are currently unknown, but could be related to several factors including relative habitat conditions, duration on and distance to seasonal ranges, and extent of human activity throughout occupied habitats. Meaningful comparisons will be evident once treatments are implemented and comparisons are possible between areas that are manipulated (treatment areas) and those that are not (control areas). We are currently working towards a habitat improvement plan and identifying beneficial development practices that are both logistically and financially feasible to implement. Investigations of habitat treatment potential are promising in the Magnolia and Ryan Gulch study areas and we expect positive native plant responses with potential acceleration of response through native seeding. Members of CDOW, BLM, and private consultants will be developing a habitat treatment plan for review and approval by the end of the year. Discussions with Williams Production LMT Co. have produced a clustered development plan to be implemented in the Ryan Gulch study area and new technologies will be implemented to reduce human activity through remote monitoring of well pads and fluid collection systems. I recently contracted with Dr. Terry Bowyer and Patrick Lendrum (MS candidate) of Idaho State University to begin a graduate project addressing mule deer migration and potential influences of human activity along migration routes. I collaborated with Chad Bishop this past winter/spring to test a new VIT design that improves VIT retention (see Bishop 2009) and will improve our ability to address neonate survival (in addition to overwinter survival) and identify fawning habitat on summer range; these factors are not currently being addressed, but could strengthen our inference about mule deer and energy development if funding and cooperative agreements were developed for this purpose. We are beginning to work collaboratively with ExxonMobile Production Co. and Colorado State University to enhance funding and potentially provide graduate student assistance addressing additional components of mule deer/energy development interactions. Additional funding and cooperative agreements will be necessary to manipulate habitat conditions to benefit mule deer and our current funding sources will need to be maintained to continue monitoring mule deer population parameters at the current level. We optimistically anticipate the opportunity to work cooperatively toward developing solutions for allowing the nation’s energy reserves to be developed in a manner that benefits wildlife and the people who value both the wildlife and energy resources of Colorado. LITERATURE CITED Anderson, C. R., Jr., and D. J. Freddy. 2008a. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Final Study Plan, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and D. J. Freddy. 2008b. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and 118 �habitat degradation—Stage I, Objective 5: Patterns of mule deer distribution & movements. Pilot Study, Colorado Division of Wildlife, Ft. Collins, CO, USA. Bartmann, R. M. 1975. Piceance deer study—population density and structure. Job Progress Report, Colorado Divison of Wildlife, Fort Collins, Colorado, USA. Bartmann, R. B., and S. F. Steinert. 1981. Distribution and movements of mule deer in the White River Drainage, Colorado. Special Report No. 51, Colorado Division of Wildlife, Fort Collins, Colorado, USA. Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monograph No. 121. Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bishop, C. J. 2009. Effectiveness of a modified vaginal implant transmitter for capturing mule deer neonates from targeted adult females. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, CO, USA. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multi-model inference: a practical information-theoretic approach. Second edition. Springer-Verlag, New York, New York, USA. Cook, R. C., J. G. Cook, D. L. Murray, P. Zager, B. K. Johnson, and M. W. Gratson. 2001. Development of predictive models of nutritional condition for rocky mountain elk. Journal of Wildlife Management 65:973-987. Cook, R. C., T. R. Stephenson, W. L. Meyers, J. G. Cook, and L. A. Shipley. 2007. Validating predictive models of nutritional condition for mule deer. Journal of Wildlife Management 71:1934-1943. Gibbs, H. D. 1978. Nutritional quality of mule deer foods, Piceance Basin, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 52:457-481. McClintock, B. T., G. C. White, K. P. Burnham, and M. A. Pride. 2008. A generalized mixed effects model of abundance for mark—resight data when sampling is without replacement. Pages 271289 in D. L. Thompson, E. G. Cooch, and M. J. Conroy, editors, Modeling demographic processes is marked populations. Springer, New York, New York, USA. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. C. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule der body composition using in vivo and post-mortem indicies of nutritional condition. Wildlife Society Bulletin 30:557-564. Stephenson, T. R., K. J. Hundertmark, C. C. Swartz, and V. Van Ballenberghe. 1998. Predicting body fat and mass in moose with untrasonography. Canadian Journal of Zoology 76:717-722. Unsworth, J. W., D. F. Pack, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked individuals. Bird Study 46:120-139. Prepared by Chuck R. Anderson, Wildlife Researcher 119 �Table 1. Survival rate estimates (Ŝ) of fawn (14 Dec. 2008—21 Mar. 2009) and adult female (14 Dec.— 20 June, 2009) mule deer in 5 winter range study areas of the Piceance in northwest, Colorado. Cohort Study area Initial sample size (n) March doe samplea (n) Ŝ (95% CI) Fawns Ryan Gulch 54 0.925 (0.853—1.000) Yellow Creek 43 0.688 (0.546—0.839) Magnolia 50 0.800 (0.688—0.911) Story/Sprague 47 0.823 (0.722—0.937) North Ridge 48 0.833 (0.728—0.939) Adult females Ryan Gulch 12 28 0.893 (0.778—1.000) Yellow Creek 13 28 0.890 (0.737—1.000) Magnolia 12 29 0.931 (0.839—1.000) Story/Sprague 13 29 0.862 (0.737—0.988) North Ridge 13 30 0.762 (0.536—0.960) a Adult female sample size following capture and radio-collaring efforts late February—early March, 2009. 120 �Table 2. Mean body measurements, Body Condition Score (BCS), and an index of relative nutritional status (rLIVINDEX) of adult female mule deer from 5 study areas in the Piceance Basin of northwest Colorado, late February—early March, 2009. Sample sizes = 30/study area and values in parentheses = SD. Loin depth (mm) Rump fat (mm) BCSa rLIVINDEXb 96.9 (4.1) 40.50 (3.03) 1.73 (1.78) 2.66 (0.55) 2.71 (0.68) 47.2 (1.1) 97.4 (4.2) 40.17 (2.95) 1.47 (0.68) 2.50 (0.60) 2.51 (0.63) 55.6 (5.7) 47.2 (1.2) 96.0 (4.1) 40.70 (3.72) 1.97 (1.00) 3.09 (0.72) 3.12 (0.77) Magnolia 55.3 (5.9) 47.7 (1.5) 87.5 (5.0) 40.53 (3.70) 1.30 (0.79) 2.56 (0.68) 2.57 (0.70) North Ridge 53.3 (5.6) 47.3 (3.3) 97.2 (4.9) 41.13 (2.70) 1.57 (1.22) 2.60 (0.56) 2.62 (0.60) Study Area Weight (kg) Hind foot length (cm) Chest girth (cm) Ryan Gulch 52.2 (5.7) 46.9 (1.8) Yellow Creek 52.9 (4.8) Story/Sprague a Body condition score taken from palpations of the rump (Cook et al. 2001) rLIVEINDEX = (cm rump fat - 0.2) + BCS if rump fat > 2 mm. Otherwise = BCS (Cook et al. 2001, 2007). b 121 �Table 3. Mark-resight abundance (N) and density estimates of mule deer from 5 winter range herd segments in the Piceance Basin, northwest Colorado, 25 March—2 April, 2009. Data represent 4 surveys from Ryan Gulch and 5 surveys from the other 4 study areas. Study area Mean No. sighted Mean No. marked N (95% CI) Density (deer/km2) Ryan Gulch Yellow Creek Magnolia Story/Sprague North Ridge 156 138 109 138 238 12 7 6 5 14 727 (626—854) 720 (605—870) 854 (716—1,027) 1,125 (853—1,509) 1,028 (874—1,230) 5.6 10.3 6.6 12.4 18.1 Figure 1. Approximate study area boundaries relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, spring 2009. 122 �Figure 2. Winter survival rates of fawn (14 December, 2008—21 March, 2009; top) and adult female (14 December—21 June, 2009; bottom) mule deer from 5 study areas in the Piceance Basin of northwest Colorado. Survival rates of Yellow Creek fawns were significantly lower (P < 0.05; Table 1) than survival of Ryan Gulch fawns. Survival rates among other fawn and doe groups were not significantly different (P > 0.05; Table 1). 123 �Figure 3. Mule deer GPS locations from 5 winter range study areas (solid lines; 15 does/study area) in the Piceance Basin of northwest Colorado, January 2008—February, 2009. 124 �Colorado Division of Wildlife July 2008 –July 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates On the Uncompahgre Plateau Period covered: July 31, 2008−July 31, 2009 Author: K. A. Logan. Personnel: K. Logan, B. Dunne, D. Ranglack, J. Timmer, S. Waters, K. Crane, T. Mathieson, M. Caddy, and T. Bonacquista of CDOW; S. Young and W. Wilson of U.S.D.A. Wildlife Services; houndmen R. Navarette and J. Knight; volunteers and cooperators including: private landowners, Bureau of Land Management, Colorado State Parks, Colorado State University and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT This report provides information in the fifth year of the reference period August 2008 through July 2009 on puma population characteristics and dynamics on the Uncompahgre Plateau. Field operations were impacted by a state government issued hiring freeze that did not allow full staffing of 2 puma capture teams during winter 2008-09. All capture efforts involving use of trained dogs, cage traps, and inspections at nurseries in 2008-09 resulted in a total of 37 puma captures (7 adult females [1 adult female captured 3 times, another captured twice], 4 adult males [1 adult male captured 3 times], 1 subadult female, and 18 cubs [2 of them captured twice each]). Five adults (4 females, 1 male) and 14 cubs were captured and marked for the first time. As of July 2009, there were 17 adults (11 females, 6 males), 1 subadult female, and 5 cubs (2 females, 3 males) with active radio-collars. Efforts to capture, sample, and mark pumas with the use of trained dogs extended from December 9, 2008 to April 30, 2009. Those efforts resulted in 71 search days, 198-202 puma tracks detected, 75-78 pursuits, and 24 puma captures. In 2008-09, capture efforts with ungulate carcasses and cage traps resulted in captures of 2 adult females and 1 subadult female. Capture and search efforts from November 2008 through March 2009 enabled us to estimate a minimum of 37 independent pumas detected on the Uncompahgre Plateau study area during that time, including 26 females and 11 males. Preliminary puma population parameters estimated during the past 4.7 years of research, included: population sex and age structure, reproduction rates, and survival rates. Data on puma reproduction rates included: average litter size = 2.77 ± 0.9081 SD, n = 26; average birth interval (mo.) = 18.462 ± 4.6035 SD, n = 16; average proportion of adult females producing cubs each year = 0.598 ± 0.1094 SD, n = 11-13 females per yr. for 4 years; secondary sex ratio = 41:31, consistent with 1:1; and average gestation length (day) = 90.5-92.3(SD = 2.5495, 125 �2.1628, respectively). Puma births occurred March through September, with 24 of 27 occurring May through September. Majority of breeding activity was February through June. Preliminary estimates of survival rates for both adult and subadult pumas in this reference period were high, and may reflect the absence of puma sport-hunting as a mortality factor. An increasing age structure of independent pumas in the reference period reflects the high survival rates. Cub survival was about 0.53 (SE = 0.1623-0.1629; Kaplan-Meier procedure) and 0.58 (± 0.1610 95% CI; binomial model). The main cause of mortality in the adults and cubs was aggression by other pumas. Dispersal from the Uncompahgre Plateau study area was documented for 8 pumas (7 male, 1 female) that dispersed during the subadult stage and moved distances ranging from about 61 to 330 linear km. We monitored 7 puma families with a radio-collared mother and at least one radio-collared cub to assess association distances during aerial locations from November 6, 2008 to March 20, 2009. The aggregate data gathered during the past 4 winters generally indicate that mothers were usually within 660 m of their cubs during the day. Preliminary comparisons between our current puma research on the Uncompahgre Plateau (4.7 years duration) and results of the Anderson et al. (1992) puma research on the plateau (7 years duration 1981-1988) were made where appropriate. Data on puma population characteristics and dynamics gathered during the reference period was used for a preliminary assessment of population-based assumptions used by CDOW to guide puma hunting management and indicated that assumptions pertaining to puma population sex and age structure, density, and expected results from modeled harvest rates are biologically supported. The CDOW structured the puma hunting season for the treatment period. The first hunting season will begin midNovember 2009 and extend to January 31, 2010 unless the quota is filled earlier. The management objective will be to achieve a stable to increasing puma population. Population model simulations indicated a harvest quota of 8 independent pumas to achieve the objective. No limit of hunters on the study area is imposed, but each hunter is required to obtain a hunting permit for the study area. In addition, an effort will be made to survey each hunter obtaining a valid permit. All pumas harvested in and around the study area will be inspected by CDOW personnel. A study plan for the treatment period was submitted for internal review in the CDOW. The plan was substantially modified and received another internal review. That version will be modified and submitted to the Mammals Research leader in fall 2009. Continuing this research includes manipulating the puma population with sport-hunting in the treatment period while also estimating puma population characteristics and vital rates. We are continuing to collaborate with colleagues in Mammals Research and at Colorado State University to assess puma population dynamics and social structure, puma-human interactions, health, habitat use, and we will incorporate a pilot project to examine individual puma detection rates using a camera grid design. 126 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates; model puma population dynamics; and plan for the remaining 5 years of the Uncompahgre Plateau Puma Project― all to improve the Colorado Division of Wildlife’s (CDOW) model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. 5. 6. 7. 8. 9. Continue gathering data on puma population sex and age structure. Continue gathering data for estimates of puma reproduction rates. Continue gathering data to estimate puma sex and age-stage survival rates. Continue gathering data on agent-specific mortality. Gather data on spatial relationships of puma mothers to their cubs during the Colorado puma hunting season as a preliminary assessment of the vulnerability of puma mothers to sport-hunting harvest. Use data on population dynamics for a preliminary evaluation of assumptions used by CDOW biologists and managers in the Data Analysis Unit puma management planning process. Work with CDOW biologists and managers to structure the puma hunting manipulation for the first year of the 5 year treatment phase. Develop a study plan for remaining 5 years of puma population research on the Uncompahgre Plateau Study Area. Collaborate with other researchers and evaluate other data sources that could be relevant to CDOW biologists and managers. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing pumas while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs 127 �identified by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/radio-collared pumas. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of puma population abundance. A descriptive study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in a 5-year reference period (i.e., absence of recreational hunting) to allow puma life history traits to interact with the main habitat factors that appear to influence puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001). Contingent upon results in the reference period, a subsequent 5-year treatment period is planned. 128 �The treatment period will involve the use of controlled recreational hunting to manipulate the puma population. TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all age stages- adults, subadults, and cubs, J. Apker, CDOW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to DAUs to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the minimum puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado Data Analysis Units (DAUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e., λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-firstbreeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. The key assumption is that the CDOW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ). Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). 129 �H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a decline of the harvest-age segment of the population by the beginning of the next hunting season. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a decline in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed in the future after we have learned the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. 130 �The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. There are cattle and domestic sheep raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area well accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates will be quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest will be tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma selection pressures in western North America for the past 100 years. Hence, the reference period, years 1―5, would provide conditions where individual pumas in this population (of estimated sex and age structure) express life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor will be catchable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This should allow researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas that might be involved in depredation on livestock or human safety incidents. In addition, all radio-collared and eartagged pumas that ranged in a buffer zone, that includes the northern halves of GMUs 61 and 62, were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CDOW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6―10, recreational puma hunting will occur on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared pumas. For managers, demonstrating that they can manage puma populations with hunting and achieve the CDOW strategic objective of managing for a healthy, selfsustainable puma population state-wide is important to their mandated responsibility. Dynamics of the 131 �puma population will be manipulated to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting). The killing of tagged and collared pumas during the treatment period will not hamper operational needs (as it would during the start-up years), because by the beginning of this period, a majority of independent pumas in the population should be marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was have a minimum of 6 puma in each of 6 categories (36 total) radiotagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Assuming that the puma population density on the study area was relatively low at the beginning of this study― about 1 adult/100 km2 and the sex ratio was equal (Anderson et al. 1992, Logan and Sweanor 2001:167), then there might have been 22 adults, 11 males and 11 females. Also assuming that the total population contained 10% subadults and 34% cubs (Logan and Sweanor 2001), then there might have been 4 subadults and 13 cubs with equal sex ratios in a total population of 39 pumas. If we achieved our logistical aim, then we should be able to quantify population characteristics and vital rates of the puma population based on a sample that includes a majority of individuals in the population. Recognizing that the population may grow, we will build upon the tagged number in each subsequent year to maintain a high proportion of marked individuals in the population. Puma capture and handling procedures were approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) and when available fecal DNA for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were fixed via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitates thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area was searched systematically multiple times per year by four-wheel-drive trucks, all-terrain vehicles, 132 �snow-mobiles, and walking. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage and door. This allowed researchers to be at the cage to handle captured pumas within 30 minutes. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers are away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of ~100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas do not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating vital rates and gathering movement data relevant to population dynamics (i.e., emigration and Data Analysis Unit boundaries). Adult, subadult, and cub pumas were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna is severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were eartagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas would provide precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPS-collars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). 133 �Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allows the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars are not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to check on their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when puma was immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHFcollared pumas were fixed about once per week (as flight schedules and weather allow) from light fixedwing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). Aerial locations also provided simultaneous location data on mothers and cubs. GPS- and VHF-collared pumas were located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes recorded on standard forms. GPS and aerial locations were mapped using GIS software. We attempted to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar that can expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM2160, ~50g, or Telonics, Inc., Mesa, Arizona MOD 210, ~100g,) when cubs weighed 2.3―11 kg (5―25 lb). Cubs with mass ≥11 kg could wear these small expandable collars until they are over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Analytical Methods Population Characteristics: Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also known as kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months (for cubs and subadults) or years (for adults). Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the cub age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) November to March which corresponds with Colorado’s puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum 134 �number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed using SYSTAT, R, and MARK software. RESULTS AND DISCUSSION Segment Objective 1 Field research to quantify puma population structure, vital rates, and causes of mortality for this report extended from August 2008 to July 2009. Our plan was to use 2 fully-staffed puma capture teams with dogs November through April, with each team operating on half the study area, with the intent of substantially boosting puma capture and sampling efforts. But, field operations were impacted by a state government mandated hiring freeze. We were limited to the principal investigator and 2 houndmen teams from October 2008 through April 2009. The principal investigator operated with the 2 houndmen teams for a single expanded moving search footprint and performed all immobilization and sampling procedures during winter and spring capture efforts. Our searches to detect puma presence covered the entire study area. By May 2009 technicians could be hired again and assisted in puma captures in cage traps and at nurseries. In addition, the Colorado State University bobcat research team facilitated the recapture of an adult female puma. We made 37 puma captures during the period (7 adult females [1 adult female captured 3 times, another captured twice], 4 adult males [1 adult male captured 3 times], 1 subadult female, and 18 cubs [2 of them captured twice each]). Five adults (4 females, 1 male) and 14 cubs were captured and marked for the first time in 2008-2009. One adult female and 2 cubs were visually observed at capture efforts, but could not be handled. A total of 39 pumas were monitored with radiotelemetry from August 2008 to July 2009 (some of these had been collared during previous years). Trained dogs were used as our main method to capture, sample, and mark adult and subadult pumas from December 9, 2008 to April 30, 2009. Those efforts resulted in 71 search days, 198-202 puma tracks detected, 75-78 pursuits, and 24 puma captures (Table 1). Puma capture efforts (i.e., search days) with dogs in this period was slightly less than our efforts in the 4 previous winters (Table 2). But, the frequency of tracks encountered was about the same as the previous winter. The pursuits increased over the 4 previous periods, as did our capture rate. The later 2 statistics were probably the result of using 2 houndmen teams. Four adult and 7 cubs were captured for the first time by using dogs (Tables 1 and 3). 135 �This included 2 non-marked cubs that could not be handled for safety reasons. Three adult male pumas and 1 large male cub were captured with dogs but could not be handled for safety reasons, and 1 adult female and her cub were visually observed but could not be caught for marking and sampling (Table 4). Two adult females (1 recaptured twice) and an adult male were recaptured and observed, but there was no need to handle them (Table 5). Puma capture efforts using ungulate carcasses and cage traps extended from August 20, 2008 to July 20, 2009. We used 36 road-killed mule deer at 17 different sites to capture one adult female and one subadult female (Tables 6). In addition, the Colorado State University bobcat research team recaptured an adult female in a trap set for bobcats, thus, providing an opportunity to change a failing GPS collar. Pumas scavenged 7 of 36 (19.4%) of the ungulate carcasses used for bait. Percentages of puma scavenging ungulate carcasses in the previous 3 years were 20%, 22.5%, and 18.3%. Other carnivores that used the ungulate baits included: black bear, bobcat, gray fox, and domestic dogs. We captured 14 cubs (8 male:6 female) for the first time (Table 7), and fit 11 of them with radiocollars (Appendix A). Three cubs were not radio-collared. In 1 case the mother returned to the nursery while we were sampling the cubs so we quickly returned the cubs to the nursery, leaving 1 collared and 1 not collared. In the other case, 2 cubs in a litter of 3 were too small to wear the collar design. Three of the cubs were bayed by our dogs and were large enough to require anesthetics for safe handling. The other 11 cubs were handled without anesthetics at their nurseries when they were 34 to 38 days old. Litters bearing these cubs were produced in August (2), September (1), April (1), and May (3). In addition to our direct puma captures with dogs December through April, we detected 10 independent pumas that we were able to identify with GPS or VHF telemetry 12 times, thus, negating the need to capture those pumas directly with dogs (Table 1). Upon detecting puma tracks that were aged at 1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. GPS data from pumas with functional GPS collars provided confirmatory information about movements of pumas. If GPS data indicated that the puma moved through the area at the time the tracks were made, then we ruled the data were confirmatory. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with nonfunctioning GPS- or radiocollars. Our search efforts throughout the study area also revealed the presence of at least 14 other independent pumas, we classified as 12 females and 2 males. We could separate the activity of these pumas from the GPS- and VHF- collared pumas in time, space, and track size differences between females and males. Moreover, females in association with cubs of different numbers, sizes, and locations enabled us to separate 5 adult females followed by 1 to 3 medium-to-large-size cubs. One of the adult females was visually observed with 2 of her 3 cubs, 2 of which we captured and marked. The tracks we found of the other pumas were too old to pursue (i.e., probability of capture with the dogs was negligible). It is also possible that 2 of the adult females were previously marked animals wearing non-functional GPS collars (Table 8). Our search and capture efforts during November 2008 through April 2009 enabled us to estimate a minimum count of 37 independent pumas detected on the Uncompahgre Plateau study area, up from a minimum count of 33 independent pumas during the November 2007 to March 2008 (Table 8). This estimate was based on the number of known radio-collared pumas, the observation of one non-collared female puma, and detection of tracks of suspected non-collared pumas or pumas with non-functional GPS collars on the study area (explained previously). In addition to the independent pumas, we also counted a minimum of 21 cubs. Of the 37 independent pumas, 23 to 25 (62-68%) were marked and 12 to 14 (32- 136 �38%) were assumed to be unmarked animals. Of the expected unmarked pumas, 12 were females and 2 were males, which might reflect lower detection rates of females, making it more difficult for us to capture and mark females. Although, we would have expected to capture, sample, and mark a larger portion of those animals had we fielded the 2 complete capture teams in winter 2008 to 2009 as previously planned. There may be variation in puma numbers on the west and east slopes of the study area. The west slope count includes 16 independent pumas (11 females, 5 males). The east slope count includes 21 independent pumas (15 females, 6 males). We used the minimum puma counts in the past 2 periods, (i.e., 33 independent pumas for November 2007 to March 2008 and 37 independent pumas for November 2008 to April 2009) to calculate preliminary minimum densities for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area. The minimum densities ranged from 2.0 to 2.2 independent pumas/100 km2. Anderson et al. (1992) studied pumas on the east slope of the Uncompahgre Plateau (i.e., GMU 62) during 1981 to 1988. Sport-hunting was banned during that study to investigate an “unexploited” puma population (Anderson et al. 1992:5). As our current effort results in larger samples and progresses in time through the reference and treatment periods, similarities and differences in results of the 2 research efforts, now separated by more than 15 years, should illuminate reliable knowledge for puma management in Colorado. Our current puma research on the Uncompahgre Plateau has been underway for 4.7 years (compared to 7 years of Anderson et al. 1992). Our data analysis at this stage of the research is not by any means exhaustive or complete because we are still in the intensive data-gathering phase, yet, our data allows some preliminary comparisons with Anderson’s (1992) completed work. In the Anderson et al. (1992) study, the average capture effort with dogs was 91.1 days per winter (range = 32 to 136, n = 7) resulting in an average capture effort of 13.9 days per puma. Of 189 pursuits of pumas, 110 (58%) were successful (either of radio-collared or non-collared animals). Anderson et al. (1992) focused on capturing pumas >27 kg in body mass while avoiding pumas <27 kg in mass. They captured 47 pumas with dogs for an average capture rate of 13.9 days per puma. Eight other pumas, all female cubs ≤7 months old, were caught in steel leg-hold traps by trappers in pursuit of furbearers, and were added to the study animal population. Two other cubs were killed by the dogs. In total, Anderson et al. (1992) captured 57 pumas, of which 49 were radio-collared. Anderson et al. (1992:49) estimated a minimum density of “resident” pumas (equivalent to our independent pumas) at 1.1 pumas/100 km2. This was practically half the density of our current preliminary minimum density estimates for independent pumas (see previously). So far, in our 5 winters, the average effort per winter to capture pumas with dogs is 77.2 days (range = 71 to 82). Of 247 pursuits, 94 (38%) were successful. We captured 41 individual pumas their first time with dogs (i.e., does not include dog-aided recaptures), yielding an average capture rate of 9.4 days per capture (i.e., 386 days/41 captures). Other capture efforts and results between the 2 studies are not comparable, because Anderson et al. (1992) did not routinely attempt to capture pumas using cage traps or capture cubs at nurseries like we are. In our current effort, we captured, sampled, and marked 109 pumas. Of those animals, 91 were radiocollared, allowing us to monitor fates of pumas in all sexes and age stages, including: 19 adult females, 12 adult males, 4 subadult females, 5 subadult males, 30 female cubs, 30 male cubs (some individuals occur in more than one age-stage). To date, this represents the largest number of individual pumas sampled for population data in Colorado. Mass recorded by Anderson et al. (1992:86) for pumas having an estimated age ≥24 months, averaged 61.6 kg for 8 males, (SD = 5.7, range = 51.8 to 70.8) and 44.5 kg for 14 females (SD = 3.6, range = 38.5 to 49.9). So far in our current study, mass for pumas ≥24 months old and weighed for the first time averaged 61.3 kg for 10 males (SD = 3.72, range 55 to 68 kg) and 38.3 kg for 18 females (SD = 137 �4.01, range = 31 to 45). Sexual dimorphism is evident in pumas, and has been described for the species throughout its range (Young and Goldman 1946). Sexual dimorphism in the puma has been explained as a potential result of sexual selection (Logan and Sweanor 2001:109). Segment Objective 2 During the past 4.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado. We examined 72 cubs from 26 litters aged 26 to 42 days old where we were reasonably sure that we counted all the cubs at the nurseries (Table 9, Appendix A). Using those litters and 1 other litter confirmed by nursling cub tracks with a GPS-collared female (i.e., n = 27 litters with approximately known birth dates), the distribution of puma births by month indicate puma births extending from March into September, with 24 of 27 births occurring May through September (Fig. 4). Our data suggests that the majority of puma breeding activity occurs February through June. The secondary male:female sex ratio was 41:31 for 26 litters where all the cubs were sexed. This ratio was not significantly different from 1:1, (X2 = 1.389 < 3.841, α = 0.05, 1 d.f.). An equal sex ratio at birth is characteristic of other puma populations in North America (Robinette et al. 1961, Logan and Sweanor 2001:69-70). The mean (±SD) and extreme sizes of the 26 litters examined at nurseries were 2.77 (±0.9081), 1 to 4 (Table 9). In addition, 16 birth intervals for 9 different female pumas averaged 18.462 months (SD = 4.6035), and ranged from 11.7 to 23.9 months (Table 9). During the past 4 biological years (i.e., 2005-06 to 2008-09) when we radio-monitored 12, 13, 12, and 11 adult female pumas per year, respectively, the proportion of adult females that produced cubs each year were 0.67, 0.69, 0.58, 0.45 with a mean ± SD of 0.598 ± 0.1094. Based on observations (from GPS and radio-telemetry data) of associations between 9 mothers and putative sires (Table 9), 10 estimated gestation periods, considering a range of days for 7 observations, averaged 90.5 to 92.3 days (SD = 2.5495, 2.1628, respectively), which is consistent with average puma gestation reported in the technical literature on puma (i.e., mean ± SD = 91.9 ± 4.1, Anderson 1983:33, mean = 91.5 ± 4.0 Logan and Sweanor 2001:414). Anderson et al. (1992:47) reported of “17 postnatal litters about 10-240 days in estimated age from 12 individual females, the mean (±SD) and extremes of litter sizes were 2.41 ± 0.8, 1-4”. “Because most postnatal young were not handled, their sex ratio is unknown” (Anderson et al.1992:48). In addition, because cubs were first observed at older ages, it is likely that some post-natal mortality had occurred. This is one explanation for smaller litters observed by Anderson et al. (1992). Anderson et al. (1992:47-48) found that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. Data on our 27 litters adds to Anderson’s data (Fig. 4), and indicates puma births in Colorado occurring in every month except January and November (so far). Anderson’s observation of two 12-month birth intervals for one female (Anderson et al. 1992:48) is at the low range of our observations (Table 9). Segment Objectives 3 & 4 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2009, we radio-monitored 12 adult male and 19 adult female pumas to quantify survival and agent-specific mortality rates (Table 10). One adult male is known to have died of natural causes. M4 was about 37 to 45 months old when he was killed by an unidentified male puma along the southeast boundary of the study area. One adult male, M5, lived in the buffer zone north of the study area where all marked pumas were protected from sport-hunting. However, M5 was killed at 54 months old by a puma hunter when M5 left the buffer zone and ranged into eastern Utah. We lost contact with 3 adult males apparently due to GPS/VHF collar failure: M1, M27, and M29. Direct observations in the field indicated that M27 was alive on 05-07-09 (camera photo), and M29 was alive on 02-25-09 (recapture). Four adult females are known to have died of natural causes. F50 was about 29 to 31 months old when she died apparently of natural causes (exact agent could not be identified). Three adult females, F54, F30, and F2 were killed by other pumas. F54 was killed at about 49 months old by a male puma on the southern boundary of the 138 �study area while apparently in direct competition for a fawn mule deer. F30 was killed by a puma of unknown sex and for unknown circumstances when she was about 60 months old. F2 was killed when she was about 92 months old by a puma of unknown sex (but thought to be a male based on presence of 8 scrapes), as was at least one of her four 87-day-old cubs M79 (Appendix A). All 3 adult females appeared to have fatal bites to the head, with canine punctures that penetrated the skull. One adult female, F7, was killed for depredation control purposes when she was about 107 months old. Preliminary estimates of adult puma survival rates indicate relatively high survival in this reference period (i.e., with no sport-hunting) (Table 11). Survival rates were estimated using the KaplanMeier procedure to staggered entry of animals (Pollock et al. 1989) for the past 4 annual and hunting season periods when samples were ≥ 5 animals in each sex category. The survival rates reflect 1 male death and 4 adult female deaths from natural causes. Data on M5 (killed by a hunter) and F7 (killed for depredation control) were right censored after the date they died. In general, adult male puma survival is higher than adult female survival in this non-hunted population state. The adult age structure, as indicated in Figure 4, is indicative of high survival rates during the past 5 winters without sport-hunting mortality. Research in New Mexico on a non-hunted puma population also indicated high adult survival rates with survival rates of adult males higher than adult females and the major cause of death being aggression by male pumas (n = 8 years; Logan and Sweanor 2001:127-138). We have radio-monitored 9 pumas, 5 males and 4 females, in the subadult age-stage (independent pumas <24 months old) (Table 12). One of those, F66, died of natural causes. F66 died at 23 months old of trauma to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer. We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire reliable estimates of their survival. Data from puma hunters provided additional information on fates of 8 pumas, 7 males and 1 female, initially captured and marked as cubs (5 males) or subadults (2 males, 1 female) on the Uncompahgre Plateau puma study area (Table 13). All 7 of the males were killed away from the study area by hunters at linear distances (i.e., from initial capture sites to kill sites) ranging from about 66 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). The female (F52) was treed and released by hunters. These pumas represent dispersal moves from the Uncompahgre Plateau. All of the pumas, except for 1 (M68, 17 months old) had reached adult ages ranging from 24 to 54 months old. Our current research effort is still too short in duration and samples too small to make meaningful comparisons with evidence in the literature regarding puma offspring dispersal rates, distances moved, and philopatry. Dispersal and philopatry have been explained as life history strategies in pumas that assist gene flow, colonization, population maintenance, and individual survival and reproductive success (Logan and Sweanor 2001). Thus, such strategies would be expected to be conserved, and expressed in puma populations in different locations. In addition, because puma emigration and immigration (i.e., via dispersal) have been shown to be important processes in puma population dynamics (Sweanor et al. 2000), we need larger samples and longer research duration in this study to understand the significance of those parameters in our study population. A preliminary estimate of puma cub survival was made with 36 radio-collared cubs (16 males, 20 females) that we marked at nurseries when they were 26 to 42 days old. Only cubs that died of natural causes were used (i.e., 3 capture-related deaths were excluded). All cubs were born from May 2005 to July 2007. For the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989), the maximum survival period was assumed to be 365 days after capture (i.e., ~13-14 months old) to coincide with the age that puma cubs would normally be expected to become independent from their mothers (Logan and Sweanor 2001). In this preliminary estimate, observations of siblings are assumed to be 139 �independent (i.e., distribution of mortalities among litters is random), but that assumption might not be reliable (Bishop et al. 2008; an overdispersion parameter will need to be estimated). We omitted 3 radiocollared cubs that died as a result of the expandable radiocollars (Appendix A). Otherwise, cubs were right censored when they reached independence, or from the date after we lost contact. Dates that bracketed the deaths of cubs were used to estimate minimum and maximum survival rates. The estimated minimum survival rate using the Kaplan-Meier procedure was 0.5285 (SE = 0.1623). The maximum estimated cub survival was practically the same, 0.5328 (SE = 0.1629). Cub survival estimated with a binomial model (Williams et al. 2001) for the same sample was 0.5833 ± 0.1610 (95% C.I.). In order to improve the reliability of puma cub survival data, we will make an effort to increase the number of radiocollared cubs that are monitored. The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. We attributed 8 cub mortalities to infanticide, and it is probable that 5 other cubs died directly from infanticide or because their mother was killed when her 4 cubs were at an age (87 days) when they could not survive without her (Appendix A). Male-caused infanticide, along with aggression-caused mortality in adult (indicated previously) and subadult pumas (Logan and Sweanor 2001) has also been a dominant mortality factor in other puma populations in North America (Logan and Sweanor 2001:115-136). Such male puma behavior has been theorized for being a strong selective force in shaping the evolution of behavioral tactics, social structure, and life history strategies in pumas (Logan and Sweanor 2001). The closure on sport-hunting on the study area and protection of marked pumas from sportharvest on the buffer area on the northern portion of the Uncompahgre Plateau for the reference period operated as designed to remove sport-hunting as a cause of death in the study population. Of the adult and subadult pumas wearing a functional GPS/VHF-collar, only 1 adult puma died due to human causes on the study or buffer areas (F7 killed for depredation control, mentioned previously). This reference condition enabled us to quantify puma population structure, survival rates, and agent-specific mortality rates of pumas in the absence of direct human-caused mortality by sport-hunting, and will allow comparisons with the treatment period when puma hunting manipulates the puma population on the study area. Furthermore, we recorded deaths of 7 non-marked pumas that died since 2004, mainly from human causes (Table 14). Six non-marked pumas (2 males, 4 females) were struck by vehicles on highways or a county road along boundaries of the study area. In addition, 2 marked female cubs (mentioned previously) were killed in vehicle collisions on a highway. Both of those cubs were offspring of F16 which has a home range straddling highway 550 south of Montrose. Of the 8 pumas killed by vehicles, 5 were dependent cubs, 2 were probably subadults, and 1 was an adult female. A bizarre natural mortality case we documented was of a non-marked adult female found in Roubideau Canyon that was lodged in a narrow fork of an aspen tree and probably died of asphyxia due to compression of the thorax. Anderson et al. (1992:50) reported on the fates of 21 radio-collared pumas (11 pumas <24 months old, and 10 ≥ 24 months old) from a total of 49 in his previous study which was intended to “assess the effects of sport-hunting on an unexploited population” (Anderson et al. 1992:5). They found 19 of the 21 deaths (i.e., 90%) were due to human causes, attributed to: legal kill outside the study area (7), research capture-related (6), predator management (3), illegal kill (2), and suspected predacide (1). Other causes of mortality included, intraspecies strife (1) and disease (1). Actual age-stage and annual survival rates and agent-specific mortality rates from our current effort cannot be clearly compared with the Anderson et al. (1992:53) effort because they pooled data for male and female pumas in seemingly arbitrary age stages that overlapped puma life history stages (i.e., cubs, subadults, adults). The Anderson et al. (1992:53) estimated survival rates with the Kaplan-Meier procedure (Pollock et al. 1989) for 20 male and 22 female pumas were: 12-24 month old = 0.642; 24-36 months old = 0.692, 36 to 48 months old = 0.917, and 48- 140 �60 months old = 0.800. Actual sample sizes within each age category were not given. There were no quantitative data allowing estimation of survival and agent-specific mortality for cubs less than 12 months old. Anderson et al. (1992) found that all 9 radio-collared male pumas dispersed from their natal areas, and 2 of 6 radio-collared females did not disperse from their natal areas (A. E. Anderson, Sep. 1993, errata for Anderson et al. 1992:61). Mean ± SD and range of dispersal distances (km) for 8 males, aged 10 to 13 months old at dispersal, were 86.2 ± 51.3, 23 to 151. For 4 females, aged 11 to 31 months old at dispersal, mean ± SD and range of dispersal distances (km) were 37.0 ± 15.3, 17 to 54 (Anderson et al. 1992:63). Segment Objective 5 To investigate the potential that puma hunters might detect puma mothers away from their cubs, we continued gathering data on spatial associations of puma mothers and their cubs during the puma hunting season, which extends from November through March each winter in Colorado. Female pumas are fair game in Colorado, unless they are accompanied by 1 or more cubs. Mothers that are caught away from their cubs could be legally harvested. Such incidents would result in cubs being orphaned. Orphaned cubs that are ≤6 months old could have a survival rate (to the subadult stage) of < 0.05. Orphaned cubs 7 to 12 months old might have a survival rate (to the subadult stage) of about 0.7 (K. Logan, unpublished data). We monitored 7 puma families with a radio-collared mother and at least 1 radio-collared cub from November 6, 2008 to March 20, 2009 during 11 airplane flights (Table 15). To assess whether mothers were apart or in close association with cubs, we considered error in aerial locations. We recovered 28 puma radiocollars (i.e., of dead pumas or shed collars from cubs) that we located from the airplane and then fixed the actual locations of collars on the ground with hand-held GPS receivers. Range of location error was 5 to 660 m (mean = 260, SD = 179.73). We used distances greater than the extreme high range of location error (660 m) as the metric to decide if puma mothers might be detected away from their cubs by hunters. In aggregate, the data for the past 4 winters include 171 observations for 1−7 families per winter (Table 15), and generally indicate that puma mothers are more likely (87% of observations) to be within 660 m of their cubs during the day in winter. An effort will be made to increase the number of radio-collared family members in subsequent winters. If the total sample size allows, we want to examine variation in mother-cub association distances on an individual female basis. Moreover, we will gather direct information on the frequency that cubs are orphaned and their survival during the treatment period when the pumas are hunted. Anderson et al. (1992:70-71) recorded 69 instances of simultaneous aerial locations of 7 pairs of puma mothers and dependent young. They reported that mothers and young were together in 21 (30.4%) of those instances, and they were 1 to 2.2 km apart in 48 (69.6%) of those instances. Segment Objective 6 We used the data gathered so far in the reference period for a preliminary evaluation of 5 assumptions used by CDOW biologists and managers to manage puma populations with sport-hunting. Assumption 1: The CDOW assumes density ranges of 2.0 to 4.6 puma/100 km2 (i.e., includes pumas of all age stages- adults, subadults, and cubs, J. Apker, CDOW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to DAUs to guide the model-based quota-setting process. Assuming that on average 66% of the population is comprised of adults and subadults (previously), then the range of density for independent pumas would be 1.3 to 3.0/100 km2. The population sex and age structure is also assumed to be similar to puma populations described in the intensive studies in the literature on puma populations (CDOW 2007). 141 �H1: Puma densities during the reference period and the treatment period will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a similar sex and age structure to puma populations studied intensively in Wyoming, Idaho, Alberta, and New Mexico (CDOW 2007). We have partially addressed H1 with a preliminary minimum estimated density of 2.0 to 2.2 independent pumas/100 km2 of estimated winter habitat on the Uncompahgre Plateau study area in RY4 (i.e., 33 minimum independent pumas/1,671 km2) and RY5 (i.e., 37 minimum independent pumas/1,671 km2). These minimum density estimates represent the mid-to-high range of density for independent resident pumas in some North American populations (i.e., range 0.3-2.2/100 km2, Logan and Sweanor 2001:167), but lower than higher estimates for independent pumas in more recent studies in Wyoming (3.4/100 km2, Anderson and Lindzey 2005) and Utah (3.2/100 km2, Choate et al. 2006). Moreover, the sex and age structure of the minimum population observed in winter of reference year 4 (i.e., RY4) is similar to descriptions of other puma populations in western states (Logan and Sweanor 2001:167). Assumption 2: The adult plus subadult (i.e., harvest-age pumas) segment of the population exhibit a moderate annual rate of growth of 15% (i.e., λ = 1.15, CDOW 2007). H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. Puma population modeling using population characteristics and vital rates from this current research effort supports this assumption (Appendix B). Expected lambda (i.e., finite rate of population change of independent pumas) ranges from 1.17 to 1.22 and an average of 1.20 ± 0.0182 SD (n = 5; TY1-TY5) for the no harvest model (Appendix B, Table B.7). Expected lambda for the modeled non-hunted puma population on the Uncompahgre Plateau are consistent with the high range of observed average annual rates of population increase for a non-hunted puma population in good quality habitat in southern New Mexico (i.e., r = 0.21, n = 4 yr.; r = 0.28, n = 4 yr.; r = 0.17, n = 4 yr.; r = 0.11, n = 7 yr.; Logan and Sweanor 2001:169-175). Puma population growth might be higher on the Uncompahgre Plateau because of higher quality habitat (i.e., greater vulnerable prey biomass), and if puma sources are nearby to the study area which provide immigrants. Assumption 3: Puma harvest rate formulations for DAUs assume that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). Harvest is assumed to be additive to natural mortality. H3a: The puma population is not expected to decline, therefore, we should be observing puma population parameters characteristic of a stable or increasing hunted puma population. Preliminary modeling results with 15% and 16% mortality in the harvest-age population indicates expected stable or increase population phases, with additive harvest mortality (Appendix B, Tables B.3, B.4, B.5, B.8, B.9, Fig. B.2). H3b: Harvest mortality of 15% of the adults and subadults will be strongly additive to other natural causes of mortality. Preliminary survival rates for annual and shorter-term hunting season periods for adult-age pumas in the reference period indicate high survival (Table 11). Similarly, a course survival rate for 9 subadult radiocollared pumas in the reference period is also high (finite rate of survival during the subadult stage: 8/9 = 0.89). These rates partially support the assumption that additive mortality caused by hunting can be expected. A direct test of this assumption will develop in the treatment period. Assumption 4: To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality 142 �guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a decline in the abundance of harvest-age pumas (i.e., adults and subadults). Preliminary modeling results with 16% mortality or greater in the harvest-age population and with greater than 45% of the harvest comprised of females indicates expected puma population declines (Appendix B, Tables B.6, B.10, B.12−B.16, Figs. B.2−B.4). Assumption 5: The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Preliminary results as indicated by the age structure of independent pumas captured for the first time in 2004-05 (Logan 2005), at first capture (Fig. 3), and the age structure of the independent puma population in March 2009 (Fig. 5), and apparently high adult and subadult survival rates during the reference period support the hypothesis for a young age structure early in the reference period with an aging structure later at the end of the period. Segment Objective 7 Principal investigator K. Logan with CDOW biologists and managers developed by consensus a preliminary structure (i.e., official approval pending Wildlife Commission decision in September 2009) to manipulate the puma population with sport-hunting on the study area during the treatment period. The hunting season will begin in mid-November and extend to January 31, unless the last puma on the design quota is killed before January 31, which will effectively close the season on the study area. The harvest quota will be 8 pumas (i.e., 15% harvest of the estimated minimum number of independent pumas), with the objective to manage for a stable to increasing population. The quota of 8 is based on the projected minimum number of independent pumas expected on the study area in winter 2009-10, modeled from a minimum count during winter 2007-08 (see Appendix B, Table B.7). No assumptions about additional pumas on the study area are made or contrived. The quota of 8 is expected to allow the population to achieve a stable or increase phase even if the quota is exceeded due to potential ideal snow-tracking conditions that could result in multiple pumas being killed within a mandatory 48-hour reporting period. Such an overharvest might be expected to reach 20 to 30% over the design harvest (in this case ~2 pumas killed over the harvest; J. Apker, Carnivore Biologist, CDOW, person. comm. June 8, 2009). The number of hunters on the study area at any particular time each hunting season will not be limited. However, each hunter on the study area will be required to obtain a hunting permit from the CDOW Montrose Service Center. Permits will be free and unlimited. Each permit will allow the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wish to continue hunting past the permit expiration date can request a new permit for another 14 days or until the hunting season on the study area closes due to the quota being reached or the end of the hunting season. (The number of pumas killed on the study area each winter will be regulated by the design quota, discussed previously.) This permit system is expected to allow the CDOW to monitor the number of hunters on the study area and to contact each hunter for survey information. All pumas harvested on the study area will be subject to the examination check and seal mandated by the State of Colorado. Hunters must report their puma kill to CDOW within 48 hours of harvest and 143 �present the puma carcass for inspection within 5 days of harvest. At the time of carcass check-in a biologist with the puma research team will inspect the puma to assist in recording information on the CDOW puma harvest data form and to collect an upper premolar tooth for aging (i.e., mandatory) and a tissue sample using a 6 mm biopsy punch (i.e., voluntary) for DNA genotyping. Each successful hunter will also be asked at that time to complete a one-page hunter survey form. All other hunters that do not report a puma kill on the study area will be contacted and asked to complete the survey. Hunter harvest will provide direct evidence of removal rates of marked puma for survival and agent-specific mortality data, and to help evaluate the relative vulnerability of pumas to harvest and potential for hunter selectivity. Hunter harvest will also reveal availability and sex and age classes of unmarked pumas on the study area. After the design quota is filled or January 31 (whichever comes first), puma research teams will immediately activate for capture operations with trained dogs. Two fully-staffed capture teams, one detailed on the east slope and one detailed on the west slope, will systematically and thoroughly search the study area to capture, sample, and GPS/VHF radiocollar pumas the remainder of winter and early spring when snow-tracking conditions can facilitate those efforts. These efforts are necessary to maintain samples to quantify population sex and age structure and estimate minimum population size and other population parameters. Segment Objective 8 Principal investigator K. Logan developed another draft study plan pertaining to the next 5 years of puma research on the Uncompahgre Plateau. The draft plan was subjected to an internal review by researchers and was circulated for review to Carnivore Biologist J. Apker, Area 18 Biologist B. Banulis, Southwest Regional Biologist S. Wait, and Area 18 Wildlife Manager R. Del Piccolo. Comments were incorporated into a substantially modified study plan which was reviewed by Mammals Researcher Dr. Chad Bishop (now the Mammals Research Leader). That study plan will be modified to address new considerations and will be submitted to Mammals Research Leader Chad Bishop in fall 2009. Segment Objective 9 Data from 26 (8 male, 18 female) GPS-collared pumas, totaling over 39 thousand GPS locations (Table 16) will be used to examine the social structure of the puma population on the Uncompahgre Plateau and to examine movements of pumas relative to Game and Data Analysis Unit boundaries. Those data will also be used in a set of collaborative projects, including: examination of puma behavior in relation to human development with Mammals Researcher Dr. Mat Alldredge, who is studying pumahuman interactions on the Colorado Front Range; modeling and mapping puma habitat in Colorado and other western states with Dr. Kevin Crooks and Dr. Chris Burdett (Department of Fish, Wildlife and Conservation Biology, Colorado State University- DFWCB, CSU); evaluation of puma detection rates using camera grids with Dr. Kevin Crooks and Ph.D. candidate Jesse Lewis (DFWCB, CSU). Furthermore, puma population and genetic data from the Uncompahgre Plateau can be used in collaboration with Dr. Alldredge’s puma research efforts on the Front Range to examine similarities or differences in puma population dynamics and social structure between the 2 environments. We are currently collaborating with Dr. Sue VandeWoude and Dr. Kevin Crooks, and postdoctoral and graduate students at the College of Veterinary Medicine and Biomedical Sciences, Department of Microbiology, Pathology, and Immunology, Colorado State University in a pilot study titled: Puma concolor immune health― Relationship to management paradigms and disease. Tissue samples (i.e., blood, saliva, feces) from pumas we capture are collected and shipped to the DMIP for analyses. That project has been expanded to The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids. A description of that project and incomplete results on infectious disease surveillance on 35 individual pumas (22 independent 144 �females, 12 independent males, and 1 male cub) sampled on the Uncompahgre Plateau are presented in Appendix C. Those data contributed to a publication in Emerging Infectious Diseases (accepted), titled Plague and wild felids: zoonotic disease in the western US , a paper on seroprevalence in populations of pumas and bobcats in the western United States by collaborators: Sarah N. Bevins1, Jeff A. Tracey1, Sam P. Franklin1, Virginia L. Schmit1, Martha L. MacMillan1, Kenneth L. Gage2, Martin E. Schriefer2, Kenneth A. Logan3, Linda L. Sweanor1, Mat W. Alldredge3, Karoline Krumm1, Walter M. Boyce4, Winston Vickers4, Seth P.D. Riley5, Lisa M. Lyren6, Erin E. Boydston6, Melody E. Roelke7, Robert Fischer6, Kevin R. Crooks1, and Sue VandeWoude1 (1Colorado State University, USA; 2DVBID Centers for Disease Control, USA; 3Colorado Division of Wildlife, USA; 4University of California, Davis, USA; 5 National Park Service, USA; 6United States Geological Survey, USA; 7 National Cancer Institute, USA). SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 4.7 years of effort in a reference period, 109 pumas have been captured, sampled, marked, and released. Of those animals, 91 were radio-collared, allowing us to monitor fates of pumas in all sexes and age stages, including: 19 adult females, 12 adult males, 4 subadult females, 5 subadult males, 30 female cubs, 30 male cubs (some individuals occur in more than one age-stage). Data from the marked animals are used to quantify puma population characteristics and vital rates in a reference situation without sport-hunting off-take as a mortality factor. Our efforts to quantify puma population characteristics and vital rates in a reference condition positioned us to develop a puma population model, and to use the population data and modeling scenarios to conduct a preliminary assessment of CDOW puma management assumptions and to guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CDOW wildlife biologists and managers for assessing puma harvest strategies. To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes on life stages and sexes. The treatment period, scheduled to begin winter 2009-10 and to extend the following 5 years, will be a population-wide evaluation of sport-hunting impacts on a puma population. Furthermore, we will continue collaboration efforts with colleagues on investigations of puma population parameter estimation, puma-human relations, puma habitat modeling and mapping, wild felid disease surveillance, and individual puma detection rates in camera grid designs. All of these efforts should enhance the Colorado puma research and management programs. 145 �LITERATURE CITED Anderson, A. E. 1983. A critical review of literature on puma (Felis concolor). Colorado Division of Wildlife Special Report No. 54. _____, D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Technical Publication No. 40. Colorado Division of Wildlife, Denver. Anderson, C. R., Jr., and F. G. Lindzey. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. Beier, P., and R. H. Barrett. 1993. The cougar in the Santa Ana Mountain Range, California. Orange County Cooperative Mountain Lion Study Final Report. Bergman, E. J., M. W. Alldredge, K. A. Logan, M. Shuette, C. J. Bishop, and D. J. Freddy. 2007. Study Plan-Pilot evaluation of predator-prey dynamics on the Uncompahgre Plateau. Pages 83-96 in Bergman, E.J. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Wildlife Research Report July: 73-96. Colorado Division of Wildlife, Fort Collins. Bishop, C.J., G. C. White, and P.M. Lukacs. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085-1093. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical informationtheoretic approach. Springer-Verlag, New York, New York, USA. Caughley, G. 1978. Analysis of vertebrate populations. John Wiley and Sons, New York. Colorado Division of Wildlife 2002-2007 Strategic Plan. 2002. Colorado Department of Natural Resources, Division of Wildlife. Denver. Colorado Division of Wildlife. 2007. Colorado mountain lion management data analysis unit revision and quota development process. Colorado Division of Wildlife, Denver. Conover, W. J. 1999. Practical nonparametric statistics. John Wiley & Sons, Inc., New York. Cooch, E., and G. White. 2004. Program MARK- a gentle introduction, 3rd edition. Colorado State University, Fort Collins. Culver, M., W. E. Johnson, J. Pecon-Slattery, and S. J. O’Brien. 2000. Genomic ancestry of the American puma (Puma concolor). The Journal of Heredity 91:186-197. Currier, M. J. P., and K. R. Russell. 1977. Mountain lion population and harvest near Canon City, Colorado, 1974-1977. Colorado Division of Wildlife Special Report No. 42. Heisey, D. M., and T. K. Fuller. 1985. Evaluation of survival and cause specific mortality rates using telemetry data. Journal of Wildlife Management 49:668-674. Kendall, W.L. 2001. The robust design for capture-recapture studies: analysis using program MARK. Pages 357-360 in R. Field, R. J. Warren, H. Okarma, and P. R. Sievert, editors. Wildlife, land, and people: priorities for the 21st century. Proceedings of the Second International Wildlife Management Congress. The Wildlife Society, Bethesda, Maryland, USA. Koloski, J. H. 2002. Mountain lion ecology and management on the Southern Ute Indian Reservation. M. S. Thesis. Department of Zoology and Physiology, University of Wyoming, Laramie. Kreeger, T. J. 1996. Handbook of wildlife chemical immobilization. Wildlife Pharmaceuticals, Inc., Fort Collins, Colorado. Laundre, J. W., L. Hernandez, D. Streubel, K. Altendorf, and C. L. Lopez Gonzalez. 2000. Aging mountain lions using gum-line recession. Wildlife Society Bulletin 28:963-966. Logan, K. A., E. T. Thorne, L. L. Irwin, and R. Skinner. 1986. Immobilizing wild mountain lions (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases. 22:97-103. _____, L. L. Sweanor, J. F. Smith, and M. G. Hornocker. 1999. Capturing pumas with foot-hold snares. Wildlife Society Bulletin 27:201-208. _____, and L. L. Sweanor. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. 146 �_____. 2004. Colorado puma research and development program: population characteristics and vital rates study plan. Colorado Division of Wildlife, Ft. Collins Research Center, Ft. Collins. _____. 2005. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. July: 105-126, Colorado Division of Wildlife, Fort Collins. _____. 2008. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. Murphy, K., M. Culver, M. Menotti-Raymond, V. David, M. G. Hornocker, and S. J. O’Brien. 1998. Cougar reproductive success in the Northern Yellowstone Ecosystem. Pages 78-112 in The ecology of the cougar (Puma concolor) in the Northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow. Otis, D. L., K. P. Burnham, G. C. White, and D. R. Anderson. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. Ott, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. Pierce, B. K., V. C. Bleich, and R. T. Bowyer. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989a. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. _____, S. R. Winterstein, and M. J. Conroy. 1989b. Estimation and analysis of survival distributions for radio tagged animals. Biometrics 45:99-109. _____, J. D. Nichols, C. Brownie, and J. E. Hines. 1990. Statistical inference for capture-recapture experiments. Wildlife Monographs 107:1-97. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. Sweanor, L. L., K. A. Logan, and M. G. Hornocker. 2000. Cougar dispersal patterns, metapopulation dynamics, and conservation. Conservation Biology 14:798-808. _____, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:1076-1084. Van Ballenberghe, V. 1983. Rate of increase of white-tailed deer on the George Reserve: a re-evaluation. Journal of Wildlife Management 47:1245-1247. Watkins, B. 2004. Mountain lion data analysis unit L-22 management plan. Colorado Division of Wildlife, Montrose. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., D. R. Anderson, K. P. Burnham, and D. L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787NERP. Los Alamos, NM, U.S.A. Worton, B. J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. Young, S. P. and E. A. Goldman. 1946. The puma: mysterious American cat. The Wildlife Institute, Washington, D. C. Prepared by: Kenneth A. Logan, Wildlife Researcher 147 �Table 1. Summary of puma capture efforts with dogs from December 9, 2008 to April 30, 2009, Uncompahgre Plateau, Colorado. Month No. Search Days 11 No. & type of puma tracks founda 16 tracks: 6 male, 6 female, 4 cub No. & type of pumas pursued 10 pursuits: 5 males, 5 females, 4 cubs No. & I.D. or type of pumas captured, observed, or identified December 6 pumas captured 8 times: M71 recaptured (not handled), M55 recaptured twice (not handled to change faulty GPS collar due to dangerous tree & cliffs), F93 captured twice- the first time, then with her 2 large cubs F95 and a male cub that could not be handled in a hole, F94 captured for the first time. In addition, male puma tracks found and attributed to M32 by VHF telemetry (no pursuit with hounds). January 17 38 tracks: 17 male, 17 pursuits: 6 males, 5 pumas captured 6 times: M55 (faulty GPS 10 female, 11 cub 4 females, 7 cubs collar changed), F93 recaptured while cub F95 and unmarked male cub escaped, F16 recaptured (faulty GPS collar changed) while M6 (consort) escaped, F96 captured for first time while 2 cubs escaped, F96 recaptured while 2 cubs escaped, cub M84 recaptured (handled to fit with new expandable cub collar). In addition, M6 and F16 were detected by tracks and identified with VHF telemetry on 2 other occasions. M51 was detected by tracks and identified with VHF telemetry and pursued, but was not caught to change his GPS collar on low battery. F93 and F95 were detected by tracks with non-marked cub and identified with VHF telemetry. February 15 64-65 tracks: 12-17 26 pursuits: 3-4 5 pumas captured: cub F97 captured for the first male, 26-31 female, males, 7-8 females, time while mother F23 & sibling F81 escaped. 24-27 cub 15 cubs Cub M82 recaptured and fit with new VHF collar, while mother F8 escaped and confirmed with VHF telemetry. Cub F98 captured for the first time; one of three cubs of an unmarked adult female puma visually observed with F98 on 217-09. M29 recaptured, but could not be handled in dangerous cliffs to replace faulty GPS collar. M99 captured for first time; sibling of F98. March 15 56 tracks: 24-26 15 pursuits: 4-5 4 pumas captured 5 times: F98 recaptured while male, 21-23 female, 9 males, 3-4 females, mother and 2 sibling cubs escaped, M99 cub 7 cubs captured for first time while mother and siblings F98 and non-marked cub escaped, M99 and nontagged cub visually observed, M100 captured for the first time. April 13 24-27 tracks: 17 0 pumas captured. One male pursued identified 7-10 pursuits: 4 male, 6 female, 1-4 males, 2 females, 1- as M55 with GPS data. Another male pursued cub identified as M100 with GPS data. Two females 4 cubs and their cubs pursued identified as F70 and F96 with 1-4 cubs with VHF telemetry. 71 198-202 tracks: 75-78 pursuits: 24 captures of 17 individuals: 4 independent TOTALS 76-83 male, 22-24 males, pumas (F93, F94, F96, M100) and 4 marked 69-76 female, 21-23 females, (F95, F97, F98, M99) and 2 non-marked cubs 49-55 cub 34-37 cubs were captured for the 1st time. 10 independent pumas were detected by tracks and identified with GPS/VHF telemetry 12 times: M6 (twice), F8, F16 (twice), M32, M51, M55, F70, F93, F96, M100. a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Pumas are not handled for a variety of safety reasons: tree too dangerous to climb for researchers, puma treed near river, creek or cliff, puma might fall from tree after drug induction. 148 �Table 2. Summary of puma capture efforts with dogs, December 2004 to April 2009, Uncompahgre Plateau, Colorado. Period Track detection effort 109/78 = 1.40 tracks/day Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day 198/71 to 202/71 = 2.79-2.84 tracks/day Pursuit effort 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture Table 3. Adult and subadult pumas captured for the first time, sampled, tagged, and released from December 2008 to May 2009, Uncompahgre Plateau, Colorado. Puma I.D. F93 F94 F96 M100 Sex F F F M Estimated Age (mo.) 72 41 36 72 Mass (kg) Capture date 12-15-08 12-19-08 01-28-09 03-27-09 32 36 40 64-68 estimated* F104 F 96 40 05-21-09 *M100 could not be weighed by scale due to steepness of terrain. 149 Capture method Dogs Dogs Dogs Dogs Location Coal Bank Canyon Shavano Valley Dolores Canyon San Miguel Canyon Cage Trap Roubideau Canyon �Table 4. Pumas that were captured and observed with aid of dogs, or observed in association with another radio-collared puma, but were not handled at that time for safety or other reasons, December 2008 to March 2009, Uncompahgre Plateau, Colorado. Puma sex Capture date Location Comments M55 Age stage or months 42 12-12-08 Dolores Canyon M55 Male 42 16 12-21-08 12-29-08 Spring Creek Dry Creek Basin Female Unk. adult 02-19-09 San Miguel Canyon Unknown 5 02-19-09 San Miguel Canyon M29 129 02-25-09 Unknown 6 03-11-09 Big Bucktail Canyon San Miguel Canyon M55 bayed in a hole then climbed a tree too dangerous for handling to replace non-functioning GPS collar. M55 bayed on cliffs too dangerous for handling. Non-marked male cub of F93 and sibling of F95 took refuge in narrow hole; unable to handle him. Non-marked adult female puma was visually observed with radio-collared cub F98 and a non-marked cub (either M99 later marked or non-marked sibling below), but could not be caught with dogs. Non-marked cub was visually observed with radio-collared cub F98 and non-marked adult puma, but could not be caught with dogs. M29 bayed in cliffs too dangerous for handling. Non-marked cub- sibling of F98 & M99- visually observed with radio-collared cub M99, but could not be caught with dogs. Table 5. Pumas recaptured with dogs, cage traps, or visually observed, December 2008 to January 2009, Uncompahgre Plateau, Colorado. Puma I.D. Recapture Date 12-08-08 Mass (kg) Observed Estimated Age (mo.) 35 Capture Method/ Location Dogs/Shavano Mesa M71 F93 12-29-08 Observed 72 Dogs/Dry Creek Basin F93 01-08-09 Observed 72 Dogs/Shavano Valley F96 01-29-09 Observed 36 Dogs/Dolores Canyon 150 Process M71 wore a functioning vhf collar; no need to handle him. F93 wore a functioning GPS collar; no need to handle her. F93 wore a functioning GPS collar; no need to handle her. F96 wore a functioning GPS collar; no need to handle her. �Table 6. Summary of puma capture efforts with ungulate road-kill baits and cage traps from August 20, 2008 to July 20, 2009, Uncompahgre Plateau, Colorado.a Carnivore activity & capture effort resultsb No puma activity detected. One deer carcass scavenged by coyotes. Deer carcasses scavenged by male puma 9-14-08; likely M55 (trail camera photos). Set cage trap 9-15-08. Puma did not return. Bobcat fed on deer carcass in cage trap. A bobcat, a black bear and domestic dogs scavenged 3 different deer carcasses. October 3 Deer carcass scavenged by bobcat. November 6 Female puma scavenged a deer carcass 11-21 to 22-08. Cage trap set 11-23-08; but, female puma did not return. Male puma scavenged a deer carcass 11-24-08, and cage trap set 11-2408. The male puma returned, walked around the trap, but did not enter. Female puma and bobcat scavenged a carcass 11-24-08. Cage trap set 11-24-08. Bobcat captured and released 1124-08. Subadult female puma F66 recaptured and radio-collared 11-25-08. December 2 No puma activity detected. February 2 A female or small male puma walked ~20 m past a deer carcass but did not feed. Another deer carcass was scavenged by a bobcat. March 4 A male puma walked ~5 m past 2 different deer carcasses but did not feed. Three deer carcasses were scavenged by 2 gray foxes and 2 bobcats. April 1 Male puma M55 scavenged a deer carcass 5-6-09. No need to recapture him. May 4 Female puma fed on a deer carcass 5-8 to 10-09. Set cage trap 5-11-09. Female puma returned but did not enter cage trap. Set 2 cage traps 5-12-09; but female puma did not return. Female puma (possibly same as previous) scavenged deer carcass 5-21-09. Cage trap set 5-21-09. F104 captured. A black bear scavenged one deer carcass. July 2 Puma F72b was recaptured 7-20-09 in cage trap set for bobcat study. Her malfunctioning GPS collar was replaced. A non-marked puma was photographed at one deer bait 7-17-09; but it did not feed. Same deer bait was scavenged by ~5 different black bears. a We used 36 road-killed mule deer at 17 different sites. Of the road-killed ungulate baits, 7 of 36 (19.4%) were scavenged by pumas. b Adult female puma F72 was recaptured in a bobcat cage trap baited with a predator call box and visual attractant. Month August September No. of Sites 2 5 Table 7. Puma cubs sampled September 2008 to June 2009 on the Uncompahgre Plateau Puma Study area, Colorado. a Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M91 M92 F95 F97 F98 M99 M101 M102 F103 M105 F106 M107 F108 M109 M M F F F M M M F M F M F M August 19, 2008 August 19, 2008 August 2007 May 23, 2008 Sep.-Oct. 2008 Sep.-Oct. 2008 April 15, 2009 April 15, 2009 April 15, 2009 May 7, 2009 May 7, 2009 May 25, 2009 May 25, 2009 May 25, 2009 35 35 488 257 122-152 152 35 35 35 38 38 34 34 34 2.5 2.8 33 20 9.5 13.6 2.8 2.5 2.1 2.6 2.6 2.0 1.75 1.75 F25 F25 F93 F23 Fb Fb F16 F16 F16 F75 F75 F94 F94 F94 110 110 56 45 Unk. Unk. 75 75 75 55 55 46 46 46 Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs with mother only with radio-telemetry. b F98 and M99 were captured in association with an non-marked adult female puma and another non-marked cub. 151 �Table 8. Minimum puma population estimate based on numbers of known radio-collared pumas, visual observations of non-marked pumas, and track counts of suspected non-marked pumas on the study area during the past 2 winters, November 2007 to March 2008 and November 2008 to April 2009, Uncompahgre Plateau study area, Colorado. Adults Winter & Region Nov.07-Mar.08 East slope West slope Totals Female Male Subadults Female Male 10 4 3 6 4 2 16 8 5 Total Independent Pumas = 33a,b 4 0 4 Nov.08-Apr.09 East slope West slope Totals Female Cubs Male Unknown sex 4 1 5 4 2 6 7 2-3 9-10 11-13 5-6 2-4 0-1 2 5 5 9-10 4 1-2 1 3 2 4 20-23 9-10 3-6 1-2 5 7 9 Total Independent Pumas = 37c,d a Of the total, 23−24 (70−73%) independent pumas were marked and 9-10 (27−30%) were assumed to be non-marked, but some might have ear-tags, tattoos, or non-functional GPS/VHF collars. b The non-marked independent pumas included: 1adult female with 2 large cubs in Happy Canyon, 1 adult female with 1 large cub in Potter Creek and 25-mile Mesa, 1 adult female with 2 large cubs in Monitor Creek, 1 adult female with 2 medium-size cubs in Potter Creek, 1 adult female with 2-3 cubs in San Miguel Canyon, and 1 female or F28 with a non-functional collar Big Bucktail Creek to San Miguel Canyon. c Of the total, 23−25 (62−68%) independent pumas were marked and 12-14 (32−38%) were assumed to be non-collared, but some might have ear-tags, tattoos, or non-functional GPS/VHF collars. d The non-marked independent pumas included: 1 adult female with 2 cubs on N. McKenzie Mesa, 1 subadult or adult female in Linscott Creek, 1 adult female in Monitor Creek, 1 subadult or adult female in Roubideau Canyon, 1 subadult or adult male in Monitor Creek, 1 adult female with 3 cubs in San Miguel Canyon, 1 adult female with ≥1 cub or F28 with a non-functional GPS collar in Big Bucktail Canyon to N. Fork Cottonwood Creek, 1 adult female or F24 with non-functional GPS collar in Horsefly Creek to Dead Horse Mesa, 1 adult female or F28 with non-functional GPS collar in San Miguel Canyon W of Pinion, 1 adult female with ≥1 cub on Mailbox Park, 1 adult female with 1 cub from McKenzie Creek to Iron Springs Mesa. 1 subadult or adult female on Iron Springs Mesa, 1 subadult female in Big Bucktail Canyon to ridge E of Nucla, 1 subadult male from Pinion across Big Bucktail Canyon and ridge E of Nucla. 152 �Table 9. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2009. Consort pairs and estimated agesa Dates pairs Estimated Estimated Estimated Observed consortedb birth datec birth interval gestation number of Female Age Male Age (mo.) (days) cubsd (mo.) (mo.) F2 53 05/28/05 3 F2 67 07/29/06 14.0 2 F2 89 05/19/08 22.0 4 F3 36 08/01/04 1 F3 50 M6 37 06/22-24/05 09/26/05 13.8 93-95 2 F3 62 09/17/06 11.7 3 F3 84 M51 60 03/31/08 07/03/08 21.5 94 3 F7 67 05/19/05 2 F7 82 08/13/06 14.9 4 F7 106 07/10/08 23.9 3 F8*e 24 06/26/05 2 F8 37 08/13/06 13.4 4 F8 60 M73 49 02/28-29/08 05/29/08 22.5 90-91 2 F16 32 09/22/05 4 F16 52 05/24/07 19.9 4 F16 75 M6 80 01/13-14/09 04/15/09 22.7 91-92 3 F23* 21 05/30/06 3 F23 45 M27 or 78 02/19-25/08 05/23/08 23.8 87-93 3 M29f 107 F24 75 M29 92 04/12-15/07 06/14/07 90-93 4 F25 74 08/01/05 1 F25 94 04/16/07 20.5 1 F25 110 08/19/08 16.1 2 F28* 36 06/09/06 2 F28 48 M29 88 12/27-29/06 03/30/07 11.7 92-93 ≥2 tracks F30* 48 M55 34 04/16-20/07 07/17/07 88-92 3 F50 21 07/01/06 1 F54 24 07/01/06 1 F70* 38 M51 60 03/10/08 06/05/08 87 3 F72* 28 07/09/08 1 F75 32 06/01/07 1 F75 55 M73 61 02/11/09 05/07/09 23 93 2 F93 56 08/07 2 F94* 46 05/27/09 3 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. 153 �Table 10. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2009, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 No. days 616 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 333 934 M6 M27 02-18-05 to 07-31-09 03-10-06 to 05-07-09 1,624 1,154 M29 04-14-06 to 02-25-09 1,048 M32 M51 M55 M71 M73 M100 F2 04-26-06 to 07-31-09 01-07-07 to 03-20-09 01-21-07 to 07-31-09 01-29-08 to 07-31-09 02-21-08 to 07-31-09 03-27-09 to 07-31-09 01-07-05 to 08-14-08 1,192 803 922 549 526 126 1,315 F3 F7 01-21-05 to 01-15-09 02-24-05 to 08-03-08 1,455 1,256 F8 F16 F23 F24 F25 F28 F30 03-21-05 to 07-31-09 10-11-05 to 07-31-09 02-05-06 to 07-31-09 01-17-06 to 09-03-08 02-08-06 to 07-31-09 03-23-06 to 09-25-07 04-15-06 to 07-29-08 1,593 1,389 1,272 960 1,269 551 836 F50 12-14-06 to 03-26-07 102 F54 01-12-07 to 08-18-07 218 F70 F72 F75 F93 F94 F96 F104 01-14-08 to 07-31-09 02-12-08 to 07-31-09 03-26-08 to 07-31-09 12-05-08 to 07-31-09 12-19-08 to 07-31-09 01-28-09 to 07-31-09 05-21-09 to 07-31-09 564 535 492 238 224 184 71 Status: Alive/Lost contact/Dead; Cause of death Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Alive. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-2208 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. Alive. Alive. Lost contact− failed GPS/VHF collar. Alive. Alive. Alive. Alive. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. Estimated age at death 92 months. Lost contact− failed GPS/VHF collar. Dead 08-03-08; killed by U.S., W.S. agent for predator control of depredation on domestic sheep. Estimated age at death 107 months. Alive. Alive. Alive. Lost contact− failed GPS/VHF collar. Alive. Lost contact− failed GPS/VHF collar. Dead; killed by another puma (sex of puma unknown) 07-29-08. Estimated age at death 60 months. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. Estimated age at death 30 months. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. Estimated age at death 49 months. Alive. Alive. Alive. Alive. Alive. Alive. Alive. 154 �Table 11. Preliminary estimated survival rates (S) of adult-age pumas during the reference period (i.e., the study area is closed to puma hunting), Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31) and the hunting season period (November 1 through March 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma deaths in this analysis pertained only to pumas that died of natural causes. Pumas that were killed by people, a non-natural cause (i.e., F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. Period of interest Annual 8/1/2005 to 7/31/2006 Annual 8/1/2006 to 7/31/2007 Annual 8/1/2007 to 7/31/2008 Annual 8/1/2008 to 7/31/2009 Hunting season 11/1/2005 to 3/31/2006 Hunting season 11/1/2006 to 3/31/2007 Hunting season 11/1/2007 to 3/31/2008 Hunting season 11/1/2008 to 3/31/2009 S 1.000 Females SE 0.0000 n 10 S 0.667* Males SE 0.2222* n 6* 0.909 0.0867 11 1.000 0.0000 5 0.831 0.0986 14 1.000 0.0000 7 0.875 0.1031 13 1.000 0.0000 8 1.000 0.0000 6 na na 4 0.909 0.0867 11 1.000 0.0000 5 1.000 0.0000 12 1.000 0.0000 9 1.000 0.0000 11 1.000 0.0000 8 Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. 155 �Table 12. Summary of subadult puma survival and mortality, December 2004 to July 2009, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 04-19-06 to 04-26-06 31 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 M31 7 190 M69 01-11-08 to 04-07-08 87 F95 12-29-08 to 07-31-09 214 Status M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Alive. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old. F52 dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adultstage home range. GPS collar nonfunctional. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-0608 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location). She has been ranging adjacent to and overlapping the northern portion of her natal area. 156 �Table 13. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2009. Puma I.D. 1st capture date on study area 1st capture location→kill or resite location (UTM, NAD27) M5 02-04-05 13S,240577Ex 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278Ex 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M43 09-15-06 12S,746919Ex 4225441N→ 13S,500000Ex 4050000N 12S,760177Ex 4242995N→ 12S,739859Ex 4308557N M49 12-05-06 12S,757241Ex 4258259N→ 12S,693350Ex 4274559N 66.1 M68 08-23-07 80.7 M69 01-11-08 13S,257371Ex 4235231N→ 12S,711262Ex 4198681N 13S,248191Ex 4246810N→ 13T,378900Ex 4591990N F52 01-10-07 13S,258058Ex 4236260N→ 13S,319217Ex 4240467N Estimated linear dispersal distance (km)* 102.2 68.6 369.6 61.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 0124-09; he was about 29 months old. M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adult-stage home range. *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill or recapture site. 157 �Table 14. Recorded deaths of non-marked pumas and of marked pumas struck by vehicles, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2009. Puma sex & ID if marked M Estimated age (mo) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870Ex4227520N Highway 62 east of Dallas divide 13S,250000Ex4222500N F F17 F 11 08-18-06 18-24 11-06-06 F 6 01-30-07 F 36 09-16-08 M 12-24 08-13-08 F F61 18 11-13-08 F 12 08-10-09 Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown Good Good Vehicle collision Good 158 Highway 550 south of Colona 13S,257602Ex4242185N Highway 550 east of Ridgway State Park 13S,259843Ex4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718Ex4255277N Highway 145 west of Placerville 13S,756490Ex4212336N Highway 550 east of Ridgway State Park 13S,259843Ex4235985N Highway 145 east of Norwood 12S,745739Ex4222548N �Table 15. Summary of puma mother and cub associations by distance (m) during airplane flights, each winter, Uncompahgre Plateau, Colorado. Monitoring period Month No. flights No. puma familiesa Ages of cubs (mo.) No. observations with mothers & cubs ≤660 m apart Nov. 9, 2005 to Nov. 3 4 2−6 9 Mar. 29, 2006 Dec. 4 4 3−7 16 Jan. 5 4 4−8 17 Feb. 4 5 5−9 16 Mar. 2 5 6−10 9 Totals 18 4−5 2−10 67 Nov. 7, 2006 to Nov. 4 4 2−3 11 Mar. 22, 2007 Dec. 4 4 2−5 11 Jan. 5 3 4−6 10 Feb. 4 4 5−7 10 Mar. 3 1 8 2 Totals 20 1−4 2−8 44 Nov. 13, 2007 to Nov. 2 1 6 1 Feb. 14, 2008 Dec. 0 1 7 NA Jan. 3 1 8 2 Feb. 3 1 9 2 Totals 8 1 6-9 5 Nov. 6, 2008 to Nov. 3 5 3-6 10 Mar. 20, 2009 Dec. 1 4 4-7 4 Jan. 2 6 5-17 8 Feb. 2 4 7-9 6 Mar. 3 2 7-10 5 Totals 11 2-6 3-17 33 a All puma mothers wore GPS-radiocollars. At least 1 cub in the litter wore a VHF radiocollar. b Mean = 1,097 m, SD = 313.95, range = 670−1,600. c Mean = 1,606 m, SD = 1,665.39, range = 678−4,101. d Mean = 1,341 m, SD = 542.34, range = 759−1,832. e Mean = 2,608 m, SD = 3,360.56, range = 799-7,641. 159 No. observations with mothers & cubs >660 m apart 2 4 3 2 0 11b 0 0 2 1 1 4c 1 NA 1 1 3d 0 0 3 0 1 4e �Table 16. Numbers of GPS locations and spans of monitoring for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to July 2009. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a M M M M M M M M F F F F F F No. locations adult 12-08-04 to 07-20-06 1,797 adult 01-28-05 to 01-14-06 958 adult 02-18-05 to 05-14-08 1,035 adult 03-12-06 to 06-21-06 313 adult 04-14-06 to 01-01-08 1,599 adult 01-07-07 to 07-15-08 1,643 adult 01-21-07 to 04-22-09 1,887 adult 03-27-09 to 06-30-09 318 adult 01-07-05 to 08-14-08 3,516 adult 01-21-05 to 05-14-08 3,344 adult 02-24-05 to 08-03-08 3.922 adult 03-21-05 to 10-10-06 1,541 adult 10-12-05 to 05-13-09 3,157 subadult, 01-04-06 to 02-04-06 113 adult 02-05-06 to 04-22-09 1,083 F24 F adult 01-17-06 to 07-25-07 1,812 F25 F adult 02-09-06 to 06-26-09 3,398 F28 F adult 03-24-06 to 08-15-07 1,499 F30 F adult 03-30-07 to 02-22-08 1,057 F50 F adult 12-14-06 to 03-26-07 352 F52 F subadult 01-10-07 to 05-08-07 383 F54 F adult 01-12-07 to 08-18-08 723 F70 F adult 01-14-08 to 04-29-09 1,486 F72 F adult 02-12-08 to 06-23-09 1,186 F75 F adult 03-26-08 to 06-03-09 1,112 F96 F adult 01-28-09 to 04-29-09 235 F104 F adult 05-29-09 to 08-19-09 274 a GPS collars on pumas were remotely downloaded at approximately 1-month intervals, except during winter 20082009 to summer 2009 due to shortage of technicians during hiring freeze to assist in airplane flights to obtain downloads and to capture pumas to replace GPS collars (lengthening the download interval saved battery power). The last date in Dates monitored includes last location from the last GPS data download acquired for an individual puma. 160 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Estimation Methods for Monitoring Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Grayshaded shapes identify areas of research addressed by puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 161 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Figure 3. Age structure of independent pumas captured and sampled for the first time on the Uncompahgre Plateau, Colorado, December 2004 to May 2009. 162 �Figure 4. Puma births detected by month during the reference period (i.e., no puma hunting), 2005 to 2009 (n = 27 litters of 14 females; 26 of the litters were examined at nurseries when cubs were 26-42 days old and 1 litter confirmed by tracks of ≥2 cubs following GPS-collared mother F28 when cubs were ~42 days old), and during the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1-8 months old), Uncompahgre Plateau, Colorado. Figure 5. Age structure of surviving independent pumas captured and sampled on the Uncompahgre Plateau, Colorado in March 2009, and after protection from sport-hunting mortality since April 2004, which includes 5 hunting seasons (Nov. through Mar., 2004-05 to 2008-09). One human-caused mortality (F7 killed for depredation control 08-03-08) was documented in the radio- and GPS-collared sample of independent pumas on the study area. This age structure assumes that pumas F3, M29, and M51 were alive on March 31, 2009; they each had non-functional GPS collars and were detected alive as late as 1-15-09, 02-25-09, and 03-20-09, respectively. Mean ± SD of adult female and adult male ages, respectively: 5.21 ± 2.29 yr. (62.54 ± 27.42 mo.); 6.31 ± 1.87 yr. (75.67 ± 22.45 mo.). 163 �APPENDIX A Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2009, Uncompahgre Plateau, Colorado. Puma I.D. Estimated Est. Est. survival span Age to last monitor date Status: Alive/Survived to subadult stage/ from 1st capture to Age at Birth alive or at death (days, Lost contact/Disappeared/ fate or last monitor capture date birth to fate) Dead; Cause of death (days) date M5 183 ~8-1-04 02-04-05 to ~1,345 Survived to subadult stage by 09-16-05; independent at ~13 04-07-08 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 4 ½ years old. F9 31 5-28-05 06-27-05 to 326-333 Lost contact― shed radiocollar 04-19-06 to 04-26-06. 4-19-06 F10 31 5-28-05 06-27-05 to 176-215 Lost contact― shed radiocollar 11-20-05― 08-10-05; last tracks of F10 with mother F2 & siblings F9 & 12-29-05 M11 observed 11-20-05. F10 disappeared by 12-30-05. M11 31 5-28-05 06-27-05 to Survived to subadult stage by 12-2-07 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Killed by a hunter in SW 918 CO 12-2-07 at 918 days (30 mo.) old F12 42 5-19-05 07-01-05 to 203-252 Lost contact― shed radiocollar 07-28-05―08-01-05. 12-08-05― Tracks of F12 found in association with mother F7 on 1201-26-06 08-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. F13 42 5-19-05 07-01-05 to 101 Dead; killed and eaten by a puma (sex unspecified) about 808-28-05 28-05. F14 26 6-26-05 07-22-05 to 226-257 Lost contact― shed radiocollar 01-20-06 to 01-25-06. 02-07-06― Tracks of F14 were observed with tracks of mother F8 & 03-10-06 sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. M15 26 6-26-05 07-22-05 to 345-353 Lost contact― shed radiocollar 06-06-06 to 06-14-06. 06-06 to 14-06 F17 34 9-22-05 10-26-05 to 330 Dead. Lost contact― shed radiocollar 06-06-06 to 06-14-06. 08-18-06 Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. F18 34 9-22-05 10-26-05 to 301-308 Dead; probably killed by another puma. Multiple bite 07-20 to 27-06 wounds to skull. 10 mo. old. M19 34 9-22-05 10-26-05 to 308-314 Lost contact― shed radiocollar 07-27-06 to 08-02-06. 07-27 to 08-02-06 M20 34 9-22-05 10-26-05 to 244-245 Lost contact― shed radiocollar 05-24-06―05-25-06. 05-24-06 F21 37 9-26-05 11-02-05 to 324 Lost contact; radiocollar quit. Last aerial location 8-16-06, 08-16-06 live signal. 164 Mother I.D. F3 F2 F2 F2 F7 F7 F8 F8 F16 F16 F16 F16 F3 �Appendix A continued Puma I.D. Estimated Age at capture (days) M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 5-30-06 F35 31 5-30-06 F36 29 6-9-06 M37 29 6-9-06 M38 41 7-29-06 M39 29 8-13-06 F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 12-21-05― 12-22-05 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 86-87 Dead; killed and eaten by male puma 12-21-05―12-22-05. F3 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 06-30-06 to 07-31-06 ~232-235 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 F23 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 38 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. F28 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 63-65 63-65 74 74 352-353 9 255 9 255 53-61 106 200 165 Mother I.D. F23 F23 F28 F2 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 Assumed dead. Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 Lost contact− shed radiocollar by 11-7 to 17-06. Treed, visually observed 03-01-07. Killed by a puma hunter 01-2809 in Deer Creek, west slope of Grand Mesa, CO at 29 months old. F7 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M44 33 Est. Birth date 8-13-06 Est. survival span from 1st capture to fate or last monitor date 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 183 7-1-06 M56c 183 ~8-13-06 F57 35 4-16-07 360 89 360 12-05-06 to 07-31-07 to 01-01-07 F53 89 01-12-07 to 02-23-07 02-14-07 to 03-01-07 05-21-07 to 06-06-07 ~456 42 ~428 subad. 200 52 166 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Lost contact− shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 2006. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. M49 was orphaned when his mother died on about 03-2607; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau 01-24-09 when ~29 months old. Lost contact― shed radiocollar 2-23-07. F53 visually observed by P. & F. Star, on 9-2-07, when F53 was ~14 months old and an independent subadult. F7 Lost contact― shed radiocollar 2-27-07. M56 observed 0301-07. Lost contact― shed radiocollar 06-07-07. Live mode 06-0607. F7 (?) F7 F3 F3 F3 F50 F54 F25 �Appendix A continued Puma I.D. Estimated Age at capture (days) M58 34 Est. Birth date 5-24-07 Est. survival span from 1st capture to fate or last monitor date 06-27-07 Age to last monitor date alive or at death (days, birth to fate) 324 F59 34 5-24-07 06-27-07 to 08-21-07 434 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 08-17-07 262 M65 34 7-14-07 08-17-07 262 167 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F16 Alive. Observed alive 11-20-07 with F16, but without siblings M58 & F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F16 Dead; research-related mortality.d F16 Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11/13/08. Not radio-collared. Not radio-collared. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. F16 F24 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) F66 37 Est. Birth date 7-17-07 Est. survival span from 1st capture to fate or last monitor date 08-23-07 to 11-05-07 Age to last monitor date alive or at death (days, birth to fate) Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Killed by a puma hunter in Disappointment Valley, CO 12-30-08 at 17 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 8/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. Not radio-collared. Apparently died before 2-4-09; no tracks found in association with F23 & siblings F81 & F97. 111 M67 37 7-17-07 08-23-07 M68 37 7-17-07 08-23-07 F74 259 6-1-07 M76 30 5-19-08 03-12-08 to 07-09-08 06-18-08 ~87 M77 30 5-19-08 06-18-08 ~87 F78 30 5-19-08 06-18-08 ~87 M79 30 5-19-08 06-18-08 87 F80 40 5-23-08 07-02-08 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 168 Mother I.D. F30 F30 F30 F75 F2 F2 F2 F2 F23 �Appendix A continued Puma I.D. Estimated Age at capture (days) F81 40 F97 8 ½ mo. 5-23-08 5-23-08 M82 37 5-29-08 M83 37 M84 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-02-08 to 07-29-09 02-04-09 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 424 354 F23 F23 295-308 5-29-08 07-05-08 to 03-20-09 or 04-02-09 07-05-08 Radio-collared. Last live location 7-29-09. Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Radio-collared. F8 36 6-5-08 07-11-08 to 02-11-09 251 Not radio-collared. Apparently died; no tracks found in association with F8 & sibling M82 2-10-09. Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located here on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 211-09. F85 36 6-5-08 07-11-08 F70 F86 36 6-5-08 07-11-08 to 07-23 to 08-03-08 M87 M88 F89 M90 Male 7A 28 28 28 36 28-35 7-3-08 7-3-08 7-3-08 7-9-08 7-10-08 07-31-08 07-31-08 07-31-08 08-14-08 ~08-07-08 to 08-14-08 Male 7B 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Female 7C 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill. Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Not radio-collared. Radio-collared Radio-collared Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for depredating on domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for depredating on domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for depredating on domestic sheep. ~48-59 28 to 35 169 Mother I.D. F8 F70 F70 F3 F3 F3 F72 F7 F7 F7 �Appendix A continued Puma I.D. Estimated Age at capture (days) M91 35 M92 35 F95 16 mo. F98 4-5 mo. Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-29-08 09-29-08 12-29-08 2-12-09 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 8-19-08 Radio-collared. F25 8-19-08 Radio-collared. F25 June-07 Radio-collared. Survived to subadult stage. F93 Sep-Oct23-24 Radio-collared. Died, probably killed by male puma Unm.F 08 (infanticide). M99 5 mo. Sep-Oct2-27-09 Radio-collared. Last location 4-22-09 on Paterson Mt. Unm.F 08 M101 35 4-15-09 05-20-09 Radio-collared. F16 M102 35 4-15-09 05-20-09 Radio-collared. F16 F103 35 4-15-09 05-20-09 Radio-collared. F16 M105 38 5-7-09 06-14-09 Radio-collared F75 F106 38 5-7-09 06-14-09 Not radio-collared; F75 returned to nursery during handling. F75 M107 34 5-25-09 06-28-09 Not radio-collared; too small. F94 F108 34 5-25-09 06-28-09 Shed radiocollar; fastener failed. F94 M109 34 5-25-09 06-28-09 Not radio-collared; too small. F94 a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, possibly restricting movement. 170 �APPENDIX B Puma Population Models and Simulations. Research on the Uncompahgre Plateau Puma Project from December 2004 to July 2009 provides estimates of puma population structure and parameters for a model-based approach developed by CDOW biometrician P. Lukacs and Mammals Researcher K. Logan to examine options for the design of the remainder of this research, and as a preliminary assessment of the CDOW puma management assumptions. Puma Population Modeling Our puma population projections for the study area involved an age-structured, deterministic, discrete time model. The additive puma population model structure is: Nt+1 = Adult Females = (SAF * NAFt + SSF * NSFt) * (1 – HAFt+1) + Adult Males = (SAM * NAMt + SSM * NSMt) * (1 – HAMt+1) + Subadult Females = ((r * SC * NCt) * (1 – HSFt+1)) * PISF/ESF + Subadult Males = (((1 − r) * SC * NCt) * (1 – HSMt+1)) * PISM/ESM + Cubs = Lỹ * AFR * NAFt+1 Terms: NAFt+1 = Number of adult females at year t+1. NAMt+1 = Number of adult males at year t+1. NSFt+1 = Number of subadult females at year t+1. NSMt+1 = Number of subadult males at year t+1. NJt+1 = Number of juveniles at year t+1. S = Survival rate for each specified sex and age stage. H = Proportion of the harvest rate comprised by each sex and age stage (e.g., 0.28 harvest rate * 0.40 adult females). r = Proportion of the subadult population that is female (e.g., 0.5; 1-0.5 = proportion of males). PI/E = Ratio of progeny + immigrants/emigrants. Lỹ = Average litter size. AFR = Proportion of adult females giving birth to new litters each year. Basic assumptions of the model include: 1) expected puma population projections and annual rates of increase (i.e., lambda) are conditional on the assigned puma population structure and demographic estimates, 2) no density dependent responses are built into the model. Density dependence might operate in puma population dynamics, with competition for food regulating adult female density and competition for mates regulating adult male density (Logan and Sweanor 2001), and 3) harvest is additive mortality. We parameterized the model with data gathered on the pumas on the study area during the first 3.7 years. (Data from this past year, 2008-09 could not be used because decisions about harvest structure for the treatment period needed to be made June of that biological year). The starting population was the minimum count of pumas and attendant estimated sex and age structure made during November 2007 to March 2008 (Table B.1). We assumed that all individuals were present in the population during that entire period. No mortalities of independent pumas were detected. But, one radio-collared subadult male emigrated by March 19, 2008. Population parameters included: estimated rates of reproduction and sex and age-stage specific survival, which included data to July 2008 (Table B.2). Some sex and age-stage specific estimates of survival (i.e., adult male, subadult male, subadult female) came from the literature 171 �(Table B.2), because our current sample sizes (i.e., number of individuals and years) may not be adequate for realistic estimates (i.e., adult males and subadults). We did not use actual rates in the literature where estimates involved the pooling of data on sexes and age stages, and where sample sizes for age stages were not presented (e.g., Anderson et al. 1992). In addition, the ratio of progeny and immigrant recruits to emigrants as a model input was from the literature, because such data is scarce and does not exist for Colorado (all references in Table B.2). We preferred using the population characteristics and parameter estimates gathered in the current research effort, because this is the puma population we intend to manipulate to assess current CDOW puma management strategies. Table B.1. Minimum puma population count on Uncompahgre Plateau study area, Colorado, November 2007 to March 2008 (RY4). The minimum count involves counting all radio- and GPS-collared pumas, all other marked pumas, and all presumably unmarked pumas detected on the study area during the period. Presumed unmarked pumas could be marked with ear-tags and tattoos. Their tracks and movements could be separated from movements of radio- and GPS-collared pumas. Or they exhibited evidence that could separate them from other local marked pumas from their tracks (i.e., distinguishable by sex, number of cubs and/or relative size of cubs varied). Region East slope West slope Totals Adults Subadults Female Male Female Male 10 4 3 4 6 4 2 0 16 8 5 4 Total Independent Pumas = 33a,b Female 4 1 5 Cubs Male 4 2 6 Unknown sex 7 2-3 20-21 Of the total, 23−24 (70−73%) independent pumas were marked and 9-10 (27−30%) were assumed to be unmarked. a 172 �Table B.2. Summary of preliminary puma population model parameter estimates obtained from the Uncompahgre Plateau Puma Project and from the literature on puma. Survival Sex and age stage Adult Female Estimate 0.87 Adult Male 0.91 Subadult Female 0.80 Subadult Male 0.60 Cub 0.50 0.90 Reference Estimated average annual survival rate (n = 2 years) for 11−13 adult females on Uncompahgre Plateau study area. Estimated average annual survival rate (n = 8 years) for adult males in a nonhunted New Mexico puma population (Logan and Sweanor 2001:127-128). Estimated annual survival rate (n = 2 years) for 5−9 adult males on Uncompahgre Plateau study area was 1.00. Estimated subadult female survival in New Mexico (0.88, n = 16; Logan and Sweanor 2001:122) adjusted downward for potential lower survival for pumas 12-24 months old on Uncompahgre Plateau (0.642, n = 14 females and 10 males combined, life stages not known or described in Anderson et al. 1992:53). Survival of 7 radio-collared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated subadult male survival in New Mexico (i.e., 0.56, n = 9; Logan and Sweanor 2001:122) adjusted upward for potential slightly higher survival for pumas of both sexes 12-24 months old (i.e., 0.642) on Uncompahgre Plateau (Anderson et al. 1992:53). Survival of 7 radiocollared pumas (5 males, 2 females) in the subadult stage in the current Uncompahgre Plateau puma study is 1.00. Estimated cub survival rate (n = 38 cubs combined sexes), on Uncompahgre Plateau study area. This survival rate is applied to the model starting with the expected number of cubs from birth in RY5. Estimated cub survival for cubs ≥7 months old, and is applied to RY4 cubs only, because the minimum count of pumas in RY4 was tallied when most cub mortality had already occurred. Survival of cubs ≥7 months old in the literature is about 0.95 (Logan and Sweanor 2001). Here, a more conservative 0.90 is used in this model. Reproduction Parameter Adult age Estimate 2+ years Litter size 2.81 Secondary sex ratio observed at nurseries 1:1 Proportion of adult females producing new litters each year 0.65 Parameter Subadult female Estimated Ratio 1.02 Subadult male 0.94 Reference Assume all females 2 years old and older are adults (Logan and Sweanor 2001: 93-94). Average litter size for 21 litters on the Uncompahgre Plateau study area = 2.810 ± 0.9808SD; litters were examined when the cubs were 26 to 42 days old. Secondary sex ratio was 33:26 for 21 litters examined at 29 to 42 days old on the Uncompahgre Plateau study area (not significantly different from 1:1, (X2 = 0.8305 < 3.841, α = 0.05, 1 d.f.). This result supported Logan and Sweanor 2001:69, n = 148). Proportion of adult females giving birth each year (n = 3 years for n = 12, 13, 12 females), Uncompahgre Plateau study area. Proportion for a non-hunted puma population in New Mexico was 0.50 (Logan and Sweanor 2001:98). Progeny + Immigrant Recruits/Emigration Ratio Reference No data for pumas in Colorado exists. Assume the ratio of female immigrants to emigrants = 1.02. This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). No data for pumas in Colorado exists. Assume the ratio of male immigrants to emigrants = 0.94, (i.e., male immigration is half of emigration). This ratio is consistent with estimates for a New Mexico puma population that functioned as a source (Sweanor et al. 2000). 173 �Puma Population Simulations We used this model to simulate puma population dynamics to examine a set of scenarios that pertain to current CDOW puma management assumptions and to the puma research and management direction on the Uncompahgre Plateau for the treatment period: 1) Puma population dynamics without hunting-caused mortality. 2) Puma harvest that would induce a stable (i.e., no growth) phase to identify a population tipping point induced by harvest mortality, expected to be 16% harvest of independent pumas. Various sex ratios of harvest composition were examined. 3) Puma harvest at the upper limit (i.e., 15% of 8-15% range, CDOW 2007) that CDOW assumes would result in a stable to increasing puma population. Various sex ratios of harvest composition were examined. 4) Puma harvest at the upper limit (i.e., 28% of >15-28% range, CDOW 2007) that CDOW assumes would result in a declining puma population. Various sex ratios of harvest composition were examined. 5) Puma harvest at a 20% harvest level intermediate to the 16% stable growth and 28% decline phase with varying female to male sex structure of the harvest. 6) Puma harvest at the historic harvest level of 26% and sex ratio of 45 females:55 males on the study area during 1994-2003. Results of Puma Population Simulations The following tables contain the expected minimum population sizes for independent pumas and annual rates of population increase conditional upon the minimum number of independent pumas detected in Reference Year 4 (RY4) and the model input parameters and assumptions (given in Tables B.1 and B.2). The total number of independent pumas is probably higher in any particular scenario because we probably did not detect all of the independent pumas in RY4. Simulations involving harvest apply the harvest following reference year 5 (RY5) and starting with treatment year 1 (TY1) to assess what might be expected to occur within the current research structure on the Uncompahgre Plateau. Our puma population simulation modeling suggest strategies to achieve increasing and declining puma populations contingent upon the set of assumptions and input demographic data. Moreover, results of this modeling effort constitute the first time that CDOW puma harvest assumptions have been evaluated by using Colorado-specific population data. Results could change as more quantitative population data are gathered and the puma population is manipulated during this research. Expected estimates of population growth were generally consistent with the current CDOW puma harvest management assumptions that were previously developed from data in the puma population literature to manage for a stable-to-increasing population, and for a declining puma population. The following series of tables (B.3 – B.16) indicate results of the individual models, followed by notes on how results may be interpreted relative to other research results on puma population dynamics and specific CDOW puma management assumptions. The harvest levels for each model are clearly stated in the left column of each table. 174 �Table B.3. Harvest Level 16% of independent pumas, sexes are harvested equally; i.e., stable phase model. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 19 12 7 6 19 12 8 7 19 13 7 7 19 13 7 7 19 14 7 7 Independent Pumas Cub 20 33 35 34 34 34 34 Total 33 45 44 45 46 46 46 Lambda* 1.37 0.98 1.02 1.01 1.01 1.00 Note: The tipping point of population stability and decline is expected to be about 16% harvest of independent male and female pumas, consistent with current CDOW puma harvest assumptions. *Lambda is the finite rate of population growth (Williams et al. 2002:136): λ = 1 + (N t+1 – N t) / N t Figure B.1. Expected minimum number of independent pumas based on population simulations with 16% harvest of independent pumas comprised of 50% males and 50% females in the harvest in TY1 to TY5. Table B.4. Harvest Level 16% of independent pumas, harvest comprised of 40% females:60% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 20 11 7 6 21 10 9 7 23 10 9 7 24 10 9 7 25 10 10 8 Note: The puma population is expected to increase. 175 Independent Pumas Cub 20 33 37 39 41 44 46 Total 33 45 44 46 48 51 53 Lambda 1.37 0.98 1.05 1.04 1.05 1.05 �Table B.5. Harvest Level 16% of independent pumas, harvest comprised of 45% females:55% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 20 11 7 6 20 11 8 7 21 11 8 7 21 12 8 7 22 12 9 7 Independent Pumas Cub 20 33 36 37 38 39 40 Total 33 45 45 46 47 49 50 Lambda 1.37 0.98 1.04 1.03 1.03 1.03 Note: The puma population is expected to increase. Table B.6. Harvest Level 16% of independent pumas, harvest comprised of 55% females:45% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 18 12 7 7 17 13 7 7 17 14 6 6 16 14 6 6 15 15 6 6 Independent Pumas Cub 20 33 34 31 30 29 27 Total 33 45 44 44 43 42 41 Lambda 1.37 0.97 1.00 0.98 0.98 0.97 Note: The puma population is expected to decline slowly. Figure B.2. Expected minimum number of independent pumas based on population simulations with 16% harvest of independent pumas comprised of varying female to male sex ratios in the harvest in TY1 to TY5. See tables B.3-6 (above) for quantities of results for each model. In reality, the ratio of females to males in the harvest may vary randomly on an annual basis, and the expected annual numbers of independent pumas may fall within the lower and upper population trend lines. 176 �Table B.7. Harvest Level No harvest. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 27 17 11 10 32 22 12 11 38 27 15 14 44 32 17 16 Independent Pumas Cub 20 33 42 49 58 69 81 Total 33 45 53 64 77 92 110 Lambda 1.37 1.17 1.22 1.20 1.20 1.19 Note: Expected lambda for the modeled non-hunted puma population on the Uncompahgre Plateau are consistent with the high range of observed average annual rates of population increase for a non-hunted puma population in good quality habitat in southern New Mexico (i.e., r = 0.21, n = 4 yr.; r = 0.28, n = 4 yr.; r = 0.17, n = 4 yr.; r = 0.11, n = 7 yr.; Logan and Sweanor 2001:169-175). Puma population growth could be higher on the Uncompahgre Plateau because of higher quality habitat (i.e., greater vulnerable prey biomass), and if puma sources are nearby to the study area. Table B.8. Harvest Level 15% of independent pumas, sexes are harvested equally. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 19 12 7 7 19 12 8 7 19 13 8 7 20 14 8 7 20 14 8 7 Independent Pumas Cub 20 33 36 35 36 36 36 Total 33 45 45 47 47 48 49 Lambda 1.37 0.99 1.04 1.02 1.02 1.01 Note: This result is consistent with current the CDOW puma harvest assumption for a stable-to-increasing population, with slow growth attributed to equal harvest of females and males. Table B.9. Harvest Level 15% of independent pumas, comprised of 40% females & 60% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 21 11 8 6 22 10 9 7 23 10 9 7 25 11 10 8 26 11 10 8 Independent Pumas Cub 20 33 38 39 42 45 48 Total 33 45 45 47 50 53 56 Lambda 1.37 0.99 1.06 1.05 1.06 1.06 Note: This result is consistent with the current CDOW puma harvest assumption for a stable-to-increasing population, with increased growth due to reduced female mortality. 177 �Table B.10. Puma population simulation results, based on the minimum number of detected independent pumas in RY4, and harvest rate of 20% of independent pumas comprised of 50% females and 50% males applied to independent pumas as a treatment during TY1-TY5. Harvest Level 20% of independent pumas, comprised of 50% females & 50% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 18 11 7 6 17 11 7 6 16 11 6 6 15 11 6 6 15 11 6 5 Independent Pumas Cub 20 33 34 31 30 28 27 Total 33 45 42 41 40 38 36 Lambda* 1.37 0.93 0.97 0.96 0.96 0.96 Note: The puma population would be expected to decline. Table B.11. Puma population simulation results, based on the minimum number of detected independent pumas in RY4, and harvest rate of 20% of independent pumas comprised of 40% females and 60% males applied to independent pumas as a treatment during TY1-TY5. Harvest Level 20% of independent pumas, comprised of 40% females & 60% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 20 10 7 5 20 8 8 6 21 8 8 6 21 8 8 6 22 7 9 6 Independent Pumas Cub 20 33 36 37 38 39 40 Total 33 45 42 42 43 43 44 Lambda 1.37 0.93 1.01 1.00 1.01 1.02 Note: The puma population would be expected to increase slowly. Table B.12. Puma population simulation results, based on the minimum number of detected independent pumas in RY4, and harvest rate of 20% of independent pumas comprised of 45% females and 55% males applied to independent pumas as a treatment during TY1-TY5. Harvest Level 20% of independent pumas, comprised of 45% females & 55% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 19 10 7 6 19 10 7 6 19 10 7 6 18 9 7 6 18 9 7 6 Independent Pumas Cub 20 33 35 34 34 34 33 Total 33 45 42 42 41 41 40 Lambda 1.37 0.94 0.99 0.98 0.99 0.99 Note: The puma population would be expected to decline slowly. The ratio of 45% females and 55% males in the harvest is the average harvest sex ratio during 1994-2003. 178 �Table B.13. Puma population simulation results, based on the minimum number of detected independent pumas in RY4, and harvest rate of 20% of independent pumas comprised of 55% females and 45% males applied to independent pumas as a treatment during TY1-TY5. Harvest Level 20% of independent pumas, comprised of 55% females & 45% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 17 12 6 6 15 12 6 6 14 12 5 5 12 12 5 5 11 12 4 4 Independent Pumas Cub 20 33 32 28 25 22 20 Total 33 45 42 40 37 34 31 Lambda 1.37 0.94 0.99 0.98 0.99 0.99 Note: The puma population would be expected to decline more rapidly. Figure B.3. A harvest level of 20% of independent pumas is expected to result in a declining population, except in the scenario consistently weighted heavily toward male harvest (i.e., 60%). Table B.14. Harvest Level 28% of independent pumas, sexes are harvested equally. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 17 10 6 6 14 9 6 5 12 8 5 4 10 7 4 4 9 6 3 3 Independent Pumas Cub 20 33 30 25 22 18 16 Total 33 45 38 33 29 25 21 Lambda 1.37 0.84 0.88 0.86 0.86 0.86 Note: This result is consistent with the current CDOW puma harvest assumption for a declining population. 179 �Table B.15. Harvest Level 28% of independent pumas, comprised of 40% females & 60% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 19 8 7 4 18 6 7 5 17 5 7 4 16 4 6 4 16 4 6 4 Independent Pumas Cub 20 33 34 32 31 30 29 Total 33 45 38 35 33 31 30 Lambda 1.37 0.84 0.93 0.93 0.95 0.95 Note: This result is consistent with the current CDOW puma harvest assumption for a declining population even with harvest weighted toward males. Yet another harvest scenario to consider for the treatment period is application of the historic puma harvest on the study area. Puma mortality data for the study area during the 10 years previous 19942003 prior to the beginning of the study reference period was tabulated after carefully geo-referencing mortality locations on the study area (Logan 2008). Model parameters from those data include: mortality rate of 14.3 independent puma mortalities per year (rounded to 14/yr.), and sex proportions of 55% males and 45% females. No other puma population data or parameter estimates were available for the study area at that time. Therefore, the scenario that was modeled pertained to the expected impact of the average annual puma mortality of independent pumas (i.e., adults and subadults) if the hypothetical population was the same as the minimum expected puma population after year 5 of the reference period (i.e., RY5). A harvest of 14 pumas/yr. is a 26% harvest rate of the expected minimum independent puma population at the start of TY1. Table B.16. Harvest Level 26% of independent pumas at start of TY1, comprised of 45% females & 55% males. Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 18 9 7 5 17 8 7 5 15 7 6 5 14 6 6 5 13 6 5 4 Independent Pumas Cub 20 33 33 30 28 26 25 Total 33 45 39 36 34 31 29 Lambda 1.27 0.87 0.93 0.92 0.93 0.93 Note: As expected, results of this model indicate puma population decline. This simulation demonstrates the negative cost of uncertainty in puma management; in this case a puma population would decline where the intended management objective was for a stable-to-increasing population. 180 �Figure B.4. Expected dynamics of a puma population with the historical harvest (1994-2003) rate on the Uncompahgre Plateau study area of 26% of the independent puma and sex ratio of 45% females to 55% males (see Logan 2008 for historical harvest data on the study area). 181 �APPENDIX C Collaborative project on disease surveillance in wild felids with College of Veterinary Medicine and Biomedical Sciences, Department of Microbiology, Pathology, and Immunology, Colorado State University. College of Veterinary Medicine and Biomedical Sciences Department of Microbiology, Immunology & Pathology 1619 Campus Delivery Fort Collins, CO 80523-1619 970-491-6144 (voice) 970-491-0603 (fax) TO: Ken Logan, Mammals Researcher, Colorado Division of Wildlife, Montrose, CO. FROM: Sue VandeWoude, DVM, Associate Professor, DMIP RE: Disease Seroprevalence in UP Pumas DATE: August 26, 2007 These specific agents were selected for analysis in order to provide a variety of types of agents (viruses: PLV, FCV, FHV, FPV; bacteria: Bartonella henselae and Yersinia pestis; and coccidian: T. gondii), a variety of modes of transmission (direct intra-specific contact, PLV; direct contact with domestic cats, FCV, FHV, FPV; arthropod transmission, B. henselae, Y. pestis; prey ingestion, T. gondii, Y. pestis). Further, at least three of these agents (PLV, FCV, B. henselae) result in chronic infections, allowing the possibility of determining genetic relatedness among organisms isolated from different individuals, and three of these agents (B. henselae, Y. pestis, T. gondii) are also potential zoonotic agents. As you are aware, our laboratory has recently been awarded a 5 year NSF Ecology of Infectious Disease grant entitled, “The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids”, with co-PI Dr. Kevin Crooks, an associate professor in the Warner College of Natural Resources at CSU. The aims of this grant are to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in large carnivore species as described on the following page. The letter of support provided by you and Mr. Dave Freddy were pivotal in demonstrating a large cohort of capable and active field collaborators willing to provide samples to support our studies. The mountain lion field work being led by your team, and the newly initiated studies by your colleague, Dr. Mat Alldredge, have provided us with renewed enthusiasm for developing our collaborations to support the goals of our study. We foresee the opportunity to interact in a mutually beneficial partnership to further the goals of all of our studies, and to maximize the information that can be gleaned about these important and ecologically significant species. We anticipate that the data we are generating will be useful for comparative seroprevalence of different geographic populations of bobcats and pumas, and for genetic phenotyping of pathogens to compare relationships among diseases spread by arthropod vectors, domestic cats, feral rodents, and interspecific contacts. As we discussed during your recent visit to CSU, these samples are most valuable to us if we can receive them directly as quickly as possible after collection. I have provided an SOP providing information about the types of samples that will be most valuable, and a draft of a ‘permissions’ document that you can use with each sample submission to provide us with guidance for any testing that is permissible on the materials we receive. This latter document will be filed and recorded electronically. We will continue to provide annual updates and communications about any publications that utilize the data resulting from your samples. Again thank you for providing these extremely valuable samples, and we look forward to our continued collaborations. Sincerely, Sue VandeWoude 182 �The effects of urban fragmentation and landscape connectivity on disease prevalence and transmission in North American felids Project Summary Sue VandeWoude (co-PI), Kevin Crooks (co-PI), Michael Lappin, Mo Salman, Walter Boyce, Ken Logan, Mat Alldredge, Carolyn Krumm, Don Hunter, Lisa Lyren, Seth Riley, Jennifer Troyer The objective of this study is to model the effects of urbanization and resultant habitat fragmentation on disease dynamics in carnivore species. Bobcats, puma, and domestic cats will be evaluated simultaneously in three divergent ecosystems: high mountain desert (Colorado), everglades (Florida), and Mediterranean scrub habitat (California). The research will: 1) assess the relationship between habitat fragmentation and prevalence of viral, bacterial, and parasitic pathogens across a gradient of urbanization, 2) use transmission dynamics of selected disease agents as markers of connectivity of fragmented populations, and 3) evaluate the effect of urbanization on the incidence of cross-species disease transmission. The results of this research will give wildlife managers a better understanding of how urbanization affects their local wildlife and assist them in future disease management planning. The combination of a uniquely qualified, broadly based research team with an extensive dataset on carnivores from across the country presents an unprecedented opportunity to investigate the disease dynamics in these rare and difficult to study species. The research efforts of each regional team will support and provide new insights for all of the regions involved, not simply their own. Training of graduate students in ecology, infectious disease, and epidemiology will be emphasized, as will training for pre- and post-doctoral veterinarians. Results will be made widely available to other scientists, conservation practitioners, and the general public. This research has a tremendous capacity to broadly impact areas of public and postgraduate education, career development for new investigators and persons from underrepresented groups, and to enhance understanding of complex infectious disease ecological problems using extensive multidisciplinary collaborations. 183 �Appendix C (continued). Preliminary results of infectious disease surveillance for puma, Uncompahgre Plateau, Colorado, 2005-2009. Puma ID UPCO2 UPCO3 UPCO7 UPCO7 UPCO7 UPCO8 UPCO4 UPCO5 UPCO6 UPCO6 UPCO23 UPCO25 UPCO28 UPCO29 UPCO31 UPCO23 UPCO27 UPCO30 UPCO50 UPCO51 UPCO52 UPCO54 UPCO55 UPCO24 UPCO69 UPCO70 UPCO71 UPCO72 UPCO73 UPCO74 UPCO75 UPCO72 Sex F F F F F F M M M M F F F M M F M F F M F F M F M F M F F F F F Capture Date 1/8/2008 1/21/2005 2/24/2005 3/30/2006 3/3/2007 3/21/2005 1/28/2005 2/4/2005 2/18/2005 4/12/2008 2/25/2008 2/8/2006 3/23/2006 4/14/2006 4/19/2006 1/4/2006 3/10/2006 4/15/2006 12/14/2006 1/7/2007 1/10/2007 1/12/2007 1/21/2007 1/17/2006 1/11/2008 1/20/2008 1/29/2008 2/12/2008 2/21/2008 3/12/2008 3/26/2008 7/20/2009 UPCO104 UPCO55 UPCOF16 UPCO66 UPCO94 UPCO96 UPCO100 UPCO82 UPCO93 UPCO71 UPCO72 UPCO73 UPCO74 F M F F F F M M F M F F F 5/21/2009 1/5/2009 1/14/2009 11/25/2008 12/19/2008 1/28/2009 3/27/2009 2/10/2009 12/15/2008 1/29/2008 2/12/2008 2/21/2008 3/12/2008 GPS NAD27 U.T.M.: Zone, E, N 13S, 245722, 4244166 13S, 241606, 4251510 13S, 246328, 4244230 13S, 245901, 4247627 13S, 247645, 4246097 12S, 727808, 4239029 13S, 257565, 4239606 13S, 240577, 4251037 13S, 247399, 4254006 13S, 257516, 4239696 12S, 723304, 4242231 13S, 258374, 4230480 12S, 722868, 4240115 12S, 723458, 4242340 12S, 746919, 4225441 12S, 730188, 4234861 12S, 722339, 4245212 13S, 248551, 4242095 12S, 753639, 4260149 13S, 238783, 4252390 13S, 258058, 4236260 13S, 252688, 4228050 13S, 258133, 4228691 12S, 737151, 4233273 13S, 248191, 4246810 13S, 247122, 4245760 12S, 754611, 4256842 13S, 258294, 4234597 12S, 728576, 4241799 12S, 729678, 4239555 12S, 732894, 4239423 13S, 255400, 4229658 12S, 745118, 4264721N 13S, 239076, 4248637 13S, 256528, 4235500 13S, 245901, 4247627 12S, 758531, 4259824 13S, 247764, 4246239 12S, 749832, 4217148 12S, 726732, 4243782 12S, 751445, 4265985 12S, 754611, 4256842 13S, 258294, 4234597 12S, 728576, 4241799 12S, 729678, 4239555 PLV + + + + I + + + + + + + + + + + + + + P P P P + P + P P P + P a a b FCV +h + + + + + + No swab - c FHV + + + + + + + No swab - FPV + + + NA NA + + + + + + + + NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA d T.g.e IgM + P - T.g.e IgG + + + + + + + + + + + + + + + + + + + + + + + + P + + B.h.f + + Y.p.g + ++ +++ ++ ++ ++ + + ++ + + + NA P + + + + + + + + + + + P + - NA NA NA NA NA NA NA NA NA + - PLV is Puma Lentivirus. FCV is Feline Calicivirus. c FHV is Feline Herpesvirus. d FPV is Feline Panleukopenia Virus e T. g. is Toxoplasma gondii. f B. h. is Bartonella hensalae. g Y. p. is Yersinia pestis. h Results: + (positive result), P (Pending result), I (Inconclusive result), NA (not applicable). b 184 �Colorado Division of Wildlife July 2008 - June 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 3003 2 : : : : : Division of Wildlife Mammals Research Predatory Mammals Conservation Cougar Demographics and Human Interactions Along the Urban-Exurban Front-range of Colorado N/A___________________ Period Covered: July 1, 2008 - June 30, 2009 Author: M.W. Alldredge Personnel: E. Joyce, T. Eyk, K. Blecha, L. Nold, K. Griffin, D. Kilpatrick, M. Paulek, B. Karabensh, M. Miller, F. Quartarone, M. Sirochman, L. Wolfe, J. Duetsch, C. Solohub, J Koehler, L. Rogstad, R. Dewalt, J. Murphy, D. Swanson, T. Schmidt, T. Howard, D. Freddy CDOW; B. Posthumus, Jeffco Open Space; D. Hoerath, K. Grady, D. Morris, Boulder County Open Space; S. OylerMcCance, USGS. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We continued analyzing cougar fecal samples collected from the 3 sibling cougars in captivity at the Foothills Wildlife Research Facility. Feces were stored at controlled temperatures after deposition and sub-sampled at monthly intervals. Genetic material has been found in samples up to 6 months postdeposition, but genotyping error rates have not yet been assessed. We are investigating degredation rates further by sampling feces in natural, uncontrolled, environments deposited at known times from known individuals. Sampling cougar feces in the field may be a feasible non-invasive sampling method to estimate cougar populations. The use of telomeres as a method to determine the age structure of bear and cougar populations has been examined and will be investigated further in the coming year. Further refinement of the age-tolength relationship for both species is warranted based on preliminary results. In addition to this, length relationships relative to genetic relatedness and individual stressors will give further insight into interpreting results from future data. This year capture efforts focused on re-collaring previously collared cougars, and capturing previously unmarked independent age cougars and cubs. We collared an additional 10 independent age cougars and also put VHF eartag transmitters on 8 cubs during the year. Mortality remained high over the year exceeding 40% for independent age cougars (predominantly human related) and exceeding 50% for cubs (predominantly starvation). Home-range patterns remained consistent to previous years. The effectiveness of aversive conditioning is still showing mixed results, which is likely a factor of the opportunistic nature of cougars using urban environments and a lack of habituation to them. Relocation of cougars as a management tool has had limited assessment, but given some success, still warrants 185 �further investigation. Mule deer are the predominant prey in cougar diets, although males will also utilize elk regularly. WILDLIFE RESEARCH REPORT COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBANEXURBAN FRONT-RANGE OF COLORADO MATHEW W. ALLDREDGE P.N. OBJECTIVE 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban front-range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus) and estimating population densities of cougars for the state of Colorado. SEGMENT OBJECTIVES Section A: Genetics 1. Evaluate differences in DNA quantity from either a scat surface collection or a cross-sectional collection. 2. Evaluate differences in DNA quantity from successive feces depositions to determine the variation in quantities of genetic material in scats. Quantify differences in epithelial shedding rates. 3. Evaluate temporal, environmental, and seasonal effects on fecal DNA quantity and quality for both controlled and uncontrolled conditions. Section B: Telomeres 4. Evaluate the potential to develop a model for estimating age of bears and cougars based on telomere length. Section C: Front-range cougars 5. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. 6. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets. 7. Continue to assess relocation of cougars as a practical management tool. 8. Assess cougar predation rates and diet composition based on GPS cluster data. SECTION A: GENETICS INTRODUCTION Genetic techniques for monitoring or research of rare, elusive, and wide ranging species are of particular interest as other techniques are either impractical or financially prohibitive. Genetic techniques for monitoring and research of cougars in Colorado may be invaluable as alternative techniques are expensive and in many situations may not be possible. Capture and handling of cougars is expensive, time consuming, and may not give representative samples of the population. Large dispersal distances of cougars, especially males, will require impractically large study areas in order to understand demographic patterns that are affected by immigration. Capture may not even be possible in suburban and exurban 186 �areas of Colorado as logistical constraints associated with private land owners will likely prohibit the use of many capture techniques. Noninvasive genetic sampling (Hoss et al. 1992, Taberlet and Bouvet 1992) has the potential to provide a realistic method of sampling a population of interest. Noninvasive sampling techniques include the use of hair snares, and scat collections (Harrison et al. 2004, Smith et al. 2005). The use of scats for sampling cougar populations may be particularly useful and provide a representative sample of the population. Scat collections can either be done by searching transects with human observers (Harrison et al. 2004) or with trained dogs (Smith et al. 2005). Scats could also be collected from kill sites. Kill sites would need to be based on mortalities of radio-collared ungulate populations. Data from noninvasive sampling techniques are useful in describing dispersal patterns and estimating population size. Noninvasive genetic data are error prone, which in many cases is due to the quantity and quality of genetic material relative to the collection of noninvasive samples. Therefore, one objective over the last year has been to develop a study to evaluate degradation rates of DNA in fecal samples with respect to time and temperature. STUDY AREA The genetic degradation study is being conducted at the Foothills Wildlife Research Facility, located in Fort Collins, Colorado. This is the facility where 3 sibling cougars have been raised in captivity and are part of other ongoing research efforts. METHODS Fecal samples were collected from the 3 sibling cougars located at the Foothills Wildlife Research Facility. During the year the entire remaining sample of 60 feces per cougar were collected and samples were placed at random into one of three treatment groups (-5 C, +5 C, and +15 C). Genetic samples were collected from these at the time of initial collection and at 2 weeks, and 1, 2, 3, 4, and 6 months post deposition. DNA was extracted and then stored at -20 C Response variables that are being measured are number of incorrect identifications, allelic dropout rates (actual number of alleles that dropout in any given sample), and number of false alleles. The primary analysis is a logistic regression on the dichotomous identification variable, treating the three temperature regimes as covariates. Additional analyses summarize the rate at which alleles dropout and the occurrence of false alleles. A total of 60 scats have been collected and sub-sampled at each time period within treatment groups. PCR and DNA sequencing is being done at the Rocky Mountain Center for Conservation Genetics and Systematics laboratory. Individual cougars are screened and genotyped using 9 -12 nuclear microsatellite loci isolated from domestic cat (Menotti-Raymond and O’Brien 1995, Menotti-Raymond et al. 1999). Three recent studies have used sets of these primers successfully on mountain lions (Ernest et al. 2000, Sinclair et al. 2001, Anderson et al. 2004). We will choose a set of these primers for our work. PCRs will be performed using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). Each 12.5μl reaction will contain 125μM each dNTP, 1X Taq buffer (Kahn et al. 1998), 0.034μM M13tailed forward primer, 0.5μM non-tailed reverse primer, 0.5μM M13 dye-labeled primer with Beckman Coulter dyes D2, D3 or D4 (Proligo), and 0.31U Taq polymerase (Promega). The thermal profile for both the forward dye-labeled and the M13 dye-labeled reactions will be as follows with the appropriate annealing temperature varying by locus: preheat at 94°C for 1 min, denature at 94 ºC for 1 min, anneal for 1 min, and extend at 72 ºC for 1 min for 35 cycles. The PCR products will be diluted and run on the CEQ8000 XL DNA Analysis System (Beckman Coulter). All loci will be run with the S400 size standard (Beckman Coulter) and analyzed using the Frag 3 default method. 187 �RESULTS AND DISCUSSION Most of the remaining samples were collected this year and the majority of the samples were genotyped. Approximately 200 samples remain to be genotyped as collections at the greater time intervals will continue into November 2009. This work is still ongoing so an assessment of genotyping error rates cannot be made. However, sufficient genetic material for genotyping has been found in samples up to 6 months old. Genetic degradation appears to occur at a slower rate than initially expected. This would indicate that scat surveys for individual identification of cougars may be a viable non-invasive sampling technique. SECTION B: TELOMERES BY M. ALLDREDGE AND J. PAULI INTRODUCTION Understanding the age structure of a population is very useful to managers, especially for hunted populations. Age structure can provide indications about the appropriateness of current harvest levels, changes that may need to occur in harvest, and the general health of a population. Typical approaches involve estimating age structure based on sampling harvested animals and obtaining ages based on tooth wear and replacement characteristics or from analyzing tooth annuli. Recently a new approach has been developed for some species that estimates the age of animals based on examining the length of telomeres in relation to the age of the animals. Telomeres are repetitive DNA sequences that cap the ends of eukaryotic chromosomes, whose nucleotide sequence (T2AG3)n is highly conserved across vertebrate species (Meyne et al. 1989). During each cell cycle telomeric repeats are lost because DNA polymerase is unable to completely replicate the 3’ end of linear DNA (Watson 1972). Thus, telomeres progressively shorten with each cell division; past research has demonstrated age-related telomere attrition in a variety of laboratory and wild species and has correlated telomere length with individual age (e.g. Hausmann et al. 2003, Hemann and Greider 2000). Using real-time quantitative polymerase chain reaction (Q-PCR; Cawthon 2002), we quantified telomere length for cougars and black bears of known-age in Colorado and Wyoming. STUDY AREA Genetic samples for black bears were obtained from blood collections taken from bears captured in Wyoming. Genetic samples for cougars were obtained from either blood or tissue samples taken from cougars in Colorado as part of either the Uncompahgre Plateau or Front-Range cougar studies. METHODS We quantified telomere length in cougar and bear tissue samples using a real-time quantitative polymerase chain reaction (Q-PCR) technique (Cawthon 2002). This method measures relative telomere lengths by determining the factor by which a sample DNA differs from an arbitrary reference DNA in its ratio of telomere repeat copy number (T) to single copy gene number (S). The T/S ratio of one individual relative to the T/S for another reflects relative differences in telomere length between individuals. This approach is highly accurate (Cawthon 2002), particularly for differentiating relative telomere length among individuals within a species (Nakagawa et al. 2004). In theory, any single copy gene sequence can be employed for standardization; we chose to use the single copy gene, 36B4, which was originally employed to develop this method for quantifying telomere length in humans (Cawthon 2002). Using genome data for eight species (carnivores, primates, birds, amphibians, ungulates, and rodents; accessible at http://www.ncbi.hlm.nih.gov/) and the computer program, ClustalX (version 1.81), we conducted a 188 �sequence alignment and have determined that the 36B4 gene is highly conserved across vertebrate taxa and appears to be a suitable internal standard for a wide range of species, including the cougars and black bears. We ran telomere PCR and single-copy gene PCR on different 96-well plates; preparation of telomere and single-copy plates was identical except for the primers. We diluted extracted DNA with distilled water to 3 ng∙μl-1. For each animal, we added 10 μl of diluted DNA to 2 adjacent wells. To generate a standard curve, we diluted DNA from an arbitrarily chosen animal to 1 ng∙μl-1, 2.5 ng∙μl-1, 4 ng∙μl-1 and 6 ng∙μl-1 and added 10 μl of each concentration to 3 adjacent wells. Between rows of samples, distilled water without template DNA was added to 2-4 wells as negative controls. Plates were sealed with a rubber cover, centrifuged briefly and heated in a thermocycler at 96 ˚ C for 10 minutes. After cooling the plate for 10 minutes, we added the final PCR reagents. For the telomere PCR, the reagents included 2.25 μl distilled water and 12.5 μl SYBR Green PCR Master Mix (Applied Biosystems). For the single-copy PCR, reagents included 2.3 μl distilled water, 12.5 μl SYBR Green PCR Master Mix. The final primer concentrations were tel 1b, 100 nM; tel 2b, 900 nM; 36B4u, 300 nM and 36B4d, 500 nM. Primer sequences were: tel 1b, 5’ CGG TTT GTT TGG GTT TGG GTT TGG GTT TGG GTT TGG GTT 3’; tel 2b, 5’ GGC TTG CCT TAC CCT TAC CCT TAC CCT TAC CCT TAC CCT 3’; (Cawthon pers. comm.; Callicott and Womack 2006) 36B4d, 5’ CCC ATT CTA TCA TCA ACG GGT ACA A 3’; and 36B4u, 5’ CAG CAA GTG GGA AGG TGT AAT CC 3’ (Cawthon 2002). After sealing the plate with a transparent adhesive cover, we briefly vortexed and centrifuged it. We used an automated thermocycler (7500 Real-Time PCR System, Applied Biosystems) to perform QPCR. For telomeres, the reaction profile began with a 94˚ C incubation for 1 minute, followed by 40 repetitions of 1 second of denaturing at 96˚ C then 1 minute of annealing-extending at 54˚ C. For the single-copy PCR, the incubation lasted 10 minutes at 95˚ C, followed by 35 repetitions of 95˚ C for 15 seconds and 58˚ C for 1 minute. Using Applied Biosystems (ABI; Applied Biosystems Foster City, CA) software, we generated a standard curve to estimate the amount of T and S for each sample. From these values we calculated the T/S ratio for each individual. RESULTS AND DISCUSSION Amplification efficiencies were high for both the single copy gene and telomere in bear and cougar samples. Standard curves obtained for both species enabled a robust estimate of relative telomere length (Figure 1). For both species, relative telomere length declined with increasing animal age (Figure 2). Because samples analyzed were obtained from blood, hair and muscle tissue, and since telomere length varies across tissue-types, preliminary regression analyses were limited to blood samples only. Although there is considerable variation in telomere lengths for age, an interesting and potentially relevant relationship between animal age and relative telomere length exists. For both species, additional samples of a particular tissue-type (e.g., blood) may help clarify the relationship between age and telomere length. Additionally, obtaining reliable age estimates and assigning individuals to biologically relevant age classes could greatly improve the analysis. For this report, we used the median estimated age from the range of potential ages that were provided. Clearly, biologically meaningful age categories would strengthen this analysis. Research on marten has shown telomeric attrition was correlated with parasite load, and body condition (Pauli et al. in prep). Such additional individual-level information may be important covariates for these species as well. With additional samples and more information we may be able to better interpret the T/S results for both black bears and cougars. 189 �SECTION C: FRONT-RANGE COUGARS INTRODUCTION At the local scale, efforts have been made to continue the cougar/human interaction study on the Front-Range of Colorado. Given that cougars currently coexist with humans within urban/exurban areas along Colorado’s Front-Range, varying levels of cougar-human interaction are inevitable. The CDOW is charged with the management of cougars, with management options ranging from minimal cougar population management, to dealing only with direct cougar-human incidents, to attempted extermination of cougars along the human/cougar spatial interface. Neither inaction or extermination represents practical options nor would the majority of the human population agree with these strategies. In the 2005 survey of public opinions and perceptions of cougar issues, 96% of the respondents agreed that it was important to know cougars exist in Colorado, and 93% thought it was important that they exist for future generations (CDOW, unpublished data). There is a growing voice from the public that CDOW do more to mitigate potential conflicts, and the Director of CDOW has requested that research efforts be conducted to help minimize future human/cougar conflicts. In order to meet these goals CDOW believes it is necessary to directly test management prescriptions in terms of desired cougar population and individual levels of response. Long-term study objectives for the Front-Range Cougar Research project will involve directly testing management responses of cougars at various levels of human interaction, as well as collecting basic information about demographics, movement, habitat use, and prey selection. The Cougar Management Guidelines Working Group (CMGWG) (2005) recommend that part of determining the level of interaction or risk between cougars and humans is to evaluate cougar behavior on a spectrum from natural, to habituated, to overly familiar, to nuisance, to dangerous. The CMGWG (2005) clearly state that there is no scientific evidence to indicate that cougar habituation to humans affects the risk of attack. As a continuation from the pilot study efforts, we have continued to assess the effectiveness of aversive conditioning as a method to alter interaction rates between cougars and humans. We also continue to monitor relocated cougars to determine the effectiveness of relocation as a management tool. The use of GPS collars obtaining up to 8 locations per day also allows for a detailed examination of demographic rates. We are monitoring cougars that utilize natural habitats and cougars that use a mixture of natural and urban habitats. This allows for an assessment of demographic rates, movement patterns, and habitat use among cougars utilizing these two habitat configurations. We have also begun monitoring cubs (approximately 6 months of age or older), primarily to determine survival but potentially to understand movement patterns and dispersal. The use of GPS collars also allows us to study predator-prey relationships and diet composition. GPS locations are divided into selection sets based on the likelihood of the set of locations (clusters) representing a kill site. A random sample of these clusters are investigated to determine what a cougar was doing at the site, and whether or not it represents a kill site. Kill sites are thoroughly investigated to determine as much information as possible about what was killed at the site. 190 �STUDY AREA The original pilot study was conducted in Boulder and Jefferson counties, in an area near Interstate 70 north to approximately Lyons, Colorado, which was also a likely area for addressing longterm research objectives (see Figure 3). The study area for the long term study includes this original area but was expanded south to highway 285. Research efforts in the additional southern portion are generally limited to capturing cougars that are in the urban setting and/or have interacted directly with humans. The study area is comprised of many land ownerships, including private, Boulder city, Boulder County, Jefferson County, and state and federally owned lands. Therefore, we have been directly involved with Boulder city and Boulder and Jefferson county governments to obtain agreements from these entities on conduct of research and protocols for dealing with potential human/cougar interactions prior to conducting any research efforts. We have also acquired permission to access numerous private properties to investigate cougar clusters and to trap cougars. METHODS Baiting, using deer and elk carcasses, has been conducted throughout the year, with a focus on areas that do not allow the use of hounds. Bait sites are monitored using digital trail cameras to determine bait site activity. Cage traps were generally used for capture when cougars removed the bait and cached it. Beginning in November, 2008 and continuing through April, 2009, hounds were also used several times per week to capture cougars. Snares were used in situations where hounds could not be used and cougars would not enter cage traps. Captured cougars were anesthetized, monitored for vital signs, aged, measured, and ear-tagged. All independent cougars (> 18 months old) were fitted with GPS collars. All cubs greater than 15 kg (approximately 6 months or older) were ear-tagged with 22 g ear-tag transmitters. For detailed capture and handling procedures see the study plan APPENDIX I. When cougars interact with humans and elicit a response from CDOW District Wildlife Managers (DWMs) they are potential candidates for aversive conditioning. However, only a subset of these will actually be conditioned and the remaining animals will not be treated in order to have a control group. At this time, we consider aversive conditioning treatments on cougars to potentially be: multiple captures and handling of cougars, single or multiple treatments using beanbags fired from a shotgun, single or multiple chases using hounds, and potential combinations of capture, hound chases, and beanbags. Initially, we want to assess situations and methods that are already being implemented by wildlife managers. The most likely scenario are incidents occurring in neighborhoods, where relocating the cougar is necessary prior to any application of an aversive conditioning treatment. For these situations, all treatments will require the relocation of the offending individual to an adjacent open-space property or similar area. Following relocation we will either chase the cougar off using rubber bullets or beanbag rounds, pepper spray, or hounds. For first time offenders we will initially try rubber bullets or beanbag rounds. Second time offenders will be chased with hounds. If rubber bullets or beanbag rounds are not affecting cougar behavior, we will begin using pepper spray on first time offenders. The other scenario that will occur are incidents in areas where a cougar can be directly conditioned or chased from the area. We will mimic the above approach as much as possible, and use rubber bullets or beanbag rounds on first time offenders. If possible we will chase individuals with hounds on their second offense, although this may not always be practical. Pepper spray may not be practical either in many situations. As a second level treatment where direct hound chases are not practical, we will attempt to capture, relocate, and aversive condition the individual. 191 �Cougars will only be relocated for management purposes, generally in conjunction with human conflict or livestock depredation. Research cougars that have been collared for other purposes of the study may also become part of the relocation group if their levels of human interaction warrant such a management action. In May, 2008, two research cougars were relocated approximately 30km after they returned to the city of Boulder following a short distance relocation. Because only a few cougars are relocated each year, we will collar and monitor all cougars that are relocated in the northeast region. Cougars will be ear-tagged and fitted with a telemetry collar (VHF, or GPS collars may be used depending on the situation). Release area is critical to the success of any relocation, however, suitable relocation areas may be difficult to find. Such an area must be far enough from the problem area, have suitable prey, and be remote enough so that the individual will not be presented with problem opportunities at or near the release site. Understanding the minimum release distance that has a reasonable chance for relocation success is useful for both logistical reasons and to increase the number of potential release sites. We evaluated cougar diet composition by using GPS location data to identify likely kill sites. Characteristics of clusters of GPS locations representing cougar-killed ungulate sites (Anderson and Lindzey 2003, Logan 2005) were used to develop a standard algorithm to group GPS points together, to provide a sound sampling frame from which statistical inference could be made about clusters that are not physically investigated. GPS collars collected locations 8 times/day to reflect time periods when cougars are both active and inactive. The clustering routine was designed to identify clusters in five unique selection sets (S1, S2,…, S5) in order to identify clusters containing two or more points, those that contained missing GPS locations, and those that were represented by single points. The clustering algorithm was written in Visual Basic and was designed to run within ARCGIS (Alldredge and Schuette, CDOW unpubl. data 2006). The widths of the spatial and temporal sampling windows were user specified, in order to meet multiple applications and research needs. This also enabled adjustment of the sampling frames to improve cluster specifications as needed. We used the following protocol to investigate cougar GPS clusters in the field. For S1 clusters, we investigated each cougar GPS location in the cluster by spiraling out a minimum of 20 m from the GPS waypoint while using the GPS unit as a guide, and visually inspecting overlapping view fields in the area for prey remains. Normally, this was sufficient to detect prey remains and other cougar sign (e.g., tracks, beds, toilets) associated with cougar. If prey remains were not detected within 20 m radius of the cluster waypoints, then we expanded our searches to a minimum of 50 m radius around each waypoint. For S2 through S5 clusters, we went to each cougar GPS location and spiraled out 50 m around each waypoint, while using the GPS unit as a guide. Depending on the number of locations, topography, and vegetation type and density, we spent a minimum of 1 hour and up to 3 hours per cluster to judge whether the cluster was a kill site. RESULTS AND DISCUSSION Collared cougars from the previous year were captured and re-collared to replace exhausted batteries throughout the year. An additional 10 independent age cougars were also captured and collared during the year (Table 1). A total of 8 cubs were captured during the year and fitted with ear-tag transmitters (Table 2). Currently there are 13 independent age cougars in the study with functioning GPS collars, one of which is in Wyoming, one was a marked cub recently collared, and one was a rehabilitation cougar that was released in Pike forest. 192 �Home ranges for collared cougars have been determined using minimum convex polygons (MCP) to depict the general pattern of use and potential overlap (Figure 4), but likely over-represent the actual area used by an individual. Home ranges exhibit similar patterns to previous years, being fairly linear in a north-south direction. Adult male home ranges are much larger than adult female home ranges. Subadult male home ranges are smaller than adult male home ranges, but are also characterized by large movements and significant overlap with adults (Figure 5). Female home ranges are smaller with sizes between 80 and 120 km2. Female home ranges also have significant overlap, especially among related individuals (Figure 6). Mortalities of collared cougars were high with 6 new mortalities during the 2008-09 year (Table 1). Causes of death included vehicle collision, unknown sources, and management or landowner euthanasia. Mortality of cubs was also high with 5 of 8 tagged kittens dying during the 2008-09 year (Table 2). In general, cause of death for cubs was related to malnutrition although vehicle collisions also occurred. All cubs were at least 3 months old prior to tagging and most cub mortality occurred in ages older than 6 months. During 2008-09 there were an additional 4 cougars that entered the aversive conditioning treatment group (Table 1). In general these situations represented cases where a cougar killed a deer or other naturally occurring prey item within city limits or urban area. These situations did not demonstrate a cougar being habituated to these areas but more likely represented a cougar opportunistically taking prey in urban areas occurring on the edge of their home ranges. Two cougars were relocated out of Boulder city during the 2008-09 year. The cougars, an older female (AF24) and a cub (AM29) were relocated together, although it was known they were not a family unit. The adult female did return to the Boulder area after about a month. The cub also returned to the Boulder area after 3 months and survived until he was approximately one year old. The one successful relocation from the previous year (AM14) is still successful with the cougar remaining in the same translocation area. A considerable amount of effort was spent on investigating GPS clusters in an attempt to understand predator prey dynamics during the 2008-09 year with 445 GPS clusters being sampled. Primary actions at these sites averaged over individuals were day beds (5.6% ± 2.7%), predation (22.9% ± 11.7%), scavenging (0.7% ± 1.4%), hunting or traveling (38.4% ± 25.5%) or unknown (32.3% ± 25.3%) (Figure 7). Examining only S1 clusters (clusters with at least 2 locations within 200m) demonstrates 42.9% ± 19.9% of these sites having evidence of predation. Mule deer were the primary prey items found at clusters with confirmed kills. Female cougar kill sites consisted of 45% adult mule deer, 16% fawn mule deer, 24% unknown age mule deer, 10% small prey items, and 5% unknown prey items (Figure 8). Male cougar kill sites consisted of 34% adult mule deer, 6% fawn mule deer, 22% unknown age mule deer, 22% adult elk, 3% calf elk, 4% unknown age elk, and 9% small prey items. Small prey items included coyote, porcupine, raccoon and domestic cats and dogs. SUMMARY Genetic analysis for cougar feces revealed that DNA is still present in samples after feces have been in controlled temperature environments for up to 6 months. Genotyping error rates still need to be assessed. However, the presence of DNA in these samples suggests that field detection of cougar scats may be a viable non-invasive population sampling technique. We have added known-age samples collected from natural environments from known cougars marked in the front-range cougar project. 193 �The use of telomeres as a method to determine the age structure of bear and cougar populations is promising and will be investigated further in the coming year. Further refinement of the age-to-length relationship for both species is warranted. In addition to this, length relationships relative to genetic relatedness and individual stressors will give further insight into interpreting results from future data. In addition to re-collaring previously collared cougars, an additional 10 independent age cougars were collared during the year. We also put VHF eartag transmitters on 8 cubs during the year. Mortality remained high over the year exceeding 40% for independent age cougars and exceeding 50% for cubs. Home-range patterns remained consistent to previous years. The effectiveness of aversive conditioning is still showing mixed results, which is likely a factor of the opportunistic nature of cougars using urban environments and a lack of habituation to them. Relocation of cougars as a management tool has had limited assessment, but given some success, still warrants further investigation. Mule deer are the predominant prey in cougar diets, although males also utilize elk regularly. LITERATURE CITED Alldredge, M.W. 2007. Cougar demographics and human interactions along the urban-exurban front range of Colorado. Wildlife Research Report July: 153-202. Colorado Division of Wildlife, Fort Collins, USA. Anderson, C. R., F. G. Lindzey, and D. B. McDonald. 2004. Genetic structure of cougar populations across the Wyoming Basin: metapopulation or megapopulation. Journal of Mammalogy 85:12071214. Boutin-Ganache, I., M. Raposo, M. Raymond, and C. F. Deschepper. 2001. M13-tailed primers improve the readability and usability of microsatellite analyses performed with two different allele-sizing methods. Biotechniques, 31:25-28. Cawthon, R. M. 2002. Telomere measurement by quantitative PCR. Nucleic Acids Research 30:e47. Cougar Management Guidelines Working Group. 2005. Cougar Management Guidelines, 1sted. WildFutures, Bainbridge Island, Washington, USA. Ernest, H. B., M. C. T. Penedo, B. P. May, M. Syvanen, and W. M. Boyce. 2000. Molecular tracking of mountain lions in the Yosemite Valey region in California: genetic analysis using microsatellites and faecal DNA. Molecular Ecology 9:433-441. Harrison, R. L., P. B. S. Clarke, and C. M. Clarke. 2004. Indexing swift fox populations in New Mexico using scats. American Midland Naturalist 151:42-49. Haussmann, M.F., D.W. Winkler, K.M. O’Reilly, C.E. Huntington, I.C.T. Nisbet, and C.M. Vleck. 2003. Telomeres shorten more slowly in long-lived birds and mammals than in short-lived ones. Proceedings of the Royal Society of London Series B 270:1387-1392. Hemann, M. T., and C. W. Greider. 2000. Wild-derived inbred mouse strains have short telomeres. Nuclei Acids Research 28: 4474-4478. Hoss, M., M. Kohn, S. Paabo, F. Knauer, and W. Schroder. 1992. Excrement analysis by PCR. Nature 359:199. Logan, K.A. 2006. Cougar population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report July:95-122. Colorado Division of Wildlife, Fort Collins, USA. Menotti-Raymond, M. and S. J. O’Brien. 1995. Evolutionary conservation of ten microsatellite loci in four species of Felidae. Journal of Heredity 86:319-322. Menotti-Raymond, M., V. A. David, L. A. Lyons, A. A. Shcaffer, J. F. Tomlin, M. K. Hutton, and S. J. O’Brien. 1999. A genetic linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57:9-23. Meyne, J, R. L. Ratliff, and R. K. Moyzis. 1989. Conservation of the human telomere sequence (TTAGGG)n among vertebrates. Proceedings of the National Academy of Sciences 86: 7049-7053. Nakagawa, S., N.J. Gemmell, and T. Burke. 2004. Measuring vertebrate telomeres: applications and limitations. Molecular Ecology 13:2523-2533. 194 �Sinclair, E. A., E. L. Swenson, M. L. Wolfe, D. C. Choate, B. Bates, and K. A. Crandall. 2001. Gene flow estimates in Utah’s cougars imply management beyond Utah. Animal Conservation 4:257-264. Smith, D. A., K. Ralls, B. L. Cypher, and J. E. Maldonado. 2005. Assessment of scat-detection dog surveys to determine kit fox distribution. Wildlife Society Bulletin 33:897-904. Taberlet, P., and J. Bouvet. 1992. Bear conservation genetics. Nature 358:197. Watson, J.D. 1972. Origin of concatameric T4 DNA. Nature-New Biology 239:197-201. Prepared by Mathew W. Alldredge, Wildlife Researcher 195 �Table 1: Capture history, aversive conditioning treatments and current status of all independent age cougars captured as part of the Front-range cougar study. Cougar ID AM02 Sex M Age 1 1.5 1.5 7 7 8 8 8 9 5 6 4 2 2 1.5 AM04 M AM06 M AF03 AF01 AM05 AM07 F F M M AF08 F AM09 M AF10 F AF19 F 8+ 8+ AF11 F 1.5 AM20 M 4 AF15 F AF17 F 6 7 9+ 1.5 3 1.5 2.5 7 Date 6/14/07 1/10/08 2/9/08 7/14/07 10/17/07 4/29/08 5/5/08 8/4/08 2/24/09 11/21/07 12/30/08 11/29/07 12/17/07 12/19/07 12/26/07 4/19/08 12/26/07 6/18/09 12/28/07 12/27/08 1/15/08 2/13/08 3/4/08 3/18/09 4/13/19 3/5/08 6/10/08 3/6/08 5/18/08 3/18/09 4/2/09 3/29/08 5/20/08 Location Lacey Prop. White Ranch Coal Creek White Ranch Eldorado Springs Magnolia/Flagstaff South Boulder North Boulder Boulder Canyon Heil Valley Ranch Heil Valley Ranch Flagstaff Table Mesa White Ranch Heil Valley Ranch Highway 7 Heil Valley Ranch West Horsetooth Heil Valley Ranch Hwy 34 (mile 70) Apex Open Space I-70 Heil Valley Ranch North Boulder Left Hand Canyon South Table Mesa US-40/Empire White Ranch West of White Ranch Coffin Top Hall Ranch Sugarloaf Four-mile Canyon Occurrence Baiting Capture effort Intraspecific mortality Baiting Livestock depredation Replace Collar Seen in town Killed deer in town Punctured intestine Capture effort Replace Collar Deer kill Deer kill Capture effort Capture effort Roadkill Capture effort Deer kill-remove collar Capture effort Roadkill Deer Kill Roadkill Capture effort Deer Kill Deer Kill Deer Kill Roadkill Capture effort Livestock Depredation Capture effort Replace Collar Pet depredation Unknown mortality 196 Capture Cage Hounds Release Loc On-site On-site Conditioning NA NA Cage Cage Hounds Free-dart Cage On-site White Ranch On-site Lindsey Centennial Cone NA Beanbag NA Beanbag Beanbag Hounds Hounds Cage Cage Hounds Hounds On-site On-site On-site On-site On-site On-site NA NA NA NA NA NA Hounds Cage Hounds On-site On-site On-site NA NA NA Cage On-site NA Hounds Cage Cage Cage On-site Heil Valley Ranch Heil Valley Ranch On-site NA Beanbag NA NA Hounds Shot Hounds Hounds Cage On-site NA On-site On-site Within 1 mile NA NA Beanbag Status Alive Alive Dead Alive Alive Alive Alive Alive Dead Alive Alive Alive Alive Alive Alive Dead Alive Alive Alive Dead Alive Dead Alive Alive Alive Alive Dead Alive Dead Alive Alive Alive Dead �Table 1 Cont. AF12 F 2 AM13 M 2 AM14 M 2 AF34 F 1.5 AM18 M 1.5 AF16 F 3 AF45 AF40 AF24 F F F 5 1.5 10+ AM31 M 1.5 AF37 F 1.5 AM21* AF32 M F 1.5 1.5 5/8/08 5/29/08 2/13/09 5/8/09 12/17/09 5/15/09 5/20/09 4/14/09 12/5/08 3/18/09 12/24/08 3/14/09 12/29/08 3/20/09 1/2/09 1/27/09 2/12/09 2/25/09 4/4/09 5/31/09 12/31/08 3/29-09 12/31/08 8/112/09 8/29/09 9/28/09 SW023 F 1 4/9/09 N. Boulder N. Boulder N. Boulder Sugarloaf Heil Valley Ranch South Boulder South Boulder Rollins Pass Heil Valley Ranch N. Boulder Evergreen Evergreen Evergreen Evergreen Gold Hill White Ranch North Boulder Hwy 7 North Boulder North Boulder Evergreen Conifer Evergreen I-70 N. Boulder Indian Hills Deer Kill Livestock depredation Deer Kill Livestock depredation Replace Collar Seen under deck Deer kill Replace Collar Capture effort Deer kill Deer kill Livestock depredation Deer Kill Livestock depredation Deer kill Capture effort Deer Kill Replace Collar Raccoon Kill Encounter Chicken coop Livestock depredation Chicken coop Roadkill Encounter Livestock depredation Cage Cage Snare Cage Hounds Free-dart Free-dart Hounds Hounds Cage Cage Cage Snare Cage Cage Hounds Cage Hounds Free-dart Shot Hounds Cage Free-dart US Forest Boulder Canyon Near Ward None On-site On-site Lindsey West of Rollinsville On-site On-site Heil Valley Ranch Mt. Evans SWA None Flying J Open Space Mt. Evans SWA On-site On-site Hall Ranch On-site Heil Valley Ranch Beanbag Beanbag Euthanized Beanbag NA None Beanbag NA NA Beanbag None Euthanized None Beanbag NA NA None NA None On-site Mt. Evans SWA On-site None None None Free-dart Cage Ward Within 1 mile None None Alive Alive Dead Alive Alive Alive Alive Alive Alive Alive Alive Dead Alive Alive Alive Alive Alive Alive Alive Dead Alive Alive Alive Dead Alive Alive Rehab Release Pike forest None Alive 197 �Table 2: Capture history, maternal relationship, aversive treatment and current status of all cubs capture as part of the Front-range cougar study. Cougar ID Sex Age Mother Date AF35 F 3 AF16 12/29/08 12/31/08 AM36 M 3 AF16 12/29/08 1/8/09 AM30 M 8 AM01 1/30/09 AM38 M 8 AM01 1/30/09 3/27/09 3/30/09 4/9/09 AM29 M 6 Euth. 2/11/09 12 6/15/09 AM21* M 12 Unkn 3/25/09 AM25 M 12 Unkn 5/22/09 9/13/09 AM41 M 12 Unkn 5/22/09 Location Evergreen Evergreen Evergreen Evergreen S. Boulder S. Boulder S. Boulder S. Boulder Morrison N. Boulder N. Boulder Table Mesa Indian Hills Occurrence Deer Kill Roadkill Deer Kill Starvation Deer Kill Deer Kill Encounter Pet Depredation Encounter Deer Kill Encounter Baiting Deer Kill Raccoon Indian Hills Deer Kill Indian Hills Encounter 198 Capture Cage Release Loc Conditioning Flying J Open Space Cage Flying J Open Space Cage Cage Free-dart Free-dart Free-dart Free-dart Free-dart Cage Cage Free-dart Free-dart Shot On-site On-site Lindsey Centennial Cone None Hall Ranch Masonville On-site On-site Perforated intestine On-site Beanbag None Euthanized None Beanbag NA None None Status Alive Dead Alive Dead Alive Alive Alive Alive Dead Alive Alive Alive Alive Dead Alive Dead �Figure 1. Example standard curve and amplification plot obtained from Q-PCR 199 �2.5 A y = 0.94 - 0.092x 0.7 B 0.6 2.0 y = 0.34 - 0.021x 0.5 ln (T/S) 1.5 0.4 0.3 1.0 0.2 0.5 0.1 0.0 0.0 0 2 4 6 8 10 0 2 4 6 8 10 Approximate age (yrs) Figure 2. Linear relationship between age and telomere length for blood samples of cougars (A) and black bears (B) inhabiting Wyoming and Colorado. 200 �Figure 3: Study area boundary with the continental divide to the west, Highway 285 on the south, Highway 34 and 36 on the north, and the edge of the foothills on the east. 201 �Figure 4: Male and female MCP homeranges for cougars with functioning GPS collars depicting the overlap in homeranges between males and females. 202 �Figure 5: Homeranges for male cougars with functioning GPS collars. Homerange size for AM13 and AM14 appear large but this is primarily a factor of management related movement (AM14) or a change in the area of use (AM13). 203 �Figure 6: Homeranges for female cougars with functioning GPS collars. Female homeranges overlap one another, which may be related individuals. 204 �Figure 7: Proportional activities reported across all 445 GPS cluster sites investigated based on the number of points at the location, evidence of activity at the location, and distance to previous locations not associated with the cluster. Figure 8: Proportion of prey items found at kill sites where evidence of prey was found. Category other is generally associated with small prey items such as coyote, porcupine, raccoon, and domestic cats and dogs. 205 �206 �Colorado Division of Wildlife July 2008 – June 2009 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 7210 1 : : : : Division of Wildlife Mammals Research Customer Services/Research Support Library Services N/A Period Covered: July 1, 2008 – June 30, 2009 Author: Kay Horton Knudsen Personnel: Kay Horton Knudsen, David J. Freddy, Michael W. Miller All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT After providing 17 years of professional library services for the entire Colorado Division of Wildlife, research librarian Jackie Boss retired in April 2007. The permanent position was retained and a formal hiring process was initiated in Fall 2007. In the interim, the library remained closed to all services. In June 2008, Kay Horton Knudsen was hired as the new research librarian and began employment with the Colorado Division of Wildlife on August 30, 2008. David J. Freddy was the Mammals Research Team Leader and supervised the librarian until his retirement in December 2008. Michael W. Miller was the interim Mammals Research Team Leader from January-June 2009. A progress report and current status of the Library are detailed below. 207 �WILDLIFE RESEARCH REPORT COLORADO DIVISION OF WILDLIFE RESEARCH LIBRARY SERVICES KAY HORTON KNUDSEN P.N. OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Division of Wildlife (CDOW) employees, cooperators, wildlife educators, and the public. SEGMENT OBJECTIVES 1. Continue to improve and modernize library services. 2. Continue to develop, improve, and implement the CDOW Research Center Library web-site. SUMMARY OF LIBRARY SERVICES The first task facing the new librarian was to sort 8 boxes of accumulated mail and re-activate the online Library catalog hosted by the vendor SirsiDynix. Discussions followed with the supervisor, other research managers, the Library committee and members of the Research staff on their vision and goals for the Library as well as their needs in the research arena. Meetings also took place with the governmental special librarians in Ft. Collins at the U.S. Forest Service, the National Wildlife Research Service (USDA’s Animal and Plant Health Inspection Service), the U.S. Geological Survey as well as with the Natural Resources Librarian at Colorado State University’s Morgan Library. From these discussions it was determined the top priority was a new web-based integrated library system (ILS) and access to research databases for Colorado Division of Wildlife employees statewide. The ILS would include a library catalog and a circulation system as well as cataloging and serials checkin modules. Other items on the ILS wish list were a hosted system (server maintained at vendor’s facility), federated searching (ability to search the catalog plus multiple databases with one search) and ability of the system to handle digital media. The librarian’s research produced a list of 4 companies providing ILS service to special libraries (as opposed to public and academic libraries); a list of requirements was sent to each vendor and phone discussions and web demonstrations followed. A more extensive web demonstration was scheduled for the CDOW research managers and Library committee. EOS International was chosen as the vendor of preference; contract negotiations and purchase orders were submitted and a final agreement was completed in December 2008. It was decided to initially purchase the basic modules (a hosted system with library catalog, circulation, cataloging and serials control) and delay other features until the system was up and running. Data migration from SirsiDynix to EOS took place in January 2009, library staff training in February and release of the Library website to CDOW staff in March 2009. During this time, Library research databases were also investigated and demonstrated. Using the same evaluation procedure as with the ILS, it was decided to purchase access to BioOne, four of EBSCO’s specialty databases (Environment Complete, Fish and Fisheries Worldwide, Wildlife and Ecology Studies Worldwide and SocIndex with Full Text) and the JSTOR Life Sciences collection. Through several of the print periodical subscriptions, the Library also has access to the publisher’s full- 208 �text online archives. When the Library catalog was released to CDOW staff (authenticated through the WildNet staff network), access was also given to the research databases and the online journal archives. The next step was training for CDOW staff on the various features of the new Library website. Group and individual sessions were held in Ft. Collins and at CDOW offices in Glenwood Springs, Grand Junction, Durango, Montrose and Colorado Springs. Demonstrations are planned at other staff meetings during the coming year. Handouts were created to assist staff with basic website use and the specialized database features such as creating subject and table of contents alerts. Other projects in the Library this year included 1) massive physical cleaning and sorting of documents to determine the resources available and to make them accessible to the librarian, 2) cataloging of new material, 3) inclusion of PDF formats into the catalog’s bibliographic file if PDF is available, 4) clean-up of bibliographic barcodes in the Library database, 5) renewal of print journal subscriptions based on discussions with research managers and consolidation of several periodical invoices into one and 6) cataloging of staff reprint articles following a request to research staff to provide copies of their publications (most often journal articles). Work-study staff was hired from Colorado State University during part of Fall semester 2008 and all of Spring semester 2009 to assist in these efforts. The librarian attended the Colorado Association of Libraries conference in Denver in November 2008, the exhibits area of the American Association of Libraries Mid-Winter meeting in Denver in January 2009, an EBSCO Train-the-Trainer session in Greeley in March 2009, a 5-day Wildlife Management Short Course offered at CSU in March/April 2009 and a Colorado InterLibrary Loan update meeting at Estes Park in April 2009. Most document requests and reference questions received in the Library are from CDOW staff or from outside researchers (generally consultants and out-of-state natural resources employees). At this time the Library is not open on a walk-in basis to the general public. CDOW employees request journal articles or items from the Library collection; outside researchers most often want a copy of a CDOW publication. Therefore the immediate focus for Library staff resources will be on organizing and cataloging Colorado publications and obtaining documents per staff request. The chart below shows the number of reference questions and document requests handled by the librarian during the past year. Please note that 1 request from a CDOW staff member may be for multiple journal or book titles. For example, in September there was a request for 50 articles/ books on crawfish and in June a request for 40 titles on raptors. August 2008 September 2008 October 2008 November 2008 December 2008 January 2009 February 2009 March 2009 April 2009 May 2009 June 2009 Reference Requests 15 21 33 14 28 33 30 35 24 13 20 209 �The Research Center Library holds 18,403 titles and 24,800 items (these are the multiple copies of a title); has 84 registered patrons (CDOW staff) and 252 items were checked out this year. There are 82 PDFs currently attached to title records in the Library catalog. Usage statistics for the research databases are given in the chart below. For BioOne and JSTOR the statistics are for the number of successful full-text article requests; the Library did not subscribe to BioOne until late February. For EBSCO, the number shown is the total number of searches by CDOW staff. January 2009 February 2009 March 2009 April 2009 May 2009 June 2009 July 2009 BioOne 0 0 7 76 30 77 55 EBSCO searches 449 1757 610 1492 1321 395 1255 Prepared by ___________________________ Kay Horton Knudsen 210 JSTOR 16 348 532 266 208 140 111 � https://cpw.cvlcollections.org/files/original/a57afbddf4264d3b9f5b37857271e3e1.pdf 40ea3445dca95c741d1c6c8b4cb8a866 PDF Text Text MAMMALS - JULY 2010 �i �WILDLIFE RESEARCH REPORTS JULY 2009 – JUNE 2010 MAMMALS PROGRAM COLORADO DIVISION OF WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). ii �STATE OF COLORADO Bill Ritter, Jr., Governor DEPARTMENT OF NATURAL RESOURCES Mike King, Executive Director WILDLIFE COMMISSION Tim Glenn, Chair……………………………………………….………..………………….……......Salida Robert Streeter, Vice Chair……………………………….……………………………………Fort Collins Mark Smith, Secretary…………………………………………………………………………….….Center David Brougham…………………………………………………………………………………Lakewood Dennis Buechler, ……………………………………………….………….….………………....Centennial Dorothea Farris………………………………………………………………………….….……Carbondale Allan Jones………………………………………………………………………………………...…Meeker John Singletary……………………………………………………………………..………………Vineland Dean Wingfield………………………………………………………………………..……………..Vernon Mike King, Executive Director, Ex-officio………….…………………...………………….…….....Denver John Stulp, Dept. of Agriculture, Ex-officio….………………………………..…………………Lakewood DIRECTOR’S STAFF Thomas Remington, Director Mark Konishi, Assistant Director-Field Operations Marilyn Salazar, Assistant Director-Support Services Jeff Ver Steeg, Assistant Director-Wildlife Programs Susan Hunt, Chief Financial Officer MAMMALS RESEARCH STAFF Chad Bishop, Mammals Research Leader Mat Alldredge, Wildlife Researcher Chuck Anderson, Wildlife Researcher Eric Bergman, Wildlife Researcher Jake Ivan, Wildlife Researcher Ken Logan, Wildlife Researcher Tanya Shenk, Wildlife Researcher Kay Knudsen, Librarian Margie Michaels, Program Assistant iii �Colorado Division of Wildlife July 2009 – June 2010 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS LYNX CONSERVATION WP 0670 POST-RELEASE MONITORING OF LYNX REINTRODUCED TO COLORADO by T. Shenk and J. Ivan……………………………….……………….01 DEER CONSERVATION WP 0663 MULE DEER BODY CONDITION MODEL by M. Rice1…………………………...27 WP 3001 POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson…………………………………………………….47 WP 3001 EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER IN MULE DEER by C. Bishop…..…………………………………………………….63 WP 3001 EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER by E. Bergman……………………………………………………………………….…81 WP 3001 DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS by C. Bishop…..………………………………..93 PREDATORY MAMMALS CONSERVATION WP 3003 PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU by K. Logan………………………………………….101 WP 3003 COUGAR DEMOGRAPHICS AND HUMAN INTERACTION ALONG THE URBAN-EXURBAN FRONT-RANGE OF COLORADO by M. Alldredge………...153 SUPPORT SERVICES WP 7210 1 LIBRARY SERVICES by K. Knudsen……..……………………………...…………177 Mindy Rice is a spatial ecologist in the Avian Research Section of the Colorado Division of Wildlife iv �v �Colorado Division of Wildlife July 2009–June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Lynx Conservation Post-Release Monitoring of Lynx Reintroduced to Colorado Period Covered: July 1, 2009 – June 30, 2010 Author: T. M. Shenk Personnel: O. Devineau, R. Dickman, P. Doherty, L. Gepfert, J. Ivan, R. Kahn, A. Keith, P. Lukacs, G. Merrill, B. Smith, T. Spraker, S. Waters, G. White, L. Wolfe All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to establish a viable population of Canada lynx (Lynx canadensis) in Colorado, the Colorado Division of Wildlife (CDOW) initiated a reintroduction effort in 1997 with the first lynx released in February 1999. From 1999-2006, 218 wild-caught lynx from Canada and Alaska were released in Colorado. Post-release monitoring was critical to assess and modify the release protocols as they were implemented to improve the survival of released individuals. Average monthly mortality rate in the reintroduction area during the first year post-release decreased with time in captivity from 0.205 [95% CI 0.069, 0.475] for lynx spending up to 7 days in captivity to 0.028 [95% CI 0.012, 0.064] for lynx spending > 45 days in captivity before release. Under the final release protocol, lynx were held in captivity and fed a high quality diet for a minimum of three weeks before release. Results suggested that keeping lynx in captivity beyond 5 or 6 weeks accrued little benefit in terms of monthly survival. We documented survival, movement patterns, reproduction, and landscape habitat-use through aerial (n = 11,580) and satellite (n = 29,258) tracking. Monthly mortality rate was estimated as lower inside the reintroduction area than outside the reintroduction area, and slightly higher for male than for female lynx, although 95% confidence intervals for sexes overlapped. Mortality was higher immediately after release (first month = 0.0368 [SE = 0.0140] inside the study area, and 0.1012 [SE = 0.0359] outside the study area), and then decreased according to a quadratic trend over time. Given the importance of adult survival in the dynamics of long-lived species, the long-term, high survival rates estimated for the reintroduced lynx both inside (0.9315, SE = 0.0325) and outside (0.8219, SE = 0.0744) the reintroduction area are promising for the establishment of a viable population of lynx in Colorado. From 1999-June 2010, there were 122 known mortalities of released adult lynx. Human-caused mortality factors were the highest causes of death with approximately 29.7% attributed to collisions with vehicles or gunshot. Starvation and disease/illness accounted for 18.6% of the deaths while 37.3% of the deaths were from unknown causes. Reproduction was first documented in 2003 with subsequent successful reproduction 1 �in 2004, 2005, 2006, 2009, and 2010. No dens were documented in 2007 or 2008. Reproduction followed a pattern of good and bad years followed by a return to good years in both the reintroduction area and outside the reintroduction area suggesting there may be a cyclic pattern to reproductive output of lynx in Colorado. If the pattern of annual reproductive and survival parameters estimated to date for lynx within the core reintroduction area would repeat over the next 20 years, the population currently in the core reintroduction area would sustain itself at existing densities. To document the continued viability of lynx in Colorado beyond the reintroduction period, some form of long-term monitoring will be needed. A site-occupancy monitoring program using cost-effective, minimally invasive techniques is currently being developed to estimate the extent, stability and potential distribution of lynx throughout Colorado. 2 �WILDLIFE RESEARCH REPORT POST RELEASE MONITORING OF LYNX (LYNX CANADENSIS) REINTRODUCED TO COLORADO TANYA M. SHENK P. N. OBJECTIVE The post-release monitoring of Canada lynx (Lynx canadensis) reintroduced into Colorado emphasized 5 primary objectives: 1. Assess and modify release protocols to ensure the highest probability of survival for each lynx released. 2. Obtain regular locations of released lynx to describe general movement patterns and habitats used by lynx. 3. Determine causes of mortality in reintroduced lynx. 4. Estimate survival of lynx reintroduced to Colorado. 5. Estimate reproduction of lynx reintroduced to Colorado. Three additional objectives were emphasized after lynx displayed site fidelity to an area: 6. Refine descriptions of habitats used by reintroduced lynx. 7. Refine descriptions of daily and overall movement patterns of reintroduced lynx. 8. Describe hunting habits and prey of reintroduced lynx. Information gained to achieve these objectives will form a basis for the development of lynx conservation strategies in the southern Rocky Mountains. SEGMENT OBJECTIVES 1. Complete winter 2009-10 field data collection on lynx habitat use at the landscape scale, hunting behavior, diet, mortalities, and movement patterns. 2. Complete data collection for the pilot study designed to estimate lynx detection probabilities using non-invasive techniques. 3. Complete spring 2010 field data on lynx reproduction. 4. Summarize and analyze data and publish information as Progress Reports, peer-reviewed manuscripts for appropriate scientific journals, or CDOW technical publications (see Appendix I). 5. Complete field research on the post-release monitoring of lynx reintroduced to Colorado and prepare a final report describing status of the lynx reintroduction. INTRODUCTION The Colorado Division of Wildlife implemented the largest Canada lynx (Lynx canadensis), and one of the largest carnivore, reintroductions programs undertaken to date. Thus, evaluating success of this program is critical, and assessing the methods used may prove useful for other ongoing or future carnivore reintroductions. The reintroduction effort was begun in Colorado in 1997, with the first lynx released in the state in 1999. The goal of the Colorado lynx reintroduction program was to establish a self-sustaining, viable population of lynx in this state. The approach taken to reach this goal was to first establish a viable lynx population within a core reintroduction area in southwestern Colorado. From this core reintroduction area, it was hoped that lynx would remain in this area and disperse on their own into 3 �suitable habitat throughout the state. Thus, 218 wild-caught lynx from Canada and Alaska were reintroduced in the core reintroduction area from 1999-2006. There were 7 critical criteria established for achieving a viable lynx population in Colorado: 1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, 2) long-term survival of lynx in Colorado, 3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, 4) reintroduced lynx must breed, 5) breeding must lead to reproduction of surviving kittens 6) lynx born in Colorado must reach breeding age and reproduce successfully, and 7) recruitment must equal or be greater than mortality over an extended period of time. These criteria were evaluated incrementally over time to gauge whether the reintroduction effort was progressing toward success (Shenk and Kahn 2002). All seven criteria have now been met. STUDY AREA Byrne (1998) evaluated five areas within Colorado as potential lynx habitat based on (1) relative snowshoe hare densities (Bartmann and Byrne 2001), (2) road density, (3) size of area, (4) juxtaposition of habitats within the area, (5) historical records of lynx observations, and (6) public issues. Based on results from this analysis, the San Juan Mountains of southwestern Colorado were selected as the core reintroduction area, and where all lynx were reintroduced. Wild Canada lynx captured in Alaska, British Columbia, Manitoba, Quebec and Yukon were transported to Colorado and held at The Frisco Creek Wildlife Rehabilitation Center located within the reintroduction area prior to release. Post-release monitoring efforts were focused in a 20,684 km2 study area which included the core reintroduction area, release sites and surrounding high elevation sites (> 2,591 m). The area encompassed the southwest quadrant of Colorado and was bounded on the south by New Mexico, on the west by Utah, on the north by interstate highway 70, and on the east by the Sangre de Cristo Mountains (Figure 1). Southwestern Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4,200 m. Engelmann spruce/subalpine fir is the most widely distributed coniferous forest type within the study area. The lynx-established core area is roughly bounded by areas used by lynx in the Taylor Park/Collegiate Peak areas in central Colorado and includes areas of continuous use by lynx, including areas used during breeding and denning (Figure 1). METHODS, RESULTS AND DISCUSSION Development of Release Protocols Post-release monitoring was critical to assess and modify the release protocols as they were implemented to improve the survival of released individuals (Shenk 1999). Under the final release protocol, lynx were held in captivity and fed a high quality diet for a minimum of three weeks before release. Thus, they were released in good body condition and one could expect that the longer the captivity, the lower the post-release mortality. This final protocol resulted in high initial post-release survival. Later, detailed analysis of lynx mortality was completed to evaluate how the different release protocols affected mortality within the first year post-release. From this analysis, it was documented that the average monthly mortality rate in the reintroduction area during the first year post-release decreased with time in captivity from 0.205 [95% CI 0.069, 0.475] for lynx spending up to 7 days in captivity to 0.028 [95% CI 0.012, 0.064] for lynx spending > 45 days in captivity before release (Devineau et al. 2010a). The results also suggested that keeping lynx in captivity beyond 5 or 6 weeks accrued little benefit in terms of monthly survival. On a monthly average basis, lynx were as likely to move out (probability = 0.196, SE=0.032) as to move back on (probability = 0.143, SE=0.034) the reintroduction area during the first year after release. Mortality was 1.6x greater outside of the reintroduction area 4 �suggesting that permanent emigration and differential mortality rates on and off reintroduction areas should be factored into sample size calculations for an effective reintroduction effort. Our results will be useful in the development of release and post-release monitoring protocols for future lynx, as well as other carnivore, reintroductions. Long-Term Survival Viability of a reintroduced population requires long-term survival and site fidelity of individuals to the reintroduction area. Over a 10-year period of the reintroduction effort (1999-2009), monthly mortality rate was estimated as lower inside the reintroduction area than outside the reintroduction area, and slightly higher for male than for female lynx, although 95% confidence intervals for sexes overlapped (Devineau et al. 2010). Mortality was higher immediately after release (first month = 0.0368 [SE = 0.0140] inside the study area, and 0.1012 [SE = 0.0359] outside the study area), and then decreased according to a quadratic trend over time. Given the importance of adult survival in the dynamics of longlived species, the long-term, high survival rates estimated for the reintroduced lynx both inside (0.9315, SE = 0.0325) and outside (0.8219, SE = 0.0744) the reintroduction area are promising for the establishment of a viable population of lynx in Colorado (Figure 2, Devineau et al. 2010b). The higher mortality outside the reintroduction area may have been influenced by habitat fragmentation, increased road density and more opportunities for human interactions. From 1999-June 2010, there were 122 known mortalities of released adult lynx. Human-caused mortality factors are currently the highest causes of death with approximately 29.7% attributed to collisions with vehicles or gunshot. Starvation and disease/illness accounted for 18.6% of the deaths while 37.3% of the deaths were from unknown causes. Lynx mortalities were documented throughout all areas lynx used, including 31 (26.3%) occurring in other states. Reproduction Reproduction is necessary to achieve a self-sustaining viable population of lynx in Colorado. Reproduction was first documented from the 2003 reproduction season and again in 2004, 2005 and 2006. Lower reproduction occurred in 2006, although a Colorado-born female gave birth to 2 kittens, documenting the first recruitment of Colorado-born lynx into the Colorado breeding population. No reproduction was documented in 2007 or 2008. The cause of the decreased reproduction from 2006 -08 is unknown. One possible explanation would be a decrease in prey abundance. Reproduction was again observed in 2009 with 5 dens and 10 kittens found in Colorado. Litter size was smaller than previously documented with only 2 kittens found in each litter in comparison to a mean of 2.8 found in previous years. In addition, a sex bias towards female kittens was evident in 2009 which was not evident in prior years. Two litters found in 2009 had both parents born in Colorado, resulting in the first documented third generation Colorado lynx from the reintroduction. The percent of females having dens increased in 2010 to 33%, similar to the highest years documented in 2004-2005. The average number of kittens per litter also returned to the previously observed mean of 2.8. Breeding males and females in 2010 included Colorado-born lynx that have established territories and are now contributing to the breeding population. Reproduction has followed a pattern of good and bad years followed by a return to good years in both the reintroduction area (Figure 3) and outside the reintroduction area suggesting there may be a cyclic pattern to reproductive output of lynx in Colorado. Such a pattern matches the classic Canada lynx-snowshoe hare (Lepus americanus) cycle (Elton 1942). Long-term studies spanning an additional10-20 years would be required to document such a cycle in Colorado. Viability The current lynx population in Colorado is comprised of surviving reintroduced adults, lynx born in Colorado from the reintroduced animals and their offspring and possibly some naturally occurring lynx. To achieve a self-sustaining, viable population of lynx, enough kittens need to be born and 5 �recruited into this population to offset the mortality that occurs and hopefully even exceed the mortality rate to achieve an increasing population. If the pattern of annual reproductive and survival parameters estimated to date for lynx within the core reintroduction area would repeat over the next 20 years, the population currently in the core reintroduction area would sustain itself at existing densities (Figure 4). FUTURE DIRECTIONS Research and monitoring efforts over the last 11 years, since the first lynx were released, have focused primarily on monitoring reintroduced animals through VHF and satellite telemetry and estimating demographic parameters of these animals. However, as more of these animals become unavailable for monitoring due to failed telemetry collars, death or movement out of the core reintroduction area, it becomes more difficult to accurately evaluate the status of the entire lynx population in Colorado, including the core reintroduction area. To document the continued viability of lynx in Colorado beyond the reintroduction period, some form of long-term monitoring will be needed to determine viability for a period of time long enough to encompass possible snowshoe hare cycles. In addition, a challenge facing Colorado Division of Wildlife is how efforts should be allocated between monitoring persistence of lynx that have established within the core reintroduction area and lynx that may be pioneering and expanding into other portions of the state. A site-occupancy monitoring program using cost-effective, minimally invasive techniques is currently being developed to estimate the extent, stability and potential distribution of lynx throughout Colorado (Shenk 2009, Appendix 2). The primary objectives of this monitoring program would be to document the distribution of lynx throughout Colorado and the stability, growth or shrinkage of this distribution over time, and to identify potential areas lynx may occupy in the future. Minimally invasive techniques (e.g., genetic identification, cameras) would be used to detect changes in lynx persistence and distribution as a foundation for assessing whether lynx continue to persist in Colorado. Such noninvasive techniques are widely desirable because they require minimal impact to the animals and are costeffective. The protocols developed will also be made available to any other agencies or entities that want to monitor lynx. Methods to extend this monitoring effort to estimate lynx density are currently being pursued. ADDITIONAL EFFORTS Additional goals of the post-release monitoring program for lynx reintroduced to the southern Rocky Mountains included refining descriptions of habitat use and movement patterns of lynx once lynx established home ranges that encompassed their preferred habitat. This work is ongoing. The program also investigated the ecology of snowshoe hare in Colorado. A study comparing snowshoe hare densities among mature stands of Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), lodgepole pine (Pinus contorta) and Ponderosa pine (Pinus ponderosa) was completed in 2004 with highest hare densities found in Engelmann spruce/subalpine fir stands and no hares found in Ponderosa pine stands (Zahratka and Shenk 2008). A study to evaluate the importance of young, regenerating lodgepole pine and mature Engelmann spruce/subalpine fir stands in Colorado by examining density and demography of snowshoe hares that reside in each was completed in 2010. Small lodgepole stands supported the highest densities of hares as well as the highest and most consistent recruitment rates. Hares survived best in spruce/fir stands while density and recruitment in these stands were intermediate. Thus, small lodgepole and mature spruce/fir likely provide the most important hare habitat in Colorado; while thinned, medium lodgepole stands appear to be relatively unimportant based on the density and demography measures in this study (J. Ivan, Colorado State University, unpublished data, Appendix 3). However, within the study area, small lodgepole stands occupied only 10% of the area 6 �covered by mature spruce/fir, and we suspect a similar pattern statewide. Additionally, the structure provided by mature spruce/fir stands is less transient than that provided by regenerating lodgepole. Thus, while density and recruitment estimates in spruce/fir stands were somewhat inferior to those collected in small lodgepole, the areal coverage and longevity of spruce/fir likely renders it as important, if not more important, to snowshoe hare and lynx management in Colorado as regenerating lodgepole (J. Ivan, Colorado State University, unpublished data, Appendix 3). Lynx is listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.)(U. S. Fish and Wildlife Service 2000). Colorado is included in the federal listing as lynx habitat. Thus, an additional objective of the post-release monitoring program is to develop conservation strategies relevant to lynx in Colorado. To develop these conservation strategies, information specific to the ecology of the lynx in its southern Rocky Mountain range, such as habitat use, movement patterns, mortality factors, survival, and reproduction in Colorado have been and will continue to be provided to regulatory agencies. SUMMARY From results to date it can be concluded that the Colorado Division of Wildlife developed release protocols that ensured high initial post-release survival of lynx, and on an individual level, lynx demonstrated they can survive long-term in areas of Colorado. We also documented that reintroduced lynx exhibited site fidelity, engaged in breeding behavior and produced kittens that were recruited into the Colorado breeding population. Following the successful reproduction in 2010, we have now documented that if the population would repeat the reproduction and mortality patterns documented over the last 10 years the lynx population would continue into the future at sustainable numbers. Thus, the final criterion of a successful reintroduction, documenting recruitment necessary to offset annual mortality, is now supported. To build upon the success of this reintroduction effort, effective conservation and management strategies will need to be developed and implemented to ensure the long-term viability of Canada lynx in Colorado. ACKNOWLEDGEMENTS The Colorado Lynx Reintroduction Program required the continued efforts of numerous personnel in the Colorado Division of Wildlife, other agencies and the general public. Such sustained dedication has resulted in the successful reintroduction of this species to our ecosystems. Funding for the reintroduction program was provided by Colorado Division of Wildlife, Great Outdoors Colorado (GOCO), Vail Associates, Colorado Wildlife Heritage Foundation, Turner Endangered Species Foundation and the U.S.D.A. Forest Service. LITERATURE CITED Bartmann, R. M., and G. Byrne. 2001. Analysis and critique of the 1998 snowshoe hare pellet survey. Colorado Division of Wildlife Report No. 20. Fort Collins, Colorado. Byrne, G. 1998. Core area release site selection and considerations for a Canada lynx reintroduction in Colorado. Report for the Colorado Division of Wildlife. Devineau, O., T. M. Shenk, P. F. Doherty Jr., G. C. White, and R. H. Kahn. 2010. Assessing release protocols for the Colorado Canada lynx (Lynx canadensis) reintroduction. Journal of Wildlife Management (in review). Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524-531. 7 �Elton, C. and M. Nicholson 1942. The ten-year cycle in numbers of lynx in Canada. Journal of Animal Ecology 11: 215-244. Shenk, T. M. 2002. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 7- 34. Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2009. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, July: 1-57. Colorado Division of Wildlife, Fort Collins, Colorado Shenk, T. M. and R. H. Kahn. Lynx reintroduction: report to wildlife commission. Colorado Division of Wildlife. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. Zahratka, J. L. and T. M. Shenk. 2008. Population estimates of snowshoe hares in the southern Rocky Mountains. Journal of Wildlife Management 72:906-912. Prepared by __________________________________________________________ Tanya Shenk, Wildlife Researcher & Jake Ivan, Wildlife Researcher 8 �Figure 1. Lynx are monitored throughout Colorado and by satellite throughout the western United States. The lynx core release area, where all lynx were released, is located in southwestern Colorado (outlines in white). A lynx-established core use area has developed in the Taylor Park and Collegiate Peak area in central Colorado. 9 �Figure 2. Variation of monthly mortality rate with time since release for Canada lynx reintroduced to Colorado, inside and outside of the study area, according to the best-AICc model (from Devineau et al. 2010). Only the first 50 months following release are shown. Figure 3. Percent of tracked Canada lynx females in the reintroduction area found with kittens in May or June from 2003 through 2010. 10 �Figure 4. Projected Canada lynx population trend in the core reintroduction area over 20 years if the pattern of reproductive and survival parameters observed over the last 8 years would repeat. The initial population sizes of 50 males and 50 females for this projection was not based on a current population estimate, however, they are not unreasonable assumptions for the study area. Using alternative initial population sizes would not change the projected pattern. 11 �APPENDIX I STATUS OF PUBLICATIONS ASSOCIATED WITH THE COLORADO LYNX REINTRODUCTION PROGRAM Five papers have been published: Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty, Jr., P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524–531. Shenk, T. M., R. H. Kahn, G. Byrne, D. Kenvin, S. Wait, J. Seidel, and J. Mumma. 2009. Canada lynx (Lynx canadensis) reintroduction in Colorado. Pages 410-421 in A. Vargas, C. Breitenmoser, and U. Breitenmoser, editors. Iberian Lynx Ex situ Conservation: An Interdisciplinary Approach. Fundacion Biodiversidad, Madrid, Spain. Shenk, T. M and, R. H. Kahn. 2009. Reintroduction of the Canada lynx (Lynx canadensis) to Colorado. in Proceedings of the Third Iberian Lynx Symposium. eds. A. Vargas, C. Breitenmoser, U. Breitenmoser, Fundacion Biodiversidad and IUCN Cat Specialist Group. Fundacion Biodiversidad, Spain. Wild, M. A., T. M. Shenk, and T. R. Spraker. 2006. Plague as a mortality factor in Canada lynx (Lynx canadensis) reintroduced to Colorado. Journal of Wildlife Diseases 42:646–650. Zahratka, J. L., and T. M. Shenk. 2008. Population estimates of snowshoe hares in the southern Rocky Mountains. Journal of Wildlife Management 72:906–912. Five additional papers are currently in review: Devineau, O., T. M. Shenk, P. F. Doherty, Jr., G. C. White, and R. H. Kahn. In review. Assessing release protocols used for the Canada lynx (Lynx Canadensis) reintroduction in Colorado: Recommendations for future efforts. Journal of Wildlife Management. Devineau, O., T. M. Shenk, P. F. Doherty, Jr., et al. In review. Modeling known-fate and nest survival data within the multistate framework: increased flexibility for telemetry studies. Journal of Applied Ecology. Wolfe, L. L., T. M. Shenk, B. Powell, and T. E. Rocke. In review. Safety of and serum antibody responses to a recombinant F1-V fusion protein vaccine intended to protect Canada lynx (Lynx Canadensis) from plague. Journal of Wildlife Diseases. Fanson, K., T. M. Shenk, et al. In review. Patterns of testicular activity in captive and wild Canada lynx. General and Comparative Endocrinology. Fanson, K., T. M. Shenk, et al. In review. Patterns of ovarian and luteal activity in captive and wild Canada lynx. General and Comparative Endocrinology. One paper is in the process of being submitted for publication and requires no additional work from CDOW personnel: Fanson, K., T. M. Shenk, et al. In prep. Patterns of stress physiology in reintroduced Canada lynx and implications for reintroduction success. General and Comparative Endocrinology. 12 �Six publications are currently in preparation and require the continued efforts of Tanya Shenk and/or Jake Ivan to complete: Theobald, D., and T. M. Shenk. In prep. Lynx habitat use at site-specific and landscape scales. Shenk, T. M. In prep. Lynx denning habitat and reproduction in Colorado. Ivan, J. S., G. C. White, and T. M. Shenk. In Prep. Using telemetry to correct for bias: an approach to estimating density from trapping grids. Ecology. Ivan, J. S., G. C. White, and T. M. Shenk. In Prep. Comparison of methods for estimating density from capture–recapture data. Journal of Applied Ecology. Ivan, J. S., G. C. White, and T. M. Shenk. In Prep. Density and demography of snowshoe hares in westcentral Colorado. Ecological Monographs. Ivan, J. S., G. C. White, and T. M. Shenk. In Prep. Daily and seasonal movements of snowshoe hares in west-central Colorado. Journal of Mammalogy. 13 �APPENDIX II PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2010-11 State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 4 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Lynx Conservation Estimating Potential Changes in Distribution of Canada Lynx in Colorado: Initial Implementation in the Core Lynx Research Area Principal Investigator Jacob S. Ivan, Wildlife Researcher, Mammals Research Tanya M. Shenk, Landscape Ecologist, NPS Cooperators Paul M. Lukacs, Biometrician, CDOW Grant J. Merrill, Research Associate, CSU Cooperative Research Unit Chad Bishop, Mammals Research Leader, CDOW STUDY PLAN APPROVAL Prepared by: Date: Submitted by; Date: Reviewed by: Date: Date: Date: Biometrician Review Date: Approved by: Date: _______________________________ Mammals Research Leader 14 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2010-11 Estimating the Extent, Stability and Potential Distribution of Canada Lynx (Lynx canadensis) in Colorado: initial implementation in the core lynx research area A Research Proposal Submitted By Jacob S. Ivan, Wildlife Researcher, Mammals Research Tanya M. Shenk, Landscape Ecologist, National Park Service A. Need: The Canada lynx (Lynx canadensis) occurs throughout the boreal forests of northern North America. While Canada and Alaska support healthy populations of the species, the lynx is currently listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.; U. S. Fish and Wildlife Service 2000) in the conterminous United States. Colorado represents the southern-most historical distribution of naturally occurring lynx, where the species occupied the higher elevation, montane forests in the state (U. S. Fish and Wildlife Service 2000). Thus, Colorado is included in the federal listing as lynx habitat. Lynx were extirpated or reduced to a few animals in Colorado, however, by the late 1970’s (U. S. Fish and Wildlife Service 2000), most likely due to multiple humanassociated factors, including predator control efforts such as poisoning and trapping (Meaney 2002). Given the isolation of and distance from Colorado to the nearest northern populations of lynx, the Colorado Division of Wildlife (CDOW) considered reintroduction as the only option to attempt to reestablish the species in the state. Therefore, a reintroduction effort was begun in 1997, with the first lynx released in Colorado in 1999. To date, 218 wild lynx were captured in Alaska or Canada and released in southwestern Colorado. The goal of the Colorado lynx reintroduction program is to establish a self-sustaining, viable population of lynx in this state. Evaluation of incremental achievements necessary for establishing viable populations is an interim method of assessing the success of the reintroduction effort. There were 7 critical criteria established for achieving a viable lynx population in Colorado: 1) development of release protocols that lead to a high initial post-release survival of reintroduced animals, 2) long-term survival of lynx in Colorado, 3) development of site fidelity by the lynx to areas supporting good habitat in densities sufficient to breed, 4) reintroduced lynx must breed, 5) breeding must lead to reproduction of surviving kittens 6) lynx born in Colorado must reach breeding age and reproduce successfully, and 7) recruitment must equal or be greater than mortality over an extended period of time. These criteria were evaluated incrementally over time to gauge whether the reintroduction effort was progressing toward success (Shenk and Kahn 2003). All seven criteria have now been met and a Canada lynx population currently exists in Colorado (Shenk and Kahn 2010). To document sustained viability of the Canada lynx population in Colorado, some form of long-term monitoring must be implemented. Lynx were released in a core reintroduction area in the San Juan Mountains of southwestern Colorado. It was hoped lynx would become established in this area and then disperse on their own throughout suitable habitat in the state. Research and monitoring efforts over the last 11 years, since the first lynx were released, have focused primarily on monitoring reintroduced animals through VHF and satellite telemetry and estimating demographic parameters of these animals (e.g., Devineau et al. 2010). However, as more of these animals become unavailable for monitoring due to failed telemetry collars, 15 �death, or movement out of state, it has become impossible to accurately evaluate the status of the lynx population in Colorado, including the Core Research Area. A minimally-invasive monitoring program is needed to estimate the distribution, stability, and persistence of lynx. Occupancy estimation, the use of presence/absence survey data to estimate the proportion of survey units occupied within a study area, is appropriate for such a program. In the past, biologists referred to presence/absence as present/not detected, because absence cannot be absolutely determined. This term, however, confuses the status of being present or not present with the activity of either detecting or not detecting an animal. This monitoring program proposed here adopts the term presence/absence with the argument that although absence cannot be determined, it can be estimated statistically using a known or estimated detection probability. The indicator used to determine the distribution of occurrence of lynx is Ψ, the proportion of primary sampling units (PSU’s) (MacKenzie et al. 2006) with lynx presence. A PSU is a square sampling unit of 75km2, the approximate mean size of a lynx winter home range as estimated by a 90% kernel utilization distribution (Shenk 2007). In order to design the most efficient statewide monitoring program, we first evaluated the detection probabilities and efficacy of 3 methods of detection (Shenk 2009) via survey work in areas where lynx were known to occur. The most efficient methods of detection were snow-tracking (daily detection probability = 0.70) and camera surveillance (daily detection probability = 0.085). Hair snares were found to be ineffective in detecting the presence of lynx (daily detection probability = 0). In addition to identifying purported lynx tracks, snow-tracking implemented at the maximum effort should also include backtracking until scat or hair samples can be collected. Such samples are used to validate that the discovered tracks were indeed lynx tracks. Furthermore, such an approach allows for individual identification (from scat only), which could be used to monitor individual movement patterns across PSU’s, reproduction, social structure and possibly apparent survival rates. A genetic library of most lynx released during the reintroduction program (some samples were missing) and most kittens found in Colorado (some samples were insufficient for individual identification) has been established and is housed with USGS Conservation Genetics Lab in Fort Collins, Colorado. This genetic library will be used to identify individuals from the scat samples collected during the monitoring program. Below we outline the objectives and approach for the estimating the distribution of lynx in the Core Research Area. Results from this study will enable us to design a larger-scale monitoring program to detect changes in lynx persistence and distribution throughout Colorado. The primary objectives of a statewide monitoring program would be to document the annual distribution of lynx throughout Colorado, the stability, growth or shrinkage of this distribution over time, and to identify potential areas lynx may occupy in the future A statewide monitoring program based on our pilot study (below) will not provide a means of estimating total population size in the state because detection of a lynx may represent a single territorial animal, a breeding pair or a family unit. To obtain a statewide lynx abundance estimate, further efforts would be needed to establish the actual or estimated number of lynx in a PSU. Furthermore, the occupancy estimation approach outlined below is not designed to provide information on reproductive success or to estimate survival. B. Objectives: The primary objectives of this study are to: 1. Estimate the distribution of lynx in the Core Research Area. 2. Further refine detection probabilities of snow-tracking and camera surveillance methods in detecting lynx. 2. Develop a standardized, valid monitoring protocol for estimating the distribution, stability and persistence of Canada lynx throughout Colorado. 16 �C. Expected Results or Benefits: The methodologies developed during this pilot study will be used to develop a valid, non-invasive or minimally invasive inventory and monitoring program to estimate the distribution of Canada lynx in Colorado. The monitoring program will provide information on the annual winter distribution, extent and habitat relationships of these parameters as well as their long-term trend which will be evaluated every 5 years. The protocols developed will be made available to any other agencies or entities that want to monitor lynx. The proposed methodology to estimate and monitor trends in lynx distribution throughout Colorado is designed to make use of technologies (e.g., genetic identification) reliant only on noninvasive or minimally invasive techniques. Such non-invasive techniques are widely desirable because they require minimal impact to the animals and because of their cost efficiencies. D. Approach The primary objective of the pilot study is to evaluate the efficacy of the proposed sampling techniques for detecting lynx presence. However, the pilot study will also include qualitative evaluation of all design methods that will be employed in a future, larger research area and statewide monitoring efforts, (i.e., the complete sampling frame). Sampling Frame and Primary Sampling Unit Selection The sampling frame will be the Core Research Area, a 20,684 km2 study area which included the core reintroduction area, release sites and surrounding high elevation sites (> 2,591 m). The area encompasses the southwest quadrant of Colorado and is bounded on the south by New Mexico, on the west by Utah, on the north by interstate highway 70, and on the east by the Sangre de Cristo Mountains (Figure 1). The sampling frame will be randomly overlayed with a contiguous grid of 75 km2 squares. The size of the square reflects a mean annual home range size of a reproducing lynx in Colorado (Shenk 2007) and is similar to home range estimates obtained for lynx in Montana (Squires and Laurion 1999). If a grid square meets the following criteria it will be identified as a PSU: 1. If ≥ 50% of the grid is located within the Core Research Area, 2. If ≥ 50 % of the grid contains conifer or montane/alpine habitat, as identified by the SWReGAP LandCover Dataset ( http://earth.gis.usu.edu/swgap/swregap_landcover_report.pdf) and 3. If ≥ 50 % of the grid is located on public land (tribal, NGO and city and county lands are considered private) as determined by COMaP (Theobald, D.M., G. Wilcox, S.E. Linn, N. Peterson, and M. Lineal. 2008. Colorado Ownership, Management, and Protection v7 database. Human Dimensions of Natural Resources and Natural Resource Ecology Lab, Colorado State University, Fort Collins, CO, www.nrel.colostate.edu/projects/comap). Each grid will be assigned a random number based on a spatially balanced randomized sample (RRQRR; Theobald et al. 2007) and then stratified by accessibility in winter (accessible or not accessible). An accessible grid is defined as one that can be easily and safely reached in winter by truck or snowmobile. The grids with the lowest 30 random numbers for each stratum will then be identified as the grids to be sampled for this study. Should a grid be found to have been placed in the wrong accessibility strata once approached in the field, its designation will be changed and the next lowest random numbered grid will replace it. The assumptions that must be met in estimating occupancy are 1) surveyed sites can be occupied by the species of interest throughout the duration of the study, with no sites becoming occupied or unoccupied during the survey period (i.e., the system is closed), 2) species are not falsely detected, but can remain undetected if present, and 3) species detection at a site is assumed to be independent of 17 �species detection at other sites (MacKenzie et al. 2006). For study, there will be 2 different methods of detection (snow-tracking and camera surveillance). Field Methods Temporal aspects of the sampling design In order to verify that the detection methods being evaluated in this pilot study are effective at detecting lynx when they are present, we need to conduct the study while we have active radio collars on lynx. Currently, we are continuing to monitor lynx with the Core Research Area for data on the demography and movement patterns of the reintroduced lynx. Thus, completing this study at the same time that active monitoring is being conducted in the research area eliminates the need for future radiocollaring efforts to conduct this study. Camera data collection will be conducted from September- June, although only photos obtained from October-March will be used in the analysis because this time period is when lynx typically maintain fidelity to a winter home range and when breeding occurs, the period of interest for document long-term persistence of lynx. All snow-tracking data will be collected from January – March, meeting the period of interest for occupancy. Lynx Detection Data Collection Two methods will be used to document the presence of lynx, based on winter accessibility of the PSU. These methods include 1) documenting the presence of lynx tracks in the snow coupled with a DNA sample collection (hair or scat found through snow-tracking) in PSU’s that are accessible in winter or 2) a photograph of a lynx captured by a surveillance camera in PSU’s that are inaccessible in winter. Camera work or snow tracking will be focused in areas of a selected PSU that a lynx would most likely use. Based on lynx habitat use in Colorado (Shenk 2005), focus areas will include mature Engelmann spruce-subalpine fir forest stands with 42-65% canopy cover and 15-20% conifer understory cover, mean slopes of 16° and elevations above 2591 m. In addition, selection of specific camera detection stations will be based on natural travel routes or the presence of lynx sign (i.e., tracks or scat). Chances of detecting lynx at these locations will be further enhanced by placing scent and visual lures at these sites. Other feline species may be attracted to these same lures, however, the probability will be low as the study will be conducted in winter and the deep snows at these elevations should preclude species such as mountain lion (Puma concolor) and bobcat (Lynx rufus) from using these areas. Establishing Detection Stations & Travel Routes To eliminate bias, any known lynx locations in the selected PSU’s will be withheld from field technicians as they select camera station locations and snowmobile/snowshoeing routes. Field personnel will, however, be provided commonly available information to select camera locations and survey routes that are feasible and most likely areas to detect lynx within a PSU (see above). Snow-Tracking Searches for tracks will be attempted by snowshoeing, driving, or snowmobiling in the PSU once enough snow has accumulated. Once tracks are observed, personnel will follow the tracks for up to 1km or until either lynx hair or scat are found and collected. All hair found in day beds or a single scat will constitute a sample. Because lynx are a federally listed species, which can result in regulatory protection, we will eliminate doubt about the presence of lynx by submitting hair or scat sampled to a conservation genetics lab to confirm species identification (see McKelvey et al. 2006). All hair and fecal samples will be submitted to the USGS Conservation Genetics Lab in Fort Collins, Colorado for identification to species and individual, if possible. The distance a track is followed will be limited to 1 km to increase efficiency in lynx detection within the PSU (i.e., it will be assumed it is quicker to find a new lynx track to follow to locate hair or scat than to pursue a single track for more than 1 km; see McKelvey et al. 2006). To evaluate the efficiency of this method and better estimate detection probability, we will record 18 �the total distance searched before a track is encountered for each day of survey effort, along with the total distance each lynx track is followed to collect a scat or hair sample. All selected accessible PSU’s will be snow-tracked for a maximum of 3 days. However, once a track has been found in a PSU detection efforts will stop. Snow-tracking will be conducted in a minimum of 25 accessible PSU’s. If time permits, up to 30 accessible PSU’s will be surveyed. Camera Traps Digital infrared surveillance cameras (RECONYX RapidFireTM Professional PC85) will be placed at 4 randomly selected detection stations among those that appear the most likely places where lynx would encounter them within the PSU, as defined above. Commercial scent lures and visual lures (e.g., CD’s, waterfowl wings) will be used at each camera detection station to enhance the probability of drawing a lynx into the station. Cameras will be strategically placed at microsites least likely to be effected by accumulating snow (e.g., we will use large trees with broad canopies that will form “tree wells” during winter). Cameras will be attached to a tree with a Master Lock TM PythonTM cable lock and powered by 12 AA lithium batteries which should ensure functionality for the duration of the study. Cameras will be placed in a minimum of 25 PSU’s. If time permits, up to 30 PSU’s will be surveyed. Cameras will be collected in May and June when access to the PSU’s are feasible. Only photos of lynx taken from October 1 – March 31 will be considered a detection. Data Analysis We will estimate the occupancy of lynx within the Core research Area. Further evaluation of each of the detection methods will be completed to refine detection probabilities (p) using data from the continued monitoring of lynx with active radio collars to document presence of lynx in some of the sampled PSU’s. A final monitoring protocol will be developed and published for use on a statewide or rangewide basis. Project Schedule Aug. 2010 • Complete sampling frame and selection of primary sampling units. • Purchase and test equipment. • Hire fall field crews. Sep. – Oct 2010 • Set up camera detection stations • Hire winter field crews. Jan.–Mar. 2011 • Conduct lynx snow-tracking surveys. • Process and submit all genetic samples collected during surveys to the USGS Conservation genetics Lab. May-Jun 2011 • Collect cameras. • Data entry. 19 �Jul-Sep 2011 • Data analyses and complete report. Personnel: Project Co-Leader: Jake Ivan, Wildlife Researcher, CDOW Project Co-Leader: Tanya Shenk, Landscape Ecologist, NPS Responsibilities: Design study, work with research associate to implement and complete field work and data entry, complete analysis, write report. Crew Leader: Responsibilities: Assist in study design and selection of PSU’s, supervise field technicians, complete all data entry, and perform other duties associated with the post-release monitoring program and the reproduction study. Field Technicians Responsibilities: Establish camera detection stations, conduct all snow-tracking and collect cameras. Data Analysis: Jake Ivan, Wildlife Researcher, CDOW Tanya Shenk, Landscape Ecologist, NPS Paul Lukacs, Biometrician CDOW Gary White, Professor Emeritus, CSU Paul Doherty, Associate Professor, CSU Estimated Budget: September 2010 – June 2011 Salary (Tech III) Salary (6 Field Technicians Fall, Tech I) Salary (6 Field Technicians, Winter, Tech II) Salary (4 Field Technicians Spring, Tech I) Misc. Supplies/Operating Equipment Repair, maintenance (snowmobiles) Detection cameras (30 @$1000 each) Processing of genetic samples collected during monitoring Vehicles (6) $ 43,500 $ 32,500 $ 35,000 $ 14,000 $ 8,000 $ 9000 $ 30,000 $ 2,000 $ 8,000 Total $182,000.00 E. Location: Southwestern and central Colorado is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce-subalpine fir is the most widely distributed coniferous forest type at elevations most typically used by lynx (2591-3353 m). The Core Reintroduction Research Area is defined as areas >2591 m in elevation within the area bounded by the New Mexico state line to the south, Taylor Mesa to the west and Monarch Pass on the north and east (Figure 1). Project headquarters will at the Fort Collins CDOW Research Center. 20 �F. Literature Cited: Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524-531. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Elsevier Academic Press. Oxford, UK. McKelvey, K. S., J. von Kienast; K.B. Aubry; G. M. Koehler; B. T. Maletzke; J. R. Squires; E. L. Lindquist; S. Loch; M. K. Schwartz. 2006. DNA analysis of hair and scat collected along snow tracks to document the presence of Canada lynx. Wildlife Society Bulletin 34: 451-455. Meaney C. 2002. A review of Canada lynx (Lynx canadensis) abundance records from Colorado in the first quarter of the 20Th century. Colorado Department of Transportation Report. Shenk, T. M. 2005. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado __________. 2009. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado Shenk and Kahn 2003. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado Shenk and Kahn 2010. The Colorado lynx reintroduction program. Report to the Colorado Division of Wildlife, Fort Collins, Colorado. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. Theobald, D.M., D.L. Stevens, Jr., D. White, N.S. Urquhart, A.R. Olsen, and J.B. Norman. 2007. Using GIS to generate spatially balanced random survey designs for natural resource applications. Environmental Management 40(1): 134-146. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. 21 �Figure 1. Study area depicting the Core Research Area, Lynx-established Core Area and relative lynx use (red is high intensity use, yellow is low intensity use). 22 �APPENDIX III Colorado Division of Wildlife August 2009 WILDLIFE RESEARCH REPORT State of __________Colorado_________ Cost Center_______3430_____________ Work Package_____0670_____________ Task No.___________2______________ ________Division of Wildlife______________ ________Mammals Research______________ ________Lynx Reintroduction_____________ ___ Density, Demography, and Seasonal __ Movements of Snowshoe Hare in Colorado ___ Federal Aid Project: N/A : Period Covered: July 1, 2009- June 30, 2010 Author: J. S. Ivan, Ph.D. Candidate, Colorado State University Personnel: Dr. T. Shenk of CDOW and Dr. G. C. White of Colorado State University. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT A program to reintroduce the threatened Canada lynx (Lynx canadensis) into Colorado was initiated in 1997. Analysis of scat collected from winter snow tracking indicates that snowshoe hares (Lepus americanus) comprise 65–90% of the winter diet of reintroduced lynx in most winters. Thus, existence of lynx in Colorado and success of the reintroduction hinge at least partly on maintaining adequate and widespread hare populations. Beginning in July 2006, I initiated a study to assess the relative value of 3 stand types for providing hare habitat in Colorado. These types include mature, uneven-aged spruce/fir forests, sapling lodgepole pine forests (“small lodgepole”), and pole-sized lodgepole pine forests (“medium lodgepole”). Estimates and comparisons of survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each stand will provide the metrics for assessing these stands. Snowshoe hare densities on the study area are low compared to densities reported elsewhere. Within the study area, hare densities during summer were generally highest in small lodgepole stands, followed by mature spruce/fir and medium lodgepole, respectively. Absolute hare densities declined considerably in summer 2007 and rebounded only slightly during summer 2008. Hare density in small and medium lodgepole stands equalized during winters. However, as with summer, overall density was much lower during the second winter compared to the first and rebounded somewhat during the last winter. Hare survival from summer to winter was relatively high whereas winter to summer survival is quite low. Survival does not appear to differ between stand types or years, although a much more thorough analysis that will include known-fate telemetry data is forthcoming. This combined analysis will provide a final winter-summer estimate, will bring much more information to bear on the estimation process, and should increase precision of all estimates by a fair amount. 23 �WILDIFE RESEARCH REPORT DENSITY AND SURVIVAL OF SNOWSHOE HARES IN TAYLOR PARK AND PITKIN JACOB S. IVAN P. N. OBJECTIVE Assess the relative value of 3 stand types (mature spruce/fir, sapling lodgepole, pole-sized lodgepole) that purportedly provide high quality hare habitat by estimating survival, recruitment, finite population growth rate, and maximum (late summer) and minimum (late winter) snowshoe hare densities for each type. SEGMENT OBJECTIVES 1. Complete mark-recapture work across all replicate stands during late summer (mid-July through midSeptember) and winter (mid-January through March). 2. Obtain daily telemetry locations on radio-tagged hares for 10 days immediately after capture periods, as well as monthly between primary trapping sessions. 3. Locate, retrieve, and refurbish radio tags as mortalities occur. SUMMARY Snowshoe hares (Lepus americanus), their famous 10-year population cycle, and close association with Canada lynx (Lynx canadensis) have been well-studied in boreal Canada for decades. Snowshoe hare range, however, extends south into the Sierra Nevada, Southern Rockies, upper Lake States, and Appalachian Mountains. Ecology of snowshoe hares in these more southerly regions is not as well understood, though hare research in the U.S. Rocky Mountains has accelerated over the past decade. Through this recent work, biologists have identified stands of young, densely-stocked conifers and those of mature, uneven-aged conifers as primary hare habitat in the region. Both stand types are characterized by dense understory vegetation that provides both browse and protection from elements and predators. From 1999 to 2006, Canada lynx were recently reintroduced into Colorado in an effort to restore a viable population to the southern portion of their former range. Snow tracking of released individuals and their progeny indicated that the majority of lynx winter diet in Colorado was comprised of snowshoe hares. Thus, long−term success of the lynx reintroduction effort hinges, at least partly, on maintaining adequate and widespread populations of snowshoe hares in the state. To improve understanding of snowshoe hare ecology in the southern portion of their range, and enhance the ability of agency personnel to manage subalpine landscapes for snowshoe hares and lynx in Colorado, I conducted an observational study to evaluate purported primary hare habitat in the state. Specifically, I estimated snowshoe hare density, survival, recruitment, and movement indices in mature, uneven-aged spruce/fir and 2 classes of young, even-aged lodgepole pine: 1) “small” lodgepole stands, which were clear cut 20−25 years prior to this study and had regenerated into densely stocked stands trees 2.54−12.69 cm in diameter, and 2) “medium” lodgpole pine stands (tree diameter = 12.70−22.85 cm) which were clear cut 40-60 years prior to this study and pre-commercially thinned ~20 years prior. I used a combination of mark-recapture and radio telemetry to estimate parameters. I sampled during both summer and winter to cover the range of annual variation in parameters. 24 �Animal density is one of the most common and fundamental parameters in wildlife ecology and was the first metric I used to evaluate the stand types. However, density can be difficult to estimate from mark-recapture data because animals can move on and off of a trapping grid during a sampling session (i.e., lack of geographic closure), which biases abundance estimates and makes them difficult convert to density. Before estimating snowshoe hare density, I developed a density estimator that uses ancillary radio telemetry locations, in addition to mark-recapture information, to account for lack of geographic closure resulting in relatively unbiased estimates of density. I derived the variance for this estimator, showed how individual covariates can be used to improve its performance, and provided an example using a subset of my snowshoe hare data. Next, I completed a series of simulations to test the performance of this “telemetry” estimator over a range of sampling parameters (i.e., capture probabilities, sampling occasions, densities, and home range configurations) likely to be encountered in the field. I also compared the percent relative bias of the telemetry estimator to two other commonly used, contemporary estimators: spatial explicit capturerecapture (SECR), and mean maximum distance moved (MMDM). The telemetry estimator performed best over most combinations of sampling parameters tested, but was inferior to SECR at low capture probabilities. The telemetry estimator was unaffected by home range configuration, whereas performance of SECR and MMDM was dependent on home range shape. Density is an important metric of habitat quality, but it can be misleading as some habitats with high animal density may function as population sinks. A complete assessment of habitat quality requires estimation of habitat-specific demographic rates in addition to density. I used the telemetry estimator to estimate snowshoe hare densities in each stand type during summer and winter, 2006-2009. I then combined mark-recapture and telemetry data to estimate survival via the Barker robust design model as implemented in Program MARK. Finally, I used age- and habitat-specific density and survival estimates to estimate recruitment in each stand type. Snowshoe hare densities were generally <1 hare/ha. During summer, hare densities were highest in small lodgepole pine, lowest in medium lodgepole pine, and intermediate in spruce/fir. During winter, densities became more similar between the 3 stand types. Annual survival of hares varied from 0.11 to 0.20. Survival tended to be higher during summer-winter intervals than during winter-summer, and higher in spruce/fir compared to the 2 lodgepole stands. Recruitment of juvenile hares occurred during all 3 summers in small lodgepole stands, 2 of 3 summers in spruce/fir stands, and in only 1 of 3 summers in medium lodgepole. In addition to density and demography, movement is an informative aspect of animal ecology as well. Timing, extent, and frequency of movements can reflect predation pressure, food scarcity/abundance, availability of mates, or seasonal changes in any of these parameters. I used telemetry data to assess movement patterns of snowshoe hares at 3 scales (daily, within-season, betweenseason) in all 3 stand types. Hares in mature, uneven-aged spruce/fir stands made daily movements at the same scale as within-season and between-season movements in that habitat type, indicating they routinely traversed their entire home range over the course of a day. Conversely, hares in small and medium lodgepole stands appeared to use their home range in a more stepwise fashion (especially hares in medium stands), making smaller movements on a daily basis, but using larger areas over longer time frames. Additionally, hares in both lodgepole stands made large movements between seasons, possibly reflecting the patchy distribution of lodgepole landscapes in the study area and the variable value of patches as mediated by snow depth. In summary, snowshoe hare density, survival, and recruitment were relatively low in medium lodgepole stands compared to spruce/fir or small lodgepole. Furthermore, hares in medium lodgepole stands made relatively large movements which may reflect poorer quality habitat. Thus, while hares occur in these stands, they do not appear to be capable self-sustaining hare populations and are probably 25 �less important than mature spruce/fir and small lodgepole. Management for snowshoe hares (and lynx) in central Colorado should focus on maintaining the latter. Given the permanent nature of spruce/fir compared to small lodgepole, and the fact that such stands cover considerably more area, mature spruce/fir may be the most valuable stand type for snowshoe hares the state. 26 �Colorado Division of Wildlife July 2009 – June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3420 0663 1 Federal Aid Project No. W-185-R : : : : Division of Wildlife Spatial analysis Deer Conservation Mule Deer Body Condition model Period Covered: July 1, 2009 - June 30, 2010 Author: M.B. Rice and K. Searle Personnel: C. Anderson, C. Bishop All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Understanding the ways that resource heterogeneity shapes the performance of individuals and the dynamics of populations is a central challenge in contemporary ecology. Emerging evidence shows that herbivores track heterogeneity in nutritional quality of vegetation by responding to phenological differences in plants, differences that result from spatial and temporal variation in conditions favoring plant growth. The objective of this study will quantify the benefits mule deer accrue from accessing habitats with asynchronous plant phenology. To examine evidence for these hypotheses we used path analysis to examine links between variation in body condition (percent fat) of adult female mule deer in western Colorado and plant phenology indices and climate. Path analysis can be used to examine both the direct (physiological) and indirect (via plant phenology) effects of climate on ungulate body condition in this population, assuming linear relationships among predictor and response variables. We implemented the analysis within the hierarchical Bayesian framework, which allowed us to separate out and properly account for different sources of uncertainty in the data and process models. Significant effects of climate and topographical variables on the slope of vegetation green-up were found, although they were not consistent across years for some effects. The only year in which the slope of vegetation green-up had a significant, and negative, effect on mule deer percent bodyfat was 2008. Process variance was lower for the NDVI submodel than for the percent fat submodel, indicating that the percent fat path equation accounted for less of the important underlying processes. In conclusion, spring precipitation seems to play the greatest role in determining winter body condition of mule deer in this study area, having a positive effect on percent bodyfat that is mediated via its effect on plant phenology, acting to decrease the slope of the green-up in spring, thereby prolonging the period of availability of high quality forage. This finding does, however, need to be validated with more years of data with sufficient numbers of animals for analysis, and with direct assessments of spring precipitation on the quality of forage available to animals in different home ranges. 27 �WILDLIFE RESEARCH REPORT MULE DEER BODY CONDITION DATA MINDY B. RICE, KATE SEARLE, CHUCK ANDERSON, AND CHAD BISHOP P. N. OBJECTIVE The objective of this study will quantify the benefits mule deer accrue from accessing habitats with asynchronous plant phenology. Using data on the winter body condition (percent fat) of adult mule deer in western Colorado and remotely-sensed plant phenology (normalized difference vegetation index, NDVI), we will evaluate the contribution of asynchronous pulses of forage emergence and growth on individual mule deer performance. SEGMENT OBJECTIVES The spatially and temporally explicit NDVI data will be used to derive indices of vegetation phenology in home ranges of individual mule deer. These indices will be used to predict observed variation in individual adult mule deer winter body condition. We hypothesize that: 1. Individuals inhabiting ranges with more asynchronous phenology will have prolonged access to high quality forage and have better winter body condition than individuals inhabiting ranges with more synchronous phenology. 2. Individuals inhabiting ranges with shorter ‘green-up’ periods will suffer from a compression in the time period over which high quality forage is available and have poorer body condition than individuals inhabiting ranges with more prolonged green-up periods. We also expect that mean winter body condition of all animals will be lower in years with shorter green-up periods than in years with longer green-up periods. 3. Winter body condition will be more strongly influenced by temporal variation in plant quality (coefficient of variation, cv, of the temporal trend in mean NDVI in an individual’s home range) than by spatial variation in plant quality (cv of NDVI across an individual’s home range at a single point in time). This is because greater temporal variation in plant quality (as indexed by NDVI) prolongs the time period over which individuals may maximize diet quality, which we expect to have a greater relative influence on body condition than spatial variation at a single point in time. INTRODUCTION Understanding the ways that resource heterogeneity shapes the performance of individuals and the dynamics of populations is a central challenge in contemporary ecology. Emerging evidence shows that herbivores track heterogeneity in nutritional quality of vegetation by responding to phenological differences in plants, differences that result from spatial and temporal variation in conditions favoring plant growth. The ability of landscapes to support herbivores is ultimately limited by the total amount of aboveground net-primary production (ANPP) available for consumption (Cebrian and Lartigue 2004; McNaughton et al. 1989). However, theory predicts that when spatial variation in temperature, nutrients, or moisture results in spatially asynchronous pulses of plant growth, herbivores are able to prolong the period during which they have access to forage of peak nutritional value. Emerging evidence suggests that limits set by ANPP can be modified by the spatial pattern and timing of plant growth. In particular, there is evidence that heterogeneity in plant communities expressed over space, particularly heterogeneity that induces variation in time by influencing plant phenology, offers fundamentally important nutritional 28 �benefits to foraging herbivores, benefits that enhance the performance of their populations. This finding means that access to heterogeneity can be a critically important feature of habitats for large, mobile herbivores (Fryxell et al. 2005; Hobbs et al. 2008; Owen-Smith 2004). The interactions between spatial and temporal heterogeneity and ungulate performance and population dynamics will mediate the response of Colorado ungulate populations to environmental change, such as land-use and climate change. Understanding the mechanisms underlying these interactions is, therefore, of great importance for prediction and management of Colorado ungulate populations in the face of environmental change. Climate change is one of the dominant threats to ecosystems around the world. Large herbivores such as mule deer have profound impacts on ecosystem structure and function, and understanding the ways in which their behavior, individual performance and population dynamics are likely to change under future climate scenarios is crucial for effective management of Colorado ecosystems. By mechanistically linking changes in climate and variation in the spatial and temporal patterns of plant phenology across landscapes with the body condition of mule deer, we will be able to make some inferences as to climate change on this important species. Secondly, as more oil and gas development occurs, there is a growing need to assess the effect of fragmentation on ungulate species. The intrusion of roads and drilling platforms in wildlife habitat has impacts on ungulate behavior. Sawyer et al. (2006) demonstrated that winter habitat selection in mule deer was altered by well pads and road development in western Wyoming; animals avoided areas up to 2.7-3.7km around well pads. Moreover, these changes in habitat use were immediate and did not decline over the 3 year study, rather mule deer selected for areas further away as development progressed (Sawyer et al. 2006). Rost & Bailey (1979) showed that mule deer avoided areas within 200m of a road. By applying an understanding of the likely implications of different development scenarios for ungulate movement and foraging patterns, we will be able to examine the effect of this development on mule deer body condition, as mediated by access to resource variation. By combining remotely accessed data such as NDVI with measurements of mule deer body condition, we will model changes in habitat quality over time and space relative to resource heterogeneity. STUDY AREA AND DATA SOURCES Initial deer body condition data is from research conducted in southwest Colorado on the southern half of the Uncompahgre Plateau and in the adjacent San Juan Mountains by Chad Bishop of the Colorado Division of Wildlife (Bishop et al. 2009). Methods outlined for the measurement of body fat is also given in Bishop et al. 2009. All deer that were supplemented in the Bishop et al. 2009 study were taken out of our analysis so we only used the control deer. The initial model will have 18 deer from 2002, 26 deer from 2003, and 30 deer from 2004 including 19 of those deer with multiple years of body condition data. Extension of this data set would include body condition data that currently exists in the Piceance region of northwest Colorado from Chuck Anderson of the Colorado Division of Wildlife. There is additional individual deer body condition data from a study in the Uncompahgre Plateau by Eric Bergman that may be included in future model development. In addition, the use of Chuck Anderson’s data from body condition in the winter of 2009 can be used as a validation data set on the development models. 29 �METHODS To examine evidence for these hypotheses we used path analysis (Shipley 2002) to examine links between variation in body condition (percent fat) of adult female mule deer in western Colorado and plant phenology indices and climate. Path analysis can be used to examine both the direct (physiological) and indirect (via plant phenology) effects of climate on ungulate body condition in this population, assuming linear relationships among predictor and response variables. We implemented the analysis within the hierarchical Bayesian framework, which allowed us to separate out and properly account for different sources of uncertainty in the data and process models. Quantifying these relationships will give insight into the likely impacts of future changes in climate on mule deer performance in this region of Colorado. Data Percent bodyfat and age Percent body fat and age data were collected over 5 non-consecutive years (Table 1). To ensure independence of samples, individuals for which there were more than one year of measurement had the second year dropped from the analysis (n=5). Percent fat measurements were taken following the rLIVINDEX method (Cook et al.2007). Home range calculations All individual deer locations were grouped by individuals and the centroid of their locations were found in ArcMap. Distances moved by each individual deer were calculated and we determined that 21 km would encompass a buffer that would represent movements by each deer. The 21 km buffer was applied to each individual deer and variables were extracted for each deer. Plant phenology We used NDVI as a proxy for vegetation phenology (greenness), which has been used extensively as a surrogate for vegetation dynamics (Bellis et al. 2008, Boone et al. 2006, Morisette et al. 2006). Data were collected from the Global Land Cover Facility (GLCF) Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day composite imagery (NASA 2000-2004). MODIS uses NASA’s terra and aqua satellites with 16 day orbits, a 2330 km swath, and a 250 m resolution. The Normalized Difference Vegetation Index (NDVI) is a ratio of red and near infrared reflectance using bands 1 and 2 of the MODIS sensors (NDVI = (NIR – RED)/(NIR + RED) where NIR is the near infrared light reflected by vegetation, and RED is the red visible light reflected by vegetation). NDVI values range from -0.25 to 1 where negative values indicate sparse green vegetation. We created several different indices from the satellite-derived NDVI measurements to test our hypotheses: Slope of NDVI during vegetation green-up (‘slope’): the slope between the mean NDVI values measured at defined dates for each individual’s home range. The dates defining the start and end of the green-up period were determined visually from plots of mean NDVI curves for all individuals in each year (green-up period April 4th to June 25th, Figure 1). This is a measure of the speed of vegetation greenup in the Spring – i.e., how elongated or compressed is the phenological development of plants in each individual’s home range. We predict that individuals inhabiting home ranges with shallower green-up slopes, therefore experiencing elongated green-up periods where the vegetation is at peak quality, will have higher body condition than those individuals inhabiting home ranges with steeper green-up slopes. 30 �Onset of vegetation emergence: the mean value of NDVI for each individual’s home range per year on April 4th. This date was determined by visual inspection of mean NDVI curves for all individuals in each year to capture the start of the green-up period (Figure 1). We predict that individuals inhabiting home ranges with an earlier vegetation onset (i.e., a higher value of NDVI on April 4th) will have higher body condition than individuals occupying home ranges with a later vegetation onset (i.e., a lower value of NDVI on April 4th). This is because individuals in home ranges with earlier vegetation onset will have a prolonged period of access to forage at peak nutritional value. Climate and topographic variables Precipitation and temperature data were collected from the prism climate group using their parameter-elevation regressions on independent slopes (PRISM) precipitation, minimum temperature, and maximum temperature layers (Daly et al. 1997). The resolution for all climatic variables was 4 km. We converted the precipitation data from hundredths of mm to inches. We converted the temperature layers from hundredths of celsius to fahrenheit. Both precipitation and temperature data were obtained from the previous years of deer body condition data. Using this data we calculated the sum of precipitation over the green-up period (beginning of April to end of June, hereafter referred to as ‘spring precipitation’), and the sum of precipitation over the previous winter (beginning of January to end of March, hereafter referred to as ‘winter precipitation’). We calculated the average minimum temperature over the current winter months (beginning of October to end of December). Elevation and aspect were collected from the USGS Digital Elevation Model (DEM) with a 30 m resolution. Elevation units were in meters and aspect was in degree categories based on the following: North (0-22.5), Northeast (22.5-67.5), East (67.5-112.5), SE(112.5-157.5), South (157.5-202.5), Southwest (202.5-247.5), West (247.5-292.5), Northwest (292.5-337.5), and North (337.5-360). All data were resampled in ArcGIS to the broadest resolution which corresponded to the climate variables at 4 km. Temperature, precipitation, elevation, slope, and NDVI were extracted using spatial analyst in Arc GIS to each individual deer’s buffer. Modeling approach We used hierarchical Bayesian path analysis to examine the direct and indirect effects of environmental variables on mule deer body condition. Path analysis requires hypothesizing causal inferential paths and testing the significance of these paths both directly and indirectly through a mediating variable. When using standard statistical methods for path analysis, variables are treated as having normal distributions and paths are estimated using least squares regression equations. However, when data are non-normally distributed, and variables are observed with error, estimation can be very difficult. Moreover, ignoring measurement error can lead to biased estimates of the regression parameters. These difficulties can be handled by employing a fully Bayesian approach. We developed a model quantifying the direct effects of plant phenology (defined by the NDVI indices outlined above) on mule deer body condition, the direct effects of climate on mule deer body condition, and the indirect effects of climate, via plant phenology, on mule deer body condition. Based on our understanding of the system, we surmised a mechanistic model for how climate and plant phenology affect individual body condition of mule deer (Figure 2). We specified relationships among environmental variables (climate, topography and NDVI metrics), animal characteristics (age at capture), and body condition (percent fat) of adult female mule deer across 5 separate years (2001, 2002, 2003, 2008, 2009). Linear models were used throughout. Plant phenology (NDVI indices) was assumed to be functions of 31 �climate and topographic variables, but uncertainties in these relationships were taken into account (Fig. 2). To implement this model within a hierarchical Bayesian framework, we specified three separate model parts; the data model, process model, and prior distributions of parameters. Data Model The data model is the likelihood linking the data to the model parameters. We have two data models, one linking observations of NDVI indices to climatic and topographic variables, and one linking observations of percent body fat to plant phenology (NDVI indices) and animal characteristics (age at capture). Both NDVI indices and percent body fat were logit transformed, such that logit(yNDVI i ,t ) ~ normal( µ NDVI i ,t , σ obs1 ) and logit(yPFi ,t ) ~ normal( µ PFi ,t , σ obs 2 ) where yNDVI i ,t is the observation for the NDVI index for the ith deer in the tth year, µ NDVI i ,t is the model prediction for the NDVI index for the ith deer in the tth year, σ obs1 is the estimate of observation error across all NDVI index observations, yPFi ,t is the observation for the percent fat for the ith deer in the tth year, µ PFi ,t is the model prediction for the percent fat for the ith deer in the tth year, and σ obs 2 is the estimate of observation error across all measurements of percent fat. Observations of percent fat for individual deer are assumed to be independent in this analysis. Radio-collared deer sometimes foraged together in the same groups; however, group dynamics were highly variable, suggesting any violations to the independence assumption were minor. Process Model The process component of the model relates the model predictions for NDVI indices and percent fat to the parameters of the model. As such, it derives the probability of the model prediction for each NDVI index for the ith deer in the nth year, µ NDVI i ,t , given the respective process model parameters, and the process variance estimate for unaccounted variation in the modeled NDVI process, σ proc1 : P ( µ NDVI i ,t | at , b 1t , b2t , b3t , b4t , σ proc1 ) , and the probability of the model prediction for percent fat for the ith deer in the nth year, µ PFi ,t , given the respective process model parameters, and the process variance estimate for unaccounted variation in the modeled percent fat process, σ proc 2 : P ( µ PFi ,t | ct , d1t , d 2t , d3t , d 4t , σ proc 2 ) . These probabilities are defined by two path equations: µ NDVI = a + b1sppt + b2 elev + b3 aspect + b4 wppt µ PF = c + b1µ NDVI + b2 wtemp + b3 wppt + b4 age 32 �where sppt is spring precipitation, elev is elevation, wppt is winter precipitation, and wtemp is winter temperature. Prior distributions Because our analysis is fully Bayesian, we specify prior distributions for all model parameters in the hierarchy. For this model, because all input variables (climate, topography and age) were standardized for the path analysis, all prior distributions were assumed to be normally distributed and uninformative (all parameters ~normal(0, 1.0E-6)). Because the data for NDVI indices and percent fat were logit transformed, these were also assumed to be normally distributed, and uninformative uniform priors were used for process variance and observation error for both the NDVI data model and percent fat data model, σ obs1 , σ obs 2 , σ proc1 , σ proc1 ~ uniform(0,1) . All models were fit using WinBUGS (Spiegelhalter et al. 1999) software and a Marcov Chain Monte-Carlo (MCMC) procedure for each model run for 1,000,000 iterations after an intial burn-in of 500,000 iterations to ensure convergence of all model parameters. Convergence diagnostics and autocorrelation statistics were used to assess the mixing of three MCMC chains per model, and to assess the MCMC sampling quality for each parameter. The resulting fully hierarchical Bayesian model is, therefore, specified by P(θ data , θ process , µ | y ) ∝ P ( y | θ data , µ ) P ( µ | θ process ) P(θ data ) P(θ process ) where : θ data includes the parameters in the data model and parameters for observation error θ process includes the parameters in the process model and parameters for process variance µ are the predictions of the process model y are the data 33 �Path Analysis Model, including random effect for year: σ obs 2 yPFi,t Data model for % fat µ PFi,t Process model for % fat yNDVI i,t σ proc2 µ NDVI i,t σ proc1 Data model for NDVI Process model for NDVI ct , d1,t , d2,t , d3,t , d4,t at ,b1,t ,b 2,t ,b3,t ,b4,t ηc ηd1 ηd 2 ηd 3 ηd 4 ηa ηb1 ηb2 ηb 3 ηb 4 σ obs1 Parameter models Hyperparameter models And the full model is specified as P(σ obs1 , σ obs 2 , σ proc1 , σ proc 2 , a, b 1 , b2 , b3 , b4 , c, d1 , d 2 , d3 , d 4 , µ NDVI i , µ PFi | yNDVI i , yPFi ) ∝ 5 n ∏ ∏ P( yNDVI | µ NDVI , σ i ,t =t 1 =i 1 5 i ,t ) n ∏ ∏ P( yPF | µ PF , σ i ,t =t 1 =i 1 5 obs1 i ,t obs 2 ) n ∏ ∏ P(µ NDVI | a , b , b , b , b , σ i ,t =t 1 =i 1 5 t 1t 2t 3t 4t proc1 ) n ∏ ∏ P(µ PF | c , d , d , d , d , σ i ,t =t 1 =i 1 1t t 2t 3t 4t proc 2 ) 5 ∏ P(a ) P(b ) P(b ) P(b ) P(b ) t =1 t 1t 2t 3t 4t 5 ∏ P (c ) P ( d ) P ( d ) P ( d ) P ( d ) t =1 t 1t 2t 3t 4t P (η a ) P(η b1 ) P(η b2 ) P(η b3 ) P(η b4 ) P(η c) P(η d1 ) P(η d 2 ) P(η d3 ) P(η d 4 ) P(σ obs1 ) P(bσ obs 2 ) P(σ proc1 ) P(σ proc 2 ) All climate, topographic and age variables were standardized prior to analysis. We used a logit transform on the observed values for each NDVI metric and percent fat. 34 �Data simulation and initial model testing Prior to running each developed model on actual data, models were tested on realistically simulated data to test their ability to converge on reasonable parameter estimates. All models performed well in simulations, converging on known parameter estimates such that 95% credible intervals for each parameter contained the true, known value. RESULTS Model convergence Models converged satisfactorily on posterior distributions for model parameters (Tables 2 and 3). Model convergence for the ‘slope’ NDVI metric was good, producing a multivariate scale reduction factor of 1.12 (Gelman and Rubin 1992). Convergence for individual parameters was assessed and found to be satisfactory (all point estimates <1.20; 97.5% quantile <1.5 scale reduction factor; Table 4) for all parameters in all years. All posterior distributions were approximately normal, and autocorrelation in the MCMC chains was not a factor after the initial burn-in period. Similarly, model convergence for the ‘onset’ NDVI metric was satisfactory, with a multivariate scale reduction factor of 1.35. Convergence for individual parameters was good; point estimates for all parameters were <1.1 with the exception of year 2002, in which point estimates for three parameters (NDVI model intercept, effect of spring precipitation on onset, and effect of elevation on onset) were approximately 1.5 (Table 3). Correspondingly, 97.5% quantiles for these three parameters in year 2002 were approximately 2. This was due to autocorrelation in the MCMC chain samples which persisted for >500,000 iterations. Autocorrelation for all other parameters in other years disappeared within the burn-in period. All posterior distributions were approximately normal. Links between climate, plant phenology and mule deer percent bodyfat Significant effects of climate and topographical variables on the slope of vegetation green-up were found (Table 2), although they were not consistent across years for some effects. For instance, spring precipitation had a negative effect on the slope of vegetation green-up in 2008, but a positive effect in 2009 (Table 2). Similarly, winter precipitation negatively affected the slope of vegetation green-up in three years (2003, 2004, 2009), but had a positive impact in 2008 (Table 2). Elevation (years 2002, 2008, 2009) and aspect (years 2003 and 2008) had positive effects on the slope of vegetation green-up. The only year in which the slope of vegetation green-up had a significant, and negative, effect on mule deer percent bodyfat was 2008 (Table 2). Age and winter precipitation also had negative effects on percent bodyfat in 2008 (Table 2). The onset of vegetation emergence was significantly influenced by several climatic and topographic variables. Again, these effects were not always consistent across years; for instance spring precipitation had a negative effect on vegetation onset in 2003 and 2008, but this effect was positive in 2009 (Table 3). Similarly, winter precipitation had a negative effect on vegetation onset in 2003 and 2004, but a positive effect in 2008 (Table 3). Aspect also produced contrasting effects in different years, having a negative effect on vegetation onset in 2003, and a positive effect in 2008. Elevation had a positive effect on vegetation onset in three years (2003, 2008 and 2009). The only year in which vegetation onset had a significant, and negative, effect on mule deer percent bodyfat was 2008 (Table 3). Winter temperature (2003) and winter precipitation (2008) both had positive effects on percent bodyfat, while age had a negative effect on percent bodyfat in 2008 (Table 3). Estimates of process variance and observation error were made for each path equation (NDVI and percent fat) across all years (Table 5). Process variance was lower for the NDVI submodel than for the 35 �percent fat submodel, indicating that the percent fat path equation accounted for less of the important underlying processes. However, observation error was lower for the percent fat submodel than for the NDVI submodel, which is to be expected given the quality of the percent fat measurements taken using the rLIVINDEX method (Cook et al. 2007). Path analysis diagrams We constructed path analysis diagrams for 2008, the only year for which we found significant effects of plant phenology – ‘slope’ (Fig. 3) and ‘onset’ (Fig. 4) - on mule deer percent bodyfat. Values are posterior means for each linear relationship. DISCUSSION Climate and topographic variables on plant phenology metrics Although the models converged well on parameter estimates for each of the five years, we restrict our discussion to the year with the greatest number of individual deer sampled (2008, n=78). We feel that drawing conclusions from the other four years, in which the number of deer sampled ranged from 18-33, is difficult given the complexity of the final model. Slope Winter precipitation, elevation and aspect all contributed to make the slope during green-up steeper, while spring precipitation decreased the slope during green-up. Higher elevation and aspect with higher degrees associated with North and West slopes likely increase the slope during green-up because higher elevations and on North and West-facing aspects probably cause a compression in the window over which microclimatic conditions are favourable for plant growth. Winter precipitation likely increases the slope during green-up because there is more soil moisture when temperature conditions become favourable for plant growth, thus speeding up plant development. Spring precipitation is likely to decrease the slope during green-up by providing additional inputs of moisture into the system, thus elongating the time window over which plant growth can occur. We detected no significant effect of winter temperature on percent bodyfat, indicating that the direct, physiological impact of winter climate is less important than the indirect climatic effects on body condition mediated through plant phenology. Both of these study areas have relatively mild winters compared to certain other herds in the Intermountain West. If winter temperatures were to have an effect on percent body fat, it would be expected to occur in higher elevation, or more northerly, winter ranges typified by severe winter weather. Winter precipitation had a positive effect on mule deer percent bodyfat in 2008; however we are reluctant to interpret this finding without reference to a longer time-series of data. In the other years for which we have data, this relationship was not significant, although this is likely related to the limited number of observations in other years. Age also had a negative effect on mule deer percent bodyfat, which is to be expected as body condition in ungulates often declines with age once a certain threshold is reached. Effect of plant phenology on mule deer percent bodyfat As predicted, the slope of the vegetation green-up period had a significant, negative correlation with mule deer percent body fat. This indicates that individuals inhabiting home ranges with more synchronous plant phenology performed less well than those individuals occupying home ranges with asynchronous phenology. 36 �Rapid green-up of vegetation during spring has been negatively correlated with growth and survival of bighorn lambs (Ovis canadensis), growth of mountain goat kids (Oreamnos americanus) in Canada, and survival of Alpine ibex kids (Capra ibex) in northern Italy (Pettorelli et al. 2007). Rapid changes in NDVI during vegetation green-up could translate to greater forage availability at a given point in time across a landscape. However, these rapid changes may also serve to compress the time window over which high quality forage is available to ungulates over a large spatial scale, such as the home range, potentially depressing diet quality over the longer-term (Pettorelli et al. 2007). The duration of the vegetation period was found to be predominantly constrained by spring weather in the Canadian study area (Pettorelli et al. 2005a). Warm temperatures in spring can override the effects of variable topography (Kudo 1991, Steltzer et al. 2009), reducing spatial heterogeneity in plant phenology over the landscape, and shortening the period over which ungulates have access to high quality forage (Pettorelli et al. 2007). Overall effects We can estimate the indirect effects of climate and topography through the mediating variable, plant phenology, on percent bodyfat by calculating the product of the standardized regression parameters for each pathway (Gajewski et al. 2005). For the slope index of plant phenology, summer precipitation had the greatest indirect influence on percent bodyfat, with a positive indirect effect of 0.85. Elevation had the strongest negative indirect effect on percent bodyfat with an indirect effect of -0.43, followed by winter precipitation (indirect effect -0.28) and aspect (indirect effect -0.15). However, because winter precipitation also had a direct effect on percent bodyfat of 0.22, its total influence on percent body fat is the sum of the direct and indirect effects (Gajewski et al. 2005), and is quite minimal (total effect of winter precipitation on mule deer percent bodyfat -0.058). Onset Onset had the opposite relationship to percent bodyfat than predicted, having a negative effect on percent bodyfat of mule deer. This is somewhat unexpected, because a higher mean NDVI value at the start of the green-up period is thought to be associated with an earlier start to the growing season, and elongated time period at which forage is at peak quality. However, a higher mean NDVI value at the start of the green-up period could also be indicative of a faster rate of green-up, which would compress the period of high quality forage for ungulates. Indeed, we suspect that this may be the case in this analysis, because of the close similarity between the parameter estimates for the independent variables for both the slope and onset models (Tables 2 and 3 and Figs 3 and 4). Pettorelli et al. (2007) found no positive effect of early vegetation onset on juvenile growth or survival in three ungulate species in Canada and northen Italy, and suggest that there is a greater influence of the average duration of the period of access to high quality forage, rather than the measure of the average timing of vegetation onset. SUMMARY Studies in boreal forests with strong seasonality at northern latitudes have found summer fattening of ungulates linked to plant phenology to be a more important climatic factor for body condition in autumn than winter bodymass loss due to harsh conditions (snow depth and temperature) (Mysterud et al. 2008). While bodymass of yearling red deer (Cervus elaphus) in Norway was linked to winter snow and temperature, it was found that the magnitude of these effects was much smaller than the indirect effects of climate operating through plants. Similarly, in our study area, we detected no significant effect of winter temperature on percent bodyfat of mule deer, while several significant effects of spring climate on bodyfat, mediated through plant phenology, were found. 37 �Pettorelli et al. (2007) detected an increase in the maximal increase in NDVI (slope) over time, suggesting a possible reflection of a warming trend, which could negatively affect alpine ungulates by compressing the period of high quality forage availability. In this study, we do not have enough years of data to reliably assess if a similar trend can be detected in this study area, but our findings do warrant increased attention to changes in climatic patterns, particularly spring precipitation, because any future decrease in spring precipitation may lead to decreases in the body condition of this important ungulate species. In conclusion, spring precipitation seems to play the greatest role in determining winter body condition of mule deer in this study area, having a positive effect on percent bodyfat that is mediated via its effect on plant phenology, acting to decrease the slope of the green-up in spring, thereby prolonging the period of availability of high quality forage. This finding does, however, need to be validated with more years of data with sufficient numbers of animals for analysis, and with direct assessments of spring precipitation on the quality of forage available to animals in different home ranges. LITERATURE CITED Bellis, L. M., A. M. Pidgeon, V. C. Radeloff, V. St-Louis, J. L. Navarro, and M. B. Martella. 2008. Modeling habitat suitability for greater rheas based on satellite image texture. Ecological applications 18: 1956-1966. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1−28. Boone, R. B., S. B. BurnSilver, and R. L. Kruska. 2008. Comparing landscape and infrastructural heterogeneity within and between ecosystems. In: Fragmentation in semi-arid and arid landscapes by K. A. Galvin, R. S. Reid, R. H. Behnke, and N. T. Hobbs. Springer, the Netherlands. Boone, R. B., S. J. Thirgood, and J. G. C. 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Winter habitat selection of mule deer before and during development of a natural gas field. Journal of Wildlife Management 70:396– 403. Shipley, B. 2002. Cause and correlation in Biology: a user’s guide to path analysis, structural equations and causal inference. Cambridge University Press, Cambridge, UK. Spiegelhalter, D. J., A. Thomas, and N. G. Best. 1999. WinBUGS Version 1.2 User Manual. Steltzer, H., C. Landry, T. H. Painter, J. Anderson and E. Ayres. 2009. Biological consequences of earlier snowmelt from desert dust deposition in alpine landscapes. Proceedings of the National Academy of Sciences of the United States of America 106:11629-11634. Prepared by _______________________ Mindy B. Rice, Spatial Ecologist 39 �Table 1. Summary of data collected on mule deer percent bodyfat for 2002, 2003, 2004, 2008 and 2009. Age is mean of all individuals captured in that year, with associated minimum and maximum in parentheses. Year 2002 2003 2004 2008 2009 Number of individuals 18 29 24 78 33 Month of capture Age February/March February/March March December March 4.5 (3.0-7.5) 3.3 (1.5-8.5) 3.4 (1.5-7.0) 4.5 (1.5-10.5) 4.5 (1.5-10.5) Table 2. Results from the path analysis for how climate affects plant phenology and mule deer percent bodyfat in western Colorado (2002-2004, 2008, 2009). All variables except ‘slope’ were standardised. Year 2002 2009 2008 2009 2002 2008 2009 2003 2008 2003 2004 2008 2009 2002 2004 2008 2009 2008 2008 2008 Metric a a b1 b1 b2 b2 b2 b3 b3 b4 b4 b4 b4 c c c c d1 d3 d4 Metric NDVI intercept NDVI intercept Spring ppt Spring ppt Elevation Elevation Elevation Aspect Aspect Winter ppt Winter ppt Winter ppt Winter ppt %Fat intercept %Fat intercept %Fat intercept %Fat intercept SLOPE Winter ppt Age Posterior mean -0.91 -5.04 -0.61 8.48 0.38 0.31 1.18 0.058 0.11 -0.15 -0.12 0.20 -0.39 -2.59 -2.43 -2.95 -2.21 -1.39 0.22 -0.087 40 95% credible interval -1.65, -0.22 -5.54, -4.53 -0.88, -0.35 7.49, 9.46 0.12, 0.64 0.021, 0.61 0.96, 1.39 0.012, 0.10 0.068, 0.15 -0.23, -0.07 -0.19, -0.05 0.021, 0.37 -0.56, -0.21 -3.65, -1.58 -3.09, -1.78 -3.65, -2.27 -3.66, -0.78 -2.42, -0.39 0.00019, 0.44 -0.16, -0.014 �Table 3. Results from the path analysis for how climate affects plant phenology and mule deer percent bodyfat in western Colorado (2002-2004, 2008, 2009). All variables except ‘onset’ were standardised. Year Metric 2003 a 2009 a 2003 b1 2008 b1 2009 b1 2003 b2 2008 b2 2009 b2 2003 b3 2008 b3 2003 b4 2004 b4 2008 b4 2004 c 2008 c 2009 c 2008 d1 2003 d2 2008 d4 2008 d3 Metric NDVI intercept NDVI intercept Spring ppt Spring ppt Spring ppt Elevation Elevation Elevation Aspect Aspect Winter ppt Winter ppt Winter ppt %Fat intercept %Fat intercept %Fat intercept ONSET Winter temp Age Winter ppt Posterior mean -3.27 -1.41 -1.82 -0.37 2.76 0.19 0.28 0.46 -0.028 0.11 -0.089 -0.072 0.13 -2.23 -2.78 -2.18 -1.46 0.41 -0.088 0.23 41 95% credible interval -4.75, -1.06 -1.67, -1.13 -2.70, -0.49 -0.52, -0.22 2.21, 3.28 0.089, 0.26 0.12, 0.44 0.34, 0.59 -0.053, -0.00098 0.087, 0.13 -0.13, -0.044 -0.11, -0.033 0.031, 0.22 -3.16, -1.32 -3.36, -2.22 -3.60, -0.74 -2.56, -0.38 0.14, 0.69 -0.16, -0.014 0.014, 0.45 �Table 4: Convergence statistics for all years and the scale reduction factors for slope and onset variables. Year 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 2002 2003 2004 2008 2009 Parameter a a a a a b1 b1 b1 b1 b1 b2 b2 b2 b2 b2 b3 b3 b3 b3 b3 b4 b4 b4 b4 b4 c c c c c d1 d1 d1 d1 d1 d2 d2 d2 d2 d2 d3 d3 d3 d3 d3 d4 d4 d4 d4 d4 SLOPE Point Estimate 1.01 1.17 1.01 1.00 1.01 1.00 1.17 1.01 1.01 1.01 1.00 1.13 1.00 1.01 1.01 1.00 1.05 1.00 1.00 1.01 1.00 1.03 1.00 1.01 1.00 1.00 1.03 1.00 1.00 1.00 1.00 1.03 1.00 1.00 1.00 1.00 1.01 1.00 1.00 1.00 1.00 1.03 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 97.5% Quantile 1.01 1.51 1.02 1.00 1.03 1.01 1.51 1.02 1.04 1.02 1.00 1.37 1.00 1.02 1.03 1.01 1.14 1.01 1.02 1.02 1.00 1.10 1.00 1.03 1.00 1.00 1/09 1.00 1.00 1.01 1.00 1.09 1.00 1.00 1.00 1.00 1.04 1.00 1.00 1.01 1.00 1.09 1.00 1.00 1.01 1.00 1.01 1.00 1.00 1.00 42 Parameter a a a a a b1 b1 b1 b1 b1 b2 b2 b2 b2 b2 b3 b3 b3 b3 b3 b4 b4 b4 b4 b4 c c c c c d1 d1 d1 d1 d1 d2 d2 d2 d2 d2 d3 d3 d3 d3 d3 d4 d4 d4 d4 d4 ONSET Point Estimate 1.00 1.52 1.03 1.00 1.01 1.01 1.52 1.03 1.00 1.02 1.00 1.35 1.03 1.00 1.00 1.01 1.12 1.03 1.00 1.00 1.00 1.04 1.00 1.00 1.00 1.01 1.03 1.00 1.00 1.00 1.01 1.03 1.00 1.00 1.00 1.00 1.01 1.00 1.00 1.00 1.00 1.02 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 97.5% Quantile 1.01 2.31 1.11 1.01 1.05 1.03 2.31 1.09 1.01 1.05 1.02 1.92 1.09 1.01 1.01 1.02 1.35 1.10 1.01 1.02 1.01 1.14 1.02 1.01 1.00 1.02 1.09 1.01 1.00 1.00 1.02 1.08 1.01 1.00 1.00 1.01 1.02 1.00 1.00 1.00 1.01 1.07 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 �Table 5. Estimates for process variance and observation error for each of the two path equation submodels (NDVI and percent fat), for the ‘slope’ and ‘onset’ vegetation phenology indices. Estimates are posterior means and 95% credible intervals estimated across all years. SLOPE Posterior mean 2.5% credible interval 97.5% credible interval Process variance (NDVI) Observation error (NDVI) Process variance (percent fat) Observation error (percent fat) ONSET Process variance (NDVI) Observation error (NDVI) Process variance (percent fat) Observation error (percent fat) 0.033 0.21 0.24 0.034 0.0017 0.042 0.077 0.0018 0.056 0.34 0.35 0.056 0.019 0.21 0.24 0.019 0.0013 0.042 0.077 0.00084 0.031 0.34 0.35 0.031 Figure 1. Mean NDVI curves for each deer captured in 2004. The vegetation green-up period was determined to occur from dates 4 to 7, corresponding to April 4th to June 25th. The ‘slope’ NDVI index was calculated by finding the slope between mean NDVI values across each individual’s home range from April 4th to June 25th (green dotted line). The ‘onset’ of vegetation green-up NDVI index was the mean NDVI value across each individual’s home range on date 4, April 4th. 2003 Mean NDVI by deer 0.7000 0.6000 0.5000 0.4000 Slope during green-up 0.3000 0.2000 0.1000 0.0000 1 2 3 4 5 6 7 8 date 43 9 10 11 12 13 14 15 �Figure 2. Path analysis diagram for how performance (percent body fat) of adult, female mule deer is affected directly and indirectly by climate and plant phenology in western Colorado. All lines in diagram represent a specific linear model. 44 �Figure 3: Path analysis diagram for how performance (percent fat) of adult, female mule deer is affected directly and indirectly by climate in western Colorado in 2008. Indirect linkages are manifested through a measure of the speed of vegetation green-up in the spring derived from NDVI measurements (‘slope’). All lines in the diagram represent a specific linear model. Thick solid lines represent strong evidence for an effect (95% credible interval does not overlap zero). Dotted lines represent no clear effect. Regression coefficient estimates are given with 95% credible intervals. ‘+’ predicted positive relationship, ‘-‘ predicted negative relationship. 45 �Figure 4: Path analysis diagram for how performance (percent fat) of adult, female mule deer is affected directly and indirectly by climate in western Colorado in 2008. Indirect linkages are manifested through a measure of the timing of vegetation green-up in the spring derived from NDVI measurements (‘onset’). All lines in the diagram represent a specific linear model. Thick solid lines represent strong evidence for an effect (95% credible interval does not overlap zero). Dotted lines represent no clear effect. Regression coefficient estimates are given with 95% credible intervals. ‘+’ predicted positive relationship, ‘-‘ predicted negative relationship. 46 �Colorado Division of Wildlife July 2009 − June 2010 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 6 Federal Aid Project: W-185-R : Division of Wildlife : Mammals Research : Deer Conservation : Population Performance of Piceance Basin Mule Deer in Response to Natural Gas Resource Extraction and Mitigation Efforts to Address Human Activity and Habitat Degradation : Period Covered: July 1, 2009 − June 30, 2010 Authors: C. R. Anderson and C. J. Bishop Personnel: E. Bergman, J. Broderick, B. deVergie, D. Finley, L. Gepfert, M. Grode, K. Kaal, T. Knowles, J. Lewis, P. Lukacs, K. Maysilles, M. Sirochman, T. Swearingen, R. Velarde, S. Wilson, L. Wolfe, CDOW; E. Hollowed, BLM; S. Monsen, Western Ecological Consulting, Inc.; D. Freddy, Hoch Berg Enterprises; H. Sawyer, Western Ecosystems Technology; P. Lendrum, T Bowyer, Idaho State University; P. Doherty, G. Wittemyer, K. Wilson, G. White, Colorado State University; M. Keech, L. Shelton, M. Shelton, R. Swisher, Quicksilver Air, Inc.; D. Felix, Olathe Spray Service, Inc.; L. Coulter, Coulter Aviation. Project support received from Federal Aid in Wildlife Restoration, Colorado Mule Deer Association, Colorado Mule Deer Foundation, Colorado State Severance Tax Fund, EnCana Corp., Shell Petroleum, and Williams Production LMT Co. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the authors. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We propose to experimentally evaluate habitat treatments that may improve the landscape to benefit mule deer (Odocoileus hemionus) and evaluate human-activity management alternatives to reduce the disturbance of energy development impacts on mule deer. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas within the state. The data presented here represent the first 2 pretreatment years of a long-term study addressing habitat modifications and improved energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. We modified the previous study design to monitor 4 winter range study areas representing varying levels of development to serve as treatment (Ryan Gulch, North Magnolia, South Magnolia) and control (North Ridge) sites and recorded habitat use and movement patterns using GPS collars (5 locations/day), estimated overwinter fawn and annual adult female survival, estimated early and late winter body condition of adult females using ultrasonography, and estimated abundance using helicopter mark-resight surveys. We attached 250 VHF collars (50—80/study area) to fawns and 80 VHF collars to does (20/study area) in early December 2009 and 100 GPS collars (25/study area) to adult female mule deer in early March 2010. Based on the data collected thus far, deer from all areas appear to 47 �be in reasonably good condition and are exhibiting high survival rates. Mild winter conditions the past 2 years certainly contributed to the observed mule deer population parameters. It will be informative to note how the different wintering mule deer herd segments react following a severe winter. Observed differences in winter concentration areas thus far may indicate behavioral modifications to areas of high development activity, but resource selection analyses will be necessary to confirm this supposition. We will continue to collect the various population and habitat use data across all study sites to evaluate the effectiveness of the habitat treatments scheduled to begin this fall. This approach will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation dollars toward less-impacted areas. We may also find that habitat mitigation efforts are not effective in developed areas at all, suggesting that habitat enhancement efforts may be only effective in areas that are not impacted by development. We are also evaluating deer behavioral responses to varying levels of development activity and habitat mitigation treatments. This will allow us to assess the effectiveness of certain Best Management Practices (BMPs) and habitat manipulations for reducing disturbance to deer. The study is slated to run through at least 2015, and preferably 2018, to adequately measure deer population responses to landscape level manipulations. 48 �WILDLIFE RESEARCH REPORT POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION CHARLES R. ANDERSON, JR and CHAD J. BISHOP PROJECT NARRITIVE OBJECTIVES 1. To determine experimentally whether enhancing mule deer habitat conditions on winter and/or transition range elicits behavioral responses, improves body condition, increases overwinter fawn survival, or ultimately, population density on mule deer winter ranges exposed to extensive energy development. 2. To determine experimentally to what extent modification of energy development practices enhance habitat selection, body condition, over-winter fawn survival, and winter range mule deer densities. SEGMENT OBJECTIVES 1. Collect and reattach GPS collars (5 location attempts/day) to maintain sample sizes for addressing mule deer habitat use and behavior patterns in 4 study areas experiencing varying levels of energy development of the Piceance Basin, northwest Colorado. 2. Estimate early and late winter body condition of adult female mule deer in each of the 4 winter herd segments 3. Monitor over-winter fawn and annual adult female mule deer survival by daily ground tracking and biweekly aerial tracking. 4. Conduct Mark-Resight helicopter surveys to estimate mule deer abundance in each study area. 5. Develop cooperative agreements to initiate habitat treatments for assessing efficacy of habitat improvement projects to mitigate energy development disturbances to mule deer. 6. Summarize data and present information in an annual Job Progress Report. INTRODUCTION Extraction of natural gas from areas throughout western Colorado has raised concerns among many public stakeholders and the Colorado Division of Wildlife that the cumulative impacts associated with this intense industrialization will dramatically and negatively affect the wildlife resources of the region. Concern is especially high for mule deer due to their recreational and economic importance as a principal game species and their ecological importance as one of the primary herbivores of the Colorado Plateau Ecoregion. Extraction of natural gas will directly affect the potential suitability of the landscape used by mule deer through conversion of native habitat vegetation with drill pads, roads, or noxious weeds, by fragmenting habitat because of drill pads and roads, by increasing noise levels via compressor stations and vehicle traffic, and by increasing the year-round presence of human activities. Extraction will indirectly affect deer by increasing the human work-force population of the region resulting in the need for additional landscape for human housing, supporting businesses, and upgraded 49 �road/transportation infrastructure. Additionally, increased traffic on rural roads will raise the potential for vehicle-animal collisions and additive direct mortality to deer populations. Thus, research documenting these impacts and evaluating the most effective strategies for minimizing and mitigating these activities will greatly enhance future management efforts to sustain mule deer populations for future recreational and ecological values. The Piceance Basin in northwest Colorado contains one of the largest migratory mule deer populations in North America and also exhibits some of the largest natural gas reserves in North America. Projected energy development throughout northwest Colorado within the next 20 years is expected to reach about 15,000 wells, many of which will occur in the Piceance Basin, which currently supports over 250 active gas well pads (http://cogcc.state.co.us). Anderson and Freddy (2008a) in their long-term research proposal identified 6 primary study objectives to assess measures to offset impacts of energy extraction on mule deer population performance. During the past 3 years, we have gathered baseline habitat utilization data from GPS-collared deer across the Piceance Basin to allow assessment of mitigation approaches that will be implemented over the next 2-3 years and evaluated for another 5-6 years. We initially selected 5 winter range study areas representing varying levels of development to serve as treatment and control sites. The past 2 years, we also estimated winter fawn survival and annual adult female survival, early and late winter body condition of adult females using ultrasonography, and deer abundance using helicopter mark-resight surveys. We started with 5 study sites to allow flexibility to respond to differences in deer behavior and changing energy development plans, which can directly affect experimental design. During the previous year, we refined our study design using our baseline deer data and current energy development plans of the major companies operating in Piceance Basin. We split 1 study area (Magnolia split into North and South Magnolia) based on differences in deer movement and behavior patterns from GPS data (Anderson 2009) and eliminated 2 other study sites (Story/Sprague and Yellow Creek) due to incompatible deer behavior patterns to adequately serve as control sites and to reduce the annual project budget to the minimum necessary to meet the original research objectives. This progress report describes the previous 2 years of addressing mule deer population performance during the pretreatment phase, which includes monitoring habitat selection and behavior patterns of adult female mule deer, overwinter fawn and adult female survival, estimates of adult female body condition during early and late winter, and abundance estimates on 4 winter range herd segments in relation to varying levels of natural gas development in control and treatment experimental areas prior to proposed experimental modifications in energy developmental practices and potential habitat improvement treatments. STUDY AREAS The Piceance Basin between the cities of Rangely, Meeker, and Rifle in northwest Colorado was selected as the project area due to its ecological importance as one of the largest migratory mule deer populations in North America and because it exhibits one of the highest natural gas reserves in North America (Fig. 1). Historically, mule deer numbers on winter range were estimated between 15,00022,000 (Bartmann 1975), and the current number of well pads (Fig.1) and projected number of gas wells in the Piceance Basin over the next 20 years is about 250 and 15,000, respectively. Mule deer winter range in the Piceance Basin is predominantly characterized as a topographically diverse pinion pine (Pinus edulis)-Utah juniper (Juniperus osteosperma; pinion-juniper) shrubland complex ranging from 1675 m to 2285 m in elevation (Bartmann and Steinert 1981). Pinion-juniper are the dominant overstory species and major shrub species include Utah serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), big sagebrush (Artemisia tridentata), Gamble’s oak (Quercus gambelii), mountain snowberry Symphoricarpos oreophilus), and rabbitbrush (Chrysothamnus spp.; Bartmann et al. 1992). The Piceance Basin is segmented by numerous drainages characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainages having been converted to mixed-grass hay 50 �fields. Grasses and forbs common to the area consist of wheatgrass (Agropyron spp.), blue grama (Bouteloua gracilis), needle and thread (Stipa comata), Indian rice grass (Oryzopsis hymenoides), arrowleaf balsamroot (Balsamorhiza sagittata), broom snakeweed (Gutierrezia sarothreae), pinnate tansymustard (Descurainia pinnata), milkvetch (Astragalus spp.), Lewis flax (Linum lewisii), evening primrose (Oenothera spp.), skyrocket gilia (Gilia aggregata), buckwheat (Erigonum spp.), Indian paintbrush (Castilleja spp.), and penstemon (Penstemon spp.; Gibbs 1978). The climate of the Piceance Basin is characterized by warm dry summers and cold winters with most of the annual moisture resulting from spring snow melt. Wintering mule deer population segments we investigated in the Piceance Basin include: North Ridge (57 km2) just north of the Dry Fork of Piceance Creek including the White River in the northeastern portion of the Basin, Ryan Gulch (130 km2) between Ryan Gulch and Dry Gulch in the southwestern portion of the Basin, North Magnolia (79 km2) between the Dry Fork of Piceance Creek and Lee Gulch in the north-central portion of the Basin, and South Magnolia (83 km2) between Lee Gulch and Piceance Creek in the south-central portion of the Basin (Fig. 1). Each of these wintering population segments has received varying levels of natural gas development: no development in North Ridge, light development in North Magnolia (0.13 pads & facilities/km2), and relatively high development in the Ryan Gulch (0.64 pads & facilities/km2) and South Magnolia (0.81 pads & facilities/km2) segments (Fig. 1). Among the 4 study areas, North Ridge will serve as an unmanipulated control site, Ryan Gulch will serve to address human-activity management alternatives (Best Management Practices; BMPs) that may benefit mule deer exposed to energy development, and North and South Magnolia will serve to address the utility of habitat treatments intended to enhance mule deer population performance in areas exposed to light (North Magnolia) and heavy (South Magnolia) energy development activities. METHODS Tasks addressed this fiscal year included mule deer capture and collaring efforts, monitoring overwinter fawn and annual adult female survival, estimating adult female body condition during early and late winter using ultrasonography, and estimating mule deer abundance applying helicopter markresight surveys. We employed helicopter net-gunning techniques (Barrett et al. 1982, van Reenen 1982) to capture 50—80 fawns and 20 adult females during early December and 25 adult females during early March in each of the 4 study areas (250 fawns and 180 does total). Once netted, all deer were hobbled and blind folded. Fawns were weighed, radio-collared and released on site, and adult females were transported to localized handling sites for collection of body measurements and were fitted with VHF (20/area during December) or GPS collars (25/area during March; 5 fixes/day; G2110B, Advanced Telemetry Systems, Isanti, MN, USA) and released. To provide direct measures of decline in overwinter body condition, we attempted to capture the same adult females during the March capture that were captured in December. Fawn collars were spliced and fitted with 2 lengths of rubber surgical tubing to facilitate collar drop during mid-summer—early autumn, adult VHF collars were attached static, and GPS collars were supplied with timed drop-off mechanisms scheduled to release early April, 2011. All radiocollars were equipped with mortality sensing options (i.e., increased pulse rate following 4 hrs of inactivity). Mule Deer Habitat Use and Movements We downloaded and organized data from GPS collars deployed March 2009 following collar drop and retrieval in early April 2010. GPS collars redeployed early March 2010 maintained the same fix schedule of attempting fixes every 5 hours. We plotted deer locations and recorded timing and distance of spring and fall 2009 migrations for each study area. Mule deer winter concentration areas were created using composite GPS data (winter locations since January 2008 from all deer) from each study area and mapped in ArcGIS (ver. 9.3) using Spatial Analyst (kernel probability density functions separated by 51 �quantiles). Mule deer resource selection analyses are pending completion of high resolution habitat data layers currently being developed by BLM (habitat data layers should be available by 2011). Mule Deer Survival Mule deer mortality monitoring consisted of daily ground telemetry tracking and aerial monitoring approximately every 2 weeks from fixed-wing aircraft. Once a mortality signal was detected, deer were located and necropsied to assess cause of death. We estimated over-winter survival on a weekly basis using the staggered entry Kaplan-Meier procedure (Kaplan and Meier 1958, Pollock et al. 1989). Capture-related mortalities (any mortalities occurring within 10 days of capture) and collar failures were censored from survival rate estimates. We estimated survival rates 28 June 2009—26 June 2010 for adult females and 6 December 2009—27 March 2010 for fawns. Premature failure of surgical tubing integrity beginning late March inhibited our ability to reasonably estimate fawn survival beyond March 27, 2010. Adult Female Body Measurements We applied ultrasonography techniques described by Stephenson et al. (1998, 2002) and Cook et al. (2001) to measure maximum subcutaneous rump fat (mm) and loin depth (longissimus dorsi muscle, mm). We estimated a body condition score (BCS) for each deer by palpating the rump (Cook et al. 2001). We combined ultrasound rump fat measurements with BCS to develop an index (rLIVINDEX; Cook et al. 2001, 2007) of the relative nutritional status of deer from each study area. We examined differences (P < 0.05) in nutritional status among study areas using a two-sample t-test. We considered differences in body condition meaningful when either mean rump fat or rLIVINDEX differed statistically between comparisons. Other body measurements recorded included pregnancy status (pregnant, barren) via blood samples, weight (kg), chest girth (cm), and hind-foot length (cm). Abundance Estimates We conducted 5 (North Magnolia) or 4 (the remaining study areas) helicopter mark-resight surveys (2 observers and the pilot) during late March, 2010 to estimate deer abundance in each of the 4 study areas. We delineated each study area from GPS locations during the same period the previous year and aerial telemetry locations of radio-collared deer within 1 week of the first mark-resight survey. Aerial fixed-wing telemetry surveys were conducted during helicopter surveys to determine which marked deer were within each survey area. We delineated flight paths in ArcGIS 9.3 prior to surveys following topographic contours (e.g., drainages, ridges) and approximating 500 m spacing throughout each study area; flight paths during surveys were followed using GPS navigation in the helicopter. Two approximately 12 x 12 cm pieces of Ritchey livestock banding material (Ritchey Livestock ID, Brighton, CO USA) were uniquely marked using number, symbol combinations and attached to each radio-collar to enhance mark-resight estimates. Each deer observed during surveys was recorded as mark ID#, unmarked, or unidentified mark. We used program MARK (White and Burnham 1999) applying the mixed logit-normal model (McClintock et al. 2008) to estimate mule deer abundance and confidence intervals. For mark-resight model evaluations, we examined parameter combinations of varying detection rates with survey occasion and whether individual sighting probabilities (i.e., individual heterogeneity) were constant or varied (σ2 = 0 or ≠ 0). Model selection procedures followed the information-theoretic approach of Burnham and Anderson (2002). 52 �RESULTS AND DISSCUSSION Deer Captures and Survival The helicopter crew captured 253 fawns and 80 does in early December 2009 and 103 does in early March 2010. Seven fawn (ultimate cause = 4 cougar predation, 2 coyote predation, 1 drowning) and 2 doe mortalities (ultimate cause = tangled in fence and coyote predation) occurred within the 10 day myopathy period following the December capture and 3 doe mortalities occurred during the March capture (all direct capture myopathy). Fawn survival during early-December 2009—late March 2010 was similar among study areas (P > 0.05) ranging from 0.872 (Ryan Gulch) to 0.945 (North Magnolia; Table 1, Fig. 2). Although mean fawn survival was higher than last year among 3 of 4 study areas (with the exception of Ryan Gulch; see Anderson 2009), differences were statistically insignificant. Annual adult female survival was also similar among study areas (P > 0.05) ranging from 0.863 (North Ridge) to 0.943 (North Magnolia; Table 1, Fig. 1) and were comparable to last year (P > 0.05; Anderson 2009). The relatively high fawn survival observed the past 2 winters is likely due to the mild winter conditions present through late March, and doe survival was consistent with other mule deer populations experiencing normal winter conditions in the western US (Unsworth et al. 1999). Seasonal Movement Patterns Migration patterns differed among areas with North Ridge and North Magnolia deer migrating east-west and South Magnolia and Ryan Gulch deer migrating south-north (Fig. 3). Median straight-line migration distances were similar ranging from 32.6 km (Ryan Gulch) to 40.1 km (North Ridge). Similar to seasonal ranges, most deer monitored exhibited strong fidelity to spring and fall migration routes (Fig. 3). Timing of mule deer migration during 2009 was similar among study areas with median spring migration dates occurring between 15 and 20 May and median fall migration dates occurring between 15 and 22 October. Migration dates were later compared to last year (Anderson 2009), occurring 8 to16 days later in the spring and 11 to 14 days later in the fall. Length of migration was relatively short among areas averaging 5 to 10 days in the spring and 4 to 7 days in the fall; these observations were comparable to last year. More detailed analyses of these migration data investigating the influence of human activity are currently being conducted by Patrick Lendrum and Terry Bowyer of Idaho State University. A final report including next year’s migration data is scheduled to be completed by spring 2012. Winter concentration areas identified from January 2008—May 2010 (Fig. 4) reasonably followed study area boundaries delineated from deer locations applied the first winter of the project (Anderson and Freddy 2009b). We noted more continuous distributions from Ryan Gulch and North Ridge deer, with South Magnolia deer exhibiting the most fragmented and concentrated distributions, which may be related to relative development densities within each study area. Future resource selection analyses will address these differences relative to habitat attributes within each area. Minor modifications to study area boundaries will be applied in the future to better address winter deer use within each study area (Fig. 4). Mule Deer Body Condition Body condition measurements of adult female mule deer suggested that North and South Magnolia deer returned from summer range (December 2009) in better condition than North Ridge deer (P < 0.05) and condition of Ryan Gulch deer was intermediate and not significantly different (P > 0.05) from the other areas (Table 2). North and South Magnolia deer maintained relatively high body condition over winter, but only North Magnolia deer were in significantly better condition than deer from North Ridge and Ryan Gulch (P < 0.05; March 2010, Table 2) by late winter. Paired comparisons of deer captured during December 2009 and March 2010 indicted that mean rump fat and % body fat declined 8.3 mm and 6.9% in North Magnolia (n = 15), 8.1 mm and 6.9 % in South Magnolia (n = 16), 3.1 mm and 53 �4.0% in North Ridge (n = 16), and 6.3 mm and 6.6% in Ryan Gulch (n = 19). In comparing late winter body condition from 2009 to 2010, we noted significant improvement from North and South Magnolia deer and similar condition from North Ridge and Ryan Gulch deer. Pregnancy rates were expectedly high ranging from 84% in Ryan Gulch (n = 25) to 100% in South Magnolia (n = 25). Early December fawn weights of males and females averaged 39.5 kg (n = 30, SD = 4.3) and 36.5 kg (n = 30, SD = 3.2) from North Magnolia, 38.5 kg (n = 42, SD = 3.8) and 35.1 (n = 18, SD = 4.0) from South Magnolia, 37.5 kg (n = 33, SD = 4.0) and 34.9 kg (n = 50, SD = 4.3) from North Ridge, and 37.1 kg (n = 23, SD = 3.3) and 34.5 kg (n = 27, SD = 3.4) from Ryan Gulch. Fawn weights were similar among areas except that male and female fawns from North Ridge were larger than Ryan Gulch fawns (P < 0.05). Because North and South Magnolia study areas were not split until December 2009 and fawn locations were not sufficiently monitored prior to that time, comparisons to 2008 fawn weights were only possible by combining data from North and South Magnolia in 2009. Both males and females from the combined Magnolia area were larger during December 2009 than December 2008. Fawn weights from the other study areas were similar between years expect for males from North Ridge, which were also larger in 2009 (P = 0.047). Mule Deer Population Estimates Mark-resight models that best predicted abundance estimates (lowest AICc; Burnham and Anderson 2002) exhibited homogenous individual sightability (σ2 = 0) for all study areas and variable sightability (P) across surveys in 3 of the 4 study areas; sightability was consistent across surveys in North Magnolia. North Ridge exhibited the highest deer density (20.1/km2) and comparably lower deer densities were observed in the other 3 areas (6.9—9.3/km2; Table 3). Abundance estimates were similar to last year (Anderson 2009) except in Ryan Gulch where deer numbers were significantly higher this year. It is unlikely deer abundance increased from 825 (95% CI = 672—1,016) to 1,442 (95% CI = 1112—1878) in 1 year, and we suspect this difference may be partially due differences in sampling approach between years. The abundance estimate from 2009 was derived from subsampling 20 to 40% of the Ryan Gulch study area (Anderson 2009), whereas the 2010 estimate was based on complete sampling of the entire study area. It is plausible that subsampling the study area resulted in a negative bias and we are more comfortable with the 2010 estimate derived from complete coverage of the study area. Abundance estimates from 2010 were similarly precise from 3 of the 4 study areas (mean CV = 0.16—0.18), with Ryan Gulch exhibiting a relatively wide CI (Table 3; mean CV = 0.27). Number of marked deer was lowest from Ryan Gulch (n = 87) and increasing sample size would improve future estimates, as would increasing the number of mark-resight surveys. Additionally, winter concentration information from the past 3 winters (Fig. 4) can be used to more efficiently focus sampling effort potentially increasing mule deer sightability. Our goal is to achieve CVs of ≤0.15 to allow detection of at least 30% population change. We will attempt to improve precision of future mark-resight abundance estimates by increasing sample size using VHF radiocollars and increasing the number of surveys when feasible; simulations suggest CVs can be improved by about 0.02 for each additional mark-resight survey (C. Anderson, unpublished data). SUMMARY AND FUTURE PLANS The goal of this study is to investigate habitat treatments and energy development practices that enhance mule deer populations exposed to extensive energy development activity. The information presented here provide data describing mule deer population parameters from the first 2 years of the pretreatment period of a long-term study intended to address how mule deer react to landscape scale habitat and human activity modifications. The pretreatment period is intended to continue 1 to 2 more winters to provide baseline data to compare against intended improvements in habitat conditions and evaluation of concentration/reduction in human development activities, which will be maintained for at least 5 years to 54 �provide sufficient time to measure how deer respond to these changes. Based on the data collected thus far, deer from all areas appear to be in reasonably good condition and are exhibiting high survival rates. Mild winter conditions the past 2 years certainly contribute to the observed mule deer population parameters. It will be informative to note how the different wintering mule deer herd segments react following a severe winter. Observed differences in winter concentration areas (Fig. 4) may indicate behavioral modifications to areas of high development activity, but resource selection analyses will be necessary to confirm this supposition. We will continue to collect the various population and habitat use data across all study sites to evaluate the effectiveness of the habitat treatments. This approach will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation dollars toward less-impacted areas. We may also find that habitat mitigation efforts are not effective in developed areas at all, suggesting that habitat enhancement efforts may be only effective in areas that are not impacted by development. In a recent project conducted on the Uncomphahgre Plateau, Bergman et al. (2009) found that habitat treatments implemented in pinyon-juniper habitat in undeveloped areas were effective for deer. We are also evaluating deer behavioral responses to varying levels of development activity and habitat mitigation treatments. This will allow us to assess the effectiveness of certain BMPs and habitat manipulations for reducing disturbance to deer. We recently developed a habitat improvement plan and intend to begin implementation this fall with completion by fall 2011 if feasible or fall 2012 in the Magnolia study areas. In addition, hay field improvements have begun and will continue in the North Magnolia area and we plan to begin discussions addressing hay field improvements in the South Magnolia study area. Recent collaboration agreements with ExxonMobil Development Co. and Colorado State University will provide graduate research opportunities to enhance data collection and inference about mule deer/energy development interactions. Collaboration with Williams Production LMT Co. have produced a clustered development plan to be implemented in the Ryan Gulch study area and new technologies will be implemented to reduce human activity through remote monitoring of well pads and fluid collection systems. We are continuing to work with Dr. Terry Bowyer and Patrick Lendrum (MS candidate) of Idaho State University to address mule deer migration and potential influences of human activity along migration routes. Additional funding and cooperative agreements will be necessary to sustain this project through completion (through at least 2015 and preferably through 2018). We optimistically anticipate the opportunity to work cooperatively toward developing solutions for allowing the nation’s energy reserves to be developed in a manner that benefits wildlife and the people who value both the wildlife and energy resources of Colorado. LITERATURE CITED Anderson, C. R., Jr. 2009. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and D. J. Freddy. 2008a. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Final Study Plan, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and D. J. Freddy. 2008b. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation—Stage I, Objective 5: Patterns of mule deer distribution & movements. Pilot Study, Colorado Division of Wildlife, Ft. Collins, CO, USA. Bartmann, R. M. 1975. Piceance deer study—population density and structure. Job Progress Report, Colorado Divison of Wildlife, Fort Collins, Colorado, USA. Bartmann, R. B., and S. F. Steinert. 1981. Distribution and movements of mule deer in the White River Drainage, Colorado. Special Report No. 51, Colorado Division of Wildlife, Fort Collins, Colorado, USA. 55 �Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monograph No. 121. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, USA. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multi-model inference: a practical information-theoretic approach. Second edition. Springer-Verlag, New York, New York, USA. Cook, R. C., J. G. Cook, D. L. Murray, P. Zager, B. K. Johnson, and M. W. Gratson. 2001. Development of predictive models of nutritional condition for rocky mountain elk. Journal of Wildlife Management 65:973-987. Cook, R. C., T. R. Stephenson, W. L. Meyers, J. G. Cook, and L. A. Shipley. 2007. Validating predictive models of nutritional condition for mule deer. Journal of Wildlife Management 71:1934-1943. Gibbs, H. D. 1978. Nutritional quality of mule deer foods, Piceance Basin, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 52:457-481. McClintock, B. T., G. C. White, K. P. Burnham, and M. A. Pride. 2008. A generalized mixed effects model of abundance for mark—resight data when sampling is without replacement. Pages 271289 in D. L. Thompson, E. G. Cooch, and M. J. Conroy, editors, Modeling demographic processes is marked populations. Springer, New York, New York, USA. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. C. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. Stephenson, T. R., K. J. Hundertmark, C. C. Swartz, and V. Van Ballenberghe. 1998. Predicting body fat and mass in moose with untrasonography. Canadian Journal of Zoology 76:717-722. Unsworth, J. W., D. F. Pack, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked individuals. Bird Study 46:120-139. Prepared by _______________________ Chuck Anderson, Wildlife Researcher 56 �Table 1. Survival rate estimates (Ŝ) of fawn (6 Dec. 2009—27 Mar. 2010) and adult female (28 June 2009—26 June 2010) mule deer from 4 winter range study areas of the Piceance Basin in northwest Colorado. Cohort Study area Initial sample size (n) March doe samplea (n) Ŝ (95% CI) Fawns Ryan Gulch 47 0.872 (0.777—0.968) South Magnolia 63 0.937 (0.876—0.997) North Magnolia 55 0.945 (0.884—1.000) North Ridge 80 0.912 (0.849—0.974) Adult females Ryan Gulch 25 47 0.868 (0.757—0.979) South Magnolia 12 38 0.873 (0.757—0.989) North Magnolia 14 44 0.943 (0.866—1.000) North Ridge 27 50 0.863 (0.748—0.978) a Adult female sample size following capture and radio-collaring efforts early March, 2010. 57 �Table 2. Mean rump fat (mm), Body Condition Score (BCS)a, and an index of relative nutritional status (rLIVINDEX)b of adult female mule deer from 4 study areas in the Piceance Basin of northwest Colorado, March and December 2009 and March 2010. Values in parentheses = SD. March 2009 Study Area Rump fat Ryan Gulch March 2010 rLIVINDEX Rump fat BCS rLIVINDEX Rump fat 1.73 (1.78) 2.66 (0.55) 2.71 (0.68) 8.35 (6.36) 4.06 (1.13) 4.71 (1.63) 2.31 (1.44) 2.35 (0.48) 2.41 (0.57) South Magnolia 1.47 (0.68) 2.50 (0.60) 2.51 (0.63) 10.05 (6.19) 4.07 (1.21) 4.87 (1.75) 3.12 (2.20) 2.64 (0.59) 2.78 (0.74) North Magnolia 1.30 (0.79) 2.56 (0.68) 2.57 (0.70) 10.20 (5.48) 4.25 (0.96) 5.07 (1.42) 3.15 (2.34) 2.85 (0.53) 2.99 (0.70) North Ridge 1.57 (1.22) 2.60 (0.56) 2.62 (0.60) 5.25 (5.65) 3.63 (1.11) 3.98 (1.59) 1.77 (1.11) 2.42 (0.49) 2.46 (0.54) a BCS December 2009 Body condition score taken from palpations of the rump (Cook et al. 2001) rLIVEINDEX = (cm rump fat - 0.2) + BCS if rump fat > 2 mm. Otherwise = BCS (Cook et al. 2001, 2007). b 58 BCS rLIVINDEX �Table 3. Mark-resight abundance (N) and density estimates of mule deer from 4 winter range herd segments in the Piceance Basin, northwest Colorado, 22—31 March 2009. Data represent 5 resight surveys from North Magnolia and 4 resight surveys from the other 3 study areas. Study area Mean No. sighted Mean No. marked N (95% CI) Density (deer/km2) Ryan Gulch 125 11 1,442 (1,112—1,878) 9.3 South Magnolia 103 18 575 (481—692) 6.9 North Magnolia 102 14 595 (498—715) 7.5 North Ridge 231 23 1,145 (975—1,348) 20.1 Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, summer 2010. 59 �Adult Female Survival, 28 June 2009—26 June 2010 Fawn Survival, 6 December 2009—27 March 2010 Figure 2. Annual and winter survival rates of adult female (28 June 2009—26 June 2010; top) and fawn (6 December, 2009—27 March, 2010; bottom) mule deer from 4 winter range study areas in the Piceance Basin of northwest Colorado. Survival rates among fawn and doe groups were statistically similar (P > 0.05; Table 1). 60 �Figure 3. Mule deer migration routes from 4 winter range study areas in the Piceance Basin of northwest Colorado, spring and fall 2009. 61 �Figure 4. Mule deer winter concentration areas (composite kernel Probability Density Functions; PDF) from 4 study areas in the Piceance Basin of northwest Colorado, December 2008—May 2010. Data from composite GPS locations of adult female mule deer by study area (5 GPS location attempts/day). 62 �Colorado Division of Wildlife July 2009 − June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Effectiveness of a Redesigned Vaginal Implant Transmitter in Mule Deer Period Covered: July 1, 2009 − June 30, 2010 Authors: C. J. Bishop, C. R. Anderson, D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Our understanding of factors that limit mule deer (Odocoileus hemionus) populations may be improved by evaluating neonatal survival as a function of dam characteristics under free-ranging conditions, which generally requires that both neonates and dams are radiocollared. The most viable technique facilitating capture of neonates from radiocollared adult females is use of vaginal implant transmitters (VITs). To date, VITs have allowed research opportunities that were not previously possible; however, VITs are often expelled from adult females prepartum, which limits their effectiveness. We redesigned an existing VIT manufactured by Advanced Telemetry Systems (ATS; Isanti, MN) by lengthening and widening wings used to retain the VIT in an adult female. Our objective was to increase VIT retention rates and thereby increase likelihood of locating birth sites and newborn fawns. We placed the newly designed VITs in 59 adult female mule deer and evaluated the probability of retention to parturition and the probability of detecting newborn fawns. We also developed an equation for determining VIT sample size necessary to achieve a specified sample size of neonates. The probability of a VIT being retained until parturition was 0.766 (SE = 0.0605) and the probability of a VIT being retained to within 3 days of parturition was 0.894 (SE = 0.0441). In a similar study using the original VIT wings (Bishop et al. 2007), the probability of a VIT being retained until parturition was 0.447 (SE = 0.0468) and the probability of retention to within 3 days of parturition was 0.623 (SE = 0.0456). Thus, our design modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). Considering dams that retained VITs to within 3 days of parturition, the probability of detecting at least 1 neonate was 0.952 (SE = 0.0334) and the probability of detecting both fawns from twin litters was 0.588 (SE = 0.0827). We expended approximately 12 personhours per detected neonate. As a guide for researchers planning future studies, we found that VIT sample size should approximately equal the targeted neonate sample size. Our study expands opportunities for conducting research that links adult female attributes to productivity and offspring survival in mule deer. 63 �WILDLIFE RESEARCH REPORT EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES CHAD J. BISHOP, CHUCK R. ANDERSON, DANIEL P. WALSH, ERIC J. BERGMAN, PETER KUECHLE, AND JOHN ROTH P. N. OBJECTIVE To redesign vaginal implant transmitters (VITs) and evaluate their retention in free-ranging mule deer. SEGMENT OBJECTIVES 1. Evaluate rates of VIT retention to parturition and fawn capture success using the newly-designed wings in free-ranging mule deer. 2. Publish findings in Journal of Wildlife Management. INTRODUCTION Mule deer (Odocoileus hemionus) fawn production and neonatal survival is influenced by dam characteristics (e.g., body condition, disease status, habitat use). To understand fawn-dam relationships, manipulative field studies are needed that allow fawn production and survival to be estimated as a function of treatments applied to adult females. For example, a study evaluating the effectiveness of winter range habitat treatments on subsequent neonatal survival would require the capture of fawns from marked adult females that verifiably used, or did not use, the habitat treatments the previous winter(s). Such studies depend on a technique that enables newborn fawns to be captured from marked adult females. The most promising technique employed to capture neonates from marked adult females is use of vaginal implant transmitters (VITs), which are placed in the vagina of adult females during early to mid gestation. In theory, adult females retain VITs until parturition, at which point VITs are expelled at birth sites along with newborn fawns. Assuming VITs are routinely monitored, researchers can promptly radiolocate shed VITs and capture the newborn fawns. Recent applications of VITs in white-tailed deer (O. virginianus; Carstensen et al. 2003, Haskell et al. 2007, Saalfeld and Ditchkoff 2007), black-tailed deer (O. hemionus columbianus; Pamplin 2003), mule deer (Bishop et al. 2007, Haskell et al. 2007), and elk (Cervus elaphus; Johnson et al. 2006, Barbknecht et al. 2009) have been moderately successful. Vaginal implant transmitters also permit measurement of fetal survival in free-ranging populations, which has important implications in populations where stillborn mortality occurs (Bishop et al. 2007, 2008, 2009). An additional advantage of using VITs to capture neonates may be a reduction in sampling bias when compared to capture techniques that rely on opportunistic fawn capture (White et al. 1972, Ballard et al. 1998, Pojar and Bowden 2004). Opportunistic techniques are susceptible to bias because of unequal capture success among vegetation types, distances to roads, fawn ages, and stages of fawning. For example, if roads are used to conduct opportunistic searches, fawn capture probability will decline with increasing distance from a road and neonates will be disproportionately sampled in areas with high road densities. When using VITs, the distribution of radio-marked adult females carrying VITs determines where neonates are sampled. Inferences will be less biased with VITs than with opportunistic capture techniques if all VITs are monitored with equal intensity during fawning and the sample of radio-marked adult females was captured with minimal bias. Thus, VITs could have broad applicability regardless of whether study objectives require that fawns be captured from previously marked adult females. 64 �The most significant problem associated with VITs has been premature expulsion and subsequent failure to locate birth sites or newborn fawns, especially in mule deer (Johnstone-Yellin et al. 2006, Bishop et al. 2007, Haskell et al. 2007). The VIT has flexible, plastic wings coated with a soft silicone that induce pressure against the vaginal wall to retain the transmitter. The VIT design facilitates a quick, non-surgical insertion process and is safe for the animal (Johnson et al. 2006), but the current wing design is inadequate with respect to retention. Bishop et al. (2007) found that 43% (SE = 4.7) of VITs in mule deer shed prepartum, although the probability of capturing ≥1 fawn was relatively high (0.792, SE = 0.0847) when VITs shed only 1–3 days prepartum. They noted that 25% (SE = 4.1) of VITs shed >3 days prepartum and that retention probability declined as deer body size increased, indicating the retention wings were too small to be effective in larger deer. Based on these results, considerable oversampling of adult females would be required in the design of future projects to achieve a target sample size of fawns. That is, extra adult females would need to be sampled to offset those adult females that shed VITs prematurely. Oversampling, in this instance, is undesirable from an animal care and use perspective and unnecessarily expensive. Thus, our objective was to redesign the plastic-silicone retention wings of VITs to allow maximum retention in larger deer species. To date, the wings used to retain VITs have been purchased from a company in New Zealand (Carter Holt Harvey Plastic Products, Hamilton, New Zealand) that originally produced them for an application in the livestock industry (Bowman and Jacobson 1998). The company manufactured 1 large wing and 1 small wing; the former has been used in production of VITs for bison (Bison bison) and elk (Cervus elaphus) whereas the latter has been used in production of VITs for deer (Advanced Telemetry Systems, Isanti, MN). Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, made an initial effort in 2004 to lengthen the retention wings by adding resin to the wing tips. Using these VITs with antennas cut to the appropriate length, Haskell et al. (2007) reported that 81% of VITs (n = 21) in deer were retained until parturition. Retention improved but the aftermarket wing-modification was problematic because the wing tips were hard and thus not ideal for placement in the vaginal canal. That study provided justification to pursue further wing development. We therefore redesigned retention wings of VITs used in deer and similar-sized ungulates, fabricated a new production mold, and evaluated retention rates of VITs in free-ranging mule deer. STUDY AREA We conducted our research in Piceance Basin and on the Roan Plateau in northwest Colorado (Fig. 1). Our winter range study area comprised 4 study units distributed across much of the Piceance Basin. The 4 units ranged in size from 70 to 130 km2 and are referenced as South Magnolia, StorySprague, Ryan Gulch, and Yellow Creek (Fig. 1). These study units are part of a larger research study evaluating effects of natural gas development and mitigation on mule deer (Anderson and Freddy 2008). Winter range habitat comprised predominantly pinyon pine (Pinus edulis) and Utah juniper (Juniperus osteosperma) and secondarily big sagebrush (Artemisia tridentata), serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), and rabbitbrush (Chrysothamnus spp.). Drainage bottoms were characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainage bottoms having been converted to irrigated, grass hay fields. Elevations ranged from 1,860 m at Piceance Creek in Ryan Gulch to 2,280 m in Yellow Creek and Story-Sprague study units. Our summer range study area comprised roughly 1,700 km2 across the Roan Plateau and Piceance Basin (Fig. 1). Principal summer range habitat types included aspen (Populus tremuloides), mountain shrub, oakbrush (Quercus gambellii), big sagebrush, and pinyon-juniper. Serviceberry, snowberry (Symphoricarpos spp.), and chokecherry (Prunus virginiana) were common species in mountain shrub communities. Elevation ranged from 2,000 m in Piceance Creek at the mouth of Story Gulch to 2,600 m on Roan Plateau. 65 �METHODS We worked with ATS personnel to redesign the M3930 VIT presently manufactured by ATS. The existing M3930 has been described in detail elsewhere (Bowman and Jacobson 1998, Carstensen et al. 2003, Johnstone-Yellin et al. 2006, Bishop et al. 2007). Our redesign included changes to the retention wings and the means by which they are attached to the transmitter body (Fig. 2). Specifically, we modified dimensions of the retention wings by lengthening them from 57 mm to 68 mm and widening them from 9 mm to 13 mm. We also added ridges to the wing surface as means to increase probability of retention to parturition. The wings were made of flexible plastic encased in silicone. We initially produced a small number of the newly-designed wings using a relatively inexpensive prototype mold, which met our target specifications and therefore was deemed acceptable. We then manufactured a production mold, necessary to produce a large number of the wings. We incorporated ejector pins into the VIT design that allow wings to be attached to the VIT transmitter body in the field. In the original design, wings were permanently affixed to the transmitter body during the VIT assembly process. Although we only used one wing size in this study, field-attachment will allow researchers to use more than one wing size or style, without purchasing extra transmitters, if additional production molds are manufactured over time. For each wing design (i.e., production mold), extra wings could be inexpensively purchased and available in the field to affix to the fixed number of transmitter bodies. Researchers could then individually fit VITs to animals in the field much in the same way radiocollars are individually fitted. During late February and early March, 2009, we captured 60 adult female deer utilizing helicopter net guns (Barrett et al. 1982, Krausman et al. 1985, White and Bartmann 1994) in conjunction with ongoing research addressing other objectives (Anderson and Freddy 2008). We captured 20 deer each in Ryan Gulch and Yellow Creek, and 10 deer each in South Magnolia and Story-Sprague study units (Fig. 1). Captured deer were hobbled, blind-folded, and ferried ≤5 km by helicopter to a central handling location. For each captured deer, we used transabdominal ultrasonography (SonoVet 2000, Universal Medical Systems, Bedford Hills, NY) to determine pregnancy status and number of fetuses (Stephenson et al. 1995, Bishop et al. 2007, Bishop et al. 2009). We also measured rump fat depth of each deer using ultrasonography and estimated a body condition score using palpation to estimate percent body fat (Stephenson et al. 2002, Cook et al. 2007). We measured mass by placing each deer on a stretcher and attaching the stretcher to a scale supported by a steel frame. We measured chest girth by placing a cloth tape around the chest immediately posterior to the front shoulders and recording measurement when deer exhaled. Last, we measured hind foot length of each deer and estimated age by evaluating tooth replacement and wear (Severinghaus 1949, Robinette et al. 1957). This aging technique is susceptible to measurement error (Hamlin et al. 2000). However, two trained observers, each with experience aging >1,000 deer in the field, estimated age of all deer in this study to minimize error and to insure that relative age differences across all deer in our sample were correctly captured in the data. We performed handling procedures in a wall-frame tent to create a dim environment for viewing ultrasound imagery. We fitted each pregnant deer with a radiocollar and VIT. Collar transmitters were turned off on Saturdays and Mondays to extend battery life for meeting other research objectives (Anderson and Freddy 2008). Each collar was equipped with a mortality sensor and store-on-board global positioning system (GPS). Mortality sensors were programmed to switch signal transmission from 60 pulses to 120 pulses per minute after remaining motionless for 8 hours. Each VIT had a temperature-sensitive switch and a pre-cut antenna (6 cm in length) with antenna tip encapsulated in a resin bead to eliminate sharp edges. The temperature-sensitive switch caused the VIT to increase pulse rates from 40 pulses to 80 pulses per minute when the temperature dropped below 32° C, which was indicative of VIT expulsion. We sterilized VITs in a chlorhexidine solution prior to insertion in the field. We inserted VITs using a clear, plastic swine vaginoscope (Jorgensen Laboratories, Inc., Loveland, CO) and alligator forceps. The 66 �vaginoscope was 15.2 cm long with a 1.59 cm internal diameter and had a smoothed end to minimize vaginal trauma. We placed vaginoscopes and alligator forceps in cold sterilization containers with chlorhexidine solution between each use and used a new pair of surgical gloves to handle the vaginoscope and VIT for each deer, and we applied lidocaine topically to the deer’s vagina to minimize irritation during VIT insertion. To insert a VIT, we folded the wings together and placed the VIT into the end of the vaginoscope. We liberally applied sterile KY Jelly to the scope and inserted it into the vaginal canal until the tip of the VIT antenna was approximately flush with the vulva. We used previous field experience to guide insertion distance and antenna length (Bishop et al. 2007). We extended alligator forceps through the vaginoscope to firmly hold the VIT in place while the scope was pulled out from the vagina. During winter and spring, we monitored live-dead status and general location of radiocollared adult females daily from the ground, except when collars were inactive, and biweekly from the air via fixed-wing aircraft. During June, we checked VIT signal status each morning of the week that radiocollars were active by aerially locating each radiocollared doe carrying a VIT. We began flights at approximately 0630 hours and completed them by 0900–1100 hours. Early flights were necessary to detect fast signals because temperature sensors of VITs expelled in open habitats and subject to sunlight often exceeded 32° C by mid-day, which caused VITs to switch back to a slow (i.e., prepartum) pulse (Newbolt and Ditchkoff 2009). When we detected a fast (i.e., postpartum) pulse rate, we ground-located the VIT and radiocollared doe in ≤3 hours using very high frequency (VHF) receivers and directional antennae. We attempted to observe behavior of the collared adult female, establish whether the VIT was shed at a birth site, and search for fawns in the vicinity of the adult female and expelled VIT. In cases where the dam moved away from the VIT (i.e., >200 m), we located the VIT to determine whether shedding occurred at a birth site and whether any stillborn fawns were present and subsequently located the collared dam to search for fawns at her location. We attempted to account for each dam’s fetus(es) as live or stillborn. We typically worked in pairs, which allowed us to effectively partition effort across the study area while maintaining efficiency when searching for neonates (i.e., two people were more effective locating a hidden neonate than one person). We described effort associated with locating fawns by calculating the number of person-hours per fawn. We also quantified cost per fawn by considering all operating and personnel expenses, including capture and VIT costs for adult females. All deer capture and handling procedures and use of VITs were approved by Colorado Division of Wildlife’s (CDOW) Institutional Animal Care and Use Committee (Project # 17-2008). We assigned the fate of each VIT to one of 4 categories: 1) retained (i.e., VIT expelled during parturition), 2) nearly-retained (i.e., VIT expelled ≤3 days prepartum), 3) not retained (i.e., VIT expelled >3 days prepartum), or 4) censored. We considered a VIT to be retained if it was expelled at or near a birth site in conjunction with parturition. For 75% of retention events, we located the VIT at a birth site and located neonate(s) near the VIT or in close proximity to the dam. In other cases, the VIT was not at a birth site but we readily found the dam and her newborn fawn(s) nearby, sometimes at a birth site 10−100 m from the VIT. In these situations, we considered a VIT retained if we documented <1-day-old fawn(s) <24 hours after the VIT was expelled. Finally, on two occasions, we considered a VIT retained because it was located at an evident birth site even though we could not locate fawns. Birth sites appeared as atypically large deer beds with soil appearing damp and with forbs and grasses flattened and radiating outward, consistent with a deer licking the site clean. On some occasions, fawns and/or placental remains were still present at birth sites when we arrived, providing positive confirmation of birth site characteristics. We distinguished VITs expelled ≤3 days prepartum as nearly-retained because they provided useful information for locating fawns, consistent with Bishop et al. (2007). We documented such cases by locating a dam’s neonate(s) one or more days after the VIT was expelled and comparing neonate age to VIT expulsion date. We estimated neonate age using hoof characteristics, condition of the umbilical cord, pelage, and behavior (Haugen and Speake 1958, Robinette et al. 1973, Sams et al. 1996, 67 �Pojar and Bowden 2004). We assumed a VIT was shed >3 days prepartum if the VIT was not at an evident birth site and we documented ≥2 of the following characteristics: 1) the adult female was located with other deer during repeated relocations for >3 days after the VIT was shed, 2) the adult female exhibited no behavioral cues indicating she had a fawn, 3) the adult female was noticeably still pregnant, and 4) we failed to locate a neonate following repeated searches for ≥1 week after the VIT was shed. We censored VITs from our retention analysis when adult females died prior to parturition or when adult females were located on private land that we did not have permission to access. In either case, we were unable to evaluate VIT retention to parturition. All females dying prior to parturition were still carrying the VITs upon death. We modeled VIT retention probability using a generalized logits model (i.e., multinomial logistic regression) in PROC LOGISTIC in SAS (SAS Institute, Cary, NC). We evaluated goodness-of-fit of the global model (i.e., model containing each predictor variable) by dividing model deviance by its degrees of freedom. We considered 3 levels of retention consistent with our description above (i.e., retained, nearlyretained, not retained) and we removed all censors from the dataset prior to analysis. Our primary purpose for this analysis was to evaluate whether our VIT design modifications increased VIT retention probability in larger deer. Our design modifications were based on the observation by Bishop et al. (2007) that VIT retention probability declined as deer body size increased. We modeled VIT retention as a function of mass (kg), hind foot length (cm), chest girth (cm), adult female age (yr), and body fat (%). We considered only linear models because we lacked a rationale for evaluating higher-order polynomial functions. Several of the variables we considered in our analysis were likely correlated because they represented different ways of expressing deer body size. We did not expect models comprising each of these variables to receive more support than simpler models. Thus, we focused our candidate model set on models with one or two variables. We evaluated all single-variable models plus we evaluated twovariable models that included age with each other variable. Age partially related to deer body size but age also related to number of times a female had previously given birth and possibly to behavioral differences among deer, either of which could have influenced retention probability. Thus, age tested hypotheses about retention probability that were not just related to body size or condition. We also considered several models with ≥3 variables to determine whether there was any support for models with higher numbers of parameters. We evaluated 13 models in total and we selected among models using Akaike’s Information Criterion adjusted for sample size (AICc; Burnham and Anderson 2002). We modelaveraged beta parameter estimates to incorporate model selection uncertainty when evaluating whether VIT retention probability varied as a function of the variables in our analysis. We did not model-average real parameter estimates because each of our predictor variables was continuous. We modeled fawn detection probability based on adult females that retained or nearly retained VITs. We planned to conduct separate analyses for singleton and twin litters, but we achieved perfect detection with singleton litters. We therefore modeled fawn detection probability considering only females with twin fetuses using a generalized logits model in SAS, and we evaluated goodness-of-fit by dividing model deviance by its degrees of freedom. We used 3 detection levels (0, 1, 2 fawns) and we modeled detection as a function of VIT retention status (retained vs. nearly-retained), VIT shed-day, adult female age, and vegetative cover at VIT expulsion site. Shed-day distinguished between VITs detected on fast pulse on Sundays and Tuesdays (dummy code = 1) and VITs detected on fast pulse during Wednesday−Friday (dummy code = 0). We used the shed-day variable to evaluate whether delayed response time, caused by our inability to monitor deer on Saturdays and Mondays, influenced our ability to detect fawns. We included adult female age in our analysis to evaluate if older females may have been more experienced at hiding fawns. Last, we used vegetative cover to evaluate if fawns were more difficult to detect in heavier cover. We expressed vegetative cover categorically as low, medium, or high based on a visual assessment at the site. Low cover class was characterized by limited understory and overstory vegetation with minimal visual obstruction at ground level (e.g., sparsely-vegetated grass, sagebrush, or mountain shrub slopes). Medium cover class was characterized by moderate to heavy 68 �vegetative cover within 1 m of the ground but limited cover above 1 m (e.g., typical sagebrush, mountain shrub sites). High cover class comprised moderate to heavy vegetative cover from ground level up to > 1 m with nearly complete visual obstruction (e.g., oakbrush, aspen-mountain shrub, dense serviceberry). We evaluated all single-variable models in addition to 4 models with ≥2 variables to determine whether there was any support for models with higher numbers of parameters. We evaluated 9 models in total and we selected among models using Akaike’s Information Criterion adjusted for sample size (AICc; Burnham and Anderson 2002). We did not model-average parameter estimates because it would have resulted in 10 different estimates of each level of fawn detection probability for a total of 30 probability estimates. These differences were not supported by the model selection results. We used our VIT retention and fawn detection probabilities to guide calculation of VIT sample sizes for planning future neonatal studies. We expressed the expected number of neonates to be encountered from a sample of VITs as: , where = neonate sample size. = sample size of adult females with VITs. = probability an adult female survives to parturition and is accessible. = probability an adult female retains her VIT to within 3 days of parturition given she survives to parturition and is accessible (i.e., VIT is retained or nearly retained). = probability adult female has twin fetuses. = probability 1 fawn is detected given an adult female retains her VIT and has twin fetuses. = probability 2 fawns are detected given an adult female retains her VIT and has twin fetuses. = probability 1 fawn is detected given an adult female retains her VIT and has one fetus. Since we had perfect detection with singleton litters and observed a high probability of detecting at least 1 fawn from twin litters, we simplified the above equation to: where is the probability of detecting at least 1 fawn, irrespective of litter size. Thus, given a targeted sample size of neonates, the estimated number of VITs required can be calculated as: We incorporated our estimates into the above equation to provide guidance for planning future studies. RESULTS AND DISCUSSION A retention wing of 1 VIT snapped at its base when the wings were squeezed together for placement into a vaginoscope, prior to insertion into a deer. No other retention wings exhibited any 69 �cracking or weakness when squeezed together, even after VITs were recovered from animals during spring and summer. Thus, we found this to be an isolated incident, and our resulting sample size was 59 deer with VITs. The probability that an adult female receiving a VIT in winter survived to parturition and was accessible (SAdF) was 0.797 (SE = 0.0529). We observed 9 adult female mortalities during winter and spring, and there was no evidence to suggest VITs were related to the mortality events. Four of the mortalities occurred within 1 week of capture and were likely capture-related. We were unable to groundmonitor 2 other adult females during the fawning period because they were located on private land that we did not have permission to access. One other adult female was inadvertently deleted from the aerial monitoring list due to miscommunication. We censored these 12 deer from our analysis of VIT retention because they did not permit evaluation of VIT retention to parturition, resulting in a sample size of 47 deer. Our global model of VIT retention probability (k = 12) adequately fit the data (deviance/df = 0.670, P = 0.991). The model of VIT retention probability with the lowest AICc included only the intercept (k = 2, ∆AICc = 0.00, wi = 0.331), although the model with deer age received some support (k = 4, ∆AICc = 1.42, wi = 0.163; Table 1). There was slight evidence that retention probability was lower in older deer ( = 0.169, SE = 0.256; Fig. 3). Also, there was slight evidence that retention probability was lower in larger deer ( = 0.086, SE = 0.171; Table 1). Based on the intercept-only model, the probability of a VIT being expelled during parturition (i.e., retained) was 0.766 (SE = 0.0605) and the probability of a VIT being expelled ≤3 days prepartum (i.e., nearly-retained) was 0.128 (SE = 0.0477). Thus, the probability of a VIT being retained to within 3 days of parturition (RVIT) was 0.894 (SE = 0.0441). Our global model of fawn detection probability (k = 12) adequately fit the data (deviance/df = 0.846, P = 0.730). The model of fawn detection probability with the lowest AICc included only the intercept (k = 2, ∆AICc = 0.00, wi = 0.600), whereas the model with the next lowest AICc included the VIT shed-day variable (k = 4, ∆AICc = 1.80, wi = 0.244; Table 2). Thus, we observed some evidence that fawn detection probability was influenced by our inability to monitor deer 2 days of the week ( = 0.537, SE = 0.738). The probability of detecting twins was 0.688 (SE = 0.114) when we located adult females <24 hours after their VITs switched to fast pulse, whereas twin detection probability was 0.500 (SE = 0.115) when our response time was delayed due to irregular monitoring. There was no evidence that probability of fawn detection was influenced by dam age or vegetative cover. Also, fawn detection probability did not meaningfully differ between females with retained and nearlyretained VITs. We detected 58 neonates and 2 stillborns from 42 adult females (1.4 neonates/female) that retained or nearly retained VITs. We detected a neonate from each adult female that had 1 fetus ( , n = 8). For adult females with twin fetuses (n = 34), based on the intercept-only model, ) was 0.353 (SE = 0.0803) and the probability of detecting the probability of detecting 1 neonate ( ) was 0.588 (SE = 0.0827). Combining litter sizes, the probability of detecting at least 1 twins ( ) was 0.952 (SE = 0.0334). The probability of an adult female having twin fetuses (TAdF) neonate ( was 0.810 (SE = 0.0613). On average, we located one neonate or stillborn per VIT in our initial sample (nNeo = 60, nVITs = 59). Thus, inputting our estimates into our sample size equation, we found that VIT sample size should roughly equal the targeted neonate sample size: 70 �We expended roughly 700 person-hours during the fawning period to locate 58 neonates and 2 stillborns, or approximately 12 person-hours per fawn located. This estimate includes hours spent searching for fawns from adult females that expelled VITs >3 days prepartum, although we were never successful in these attempts. We expended $31,000 to net-gun our sample of adult females, $15,000 on VITs, $10,000 on fixed wing monitoring, and $20,000 on personnel. Thus, we expended approximately $1,267 per neonate located. We did not include adult female radio collars in this cost estimate because we used GPS collars to meet other research objectives, yet VHF collars would have sufficed for locating neonates. Assuming VHF collars were used on adult females at a rate of $250 per collar, our cost estimate is approximately $1,520 per fawn. Our wing modification increased VIT retention in adult female mule deer. Our results are consistent with Haskell et al. (2007), who observed 81% retention (17/21) in the final year of their study after lengthening VIT wings and preventing antennas from protruding >1 cm past the vulva. Our study expanded on Haskell et al. (2007) by incorporating VIT wing modifications into the manufacturing process and conducting a focused field evaluation of those modifications. Investigators using the original VIT wing design in mule deer observed much lower rates of retention than we observed (Johnstone-Yellin et al. 2006, Bishop et al. 2007, Haskell et al. 2007). Using the original design, Bishop et al. (2007) found that the probability of VIT expulsion during parturition was 0.447 (SE = 0.0468), and the probability of VIT expulsion during parturition or ≤3 days prepartum was 0.623 (SE = 0.0456). We employed the same methodology as Bishop et al. (2007), except for the wing modification. Our study area was 100 km north of where Bishop et al. (2007) conducted their study. Assuming the 2 studies are comparable, our wing modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). The intercept-only model of VIT retention probability received the most Akaike weight, which is partly a reflection of our limited sample size. However, overall high rates of retention likely explain why we did not observe any strong relationships between VIT retention and deer body size. Bishop et al. (2007) found that larger deer were more likely to expel VITs prematurely, which was our basis for modifying VIT wings and conducting this study. Our results suggest the wing modifications effectively reduced premature expulsion, particularly in larger deer (Fig. 4). We documented a high probability of detecting at least 1 fawn from adult females that retained or nearly retained VITs, regardless of litter size. When a VIT was shed and evidence suggested the adult female was near parturition or had already given birth, we conducted intense searches up to 1 hour in length for successive days until a fawn was found. Thus, irrespective of vegetative cover or other covariates we assessed, we usually found a fawn when a VIT was adequately retained because it focused our search effort. Our likelihood of detecting twins was somewhat lower, in part because of our irregular monitoring schedule. However, other factors explain why twin detection probability was lower. First, our search intensity decreased when searching for a second fawn. For example, if we had searched most of an hour before detecting the first fawn, we typically limited our search time for a second fawn to minimize our disturbance to the adult female. Second, we did not place radio collars on fawns, and therefore, we could not relocate radiocollared fawns to search for their siblings. The technique of relocating a radiocollared fawn to locate its sibling was found to be successful in a previous study in Colorado (Bishop et al. 2009). During this earlier study, when a dam was known to have twin fetuses yet only one fawn was located and radiocollared during the initial capture attempt, the sibling fawn was found 45% of the time (10/22) by relocating the initial radiocollared fawn 1−2 days post-capture (C. J. Bishop, CDOW, unpublished data). Based on this rate, we would expect our probability of detecting both fawns from twin litters to be roughly 0.77 had we radiocollared fawns during our study. We found that our sample size of detected neonates roughly equaled our sample size of VITs, which provides a useful guide for planning future research using our modified wing design. However, 71 �this recommendation may overestimate VIT sample size because of our lower rate of twin detection and because adult female survival was lower than we anticipated. Fortunately, accessibility of adult females was higher than expected considering we lacked permission to access a large tract of land in the middle of summer range. Bishop et al. (2007) observed 0.97 survival of adult females to parturition and 0.99 were accessible during fawning (SAdF = 0.95). Adult female survival and accessibility is specific to study area. Twinning probability may also vary regionally. We therefore recommend use of the following equation for planning VIT sample size that incorporates information specific to the study area or region of interest: Bishop et al. (2007) expended 7 person-hours per captured fawn from adult females with successful VITs, 16 person-hours per fawn from females with partially successful VITs, and 42 personhours per fawn from females with failed VITs and females not receiving VITs. Given their observed VIT success rates, Bishop et al. (2007) would have required approximately 1,315 person-hours to locate 60 neonates, or 22 person-hours per fawn. Assuming these studies are comparable, increased VIT success associated with our modified wing design resulted in a 45% reduction in labor required to locate a fawn from a radiocollared adult female. The VIT technique is effective but expensive to employ. Actual cost of the technique, however, depends on what costs are already incurred to meet other research objectives. For example, in Colorado and elsewhere, researchers have begun estimating late-winter deer body condition as a response variable to accompany survival estimates. In these cases, adult female capture and radio collar costs are already accounted for in the base study, and thus, incorporation of VITs to facilitate neonate capture becomes much more cost-effective. In our study, where adult female capture and collar costs were covered by ongoing research efforts, the added cost of incorporating VITs and neonate capture was $750 per fawn. SUMMARY Use of VITs in well-designed field studies should increase our understanding of factors limiting deer populations by allowing investigators to link fawn production and survival to dam characteristics under free-ranging conditions. A primary drawback of VITs in deer has been the failure of many adult females to retain VITs to parturition. We increased VIT retention in mule deer by lengthening and widening wings used to retain a VIT in the vaginal canal. Researchers employing VITs with our modified wing design should require minimal oversampling to offset failures caused by early expulsion, thereby rendering the technique more cost-effective and reliable. Our findings provide explicit guidance for planning a fetal-neonatal deer study involving VITs. The question remains as to whether premature expulsion of VITs can be eliminated in mule deer. We observed modest evidence that deer expelling VITs >3 days prepartum were older and larger than deer that retained or nearly-retained VITs. We therefore recommend manufacturing slightly larger wings for large, older mule deer (e.g., >65 kg and >5 yrs old) as a possible strategy to further investigate VIT retention. LITERATURE CITED Anderson, C. R., and D. J. Freddy. 2008. 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Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a netgun. Wildlife Society Bulletin 13:71−73. Newbolt, C. H., and S. S. Ditchkoff. 2009. Effects of environmental conditions on performance of vaginal implant transmitters. Journal of Wildlife Management 73:303−305. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Robinette, W. L., C. H. Baer, R. E. Pillmore, and C. E. Knittle. 1973. Effects of nutritional change on captive mule deer. Journal of Wildlife Management 37:312−326. Robinette, W. L., D. A. Jones, G. Rogers, and J. S. Gashwiler. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134−153. 73 �Saalfeld, S. T., and S. S. Ditchkoff. 2007. Survival of neonatal white-tailed deer in an exurban population. Journal of Wildlife Management 71:940−944. Sams, M. G., R. L. Lochmiller, E. C. Hellgren, W. D. Warde, and L. W. Varner. 1996. Morphometric predictors of neonatal age for white-tailed deer. Wildlife Society Bulletin 24:53−57. Severinghaus, C. W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195−216. Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557−564. Stephenson, T. R., J. W. Testa, G. P. Adams, R. G. Sasser, C. C. Schwartz, and K. J. Hundertmark. 1995. Diagnosis of pregnancy and twinning in moose by ultrasonography and serum assay. Alces 31:167−172. White, G. C., and R. M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248−252. White, M., F. F. Knowlton, and W. C. Glazener. 1972. Effects of dam-newborn fawn behavior on capture and mortality. Journal of Wildlife Management 36:897−906. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 74 �Figure 1. Location of winter and summer range study areas in Piceance Basin and Roan Plateau, northwest Colorado. Winter range study units where we captured and radio-marked mule deer are noted as: YC = Yellow Creek, RG = Ryan Gulch, SM = South Magnolia, and SS = Story-Sprague. 75 �A B Figure 2. Three-dimensional view (A) and dimensions (B) of a modified retention wing used to retain vaginal implant transmitters in adult female mule deer. The displayed dimensions at bottom include a nylon core with an elastomeric overmold that protects deer from any sharp or rigid edges. 76 �Figure 3. Estimated probability and 95% confidence interval of adult female mule deer retaining vaginal implant transmitters (VITs) to within 3 days of parturition as a function of deer age in northwest Colorado. 77 �Figure 4. Estimated probabilities and 95% confidence intervals of adult female mule deer retaining vaginal implant transmitters (VITs) to within 3 days of parturition as a function of deer body mass in Colorado using original (solid line, Bishop et al. 2007) and modified (dashed line, this study) VIT retention wings. 78 �Table 1. Model selection results, based on Akaike’s Information Criterion with small sample size correction (AICc), from an analysis of vaginal implant transmitter (VIT) retention in adult female mule deer as a function of adult female age (yr), mass (kg), hind foot length (cm), chest girth (cm), and body fat (%) in northwest Colorado, USA, 2009. Model k AICc ∆AICc wi Intercept only 2 70.58 0.00 0.331 Age 4 72.00 1.42 0.163 Foot length 4 72.88 2.30 0.105 Age, fat 6 72.96 2.39 0.100 Mass 4 73.57 2.99 0.074 Fat 4 73.66 3.08 0.071 Chest girth 4 73.79 3.21 0.066 Age, chest girth 6 75.10 4.52 0.035 Age, foot length 6 75.45 4.88 0.029 Age, mass 6 76.32 5.74 0.019 Age, foot length, chest girth 8 78.53 7.95 0.006 79 �Table 2. Model selection results, based on Akaike’s Information Criterion with small sample size correction (AICc), from an analysis of fawn detection probability associated with adult females that retained or nearly-retained vaginal implant transmitters (VITs) in northwest Colorado, 2009. We modeled detection probability as a function of VIT retention status (retained vs. nearly-retained), adult female age (yr), the day of the week VITs were shed (i.e., shed-day), and amount of vegetative cover at VIT shed sites. We evaluated detection probability relative to shed day because we were unable to monitor radio signals on Saturdays and Mondays. Model k AICc ∆AICc wi Intercept only 2 61.94 0.00 0.600 Shed-day 4 63.74 1.80 0.244 Retention status 4 66.07 4.13 0.076 Age 4 66.26 4.32 0.069 Cover 6 70.46 8.52 0.008 Shed-day, cover 8 73.22 11.28 0.002 Shed-day, cover, retention status 10 79.53 17.59 0.000 Age, shed-day, cover 10 80.24 18.30 0.000 80 �Colorado Division of Wildlife July 2009 – June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 2 Federal Aid Project No. W-185-R : : : : Division of Wildlife Mammals Research Deer Conservation Evaluation of Winter Range Habitat Treatments On Over-winter Survival and Body Condition of Mule Deer Period Covered: July 1, 2009 - June 30, 2010 Author: E.J. Bergman; project cooperators, C.J. Bishop, D.J. Freddy, G.C. White and P. Doherty Personnel: C. Anderson, L. Baeten, D. Baker, B. Banulis, J. Boss, A. Cline, D. Coven, M. Cowardin, K. Crane, R. Del Piccolo, B. deVergie, B. Diamond, K. Duckett, S. Duckett, J. Garner, D. Hale, C. Harty, A. Holland, E. Joyce, D. Kowalski, B. Lamont, R. Lockwood, S. Lockwood, D. Lucchesi, D. Masden, J. McMillan, M. Michaels, G. Miller, Mike Miller, Melody Miller, C. Santana, M. Sirochman, T. Sirochman, M. Stenson, R. Swygman, C. Tucker, D. Walsh, S. Waters, B. Watkins, P. Will, L. Wolfe, V. Yavovich, K. Yeager, M. Zeaman CDOW, L. Carpenter - Wildlife Management Institute, D. Felix, L. Felix - Olathe Spray Service, P. Johnston, M. Keech, D. Rivers, J. Rowe, L. Shelton, M. Shelton, R. Swisher, S. Swisher - Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We completed a five year, multi-area study to assess the impacts of landscape level winter range habitat improvement efforts on mule deer population performance. This study took place on the Uncompahgre Plateau and in adjacent valleys in southwestern Colorado. We measured over-winter fawn survival and total deer density annually on 5 study areas. Four study areas were permanently located, whereas location of the fifth area varied each year to reflect the range of variability in habitat treatments across the southern half of the Uncompahgre Plateau. Additionally, on 2 of the study areas we estimated late winter body condition of does. Compared to results from other research throughout the West, as well as on the Uncompahgre Plateau, survival estimates for 6-month old mule deer fawns were highly variable between areas, and tended to be near published long term averages (mean survival rate of 0.59 (0.04 SE)). Preliminary evidence suggests that areas that have received habitat treatments have higher fawn survival. Based on estimates of total body fat for adult female deer, there was a slight distinction between treatment and reference study areas. Point estimates of deer density on the study areas varied between winters, but in general density estimates did not show a trend between years. Major fluctuations within density estimates are likely attributable to animal movements. All final analyses will be completed during the fall of 2010 and submitted to peer-reviewed publication upon completion. 81 �WILDLIFE RESEARCH REPORT EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER ERIC J. BERGMAN P.N. OBJECTIVES To determine experimentally whether mechanical/chemical treatments of native habitat vegetation will increase over-winter mule deer fawn survival, adult doe body condition, and localized deer densities on the Uncompahgre Plateau in southwest Colorado and to conduct a simulation based optimization study to determine optimal foraging and movement strategies of deer under variable environmental and habitat conditions. SEGMENT OBJECTIVES 1. Complete all field efforts associated with the assessment of mechanical/chemical treatments on survival and body condition of deer. 2. Complete first segment of academic dissertation requirements of PhD requirements through Colorado State University. 3. Initiate final analyses for survival, density and body condition components of the study. 4. Complete preliminary narrative for optimal foraging and movement strategy work. INTRODUCTION A common trend among many terrestrial, mammalian systems is a tendency to cycle between population highs and lows (Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001, Clutton-Brock and Pemberton 2004). While the true cause of these cycles is likely a merger of habitat quality, weather, disease, predation, sport hunting, competition and community population dynamics, it is often necessary or intriguing for wildlife managers and ecologists to identify the primary limiting factor to population growth. Without exception, mule deer populations have also demonstrated a tendency to show large fluctuations. Several dramatic declines have been observed since the turn of the 19th century (Connolly 1981, Gill 2001, Hurley and Zager 2004). However, only one period of increase, a general trend during the 1940's and 1950's, has been noted. The most recent and pressing decline took place during the 1990's (Unsworth et al. 1999). Colorado has not escaped these tendencies, with certain parts of the state experiencing population declines by as much as 50% between the 1960's and present time (Gill 2001, B. Watkins personal communication). Primarily due to the value of mule deer as a big game hunting species, wildlife managers' challenges are two-fold: understanding the underlying causes of mule deer population change and managing populations to dampen the effects of these fluctuations. In Colorado, the role of habitat as the limiting factor for mule deer populations was recently tested. Specifically, the role of forage quality and quantity on over-winter fawn survival was tested using a treatment/reference cross-over design with ad libitum pelleted food supplements as a substitute for instantaneous high quality habitat improvements (Bishop et al. 2009). The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e. if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the primary limiting factor on populations. As such, nutrition enhancement treatments increased fawn survival rate by 0.22 (Bishop et al. 2009). This research effectively identified some of the underlying processes in mule deer population regulation, but did not test the effectiveness of acceptable habitat management techniques. Due to the undesirable effects of feeding 82 �wildlife (e.g. artificially elevating density, increased potential for disease transmission and cost), a more appropriate technique for achieving a high quality nutrition enhancement needs to be assessed. We designed and initiated a multi-year, multi-area study to assess the impacts of landscape level winter range treatments on mule deer population performance. We conducted the study on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado because this area had an active history of habitat treatments that were implemented in part to enhance deer populations. To assess the impacts of habitat treatments on mule deer in these areas, we measured over-winter fawn survival, mule deer density and late winter body condition. STUDY AREA At the onset of this study (Bergman et al. 2005), we identified 2 pairs of treatment/reference study areas, stratified into historically known high and low deer density areas. The selection process for these pairs of experimental units followed several strict guidelines: 1) Treatment/reference units could not be further than 10km apart, but needed to have adequate buffer to minimize the movement of animals between the treatment and reference areas. 2) Reference study areas could not have received any mechanical treatment during the past 30 years. 3) Strata were defined by winter range type (all experimental units had to be in pinyon/juniper winter range) and deer density. 4) Treatment units needed to have received mechanical treatment in the past, but also had to be capable of receiving further treatments during the study period. Each winter a 5th study area was added to increase the level of inference that could be drawn from this study. For each of the 4 winters covering the study period, this 5th study area shifted between 4 randomly selected areas. The treatment history on each of these additional study areas varied, but was representative of what can be expected of typical winter-range treatments. During the first winter of this study, this 5th study area fell on Shavano Valley. Treatments on Shavano Valley were primarily composed of roller-chopping in the higher pinyon/juniper range and were reseeded with browse species. During the second winter of the study, the 5th study area fell on the Colona Tract (~5km2) of Billy Creek State Wildlife Area (approximately 15km south of Montrose, CO). The treatment history of Colona Tract was primarily composed of brush mowing and chemical control of weeds and dry land fertilization of preferred species. During the third winter of the study, the 5th study area was located at McKenzie Buttes. The treatments at McKenzie Buttes were slightly older (10-15 years) and were also composed of rollerchopping. During the final year of the study, the 5th study area was located at Transfer Road. The treatments available to deer at Transfer were younger (1-2 years) and were composed of hydro-ax and some roller-chopping. The high density treatment area was located on the Billy Creek tract of Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). The high density reference area was located around Beaton Creek (approximately 15km south of Montrose, CO and approximately 5km north of Billy Creek State Wildlife Area). Both of the high density study areas were located in GMU 65 (DAU D-40). The low density treatment area was located on Peach Orchard Point, on/near Escalante State Wildlife Area (approximately 25km southwest of Delta, CO). The low density reference area was located on Sowbelly and Tatum draws (approximately 25km west of Delta, CO and approximately 8km from Peach Orchard Point). Both of the low density study areas were located in GMU 62 (DAU D-19). All of the other study areas, mentioned above, were also located in GMU 62 (DAU D-19) to the west of Montrose, CO. 83 �METHODS Twenty-five mule deer fawns were captured and radio-collared in each of the 5 study areas. Fawns were captured via baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) and helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) between mid-November and lateDecember. To make fawn collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars after approximately 6 months. On a daily basis, from December through May, we monitored the radioed fawns in order to document live/death status. This allowed us to determine accurately the date of death and estimate the proximate cause of death. Daily monitoring was done from the ground to maximize efficient collection of mortalities and assessment of cause specific mortality. Weekly aerial telemetry flights were conducted to insure that all deer were heard at least once a week, allowing weekly survival estimates for each study area. To estimate body condition, an additional 30 adult female deer were captured via helicopter netgunning and fitted with temporary neckbands, in late-February within each of the 2 high density study areas. For body condition work, we relied on methods that employed the use of ultrasonography to estimate total body fat (Stephenson et al. 1998, Cook 2000, Stephenson et al. 2002). Blood samples were also collected for endocrinology and pregnancy tests. During late winter (early-March) we estimated deer density on each of our study areas. Helicopter based mark-resight techniques were used for density estimation (Gill 1969, Bartmann et al. 1986, Kufeld et al. 1980, Freddy et al. 2004). Preliminary survival analyses were conducted on all years of data. In addition to including individual covariates (fawn sex and mass), we explored the role of habitat treatment history on survival. Due to the preliminary nature of these analyses and the ongoing status of the habitat treatment work, we did not attempt to rank individual study areas. Estimating survival for study areas was done in 5 different forms. The simplest form was constant survival where all study areas were pooled and survival was estimated using a single parameter (hereafter “constant”). The second simplest form was to estimate survival for each unique study area (i.e., 8 survival estimates were generated, hereafter “area”). The remaining 3 forms allowed study areas to be partitioned according to treatment history. The simplest of these forms was a comparison between treatment areas and reference study areas in which each study areas was partitioned into one of these two categories (i.e., two survival parameters, hereafter “treatment/reference”). The next simplest of these forms segregated study areas by treatment type. In this form, study areas were either reference areas (no treatment), management treatments (areas that received a typical management treatment at some point during the past 10 years), or repeated treatments (areas that received a typical management treatment but also received additional and repeated efforts in an attempt to force treatment effect). Thus, in this form (hereafter “treatment type”), the number of parameters dedicated to estimating survival rates across all study areas was 3. The final form followed the “treatment type” form, but further partitioned study areas according to a density/treatment gradient. A total of 5 parameters were used to estimate survival (high-density repeated treatment, high-density reference, management treatment, low-density super treatment and low-density reference, hereafter “treatment type by density”). All survival models were evaluated in program MARK using the known-fate model type with logit link function (White and Burnham 1999). All models were compared using Akaike's Information Criterion corrected for small sample size (Burnham and Anderson 2003). 84 �All preliminary abundance and density estimates were computed using program NOREMARK (White 1996). With the advancement of abundance theory and with improvements in software, abundance and density estimates will also be computed using Mark Resight models in program MARK (White and Burnham 1999). RESULTS AND DISCUSSION Preliminary survival models indicate that the individual parameter most influencing over-winter fawn survival was fawn mass (Table 1). Fawn sex did not appear to add much additional strength or support to any given model. Of particular interest to this study is that models incorporating study area treatment level were among the top performing models for the entire suite of models run, and the most supported model took treatment type by density into account. Closely competing with this model was one which estimated a constant survival rate, but thereby benefited by estimating 4 fewer parameters. The strongest model support for the model that estimated survival rates according to the treatment type by density structure lends credence to the study design and will likely become refined with a more complete analysis. Late winter body condition estimates for adult females were consistent during all years of this study, but they tended to be higher than those estimates during previous research on the Uncompahgre Plateau (Bishop et al. 2009 and C.J. Bishop, personal communication). The lowest single total percent body fat estimate for this study was recorded during the final winter, despite the fact that observations of winter severity indicated that body fat estimates likely should have been higher. For the two study areas where body condition estimates were measured, they did have a tendency to reflect the same trends that were observed in survival estimates. However, there was no apparent statistical distinction in total percent body fat between our study areas. This lack of distinction was also observed in the levels of the T3 hormone, but not in the T4 hormone (nmol/l) (Table 2). Pregnancy rates were surprisingly variable during this study (Table 2). Density estimates were collected during March for all five study areas, during all years of the study. No major modifications were made to the field methodology, however, addition of new models into program MARK (White and Burnham 1999) allow for comparisons to occur with abundance/density estimates generated in program NOREMARK (White 1996). These analyses have not been completed. However, a summary of the 4 years of data include the observation that the variance surrounding abundance estimates of each study area are higher than expected. Enough data do not exist to isolate the variance components of these estimates. Overall, no major changes in abundance, in any of the study areas, are believed to have occurred. Progress towards completion of the requirements for a PhD was also made during the 2009-2010 year. As of summer 2010, an additional 3 classes and a total of 14 credits are needed to complete the scholastic requirements. A draft study plan regarding the optimization of deer movement and foraging behavior was developed, but expansion of these ideas and simulation modeling techniques can be expected during the 2010-2011 year (Appendix I). SUMMARY Survival rates for mule deer fawns across our study areas averaged 59% with a measured high of 65% and measured low of 38%. Overall body condition parameter estimates for late-winter adult female deer were moderately low, which did not coincide with the milder winter conditions that were observed throughout deer winter range in Colorado. Pregnancy rates were slightly lower, but still within the long term range of observed data. Estimates of total deer density across our study areas continued to reflect historical estimates, but a dramatic early spring shift in movement was observed on one study area. 85 �Overall, a consistent trend of higher survival of fawns was observed in treated study areas, indicating winter range treatments likely have a positive effect on survival. The magnitude and overall population effect of these impacts will be quantified during the next 12-18 months. LITERATURE CITED Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M., L.H. Carpenter, R.A. Garrott, and D.C. Bowden. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. —————, G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. Bergman, E.J., C.J. Bishop, D.J. Freddy, G.C. White. 2005. Pilot evaluation of winter range habitat treatments of mule deer fawn over-winter survival. Wildlife Research Report July: 23-35. Colorado Division of Wildlife, Fort Collins, USA. Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172. Burnham, K.P. and D.R. Anderson. 2003. Model selection and multi-model inference. Springer, New York, USA. Clutton-Brock, T., and J. Pemberton, editors. 2004. Soay sheep: dynamics and selection in an island population. Cambridge University Press, UK. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. Cook, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain Elk. Thesis, University of Idaho, Moscow, USA. Freddy, D.J., G.C. White, M.C. Kneeland, R.H. Kahn, J.W. Unsworth, W.J. DeVergie, V.K. Graham, J.H. Ellenberger, and C.H. Wagner. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. Gill, R.B. 1969. A quadrat count system for estimating game populations. Colorado Division of Game, Fish and Parks, Game Information Leaflet 76. Fort Collins, USA. ————— 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Hurley, M., and P. Zager. 2004. Southeast mule deer ecology - Study I: Influence of predators on mule deer populations. Progress Report, Idaho Department of Fish and Game, Boise, USA. Jedrzejewska, B., and W. Jedrzejewski. 1998. Predation in Vertebrate Communities: the Białowieża Primeval Forest as a case study. Springer-Verlag, Berlin, Germany. Krebs, C.J., S. Boutin, and R. Boonstra, editors. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. Kufeld, R.C., J.H. Olterman, and D.C. Bowden. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. Ramsey, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. Schmidt, R.L., W.H. Rutherford, and F.M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. Stephenson, T.R., V.C. Bleich, B.M. Pierce, and G.P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. 86 �————— , T. R., K. J. Hundertmark, C. C. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717722. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, C.C. 1996. NOREMARK: population estimation from mark-resighting surveys. Wildlife Society Bulletin. 24:50-52. White, G.C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Prepared by Eric J. Bergman, Wildlife Researcher 87 �Table 1. Preliminary survival model results for radio collared fawns on the Uncompahgre Plateau. Model ŝ (Treatment Type by Density) + mass ŝ (Constant) + mass ŝ (Treatment Type by Density) + sex + mass ŝ (Treatment/Reference) + mass ŝ (Treatment Type) + mass ŝ (Constant) + sex + mass ŝ (Treatment/Reference) + sex + mass ŝ (Treatment Type) + sex + mass ŝ (Area) + mass ŝ (Area) + sex + mass ŝ (Treatment Type by Density) ŝ (Treatment Type by Density) + sex ŝ (Area) ŝ (Area) + sex ŝ (Constant) ŝ (Treatment Type) ŝ (Constant) + sex ŝ (Treatment/Reference) ŝ (Treatment Type) + sex ŝ (Treatment/Reference) + sex AICc 1293.577 1294.706 1294.712 1295.336 1295.557 1295.724 1296.047 1296.457 1298.547 1299.686 1319.598 1320.269 1323.900 1324.675 1324.726 1324.915 1325.300 1325.317 1325.545 1326.176 ∆AICc 0.000 1.129 1.135 1.759 1.980 2.147 2.470 2.880 4.970 6.109 26.021 26.693 30.324 31.098 31.149 31.338 31.723 31.741 31.968 32.599 ωi 0.255 0.145 0.145 0.106 0.095 0.087 0.074 0.060 0.021 0.012 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 k 6 2 7 3 4 3 4 5 9 10 5 6 8 9 1 3 2 2 4 3 Table 2. Late-winter body condition estimates for female adult mule deer on the Uncompahgre Plateau. Sample sizes were 30 does in each area. Mean T3 and T4 samples are reported in nmol/l. Parameters marked with an asterisk designate a significant difference between areas at the 0.05 level. Year 2005-2006 2006-2007 2007-2008 2008-2009 Parameter % Body Fat T3* T4 % Body Fat T3 T4 % Body Fat T3 T4* % Body Fat T3 T4* Billy Creek 8.80% (2.02) 1.12 (0.28) 70.69 (20.94) 7.61% (1.94) 1.55 (0.53) 88.23 (19.53) 8.09% (1.10) 1.17 (0.28) 94.30 (20.7) 7.20% (1.85) 1.22 (0.32) 74.63 (14.61) 88 Buckhorn N.A. N.A. N.A. 7.03% (1.80) 1.42 (0.31) 78.07 (22.34) 7.20% (1.69) 1.17 (0.56) 56.20 (23.30) 6.25% (1.63) 1.26 (0.35) 54.77 (19.34) Sowbelly 9.81% (2.88) 1.41 (0.51) 79.97 (15.80) N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. �APPENDIX I Optimizing mule deer winter range treatments: allocating resources in highly dynamic and stochastic systems Introduction During the past three decades, wildlife and habitat managers have extensively worked to improve habitat for wildlife. With the development and incorporation of more sophisticated equipment into landscape management, the state of the art has progressed and evolved over the past three decades. However, two primary assumptions often underlying and justifying these efforts have been that landscape treatments benefit wildlife and that when delivered, landscape treatments are utilized by wildlife. The focus of this chapter will be to delve into the latter of these two assumptions and to explore the likelihood that when delivered, habitat treatments will be utilized. This chapter will have two primary objectives. The first objective will utilize simulation and optimality modeling (Mangel and Clark 1989) to determine under what conditions mule deer would be most benefited by moving into a landscape that has been altered. As a case scenario, in western Colorado there is strong evidence that mule deer population performance is limited by winter range forage conditions. In cases where winter range forage is abundant and of high quality, there is circumstantial evidence that deer move down from summer and transition range regardless of habitat or weather conditions at higher elevations. In most of these cases, agricultural fields compose at least a nominal proportion of available winter range. Current dogma suggests that earlier movements by deer are directed at capitalizing on vestigial forage in these fields which is typically of high nutritional content. Of equal importance/concern to wildlife managers under this scenario is the movement of deer onto winter range when agricultural fields are absent. These are the areas where habitat improvement efforts are most commonly focused, in an effort to increase the local carrying capacity and to help stabilize populations. However, a largely unknown component to the effectiveness of landscape treatments pertains to the ability or willingness of deer to utilize treatment areas. An underlying assumption of deer movement and habitat selection behavior is that most individuals in a population make the best decision possible under the given circumstances. As such, deer in areas without high quality winter range can be expected to have made movement decisions based on the quality, abundance and availability of forage on summer and transition ranges. By modeling individual behavior (and its inherent variability), we hope to learn under what conditions a herd would most likely utilize and benefit from habitat improvements in areas that have not historically been used by deer. In particular to the second objective of this study, we wish to use stochastic dynamic programming and simulation models to establish a decision-theoretic framework for landscape managers to apply in the a priori selection and delivery of winter range landscape treatments for mule deer (Williams et al. 2001). There are a great number of factors that determine the quality of a mule deer herd from a manager’s perspective. Under most settings, wildlife managers’ objectives are typically to increase herd productivity or to stabilize a declining herd. However, there are costs associated with all management decisions. In the case of landscape management for mule deer, the primary cost is financial. With finite monetary resources available for landscape management, a manager needs to know with as much certainty as possible if a landscape treatment will benefit deer. The opportunity cost of delivering a treatment to one herd is typically that a treatment cannot be delivered to another herd. But in light of environmental stochasticity, uncertainty remains high under the best of circumstances. 89 �Methods To address this optimal movement behavior question, I will use stochastic dynamic programming methods. I believe four key factors influence a deer’s decision to move from summer and transition range onto winter range. Of these factors, the suitability of summer/transition range will be modeled purely as a stochastic variable. Availability of summer range is heavily dependent on weather conditions with harsh weather driving availability/suitability down and mild weather making range more accessible. Winter range forage quality, the second key factor, is also dynamic as a result of management efforts. Typically efforts to improve winter range quality are realized 1-2 years after an application as effectiveness is dependent on growing conditions. However, an element of stochasticity must also be present in this factor as during the most extreme winters, availability is further depressed. The third factor, number of competitors, is also dynamic but largely non-stochastic. Typically a trend of increase or decrease is observed in number of deer during consecutive winters. The fourth factor, cost of movement, is a merger of the other factors and is ultimately linked to an individual deer’s body condition. While the most nebulous from a management standpoint, this is potentially the most influential factor that motivates a deer to either vacate or continue to occupy summer/transition range. For an overview of my thinking thus far, please see Figure A1. To address the second objective of this work, I wish to identify a management structure for landscape enhancement from an adaptive standpoint. As understanding of deer movement behavior is pursued through an optimality modeling framework, circumstances conducive to deer use of winter range should be identified. From a management standpoint, an optimal decision framework for when and where landscape treatment efforts should be most useful would be beneficial. Ideally habitat treatment manipulations can be structured under an adaptive management framework in which resources for manipulating winter range can be optimally allocated based on expected mule deer population response. To further these interests and to develop necessary skills, I hope to take classes on such modeling techniques during my studies. Literature Cited Clark, C.W. and M. Mangel. 1989. Dynamic modeling in behavioral ecology. Princeton University Press, USA. Williams, B.K., J.D. Nichols and M.J. Conroy. 2001. Analysis and management of animal populations. Academic Press, New York, USA. 90 �Deer on summer range must decide when to migrate to winter range – to choose wisely is to live, to chose poorly is to die Hard Winter = Poor Conditions, all deer move Average Winter = Average Conditions, all deer eventually move Mild Winter = Good Conditions, not all deer move Factors Influencing This Decision A) High Quality and Abundance (Move) Suitability of summer/transition range during winter (stochastic) High Quality but Poor Abundance (????) B) Winter Range Forage Quality and Quantity (our management tool) Poor Quality and Poor Abundance (Don’t Move) C) Number of Competitors Relative to Winter Carrying Capacity (stochastic with a trend) D) Poor Quality but High Abundance (????) Too Many (stay as long as possible) At Carrying Capacity (move based on condition and climate , stochastic) Below Carrying Capacity (move based on climate, stochastic) Cost of Movement Actual energetic (caloric) cost of movement doesn’t change, but impact of movement effects each individualt differently based on caloric Reserves, thus, this is stochastic Figure A1. Conceptual diagram depicting four key factors that influence a deer’s decision to move from summer/transitional range to winter range. The different levels and relative predictability of each factor are also depicted. Underlying assumptions to this conceptual diagram are that summer/transition range typically has higher quality and abundance of browse, winter range is always available and that deer can be expected to make the best decision given current resources and body condition. 91 �92 �Colorado Division of Wildlife July 2009 − June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2009 − June 30, 2010 Authors: C. J. Bishop, D. P. Walsh, M. W. Alldredge, E. J. Bergman, and C. R. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique should significantly reduce stress that is typically associated with capture and handling and eliminate capturerelated mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fullyfunctional prototype of the device. We will conduct an extensive field evaluation of the device with freeranging mule deer during 2010-11. 93 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, DANIEL P. WALSH, MATHEW W. ALLDREDGE, ERIC J. BERGMAN, AND CHUCK R. ANDERSON P. N. OBJECTIVE To develop and evaluate a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. SEGMENT OBJECTIVES 1. Work with a professional engineering firm to produce a fully-functional prototype of an automated collaring device for ≥6-month-old mule deer fawns. INTRODUCTION The Colorado Division of Wildlife (CDOW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240 deer fawns are captured annually to monitor survival among 4 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CDOW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., >$5,000 ea.) would reduce CDOW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described 94 �above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CDOW’s operating expenses and improve animal welfare. Therefore, our objective is to design, produce, and evaluate a fully-functional prototype of an automated collaring device for ≥6-month-old mule deer fawns. STUDY AREA We conducted all evaluations with captive deer at the FWRF in Fort Collins, Colorado. We conducted limited evaluations with free-ranging deer near Fort Collins in north-central Colorado. We plan to conduct extensive field evaluations with free-ranging deer in north-central Colorado and elsewhere in Colorado once a fully-functioning device is produced. METHODS We initially wrote a study plan and identified detailed device specifications to guide development of the automated collaring device. We approached Colorado State University’s Mechanical Engineering Department to discuss their interest in helping design such a device. In result, the collaring device became a senior design project for 6 CSU engineering students during the 2008-09 school year. We met with the students weekly and provided them a materials budget of $10,000 to produce a prototype device. We conducted staged evaluations of device components during the year by working with captive deer at FWRF. We also conducted limited evaluations with free-ranging deer near the end of the year. Field evaluations focused primarily on how deer utilized and interacted with the device to guide subsequent design and development decisions. We documented utilization and interactions using direct observation and motion-sensor digital cameras. We relied exclusively on digital cameras when we were not on-site during an evaluation. Automation of the collaring device was disabled any time we were not present to prevent any potential harm to deer. Following preliminary field evaluations, we refined our design specifications and developed a contract with Dynamic Group Circuit Design (DGCD), located in Fort Collins, Colorado, to produce a fully-functional prototype device. We routinely met with electrical engineers from DGCD, and a mechanical engineer subcontracted by DGCD, during the course of the year. These meetings ensured that our device specifications were being satisfactorily met from both engineering and deer biology perspectives. RESULTS AND DISCUSSION We produced a fully-functional prototype device that met our design specifications as set forth in the contract. The prototype device comprises an aluminum cage attached to a bait compartment. Deer enter the device through an adjustable opening at the front of the cage. The adjustable opening can be used to deter entry of larger animals by adjusting both width and height. The sides of the cage comprise one-way gates that prevent entry into the device but allow an animal to exit the device at any point. The bait compartment is accessed through an opening positioned at the rear of the cage. An expandable radio collar is placed in this opening by extending it around four rectangular, aluminum plates that hold the collar in the fully-expanded position (Fig. 1). Radio collars are made expandable by attaching springs to each end of the transmitter; that is, springs are used in place of belting on standard radio collars. Clear plexiglass separates the cage from the bait compartment to maximize visibility. A deer is able to extend its head and neck through the expanded radio collar positioned in the rear opening to access the bait in the bait compartment, which is the only access point to the bait (i.e., it cannot be reached by an animal outside of the device). The floor of the cage is a scale that continuously records weight and informs device operation. Only animals in a specified weight range can be collared, which allows the user to 95 �target fawns and avoid collaring adult deer. Specifically, the mechanism that releases the collar around a deer’s neck will not trigger when an animal is too heavy or too light. Also, an actuator moves a plexiglass plate into the space between the rear cage opening and the bait pan, preventing animals outside of the weight range from accessing the bait. Shortly after a non-target animal exits the device, the collar release mechanism is once again ready to fire and the actuator lowers the plexiglass plate so that the bait is accessible. To prevent an animal from being collared twice, a loop antenna is placed around the entrance to the cage and connected to a radio frequency identification (RFID) reader. All collars used with the device include a small RFID transponder sewn into the collar material. If a previously-collared fawn enters the cage, the RFID transponder is detected, which in turn prevents the collar from being released and activates the actuator to block access to the bait. If a deer enters the cage that is in the specified weight range and has not been previously collared, the collar will release around the deer’s neck once it accesses the bait. The collar release is triggered when a deer’s head breaks an infrared beam positioned immediately above the bait pan. The collar is released by activating a solenoid, which in turn releases a lever that causes the upper 2 aluminum plates holding the expanded collar in place to collapse (Figs. 2 and 3). The collar is then situated around the deer’s neck. When the collar is released, 2 different cameras are immediately activated to take a series of 3 photographs each. One camera is positioned in the back of the bait compartment and set to take a closeup photo of the top of the deer’s head. The second camera is positioned in the floor of the cage and set to take a photo of the deer’s abdomen and groin. These cameras are activated only when a collar is released and facilitate determination of deer sex. Last, when a collar is released, the device records and stores the weight of the deer. An external computer can be hooked up to the device to change program settings, remotely operate the device, and upload weight data. The device is powered by a 12 volt battery that must be recharged every 2-3 days assuming continuous operation. DGCD prepared a user’s manual that explains device operation and detailed schematics to allow future production. We will evaluate effectiveness of the device in the field during 2010-11. Initially, we will only set the device with a collar when we are present and able to directly observe deer interactions with the device. After collaring 5-10 animals in this manner and troubleshooting any problems with the device, we will set the device to operate remotely without an observer on-site, which is how it is intended to be used. SUMMARY We developed a fully-functional prototype of an automated collaring device for mule deer in collaboration with professional engineers. The automated collaring device is designed to allow biologists and researchers to radio-collar portions of their deer samples with minimal time and expense because no animal handling is required and deer can be collared at any time. Primary time commitments include baiting sites, moving device(s) among sites, and adding collars to the devices. The collaring device should also have distinct benefits for studies in urban environments by providing a non-invasive technique for collaring deer. The collaring device should significantly reduce stress that is typically associated with capture and handling and there should be no capture-related mortality. We also have designed the collaring device so that it should be relatively easy to adjust to target adult deer and other ungulate species. Last, the collaring device should have wide applicability for ungulate researchers and managers beyond Colorado. We will be evaluating the device in the field with free-ranging mule deer during the coming year and making additional modifications as necessary. 96 �LITERATURE CITED Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108−114. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 97 �Figure 1. View of the radio collar and bait compartment of an automated collaring device for mule deer. To reach bait, deer must extend their head and neck through the expanded radio collar. 98 �Figure 2. View of the collar release mechanism in an automated collaring device for mule deer. 99 �Figure 3. Female mule deer fawn accessing bait by extending her head through an expanded radiocollar. The prototype device will be evaluated extensively in the field with free-ranging deer during 2010-11. 100 �Colorado Division of Wildlife July 2009 –July 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project No. N/A : : : : : Division of Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates On the Uncompahgre Plateau Period covered: July 31, 2009−July 31, 2010 Author: K. A. Logan. Personnel: K. Logan, C. Burnett, B. Dunne, A. Greenleaf, J. Knight, R. Navarrete, J. Waddell, S. Waters, K. Crane, T. Mathieson, J. Koch, and T. Bonacquista of CDOW; S. Young and W. Wilson of U.S.D.A. Wildlife Services; volunteers and cooperators including: private landowners, Bureau of Land Management, Colorado State Parks, Colorado State University and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife initiated a 10-year study on the Uncompahgre Plateau in 2004 to quantify puma population characteristics in the absence (reference period, yrs 1-5) and presence (treatment period, yrs 6-10) of hunting. The purpose of the study is to evaluate assumptions underlying the Colorado Division of Wildlife’s model-based approach to managing pumas with sport-hunting in Colorado. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 pumas for population research purposes on the Uncompahgre Plateau (Logan 2009). This report informs on the first year of the treatment period (TY1), August 2009 through July 2010, on puma population characteristics and dynamics with hunting as a mortality factor. Puma sporthunting opened November 16 and closed December 11, 2009 after a quota of 8 independent pumas was harvested. The harvest was designed to test the management assumption that a 15% harvest of independent pumas results in a stable-to-increasing population. A total of 9 pumas were killed: 2 adult females, 1 subadult female, 5 adult males, and 1 dependent cub. The harvest of 8 independent pumas represented 15% of the expected (i.e., modeled) 53 independent pumas and 14.5% of the minimum number of 55 independent pumas counted 2009-10. Independent females and males comprised 37.5% and 62.5% of the harvest, respectively. Four other radio-collared pumas, 1 adult female and 3 adult male, in the study area population were killed in GMUs adjacent to the study area. The total harvest of 12 independent pumas represented 21.8% of the minimum count of independent pumas. Eight independent pumas will be the harvest quota for the 2010-11 hunting season (TY2). Seventy-nine hunters requested mandatory permits with an attached voluntary hunter survey in TY1. Seventy-one of the hunters provided responses to written (n = 43) or telephone call follow-up contact (n = 28). An estimated 67 hunters 101 �actually hunted on the study area, of which 13% harvested pumas and 24% captured pumas (i.e., harvested plus treed and released). All hunters responded that they were selective hunters, and the capture and population data indicated that most successful hunters practiced selection. From August 2009 to July 2010 thirty-three individual pumas were captured 38 times. Two capture teams with dogs operated over 86 search days from December 2009 through April 2010 to find 266 puma tracks, pursue pumas 93 times, and capture 21 pumas 26 times. Capture efforts with cage traps resulted in the recapture of 2 adult pumas and 1 cub. Nine cubs were observed for the first time at nurseries. A total of 42 pumas were monitored by radiotelemetry. Search efforts also revealed the presence of at least 15 other independent pumas. Our minimum count of independent pumas from September 2009 to April 2010 was 55, including 31 females and 24 males. A preliminary minimum estimated density of independent pumas was 3.29/100 km2. The proportion of radio-collared adult females giving birth in the August 2009 to July 2010 biological year was 0.42 (8/19). Seven litters that could be dated to month of birth were produced in June (4), July (2), and August (1). We monitored 19 female and 8 male adult radio-collared pumas for survival and agentspecific mortality. Survival rates in TY1 with hunting were generally lower than in the reference period without hunting. Causes of mortality were vehicle strikes and hunting. In addition, all 5 adult males with malfunctional radiocollars since the beginning of this study were harvested by hunters in TY1. Two radiomonitored subadult males died apparently due to natural causes. Of 19 cubs monitored with radiotelemetry, 5 died, all associated with infanticide. A non-marked adult male was also killed by a vehicle on the boundary of the study area. Puma harvest data also provided information on dispersals of 12 male and 1 female puma initially marked on the study area. Those pumas moved from about 60 to 370 km from initial capture sites. A pilot study on detection probabilities of pumas using a camera grid for a mark-recapture design was conducted in collaboration with Colorado State University Researchers J. Lewis and K. Crooks as they studied bobcats on the east slope of our study area. Two camera grids, Area 1 and Area 2, were on the east slope of the study area. Each grid was 80 square kilometers in size and contained 20 cells which were each 4 square kilometers. Cameras operated for 108 days from August 21 to December 7, 2009. Detection probabilities for 4 adult radio-collared pumas on Area 1 and 5 adult pumas on Area 2 were 0.75 and 0.80, respectively. Those pumas were photographed a total of 51 times: 17 times in Area 1 and 34 times in Area 2. Males were detected more frequently than females. Four other marked pumas without functioning collars were also detected 7 times. Non-marked pumas were photographed 31 times, representing 2 to 4 individuals in Area 1 and 3 to 5 individuals in Area 2. The next step in this collaboration is to conduct an intensive evaluation of pilot study data to model detection probability, estimate precision, and define the survey area for a camera grid design specifically for puma. Data are continued to be gathered for other collaborative projects with Mammals Research and CSU investigators on puma behavior, social organization, population dynamics, and habitat use. 102 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates; model puma population dynamics; develop and execute the puma harvest manipulation to begin the population-wide test of Colorado Division of Wildlife (CDOW) puma management assumptions in the first year of a five-year Treatment Period of the Uncompahgre Plateau Puma Project― all to improve the CDOW model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. Execute the first year of the five-year treatment period by working with CDOW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Continue gathering data on puma population sex and age structure. 3. Continue gathering data for estimates of puma reproduction rates. 4. Continue gathering data to estimate puma sex and age-stage survival rates. 5. Continue gathering data on agent-specific mortality. 6. Collaborate with Colorado State University (CSU) researchers on a pilot project to assess puma detection probability in a camera grid design. 7. Collaborate with other researchers involved with puma biology and ecology. INTRODUCTION Colorado Division of Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CDOW objective of actively managing pumas while “achieving healthy, self-sustaining populations”(CDOW 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CDOW’s wildlife managers and biologists prior to initiating the project. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CDOW employees. In general, CDOW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CDOW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). 103 �● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). ● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CDOW to achieve its strategic goal in puma management (Fig.1). This project has been addressing all of the gray-shaded components on the left side of the conceptual model in Figure 1. Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/VHF-radio-collared pumas. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CDOW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of puma population abundance. A descriptive and manipulative study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in two 5-year periods. A completed 5-year reference period, 2004-09, (i.e., absence of recreational hunting) allowed puma life history traits to interact with the main habitat factors that influenced puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001, Logan 2009). A subsequent 5-year treatment period started in 2009-10 will involve the use of controlled recreational hunting to manipulate the puma population. 104 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CDOW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all age stages- adults, subadults, and cubs, J. Apker, CDOW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to DAUs to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado Data Analysis Units (DAUs) is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-firstbreeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. The key assumption is that the CDOW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ). Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a declining trend of the harvest-age segment of the population. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of 105 �greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a declining trend in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Researchers in Wyoming (Anderson and Lindzey 2005) concluded that sex and age composition of the harvest varies predictably with puma population size because the likelihood of a specific sex or age class of puma being harvested (with the use of hounds) is a product of the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Results of that study suggest that managers could use sex and age composition of the harvest to infer puma population changes (Anderson and Lindzey 2005). The CDOW currently uses this approach as one tool to infer potential DAU puma population dynamics (CDOW 2008). This assumes no purposeful selection by hunters for any particular sex or age-stage other than the puma must be legal (i.e., independent subadult or adult, not a lactating female or a female in association with spotted cubs) and that changes in the sex and age structure of the harvested pumas is due solely to changes in the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Theoretically, pumas that travel longer distances with movements that intercept access routes used by hunters (i.e., roads, trails) should be more exposed to detection by hunters and thus vulnerable to harvest. A key assumption to this method is that pumas are killed as they are encountered and the harvest sex and age composition will reliably indicate whether a population is stable, increasing, or declining even if harvest intensity does not vary. Thus, an alternate view is that a population segment, such as independent females, may be more abundant and have shorter movement lengths, yet be detected more frequently by hunters. However, because the same intensively studied Wyoming puma population was manipulated over 6 years with varying intensities of harvest (Anderson and Lindzey 2005), variations in harvest structure using the same harvest level over a period of years could not be examined. This is a property we will investigate during the treatment period on the Uncompahgre Plateau puma study. Moreover, we will directly evaluate to what extent puma harvest might be influenced by hunter selection. A hunter survey is intended to reveal puma hunter behavior, detection of different classes of pumas, and lack of or presence of hunter selection. We want to examine the usefulness of this approach in Colorado. CDOW managers attempt to weight sport-harvest toward male pumas in GMUs with the stable-to-increasing population objective with an active educational program (i.e., mandatory hunter exam, brochure, workshops). Thus, there is a need to test assumptions associated with the Anderson and Lindzey (2005) method. H6: No hunter selection is practiced so that the sex and age structure of pumas harvested by hunters in this population protected from hunting during a 5-year reference period and subsequently managed for stability or increase with conservative harvest levels will reflect the relative vulnerabilities to detection and capture with dogs during each year in the 5-year treatment period in this order from high to low vulnerabilities: subadult males, adult males, subadult females, adult females without cubs or with cubs >6 months old, and adult females with cubs ≤6 106 �months old (Barnhurst 1982, Anderson and Lindzey 2005). In each of the 5 years of the treatment period, subadults and adult males should comprise the majority of the harvest and reflect the assumed sex and age structure (Anderson and Lindzey 2005) of a puma population managed for a stable to increasing phase and not hunted for 5 previous years (i.e., a puma population source). Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CDOW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed as we learn the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. Cattle and domestic sheep are raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area highly accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates 107 �will be quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest will be tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma selection pressures in western North America for at least the past 100 years. Hence, the reference period, years 1―5, provided conditions where individual pumas in this population (of estimated sex and age structure) expressed life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor was vulnerable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This allowed researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged pumas that ranged in a buffer zone in the northern halves of GMUs 61 and 62 were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CDOW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6―10, recreational puma hunting will occur on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CDOW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas will be influenced mainly by recreational hunting, which will be quantified by agent-specific mortality rates of radio-collared pumas. Dynamics of the puma population will be manipulated to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting). The killing of tagged and collared pumas during the treatment period is not hampering operational needs (as it would have during the start-up years), because a majority of independent pumas in the population have already been marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CDOW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the 108 �study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Puma capture and handling procedures were approved by the CDOW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were fixed via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitated thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area was searched systematically multiple times per winter by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, and walking. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CDOW, attending veterinarian, pers. comm.). Immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). Pumas that climbed trees too dangerous for the pumas or researchers were released without handling, or we encourage the animals to leave the tree by heaving snowballs toward them. If the pumas climbed a safe tree, then we handled them as described above. A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage and door. Researchers handled captured pumas within 30 minutes of capture. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers were away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of 30 to 100 m to minimize disturbance and human scent at nurseries. Immediately after handling 109 �processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas did not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating numbers, vital rates, and gathering movement data relevant to population dynamics (i.e., emigration and Data Analysis Unit boundaries). Adult, subadult, and cub pumas were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were ear-tagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas provided precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPScollars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allowed the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars were not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to determine their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when puma was immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHFcollared pumas were fixed about once per week (as flight schedules and weather allowed) from light fixed-wing aircraft (e.g., Cessna 182) fitted with radio signal receiving equipment (Logan and Sweanor 2001). GPS- and VHF-collared pumas were located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes recorded on standard forms. GPS and aerial locations were mapped using GIS software. We attempted to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar that can expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM2160, 47g, Telonics, Inc., Mesa, Arizona MOD 080, 62g, or Telonics MOD 205, 90g,) when cubs weighed 2.3―11 kg (5―25 lb). Cubs could wear these small expandable collars until they are over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). 110 �Analytical Methods Population Characteristics: Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also called kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months or years. Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the subadult age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) mainly during November to March which corresponds with Colorado’s puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed in a variety of software (e.g., SYSTAT, R, and MARK). 111 �RESULTS AND DISCUSSION Segment Objective 1 Puma harvest: This biological year, August 2009 to July 2010, was the first year of the treatment period in this study of puma population dynamics on the Uncompahgre Plateau. Principal investigator K. Logan with CDOW biologists and managers developed a structure (i.e., officially approved by Wildlife Commission decision in September 2009) to manipulate the puma population with sport-hunting and to survey hunters. The hunting season on the study area began on November 16, 2009 and was scheduled to extend to January 31, 2010, unless the harvest quota was taken before then. The design harvest quota was 8 pumas (i.e., 15% harvest of the estimated minimum number of independent pumas), with the objective to manage for a stable to increasing population. This design harvest tests the CDOW’s current assumption that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-toincreasing puma population (Assumption and Hypothesis 3 p.5 this report). The quota of 8 was based on the projected minimum number of 53 independent pumas expected on the study area in winter 2009-10, modeled from a minimum count of pumas during winter 2007-08 (Table 1). We relied on the count data from 2007-08 because that was the last year in the reference period in which a fully staffed research team was able to adequately survey the study area in winter capture operations. The next year, 2008-09 (i.e., the last year of the reference period), a state government-mandated hiring freeze contributed to subpar winter capture operations, and thus, an inadequate minimum count effort. The number of puma hunters on the study area was not limited. Each hunter on the study area was required to obtain a hunting permit from the CDOW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date requested a new permit for another 14 days or until the hunter killed a puma within the season, or the season on the study area closed due to the quota being reached, or the end of the hunting season. This permit system allowed the CDOW to monitor the number of hunters on the study area and to contact each hunter for survey information (see later). All pumas harvested on the study area were examined by principal investigator K. Logan and sealed as mandated by Colorado statute. All successful hunters reported their puma kill and presented the puma carcass for inspection by CDOW within 48 hours of harvest. Upon inspection data was recorded on the puma harvested, including: sex, age, and location of harvest. In addition, an upper premolar tooth was collected for aging (i.e., mandatory) and a tissue sample was collected for DNA genotyping. Each successful hunter was also asked at that time to complete a one-page hunter survey form. All other hunters that did not report a puma kill on the study were asked to complete the survey form and return it in a stamped envelope that was provided. An attempt was made to contact other hunters by telephone if they did not mail in surveys. The puma hunting season occurred on the study area from November 16 to December 11, 2009, taking 26 days to fill the quota of 8 pumas. Nine pumas were killed, including: 2 adult females, 1 subadult female, 5 adult males, and 1 dependent male cub (Table 2). Three of the pumas were killed on the last day, resulting in the quota being exceeded by 1 puma. Of the harvested pumas, 3 were marked: dependent male cub M91 (offspring of F25), and 2 adult males M51 and M71. In addition to the pumas killed on the study area, 1 adult female (F110) and 3 adult males (M27, M29, M100) that had home ranges overlapping the study area were killed off the study area on adjoining GMUs (Table 3). The harvest of 8 independent pumas on the study area was 14.5% (8/55*100) of the minimum count of 55 independent pumas, including 31 females and 24 males, estimated by the research team 112 �during September 2009 to April 2010 (Table 4). Independent females and males comprised 37.5% (3/8*100) and 62.5% (5/8*100) of the harvest, respectively. This harvest structure was 9.7% (3/31*100) of the independent females and 20.8% (5/24*100) of the independent males. Considering the harvest of 4 other radio-collared adults (F110, M27, M29, M100) off the study area, which had home ranges overlapping on and off the study area, a harvest of 12 independent pumas was 21.8% (12/55*100) of the minimum number of independent pumas. The harvest composition of 4 females and 8 males was comprised of 33.3% (4/12*100) females and 66.7% (8/12*100) males. This harvest structure was 12.9% (4/31*100) of the independent females and 33.3% (8/24*100) of the independent males in the minimum count. The minimum count of independent pumas in 2009-10 was highly consistent with the expected number and sex structure of independent pumas projected by the deterministic, discrete time model (see Tables 1 and 4. Minimum count 2009-10 = 55 independent pumas, including 31 females, 24 males. Model projected independent pumas = 53, including 31 females, 22 males). Therefore, we used the model to guide the decision to manipulate the puma population with a harvest of 8 independent pumas in the 201011 hunting season to emulate an approximate 15% harvest of independent pumas to achieve a stable to increasing population objective while also considering that a number of independent pumas in the study area population will probably be killed outside of the study area as in the 2009-10 hunting season (Fig. 3). The projected population trends are stable-to-increasing. Hunter permits and survey: Mandatory permits with the voluntary survey attached were requested by 79 individual hunters. Thirty-three of the hunters requested a second permit after the first one expired after 14 days. Seventy-one hunters (90%) provided responses to the voluntary survey either by turning in the survey (i.e., n = 43) or providing information during follow-up telephone calls (i.e., n = 28) by principal investigator K. Logan. The remaining 8 hunters could not be contacted, because either they did not have working phone numbers or they did not return calls. Of the respondents, 11 hunters indicated that they did not hunt on the study area. As a proportion of the 71 respondents, the number that hunted extrapolated to the total of 79 hunters (60/71 = 0.845) indicated that about 67 hunters took to the field for pumas on the study area during the 26-day hunting season. Considering that 67 hunters were estimated to be afield, then 13% harvested pumas (9/67*100) and 24% of individual hunters captured pumas (16/67*100; see captured and released pumas below and in Table 5). In response to the survey question, “Do you consider yourself a selective or non-selective hunter?” all the respondents that hunted on the study area indicated that they were selective hunters. (A selective hunter is one that purposely is hunting for a specific type of legal puma, such as a male, large male, or large female. A non-selective hunter is one that intends to take whatever legal puma is first encountered or caught, with no desire for sex or size.) Yet, selective hunter was indicated by the 3 hunters that killed a subadult female, a lactating female, and a dependent male cub, which may indicate that in fact not all the hunters are selective or some cannot distinguish types (i.e., sex, age stage) of pumas in the field to practice selection. On the other hand, hunter surveys also revealed that hunters treed pumas on the study area, but they chose not to kill them (Table 5). Those hunters reported they treed pumas 14 times, including 9 females and 5 males. All 9 females were described by the hunters as adult age; 2 males were described as adult age, and 3 males were described as subadults. Five of the treed pumas were marked, including adult female F8 treed twice, adult female F74, and 2 yellow ear-tagged subadult males (numbers could not be distinguished). Hunters gave various reasons for not wanting to kill the pumas, including reasons based on puma sex and size (Table 5). These preliminary survey and harvest data indicate independent females were probably captured slightly more frequently than independent males (i.e., ratio 12 females:10 males; females = 3 harvested + 9 captured and released; males = 5 harvested + 5 captured and released). This sex structure was consistent with the sex structure of the independent pumas in the minimum count (Table 4). Yet, the harvest was comprised of mostly males (3 females, 5 males). 113 �This preliminary assessment from TY1 puma harvest and hunter survey data suggests that most hunters that captured pumas were selective and influenced harvest sex and age composition. Segment Objective 2 After the design quota was filled, puma research teams immediately activated for capture operations with trained dogs. Two fully-staffed capture teams, one detailed on the east slope and one detailed on the west slope, systematically and thoroughly searched the study area to capture, sample, and GPS/VHF radiocollar pumas the remainder of winter and early spring 2009-10. These efforts along with cage trap efforts and hand-capturing cubs at nurseries maintained samples to quantify population sex and age structure, survival, and agent-specific mortality, and allowed determination of minimum population size on the study area. We made 34 puma captures of 28 individuals from August 2009 to July 2010 (Tables 6-11). Twenty-one individual pumas were captured with dogs 26 times. Three pumas were captured in cage traps. Cubs were captured at nurseries 5 times. A total of 42 pumas were monitored with radiotelemetry from August 2009 to July 2010 (some of these had been collared in previous years). In addition, 2 cubs were monitored from birth to death at the nursery by monitoring the GPS and VHF data of their mother. Trained dogs were used as our main method to capture, sample, and mark adult and subadult pumas from December 15, 2009 to April 30, 2010. Those efforts resulted in 86 search days, 266 puma tracks detected, 93 pursuits, and 26 puma captures (Table 6). Search days with dogs in this period was greater than our efforts in the 4 previous winters by 4 to 15 days (Table 12). In addition, this was the first year we deployed 2 fully-staffed hound capture teams. The frequency of tracks (tracks/day) encountered was higher than the previous 5 winters. The pursuits increased over all previous years by 18 to 58, with the lowest number of pursuits occurring in the first year of this study (2004-05). The capture rate was also the highest by 2 to 12 captures. Increased capture efforts and captures were probably the result of using 2 fully-staffed houndsmen teams even though the puma population had been reduced due to harvest just before our capture operations. Researchers also recorded instances when the first tracks ≤1 day old of independent pumas were encountered on each search route each day to represent encounters with puma tracks that could be pursued by houndsmen. The count was: 37 tracks of females, including 5 associated with cubs; 21 tracks of males; and 2 tracks of unspecified sex. The ratio of female to male tracks was consistent with the sex structure of independent pumas in our minimum count (Table 4). Puma capture efforts using ungulate carcasses and cage traps extended from September 11, 2009 to May 17, 2010 (Table 10). We used 21 road-killed mule deer at 17 different sites, but did not capture any pumas. However, 2 adult pumas (M55, F94) were each recaptured in cage traps at mule deer kills they made. Pumas scavenged at 3 of 17 (17.65%) sites where ungulate carcasses were used for bait. A bobcat trapper inadvertently caught male cub M112 (offspring of F70) in a cage trap. The trapper notified us, and we sampled, tagged, radio-collared, and released the cub. The cub successfully rejoined his family. We captured 5 cubs, all males for the first time (Table 11), and fit all with radio-collars (Appendix A). Two cubs of F3 were captured at nurseries, 2 were bayed by hounds (M115 of F28, M117 of F119), and 1 was caught in a bobcat cage trap (M112 of F70, see above). In addition, we found 2 male cubs (P1016, P1017) of F72 that were killed by male puma M32 on the day we investigated the nursery to sample and tag the cubs (see later). Two cubs of F93 were observed in the nursery at about 28 days old, but they could not be handled because the rock structure of the nursery afforded them complete protection from capture. 114 �In addition to our direct puma captures with dogs December through April, we detected 16 pumas that we were able to identify with GPS or VHF telemetry 38 times, thus, negating the need to capture those pumas directly with dogs (Table 6). Upon detecting puma tracks that were aged at ≤1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. GPS data from pumas with functional GPS collars provided confirmatory information about movements of pumas. If GPS data indicated that the puma moved through the area at the time the tracks were made, then we ruled the data were confirmatory. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with nonfunctioning GPS- or radiocollars. Our search efforts throughout the study area also revealed the presence of at least 15 other independent pumas, we classified as 9 females and 6 males. Two of the males were treed by our hounds, but we could not handle the pumas because they climbed dangerous trees (Table 7). We could separate the activity of the other pumas from the GPS- and VHF- collared pumas in time, space, and track size differences between females and males. Moreover, females in association with cubs of different numbers, sizes, and locations enabled us to separate 2 adult females followed by 2 to 3 medium-to-large-size cubs. The tracks we found of the other pumas were too old to pursue (i.e., probability of capture with the dogs was negligible). One of the adult females was likely F74, which was also treed and observed by a puma hunter on December 9, 2009. It is also possible that 1 of the adult females was previously marked animal F24 wearing non-functional GPS collar. Our search and capture efforts during September 2009 through April 2010 enabled us to quantify a minimum count of 55 independent pumas detected on the Uncompahgre Plateau study area, including 31 independent females and 24 independent males (Table 4). This count was based on the number of known radio-collared pumas, non-marked pumas harvested by hunters on the study area, observations of marked and non-marked pumas observed by researchers or treed and released by hunters on the study area, and fresh puma tracks (i.e., ≤ 1 days old) observed by researchers that could not be attributed to pumas with functioning radiocollars. The estimated age structure of independent pumas in November 2009 at the beginning of the puma hunting season in Treatment Year 1 (TY1) on the Uncompahgre Plateau study area is depicted in Figure 4. In addition to the independent pumas, we also counted a minimum of 20 to 25 cubs. Of the 55 independent pumas, 34 to 35 (62-64%) were marked and 20 to 21 (36-38%) were assumed to be unmarked animals. Of the expected unmarked pumas, 10 to 11 were females and 10 were males. The abundance and sex structure of independent pumas on the east and west slopes of the study area were similar. The east slope count included 28 independent pumas (17 females, 11 males). The west slope count included 27 independent pumas (14 females, 13 males). Considering the minimum count of 55 independent pumas, a preliminary minimum density for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area was 3.29 independent pumas/100 km2. Segment Objective 3 During the past 5.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado. Puma reproduction data (i.e., litter size, sex structure, gestation, birth interval, proportion of females giving birth per year) were summarized for the reference period in Logan (2009). We observed 6 litters born in June (3), July (2), and August (1) 2010, each with 1 to 3 cubs each, born to radio-collared females. We found sign (i.e., nurseries, tracks) of a fourth litter born in June to a GPS-collared female (F111); but, we could not catch the cubs before they developed well enough to escape us (about 6 weeks old). Data on reproduction observed in this first year of the treatment period were added to Table 13, but will not be summarized again until the end of the period. The proportion of radio-collared adult females giving birth from August 2009 to July 2010 biological year was 0.53 (8/15). 115 �Considering our 32 total observed litters and 2 other litters confirmed by nurseries and nursling cub tracks with GPS-collared females, all with cubs 26 to 42 days old, the distribution of puma births by month indicate births extending from March into September, with 24 of 34 births (70.6%) occurring May through July (Fig. 5). Our data suggests that the large majority of puma breeding activity occurred February through April. In contrast, Anderson et al. (1992:47-48) found on the Uncompahgre Plateau that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. Data on our 34 litters added to Anderson’s data (Fig. 5), and indicated puma births on the Uncompahgre Plateau occurred in every month except January and November (so far). Segment Objectives 4 & 5 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2010, we radio-monitored 14 adult male and 26 adult female pumas to quantify survival and agent-specific mortality rates (Table 14). Survival and agent-specific mortality of adult pumas were summarized for the reference period in Logan (2009). Preliminary estimates of adult puma survival rates in the absence of sport-hunting indicated relatively high survival, with adult male survival generally higher than adult female survival (Table 15). For this first year of the treatment period, we monitored 19 adult radio-collared females and 8 radio-collared adult males. The initial indication is that adult survival rates declined for adult females and males (Table 15). But, no conclusions should be drawn with only 1 year in the treatment period (TY1). The primary interest is the magnitude of reduction in survival, and the implications of those survival rates for population growth rate. This is what ultimately allows us to evaluate the effect of this harvest level for our population management assumptions when the goal is a stable to increasing population. Causes of mortality for adult pumas with functioning radiocollars in TY1 were due to vehicle strikes on roadways (2 females, 1 male) and hunting (1 female, 1 male). In addition, all 5 adult males which developed non-functional radiocollars (M1, M27, M29, M51; Table 3) or shed a collar (M71) since the beginning of this study were harvested by hunters in TY1. Inclusion of those adult males in the survival estimate indicated a substantially lower adult male survival rate in TY1 (Table 15). We have radio-monitored 11 pumas, 4 females and 7 males, in the subadult age-stage (independent pumas <24 months old) (Table 16). Three died before reaching adulthood, indicating a preliminary finite survival rate of 0.727. All 3 subadults apparently died of natural causes. F66 died at 23 months old of trauma to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer. M99 died at about 16 months old due to unknown causes; but, punctures in the skull suggested strife with another puma. M115 died at about 14 months old due to complications of a broken left foreleg, cause unknown. This injury probably affected his ability to efficiently kill prey. We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire reliable estimates of their survival. Data from puma hunters provided additional information on fates of 13 pumas, 12 males and 1 female, initially captured and marked as cubs (10 males) or subadults (2 males, 1 female) on the Uncompahgre Plateau puma study area (Table 17). All 12 of the males were killed away from the study area by hunters at linear distances (i.e., from initial capture sites to kill sites) ranging from about 60 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). The female (F52) was treed and released by hunters in December 2008 and 2009 south of Powderhorn, Colorado, indicating that she probably established an adult home range there. These pumas represent dispersal moves from the 116 �Uncompahgre Plateau. Eleven of the 13 pumas (except M68, 17 months old and M82, 19 months old) had reached adult ages ranging from 24 to 55 months old. A preliminary estimate of cub survival during the reference period was summarized in Logan 2009. In that summary 36 radio-collared cubs (16 males, 20 females) marked at nurseries when they were 26 to 42 days old were used for a Kaplan Meier procedure cub survival estimate of about 0.53 to one year of age. The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. In this first year of the treatment period, we monitored the fates of 19 cubs (Appendix A). Five of the cubs were known to have died, all of them associated with infanticide. Two (M101, F103) were orphaned at 149 days old when their mother (F16) was hit by a vehicle on County Road 1 on September 11, 2009. The 2 cubs were killed and partially eaten by adult male puma M55 on September 17 and 19, 2009. Fate of their sibling M102 was unknown because of a failed radiocollar after September 4, 2009. But M102 probably would have died of starvation if he was not killed by M55. F72’s 2 male cubs were killed, and 1 partially eaten, by adult male puma M32 at the nursery when the cubs were 39 days old on July 21, 2010. Mother F72 was about 2 km away from the nursery at the time the cubs met their fate. A greater number of cubs over a longer period of time must be sampled before estimating cub survival and agent-specific mortality rates in the treatment period. In addition, a 2-year-old non-marked male puma was struck and killed by a vehicle on highway 62 in Leopard Creek on the south boundary of the study area on August 25, 2010. This mortality made the twelfth puma death recorded due to vehicle collision on the study area since 2004 (Table 18). Five of the 12 pumas were marked, including 3 adults with GPS/VHF collars. Those 3 adults died during the first year of the treatment period. Segment Objective 6 We wanted to enhance this project with reliable estimates of puma abundance and density (see Objective 5, page 4). Because a majority of independent pumas were individually marked on the study area, we decided to explore the potential of using a camera grid mark-recapture structure to derive puma abundance estimates by first examining detection probabilities in a pilot effort. This effort is an attempt to develop puma population monitoring methods (Fig. 1). A camera grid mark-recapture approach is a method for counting pumas independent from our main method of capturing pumas with searches on snow-covered routes and dogs and thus has the potential of providing unbiased estimates. For this pilot project, we collaborated with Colorado State University Researchers Jesse Lewis (Ph.D. candidate) and Dr. Kevin Crooks (Dep. of Fish, Wildlife, and Conservation Biology) who studied bobcat distribution, abundance, and behaviors on the eastern slope of our Uncompahgre Plateau puma study area. Because those researchers used a camera grid design for bobcats where we also had GPS/VHF- collared pumas, this gave our project an opportunity to evaluate puma detection probability on a small scale. This was a first step in considering the usefulness of a camera grid design for puma abundance estimates. We established 2 camera grids on the east slope of the study area (Fig. 6). Each grid was 80 square kilometers in size and contained 20 cells which were each 4 square kilometers. We searched each grid for potential camera sites with the intention to maximize the encounter of a puma or bobcat with a camera. We used our general knowledge about puma and bobcat behavior to place the cameras and did not use any GPS/VHF data on puma locations. Felid sign on the ground (i.e., tracks, feces, scrapes) helped to guide our camera placement. Initially we placed 1 Cuddeback Capture digital camera (Park Falls, WI) in each cell at the site we deemed best to intercept wild felids, and did not use scent or sight lures in an attempt to attract the felids. One alternate camera site was placed in Area 1 and 5 alternate camera sites were placed in Area 2 to increase the sample effort in canyon bottoms relative to canyon rims. All cameras were set at the highest design setting of 1 photo per 30 seconds if the passive infrared 117 �sensor were activated and serviced every 2 weeks to ensure operation and fresh batteries. Cameras operated for 108 days from August 21 to December 7, 2009. During the period that the cameras operated, 4 adult (2 females, 2 males) GPS/VHF-collared pumas ranged on Area 1 and 5 adult (3 females, 2 males) GPS/VHF-collared pumas ranged on Area 2. Those pumas were photographed a total of 51 times: 17 times in Area 1 and 34 times in Area 2. Three of 4 adult pumas (probability 0.75) on Area 1 and 4 of 5 adult pumas (probability 0.80) were detected 2 to 19 times each in the 108 day period. Daily detection rates ranged from 0.02 to 0.18 (Table 19). Detection rates varied among individuals, and were the highest for adult males. Both adult pumas that were not detected were females. One, F16, died on September 11, so was available for 21 days. The other, F70, had a new litter of cubs on August 31 at a nursery in a canyon between the 2 camera grids where she focused her activities. Then on September 23 her GPS collar quit functioning and we were unaware of her movements. In addition, 4 other marked pumas without functioning collars were detected by cameras a total of 7 times. Those pumas were: adult F3 (detected 3 times; non-functional GPS collar), adult M71 (detected twice; eartags, shed expandable VHF collar), a subadult female detected once (orange eartag right pinna), and a male cub detected once (yellow eartag left pinna). Non-marked pumas were photographed 31 times on the camera grids. In Area 1 non-marked pumas were photographed 20 times at primary cameras and once at the alternate camera. We estimated the photos represented 2 to 4 individual independent pumas. In Area 2 non-marked pumas were photographed 8 times at primary cameras and twice by alternate cameras. We estimated the photos represented 3 to 5 independent pumas. Any of the non-marked pumas could have ranged on both camera grid areas. Our next step in this collaborative process is to analyze the photographic data on the 2 grids, including modeling detection probabilities with landscape and puma covariates and to examine expected estimates of precision. We also will examine population closure and investigate methods for defining the survey area by using the GPS and VHF locations of pumas with functioning collars that used the camera grid areas. This information will be used to assess the feasibility of designing a camera grid specifically to obtain accurate and precise estimates of puma abundance and density on a portion of the Uncompahgre Plateau study area. This phase is expected to be completed by July 2011. Segment Objective 7 Data from 28 (8 male, 20 female) GPS-collared pumas, totaling over 48 thousand GPS locations (Table 20) will be used to examine behaviors and social structure of the puma population on the Uncompahgre Plateau, including movements of pumas relative to Game and Data Analysis Unit boundaries and vulnerability to hunter detection. Those data will also be used in a set of collaborative projects, including: examination of puma behavior in relation to human development with Mammals Researcher Dr. Mat Alldredge, who is studying puma-human interactions on the Colorado Front Range and modeling and mapping puma habitat in Colorado and other western states with Dr. Kevin Crooks and Dr. Chris Burdett (Department of Fish, Wildlife and Conservation Biology, Colorado State UniversityDFWCB, CSU). Furthermore, puma population and genetic data from the Uncompahgre Plateau can be used in collaboration with Dr. Alldredge’s puma research efforts on the Front Range to examine similarities or differences in puma population dynamics and behaviors between the 2 environments. 118 �SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 5.7 years of effort 125 pumas have been captured, sampled, marked, and released. Of those animals, 107 were radiomonitored, allowing us to monitor fates of pumas in all sexes and age stages, including: 25 adult females, 13 adult males, 4 subadult females, 7 subadult males, 32 female cubs, 39 male cubs (some individuals occur in more than one age-stage). Data from the marked animals were used to quantify puma population characteristics and vital rates in a reference period without sport-hunting off-take as a mortality factor from December 2004 to July 2009. Puma population characteristics and vital rates in a reference condition allowed us to develop a puma population model, and to use population data and modeling scenarios to conduct a preliminary assessment of CDOW puma management assumptions and guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CDOW wildlife biologists and managers for assessing puma harvest strategies. The first year of the 5-year treatment period was August 2009 to July 2010 in which sport-hunting is a mortality factor. The treatment period will be a population-wide test of CDOW puma management assumptions. The puma harvest quota for TY2 will be 8 independent pumas, and the hunters will be surveyed again. To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes on life stages and sexes. Furthermore, we will continue collaboration efforts with colleagues on investigations of puma population parameter estimation, pumahuman relations, puma habitat modeling and mapping, and individual puma detection rates in camera grid designs. All of these efforts should enhance the Colorado puma research and management programs. 119 �LITERATURE CITED Anderson, A. E. 1983. A critical review of literature on puma (Felis concolor). Colorado Division of Wildlife Special Report No. 54. _____, D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Technical Publication No. 40. Colorado Division of Wildlife, Denver. Anderson, C. R., Jr., and F. G. Lindzey. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. 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Journal of Wildlife Management 49:668-674. Karanth, K. U., and J. D. Nichols. 2002. Monitoring tigers and their prey: A manual for researchers, managers and conservationists in tropical Asia. Centre for Wildlife Studies, Bangalore, India. Koloski, J. H. 2002. Mountain lion ecology and management on the Southern Ute Indian Reservation. M. S. Thesis. Department of Zoology and Physiology, University of Wyoming, Laramie. Kreeger, T. J. 1996. Handbook of wildlife chemical immobilization. Wildlife Pharmaceuticals, Inc., Fort Collins, Colorado. Laundre, J. W., L. Hernandez, D. Streubel, K. Altendorf, and C. L. Lopez Gonzalez. 2000. Aging mountain lions using gum-line recession. Wildlife Society Bulletin 28:963-966. Logan, K. A., E. T. Thorne, L. L. Irwin, and R. Skinner. 1986. Immobilizing wild mountain lions (Felis concolor) with ketamine hydrochloride and xylazine hydrochloride. Journal of Wildlife Diseases. 22:97-103. _____, L. L. Sweanor, J. F. Smith, and M. G. Hornocker. 1999. Capturing pumas with foot-hold snares. Wildlife Society Bulletin 27:201-208. _____, and L. L. Sweanor. 2001. Desert puma: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. _____. 2009. Puma population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report. Colorado Division of Wildlife, Fort Collins. Murphy, K., M. Culver, M. Menotti-Raymond, V. David, M. G. Hornocker, and S. J. O’Brien. 1998. Cougar reproductive success in the Northern Yellowstone Ecosystem. Pages 78-112 in The ecology of the cougar (Puma concolor) in the Northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow. Ott, R. L. 1993. An introduction to statistical methods and data analysis. Fourth edition. Wadsworth Publishing Co., Belmont, California. Pierce, B. K., V. C. Bleich, and R. T. Bowyer. 2000. Social organization of mountain lions: does land a tenure system regulate population size? Ecology 81:1533-1543. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. 120 �Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Seidensticker, J. C., M. G. Hornocker, W. V. Wiles, and J. P. Messick. 1973. Mountain lion social organization in the Idaho Primitive Area. Wildlife Monographs No. 35. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 121 �Table 1. Projected puma population growth modeled from a minimum count of independent pumas during winter 2007-08 reference period year 4 (RY4). Treatment period year 1 (TY1), shaded in gray, indicates the results used to derive a quota of 8 independent pumas, representing 15% of the independent pumas (from Logan 2009). Harvest Level No harvest. Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 27 17 11 10 32 22 12 11 38 27 15 14 44 32 17 16 Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Independent Pumas Cub 20 33 42 49 58 69 81 Total 33 45 53 64 77 92 110 Lambda 1.37 1.17 1.22 1.20 1.20 1.19 Table 2. Pumas harvested by sport-hunters in Treatment Year 1 (TY1) on the Uncompahgre Plateau Study Area, Colorado, November 16 to December 11, 2009. Puma sex/age/mark M (cub of F25) M Age (yr.) 1.25 2-3 11/21/2009 F 4 12/9/2009 F 1.5-2 12/9/2009 M 4 M 4 12/9/2009 F (lactating) M 2 12/11/2009 M 2-3 7 Previous I.D. M91 M71 M51 Date of kill Location/UTM Hunter/status 11/17/2009 Pleasant Valley/ 13S,247640E,4228470N Little Bucktail Creek/ 12S,726165E,4240290N San Miguel Canyon/ 12S,732268E,4234711N Pinyon Ridge/ 13S,256380E,4241740N Spring Creek/ 12S,762033E,4248487N Horsefly Canyon (E)/ 13S,249114E,4240143N Roubideau Canyon/ 12S,746670E,4254762N Shavano Valley/ 12S,761117E,4256800N Mailbox Park/ 12S, 726524E,4234984N Jack Flowers/ Resident Ty Spangler/ Resident Larry McPeak/ Non-resident M. Ryan Hatter/ Resident Caleb Marquardt/ Resident Darren Reed/ Resident Brian Coe/ Non-resident Darrel Moberly/ Resident Donald Gambril/ Non-resident 12/9/2009 12/11/2009 12/11/2009 122 �Table 3. Five other independent pumas from the Uncompahgre Plateau Study Area killed by hunters off of the study area. Four adult pumas– F110, M27, M29, M100– were in the minimum count on the study area in winter 2009-10.a Adult male M1 probably no longer ranged on the study area. Puma sex/age/mark M29/adult Date of kill 11/16/2009 Place of kill/UTM Hunter/status Beaver Creek (GMU70east) Syver Bicknase/ 12S,745500E,4219660N Resident M27/adult 12/9/2009 N. Fork Mesa Creek (GMU61north) Kevin Thornton/ 12S,693422E,4266607N Non-resident M1/adult 1/2/2010 West Bang’s Canyon (GMU40) Outfitter Steve Biggerstaff 12S,710656E,4314243N M100/adult 1/16/2010 Naturita Canyon Outfitter Wade Wilson 12S,734604E,4216634N F110/adult 2/25/2010 Naturita Creek Alex Sokolik/ 12S,721010E,4230929N Resident a All five adult male pumas with non-functioning (4) or shed (1) radiocollars were killed during TY1 either on (M51, M71) or off (M1, M27, M29) of the UP Study Area. Table 4. Minimum count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during September 2009 to April 2010, Uncompahgre Plateau study area, Colorado. Study Area Adults Subadults region Female Male Female Male East slope 16 10 1 1 West slope 14 10 0 3 subtotals 30 20 1 4 Total Independent Pumas = 55, including 31 females, 24 males Female 1 3 4 Cubs Male 4 3 7 Unknown sex 4-8* 5-6 9-14 *One adult non-marked female puma was killed by a hunter in Roubideau Canyon. The female puma was lactating, indicating she had nurslings. Up to 4 cubs were assumed to be in the litter. 123 �Table 5. Pumas captured and released by sport-hunters in Treatment Year 1 (TY1) on the Uncompahgre Plateau Study Area, Colorado, November 16 to December 11, 2009. Data are from puma hunter responses in 71 voluntary surveys, including: 43 original surveys on mandatory permits and 28 telephone contacts with hunters that did not return surveys on permits. Total response rate from 79 individual hunters was 90% (71/79 = 0.899*100). Puma sex/age stage/mark F/adult/none Date of capture 12/1/2009 Capture location Hunter name Preston Joseph 12/8/2009 N. Fork Cottonwood Creek N. Fork Cottonwood Creek DeVinney Canyon F/adult/F8 collar & eartag M/subadult/ yellow eartags in both ears (numbers not distinguished) F/adult/F74 orange eartags 12/7/2009 12/9/2009 Cottonwood Creek 11/30 to 12/7/2009 11/30 to 12/7/2009 Loghill Mesa, Fisher Creek area Loghill Mesa, Fisher Creek area Larry McPeak, guided by Stan Garvey Zachary Prock & Dustin Braiser Zachary Prock F/adult/none M/subadult/none 12/11/2009 Big Bucktail Canyon Brian Hibbert F/adult/F8 collar & eartag 11/23 to 12/11/2009 N. Fork Cottonwood Creek Gerald Sickels, Jr. F/adult/none 11/23 to 12/11/2009 East of Nucla Gerald Sickels, Jr. F/adult/none 11/23 to 12/11/2009 Pinyon, Cottonwood Creek Gerald Sickels, Jr. M/subadult/yellow eartag 11/23 to 12/11/2009 San Miguel Canyon below Pinyon Gerald Sickels, Jr. M/adult/none 11/23 to 12/11/2009 Mailbox Park Gerald Sickels, Jr. M/adult/none 11/23 to 12/11/2009 Dead Horse Mesa Gerald Sickels, Jr. F/adult/none Late 11/2009 Pinyon Ridge Micah Brogden F/adult/none 124 Ryan Weimer Gary Gleason Reason for releasing the puma given by hunter Did not want to kill a female puma. Outfitter R. Weimer did not want hunter to kill a female puma. Did not want to kill a small male puma. Estimated ~125 lb. Did not want to kill a female. L. McPeak later in same day killed another adult female puma. Hunters will not kill a female puma.* Will not kill a female puma. *These 2 females treed ~4 days apart. One seemed younger than the other, so thought to be different females. But, could have been same puma. Did not want to kill a small male puma. B. Hibbert estimated puma about 1.5 years old. Likes to look at the pumas and train his dogs. Does not want to kill a female puma. Likes to look at the pumas and train his dogs. Does not want to kill a female puma. Likes to look at the pumas and train his dogs. Does not want to kill a female puma. Likes to look at the pumas and train his dogs. Does not want to kill a small male. Wants to kill a big male puma. Likes to look at the pumas and train his dogs. Does not want to kill an average male. Wants to kill a big male puma. Likes to look at the pumas and train his dogs. Does not want to kill an average male. Wants to kill a big male puma. Not interested in killing any puma. Likes to hunt pumas with dogs. �Table 6. Summary of puma capture efforts with dogs from December 15, 2009 to April 30, 2010, Uncompahgre Plateau, Colorado. Month December No. Search Days 10 No. & type of puma tracks founda,b 27 tracks: 12 male, 15 female, 0 cub Tracks ≤1 day old: 5 male, 8 female, 0 cub No. & type of pumas pursued 10 pursuits: 4 males, 6 females , 0 cubs January 20 80 tracks: 24 male, 35 female, 21 cub Tracks ≤1 day old: 11 male, 15 female, 10 cub 23 pursuits: 7 males, 10 females, 6 cubs February 22 77 tracks: 19-20 male, 36-37 female, 20 cub; 1 unknown sex Tracks ≤1 day old: 11 male, 24 female, 12 cub 36 pursuits: 7 males, 17 females, 12 cubs March 23 58 tracks: 16 male, 26 female, 16 cub Tracks ≤1 day old: 7 male, 14 female, 10 cub 18 pursuits: 4 males, 8 females, 6 cubs April 19 No. & I.D. or type of pumas captured, observed, or identified 2 pumas captured 3 times: F3 recaptured (nonfunctioning GPS collar replaced). One adult male puma ~2-3 yr. old captured twice, but not handled due to dangerous trees. In addition, adult F93 associated once with tracks by VHF telemetry (no pursuit with hounds). 6 pumas captured 9 times: M55 recaptured twice; F70 recaptured once; F111, F115, & F116 captured for first time. Then M115 & F116 recaptured. One adult male ~2-3 yr. old was captured, but not handled due to dangerous tree. In addition, 5 adult pumas were associated with tracks 6 times with VHF or GPS telemetry: M55 twice (VHF), F70 (GPS), F72 (GPS), F93 (VHF), F111 (GPS). 10 pumas captured 12 times: F23 recaptured 3 times, but in trees too dangerous for handling to replace her non-functional GPS collar. F28 recaptured in a tree too dangerous for handling to replace her non-functional GPS collar. M32 recaptured (VHF collar replaced). F72 recaptured (non-functional GPS collar replaced). Cubs F106, M107 & F108 recaptured (expandable radiocollars fitted on F106 & F108). M114, M117, F118 captured for the first time. In addition, 7 adult pumas were associated with tracks 9 times via VHF or GPS telemetry: M32 (VHF), F70 (GPS), F95 (VHF), F111 three times (GPS), F113 (VHF), F116 (VHF), F118 (VHF). 3 pumas captured: F96 and M115 recaptured. F119 captured for first time. In addition, 8 pumas were associated with tracks 16 times via VHF telemetry and/or GPS: F3 three times (GPS, VHF & GPS, VHF), M6 twice (VHF), M55 four times (VHF, GPS, VHF & GPS twice), F70 three times (VHF, GPS twice), cub M112 once (VHF), F93 once (VHF), F96 once (GPS), and cub M115 (VHF). 0 pumas captured physically, but F95 identified in one pursuit with VHF telemetry. In addition, 3 adult pumas associated with tracks with VHF telemetry: F93, F104, F118. 24 tracks: 11-12 male, 6 pursuits: 2-3 12-13 female, males, 3-4 females, 0 cub 0 cubs Tracks ≤1 day old: 3-4 male, 6-7 female, 0 cub 86 266 tracks: 93 pursuits: 21 individual pumas were captured 26 times with TOTALS 82-84 male, 24-24 males, aid of dogs. In addition, 16 radio-collared pumas 124-126 female, 44-45 females, were detected 38 times by tracks and identified 57 cub, 24 cubs with VHF and/or GPS telemetry. 1 unknown sex Tracks ≤1 day old: 37-38 male 67-68 female 32 cub a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Researchers also recorded instances when the first puma tracks ≤1 day old were encountered on each search route each day. The count was: 37 tracks of females, including 5 associated with cubs; 21 tracks of males; and 2 tracks of unspecified sex. 125 �Table 7. Adult and subadult pumas captured for the first time, sampled, tagged, and released from December 2009 to April 2010, Uncompahgre Plateau, Colorado. Puma I.D. MA* MB* F111 M112 F113 M114 M115 F116 M117 F118 F119 Sex Estimated Age (mo.) 24-36 24-36 24-27 4.7 36 36 14 36-48 6 18-24 60-72 M M F M F M M F M F F Mass (kg) Unknown Unknown 35 10 47 63 39 49 12 38 46 Capture date 12-16-09 01-03-10 01-01-10 01/23/10 01/26/10 02-27-10 01-13-10 01-20-10 02-05-10 02-25-10 03-25-10 Capture method Dogs Dogs Dogs Cage trap Cage trap Dogs Dogs Dogs Dogs Dogs Dogs Location West Fork Dry Creek Basin East Fork Dry Creek Basin Cushman Canyon Horsefly Canyon (east slope) McKenzie Butte McKenzie Butte San Miguel Canyon San Miguel Canyon San Miguel Canyon Big Bucktail Canyon San Miguel Canyon * Pumas MA and MB were adult males that could not be handled because they climbed dangerous trees. Table 8. Pumas that were captured and observed with aid of dogs, or observed in association with another radio-collared puma, but were not handled at that time for safety reasons, December 2009 to April 2010, Uncompahgre Plateau, Colorado. Puma sex & I.D. Capture date Location Comments MA Age stage or months 24-36 12-16-09 West Fork Dry Creek Basin MB 24-36 01-03-10 East Fork Dry Creek Basin F23 72 02-23-10 San Miguel Canyon F23 72 02-24-10 Big Bucktail Creek F23 72 02-25-10 San Miguel Canyon F28 89 02-01-10 Tomcat Creek Puma climbed dangerous tree, not handled. No noticeable marks. Puma climbed dangerous tree, not handled. This puma obviously larger than MA (above). F23 climbed dangerous tree, not handled to change non-functional GPS collar. F23 climbed dangerous tree, not handled to change non-functional GPS collar. F23 climbed dangerous tree, not handled to change non-functional GPS collar. F28 climbed dangerous tree, not handled to change non-functional GPS collar. F28 was in association with M115, apparently her offspring. 126 �Table 9. Pumas recaptured with dogs, cage traps, or visually observed, November 2009 to May 2010, Uncompahgre Plateau, Colorado. Puma I.D. Recapture Date 12-23-09 Mass (kg) Not weighed Estimated Age (mo.) 101 M32 02-04-10 54 100 Capture Method/ Location Dogs/East Fork Dry Creek Basin Dogs/Dry Creek Basin F3 M55 11-06-09 70 66 Cage trap/Puma Canyon M55 01-07-10 Observed 68 Spring Creek Canyon M55 01-24-10 Observed 68 Linscott Canyon M67 02-24-10 73 31 Dogs/Tomcat Creek F70 01-19-10 Not weighed 63 F72 02-09-10 Observed 47 Dogs/Horsefly Canyon (east slope) Dogs/Loghill Mesa F94 05-13-10 Not weighed 58 F96 03-11-10 43 50 Cage trap/Pinyon Hills west of Happy Canyon Dogs/Happy Canyon F106 02-10-10 20 9 Dogs/Dry Park M107 02-24-10 Observed 9 Dogs/Spring Creek Canyon F108 02-24-10 20 9 Dogs/Spring Creek Canyon M115 01-21-10 Observed 14 Dogs/San Miguel Canyon M115 03-18-10 34 16 Dogs/North Fork Cottonwood Creek F116 01/21/10 Observed 36-48 Dogs/San Miguel Canyon 127 Process Non-functional GPS collar replaced. M32’s old VHF collar was replaced. M55’s old GPS collar was replaced. M55 was wearing a functional GPS collar. No need to handle. M55 was wearing a functional GPS collar. No need to handle. M67 fitted with VHF collar. Offspring of F30, born July 17, 2007. Non-functional GPS collar replaced. F72 wore functional GPS collar, no need to handle. F94’s VHF collar changed to GPS collar. F96’s old GPS collar was replaced. F106 fitted with expandable VHF collar. Offspring of F75, born May 7, 2009. M107 captured with sibling F108, offspring of F94, born May 25, 2009. F108 captured with sibling M107, offspring of F94, born May 25, 2009. F108 fitted with expandable VHF collar. Attempted to capture female puma with M115. Dogs got on M115’s tracks. M115 handled to examine draining wound to left foreleg that occurred about 1-2 weeks prior to this capture; cause unknown. Broken bone detected by palpation. Left ulna was broken (examined later at mortality 08/06/10). F116 wore functional VHF collar, no need to handle. �Table 10. Summary of puma capture efforts with cage traps from September 11, 2009 to May 17, 2010, Uncompahgre Plateau, Colorado.* Month September No. of Sites 2 Carnivore activity & capture effort results Set cage trap with mule deer and predator call box on east rim Roubideau Canyon 09-11-09 to 09-15-09. Adult female puma with 2 large cubs visited 09-13-09; clawed at deer carcass, but did not feed; clawed at call box. Puma family did not return. October 1 A non-collared puma (probably subadult or adult female) visited the fawn mule deer carcass 10-17-10, but did not feed (Reconyx camera photos). A black bear walked ~10 m from the carcass, but did not feed. Mule deer carcasses scavenged by bobcats and magpies. November 2 Cage trap set with catnip oil and K-9 call scent bait and predator call box and stuffed toy rabbit 11-03-09 to 11-06-09. Cage trap closed due to proximity of puma F72 to trap. Puma M55 was recaptured at a mule deer buck he killed 11-06-09. January 2 Set cage trap with mule deer buck killed by male puma 01-04 to 08-10. Male puma was treed by dogs on 01-03-10, but could not be safely handled in East Fork Dry Creek. Puma did not return to its deer kill and cage trap. Bobcat trapper inadvertently captured cub M112 in cage trap on west rim Horsefly Canyon 0123-10. M112 offspring of F70. February 2 A bobcat and Golden Eagle scavenged mule deer carcasses. March 12 Puma F94 and cubs walked with 10 m of a mule deer carcass with predator call box, but did not feed 03-29-10. A male puma walked by mule deer carcass with predator call box, but did not feed 03-18-10. A male puma scraped 2 m from mule deer carcass, but did not feed 03-2310. Puma F96 investigated a predator call box set about 10 m from a mule deer carcass and clawed the call box, but did not feed on the deer. April 6 Puma F94 and cubs M107, F108 consumed a mule deer carcass 04-03 to 07-10. A male puma scavenged a mule deer carcass sometime during 04-05 to 13-10, possibly M55. M55 scavenged from another mule deer carcass on 04-05-10. May 3 Cage trap set 05-13-10 with mule deer doe killed by a female puma in Pinyon Hills; recaptured F94. Tracks indicated a male puma walked ~15 m from 2 cage traps with call boxes and scent lures, but did not go to cage traps to investigate. * We used 21 road-killed mule deer at 17 different sites. Of the road-killed deer baits, 3 of 17 (17.65%) were scavenged by pumas. Table 11. Puma cubs sampled July 2009 to July 2010 on the Uncompahgre Plateau Puma Study area, Colorado. a Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M112 M115 M117 M120 M121 P1016b P1017b M M M M M M M August 31, 2009 November 2008 August 2009 June 28, 2010 June 28, 2010 June 12, 2010 June 12, 2010 145 427 183 30 30 39 39 10 39 12 2.5 2.2 2.1 half eaten F70 F28 F119 F3 F3 F72 F72 52 68 66 107 107 51 51 Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs caught with mothers without radiocollars or mothers with non-functioning radiocollars. b Cubs P1016 and P1017 were monitored from birth via F72’s GPS data and visual of her nursery to the day of their death; but the cubs were not individually marked. Individual identification of non-marked pumas were designated with P one thousand series numbers (e.g., P1016). On the day we investigated F72’s nursery, male adult puma M32 was at the nursery; he had killed both cubs and half-consumed one about 3 to 6 hours before our arrival. 128 �Table 12. Summary of puma capture efforts with dogs, December 2004 to April 2010, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 Dec. 15, 2009 to April 30, 2010 Track detection effort 109/78 = 1.40 tracks/day 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 198/71 to 202/71 = 2.79-2.84 tracks/day 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day 266/86 = 3.09 tracks/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 93/86 = 1.08 pursuit/day 86/93 = 0.92 day/pursuit 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture 26/86 = 0.30 capture/day 9 pumas captured for first time 9/86 = 0.11 capture/day 86/26 = 3.31 day/capture 86/9 = 9.56 day/capture 129 �Table 13. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2010. Consort pairs and estimated agesa Dates pairs Estimated Estimated Estimated Observed consortedb birth datec birth interval gestation number of Female Age Male Age (mo.) (days) cubsd (mo.) (mo.) F2 53 05/28/05 3 F2 67 07/29/06 14.0 2 F2 89 05/19/08 22.0 4 F3 36 08/01/04 1 F3 50 M6 37 06/22-24/05 09/26/05 13.8 93-95 2 F3 62 09/17/06 11.7 3 F3 84 M51 60 03/31/08 07/03/08 21.5 94 3 F3 107 M55 69 03/28-31/10 06/28/10 23.8 89-92 2 F7 67 05/19/05 2 F7 82 08/13/06 14.9 4 F7 106 07/10/08 23.9 3 F8*e 24 06/26/05 2 F8 37 08/13/06 13.4 4 F8 60 M73 49 02/28-29/08 05/29/08 22.5 90-91 2 F16 32 09/22/05 4 F16 52 05/24/07 19.9 4 F16 75 M6 80 01/13-14/09 04/15/09 22.7 91-92 3 F23* 21 05/30/06 3 F23 45 M27 or 78 02/19-25/08 05/23/08 23.8 87-93 3 M29f 107 F24 75 M29 92 04/12-15/07 06/14/07 90-93 4 F25 74 08/01/05 1 F25 94 04/16/07 20.5 1 F25 110 08/19/08 16.1 2 F28* 36 06/09/06 2 F28 48 M29 88 12/27-29/06 03/30/07 11.7 92-93 ≥2 tracks F28 68 11/08 1 F30* 48 M55 34 04/16-20/07 07/17/07 88-92 3 F50 21 07/01/06 1 F54 24 07/01/06 1 F70* 38 M51 60 03/10/08 06/05/08 87 3 F70 52 08/31/09 14.8 3 F72* 28 07/09/08 1 F72 51 06/12/10 23.1 2 F75 32 06/01/07 1 F75 55 M73 61 02/11/09 05/07/09 23.2 93 2 F93 56 08/07 2 F93 90 06/16/10 2 F94* 46 05/27/09 3 F94 60 M55 70 04/15/10 07/15/10 13.3 91 3 F104 110 07/08/10 1 F111* 32 06/16/10 ≥1 tracks F116g 36-48 2009 2 F119 66 08/09 2 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. g When captured on 1/20/10, puma F116 was in association with 2 large cubs which were not captured. 130 �Table 14. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2010, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 M6 02-18-05 to 05-21-10 M27 03-10-06 to 05-07-09 M29 04-14-06 to 02-25-09 M32 M51 04-26-06 to 07-31-10 01-07-07 to 03-20-09 M55 M67 M71 01-21-07 to 07-31-10 08-23-07 to 07-31-10 01-29-08 to 11-12-09 M73 M100 02-21-08 to 07-31-10 03-27-09 to 07-31-09 M114 02-27-10 to 06-23-10 F2 01-07-05 to 08-14-08 F3 F7 01-21-05 to 07-31-10 02-24-05 to 08-03-08 F8 F16 03-21-05 to 07-31-10 10-11-05 to 09-11-09 F23 02-05-06 to 02-25-10 F24 F25 01-17-06 to 09-03-08 02-08-06 to 09-04-09 Status: Alive/Lost contact/Dead; Cause of death Dead. Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. M1 was killed by a puma hunter on 01-02-10 west of Bang’s Canyon, north of Unaweep Canyon, GMU 40. M1 was about 97 months old at death. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Dead. M6 was struck and killed by a vehicle on highway 550 south of Colona, CO on 05-21-10. M6 was about 99 months old at death. Dead. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-22-08 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. M27 was killed by a puma hunter on 12-09-09 in the North Fork Mesa Creek, Uncompahgre Plateau, GMU 61 North. M27 was about 100 months old at death. Dead. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. M29 was killed by a puma hunter on 11-16-09 in Beaver Canyon, GMU 70 East. M29 was about 121 months old at death. Alive. Dead. Lost contact− failed GPS/VHF collar after 03-20-09. Killed by a puma hunter on 12-11-09 in Shavano Valley, Uncompahgre Plateau study area. M51 was about 77 months old at death. Alive. Alive. M67 is offspring of F30. Dead. Lost contact– M71 shed his VHF collar with an expansion link on about 11-12-09. He was killed by a puma hunter on 12-09-09 on the west rim of Spring Creek Canyon, Uncompahgre Plateau study area. M71 was about 47 months old at death. Alive. Dead. M100 was killed by a puma hunter on 01-16-10 in Naturita Canyon, GMU 70 East. M100 was about 63 months old at death. Lost contact– after 06-23-10. VHF collar may have failed or puma dispersed. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. F2 was about 92 months old at death. Lost contact− failed GPS/VHF collar. Dead. Killed by U.S. Wildlife Services agent 08-03-08 for predator control of depredation on domestic sheep. F7 was about 107 months old at death. Alive. Dead. F16 was struck and killed by a vehicle on Ouray County Road 1 southwest of Colona, CO on 09-11-09. F16 was about 80 months old at death. Lost radio contact after12-02-09. Recaptured F23 on the study area 02-25-10, but could not be handled to replace non-functional GPS collar. Lost radio contact after 09-03-08− failed GPS/VHF collar. Lost radio contact after 09-04-09– failed GPS/VHF collar. 131 �Puma I.D. F28 Monitoring span 03-23-06 to 02-01-10 F30 04-15-06 to 07-29-08 F50 12-14-06 to 03-26-07 F54 01-12-07 to 08-18-07 F70 F72 F75 01-14-08 to 07-31-10 02-12-08 to 07-31-10 03-26-08 to 02-10-10 F93 F94 F95 F96 F104 F110 12-05-08 to 07-31-10 12-19-08 to 07-31-10 08-01-09 to 07-31-10 01-28-09 to 07-31-10 05-21-09 to 07-31-10 09-21-09 to 02-25-10 F111 F113 01-01-10 to 07-31-10 01-26-10 to 06-06-10 F116 F118 F119 01-20-10 to 07-31-10 02-25-10 to 07-31-10 03-25-10 to 07-31-10 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Lost radio contact after 09-25-07− failed GPS/VHF collar. Recaptured on the study area 02-01-10, but could not be handled to replace nonfunctional GPS/VHF collar. Dead. Killed by another puma (sex of puma unknown) 07-29-08. F30 was about 60 months old at death. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. F50 was about 30 months old at death. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. F54 was about 49 months old at death. Alive. Alive. Lost radio contact after 09-29-09– failed GPS/VHF collar. F75 in association with her cubs M105 and F106 when F106 was recaptured on 02-10-10 on the study area. Alive. Alive. Alive. Alive. Alive. Dead. Killed by a puma hunter on 02-25-10 in GMU 70 East. F110 was about 41 months old at death. Alive. Dead. F113 died 06-06-10 of injuries consistent with being struck by a vehicle. GPS data indicated that F113 had crossed highway 550 and roads on Loghill Mesa north of Ridgway 24-30 hours before she died in McKenzie Creek. F113 was about 42 months old at death. Alive. Alive. Alive. 132 �Table 15. Preliminary estimated survival rates (S) of adult-age pumas during the 4 years in the reference period (i.e., the study area is closed to puma hunting) and 1 year in the treatment period, Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma survival in the reference period pertained only to pumas that died of natural causes. Pumas that were killed by people in the reference period, a non-natural cause (i.e., F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. In the treatment period all sources of natural and human-caused mortality are considered in the survival estimates. Period of interest S 1.000 Females SE 0.0000 S 0.667a Males SE 0.2222a n 6a Reference Annual 8/1/2005 to 7/31/2006 0.909 0.0867 11 1.000 0.0000 5 Reference Annual 8/1/2006 to 7/31/2007 0.831 0.0986 14 1.000 0.0000 7 Reference Annual 8/1/2007 to 7/31/2008 0.875 0.1031 13 1.000 0.0000 8 Reference Annual 8/1/2008 to 7/31/2009 0.784 0.1011 19 0.667 0.1924 8 Treatment Annual 8/1/2009 to 7/31/2010 Treatment Annualb 0.333b 0.1361b 12b 8/1/2009 to 7/31/2010 With mortalities of all marked adult males a Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. b This second estimate of adult male puma survival includes 5 males that had non-functional (4) or shed (1) radiocollars. All adult males with non-functional or shed radiocollars in this study survived into treatment year 1 (TY1), which was expected considering adult male survival in 3 previous years. All 5 of those adult males were detected and killed by hunters in TY1. 133 n 10 �Table 16. Summary of subadult puma survival and mortality, December 2004 to July 2010, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 04-19-06 to 04-26-06 31 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 M31 7 190 M69 01-11-08 to 04-07-08 87 F95 12-29-08 to 07-31-09 214 M99 02-27-09 to 04-22-09 54 Status M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Alive. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old, a young adult. F52 dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adultstage home range. GPS collar nonfunctional. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-0608 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location) and an adult by about 24 month old (Aug. 2009). F95 established an adult home range adjacent to and overlapping the northern portion of her natal area. M99 died on unknown causes; but, possibly killed by another puma (holes in skull) in Jan. 2010 when he was about 16 months old. His radiocollar quit after 54 days. 134 �Table 16 continued. Puma I.D. M115 Monitoring span 01-13-10 to 07-21-10 No. days 189 Status M115 was offspring of F28, born in Nov. 2008. He was about 14 months old when first captured on Jan. 13, 2010. When he was recaptured on Mar. 18, 2010, he had previously suffered a broken left ulna. M115 was probably independent by July15, 2010 when he was located outside of his natal area on a probably dispersal move. M115 died on about July 21, 2010 apparently from complications of his broken left foreleg; possibly not allowing him to kill prey sufficiently for survival. M115 was about 20 months old at death. 135 �Table 17. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2010. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M5 02-04-05 13S,240577E, 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278E, 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M39 09-11-06 M43 09-15-06 12S,746919E, 4225441N→ 13S,500000Ex 4050000N 12S,724270E, 4243610N→ 12S,709889E, 4313490N 12S,760177E, 4242995N→ 12S,739859E, 4308557N M48 10-18-06 52.0 M49 12-05-06 12S,756676E, 4247777N→ 12S,704982E, 4248998N 12S,757241E, 4258259N→ 12S,693350E, 4274559N M58 06-27-07 73.2 M65 08-17-07 M68 08-23-07 13S,258543E, 4238071N→ 13S,274670E, 4309488N 12S,738144E, 4233628N→ 12S,684084E, 4314200N 13S,257371E, 4235231N→ 12S,711262E, 4198681N Estimated linear dispersal distance (km)* 102.2 71.3 68.6 66.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M39 was offspring of F8, born August 2006. M39 was killed by a puma hunter in Bangs Canyon, GMU 40 on 03-12-10 when he was 43 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29 months old. M48 was the offspring of F3, born September 2006. M48 was killed by a puma hunter in Tabeguache Creek, GMU 61 North on 12-27-09 when he was 39 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 0124-09; he was about 29 months old. M58 was offspring of F16, born May 2007. M58 was killed by a puma hunter on 12-27-09 in the North Fork of the Gunnison River north of Paonia, GMU 521; he was 31 months old. 97.0 M65 was offspring of F24, born July 2007. M65 was killed by a U.S. Wildlife Service agent for depredation on llamas in the Little Dolores River on 11-07-09. M65 was 28 months old. 80.7 M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. 136 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M69 01-11-08 13S,248191E, 4246810N→ 13T,378900E, 4591990N M82 07-05-08 F52 01-10-07 12S,726901E, 4243463N→ 13S,255316E, 4216768N 13S,258058E, 4236260N→ 13S,319217E, 4240467N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 369.6 M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. 60.5 M82 was offspring of F8, born May 2008. M82 was killed by a hunter on 12-10-09 in the Beaver Creek fork of East Dallas Creek, GMU 65. M82 was 19 months old. 61.1 F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old . F52 was treed again by puma hunters on about 12-16-09 south of Powderhorn: 13S,319480E,4233219N. F52 was about 53-55 months old. This suggests that F52 has an adult home range in that area. *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill or recapture site. 137 �Table 18. Recorded deaths of non-marked and marked pumas struck by vehicles and other unusual causes, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2010. Puma sex & ID if marked M Estimated age (mo) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870E,4227520N Highway 62 east of Dallas divide 13S,250000E,4222500N F17a 11 08-18-06 F 18-24 11-06-06 F 6 01-30-07 F 36 09-16-08 M 12-24 08-13-08 F61a 18 11-13-08 F 12 08-10-09 F16b 80 09-11-09 M6b 99 05-21-0 F113b 42 06-06-10 Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown, decomposed Good Good Good Good Good Good Not pregnant or lactating M 24 08-25-10 Vehicle Excellent P1018c collision a Subadult marked (i.e., tattoos, eartags), but not radio-collared. b Adult GPS/VHF-collared pumas. c Non-marked puma with P one-thousand number designation. 138 Highway 550 south of Colona 13S,257602E,4242185N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718E,4255277N Highway 145 west of Placerville 13S,756490E,4212336N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 145 east of Norwood 12S,745739E,4222548N Ouray County Road 1 13S,253733E,4240060N Highway 550 south of Colona 13S,258610E,4236805N F113 crossed Highway 550 and roads on Loghill Mesa 24-30 hours before she died in McKenzie Creek 13S,257272E,4238435N Highway 62 Leopard Creek 12S,237747E,4220330N �Table 19. GPS- and VHF-collared pumas with functioning collars using two camera grids (Area 1Loghill, Area 2- Delores Creek to Spring Creek) during August 21 to December 7, 2009 (i.e., 108 days), Uncompahgre Plateau, Colorado. Area 1- Loghill Puma Sex Estimated Collar & Number of Capture rate per day for ID Age (mo.) data type detections by primary camera configuration Aug.-Dec. cameras in grid (photo per puma/no. days) 2009 primary/alternate cameraa F16 female 79-83 GPS 0 0 F72 female 41-45 GPS 4/0 4/108 = 0.04 M6 male 90-94 VHF 6/0 6/108 = 0.06 M55 male 50-54 GPS 7/0 7/108 = 0.06 Area 2- Delores Creek to Spring Creek Puma Sex Estimated Collar & Number of Capture rate per day for ID Age (mo.) data type detections by primary camera configuration Aug.-Nov. cameras in grid (photo per puma/no. days) 2009 primary/alternate camerab F70 female 52-56 GPS 0 0 F94 female 49-53 VHF 3/1 3/108 = 0.03 F96 female 43-49 GPS 2/0 2/108 = 0.02 M32 male 96-100 VHF 4/0 4/108 = 0.04 M55 male 50-54 GPS 19/5 19/108 = 0.18 a Aug. 21 to Nov. 2 (74 days) to detect 3 of 4 adult pumas with functioning collars for first time. Aug. 21 to Oct. 20 (61 days) to detect 4 of 5 adult pumas with functioning collars for first time. It took 88 days (Aug. 21 to Nov. 16) to also detect 2 adult pumas with non-functioning collars. b 139 �Table 20. Numbers of GPS locations and spans of monitoring for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to July 2010. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a M M M M M M M M F F F F F F No. locations adult 12-08-04 to 07-20-06 1,797 adult 01-28-05 to 01-14-06 958 adult 02-18-05 to 05-14-08 1,035 adult 03-12-06 to 06-21-06 313 adult 04-14-06 to 01-01-08 1,599 adult 01-07-07 to 07-15-08 1,643 adult 01-21-07 to 08-09-10 3,226 adult 03-27-09 to 01-16-10 923 adult 01-07-05 to 08-14-08 3,516 adult 01-21-05 to 05-14-08 3,344 adult 02-24-05 to 08-03-08 3,922 adult 03-21-05 to 10-10-06 1,541 adult 10-12-05 to 09-10-09 3,801 subadult, 01-04-06 to 02-04-06 113 adult 02-05-06 to 09-04-09 2,281 F24 F adult 01-17-06 to 07-25-07 1,812 F25 F adult 02-09-06 to 06-26-09 3,398 F28 F adult 03-24-06 to 08-15-07 1,499 F30 F adult 03-30-07 to 02-22-08 1,057 F50 F adult 12-14-06 to 03-26-07 352 F52 F subadult 01-10-07 to 05-08-07 383 F54 F adult 01-12-07 to 08-18-08 723 F70 F adult 01-14-08 to 07-01-10 2,429 F72 F adult 02-12-08 to 07-07-10 2,842 F75 F adult 03-26-08 to 06-03-09 1,112 F96 F adult 01-28-09 to 08-08-10 1,061 F104 F adult 05-29-09 to 08-09-10 1,349 F111 F adult 01-01-10 to 08-02-10 488 F113 F adult 01-27-10 to 06-06-10 445 a GPS collars on pumas were remotely downloaded at approximately 1-month intervals, except during winter 20082009 to summer 2009 due to shortage of technicians during hiring freeze to assist in airplane flights to obtain downloads and to capture pumas to replace GPS collars (lengthening the download interval saved battery power). The last date in Dates monitored includes last location from the last GPS data download acquired for an individual puma. 140 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Methods for Monitoring Populations Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 141 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Figure 3. Expected (i.e., modeled) number of independent pumas on the Uncompahgre Plateau Study area after the harvest of 14.5% and 21.8% of independent pumas observed in the 2009-10 hunting season. The 14.5% harvest rate represents 8 independent pumas (3 females, 5 males) killed inside the study area. The 21.8% harvest represents 12 independent pumas (4 females, 8 males), including 4 pumas (1 female, 3 males) killed outside of the study area in addition to 8 killed inside the study area. The projected lines represent the expected population trends resulting from the observed harvest rates and sex structure. 142 �Figure 4. Estimated age structure of independent pumas in November 2009 at the beginning of the puma hunting season in Treatment Year 1 (TY1) on the Uncompahgre Plateau, Colorado. All these pumas were captured and sampled by researchers or harvested by hunters and examined by researchers. Mean ± SD of female and male ages, respectively: 4.55 ± 2.11 yr. (54.63 ± 25.29 mo.), n = 19; 5.48 ± 2.57 yr. (65.71 ± 30.88 mo.), n = 14. Figure 5. Puma births (black bars) detected by month during 2005 to 2010 (n = 34 litters of 17 females; 32 of the litters were examined at nurseries when cubs were 26-42 days old and 2 litters confirmed by tracks of ≥1 cubs following GPS-collared mothers F28 and F111 when cubs were ≤42 days old). Also shown (gray bars) are results of the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1 to 8 months old), Uncompahgre Plateau, Colorado. 143 �Montrose Figure 6. Layout of 2 camera grids on the east slope of the Uncompaghre Plateau Puma Study Area. Each grid was 80 square kilometers in size and contained 20 cells which were each 4 square kilometers. Area 1 was the south grid that covered Loghill Mesa to upper Horsefly Canyon. Area 2 was the north grid that covered from Dolores Canyon to Spring Creek Canyon. 144 �Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2010, Uncompahgre Plateau, Colorado. Puma I.D. M5 Estimated Age at capture (days) 183 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 02-04-05 to 04-07-08 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death ~8-1-04 F9 31 5-28-05 F10 31 5-28-05 ~1,345 F3 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 06-27-05 to 12-2-07 326-333 Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 4.5 years old. Lost contact― shed radiocollar 04-19-06 to 04-26-06. Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 12-30-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old Lost contact― shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 1208-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Dead; killed and eaten by a puma (sex unspecified) about 828-05. Lost contact― shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-06-06 to 06-14-06. F2 M11 31 5-28-05 F12 42 5-19-05 07-01-05 to 12-08-05― 01-26-06 F13 42 5-19-05 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F16 308-314 Dead. Lost contact― shed radiocollar 06-06-06 to 06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Dead; probably killed by another puma. Multiple bite wounds to skull. 10 mo. old. Lost contact― shed radiocollar 07-27-06 to 08-02-06. F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 244-245 Lost contact― shed radiocollar 05-24-06―05-25-06. F16 F21 37 9-26-05 Lost contact; radiocollar quit. Last aerial location 8-16-06, live signal. F3 176-215 918 203-252 101 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 11-02-05 to 08-16-06 301-308 330 324 145 Mother I.D. F2 F2 F7 F7 F8 F8 F16 F16 �Appendix A continued Puma I.D. Estimated Age at capture (days) M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 5-30-06 F35 31 5-30-06 F36 29 6-9-06 M37 29 6-9-06 M38 41 7-29-06 M39 29 8-13-06 Est. Birth date F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 12-21-05― 12-22-05 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 86-87 Dead; killed and eaten by male puma 12-21-05―12-22-05. F3 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 06-30-06 to 07-31-06 ~232-235 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 F23 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 38 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. F28 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 03-12-10 in GMU 40 when 43 months old. Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 Assumed dead. Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 Lost contact− shed radiocollar by 11-7 to 17-06. Treed 0301-07. Killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO at 29 months old. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 01-28-09 in GMU 41 when 29 months old. F7 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 63-65 63-65 74 74 352-353 9 255 9 255 53-61 106 200 146 Mother I.D. F23 F23 F28 F2 F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M44 33 Est. Birth date 8-13-06 Est. survival span from 1st capture to fate or last monitor date 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 183 7-1-06 360 89 360 12-05-06 to 07-31-07 to 01-01-07 F53 89 01-12-07 to 02-23-07 ~456 42 ~428 subad. 147 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Lost contact− shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. He was still dependent on F7. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 2006. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 61 when 39 months old. M49 was orphaned when his mother died on about 03-2607; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau (GMU 61 N) 01-24-09 when ~29 months old. Lost contact― shed radiocollar 2-23-07. F53 visually observed by P. & F. Star, on 9-2-07, when F53 was ~14 months old and an independent subadult. Mother I.D. F7 F7 F3 F3 F3 F50 F54 �Appendix A continued Puma I.D. Estimated Age at capture (days) M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 200 Lost contact― shed radiocollar 2-27-07. M56 observed 0301-07. Lost contact― shed radiocollar 06-07-07. Live mode 06-0607. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 521 when 31 months old. Alive. Observed alive 11-20-07 with F16, but without siblings M58 & F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F7 (?) Dead; research-related mortality.d F16 Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11/13/08. Not radio-collared. Not radio-collared. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Survived to adult stage; dispersed from natal area. Killed by Wildlife Services for depredation control on 11-07-09 when 28 months old. F16 52 324 434 F59 34 5-24-07 06-27-07 to 08-21-07 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 08-17-07 262 M65 34 7-14-07 08-17-07 262 148 F25 F16 F16 F24 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) F66 37 Est. Birth date 7-17-07 Est. survival span from 1st capture to fate or last monitor date 08-23-07 to 11-05-07 Age to last monitor date alive or at death (days, birth to fate) Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in Disappointment Valley, CO (GMU 71) 12-30-08 at 17 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 8/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. Not radio-collared. Apparently died before 2-4-09; no tracks found in association with F23 & siblings F81 & F97. 111 M67 37 7-17-07 08-23-07 M68 37 7-17-07 08-23-07 F74 259 6-1-07 M76 30 5-19-08 03-12-08 to 07-09-08 06-18-08 ~87 M77 30 5-19-08 06-18-08 ~87 F78 30 5-19-08 06-18-08 ~87 M79 30 5-19-08 06-18-08 87 F80 40 5-23-08 07-02-08 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 149 Mother I.D. F30 F30 F30 F75 F2 F2 F2 F2 F23 �Appendix A continued Puma I.D. Estimated Age at capture (days) F81 40 F97 8 ½ mo. 5-23-08 5-23-08 M82 37 M83 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-02-08 to 07-29-09 02-04-09 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 424 354 F23 F23 5-29-08 07-05-08 to 03-20-09 or 04-02-09 295-308 37 5-29-08 07-05-08 M84 36 6-5-08 07-11-08 to 02-11-09 Radio-collared. Last live location 7-29-09. Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Radio-collared. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in 12-10-09 GMU 65 when 19 months old. Not radio-collared. Apparently died; no tracks found in association with F8 & sibling M82 2-10-09. Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located here on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 211-09. F85 36 6-5-08 07-11-08 F70 F86 36 6-5-08 07-11-08 to 07-23 to 08-03-08 M87 M88 F89 M90 Male 7A 28 28 28 36 28-35 7-3-08 7-3-08 7-3-08 7-9-08 7-10-08 07-31-08 07-31-08 07-31-08 08-14-08 ~08-07-08 to 08-14-08 Male 7B 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Female 7C 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill. Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Not radio-collared. Radio-collared Radio-collared Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died of starvation after orphaned. F7 shot on 8-3-08 for killing domestic sheep. 251 ~48-59 28 to 35 150 Mother I.D. F8 F8 F70 F70 F3 F3 F3 F72 F7 F7 F7 �Appendix A continued Puma I.D. Estimated Age at capture (days) M91 35 M92 35 F95 16 mo. Est. Birth date Age to last monitor date alive or at death (days, birth to fate) 8-19-08 8-19-08 June-07 Est. survival span from 1st capture to fate or last monitor date 09-29-08 09-29-08 12-29-08 Sep-Oct08 Sep-Oct08 02-12-09 to 03-08-09 2-27-09 to 01-2010 146-176 05-20-09 to 09-19-09 05-20-09 157 05-20-09 to 09-17-09 06-14-09 to 02-09-10 06-14-09 to 03-16-10 159 241 F98 4-5 mo. M99 5 mo. M101 35 4-15-09 M102 35 4-15-09 F103 35 4-15-09 M105 38 5-7-09 F106 38 5-7-09 M107 34 5-25-09 F108 34 5-25-09 M109 M112 34 145 5-25-09 8-31-09 06-28-09 to 02-24-10 06-28-09 to 03-05-10 06-28-09 05-04-10 M115 14 mo. Nov.-08 07-21-10 610 M117 6 mo. Aug.-09 02-05-10 275 P1016(M) 39 6-12-10 06-12-10 to 07-21-10 39 P1017(M) 39 6-12-10 06-12-10 to 07-21-10 39 488 278 275 250 246 151 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Radio-collared. Radio-collared. Radio-collared. Survived to adult stage. Established adult home range overlapping F93’s home range. Radio-collared. Died, probably killed by male puma (infanticide). Radio-collared. Last location 4-22-09 on Paterson Mt. Died as 16-month old subadult in San Miguel Canyon. Cause of death unknown, possibly killed by another puma. Radio-collared. Died; killed by puma M55 after cub was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 9-4-09. Did not find evidence of M102 associated with deaths of siblings M101 and F103. But M102 probably died. Radio-collared. Died; killed by puma M55 after cub was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 2-9-10 due to shed collar. F25 F25 F93 Not radio-collared at nursery; F75 returned to nursery during handling. Radio-collared later on 2-10-10. Lost contact due to shed collar 3-16 to 29-10. Not radio-collared; too small. Recaptured 2-24-10; not collared. Shed radiocollar at nursery; fastener failed. Recaptured and re-collared 2-24-10. Shed collar ~3-5-10. Not radio-collared; too small. Radio-collared. Lost contact after 5-4-10 (last live signal) possibly due to failed transmitter. Radio-collared. M115 died as a subadult (~20 mo. old) due to complications of a broken left foreleg (natural cause). Radio-collared. Lost contact after 5-14-10 (last live signal); shed collar found on 7-15-10 in the natal area. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. F75 Unm.F Unm.F F16 F16 F16 F75 F94 F94 F94 F70 F28 F119 F72 F72 �Appendix A continued Puma I.D. Estimated Est. Est. survival span Age to last monitor date Status: Alive/Survived to subadult stage/ Mother Age at Birth from 1st capture to alive or at death (days, Lost contact/Disappeared/ I.D. birth to fate) capture date fate or last monitor Dead; Cause of death (days) date M120 30 6-28-10 07-28-10 Radio-collared. F3 M121 30 6-28-10 07-28-10 Radio-collared. F3 M122 35 7-8-10 08-12-10 Radio-collared. F104 F123 29 7-15-10 08-13-10 Radio-collared. F94 F124 29 7-15-10 08-13-10 Radio-collared. F94 M125 29 7-15-10 08-13-10 Radio-collared. F94 a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, possibly restricting movement 152 �Colorado Division of Wildlife July 2009 - June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 2 Federal Aid Project No. N/A : : : : : : Division of Wildlife Mammals Research Predatory Mammals Conservation Cougar Demographics and Human Interactions Along the Urban-Exurban Front-range of Colorado Period Covered: July 1, 2009 - June 30, 2010 Author: M.W. Alldredge Personnel: E. Joyce, T. Eyk, K. Blecha, L. Nold, K. Griffin, D. Kilpatrick, M. Paulek, B. Karabensh, D. Wroe, M. Miller, F. Quartarone, M. Sirochman, L. Wolfe, J. Duetsch, C. Solohub, J Koehler, L. Rogstad, R. Dewalt, J. Murphy, D. Swanson, T. Schmidt, T. Howard, D. Freddy CDOW; B. Posthumus, Jeffco Open Space; D. Hoerath, K. Grady, D. Morris, A. Hatfield Boulder County Open Space; H. Swanson, R. Hatfield, J. Reale Boulder Open Space and Mountain Parks; S. Oyler-McCance, USGS. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Sampling cougar feces in the field may be a feasible non-invasive sampling method to estimate cougar populations. We continued analyzing cougar fecal samples collected from the 3 sibling cougars in captivity at the Foothills Wildlife Research Facility. Feces were stored at controlled temperatures after deposition and sub-sampled at monthly intervals. Genetic material has been found in samples up to 6 months post-deposition, but genotyping error rates have not yet been assessed. We are investigating degradation rates further by sampling feces in natural, uncontrolled, environments deposited at known times from known individuals. All samples have been obtained and genotyped, and final analysis and a summary report is in progress. The use of telomeres as a method to determine the age structure of bear and cougar populations has continued to be examined. Further refinement of the age-to-length relationship for both species is warranted based on preliminary results. In addition to this, length relationships relative to genetic relatedness and individual stressors will give further insight into interpreting results from future data. Our principal research objective is to assess cougar population ecology, prey use, movements, and interactions with humans along the urban-exurban front-range of Colorado. This year capture efforts focused on re-collaring previously collared cougars, and capturing previously unmarked independent age cougars and cubs. We collared an additional 16 independent age cougars. Mortality remained high over the year exceeding 40% for independent age cougars (predominantly human related) and exceeding 50% 153 �for cubs (predominantly starvation). Home-range patterns remained consistent to previous years. The effectiveness of aversive conditioning is still showing mixed results, which is likely a factor of the opportunistic nature of cougars using urban environments and a lack of habituation to them. Cougar/human interactions were minimal this year compared with previous years. Relocation of cougars as a management tool has had limited assessment, but given some success, still warrants further investigation. Mule deer are the predominant prey in cougar diets, although males will also utilize elk regularly. 154 �WILDLIFE RESEARCH REPORT COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBANEXURBAN FRONT-RANGE OF COLORADO MATHEW W. ALLDREDGE P.N. OBJECTIVE 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban front-range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus) and estimating population densities of cougars for the state of Colorado. SEGMENT OBJECTIVES Section A: Genetics 1. Evaluate differences in DNA quantity from either a scat surface collection or a cross-sectional collection. 2. Evaluate differences in DNA quantity from successive feces depositions to determine the variation in quantities of genetic material in scats. Quantify differences in epithelial shedding rates. 3. Evaluate temporal, environmental, and seasonal effects on fecal DNA quantity and quality for both controlled and uncontrolled conditions. Section B: Telomeres 4. Evaluate the potential to develop a model for estimating age of bears and cougars based on telomere length. Section C: Front-range cougars 5. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. 6. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets. 7. Continue to assess relocation of cougars as a practical management tool. 8. Assess cougar predation rates and diet composition based on GPS cluster data. SECTION A: GENETICS INTRODUCTION Genetic techniques for monitoring or research of rare, elusive, and wide ranging species are of particular interest as other techniques are either impractical or financially prohibitive. Genetic techniques for monitoring and research of cougars in Colorado may be invaluable as alternative techniques are expensive and in many situations may not be possible. Capture and handling of cougars is expensive, time consuming, and may not give representative samples of the population. Large dispersal distances of cougars, especially males, will require impractically large study areas in order to understand demographic patterns that are affected by immigration. Capture may not even be possible in suburban and exurban areas of Colorado as logistical constraints associated with private land owners will likely prohibit the use of many capture techniques. 155 �Noninvasive genetic sampling (Hoss et al. 1992, Taberlet and Bouvet 1992) has the potential to provide a realistic method of sampling a population of interest. Noninvasive sampling techniques include the use of hair snares, and scat collections (Harrison et al. 2004, Smith et al. 2005). The use of scats for sampling cougar populations may be particularly useful and provide a representative sample of the population. Scat collections can either be done by searching transects with human observers (Harrison et al. 2004) or with trained dogs (Smith et al. 2005). Scats could also be collected from kill sites. Kill sites would need to be based on mortalities of radio-collared ungulate populations. Data from noninvasive sampling techniques are useful in describing dispersal patterns and estimating population size. Noninvasive genetic data are error prone, which in many cases is due to the quantity and quality of genetic material relative to the collection of noninvasive samples. Therefore, one objective over the last year has been to develop a study to evaluate degradation rates of DNA in fecal samples with respect to time and temperature. STUDY AREA The genetic degradation study is being conducted at the Foothills Wildlife Research Facility, located in Fort Collins, Colorado. This is the facility where 3 sibling cougars have been raised in captivity and are part of other ongoing research efforts. METHODS Fecal samples were collected from the 3 sibling cougars located at the Foothills Wildlife Research Facility. During the year the entire remaining sample of 60 feces per cougar were collected and samples were placed at random into one of three treatment groups (-5 C, +5 C, and +15 C). Genetic samples were collected from these at the time of initial collection and at 2 weeks, and 1, 2, 3, 4, and 6 months post deposition. DNA was extracted and then stored at -20 C Response variables that are being measured are number of incorrect identifications, allelic dropout rates (actual number of alleles that dropout in any given sample), and number of false alleles. The primary analysis is a logistic regression on the dichotomous identification variable, treating the three temperature regimes as covariates. Additional analyses summarize the rate at which alleles dropout and the occurrence of false alleles. A total of 60 scats have been collected and sub-sampled at each time period within treatment groups. PCR and DNA sequencing is being done at the Rocky Mountain Center for Conservation Genetics and Systematics laboratory. Individual cougars are screened and genotyped using 9 -12 nuclear microsatellite loci isolated from domestic cat (Menotti-Raymond and O’Brien 1995, Menotti-Raymond et al. 1999). Three recent studies have used sets of these primers successfully on mountain lions (Ernest et al. 2000, Sinclair et al. 2001, Anderson et al. 2004). We chose a set of these primers for our work. PCRs were performed using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). Each 12.5μl reaction contained 125μM each dNTP, 1X Taq buffer (Kahn et al. 1998), 0.034μM M13-tailed forward primer, 0.5μM non-tailed reverse primer, 0.5μM M13 dye-labeled primer with Beckman Coulter dyes D2, D3 or D4 (Proligo), and 0.31U Taq polymerase (Promega). The thermal profile for both the forward dye-labeled and the M13 dye-labeled reactions were as follows with the appropriate annealing temperature varying by locus: preheat at 94°C for 1 min, denature at 94 ºC for 1 min, anneal for 1 min, and extend at 72 ºC for 1 min for 35 cycles. The PCR products were diluted and run on the CEQ8000 XL DNA Analysis System (Beckman Coulter). All loci were run with the S400 size standard (Beckman Coulter) and analyzed using the Frag 3 default method. 156 �RESULTS AND DISCUSSION All samples have been collected and samples have been genotyped. Approximately 30 samples were collected in the field from radio-marked cougars over a range of deposition times and these have been genotyped as well. This work is still ongoing so an assessment of genotyping error rates has not been made. However, sufficient genetic material for genotyping has been found in samples up to 6 months old. Genetic degradation appears to occur at a slower rate than initially expected. This would indicate that scat surveys for individual identification of cougars may be a viable non-invasive sampling technique, if an efficient means of finding cougar scat in the field is available. SECTION B: TELOMERES BY M. ALLDREDGE AND J. PAULI INTRODUCTION Understanding the age structure of a population is very useful to managers, especially for hunted populations. Age structure can provide indications about the appropriateness of current harvest levels, changes that may need to occur in harvest, and the general health of a population. Typical approaches involve estimating age structure based on sampling harvested animals and obtaining ages based on tooth wear and replacement characteristics or from analyzing tooth annuli. Recently a new approach has been developed for some species that estimates the age of animals based on examining the length of telomeres in relation to the age of the animals. Telomeres are repetitive DNA sequences that cap the ends of eukaryotic chromosomes, whose nucleotide sequence (T2AG3)n is highly conserved across vertebrate species (Meyne et al. 1989). During each cell cycle telomeric repeats are lost because DNA polymerase is unable to completely replicate the 3’ end of linear DNA (Watson 1972). Thus, telomeres progressively shorten with each cell division; past research has demonstrated age-related telomere attrition in a variety of laboratory and wild species and has correlated telomere length with individual age (e.g. Hausmann et al. 2003, Hemann and Greider 2000). Using real-time quantitative polymerase chain reaction (Q-PCR; Cawthon 2002), we quantified telomere length for cougars and black bears of known-age in Colorado. STUDY AREA Genetic samples for black bears were obtained from blood collections taken from bears captured in Wyoming and Colorado. Genetic samples for cougars were obtained from either blood or tissue samples taken from cougars in Colorado as part of either the Uncompahgre Plateau or Front-Range cougar studies. METHODS We quantified telomere length in cougar and bear tissue samples using a real-time quantitative polymerase chain reaction (Q-PCR) technique (Cawthon 2002). This method measures relative telomere lengths by determining the factor by which a sample DNA differs from an arbitrary reference DNA in its ratio of telomere repeat copy number (T) to single copy gene number (S). The T/S ratio of one individual relative to the T/S for another reflects relative differences in telomere length between individuals. This approach is highly accurate (Cawthon 2002), particularly for differentiating relative telomere length among individuals within a species (Nakagawa et al. 2004). In theory, any single copy gene sequence can be employed for standardization; we chose to use the single copy gene, 36B4, which was originally employed to develop this method for quantifying telomere length in humans (Cawthon 2002). Using genome data for eight species (carnivores, primates, birds, amphibians, ungulates, and rodents; accessible 157 �at http://www.ncbi.hlm.nih.gov/) and the computer program, ClustalX (version 1.81), we conducted a sequence alignment and have determined that the 36B4 gene is highly conserved across vertebrate taxa and appears to be a suitable internal standard for a wide range of species, including the cougars and black bears. We ran telomere PCR and single-copy gene PCR on different 96-well plates; preparation of telomere and single-copy plates was identical except for the primers. We diluted extracted DNA with distilled water to 3 ng∙μl-1. For each animal, we added 10 μl of diluted DNA to 2 adjacent wells. To generate a standard curve, we diluted DNA from an arbitrarily chosen animal to 1 ng ∙μl-1, 2.5 ng∙μl-1, 4 ng∙μl-1 and 6 ng∙μl-1 and added 10 μl of each concentration to 3 adjacent wells. Between rows of samples, distilled water without template DNA was added to 2-4 wells as negative controls. Plates were sealed with a rubber cover, centrifuged briefly and heated in a thermocycler at 96 ˚ C for 10 minutes. After cooling the plate for 10 minutes, we added the final PCR reagents. For the telomere PCR, the reagents included 2.25 μl distilled water and 12.5 μl SYBR Green PCR Master Mix (Applied Biosystems). For the single-copy PCR, reagents included 2.3 μl distilled water, 12.5 μl SYBR Green PCR Master Mix. The final primer concentrations were tel 1b, 100 nM; tel 2b, 900 nM; 36B4u, 300 nM and 36B4d, 500 nM. Primer sequences were: tel 1b, 5’ CGG TTT GTT TGG GTT TGG GTT TGG GTT TGG GTT TGG GTT 3’; tel 2b, 5’ GGC TTG CCT TAC CCT TAC CCT TAC CCT TAC CCT TAC CCT 3’; (Cawthon pers. comm.; Callicott and Womack 2006) 36B4d, 5’ CCC ATT CTA TCA TCA ACG GGT ACA A 3’; and 36B4u, 5’ CAG CAA GTG GGA AGG TGT AAT CC 3’ (Cawthon 2002). After sealing the plate with a transparent adhesive cover, we briefly vortexed and centrifuged it. We used an automated thermocycler (7500 Real-Time PCR System, Applied Biosystems) to perform Q-PCR. For telomeres, the reaction profile began with a 94 ˚ C incubation for 1 minute, followed by 40 repetitions of 1 second of denaturing at 96˚ C then 1 minute of annealing-extending at 54˚ C. For the single-copy PCR, the incubation lasted 10 minutes at 95˚ C, followed by 35 repetitions of 95˚ C for 15 seconds and 58˚ C for 1 minute. Using Applied Biosystems (ABI; Applied Biosystems Foster City, CA) software, we generated a standard curve to estimate the amount of T and S for each cougar/bear sample. From these values we calculated the T/S ratio for each individual. RESULTS AND DISCUSSION Amplification efficiencies were reasonable and consistent for both the single copy gene and telomere in the cougar samples. Standard curves obtained for cougars enabled a robust estimate of relative telomere length. However, there was considerable inconsistency in the standards used to quantify black bear telomere length and single copy gene. Estimated PCR efficiencies ranged from 51-263% and individual standards fluctuated even within a reaction. In general, inconsistent PCR amplifications prevent reliable estimation of telomere length and is often the consequence of poor sample quality. The DNA samples from black bears used quantify telomere length had low concentrations, and were potentially damaged during shipment to Laramie. Because of the limitation in these samples and resultant data, we did not calculate relative telomere length for black bears. Once age estimates have been obtained from the cougars for which we quantified telomere length, we will explore the relationship between age class and relative telomere length. 158 �SECTION C: FRONT-RANGE COUGARS BY M. ALLDREDGE AND K. BLECHA INTRODUCTION At the local scale, efforts have been made to continue the cougar/human interaction study on the Front-Range of Colorado. Given that cougars currently coexist with humans within urban/exurban areas along Colorado’s Front-Range, varying levels of cougar-human interaction are inevitable. The CDOW is charged with the management of cougars, with management options ranging from minimal cougar population management, to dealing only with direct cougar-human incidents, to attempted extermination of cougars along the human/cougar spatial interface. Neither inaction nor extermination represents practical options nor would the majority of the human population agree with these strategies. In the 2005 survey of public opinions and perceptions of cougar issues, 96% of the respondents agreed that it was important to know cougars exist in Colorado, and 93% thought it was important that they exist for future generations (CDOW, unpublished data). There is a growing voice from the public that CDOW do more to mitigate potential conflicts, and the Director of CDOW has requested that research efforts be conducted to help minimize future human/cougar conflicts. In order to meet these goals CDOW believes it is necessary to directly test management prescriptions in terms of desired cougar population and individual levels of response. Long-term study objectives for the Front-Range Cougar Research project will involve directly testing management responses of cougars at various levels of human interaction, as well as collecting basic information about demographics, movement, habitat use, and prey selection. The Cougar Management Guidelines Working Group (CMGWG) (2005) recommend that part of determining the level of interaction or risk between cougars and humans is to evaluate cougar behavior on a spectrum from natural, to habituated, to overly familiar, to nuisance, to dangerous. The CMGWG (2005) clearly state that there is no scientific evidence to indicate that cougar habituation to humans affects the risk of attack. As a continuation from the pilot study efforts, we have continued to assess the effectiveness of aversive conditioning as a method to alter interaction rates between cougars and humans. We also continue to monitor relocated cougars to determine the effectiveness of relocation as a management tool. The use of GPS collars obtaining up to 8 locations per day also allows for a detailed examination of demographic rates. We are monitoring cougars that utilize natural habitats and cougars that use a mixture of natural and urban habitats. This allows for an assessment of demographic rates, movement patterns, and habitat use among cougars utilizing these two habitat configurations. We have also begun monitoring cubs (approximately 6 months of age or older), primarily to determine survival but potentially to understand movement patterns and dispersal. The use of GPS collars also allows us to study predator-prey relationships and diet composition. GPS locations are divided into selection sets based on the likelihood of the set of locations (clusters) representing a kill site. A random sample of these clusters are investigated to determine what a cougar was doing at the site, and whether or not it represents a kill site. Kill sites are thoroughly investigated to determine as much information as possible about what was killed at the site. STUDY AREA The original pilot study was conducted in Boulder and Jefferson counties, in an area near Interstate 70 north to approximately Lyons, Colorado, which was also a likely area for addressing longterm research objectives (see Figure 1). The study area for the long term study includes this original area but was expanded south to highway 285. Research efforts in the additional southern portion are generally 159 �limited to capturing cougars that are in the urban setting and/or have interacted directly with humans. The study area is comprised of many land ownerships, including private, Boulder city, Boulder County, Jefferson County, and state and federally owned lands. Therefore, we have been directly involved with Boulder city and Boulder and Jefferson county governments to obtain agreements from these entities on conduct of research and protocols for dealing with potential human/cougar interactions prior to conducting any research efforts. We have also acquired permission to access numerous private properties to investigate cougar clusters and to trap cougars. METHODS Baiting, using deer and elk carcasses, has been conducted throughout the year, with a focus on areas that do not allow the use of hounds. Bait sites are monitored using digital trail cameras to determine bait site activity. Cage traps were generally used for capture when cougars removed the bait and cached it. Beginning in November, 2009 and continuing through April, 2010, hounds were also used several times per week to capture cougars. Snares were used in situations where hounds could not be used and cougars would not enter cage traps. Captured cougars were anesthetized, monitored for vital signs, aged, measured, and ear-tagged. All independent cougars (> 18 months old) were fitted with GPS collars. All cubs greater than 15 kg (approximately 6 months or older) were ear-tagged with 22 g ear-tag transmitters. For detailed capture and handling procedures see the study plan APPENDIX I. When cougars interact with humans and elicit a response from CDOW District Wildlife Managers (DWMs) they are potential candidates for aversive conditioning. However, only a subset of these will actually be conditioned and the remaining animals will not be treated in order to have a control group. At this time, we consider aversive conditioning treatments on cougars to potentially be: multiple captures and handling of cougars, single or multiple treatments using beanbags fired from a shotgun, single or multiple chases using hounds, and potential combinations of capture, hound chases, and beanbags. Initially, we want to assess situations and methods that are already being implemented by wildlife managers. The most likely scenario are incidents occurring in neighborhoods, where relocating the cougar is necessary prior to any application of an aversive conditioning treatment. For these situations, all treatments will require the relocation of the offending individual to an adjacent open-space property or similar area. Following relocation we will either chase the cougar off using rubber bullets or beanbag rounds, pepper spray, or hounds. For first time offenders we will initially try rubber bullets or beanbag rounds. Second time offenders will be chased with hounds. If rubber bullets or beanbag rounds are not affecting cougar behavior, we will begin using pepper spray on first time offenders. The other scenario that will occur are incidents in areas where a cougar can be directly conditioned or chased from the area. We will mimic the above approach as much as possible, and use rubber bullets or beanbag rounds on first time offenders. If possible we will chase individuals with hounds on their second offense, although this may not always be practical. Pepper spray may not be practical either in many situations. As a second level treatment where direct hound chases are not practical, we will attempt to capture, relocate, and aversive condition the individual. Cougars will only be relocated for management purposes, generally in conjunction with human conflict or livestock depredation. Research cougars that have been collared for other purposes of the study may also become part of the relocation group if their levels of human interaction warrant such a management action. Because only a few cougars are relocated each year, we will collar and monitor all cougars that are relocated in the northeast region. Cougars will be ear-tagged and fitted with a telemetry collar (VHF, or GPS collars may be used depending on the situation). 160 �Release area is critical to the success of any relocation, however, suitable relocation areas may be difficult to find. Such an area must be far enough from the problem area, have suitable prey, and be remote enough so that the individual will not be presented with problem opportunities at or near the release site. Understanding the minimum release distance that has a reasonable chance for relocation success is useful for both logistical reasons and to increase the number of potential release sites. We evaluated cougar diet composition by using GPS location data to identify likely kill sites. Characteristics of clusters of GPS locations representing cougar-killed ungulate sites (Anderson and Lindzey 2003, Logan 2005) were used to develop a standard algorithm to group GPS points together, to provide a sound sampling frame from which statistical inference could be made about clusters that are not physically investigated. GPS collars collected locations 7 to 8 times/day to reflect time periods when cougars are both active and inactive. The clustering routine was designed to identify clusters in five unique selection sets (S1, S2,…, S5) in order to identify clusters containing two or more points, those that contained missing GPS locations, and those that were represented by single points. The clustering algorithm was written in Visual Basic and was designed to run within ARCGIS (Alldredge and Schuette, CDOW unpubl. data 2006). The widths of the spatial and temporal sampling windows were user specified, in order to meet multiple applications and research needs. This also enabled adjustment of the sampling frames to improve cluster specifications as needed. We used the following protocol to investigate cougar GPS clusters in the field. For S1 clusters, we investigated each cougar GPS location in the cluster by spiraling out a minimum of 20 m from the GPS waypoint while using the GPS unit as a guide, and visually inspecting overlapping view fields in the area for prey remains. Normally, this was sufficient to detect prey remains and other cougar sign (e.g., tracks, beds, toilets) associated with cougar. If prey remains were not detected within 20 m radius of the cluster waypoints, then we expanded our searches to a minimum of 50 m radius around each waypoint. For S2 through S5 clusters, we went to each cougar GPS location and spiraled out 50 m around each waypoint, while using the GPS unit as a guide. Depending on the number of locations, topography, and vegetation type and density, we spent a minimum of 1 hour and up to 3 hours per cluster to judge whether the cluster was a kill site. RESULTS AND DISCUSSION Collared cougars from the previous year were captured and re-collared to replace exhausted batteries throughout the year. An additional 16 independent age cougars were also captured and collared during the year (Table 1). Currently there are 18 independent age cougars in the study with functioning GPS collars, including a rehabilitation cougar that dispersed to New Mexico. Home ranges for collared cougars have been determined using minimum convex polygons (MCP) to depict the general pattern of use and potential overlap (Figure 2), but likely over-represent the actual area used by an individual. Home ranges exhibit similar patterns to previous years, being fairly linear in a north-south direction. Adult male home ranges are much larger than adult female home ranges. Subadult male home ranges are smaller than adult male home ranges, but are also characterized by large movements and significant overlap with adults (Figure 2). Female home ranges are smaller with sizes between 80 and 120 km2. Female home ranges also have significant overlap, especially among related individuals (Figure 2). 161 �Mortalities of collared cougars were high with 7 new mortalities during the 2009-10 year (Table 1). Causes of death included vehicle collision, unknown sources, hunting, and management or landowner euthanasia. Field investigations of GPS clusters have been conducted on 31 of the radio collared cougars in order to understand predation and feeding habits. From Aug 1, 2008 untill July 31, 2010, we have visited >1,402 clusters (S1-S5 types). However, only 1,100 of these clusters were considered to be random samples and thus inferences have only been drawn from this subset representative of the feeding habits of the cougars. Each cluster was classified by the probable behavior of the focal cougar. These sites averaged over the individuals were BED sites (12.8% ± 6.2%), UNKNOWN (63.8% ± 5.5%), and FEEDING sites (23.7% ±3.8%). Of the FEEDING sites, 21.5% ±3.8% were KILL sites and 2.2% ± 1.1% were SCAVENGING sites. UKNOWN sites were any site where no prey remains or cougar bedding sign was found, and is thus thought to represent travelling and/or hunting activities. When examining 477 random S1 clusters (clusters with at least 2 locations within 200m) we found a 46.4% ± 16.3% chance of being a probable FEEDING site. 622 of the clusters visited were of the S2, S3, S4, and S5 cluster types, and these showed to have a much lower probability of being a FEEDING site (6.3% ± 2.7%). Of particular interest was that the percentage of SCAVENGING cases represented 9.9% (± 5.7%) of known FEEDING sites. Of the known FEEDING sites, a vast majority (85.5%) were detected with the S1 cluster types, while a smaller percentage were detected with the S2-S5 cluster types (Figure 3). For prey composition, we calculated the frequency (percentage) of occurrence of food items, averaged over the sample of collared cougars. Of the clusters with feeding activity, mule deer were the primary prey items (67.5% ± 11.9%), non-cervids were secondary (19.1% ± 10.7%), and elk the least used (13.3% ± 7.6%) found at clusters with confirmed feeding activity (Figure 4). Elk were found as prey items at clusters for male cougars (33.9%) much more frequently than female cougars (2.0% ± 1.9%). Females fed on deer (77.7% ± 13.3%) more frequently than males (49.1% ±19.6%) but differences are not yet substantiated to be significant. No significant differences were found between the frequencies of alternative prey items fed upon between females (20.3% ± 13.1%) and males (16.9% ± 19.3%) (Figure 5). For this preliminary analysis, we also grouped prey items by relative size (Table 3). Female cougars killed a significantly higher proportion of Class 3 (i.e. coyote or fawn sized) prey compared to male cougars. Females also killed a much larger proportion of Class 2 prey compared to males. Males killed a significantly higher proportion of Class 5 and 6 prey compared to females (Figure 6). When pooling Class 1-3 into a small prey category, and Class 4-6 into a large prey category, we can speculate that males feed upon a higher proportion of large prey compared to females while females feed upon a higher proportion of small prey. A large difference does exist within males, as larger prey items (80.6% ± 14.1%) are fed upon much more frequently than smaller prey (19.4% ± 14.1%) (Figure 7). GPS cluster locations are downloaded in monthly intervals, and then visited during the next monthly interval. Because our GPS cluster investigation sampling scheme utilizes a random representative sample of prey items from the entire time period a focal cougar is collared, a variable time lag exists between the day that a GPS cluster is made and when personnel can conduct a field visit to the actual site. This variable time lag may range between 1-60 days, and it is suspected that some prey items are missed as decomposition and scavengers can make it more difficult for field observers to verify the presence of prey remains. To investigate if a real bias may exist, we grouped each cluster by the time lag into 15 day intervals (1-15, 16-30, 31-45, 46-60). We then calculated the frequency of each probable action category (BED, FEEDING, UNKNOWN) occuring in each interval. To examine if a seasonal effect is possible, we classified clusters by the season that they were created in. October 1 – April 30 was considered winter, while May 1 – September 30 was considered summer. We found that the FEEDING actions decreased as the time lag increased. This was accompanied by an increase in the frequency of 162 �sites that were classified as UNKNOWN (Figure 8). This same pattern was observed when looking at the summer clusters (Figure 9), but not as apparent in the winter seasons (Figure 10). SUMMARY Genetic analysis for cougar feces revealed that DNA is still present in samples after feces have been in controlled temperature environments for up to 6 months. Genotyping error rates still need to be assessed. However, the presence of DNA in these samples suggests that field detection of cougar scats may be a viable non-invasive population sampling technique. We have added known-age samples collected from natural environments from known cougars marked in the front-range cougar project. The use of telomeres as a method to determine the age structure of bear and cougar populations is promising and will be investigated further in the coming year. Further refinement of the age-to-length relationship for both species is warranted. In addition to this, length relationships relative to genetic relatedness and individual stressors will give further insight into interpreting results from future data. In addition to re-collaring previously collared cougars, an additional 16 independent age cougars were collared during the year. Mortality remained high over the year exceeding 40% for independent age cougars and exceeding 50% for cubs. Home-range patterns remained consistent to previous years. The effectiveness of aversive conditioning is still showing mixed results, which is likely a factor of the opportunistic nature of cougars using urban environments and a lack of habituation to them. Relocation of cougars as a management tool has had limited assessment, but given some success, still warrants further investigation. Mule deer are the predominant prey in cougar diets, although males also utilize elk regularly. LITERATURE CITED Alldredge, M.W. 2007. Cougar demographics and human interactions along the urban-exurban front range of Colorado. Wildlife Research Report July: 153-202. Colorado Division of Wildlife, Fort Collins, USA. Anderson, C. R., F. G. Lindzey, and D. B. McDonald. 2004. Genetic structure of cougar populations across the Wyoming Basin: metapopulation or megapopulation. Journal of Mammalogy 85:12071214. Boutin-Ganache, I., M. Raposo, M. Raymond, and C. F. Deschepper. 2001. M13-tailed primers improve the readability and usability of microsatellite analyses performed with two different allele-sizing methods. Biotechniques, 31:25-28. Cawthon, R. M. 2002. Telomere measurement by quantitative PCR. Nucleic Acids Research 30:e47. Cougar Management Guidelines Working Group. 2005. Cougar Management Guidelines, 1sted. WildFutures, Bainbridge Island, Washington, USA. Ernest, H. B., M. C. T. Penedo, B. P. May, M. Syvanen, and W. M. Boyce. 2000. Molecular tracking of mountain lions in the Yosemite Valey region in California: genetic analysis using microsatellites and faecal DNA. Molecular Ecology 9:433-441. Harrison, R. L., P. B. S. Clarke, and C. M. Clarke. 2004. Indexing swift fox populations in New Mexico using scats. American Midland Naturalist 151:42-49. Haussmann, M.F., D.W. Winkler, K.M. O’Reilly, C.E. Huntington, I.C.T. Nisbet, and C.M. Vleck. 2003. Telomeres shorten more slowly in long-lived birds and mammals than in short-lived ones. Proceedings of the Royal Society of London Series B 270:1387-1392. Hemann, M. T., and C. W. Greider. 2000. Wild-derived inbred mouse strains have short telomeres. Nuclei Acids Research 28: 4474-4478. Hoss, M., M. Kohn, S. Paabo, F. Knauer, and W. Schroder. 1992. Excrement analysis by PCR. Nature 359:199. 163 �Logan, K.A. 2006. Cougar population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report July:95-122. Colorado Division of Wildlife, Fort Collins, USA. Menotti-Raymond, M. and S. J. O’Brien. 1995. Evolutionary conservation of ten microsatellite loci in four species of Felidae. Journal of Heredity 86:319-322. Menotti-Raymond, M., V. A. David, L. A. Lyons, A. A. Shcaffer, J. F. Tomlin, M. K. Hutton, and S. J. O’Brien. 1999. A genetic linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57:9-23. Meyne, J, R. L. Ratliff, and R. K. Moyzis. 1989. Conservation of the human telomere sequence (TTAGGG)n among vertebrates. Proceedings of the National Academy of Sciences 86: 7049-7053. Nakagawa, S., N.J. Gemmell, and T. Burke. 2004. Measuring vertebrate telomeres: applications and limitations. Molecular Ecology 13:2523-2533. Sinclair, E. A., E. L. Swenson, M. L. Wolfe, D. C. Choate, B. Bates, and K. A. Crandall. 2001. Gene flow estimates in Utah’s cougars imply management beyond Utah. Animal Conservation 4:257-264. Smith, D. A., K. Ralls, B. L. Cypher, and J. E. Maldonado. 2005. Assessment of scat-detection dog surveys to determine kit fox distribution. Wildlife Society Bulletin 33:897-904. Taberlet, P., and J. Bouvet. 1992. Bear conservation genetics. Nature 358:197. Watson, J.D. 1972. Origin of concatameric T4 DNA. Nature-New Biology 239:197-201. Prepared by Mathew W. Alldredge, Wildlife Researcher 164 �Table 1: Capture history, aversive conditioning treatments and current status of all independent age cougars captured as part of the Front-range cougar study. Cougar ID AM02 Sex M Age 1 1.5 1.5 7 7 8 8 8 9 5 6 7 7 4 2 2 4 5 1.5 AM04 M AM06 M AF03 AF01 AM05 F F M AM07 M AF08 F AM09 M AF10 F AF19 F AF11 F 8+ 1.5 AM20 M 4 1.5 3 1.5 2.5 7 8+ 8+ Date 6/14/07 1/10/08 2/9/08 7/14/07 10/17/07 4/29/08 5/5/08 8/4/08 2/24/09 11/21/07 12/30/08 2/2/10 2/15/10 11/29/07 12/17/07 12/19/07 12/4/09 4/4/10 12/26/07 4/19/08 12/26/07 6/18/09 12/28/07 12/27/08 1/15/08 2/13/08 3/4/08 3/18/09 4/13/09 1/20/09 3/5/08 6/10/08 3/6/08 Location Lacey Prop. White Ranch Coal Creek White Ranch Eldorado Springs Magnolia/Flagstaff South Boulder North Boulder Boulder Canyon Heil Valley Ranch Heil Valley Ranch Reynolds Ranch White Ranch Flagstaff Table Mesa White Ranch White Ranch Golden Heil Valley Ranch Highway 7 Heil Valley Ranch West Horsetooth Heil Valley Ranch Hwy 34 (mile 70) Apex Open Space I-70 Heil Valley Ranch North Boulder Left Hand Canyon Dowe Flats South Table Mesa US-40/Empire White Ranch Occurrence Baiting Capture effort Intraspecific mortality Baiting Livestock depredation Replace Collar Seen in town Killed deer in town Punctured intestine Capture effort Replace Collar Replace Collar Hunter Deer kill Deer kill Capture effort Replace collar Roadkill Capture effort Roadkill Capture effort Deer kill-remove collar Capture effort Roadkill Deer Kill Roadkill Capture effort Deer Kill Deer Kill Deer Kill Deer Kill Roadkill Capture effort 165 Capture Cage Hounds Release Loc On-site On-site Conditioning NA NA Cage Cage Hounds Free-dart Cage On-site White Ranch On-site Lindsey Centennial Cone NA Beanbag NA Beanbag Beanbag Hounds Hounds Hounds On-site On-site On-site NA NA NA Cage Cage Hounds Hounds On-site On-site On-site On-site NA NA NA NA Hounds On-site NA Hounds Cage Hounds On-site On-site On-site NA NA NA Cage On-site NA Hounds Cage Cage Cage Cage On-site Heil Valley Ranch Heil Valley Ranch On-site On-site NA Beanbag NA NA NA Hounds On-site NA Status Alive Alive Dead Alive Alive Alive Alive Alive Dead Alive Alive Alive Dead Alive Alive Alive Alive Dead Alive Dead Alive Alive Alive Dead Alive Dead Alive Alive Alive Alive Alive Dead Alive �AF15 F 6 7 AF17 F 9+ AF12 F 2 AM13 M 2 AM14 M 3 2 AF34 F 3 1.5 AM18 M 2.5 1.5 AF16 F 3 AF45 AF40 F F AF24 F 5 1.5 2.5 10+ AM31 M 1.5 AF37 F 2.5 1.5 AM21* M 1.5 5/18/08 3/18/08 4/2/09 3/25/10 3/29/08 5/20/08 5/8/08 5/29/08 2/13/09 5/8/08 12/17/08 12/17/09 5/15/08 5/20/08 4/14/09 2/16/10 12/5/08 3/18/09 1/4/10 12/24/08 3/14/09 12/29/08 3/20/09 1/2/09 1/27/09 2/22/10 2/12/09 2/25/09 4/4/09 5/31/09 12/31/08 3/29-09 2/16/10 12/31/08 8/11/09 8/29/09 West of White Ranch Coffin Top Hall Ranch Coffin Tip Sugarloaf Four-mile Canyon N. Boulder N. Boulder N. Boulder Sugarloaf Heil Valley Ranch Heil Valley Ranch South Boulder South Boulder Rollins Pass Left Hand Canyon Heil Valley Ranch N. Boulder Heil Valley Ranch Evergreen Evergreen Evergreen Evergreen Gold Hill White Ranch White Ranch North Boulder Hwy 7 North Boulder North Boulder Evergreen Conifer Douglas, WY Evergreen I-70 N. Boulder Livestock Depredation Capture effort Replace Collar Replace Collar Pet depredation Unknown mortality Deer Kill Livestock depredation Deer Kill Livestock depredation Replace Collar Replace Collar Seen under deck Deer kill Replace Collar Replace Collar Capture effort Deer kill Replace Collar Deer kill Livestock depredation Deer Kill Livestock depredation Deer kill Capture effort Replace Collar Deer Kill Replace Collar Raccoon Kill Encounter Chicken coop Livestock depredation Hunter Chicken coop Roadkill Encounter 166 Shot Hounds Hounds Hounds Cage On-site On-site On-site Within 1 mile NA NA NA Beanbag Cage Cage Snare Cage Hounds Hounds Free-dart Free-dart Hounds Hounds Hounds Cage Hounds Cage Cage Snare Cage Cage Hounds Snare Cage Hounds Free-dart Shot Hounds Cage US Forest Boulder Canyon Near Ward None On-site On-site On-site Lindsey West of Rollinsville On-site On-site On-site Heil Valley Ranch On-site Mt. Evans SWA None Flying J Open Space Mt. Evans SWA On-site On-site On-site Hall Ranch On-site Heil Valley Ranch Beanbag Beanbag Euthanized Beanbag NA NA None Beanbag NA NA NA Beanbag NA None Euthanized None Beanbag NA NA NA None NA None On-site Mt. Evans SWA None None Free-dart On-site None Free-dart Ward None Dead Alive Alive Alive Alive Dead Alive Alive Dead Alive Alive Alive Alive Alive Alive Alive Alive Alive Alive Alive Dead Alive Alive Alive Alive Alive Alive Alive Alive Dead Alive Alive Dead Alive Dead Alive �AF32 AM46 F M 2 1.5 2 3/???/10 9/28/09 11/13/09 AF50 AM44 F M 3 6 AM606 AF54 AF52 AM51 AF56 AF55 M F F M F F 2 4 4 1.5 1.5 4 11/24/09 12/15/09 3/18/10 1/6/10 1/14/10 1/28/10 1/28/10 2/22/10 2/23/10 AM53 AM60 AF58 AF62 AF59 M M F F F 4 2 1.5 5 5 3/13/10 3/29/10 4/4/10 4/13/10 4/22/10 SW023 SW026 SW107 F M M 1 1 1 4/9/09 10/20/09 5/7/10 Loveland?? Indian Hills Evergreen Genesee West of Boulder White Ranch White Ranch Boulder White Ranch Hall Ranch Hall Ranch Conifer Conifer Conifer Genesee Walker Ranch Table Mesa Walker Ranch Blue Jay/Jamestown Livestock depredation Livestock depredation Elk kill Livestock depredation Deer kill Capture effort Replace collar Seen in town Capture effort Capture effort Capture effort Livestock depredation Livestock depredation Pet Depredation Elk Kill Baiting Baiting Elk Kill Deer Kill Cage Cage Shot Cage Hounds Hounds Free-dart Hounds Hounds Hounds Cage Cage Cage Cage Cage Cage Cage Cage Within 1 mile On-site None None On-site On-site On-site MacGregor Ranch On-site On-site On-site Mt. Evans SWA Mt. Evans SWA Euthanized On-site On-site On-site On-site On-site NA NA NA None NA NA NA Beanbag Beanbag NA NA NA NA NA Dead Alive Alive Dead Alive Alive Alive Alive Alive Alive Alive Alive Alive Dead Alive Alive Alive Alive Alive Rehab Rehab Rehab Release Release Release Pike forest Hermit Park Radium None NA NA Alive Alive Unkn 167 �Table 2: Capture history, maternal relationship, aversive treatment and current status of all cubs capture as part of the Front-range cougar study. Cougar ID Sex Age Mother Date AF35 F 3 AF16 12/29/08 12/31/08 AM36 M 3 AF16 12/29/08 1/8/09 AM30 M 8 AM01 1/30/09 AM38 M 8 AM01 1/30/09 3/27/09 3/30/09 4/9/09 AM29 M 6 Euth. 2/11/09 12 6/15/09 AM21* M 12 Unkn 3/25/09 AM25 M 12 Unkn 5/22/09 9/13/09 AM41 M 12 Unkn 5/22/09 Location Evergreen Evergreen Evergreen Evergreen S. Boulder S. Boulder S. Boulder S. Boulder Morrison N. Boulder N. Boulder Table Mesa Indian Hills Occurrence Deer Kill Roadkill Deer Kill Starvation Deer Kill Deer Kill Encounter Pet Depredation Encounter Deer Kill Encounter Baiting Deer Kill Raccoon Indian Hills Deer Kill Indian Hills Encounter 168 Capture Cage Release Loc Conditioning Flying J Open Space Cage Flying J Open Space Cage Cage Free-dart Free-dart Free-dart Free-dart Free-dart Cage Cage Free-dart Free-dart Shot On-site On-site Lindsey Centennial Cone None Hall Ranch Masonville On-site On-site Perforated intestine On-site Beanbag None Euthanized None Beanbag NA None None Status Alive Dead Alive Dead Alive Alive Alive Alive Dead Alive Alive Alive Alive Dead Alive Dead �Table 3: Classification scheme for the most common prey items found at cluster sites. Other uncommon prey items were found including gray fox, corvids, bighorn sheep lamb. PREY CLASS 1 2 3 4 4.5 5 6 PREY ITEM (example) Squirrel, Bird, Rabbit Porcupine, Domestic Cat, Fox, Raccoon, Skunk Coyote, Fawn Deer, Domestic Dog Calf Elk, Yearling Deer Unknown Deer Yearling Elk, Adult Deer, Alpaca Adult Elk, Horse, Cattle 169 SIZE (small/large) Small Small Small Large Large Large Large �Figure 1: Study area boundary with the continental divide to the west, Highway 285 on the south, Highway 34 and 36 on the north, and the edge of the foothills on the east. 170 �Figure 2: Male and female MCP homeranges for cougars with functioning GPS collars depicting the overlap in homeranges between males and females. 171 �4.0% 4.0% 6.2% 0.4% S1 S2 S3 S4 S5 85.5% Figure 3: Percentage of feeding sites detected with S1, S2, S3, S4, and S5 cluster types. Figure 4: Mean proportion of Deer, Elk, and non-cervid prey remains found at feeding sites. Mean proportion drawn from the mean of 31 subject cougars (n=31). Error bars represent 95% Confidence Limits with an assumed normal distribution. 172 �Figure 5: Mean proportion of Deer, Elk, and non-cervid prey remains found at feeding sites, classified by cougar sex. Averaged over female subject cougars and male subject cougars, (Female n = 20, Male n=11). Error bars represent 95% Confidence Limits with assumed normal distribution. Figure 6: Mean proportion of sites with confirmed Class 1, 2, 3, 4, 4.5, 5 and 6 prey types for male and female subjects. (Female n = 20, Male n=11) Error bars represent 95% confidence intervals assuming a normal distribution. Female subject killed a significantly higher proportion of Class 3 prey over male subjects. Females also killed a much larger proportion of Class 2 prey over male subjects, but statistical significance is unknown. Males killed a significantly higher proportion of Class 6 prey over females. Males also killed a higher proportion of Class 5 prey over females, but statistical significance is unknown. 173 �Figure 7: Frequency of large and small prey found at cougar feeding sites. Small prey consisted of Prey classes 1-3 (small mammals-Fawn deer). Large prey consisted of prey classes 4-6. Figure 8: Frequency of occurance for the three primary actions at GPS cluster sites, categorized by time lag (i.e. 0-15 days) from when site was visited by the focal cougar to visitation by field personnel. Number of clusters in each time lag is represented by n. As time passes, chances of detecting feeding evidence decreases. 174 �Figure 9: Frequency of occurance for the three primary actions at GPS cluster sites in the summer season, categorized by time lag (i.e. 0-15 days) from when site was visited by the focal cougar to visitation by field personnel. Number of clusters in each time lag is represented by n. As time passes, chances of detecting feeding evidence decreases. Figure 10: Frequency of occurance for the three primary actions at GPS cluster sites in the winter season, categorized by time lag (i.e. 0-15 days) from when site was visited by the focal cougar to visitation by field personnel. Number of clusters in each time lag is represented by n. Visitation time lag is not as strong as a predictor for the frequency of occurrence of feeding activity. 175 �176 �Colorado Division of Wildlife July 2009 – June 2010 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 7210 1 : : : : Division of Wildlife Mammals Research Customer Services/Research Support Library Services N/A Period Covered: July 1, 2009 – June 30, 2010 Author: Kay Horton Knudsen Personnel: Kay Horton Knudsen, Chad Bishop All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife Research Center Library has existed for several decades in the Ft. Collins office. A library housed in the Denver office was moved to Ft. Collins many years ago. Early librarians, Marian Hershcopf and Jackie Boss, can be credited with the physical organization of the Library including seven decades of Federal Aid reports, almost 50 years of Wildlife Commission reports and a unique book and journal collection. Jackie Boss retired in April 2007 and the Library was temporarily closed to all services. Kay Horton Knudsen was hired as the new Research Center Librarian and began employment with CDOW on August 30, 2008. The goal, as stated by a former supervisor, was to reopen the Library and expand the electronic and digital capabilities of library services to the entire Colorado Division of Wildlife. Chad Bishop became the Mammals Research Team Leader in July 2009. His duties include supervision of the Research Center Library. A progress report and current status of the Library are detailed below. 177 �WILDLIFE RESEARCH REPORT COLORADO DIVISION OF WILDLIFE RESEARCH LIBRARY SERVICES KAY HORTON KNUDSEN P.N. OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Division of Wildlife (CDOW) employees, cooperators and wildlife educators. SEGMENT OBJECTIVES 1. Continue to improve and modernize library services. 2. Continue to develop, improve, and implement the CDOW Research Center Library web-site. SUMMARY OF LIBRARY SERVICES When the Research Center Library reopened in August 2008, the librarian was charged with choosing and implementing a web-based Integrated Library System (ILS) and purchasing statewide access for Colorado Division of Wildlife staff to online research databases. Once those systems were available on a new Library website, training and outreach to staff should take place. Alongside these online efforts was the task of physical organization and cleaning of the Library offices, cataloging the backlog of purchased books and staff reprint articles, streamlining the periodical selection/purchase process and, with the help of work-study staff from Colorado State University, sorting through stacks of donated documents. EOS International was chosen as the vendor for the ILS. It was decided to initially purchase the basic modules (a hosted system with library catalog, circulation, cataloging and serials control) and delay other features until the system was up and running. The Library website was released to CDOW staff in March 2009. Full-text searchable PDFs of Division reports and staff reprints were added to the online catalog as they became available to the librarian. The next module purchased from EOS was Indexer – this feature allows for full-text searching of the linked PDFs and was implemented in December 2009. In addition to the catalog of books and reports housed in the Ft. Collins Library, the Library website also gives all CDOW staff access to research databases. Current subscriptions include BioOne, four of EBSCO’s specialty databases (Environment Complete, Fish and Fisheries Worldwide, Wildlife and Ecology Studies Worldwide and SocIndex with Full Text), SORA (Avian journals) and the JSTOR Life Sciences collection. Through several of the print periodical subscriptions, the Library also has access to the publisher’s full-text online archives. Backfiles of major wildlife and aquatic journals were purchased to expand the full-text capability. CDOW staff are authenticated through WildNet (intranet) eliminating the need for individual usernames and passwords. The next step was training of CDOW staff on the various features of the new Library website. Group and individual sessions were held in Ft. Collins and at CDOW offices in Glenwood Springs, Grand Junction, Durango, Montrose, Colorado Springs, Denver, Hot Sulphur Springs, and Gunnison during 2009 and 2010. Handouts were created to assist staff with basic website use and the specialized database features such as creating subject and table of contents alerts. 178 �Other projects in the Library this year included: 1) reorganization of the book, reference and journal collections to make them more accessible to the library staff, 2) weeding and storing duplicate copies and updating the catalog records as part of the first project, 3) cataloging new material, 4) continued addition of PDF formats into the catalog’s bibliographic file, 5) clean-up of old-style bibliographic barcodes in the Library database, 6) renewal of print journal subscriptions based on discussions with research managers and the cancellation of print journals when full-text was available electronically, 7) printing and cataloging of the Data Analysis Unit (DAU) reports to maintain a historic record in the Library collection, 8) discussion with vendors on adding a federated/integrated search capability to the Library catalog and 9) initial research and testing of equipment and options for digitization of CDOW documents; a printer/scanner was purchased. A job duty of the librarian is to assist with CDOW research publications. Sagebrush of Colorado by Alma H. Winward was reprinted; the full-color brochure from 2004 is a popular state publication. Two Special Reports were recently issued: number 81, Colorado bighorn sheep management plan, 20092019 and number 82, A Compendium of crustacean zooplankton and Mysis diluviana collections from selected Colorado reservoirs and lakes, 1991-2009. The librarian attended the Colorado Association of Libraries conference in Denver in November 2009, and the international WebWise10 conference on digitization in libraries in Denver in March 2010. There was also the opportunity to participate in several online “webinars” sponsored by various vendors and library agencies to expand knowledge on trends in the library field. With the introduction of the expanded library services and the training sessions, the number of requests for documents or research assistance has grown. Most questions received in the Library are from CDOW staff or from outside researchers (generally consultants and out-of-state natural resources employees). At this time the Library is not open on a walk-in basis to the general public but the librarian does assist the Help Desk at the Denver office with questions they receive. CDOW employees generally request journal articles or items from the Library collection; outside researchers most often want a copy of a CDOW publication. The chart below shows the number of reference questions and document requests handled by the librarian during the past 2 years. Please note that one request from a CDOW staff member may be for multiple journal or book titles. Reference Requests August 2008 September 2008 October 2008 November 2008 December 2008 January 2009 February 2009 March 2009 April 2009 May 2009 June 2009 July 2009 August 2009 September 2009 October 2009 November 2009 December 2009 January 2010 February 2010 March 2010 April 2010 May 2010 June 2010 15 21 33 14 28 33 30 35 24 13 20 179 Reference Requests 20 25 30 38 28 32 62 43 36 23 17 26 �STATISTICS: The Research Center Library holds 18,390 titles and 23,912 items (these are the multiple copies of a title) and has 108 registered patrons (CDOW staff). There were 2,026 searches conducted in the Library catalog during the year. Usage statistics for the research databases are given in the chart below. For American Fisheries Society, BioOne and EBSCO the numbers are for the total searches run; for JSTOR the statistics are for the number of successful full-text article requests. July 2009 August 2009 September 2009 October 2009 November 2009 December 2009 January 2010 February 2010 March 2010 April 2010 May 2010 June 2010 TOTAL American Fisheries 27 20 3 81 53 81 83 152 128 41 56 37 762 BioOne EBSCO searches JSTOR 172 49 87 103 64 105 123 113 91 33 35 9 984 1255 261 872 442 686 647 764 652 1448 331 381 487 8226 111 190 187 166 289 249 361 238 322 176 116 84 2489 Prepared by ___________________________ Kay Horton Knudsen, Librarian 180 � https://cpw.cvlcollections.org/files/original/7cd810dd6211f3c05a0e40bde15759b8.pdf 913bc859c64272f4d2a65cc7163f46dc PDF Text Text i ��WILDLIFE RESEARCH REPORTS JULY 2010 – JUNE 2011 MAMMALS PROGRAM COLORADO DIVISION OF PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). i �STATE OF COLORADO John Hickenlooper, Governor DEPARTMENT OF NATURAL RESOURCES Mike King, Executive Director PARKS AND WILDLIFE COMMISSION Tim Glenn, Chair……………………………………………….………..………………….……......Salida Gary Butterworth, Vice Chair…………………………………………………………..…Colorado Springs Mark Smith, Secretary…………………………………………………………………………….….Center David Brougham……………………………………………………………………………………..Denver Chris Castilian ……………………………………………….………….….………………..............Denver Dorothea Farris………………………………………………………………………….….……Carbondale Allan Jones………………………………………………………………………………………...…Meeker Bill Kane………………………………………………………………………………………………Basalt Gaspar Perricone………………………………………………………………………………….….Denver Jim Pribyl……………………………………………………………………………………………Boulder John Singletary……………………………………………………………………..…………………Pueblo Robert Streeter…………….……………………………….……………………………………Fort Collins Lenna Watson………………………………………………………………………………..Grand Junction Dean Wingfield………………………………………………………………………..……………....Yuma Mike King, Executive Director, Ex-officio………….…………………...………………….…….....Denver John Salazar, Dept. of Agriculture, Ex-officio….………………………………..…….…………….Denver DIRECTOR’S LEADERSHIP TEAM Rick Cables, Director Ken Brink, Steve Cassin, Greg Gerlich, Marilyn Gallegos Ramirez, Susan Hunt, Gary Thorson, Jeff Ver Steeg MAMMALS RESEARCH STAFF Chad Bishop, Mammals Research Leader Mat Alldredge, Wildlife Researcher Chuck Anderson, Wildlife Researcher Eric Bergman, Wildlife Researcher Jake Ivan, Wildlife Researcher Heather Johnson, Wildlife Researcher Ken Logan, Wildlife Researcher Kay Knudsen, Librarian Margie Michaels, Program Assistant ii �Colorado Division of Parks and Wildlife July 1, 2010 − June 30, 2011 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS LYNX / WOLVERINE CONSERVATION WP 0638 ASSESSING THE EFFECACY OF MONITORING WOLVERINE ON A REGIONAL SCALE USING OCCUPANCY AND ABUNDANCE ESTIMATION by J. Ivan……………………………………………………………...…1 WP 0670 MONITORING CANADA LYNX IN COLORADO USING OCCUPANCY ESTIMATION: INITIAL IMPLEMENTATION IN THE CORE LYNX RESEARCH AREA by J. Ivan……………………………….………………………...11 WP 0670 PREDICTED LYNX HABITAT IN COLORADO by J. Ivan………………………….21 DEER / ELK CONSERVATION WP 3001 PROGRAM FINAL REPORT DEER CONSERVATION RESEARCH FOR 5-YEAR FEDERAL AID GRANT W-185-R by C. Bishop…..………………………..37 WP 3001 POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson……………………………………………………..51 WP 3001 EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER IN MULE DEER by C. Bishop…..……………………………………………………..71 WP 3001 EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER by E. Bergman.................................................................................................................77 WP 3001 DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS by C. Bishop….………………………………...85 WP 3001 ASSESSMENT OF SURVIVAL AND OPTIMAL HARVEST STATEGIES OF ADULT MALE MULE DEER IN MIDDLE PARK, COLORADO by E. Bergman………………………………………………………………………….97 WP 3002 EVALUATING SOLUTIONS TO REDUCE ELK AND MULE DEER DAMAGE ON AGRICULTURAL RESOURCES by H. Johnson………………………………..123 PREDATORY MAMMALS CONSERVATION WP 3003 BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS by H. Johnson………………………………………………………………139 iii �WP 3003 PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU by K. Logan………………………………………….177 WP 3003 COUGAR DEMOGRAPHICS AND HUMAN INTERACTION ALONG THE URBAN-EXURBAN FRONT-RANGE OF COLORADO by M. Alldredge………...237 SUPPORT SERVICES WP 7210 LIBRARY SERVICES by K. Knudsen……..……………………………...………….293 iv �Colorado Division of Parks and Wildlife July 2010–June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0638 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Wolverine Conservation Assessing the efficacy of monitoring wolverine on a regional scale using occupancy and abundance estimation Period Covered: July 1, 2010 – June 30, 2011 Author: J. S. Ivan Personnel: M. Schwartz, USFS Rocky Mountain Research Station; M. Ellis, University of Montana All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The wolverine (Gulo gulo) has a circumpolar distribution comprised mostly of tundra and boreal forest. However, its current range extends southward in peninsular fashion to the Cascades and Rocky Mountains of the conterminous United States. Recently the U.S. Fish and Wildlife Service ruled that the North American wolverine in the contiguous U. S. is a candidate species for protection under the Endangered Species Act. Thus, there is considerable interest in identifying monitoring schemes capable of detecting declines in wolverine populations over a large scale. We used spatially explicit simulations in which wolverine were sampled on a virtual landscape to quantify our ability to detect declines using robust-design occupancy estimation. We systematically varied 1) the number of sample units surveyed, 2) the number of visits made to each unit in the sample, and 3) the rate of population decline and computed the power to detect declines under various scenarios. Initial results indicate that occupancy estimation may work well for detecting large declines (50% decline over 10 years), but power to detect less catastrophic declines was low. Approximately 100 sample units would need to be surveyed to have adequate power to detect a 50% decline over 10 years. A census (350 sample unit) would be needed to ensure decent power for detecting smaller declines. Power increases as number of visits to each sample unit increases from 2 to 3 per survey season, but making more than 3 visits does not increase power substantially. If confronted with design tradeoffs that lead to having a better detection probability vs. those that allow for more units to be sampled, it is better to increase detection probability and survey fewer units. Future simulations will address the power to detect increases in population size in addition to declines, and we will attempt to compare power to detect declines using abundance estimation with that obtained using occupancy estimation. 1 �WILDLIFE RESEARCH REPORT ASSESSING THE EFFICACY OF MONITORING WOLVERINE ON A REGIONAL SCALE USING OCCUPANCY AND ABUNDANCE ESTIMATION. JACOB S. IVAN P. N. OBJECTIVE Assess power for detecting trends in wolverine population growth using occupancy and abundance estimation. SEGMENT OBJECTIVES 1. Build code to simulate realistic distribution and space use of wolverine on the landscape. 2. Build code to realistically simulate sampling the wolverine population using an occupancy framework. 3. Build code to analyze data “collected” via occupancy surveys. 4. Summarize results of 100s of iterations of randomly generated wolverine distributions and subsequent occupancy surveys; plot power to detect trends against various scenarios intended to reflect the range of conditions expected for both the sampling and process portions of the simulation. INTRODUCTION The wolverine (Gulo gulo) has a circumpolar distribution comprised mostly of tundra and boreal forest. However, its current range also extends southward in peninsular fashion to the Cascades and Rocky Mountains of the conterminous United States. Recently the U.S. Fish and Wildlife Service ruled that the North American wolverine in the contiguous U. S. was a candidate for protection under the Endangered Species Act (U.S. Fish and Wildlife Service 2010). Therefore, considerable interest exists in identifying monitoring schemes capable of detecting declines in wolverine populations over a large scale. Colorado Parks and Wildlife (CPW) has expressed interest in potentially pursuing a wolverine reintroduction, and monitoring program would be an integral part of such an effort. Additionally, with minor modifications, the simulation approach outlined here could be used to inform current Canada lynx (Lynx canadensis) monitoring efforts in Colorado. Thus, the work described here holds benefits for wolverine conservation in general as well as current and future CPW projects. Estimating abundance or occupancy are 2 means around which a monitoring scheme for wolverines could be constructed. Within these general approaches, there are numerous sampling methods that could be employed in the field. For instance, individual identification necessary for abundance estimation can be obtained from pelage patterns (Royle et al. 2011), scat samples (Flagstad et al. 2004, Ulizio et al. 2006), hair snags (Mulders et al. 2007), or a combination of methods (Magoun et al. 2011). Similarly, occupancy information can be obtained via aerial track surveys (Magoun et al. 2007, Gardner et al. 2010), remote cameras (R. Inman, Wildlife Conservation Society, unpublished data) or any genetic sampling technique. In all cases, the models used to estimate abundance and/or occupancy are the same; field methods only change the probability of detecting (and potentially identifying an individual(s) and the cost of obtaining those detections. Our aim was to use simulation to generically estimate power for detecting population declines of interest in the Northern Rockies. Simulations are spatially explicit, sampling occurs randomly and we are currently using robust design occupancy models to look at power. Here we report only on our initial simulations using occupancy estimation. 2 �METHODS Simulated landscape and wolverine distribution All simulations were programmed in R (R Core Development Team 2011), with calls to C++ (Stroustrup 1997), RMARK (Laake and Rexstad 2011), and MARK (White and Burnham 1999) as necessary. The simulation landscape included Idaho, western Montana, and northwest Wyoming (Figure 1). We overlaid this landscape with a raster dataset depicting “persistent spring snow” as this layer adequately captures the bioclimatic niche of wolverines (Copeland et al. 2010). Each 500-m pixel in the raster could take values 1 to 7 depending on the number of years from 2000-2006 that snow was present between April 24 and May 15 in that pixel. At the beginning of each iteration of the simulation, we randomly dispersed home range centers across the landscape subject to the following constraints based on wolverine ecology (Figure 2): 1) 2) 3) 4) Home range centers (points) were required to fall within the spring snow layer. Male home range centers were required to be >12.5 km apart. Female home range centers were required to be >8.5 km apart. Female home range centers could fall within male buffers, and transient males could fall within resident male or female buffers. Once home range centers were distributed, we temporarily assigned each animal a bivariate normal utilization distribution scaled to match UD estimates from the literature. To impart more realism in these UDs, we multiplied the bivariate normal kernel for each animal by the underlying spring snow layer, then divided each pixel value in the resulting product by the total of all values for that animal to recreate a probability distribution. Functionally this process produces a center-weighted UD in which mass is piled up over pixels with higher values of persistent spring snow. Each animal’s UD was different depending on the underlying configuration of spring snow. We began each simulation with 200 males, 200 females, and 100 transients for a total of 500 wolverines in the Northern Rockies landscape. Our simulated population size was based on available wolverine abundance information and expert opinion. We then simulated a 10%, 20%, or 50% decline in this population over 10 years by randomly removing individuals from the landscape at each time step. Simulated Sampling To simulate collection of occupancy data, we overlaid a sampling grid of 225km2-cells (n = 385 total cells) across the landscape. This cell size corresponds roughly to the home range size of female wolverine. At the beginning of each year, we computed the probability of at least 1 wolverine being available to sample in each cell on any given occasion for each cell in sampling grid: where w = total number of wolverines in the simulation. For each visit within a given year, we drew a random uniform number (i.e., U(0,1)) and compared this number to the product: p(≥1 wolverine available)p(wolverine detected | available). If the random number was less than this product, wolverine were detected in that cell on that visit (occasion) and we entered a “1” in the encounter history for that cell-occasion. Otherwise, we entered a “0.” We proceeded to sample in this manner for each visit to each cell for each year of the simulation. This results in a vector of 0s and 1s (i.e., an encounter history) for each cell that is 10x in length where “x” is the number of visits made during each of 10 years. For each unique landscape and declining wolverine population, we created several different datasets using this general sampling process. We specified detection probability, p(wolverine detected | available), to be 3 �either 0.2 or 0.8 and specified the number of visit to each cell in a year to be 2, 3, 4, 5, 6, or 7. This results in 2 × 6 = 12 datasets for each simulated population decline. We also considered the situation in which surveys could only be accomplished every other year, which resulted in another 12 datasets in which no data were collected during even years. Analysis of simulated data For each simulated dataset we used the R (R Development Core Team 2011) package RMARK (Laake and Rexstad 2011) to construct a robust design occupancy model (MacKenzie et al. 2006, p. 183224) for fitting in program MARK(White and Burnham 1999). We allowed the occupancy (use) parameter (ψt) as well as colonization (γt) and extinction (εt) to vary through time in an unconstrained manner, but constrained detection probability (p) to be constant to reflect how it was simulated. This resulted in 10 estimates of probability of occupancy, or use, from each dataset. We then fit a random effects trend model to these 10 data points (also using the RMARK interface for MARK to account for covariance between estimates; Figure 4), and retained the slope of the trend line along with 95% confidence interval for that slope. When the 95% confidence interval for the slope of the trend line did not include zero, we considered a trend detected, otherwise a trend was not detected. The number of times a trend was detected out of the total simulations is an estimate of the power of the approach to identify the specified declines given the number of visits and detection probability specified. RESULTS As expected, initial results indicate that occupancy estimation should work well for detecting large declines (50% decline over 10 years, λ = 0.933) when detection probability is high (p = 0.8). Under these conditions, power was 80% when sampling 50 units, regardless of the number of visits, and approached 100% when sampling 100 units (Figure 5, “continuous sampling” panels). Power declined some, but was still respectable, even when detection probability was low (p = 0.2). In that case a power of 0.8 could be achieved with 4-6 visits to 100 sample units. Power to detect a 20% decline over 10 years (λ = 0.977) was diminished, however, especially when detection probability was low. For instance, in order to achieve 80% power, even with high detection probability, would require surveys in an estimated 300 sample units. There is no realistic chance of detecting minor declines (e.g., 10% over 10 years, λ = 0.989) using occupancy estimation (Figure 5). Not surprisingly, power declines when sampling occurs every other year rather than annually (Figure 5, “gap sampling” panels). However, if detection probability is high, adequate power (0.8) can be achieved to detect a 50% decline over 10 years if such a scheme is implemented in a reasonable number of sample units (100), even with as few as 2-3 visits. Ability to detect smaller declines (20% or 10% over 10 years) is poor regardless of detection probability, number of sample units or number of visits (Figure 5, “gap sampling” panels). Generally, we found that when detection probability is high, power increases as number of visits to each sample unit increases from 2 to 3 per survey season, but making more than 3 visits does not increase power substantially. However, when detection probability is low, gains can be realized by making more visits. This result re-confirms a well-documented phenomenon unique to occupancy estimation (MacKenzie et al. 2006, p. 168). Also, if confronted with design tradeoffs that lead to having a better detection probability vs. those that allow for more units to be sampled, it is always better to increase detection probability and survey fewer units. DISCUSSION Our initial simulations suggest that occupancy estimation may work well in a monitoring context if the survey techniques employed have relatively high detection probability and interest lies only in 4 �detecting sharp declines in the population. Future work on this project will focus on determining the effects of varying the size of sample units, using alternate starting population sizes, detecting increasing trends rather than decreasing, and making sure that detection and occupancy estimates match well with recently collected pilot data (R. Inman, unpublished data). Additionally, we will incorporate cost functions into the modeling effort and investigate how well occupancy estimation compares to abundance estimation, which can be accomplished by sampling with hare snares or by photographing unique throat patch patterns via remote camera LITERATURE CITED Aubry, K. B., G. M. Koehler, and J. R. Squires. 2000. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. Copeland, J. P., K. S. McKelvey, K. B. Aubry, A. Landa, J. Persson, R. M. Inman, J. Krebs, E. Lofroth, H. Golden, J. R. Squires, A. Magoun, M. K. Schwartz, J. Wilmot, C. L. Copeland, R. E. Yates, I. Kojola, and R. May. 2010. The bioclimatic envelope of the wolverine (Gulo gulo): do climatic constraints limit its geographic distribution? Canadian Journal of Zoology-Revue Canadienne De Zoologie 88:233-246. Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty, P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524-531. Dolbeer, R. A., and W. R. Clark. 1975. Population ecology of snowshoe hares in the central Rocky Mountains. Journal of Wildlife Management 39:535-549. Flagstad, O., E. Hedmark, A. Landa, H. Broseth, J. Persson, R. Andersen, P. Segerstrom, and H. Ellegren. 2004. Colonization history and noninvasive monitoring of a reestablished wolverine population. Conservation Biology 18:676-688. Gardner, C. L., J. P. Lawler, J. M. Ver Hoef, A. J. Magoun, and K. A. Kellie. 2010. Coarse-Scale Distribution Surveys and Occurrence Probability Modeling for Wolverine in Interior Alaska. Journal of Wildlife Management 74:1894-1903. Getz, W. M., S. Fortmann-Roe, P. C. Cross, A. J. Lyons, S. J. Ryan, and C. C. Wilmers. 2007. LoCoH: Nonparameteric Kernel Methods for Constructing Home Ranges and Utilization Distributions. Plos One 2. Getz, W. M., and C. C. Wilmers. 2004. A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography 27:489-505. Hodges, K. E. 2000a. The ecology of snowshoe hares in northern boreal forests. Pages 117-161 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. _____. 2000b. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163-206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. Ivan, J. S. 2011. Density, demography, and seasonal Movement of snowshoe hares in central Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. Laake, J. L., and E. Rexstad. 2011. RMark - an alternative approach to building linear models in MARK. in E. Cooch, andG. C. White, editors. Program MARK: A gentle introduction. 5 �MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, UK. Magoun, A. J., C. D. Long, M. K. Schwartz, K. L. Pilgrim, R. E. Lowell, and P. Valkenburg. 2011. Integrating Motion-Detection Cameras and Hair Snags for Wolverine Identification. Journal of Wildlife Management 75:731-739. Magoun, A. J., J. C. Ray, D. S. Johnson, P. Valkenburg, F. N. Dawson, and J. Bowman. 2007. Modeling wolverine occurrence using aerial surveys of tracks in snow. Journal of Wildlife Management 71:2221-2229. McKelvey, K. S., K. B. Aubry, and Y. K. Ortega. 2000. History and distribution of lynx in the contiguous United States. Pages 207-264 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. Mulders, R., J. Boulanger, and D. Paetkau. 2007. Estimation of population size for wolverines Gulo gulo at Daring Lake, Northwest Territories, using DNA based mark-recapture methods. Wildlife Biology 13:38-51. Pebesma, E. J. 2004. Multivariable geostatistics in S: the gstat package. Computers & Geosciences 30:683-691. Royle, J. A., A. J. Magoun, B. Gardner, P. Valkenburg, and R. E. Lowell. 2011. Density Estimation in a Wolverine Population Using Spatial Capture-Recapture Models. Journal of Wildlife Management 75:604-611. Ruediger, B., J. Claar, S. Gniadek, B. Holt, L. Lyle, S. Mighton, B. Naney, G. Patton, T. Rinaldi, J. Trick, A. Vendehey, F. Wahl, N. Warren, D. Wenger, and A. Williamson. 2000. Canada lynx conservation assessment and strategy. 2nd edition. R1-00-53, U.S. Department of Agriculture, Forest Service, U.S. Department of Interior, Fish and Wildlife Service, Bureau of Land Management, National Park Service, Missoula, Montana, USA. Service, U. S. F. a. W. 2010. Endangered and threatened wildlife and plants: 12-month finding on a petition to list the North American wolverine as endangered or threatened. Federal Register. Shenk, T. M., and R. H. Kahn. 2010. The Colorado lynx reintroduction program. Colorado Division of Wildlife. Stroustrup, B. 1997. The C++ Programming Language. 3rd edition. Addison Wesley Longman, Reading, MA, USA. Team, R. D. C. 2011. R Foundation for Statistical Computing, Vienna, Austria. Theobald, D. M., and T. M. Shenk. 2011. Areas of high habitat use from 1999-2010 for radio-collared Canada lynx reintroduced to Colorado. Colorado State University. Ulizio, T. J., J. R. Squires, D. H. Pletscher, M. K. Schwartz, J. J. Claar, and L. F. Ruggiero. 2006. The efficacy of obtaining genetic-based identifications from putative wolverine snow tracks. Wildlife Society Bulletin 34:1326-1332. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Yee, T. W. 2010. The VGAM package for categorical data analysis. Journal of Statistical Software 32:134. _____. 2011. Zahratka, J. L., and T. M. Shenk. 2008. Population estimates of snowshoe hares in the southern Rocky Mountains. Journal of Wildlife Management 72:906-912. Zuur, A. F., E. N. Ieno, N. J. Walker, A. A. Saveliev, and G. M. Smith. 2009. Mixed Effects Models and Extensions in Ecology with R. Springer, New York, New York, USA. Prepared by ______________________________________ Jake S. Ivan, Wildlife Researcher 6 �Figure 1. Study area for simulation including montane regions of Idaho, western Montana, and northwest Wyoming. Black polygons indicate primary wolverine habitat defined as areas with snowcover between April 24 and May 15 during at least 1 year from 2000-2006. 7 �Figure 2. Example distribution of home range centers for male, female, and transient wolverines on the virtual landscape. Home range centers were required to fall within the spring snow layer, and intrasexual territorialty was enforced, except for transient individuals. The buffer around male home range centers was 12.5 km; female buffers were 8.5 km. 8 �Figure 3. Simulated utilization distributions (UDs) for each individual were created by positioning a bivariate normal UD directly over each home range center (see Figure 2) then multiplying by the underlying persistent snow layer to form a modified, more realistic UD unique to each individual. Figure 4. Example output from a single simulation: estimates of occupancy over a 10-year period fitted with a linear random effects model. If the 95% confidence interval on the slope of the linear trend did not include zero, then we concluded that a trend had been detected. The percentage of iterations in which trends were detected out of the total iterations provided a measure of power. 9 �Figure 5. Power to detect population declines of 50% (λ=0.933), 20% (λ=0.977), and 10% (λ=0.989) using occupancy estimation. Curves represent 2 levels of detection probability (0.2 and 0.8) and varying number of visits annually to a sampled unit (2, 3, 4, 5, 6, 7). Top 3 panels depict estimates of power when occupancy surveys occur annually; bottom 3 panels depict power when surveys are conducted biannually. Note that the lowest power to detect a 50% decline with annual sampling is apparently realized with 7 visits to each sampling unit. This result is counterintuitive, and likely due to a coding error. It will be addressed in future simulations. 10 �Colorado Division of Parks and Wildlife July 2010–June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Monitoring Canada Lynx in Colorado Using Occupancy Estimation: Initial Implementation in the Core Lynx Research Area Period Covered: July 1, 2010 – June 30, 2011 Author: J. S. Ivan Personnel: T. Shenk, G. Merrill, E. Newkirk All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 (Devineau et al. 2010). In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established. The purpose of this project was to develop a scientifically rigorous statewide plan to monitor this newly established population. Occupancy estimation, the use of presence/absence data to estimate the proportion of sample units used by a species within a study area, is appropriate for such a program. To evaluate this approach and provide initial estimates of occupancy and detection probability for planning purposes, we conducted a pilot occupancy estimation project in the core reintroduction area in the San Juan Mountains of southwestern Colorado. Lynx habitat in the study area was divided into 75−km2 sample units (8.66 km x 8.66 km cells), and we stratified the units into those accessible for snow tracking and “inaccessible” units which were sampled via remote cameras. We randomly sampled 30 units from each stratum. Sampling consisted of making multiple visits to each selected unit. We covered 2,178 km during our snow tracking effort (min= 1.4, max = 81.7 per visit) and detected lynx on 12 of the 30 sample units. Estimates of occupancy and detection probability from the top model were 0.62 and 0.37-0.43, respectively. Of the 120 cameras we deployed in late fall to survey the 30 inaccessible units, 113 were still operational when retrieved in early summer; 6 had memory cards that reached capacity in either May or June; 1 was stolen. We obtained 151,191 photos (min = 90, max = 6,948 per camera) from this effort. Work to assign species for each photo is ongoing. These pilot data will be used to conduct simulations and power analyses to determine how many sample units will be required to detect a statewide decline in Canada lynx, assuming that a decline in the actual population will be tied to a decline in the proportion of sample units used by lynx. 11 �WILDLIFE RESEARCH REPORT MONITORING CANADA LYNX IN COLORADO USING OCCUPANCY ESTIMATION: INITIAL IMPLEMENTATION IN THE CORE LYNX RESEARCH AREA JACOB S. IVAN P. N. OBJECTIVE Assess the use of occupancy estimation as a means of monitoring Canada lynx in Colorado using the Core Research Area in the San Juan Mountains as a test site. 1. Obtain initial estimates of occupancy and detection probability based on pilot work. 2. Conduct power analyses using initial estimates to determine the number of sample units, number of visits, and periodicity of sampling required to detect declines of interest in the statewide lynx population. 3. Develop a standardized, statistically rigorous monitoring protocol for estimating the distribution, stability and persistence of Canada lynx in Colorado. SEGMENT OBJECTIVES 1. 2. 3. 4. Assess and suggest modifications to survey protocols. Construct database to store and query survey information. Obtain initial estimates of occupancy and detection probability based on pilot work. Determine covariates and covariate structures that will be most useful for modeling occupancy and detection probability in the future. 5. Determine the efficacy of collecting lynx scat during occupancy surveys and whether such collections can be helpful in identification of putative lynx tracks and/or individuals. INTRODUCTION The Canada lynx (Lynx canadensis) occurs throughout the boreal forests of northern North America. While Canada and Alaska support healthy populations of the species, the lynx is currently listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.; U. S. Fish and Wildlife Service 2000) in the conterminous United States. Colorado represents the southern-most historical distribution of naturally occurring lynx, where the species occupied the higher elevation, montane forests in the state (U. S. Fish and Wildlife Service 2000). Lynx were extirpated or reduced to a few animals in Colorado, however, by the late 1970’s (U. S. Fish and Wildlife Service 2000), most likely due to multiple human-associated factors, including predator control efforts such as poisoning and trapping (Meaney 2002). Given the isolation of and distance from Colorado to the nearest northern populations of lynx, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) considered reintroduction as the best option to reestablish the species in the state. Therefore, a reintroduction effort was begun in 1997, and 218 lynx were released into Colorado from 1999 – 2006 (Devineau et al. 2010). The goal of the Colorado lynx reintroduction program was to establish a selfsustaining, viable population of lynx. Progress toward this goal was tracked via evaluation of critical criteria related to lynx survival, fidelity, and recruitment. Recently, CPW determined that the criteria had been met and a viable Canada lynx population currently exists in Colorado (Shenk and Kahn 2010). In order to track the distribution, stability, and persistence of this new lynx population, a minimally-invasive, long-term, statewide monitoring program is required. Abundance estimation is not 12 �feasible logistically and presents statistical difficulties even when field logistics can be managed. However, occupancy estimation, which uses detection/non-detection survey data to estimate the proportion of area occupied in a study area, is appropriate and feasible. In short, such a monitoring scheme requires multiple visits to a sample of survey units, and on each visit observers record whether a lynx was detected or not. Such information can be used to compute the probability of detecting a lynx given that it is present on a unit, which can in turn be used to estimate the proportion (ψ) of all survey units that are occupied. This metric can be tracked through time and is assumed to be closely tied to the size and extent of the lynx population. That is, if the proportion of survey units occupied by lynx declines through time, we assume this is due to a decline in the lynx population itself. Additionally, occupancy surveys can provide information relative to the distribution of lynx in the state. CPW initiated work to evaluate detection methods for occupancy estimation in 2009-2010 (Shenk 2009). Three methods of detecting lynx were tested in sample units where lynx were known to occur: snow tracking surveys, remote camera surveillance, and hair snags. The best method for detecting lynx was snow-tracking (daily detection probability = 0.70). Camera surveillance was far less efficient (daily detection probability = 0.085), and hair snares were ineffective (daily detection probability = 0.0; Ivan and Shenk 2010). Snow tracking, however, requires safe and extensive access to a survey unit via truck and/or snowmobile. Therefore, it cannot be used in roadless or wilderness areas, which may provide important lynx habitat. Here we build on this work to test occupancy estimation on a large scale using snow tracking where accessibility permitted it, and remote cameras in areas that were not accessible. METHODS Study Area The study area consisted of the 20,684 km2 “Lynx Core Research Area” in southwest Colorado. The Core Research Area is defined as areas >2591 m (>8500 ft) in elevation within the area bounded by New Mexico to the south, Taylor Mesa to the west, and Monarch Pass on the north and east (Figure 1). Topography in this area is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce (Picea engelmanii) − subalpine fir (Abies lasiocarpa) is the most widely distributed coniferous forest type at elevations most typically used by lynx (2591-3353 m, 8500-11,000 ft). Sampling The study area was divided into 75 km2 (8.66 km × 8.66 km) sample units, which reflects the mean annual home range size of reproducing lynx in Colorado (Shenk 2007) and Montana (Squires and Laurion 1999). Sample units that did not meet the following criteria were discarded as they did not represent potential lynx habitat that could be surveyed. ≥ 50 % of the cell contained conifer or montane/alpine habitat, as identified by the SWReGAP LandCover Dataset ( http://earth.gis.usu.edu/swgap/swregap_landcover_report.pdf) and 2. ≥ 50 % of the cell was located on public land (tribal, NGO and city and county lands are considered private) as determined by COMaP (Theobald, D.M., G. Wilcox, S.E. Linn, N. Peterson, and M. Lineal. 2008. Colorado Ownership, Management, and Protection v7 database. Human Dimensions of Natural Resources and Natural Resource Ecology Lab, Colorado State University, Fort Collins, CO, www.nrel.colostate.edu/projects/comap). 1. Each of the remaining sample units was assigned a random number resulting from a spatially balanced sampling scheme (RRQRR; Theobald et al. 2007) and units were stratified by accessibility for snow tracking or camera surveys. The cells with the lowest 30 random numbers for each stratum were 13 �selected for sampling during the pilot work. A few cells in both strata were discarded once field work began due to access issues and these were replaced with cells 31, 32, etc. Snow tracking Surveys Teams of 2 observers generally searched for lynx tracks within a sample unit using snowmobiles, although portions of some units were surveyed via truck or snowshoe. An effort was made to survey all portions of each unit as access allowed. Each of the 30 units selected for sampling was visited 3 times − roughly once per month from January through March. Occasionally a “visit” actually took place over consecutive days as some units could not be covered completely from a single access point. Once tracks were detected in a unit, that visit was considered complete and no further surveying occurred until the next visit. However, observers forward and back-tracked to find a scat sample. For each visit, observers recorded number of kilometers surveyed, tracking conditions (poor, fair, good, excellent), other species detected, location of lynx tracks, and time/distance to scat discovery. Camera Surveys Four remote camera sets (RECONYX RapidFireTM Professional PC85) were placed within each selected “inaccessible” sample unit during September and October. Placement of camera sets was not random within the unit; they were placed strategically on the landscape to maximize coverage of the sample unit and exploit microsites most likely to be used by lynx. Camera sets consisted of 1) a remote camera mounted to a tree using a Master Lock TM PythonTM cable lock, 2) a target tree at which the camera was pointed, generally about 5-10m away, 3) a compact disc strung from a nearby branch to visually attract lynx from a distance, 4) 2 feathers strung up in such a manner as to entice lynx to walk between the camera and the target tree, and 5) wool soaked in commercial scent lure that was packed into the bark of the target tree to hold lynx in front of the camera (Figure 2). Cameras were placed higher than usual, about head-height, and pointed slightly downward at the target tree so photos could be obtained during both snow-free periods and during periods of accumulating snow. Cameras were collected during June and July at which time the number of photos, percent of memory card used, percent battery life remaining, and condition of visual/scent lures was recorded. Analysis Assumptions inherent in occupancy estimation are 1) surveyed sites are either occupied or not occupied by the species of interest throughout the duration of the study; no sites change status during the survey period (i.e., the system is closed), 2) the probability of occupancy is constant across sites or can be modeled using covariates, 3) the probability of detection is constant across sites or can be modeled using site-specific covariates, and 4) species detection at a site is assumed to be independent of species detection at other sites (MacKenzie et al. 2006). Sampling mobile carnivores such as lynx presents a clear violation of the first assumption as individuals undoubtedly move into and out of sample units routinely. Fortunately, estimation can proceed, but the quantities estimated are different from traditional occupancy estimation. Rather than estimating the probability that a unit is occupied by lynx, we now estimate the probability that a sample unit is used by lynx. Also, the estimated detection parameter is not the probability of detection given a site is occupied, it is the product of a) the probability of detection given the species is available for detection, and b) the probability that the species was available. These subtleties aside, the procedure still gives a metric (use) that can be monitored through time to detect trends. We used the “Occupancy Estimation” data type in Program MARK to produce initial estimates of occupancy (i.e., use, ψ) and detection probability (p) for the snow tracking stratum. We hypothesized that some metric of the number of kilometers surveyed, or number that could be surveyed, would be important in explaining variation in detection probability as it should be an indicator of the amount of access to a unit. Surveys on units with more access should stand a better chance of detecting lynx if they are present. We further hypothesized that tracking conditions during a given visit should have an effect on detection 14 �probability. Finally, we did not expect differences among survey teams as both teams were experienced, but we wanted to test that assumption. Therefore, we considered 5 covariates that may explain variation in p: 1) total road length available for surveying in each sampled unit, 2) Kilometers surveyed during each visit, 3) maximum number of kilometers surveyed during any visit to a given unit, 4) tracking conditions during each visit, and 5) observer effect. We hypothesized that the proportion of spruce/fir cover in each unit may affect the probability of use, as might proportion of willow (Salix spp.), and subalpine/alpine meadow. Thus, we considered those 3 covariates as potentially important for explaining variability in ψ. As this analysis is exploratory, we held ψ constant and built an additive model for each detection covariate (one at a time) to determine the best structure for p. Similarly, we held p constant and fit additive models using the 3 covariates for ψ. We combined the best structure as determined by AICc (Burnham and Anderson 2002) for each parameter and used results from that single model to produce initial estimates of p and ψ. We also ran a model where both p and ψ were held constant as a baseline for comparison. Occupancy estimation for the camera stratum will proceed in a similar fashion as above, but data from the photos is incomplete at this time. Photos will be grouped by month (November to March) for each sample unit such that encounter histories will have 5 “visits” rather than 3. Due to this grouping, there are no meaningful covariates for p. Individual cameras recorded moon phase and temperature for each photo, but aggregated over a month, these data are not helpful. Some camera sets used different scent lures than others, but aggregating by unit negates the utility of this information as well. We will consider the same covariates on ψ as listed above. RESULTS On average, we covered 24.71 km per visit to each accessible sample unit (min = 1.40 km, max = 81.67 km) for a total of 2,184 km surveyed. We detected 20 lynx tracks in 12 of the 30 units sampled (i.e., tracks were detected on multiple visits to some units; Figure 1). We were able to collect scat from 13 of the 20 tracks, and mean forward/backtracking distance to scat discovery was 0.65 km (min = 0.05, max = 1.60). According to AICc, the best structures for p and ψ were “kilometers surveyed per visit” and “proportion spruce-fir,” respectively (Table 1). No other structure for either parameter resulted in improvement over constant p and ψ with the exception of modeling ψ as a function of “proportion willow.” In fact, this was the AICc top structure, but the parameters could not be estimated so it was dropped from the model set. Estimates (SE) from the model that combined the best structures were ψ = 0.62 (0.25), p1= 0.37 (0.10), p2= 0.37 (0.10), and p3 = 0.43 (0.10) where pi is the detection probability for visit I (i.e., p1 is the estimated detection probability for January, p2 = February, p3 = March) . As expected, the slope of the spruce-fir effect was highly positive. Probability of use was 0.5 when proportion spruce-fir approached 0.35, and probability of use went to 1.0 when proportion sprucefir approached 0.6 (Figure 3). The relationships between “proportion meadow” and ψ and “proportion willow” and ψ were also positive, but the relationships were weaker as confidence intervals for these slopes covered zero. The relationship between p and kilometers surveyed was negative. Similarly, the relationship between p and visit condition was opposite of our hypothesis (as visit conditions improved, detection probability declined). There was no relationship between “total road length” or “maximum kilometers surveyed” and detection probability. We did not detect differences between teams of observers. 15 �Genetic analysis of scat samples is ongoing. By December 2010, we should be able to assess whether scats were of high enough quality to confirm species and/or individual identification. Of the 120 cameras deployed during Fall 2010, 113 were still operational when retrieved in Summer 2011 after 234-309 days of deployment. Six had memory cards that reached capacity in either May or June, and one camera was stolen. On average, we obtained 1,260 photos per camera (min = 90, max = 6,948) for a total of 151,191 photos. At the time of retrieval, compact discs were still operational for 46% of camera sets, feathers were operational at 64% of sets, and remnants of scent lure were detected at 55% of sets. DISCUSSION Initial results indicate that occupancy (use) can be adequately modeled using data collected via snow tracking. Precision on estimates of ψ and p was relatively poor, but this can be addressed by sampling more units and/or making more visits. Modeling p as a function of the “kilometers surveyed per visit” was a better fit for the data than modeling it as a function of either “total road length within a unit” or “visit conditions.” However, we recommend continuing to record “total road length” and “visit conditions” in future surveys as it seems reasonable that these covariates should impact detection probability, and their effects may show through as sample size increases. Similarly, we recommend retaining all covariates on ψ to assess their performance with a larger dataset. The relationship between p and “kilometers surveyed per visit” was negative, which is likely an artifact of how the units were sampled – when lynx were detected, surveying stopped, so detection probability was higher for visits with few kilometers surveyed. The relationship between p and “visit condition” was opposite of our hypothesis (as visit conditions improved, detection probability declined). Our condition criteria were based largely on the freshness of the snow and degree of melting/crusting where fresh snow was assigned the best condition, and older, crusted snow was assigned the worst. Functionally, this index is an inverse of “time-since-snowfall.” Therefore, it is sensible that “poor” condition indices resulted in higher detection probabilities. While the immediate conditions were poor for tracking, significant time had passed in which lynx could move around and leave tracks to be discovered. We estimated that lynx used approximately 62% of the sample units available in the Core Research Area. However, for this pilot study, lynx habitat was coarsely defined as units with >50% spruce/fir and >50% public land. In several cases, sampled units met these criteria, but field crews that actually made visits indicated these units did not appear to include much lynx habitat. CPW is currently finishing an analysis to produce a map of predicted lynx habitat throughout the state. In the future, we expect to use this map to frame the population of units to sample for lynx monitoring. This more refined population of sample units should reduce time wasted surveying units that do not include good lynx habitat, and will result in an increased estimate of probability of use. Photos from cameras deployed to sample the inaccessible stratum have not been fully processed, therefore we cannot determine whether that portion of the study worked well enough to be included in any future monitoring effort. Roughly half of the visual attractants we used did not operate through the entirety of the study. These attractants are important for drawing lynx to the set from a distance and their failure diminishes the utility of the cameras for detecting lynx. If cameras are to be used in the future, design changes will be necessary to ensure that most of these visual attractants operate throughout the sampling season. 16 �ACKNOWLEDGMENTS We thank Britta Schielke, Cate Brown, Wendy Lanier, Joan Meiners, Shane McKenzie, Nick Burgmeier, Doug Clark, Bob Peterson, Tim Hanks, Kei Yasuda, Ashley Bies, Tyler Kelly, Alyssa Winkler, and Carolyn Shores for their efforts in the field. Dale Gomez and Rhandy Ghormley (USFS) graciously coordinated housing for seasonal crews. We thank various personnel from both the Rio Grande and San Juan National Forests for logistical help in the field. Funding was provided by a U.S. Fish and Wildlife Service Section 6 Grant. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model Selection and Multimodel Inference: A practical information-theoretic approach. Springer, New York, New York, USA. Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524-531. Ivan, J. S., and T. M. Shenk. 2010. Estimating the Extent, Stability and Potential Distribution of Canada Lynx (Lynx canadensis) in Colorado: initial implementation in the core lynx research area. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Elsevier Academic Press, Oxford, UK. McKelvey, K. S., J. von Kienast; K.B. Aubry; G. M. Koehler; B. T. Maletzke; J. R. Squires; E. L. Lindquist; S. Loch; M. K. Schwartz. 2006. DNA analysis of hair and scat collected along snow tracks to document the presence of Canada lynx. Wildlife Society Bulletin 34: 451-455. Meaney C. 2002. A review of Canada lynx (Lynx canadensis) abundance records from Colorado in the first quarter of the 20Th century. Colorado Department of Transportation Report. Shenk, T. M. 2005. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2009. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. Shenk, T.M., and R. H. Kahn. 2003. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2010. The Colorado lynx reintroduction program. Report to the Colorado Division of Wildlife, Fort Collins, Colorado. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337-349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. Theobald, D.M., D.L. Stevens, Jr., D. White, N.S. Urquhart, A.R. Olsen, and J.B. Norman. 2007. Using GIS to generate spatially balanced random survey designs for natural resource applications. Environmental Management 40(1): 134-146. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. Prepared by ______________________________________ Jake S. Ivan, Wildlife Researcher 17 �Table 1. Model selection results for estimating occupancy of sample units by Canada Lynx (Lynx canadensis) in the Core Research Area, San Juan Mountains, Colorado, Winter 2010-2011. Model AICc ΔAICc AICc Wt Num Par p(KmSurveyPerVisit)ψ(SprFir) 81.25 0.00 0.78 4 p(.)ψ(SprFir) 84.23 2.98 0.17 3 p(KmSurveyPerVisit)ψ(.) 88.60 7.35 0.02 3 p(.)ψ(.) 89.95 8.70 0.01 2 p(TtlRoadLen)ψ(.) 90.29 9.04 0.01 3 p(.)ψ(Meadow) 91.25 9.99 0.01 3 p(Observer)ψ(.) 92.10 10.85 0.00 3 p(MaxKmSurv)ψ(.) 92.42 11.17 0.00 3 p(VisitCond)ψ(.) 97.77 16.52 0.00 5 Figure 1. Canada lynx Core Research Area in southwest Colorado. Squares are 75km2 sample units available for occupancy surveys. Blue represents the sample of 30 “accessible” units selected for snow tracking surveys. Orange are “inaccessible” units selected for surveys using remote cameras. Crosshatching indicates accessible units where lynx were detected. The data from inaccessible units has not been fully processed and units where lynx were detected are not shown. 18 �Figure 2. General configuration of remote camera sets for detecting Canada lynx. Four such sets were deployed in each of 30 inaccessible sample units from Fall 2010 to Summer 2011. 19 �Figure 3. Estimated probability of use (ψ) and 95% confidence intervals plotted against proportion spruce/fir in a sample unit. Relationship is based on snow tracking occupancy surveys completed in southwest Colorado, Winter 2010-2011. 20 �Colorado Division of Parks and Wildlife July 2010–June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 0670 N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Predicted lynx habitat in Colorado N/A Period Covered: July 1, 2010 – June 30, 2011 Author: J. S. Ivan Personnel: M. Rice, P. Lukacs, T. Shenk (National Park Service), D. Theobald (Colorado State University), E. Odell All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 (Devineau et al. 2010). In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established (Shenk and Kahn 2010). The purpose of this project was to develop a statewide predictive map of relative lynx use based upon location data collected during the reintroduction period. To build the map, we divided the state into 1.5 km × 1.5 km cells and tallied the number of locations in each cell. We then fit models to these count data using vegetation, elevation, slope, wetness, and degree of human development in each cell as predictor variables. We produced models for both summer and winter habitat use. We found that regardless of season, lynx were positively associated with spruce/fir (Picea engelmannii/Abies lasiocarpa), mixed spruce/fir, aspen (Populus tremuloides), elevation and slope; they were negatively associated with distance to large forest patches. During summer, lynx use of lodgepole pine (Pinus contorta) stands was predicted to increase. Lynx were predicted to avoid montane forest (Douglas-fir [Pseudotsuga menziesii], Ponderosa pine [Pinus ponderosa]), and areas near high traffic volume road segments, especially during summer. These maps of predicted lynx use should aid land managers in prioritizing areas for conservation, development, and resource extraction with respect to potential impacts to lynx and lynx habitat. 21 �WILDLIFE RESEARCH REPORT PREDICTED LYNX HABITAT IN COLORADO JACOB S. IVAN P. N. OBJECTIVE Use location data collected during Canada lynx (Lynx canadensis) reintroduction to build a model of relative use, then apply this model statewide to produce a predictive map of relative lynx use for Colorado. SEGMENT OBJECTIVES 1. Compile and filter raw location data to isolate highest quality lynx locations. 2. Compile spatial data for use as covariates for the model (e.g. vegetation type, elevation, etc). 3. Build a series of candidate models to explain variation on locations across the landscape using covariate data layers. 4. Model-average predictions from all candidate models to produce a maps of predicted relative use for Colorado. INTRODUCTION In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 by the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW], Devineau et al. 2010). In 2010, CPW determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established (Shenk and Kahn 2010). Attainment of this goal is a conservation success, but it has also created a series of issues for land management agencies to consider as they plan changes to the landscape. These issues require knowledge of the types of landscapes and forest stands important for reproduction, movement, dispersal, and general home range use by lynx. As a first step toward providing this information, Theobald and Shenk (2011) conducted an analysis to describe the types of areas that were known to be used by re-introduced lynx. Specifically, they used LoCoH (Getz and Wilmers 2004, Getz et al. 2007) methods to create a population-level utilization distribution (UD, a probability surface of lynx occurrence) for lynx in Colorado. They then summarized landscape attributes within the 90% isopleth (i.e., polygon(s) containing 90% of the probability surface) of this UD. This work provides valuable information regarding the types of areas that were known to be used by lynx from 1999 to 2010. By nature of the data collection and research focus, most of this “use” information was derived from core areas in the San Juan Mountains of southwest Colorado and Sawatch Range in the central part of the state. The purpose of the current project is to extend the work of Theobald and Shenk (2011) by producing a map of predicted lynx use on a statewide scale. Such an exercise will identify areas within Colorado that should contain high quality lynx habitat, regardless of whether or not it was used by the sample of radio-telemetered individuals tracked during reintroduction research. Both works have strengths and weaknesses, but together they provide tools for prioritizing areas for conservation, development, and resource extraction with respect to potential impacts to lynx. 22 �METHODS Location Data Location data were collected from reintroduced lynx using 2 types of telemetry devices. All lynx released into Colorado, and those subsequently captured or re-captured, were fitted with a traditional VHF transmitter. VHF data were collected via telemetry from fixed-wing aircraft at approximately weekly intervals when research was ongoing during winter (approximately December – March) and reproductive seasons (May – June), but less often otherwise. Beginning in April 2000, released and captured lynx were outfitted with dual VHF-Argos satellite collars. In addition to sampling via fixed-wing aircraft, the satellite portion of these collars transmitted repeatedly for 12 hours, 1 day per week, year-round. Nearly 40,000 combined locations were collected between VHF and satellite sampling. These data were originally intended for assessing the success of the reintroduction and served CDOW well in estimating survival, productivity, and dispersal. They were not intended for use in constructing a predictive map of habitat use. We used only the best subset of these data following the filters applied by Theobald and Shenk (2011). Specifically, locations obtained during the first 6 months post-release were removed in order to exclude atypical movements made by animals that had not yet settled into home ranges. Next, poor precision satellite data (e.g., Argos location codes A, B, Z, 0 which do not have associated error estimates) were filtered out because they were too unreliable to be informative of lynx habitat use. We minimized dependence among locations (satellite collars transmitted several times per day, and a VHF location could have been obtained during the same day as well) by retaining only the most precise location for each lynx on a given day. When ties occurred, a single location was randomly selected from among the most precise locations. Finally, we discarded all data from lynx that were located fewer than 30 times over the course of the study. Predictor variables After filtering the location data, we assembled raw covariate data. We obtained housing density (HDENS, units per 1000 ha), road density (RDENS, km/km2 − all roads), slope (SLOPE), elevation (ELEV), topographic wetness (TW), distance to high-volume road segments (D10K, annual average daily traffic volume > 10,000 vehicles), and distance to mesic forest patches >50 ha (D50HA) from Theobald and Shenk (2011). We also downloaded vegetation data from the Colorado Vegetation Classification Project (CVCP, Colorado Division of Wildlife, U.S. Department of Interior Bureau of Land Management, U.S. Forest Service. http://ndis.nrel.colostate.edu/coveg/). CVCP is geographically limited to Colorado, but it accurately depicts many vegetation types that may be important to lynx including riparian zones and willow. Other vegetation data sources (i.e., LANDFIRE) have the advantage of a larger spatial extent, but classification of these non-forest vegetation types is not as detailed. We reclassified the 114 vegetation types in CVCP into 17 classes to simplify the number of covariates available for analysis (Appendix 1). Next, we divided the western portion of Colorado into 1.5 km × 1.5 km cells, which corresponds to 1 SD of the error distribution for the most imprecise (satellite) locations retained for analysis, as well as the smallest 90% UD observed for an individual lynx (Theobald and Shenk 2011). We computed the proportion of different vegetation types in each cell as well as mean SLOPE, ELEV, TW, HDENS, RDENS, D10K, and D50HA. We excluded cells with mean elevations <2,438m (8000 ft), assuming such cells do not provide habitat for lynx. This cutoff is consistent with previous literature (McKelvey et al. 2000, Ruediger et al. 2000), and over 99% of locations from our dataset were above 2,438m. We then standardized each covariate using all cells we intended to make predictions for. To maximize precision of parameter estimates and guard against erroneous predictions later on, we computed a correlation matrix between the potential explanatory variables but none were highly correlated (correlation coefficients were all <0.52 for covariates listed here). 23 �Analysis The response variable of interest for our models was the number of locations per individual in each cell, which we sought to predict using landscape attributes of the cells. We only used cells with ≥1 location for the purpose of constructing models. Excluding cells with no locations (zero counts) results in models that reflect relative use by lynx rather than resource selection. Thus in the generation of the model, we avoided delineation of what was available and suitable to lynx but never used (i.e., we avoided decisions regarding how many zero-count cells to include in the dataset and where they should come from on the landscape), which is a criticism of resource selection approaches. Furthermore, given ~10 years of work including weekly locations on hundreds of animals, we argue that nearly all cells in the Core Study Area that were suitable and available included ≥1 lynx location. This approach does, however, warrant the use of zero-truncated probability models to avoid possibly introducing bias in parameter estimates (Zuur et al. 2009, p. 269). In addition, we expected the data to be over-dispersed (variance of the counts was expected to be larger than the mean), we knew the number of locations collected per animal varied considerably, and we anticipated spatial autocorrelation in the residuals. To evaluate these assertions and determine the best model structure for our data, we successively compared the fits of a basic Poisson generalized linear model (GLM), negative binomial GLM, zero-truncated negative binomial (ZTNB), and ZTNB with an offset. We compared the fit of these alternate structures using Akaike’s Information Criterion (AIC, Burnham and Anderson 2002) and found that fitting a basic negative binomial GLM was an improvement over a Poisson (ΔAIC = 700.4), ZTNB was an improvement over the negative binomial (ΔAIC = 6463.0), and ZTNB with an offset provided the best fit (ΔAIC = 53.7). Thus, we used a ZTNB with an offset as the base model structure. We fit all models using the VGAM package (Yee 2010, 2011) in R (R Core Development Team 2011). To assess spatial autocorrelation we computed a variogram using the gstat package (Pebesma 2004) and standardized residuals from a highly parameterized model (including all covariates below; Figure 1). We found minimal autocorrelation, so we proceeded to build ZTNB models absent spatial structure in the error term. Within the general ZTNB model structure, we specified the candidate model set by including combinations of covariates for modeling the mean count for each cell as follows: 1) Lynx are associated with conifer forests and deep snow, and they rely heavily on snowshoe hares. In the Southern Rockies, lynx occur largely in conifer stands within the sub-alpine zone (Aubry et al. 2000). Therefore, we included proportion spruce/fir (SF, Picea engelmannii/Abies lasiocarpa,), mixed spruce/fir (MIXSF, spruce/fir mixed with Douglas-fir [Pseudotsuga menziesii], aspen [Populus tremuloides], and/or lodgepole pine [Pinus contorta], distance to forest patch >50ha (D50HA), ELEV, and SLOPE in every model. We expected positive associations with each of these covariates except D50HA, which we expected to be negative. 2) Research conducted during the reintroduction of lynx into Colorado focused primarily in the southern portion of the state. Lodgepole pine (LODGE) occurs only in the northern portion of the state, so we know relatively little regarding the importance of this vegetation type with respect to habitat use by lynx. Therefore, we included a LODGE effect in some models, but when LODGE entered as a covariate, we also included a LODGE × latitude (NORTH) interaction to attempt to account for the distribution of this forest type in Colorado. Thus, lodgepole pine was allowed to be an important predictor of lynx use (or not) depending on latitude. 3) Vegetation types other than spruce/fir occur in or adjacent to the subalpine zone. We know relatively little about how lynx use these types but they may be important intermittently and/or as travel corridors. Therefore, we also built models that included combinations of montane forest (MONFOR: Douglas-fir, Ponderosa pine [Pinus ponderosa], and mixed Doug-fir/ponderosa pine), aspen (ASPEN), willow (WILLOW), and montane shrub (MONSHB: Gambel oak 24 �[Quercus gambelii], serviceberry [Amelanchier utahensis], and snowberry [Symphoricarpos sp.]). 4) Though lynx are considered a high elevation species, we opted to exclude “alpine” in any model because lynx are forest-dwelling, and there are few opportunities to manage structure of alpine areas, which included both alpine tundra and rock/snow/ice. 5) Lynx are often considered reclusive. Thus, covariates representing human development might be important predictors of habitats used (or not used) by lynx, and we initially considered HDENS, RDENS, and D10K as potential covariates to include in the model set. However, initial modelfitting resulted in HDENS and RDENS having slightly positive effects on lynx locations (but confidence intervals on these slopes were largely centered on zero indicating the effect was negligible), which is probably an artifact of the trapping/collaring effort that often occurred near roads due to logistical considerations. Many cells outside of those used to construct the models had HDENS and RDENS scores that were orders of magnitude above those used to construct the models. Thus, when projected to the entire set of cells covering western Colorado, these models predicted the best lynx habitat in highly developed, urban areas with high road density. Given this implausible result, we excluded HDENS and RDENS from the analysis. We retained D10K because high volume road segments occurred throughout broad areas used by lynx (nearly every state highway has high volume segments) and it did not result in completely implausible results. We expected counts of lynx locations to be positively associated with distance to high traffic volume road segments. 6) TW was excluded from all models after initial model-fitting produced a result similar to HDENS and RDENS. TW was positively associated with lynx locations, which seems reasonable, but when projected to the expanse of western Colorado, the best lynx habitat was predicted in heavily irrigated agricultural areas, residential lawns, and lakes. These features had TW values that were orders of magnitude larger than any forest-dominated cell. Note that this phenomenon, predicting beyond the range of data used to build the model, can be risky, and it may have operated similarly on other variables but went undetected. 7) Lynx often make long-distance movements outside of the winter season, and these movements may include use of many types of vegetation. Therefore, we fit the model set to summer locations (April through October) and then to winter locations (November through March). Seasonal definitions were based on mean daily movement patterns of telemetered lynx (Theobald and Shenk unpublished data). We expected that the association between lynx locations and vegetation types other than SF and MIXSF would vary with season, with more use of these perceived secondary types during summer. In summary, our model set included all combinations of 5 vegetation types (LODGE, MONFOR, ASPEN, WILLOW, MONSHB) and D10K. Each combination was always paired with the base covariates (SF, MIXSF, ELEV, SLOPE, D50HA) listed in 1) above. This resulted in 26 = 64 models. We used Akaike’s Information Criterion (AIC, Burnham and Anderson 2002) to determine which model structures best explained variation in lynx locations, to assess the importance of each covariate, and to model-average predictions of lynx use for each cell across all models. Predictions were defined as the probability of observing at least 10 locations in a cell over a hypothetical 10-year sampling period, which corresponds to an average of 1 location per year over the time frame of the actual data generating process. We color-coded predictions into 10 quantiles for display such that each color represents 10% of the total (i.e., the darkest red represents the predicted best 10% of cells, dark red plus deep orange represent the predicted best 20% of cells, etc.) 25 �RESULTS The final winter dataset consisted of 3,915 locations from 68 individuals (min = 30 locations/lynx, max = 113, mean = 57.6). Winter cell counts ranged from 1 to 29 (mean = 2.3). Summer data consisted of 5,464 locations from 74 individuals (min = 30, max = 178, mean = 73.8). Summer cell counts ranged from 1 to 36 total lynx locations (mean = 2.8). Predicted Winter Use As expected, relative predicted use by lynx during winter months was negatively associated with D50HA and positively associated with SF, MIXSF, ELEV, and SLOPE (Table 1). Of these associations, SF was strongest (largest magnitude and 95% confidence interval [±2×SE] was well away from zero), followed by ELEV, MIXSF, and D50HA, respectively. The parameter estimate for SLOPE was small and its 95% CI substantially overlapped zero in all models. Thus it was not important in explaining variation in predicted habitat use. Of the covariates that were not included in every model, ASPEN was strongly, positively associated with use and was the only effect in this group that was clearly different from zero. MONSHB was negatively associated with predicted lynx use, but evidence for this effect was weak. WILLOW, MONFOR, and D10K were somewhat positively associated with lynx use, but evidence for these effects was relatively weak as well. LODGE and NORTH did not appear in any of the top models (cumulative AIC weights = 0.12). The winter predictive map reflects the strong effect of SF. Arbitrarily defining the top 20% of predictions as high quality lynx habitat, there are 1,869,975 ha of such habitat in Colorado. Most of this is predicted to occur in the southern part of the state in the San Juan, Culebra, and Wet Mountain Ranges (Figure 2). In the central portion of the state, high predicted use is expected in the northern Sawatch and West Elk Ranges, along with Grand Mesa. The Park Range and Flat Tops comprise the best predicted winter lynx habitat farther north (Figure 2). Predicted Summer Use Associations between relative predicted summer use and SF, MIXSF, ELEV, SLOPE, and D50HA were similar to those observed during winter (Table 2). However, the association with SLOPE was much stronger (larger effect and 95% CI indicated clear separation from zero) during summer, possibly due to den site selection and attendance during this time of year. The association with D50HA was slighter stronger as well. Of the covariates not included in every model, MONFOR and MONSHB were negatively associated with lynx locations; LODGE, NORTH, ASPEN, WILLOW, and D10K were positively associated. The effects of MONFOR, ASPEN, and D10K were substantially different from zero based on 95% CIs. Effects of other covariates were not clearly different from zero. The summer predictive map reflects more dispersed predicted use by lynx with LODGE, NORTH, and the LODGE × NORTH interaction playing a larger role (Figure 3). The central and southern Sawatch Range in central Colorado is predicted to have more use than during winter, whereas use on Grand Mesa is predicted to decline. In the northern part of the state, lynx use is predicted to shift more toward the Medicine Bow and Front Ranges. Using the same definition as before, we predict 1,791,675 ha of high quality summer habitat in Colorado. The overlap between high quality summer and winter cells (as arbitrarily defined above) is ~95%. DISCUSSION The data analyzed here were not collected for the purpose of constructing a predictive map and suffer from at least two shortcomings. First, the locations were not precise. We attempted to account for 26 �this imprecision by modeling at a 1.5 km scale, but matching covariates, response variables, and predictions at this scale reduces the clarity of relationships and weakens the modeling process. Second, the bulk of the reintroduction research effort, from which these data originated, was conducted in the southern and central portions of Colorado. Lodgepole pine only occurs in the northern 2/3 of the state, and is dominant there. Thus, predicting lynx habitat use in northern Colorado is difficult because the landscape is very different, yet we have little data available to help model lynx response to that landscape. That is, we are extrapolating beyond the range of covariates used to fit the models, which is tenuous. Caution should be exercised in interpreting results north of I-70. In addition to issues regarding the location data, we also lack important vegetation data that could be crucial in making accurate predictions. Snowshoe hares (Lepus americanus) are tied to forests with dense understory cover throughout their range (Hodges 2000a;b), including Colorado (Dolbeer and Clark 1975, Zahratka and Shenk 2008, Ivan 2011). Given the close tie between hares and lynx, habitat use of the latter should be strongly tied to understory cover as well. However, we have no covariate data for understory. Our models treat all spruce/fir, mixed spruce/fir, and lodgepole forests equally, but the quality of these forests likely varies considerably. Additionally, pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) epidemics throughout the state are drastically changing the structure and composition of current and future forests. Our predictions are based on forest composition prior to these outbreaks. Despite these weaknesses, the predictive maps constructed here also have a distinct strength in that they were constructed objectively from rigorous mathematical models based on empirical data collected from wild lynx. They are the first such maps for Colorado. Results from this effort confirm relationships that were already known (e.g., lynx are strongly associated with high elevation spruce/fir and mixed spruce/fir forests but avoid lower elevation montane forests and montane shrublands), and highlight others that may be of interest. For instance, we found clear evidence that lynx use was positively associated with ASPEN during both summer and winter. It is unclear what the ecological relationship between the two might be and we have no causal evidence for ASPEN driving lynx use. However, this pattern is not a simple artifact of ASPEN occurring near SF or MIXSF − our preliminary vetting of potential covariates indicated that the correlation between ASPEN and SF or MIXSF was small and negative (-0.15 and -0.14, respectively). We also found evidence that lynx use of lodgepole forests may increase during summer, and that they tend to avoid areas near high traffic volume road segments, especially in summer. The strengths of this analysis and resulting maps merit their inclusion as a tool for making land management decisions. However, inherent weaknesses of the data require the reader to exercise caution when interpreting results. These maps should be viewed as a compliment to expert opinion and existing maps produced by other means. When assessing habitat quality for lynx at a given project site, it is imperative that managers consider current stand characteristics (especially understory) in formulating land use plans or specific management recommendations relative to lynx. LITERATURE CITED Aubry, K. B., G. M. Koehler, and J. R. Squires. 2000. Ecology of Canada lynx in southern boreal forests. Pages 373-396 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. 27 �Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty, P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524-531. Dolbeer, R. A., and W. R. Clark. 1975. Population ecology of snowshoe hares in the central Rocky Mountains. Journal of Wildlife Management 39:535-549. Getz, W. M., S. Fortmann-Roe, P. C. Cross, A. J. Lyons, S. J. Ryan, and C. C. Wilmers. 2007. LoCoH: Nonparameteric Kernel Methods for Constructing Home Ranges and Utilization Distributions. Plos One 2. Getz, W. M., and C. C. Wilmers. 2004. A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography 27:489-505. Hodges, K. E. 2000a. The ecology of snowshoe hares in northern boreal forests. Pages 117-161 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. _____. 2000b. Ecology of snowshoe hares in southern boreal and montane forests. Pages 163-206 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. Ivan, J. S. 2011. Density, demography, and seasonal Movement of snowshoe hares in central Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. McKelvey, K. S., K. B. Aubry, and Y. K. Ortega. 2000. History and distribution of lynx in the contiguous United States. Pages 207-264 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S. McKelvey, andJ. R. Squires, editors. Ecology and conservation of lynx in the United States. University Press of Colorado, Boulder, Colorado, USA. Pebesma, E. J. 2004. Multivariable geostatistics in S: the gstat package. Computers & Geosciences 30:683-691. R Core Development Team. 2011. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3900051-07-0, URL http://www.R-project.org/. Ruediger, B., J. Claar, S. Gniadek, B. Holt, L. Lyle, S. Mighton, B. Naney, G. Patton, T. Rinaldi, J. Trick, A. Vendehey, F. Wahl, N. Warren, D. Wenger, and A. Williamson. 2000. Canada lynx conservation assessment and strategy. 2nd edition. R1-00-53, U.S. Department of Agriculture, Forest Service, U.S. Department of Interior, Fish and Wildlife Service, Bureau of Land Management, National Park Service, Missoula, Montana, USA. Shenk, T. M., and R. H. Kahn. 2010. The Colorado lynx reintroduction program. Colorado Division of Wildlife. Theobald, D. M., and T. M. Shenk. 2011. Areas of high habitat use from 1999-2010 for radio-collared Canada lynx reintroduced to Colorado. Colorado State University. Yee, T. W. 2010. The VGAM package for categorical data analysis. Journal of Statistical Software 32:134. _____. 2011. VGAM: Vector Generalized Linear and Additive Models. R package version 0.8-3. URL http://CRAN.R-project.org/package=VGAM. Zahratka, J. L., and T. M. Shenk. 2008. Population estimates of snowshoe hares in the southern Rocky Mountains. Journal of Wildlife Management 72:906-912. Zuur, A. F., E. N. Ieno, N. J. Walker, A. A. Saveliev, and G. M. Smith. 2009. Mixed Effects Models and Extensions in Ecology with R. Springer, New York, New York, USA. Prepared by ______________________________________ Jake S. Ivan, Wildlife Researcher 28 �D10K MONSHB WILLOW ASPEN MONFOR LODGE: NORTH NORTH LODGE SLOPE ELEV D50HA MIXSF SF Table 1. Model selection results (top 10 of 64) and parameter estimates (SE) for zero-truncated negative binomial models fit to cell counts of Canada lynx locations collected during winter (November – March) 1999-2010, southwest and central Colorado, USA. AIC ΔAIC AIC Wt. K 0.53 0.15 -1.1 0.24 0.07 (0.07) (0.08) (0.69) (0.11) (0.06) 0.28 0.06 (0.08) (0.04) 4672.1 0.0 0.15 9 0.48 0.13 -1.09 0.29 0.04 (0.06) (0.07) (0.69) (0.11) (0.05) 0.26 (0.08) 4672.9 0.8 0.10 8 0.52 0.14 -1.09 0.21 0.07 (0.07) (0.08) (0.69) (0.11) (0.06) 0.28 0.07 -0.33 (0.08) (0.04) (0.38) 4673.2 1.1 0.09 10 0.53 0.17 -1.12 0.25 0.07 (0.07) (0.08) (0.69) (0.11) (0.06) 0.27 0.06 (0.08) (0.04) 0.08 4673.2 (0.09) 1.1 0.09 10 0.48 0.15 -1.12 0.3 0.04 (0.06) (0.08) (0.69) (0.11) (0.05) 0.25 (0.08) 0.09 4673.8 (0.09) 1.7 0.06 9 0.54 0.16 -1.1 0.27 0.07 (0.07) (0.08) (0.69) (0.13) (0.06) 0.08 0.29 0.06 (0.22) (0.08) (0.04) 4673.9 1.9 0.06 10 0.47 0.12 -1.09 0.27 0.04 (0.07) (0.07) (0.69) (0.11) (0.05) 0.26 (0.08) 4674.1 2.1 0.05 9 0.52 0.16 -1.12 0.22 0.07 (0.07) (0.08) (0.69) (0.11) (0.06) 0.28 0.06 -0.32 0.08 4674.3 (0.08) (0.04) (0.38) (0.09) 2.2 0.05 11 4674.8 2.8 0.04 9 0.08 4675.0 (0.09) 3.0 0.03 11 0.49 0.14 -1.1 0.31 0.04 (0.07) (0.08) (0.69) (0.13) (0.05) 0.05 0.26 (0.22) (0.08) 0.54 0.18 -1.13 0.27 0.07 (0.08) (0.08) (0.69) (0.13) (0.06) 0.08 0.28 0.06 (0.22) (0.08) (0.04) 29 -0.29 (0.37) �-2.75 (0.7) 0.34 0.26 0.11 (0.13) (0.05) (0.11) 0.08 (0.1) 0.24 (0.12) AIC ΔAIC AIC Wt. K 0.2 (0.08) 6684.3 0.0 0.13 13 0.2 (0.08) -0.66 (0.5) 0.2 (0.08) 6684.4 0.1 0.13 14 0.39 0.11 -2.76 0.19 0.24 (0.06) (0.06) (0.67) (0.11) (0.05) -1.81 0.14 (0.39) (0.08) -0.87 (0.51) 0.15 (0.07) 6684.6 0.3 0.11 11 0.41 0.13 -2.77 0.23 0.25 (0.06) (0.06) (0.67) (0.11) (0.05) -1.82 0.13 (0.39) (0.08) 0.15 (0.07) 6685.9 1.6 0.06 10 0.34 0.07 -2.95 (0.05) (0.06) (0.67) -1.84 (0.39) -0.76 (0.49) 0.16 (0.07) 6686.0 1.7 0.06 10 -1.78 0.15 (0.39) (0.08) -0.85 (0.5) 6686.2 1.9 0.05 10 0.2 (0.08) 6686.3 2.0 0.05 14 -0.67 (0.5) 0.19 (0.08) 6686.3 2.0 0.05 15 0.39 0.11 -2.77 0.2 0.24 (0.06) (0.06) (0.67) (0.11) (0.05) -1.81 0.14 0 -0.86 (0.39) (0.08) (0.04) (0.51) 0.15 (0.07) 6686.6 2.3 0.04 12 0.36 0.09 -2.94 0.13 0.25 (0.05) (0.06) (0.67) (0.09) (0.05) -1.86 (0.38) 0.16 (0.07) 6686.8 2.4 0.04 9 0.09 (0.1) 0.25 (0.05) 0.4 0.08 -2.75 0.21 0.25 (0.06) (0.06) (0.67) (0.11) (0.05) -1.65 (0.4) D10K 0.45 0.11 (0.07) (0.07) MONSHB LODGE: NORTH 0.25 -1.65 0.2 (0.12) (0.39) (0.08) WILLOW NORTH 0.08 (0.1) ASPEN LODGE 0.38 0.27 0.13 (0.12) (0.05) (0.11) SLOPE -2.74 (0.7) ELEV D50HA 0.47 0.11 (0.07) (0.07) SF MIXSF MONFOR Table 2. Model selection results (top 10 of 64) and parameter estimates (SE) for zero-truncated negative binomial models fit to cell counts of Canada lynx locations collected during summer (April – October) 1999-2010, southwest and central Colorado, USA. 0.47 0.12 (0.07) (0.07) -2.74 (0.7) 0.37 0.27 0.13 (0.12) (0.05) (0.11) 0.08 (0.1) 0.25 -1.65 0.2 0.01 (0.12) (0.39) (0.08) (0.04) 0.46 0.11 (0.07) (0.07) -2.74 (0.7) 0.33 0.27 0.11 (0.13) (0.05) (0.11) 0.07 (0.1) 0.24 (0.12) -1.65 (0.4) 30 0.2 0.01 (0.08) (0.04) �Figure 1. Variogram contructured using standardizied residuals from a highly parameterized model fit to count data of lynx locations within 1.5km × 1.5km cells, 1999-2011, southwestern and central Colorado. Variance among pairs of points is similar regardless of the distance separating them, indicative of a lack of residual spatial autocorrelation after fitting important covariate effects. Strong evidence of spatial autocorrelation in residuals would result in a graph with small variance between pairs points that are near to each other, and larger variance at greater distances (i.e., a monotonically increasing pattern). 31 �Figure 2. Predicted winter habitat use by Canada lynx in western Colorado. Predictions are probabilities of observing at least 10 locations within a 1.5 × 1.5km cell over a hypothetical 10-year sampling period. Predictions were averaged across 64 models constructed using all combinations of covariates of interest. 32 �Figure 3. Predicted summer habitat use by Canada lynx in western Colorado. Predictions are probabilities of observing at least 10 locations within a 1.5 × 1.5km cell over a hypothetical 10-year sampling period. Predictions were averaged across 64 models constructed using all combinations of covariates of interest. 33 �Appendix I. Raster reclassification of CVCP dataset for use in lynx predictive map analysis. Lynx Reclass Null 2 2 2 1 1 1 1 4 4 8.2 4 4 4 4 4 14 4 4 4 8.2 8.2 8.2 8.2 8.2 8.2 8.1 8.1 8.2 8.2 8.2 8.2 8.2 4 8.2 4 4 4 4 8.2 10 10 8.1 8.2 8.1 8.1 3.1 8.2 10 10 10 CVCP Value 0 1 2 3 4 5 6 7 8 9 10 11 12 13 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 43 44 46 47 48 49 50 51 53 54 55 Description Unclassified Urban/Built Up Residential Commercial Agriculture Land Dryland Ag Irrigated Ag Orchard Rangeland Grass/Forb Rangeland Snakeweed/Shrub Mix Grass Dominated Forb Dominated Grass/Forb Mix Mid-grass Prairie Short-grass Prairie Sand Dune Complex Foothill and Mountain Grasses Disturbed Rangeland Sparse Grass (Blowouts) Shrub/Brush Rangeland Sagebrush Community Saltbush Community Greasewood Sagebrush/Gambel Oak Mix Snakeweed Snowberry Snowberry/Shrub Mix Bitterbrush Community Salt Desert Shrub Community Sagebrush/Greasewood Shrub/Grass/Forb Mix Sagebrush/Grass Mix Rabbitbrush/Grass Mix Sagebrush/Mesic Mtn Shrub Mix Grass/Misc. Cactus Mix Winterfat/Grass Mix Bitterbrush/Grass Mix Grass/Yucca Mix Sagebrush/Rabbitbrush Mix Pinon-Juniper Juniper Gambel Oak Xeric Mountain Shrub Mix Mesic Mountain Shrub Mix Serviceberry/Shrub Mix Upland Willow/Shrub Mix Manzanita PJ-Oak Mix PJ-Sagebrush Mix PJ-Mtn Shrub Mix 34 �Lynx Reclass 10 10 10 10 11 8.1 13 9.1 13 12 9.1 9.1 9.2 13 13 13 9.2 9.2 9.2 13 9.1 13 13 13 13 12 9.2 13 13 14 6 6 1 2 7 7 7 7 7 6 7 7 3.2 3.2 3.2 3.1 3.2 3.1 3.2 3.2 3.2 5 CVCP Value 56 57 58 59 62 63 65 66 67 68 69 70 71 72 73 75 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 96 97 98 99 100 101 102 103 104 105 106 108 109 110 111 112 113 114 Description Sparse PJ/Shrub/Rock Mix Sparse Juniper/Shrub/Rock Mix Juniper/Sagebrush Mix Juniper/Mtn Shrub Mix Aspen Aspen/Mesic Mountain Shrub Mix Ponderosa Pine Englemann Spruce/Fir Mix Douglas Fir Lodgepole Pine Sub-Alpine Fir Spruce/Fir Regeneration Spruce/Lodgepole Pine Mix Bristlecone Pine Ponderosa Pine/Douglas Fir Mix Limber Pine Lodgepole/Spruce/Fir Mix Fir/Lodgepole Pine Mix Douglas Fir/Englemann Spruce Mix Mixed Forest Land Spruce/Fir/Aspen Mix P. Pine/Gambel Oak Mix Ponderosa Pine/Aspen Mix Douglas Fir/Aspen Mix P. Pine/Aspen/Gamble Oak Mix Lodgepole Pine/Aspen Mix Spruce/Fir/Lodgepole/Aspen Mix Ponderosa Pine/Mesic Mtn. Shrub Ponderosa Pine/Aspen/Mesic Mtn. Barren Land Rock Talus Slopes & Rock Outcrops Soil Disturbed Soil Alpine Meadow Alpine Forb Dominated Alpine Grass Dominated Alpine Grass/Forb Mix SubAlpine Shrub Community Snow Subalpine Meadow Subalpine Grass/Forb Mix Riparian Forested Riparian Cottonwood Conifer Riparian Shrub Riparian Willow Exotic Riparian Shrubs Herbaceous Riparian Sedge Water 35 �36 �Colorado Division of Parks and Wildlife July 1, 2010 − June 30, 2011 PROGRAM FINAL REPORT DEER CONSERVATION RESEARCH FOR 5-YEAR FEDERAL AID GRANT W-185-R JULY 2006 – JUNE 2011 State of Colorado Cost Center 3430 Work Package 3001 Federal Aid Project W-185-R : Division of Parks and Wildlife : Mammals Research : Deer Conservation Research : Period Covered: July 1, 2006 – June 30, 2011 Authors: Chad J. Bishop, Charles R. Anderson, Jr., and Eric J. Bergman Principal Investigators: M. W. Alldredge, C. R. Anderson, E. J. Bergman, C. J. Bishop, D. J. Freddy, P. M. Lukacs, D. P. Walsh, and B. E. Watkins. Colorado Division of Wildlife; P. F. Doherty and G. C. White, Colorado State University ABSTRACT This report highlights the accomplishments of mule deer research and associated activities conducted by the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) with the funding support of Federal Aid Grant W-185-R during the 5-year grant segment, July 2006-June 2011. Two major multi-year research projects addressing mule deer population limiting factors and habitat enhancements were completed and reported upon during this segment. Two other major multi-year research projects were designed and implemented during this period. One project is comprehensively addressing approaches to mitigate the impacts of natural gas development on mule deer. The other project is evaluating survival rates and harvest management of adult male mule deer. Several other smaller research projects were designed and implemented, addressing mule deer-elk-cougar interactions and development of techniques for marking and monitoring mule deer. Additionally, funding provided scientific and technical expertise for mule deer population monitoring and analysis. Research experiments provided strong evidence that habitat nutritional quality had a greater impact on net productivity of mule deer than did existing levels of coyote, cougar, and black bear predation and that mechanical habitat treatments in senescent pinyon-juniper winter ranges were an effective strategy for increasing deer survival by increasing the amount of higher-quality forage. These research results provided wildlife managers support and direction for managing pinyon-juniper habitat across western Colorado. These research results also framed the experimental design for evaluating approaches to mitigate impacts of natural gas development on deer. Specifically, a large field experiment was initiated in northwest Colorado to evaluate effectiveness of habitat treatments in late-seral pinyon juniper and mountain shrub habitats that are experiencing high-intensity and low-intensity energy development. From activities supported by this Grant during this segment, principal investigators published 13 peer-reviewed scientific articles for prominent wildlife research journals, provided 21 annual CPW Wildlife Research Reports summarizing yearly progress of projects, provided 34 presentations at professional meetings or workshops, and initiated 2 graduate student projects. The cumulative impact of 37 �this programmatic effort provides Colorado the basis to progress and proactively sustain the mule deer resource in an increasingly complex landscape. The relative success of mule deer management in Colorado reflects the positive synergy between the terrestrial research and management sections in sharing expertise, financial resources, staffing, and common goals. 38 �PROGRAM FINAL REPORT DEER CONSERVATION RESEARCH FOR 5-YEAR FEDERAL AID GRANT W-185-R JULY 2006 – JUNE 2011 CHAD J. BISHOP, CHARLES R. ANDERSON, JR., AND ERIC J. BERGMAN PROGRAM NEED During the late 1990s, CPW was challenged by sportsmen and other stakeholders to investigate potential causes of declining numbers of mule deer in Colorado. The concerns of stakeholders gained the attention of the Colorado Legislature which directed CPW to prepare a document to address causes of the mule deer decline and outline a plan of action to reverse the perceived trend in mule deer populations. That document was prepared for the legislature in 1999 (Gill et al. 2001) and established the direction and objectives for mule deer management and research beginning in 1999. At the same time, the Colorado Wildlife Commission approved statewide limitations on hunting licenses for mule deer, which significantly reduced the number of deer harvested annually in Colorado. Several years later, a sudden and significant increase in natural gas development in the Piceance Basin of northwest Colorado prompted mule deer researchers and managers to initiate a comprehensive effort to mitigate development impacts on deer. The research projects conducted during this 5-year grant period directly or indirectly addressed these various management issues and concerns. This report highlights the accomplishments of research efforts conducted by CPW from July 1, 2006 through June 30, 2011 that were wholly or partially supported by Federal Aid Grant funds. PROGRAM NARRATIVE OBJECTIVES The primary Program Narrative research objectives were divided into two broad categories: 1) managing factors limiting mule deer populations, and 2) monitoring mule deer populations. The specific project objectives were: Managing Factors Limiting Mule Deer Populations Project 1 Objective. Evaluate the impacts of prescribed landscape habitat manipulations in senescent pinyon-juniper habitats on behavior and demographics (survival, reproduction, densities) of mule deer populations. Project 2 Objective. Evaluate approaches to mitigate the impacts of natural gas resource extraction and other related human-caused developments on mule deer habitats and population demographics. Project 3 Objective. Investigate behavioral and spatial relationships between mule deer and elk, and among mule deer, elk, and cougar as these species simultaneously utilize prescribed landscape habitat manipulations. Monitoring Mule Deer Populations Project 4 Objective. Evaluate the technical quality and applications of statewide mule deer research and management systems. Project 5 Objective. Evaluate new approaches to monitoring mule deer population demographics and habitat conditions. 39 �Project 6 Objective. Evaluate hunting systems that could maintain a balance between hunter opportunity and the quality of hunting experience. RESULTS Objective 1. Evaluate the impacts of prescribed landscape habitat manipulations in senescent pinyon-juniper habitats on behavior and demographics (survival, reproduction, densities) of mule deer populations. Project Objective 1 was formulated in response to field research conducted during the previous 5year grant cycle, which indicated that habitat quality was ultimately limiting mule deer population growth in western Colorado. Final data analyses and preparation of publications from this research was completed during 2006-2008, and therefore, are reported here as part of this project objective. We evaluated the effect of enhanced nutrition of deer during winter and spring on fecundity and survival rates of free-ranging mule deer on the Uncompahgre Plateau in southwest Colorado. The treatment represented an instantaneous increase in nutritional carrying capacity of a pinyon (Pinus edulis)−Utah juniper (Juniperus osteosperma) winter range and was intended to simulate optimum habitat quality. Prior studies on the Uncompahgre Plateau indicated predation and disease were the most common proximate causes of deer mortality. By manipulating nutrition and leaving natural predation unaltered, we determined whether habitat quality was ultimately a critical factor limiting the deer population. We measured annual survival and fecundity of adult females and survival of fawns, then estimated population rate of change as a function of enhanced nutrition. Our estimate of the population rate of change was 1.165 (SE = 0.036) for deer receiving the nutrition treatment and 1.033 (SE = 0.038) for control deer. We documented food limitation in the Uncompahgre deer population because survival of fawns and adult females increased considerably in response to enhanced nutrition. We found strong evidence that enhanced nutrition of deer reduced coyote (Canis latrans) and mountain lion (Puma concolor) predation rates of ≥6-month-old fawns and adult females. We concluded that winter-range habitat quality was a limiting factor of the Uncompahgre Plateau mule deer population. We, therefore, recommended evaluating habitat treatments for deer that were designed to set-back succession and increase productivity of late-seral pinyon-juniper habitats that presently dominate the winter range. Pinyon-juniper habitats across western Colorado have been exposed to minimal natural disturbance during recent decades. In particular, the natural role of fire in these systems has been significantly altered through aggressive efforts to extinguish fires ignited by lightning strikes. Fire suppression has become necessary because human dwellings are scattered across pinyon-juniper habitat throughout much of western Colorado. This has caused many mule deer winter ranges to become dominated by late-seral pinyon-juniper, which is unproductive for mule deer. Collaborative management efforts among state and federal agencies, NGOs, and private citizens have been initiated to incorporate disturbance into pinyon-juniper systems through the use of prescribed fire and mechanical treatments that remove or mulch pinyon and juniper trees. We evaluated the effectiveness of these types of habitat treatments on mule deer body condition, survival, and density. Peer-Reviewed Publications: Watkins, B. E., C. J. Bishop, E. J. Bergman, A. Bronson, B. Hale, B. F. Wakeling, L. H. Carpenter, and D. W. Lutz. 2007. Habitat guidelines for mule deer: Colorado Plateau shrubland and forest ecoregion. Mule Deer Working Group, Western Association of Fish and Wildlife Agencies. Schultheiss, P. C., H. Van Campen, T. R. Spraker, C. J. Bishop, L. L. Wolfe, and B. Podell. 2007. Malignant catarrhal fever associated with ovine herpesvirus-2 in free-ranging mule deer in Colorado. Journal of Wildlife Diseases 43:533−537. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085−1093. 40 �Bishop, C. J., B. E. Watkins, L. L. Wolfe, D. J. Freddy, and G. C. White. 2009. Evaluating mule deer body condition using serum thyroid hormone concentrations. Journal of Wildlife Management 73:462−467. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1−28. Annual Wildlife Research Reports: Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2007. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 59-71. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2007. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 73-96. Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2008. Effect of nutrition and habitat enhancements on mule deer recruitment and survival rates. Colorado Division of Wildlife, Wildlife Research Report July: 39-51. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2008. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 53-62. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 101-110. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2010. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 81-91. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2011. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Presentations at Professional Meetings/Workshops/Symposia: Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2006. Effect of enhanced nutrition of freeranging mule deer on population performance. The Wildlife Society 13th Annual Conference, September 23−27, Anchorage, Alaska, USA. Bishop, C. J., G. C. White, D. J. Freddy, and B. E. Watkins. 2007. Effect of enhanced nutrition of freeranging mule deer on population performance and effectiveness of vaginal implant transmitters. Colorado State University Student Chapter of The Wildlife Society, February 26, Fort Collins, Colorado, USA. Bishop, C. J. 2007. Capture techniques and radio-telemetry used in wildlife research and management, and an example of technique application using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, March 26−30, Fort Collins, CO, USA. Bishop, C. J., and E. J. Bergman. 2007. Status of big game habitats and implications for wildlife within the Colorado Plateau. Plant Community Restoration Workshop, September 5−7, Grand Junction, Colorado, USA. Bishop, C. J., G. C. White, and P. M. Lukacs. 2007. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. The Wildlife Society 14th Annual Conference, September 22−26, Tucson, Arizona, USA. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Colorado Chapter of The Wildlife Society Annual Meeting, January 23−25, Denver, Colorado, USA. 41 �Bishop, C. J. 2008. Capture techniques and radio-telemetry used in wildlife research and management, and an example of technique application using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, April 1, Fort Collins, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2008. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado Division of Wildlife Research Review, August 20-21, Denver, CO, USA. Bergman, E. J. 2009. Monitoring habitat for deer. Joint Meeting of Colorado’s Habitat Partnership Program and the Colorado Chapter of The Wildlife Society, February 5, Grand Junction, CO, USA. Bishop, C. J. 2009. Capture techniques and radio-telemetry used in wildlife research and management, ungulate ecology, and a case study using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, March 31, Fort Collins, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Colorado State University Student Chapter of The Wildlife Society, April, Fort Collins, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. 2009 Western States and Provinces Deer and Elk Workshop, May, Spokane, Washington, USA. Bishop, C. J. 2010. Capture techniques and radio-telemetry used in wildlife research and management, ungulate ecology, and a case study using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, March 30, Fort Collins, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2010. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Joint Meeting of Colorado’s Habitat Partnership Program and the Colorado Section of the Society of Range Management, December 1, Grand Junction, CO, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2011. Evaluation of winter range habitat treatments on overwinter survival of mule deer. Northwest Region Biology Days, January 19, Glenwood Springs, CO, USA. Bishop, C. J. 2011. Capture techniques and radio-telemetry used in wildlife research and management, ungulate ecology, and a case study using the Uncompahgre deer research study. Colorado State University’s Wildlife Management Short Course, March 29, Fort Collins, CO, USA. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2011. Effect of enhanced nutrition of free-ranging mule deer on population performance. 2011 Western States and Provinces Deer and Elk Workshop, May 17, Santa Ana Pueblo, New Mexico, USA. Bergman, E. J., C. J. Bishop, D. J. Freddy, G. C. White, and P. F. Doherty. 2011. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. 2011 Western States and Provinces Deer and Elk Workshop, May 17, Santa Ana Pueblo, New Mexico, USA. Objective 2. Evaluate approaches to mitigate the impacts of natural gas resource extraction and other related human-caused developments on mule deer habitats and population demographics. We designed and implemented a project to experimentally evaluate habitat treatments and human-activity management alternatives (i.e., best management practices; BMPs) that may benefit mule deer exposed to extensive energy development. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas within the state. This project was initiated in 2007 and is expected to go to 2016 at a minimum and ideally to 2019. The project timeline was recently extended by 1 year due to a delay in implementing habitat mitigation treatments. The Piceance Basin in northwest Colorado supports one of the largest migratory mule deer populations in North America and also exhibits one of the highest natural gas reserves in North America. 42 �Public stakeholders and CPW are concerned that the cumulative impacts of natural gas extraction will negatively affect mule deer and other wildlife resources in the region. Concern is particularly high for mule deer due to their recreational and economic importance as a principal game species and their ecological importance as one of the primary herbivores of the Colorado Plateau Ecoregion. Extraction of natural gas is directly affecting the potential suitability of the landscape for mule deer by converting native habitat vegetation to drill pads, roads, and noxious weeds, by fragmenting habitat because of drill pads and roads, by increasing noise levels via compressor stations and vehicle traffic, and by increasing the year-round presence of human activities. Extraction is indirectly affecting deer by increasing the human work-force population of the region and the subsequent need for developing additional landscape for human housing, supporting businesses, and upgraded road/transportation infrastructure. Additionally, increased traffic on rural roads is raising the potential for direct mortality from vehicle-animal collisions. Thus, research documenting these impacts and evaluating the most effective strategies for minimizing and mitigating these activities will greatly enhance future management efforts to sustain mule deer populations for future recreational and ecological values. Impacts of natural gas development may be most effectively mitigated for mule deer by restoring or enhancing habitat conditions on or adjacent to disturbed sites and by modifying development practices. However, we presently lack information to appropriately guide the expenditure of mitigation dollars to offset or lessen impacts. The purpose of this project is to address these mitigation questions so that dollars are spent wisely. For example, it remains unknown whether we can effectively mitigate impacts of natural gas development by treating habitat within a developing area. Results from this study will indicate whether mitigation dollars would be better spent enhancing/restoring habitat on-site or enhancing habitat in adjacent, undeveloped areas. Although not hypothesized, there is also the possibility that efforts to enhance habitat within heavily developed areas have a negative impact on deer and other species by causing further disturbance. Thus, this project will scientifically assess approaches for mitigating effects of natural gas development on mule deer to guide future management decisions. From December 2007 to present, we gathered baseline demographic and habitat utilization data from radio-collared deer across the Piceance Basin to allow assessment of mitigation approaches that are presently being implemented. We selected 5 winter range study areas representing varying levels of development to serve as treatment and control sites and recorded habitat use and movement patterns using GPS collars. We also estimated winter fawn survival and annual adult female survival, late winter body condition of adult females using ultrasonography, and deer abundance using helicopter mark-resight surveys. We started with 5 study sites to allow flexibility to respond to changing energy development plans, which can directly affect experimental design. In 2009, we refined our study design using our baseline deer data and current energy development plans of the major companies operating in Piceance Basin. We also eliminated a study site to reduce the annual project budget to the minimum necessary to meet the original research objectives. During December 2010-January 2011, we implemented 100 acres of habitat treatments as a pilot effort to evaluate logistics and effectiveness of habitat treatment strategies. We will implement an additional 1,100 acres of habitat treatments across two of our study sites as a mitigation strategy during 2011-13. ExxonMobil Corporation is directly funding all habitat treatments in this research as part of an agreed-upon mitigation plan with CPW. One study site receiving habitat treatments has undergone extensive energy development whereas the other site receiving treatments is experiencing modest development. We will continue to collect the various population and habitat use data across all study sites in order to evaluate the effectiveness of the habitat treatments. This approach will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation dollars toward less-impacted areas. We may also find that habitat mitigation efforts are not effective in developed areas at all, suggesting that habitat enhancement efforts may be only effective in areas that are not impacted by development. In 2010, we initiated a PhD project 43 �in collaboration with Colorado State University and ExxonMobil to evaluate deer behavioral responses to varying levels of development activity and habitat mitigation treatments. ExxonMobil is funding this project via a cooperative funding agreement with Colorado State University and CPW. This will allow us to assess the effectiveness of certain BMPs and habitat manipulations for reducing disturbance to deer. We also initiated a Masters project in collaboration with CSU and funded by ExxonMobil to evaluate vegetation responses to the habitat treatments described above. Danielle Johnston in the Avian Research Section is taking the lead on this project, working in collaboration with Chuck Anderson. Last, we plan to initiate a PhD project in collaboration with CSU during FY 11-12 to measure neonatal deer survival, also funded by ExxonMobil. Through combined funding from Federal Aid and energy companies, we are comprehensively evaluating effects of natural gas development on deer and associated mitigation strategies. Annual Wildlife Research Reports: Anderson, C. R., and D. J. Freddy. 2007. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Colorado Division of Wildlife, Wildlife Research Report July: 103-110. Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Stage I, Objective 5: patterns of mule deer distribution and movements. Colorado Division of Wildlife, Wildlife Research Report July: 63-86. Anderson, C. R. 2009. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Colorado Division of Wildlife, Wildlife Research Report July: 111-124. Anderson, C. R., and C. J. Bishop. 2010. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Colorado Division of Wildlife, Wildlife Research Report July: 47-62. Anderson, C. R., and C. J. Bishop. 2011. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Presentations at Professional Meetings/Workshops/Symposia: Anderson, C. R., and D. J. Freddy. 2008. Population performance of Piceance Basin mule deer in relation to natural gas development and mitigation measures to address habitat degradation and human activity management alternatives. Tri-state energy meeting addressing wildlife management in relation to energy development activities, Parachute, CO, USA. Anderson, C. R. 2008. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Energy Company Cooperators Meeting, October, Grand Junction, CO, USA. Anderson, C. R. 2009. Population performance of Piceance Basin mule deer in relation to natural gas development and mitigation measures to address habitat degradation and human activity management alternatives. Graduate-Faculty Seminar Series, Colorado State University, September 18, Fort Collins, CO, USA. Anderson, C. R. 2009. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Energy Company Cooperators Meeting, October, Grand Junction, CO, USA. Anderson, C. R. 2010. Population performance of Piceance Basin mule deer in relation to natural gas development and mitigation measures to address habitat degradation and human activity management alternatives. Faculty-Student Seminar, Western State College, Gunnison, CO, USA. 44 �Anderson, C. R., and C. J. Bishop. 2010. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Energy Company Cooperators Meeting, October, Grand Junction, CO, USA. Anderson, C. R. 2010. Piceance Basin mule deer and energy development: improving winter range habitat as mitigation. Joint Meeting of Colorado’s Habitat Partnership Program and Colorado Section of the Society for Range Management, December 1, Grand Junction, CO, USA. Anderson, C. R. 2011. Piceance Basin mule deer and energy development: improving winter range habitat as mitigation. Northwest Region Biology Training, January 19, Glenwood Springs, CO, USA. Anderson, C. R., and C. J. Bishop. 2011. Current understanding of mule deer-energy development interactions in the western United States. Northwest Region Biology Training, January 19, Glenwood Springs, CO, USA. Northrup, J., G. Wittemyer, and C. R. Anderson. 2011. Behavioral response of mule deer to energy development activities in the Piceance Basin, Colorado. Colorado Chapter of The Wildlife Society Annual Meeting, February 25, Fort Collins, CO, USA. Objective 3. Investigate behavioral and spatial relationships between mule deer and elk, and among mule deer, elk, and cougar as these species simultaneously utilize prescribed landscape habitat manipulations. We capitalized on an opportunity to simultaneously monitor spatial movements and predator-prey dynamics of radio-collared mule deer, elk, and cougars on the Uncompahgre Plateau. Mule deer were marked as part of ongoing research described above under Objective 1. Elk were marked as part of a pilot study to monitor spatial movements of deer and elk on the Uncompahgre Plateau, and cougars were marked with GPS collars as part of a long-term research study (not funded by Federal Aid) evaluating the effects of harvest on cougar populations and the assumptions used by CPW to manage cougar populations. Our primary goal was to improve understanding of cougar-prey dynamics. We investigated GPS location clusters for cougars and assessed if a predation event occurred and what species of prey was involved. Locations of predation events were assessed in relation to vegetation treatments applied to the landscape to benefit mule deer and elk. As predicted, cougar kill sites were associated with deer and elk distribution. The greatest density of kill sites occurred across mid-upper elevation deer winter range where overlap of wintering elk and deer was greatest. We investigated 462 clusters during this pilot study. Kill probability increased as cluster size increased. Kill probability exceeded 0.9 with ≥ 10 locations/cluster and approached 1 with ≥ 15 locations/cluster. The probability of a kill was high if a cougar spent >2 days in the same general area, and a kill was essentially certain if a cougar spent >3 days in the same general area. There was some probability of a kill at clusters that comprised only 1 location, indicating that isolated cougar locations may periodically be associated with kills and should not be ruled out when using GPS location data to address cougar prey utilization. Our estimates of kill probability are conservative because the estimates assume prey detection probability was 1, which is unlikely. Cougars killed adult deer, fawn deer, adult elk, and calf elk in roughly equal proportions. Each prey class comprised 0.22−0.24 of the total kill. Kill composition varied as a function of percent vegetative cover and elevation. In FY 09-10, for logistical and study design reasons, we transitioned all research on this objective to a non-Federal Aid cougar project along the Front Range of Colorado. Annual Wildlife Research Reports: Alldredge, M. W., E. J. Bergman, C. J. Bishop, K. A. Logan, and D. J. Freddy. 2008. Pilot evaluation of predator-prey dynamics on the Uncompahgre Plateau. Colorado Division of Wildlife, Wildlife Research Report July: 87-104. 45 �Objective 4. Evaluate the technical quality and applications of statewide mule deer research and management systems. Considerable progress has been made during recent decades in developing and implementing quality mule deer research and management programs within CPW by enlisting the biostatistical support of faculty at Colorado State University (CSU). This objective has been attained for many years via annual contract for professional services with individual faculty at CSU. Federal Aid grant funding has routinely been used to help fund this contract to support mule deer management and research. Other funds (non-Federal Aid) have also supported this contract, which permits biostatistical support of other research and management functions in CPW as well. During 2006-07, Gary White (CSU faculty) provided support to CPW biologists on designing and implementing harvest surveys, terrestrial inventory systems, and population modeling procedures. Ongoing support was also provided for CPW’s DEAMAN software package, which was used by staff for the storage, summary, and analysis of mule deer and other big game population and harvest data. In July 2007, CPW terminated the annual contract with faculty at CSU after hiring a permanent biometrician within CPW to provide these same services in-house. Peer-Reviewed Publications: McClintock, B. T., G. C. White, and K. P. Burnham. 2006. A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities. Journal of Agricultural, Biological, and Ecological Statistics 11:231-248. Martin, D. J., G. C. White, and F. M. Pusateri. 2007. Occupancy rates by swift foxes (Vulpes velox) in eastern Colorado. Southwestern Naturalist 52:541-551. White, G. C. 2008. Closed population estimation models and their extensions in Program MARK. Environmental and Ecological Statistics 15:89-99. Odell, E. A., F. M. Pusateri, and G. C. White. 2008. Estimation of occupied and unoccupied black-tailed prairie dog colony acreage in Colorado. Journal of Wildlife Management 72:1311-1317. Conn, P. B., D. R. Diefenbach, J. L. Laake, M. A. Ternent, and G. C. White. 2008. Bayesian analysis of wildlife age-at-harvest data. Biometrics 64:1170-1177. Annual Wildlife Research Reports: White, G. C. 2007. Multispecies investigations consulting services for mark-recapture analysis. Colorado Division of Wildlife, Wildlife Research Report July: 97-101. Objective 5. Evaluate new approaches to monitoring mule deer population demographics and habitat conditions. We conducted two separate research projects focused on the development and evaluation of new approaches to enhance monitoring of mule deer populations for research and management: 1) modification and evaluation of vaginal implant transmitters in deer, and 2) development of an automated collaring device for mule deer. Redesigned Vaginal Implant Transmitters Our understanding of factors that limit mule deer populations may be improved by evaluating neonatal survival as a function of dam characteristics under free-ranging conditions, which generally requires that both neonates and dams are radiocollared. The only viable technique facilitating capture of neonates from radiocollared adult females is use of vaginal implant transmitters (VITs). To date, VITs have allowed research opportunities that were not possible previously; however, VITs are often expelled from adult females prepartum, which limits their utility. During the previous 5-year Federal Aid Grant Segment, we evaluated effectiveness of VITs in mule deer. Based on this research, during the current grant segment, we redesigned an existing vaginal implant transmitter (VIT) manufactured by Advanced 46 �Telemetry Systems (ATS) by lengthening and widening wings used to retain the VIT in an adult female. Our objective was to increase VIT retention rates to increase likelihood of locating birth sites and newborn fawns. We placed the newly designed VITs in 59 adult female mule deer and evaluated the probability of retention to parturition and the probability of detecting newborn fawns. The probability of a VIT being retained until parturition was 0.766 (SE = 0.0605) and the probability of a VIT being retained to within 3 days of parturition was 0.894 (SE = 0.0441). In our earlier study using the original VIT wings, the probability of a VIT being retained until parturition was 0.447 (SE = 0.0468) and the probability of retention to within 3 days of parturition was 0.623 (SE = 0.0456). Thus, our design modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). Considering dams that retained VITs to within 3 days of parturition, the probability of detecting at least 1 neonate was 0.952 (SE = 0.0334) and the probability of detecting both fawns from twin litters was 0.588 (SE = 0.0827). Our study expands opportunities for conducting research that links adult female attributes to productivity and offspring survival in mule deer. Automated Collaring Device for Deer We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique significantly reduces stress that is typically associated with capture and handling and should eliminate capture-related mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fully-functional prototype of the device. We conducted an extensive field evaluation of the device with free-ranging mule deer during winter 2010-11. We successfully collared, weighed, and identified sex of 6 different mule deer fawns across 4 winter range locations along Colorado’s northern Front Range. Collars were purposefully made to shed from deer within several weeks or months of being captured. Two fawns were successfully re-collared after they shed the first collars they received. Thus, we observed 8 successful collaring events involving 6 different fawns. Most fawns demonstrated minimal response to collaring events, either remaining in the device or calmly exiting. Certain components of the collaring device failed to function optimally when temperatures dropped below approximately −15° C, while other components did not adequately withstand mule deer use under field conditions. Also, certain behaviors of mule deer when approaching and using the device created circumstances where it was possible to collar the same animal twice, which happened on one occasion. We identified a series of device modifications that would be necessary to address these various issues. We will modify the device accordingly and conduct a follow-up field evaluation during 2011-12. Peer-Reviewed Publications: Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bishop, C. J., C. R. Anderson, Jr., D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. 2011. Effectiveness of a redesigned vaginal implant transmitter in mule deer. Journal of Wildlife Management 75:1797−1806. Annual Wildlife Research Reports: Bishop, C. J., D. P. Walsh, M. W. Alldredge, E. J. Bergman, and C. R. Anderson. 2009. Development of an automated device for collaring and weighing mule deer fawns. Colorado Division of Wildlife, Wildlife Research Report July: 55-67. 47 �Bishop, C. J., C. R. Anderson, D. P. Walsh, P. Kuechle, J. Roth, and E. J. Bergman. 2009. Effectiveness of a redesigned vaginal implant transmitter in mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 69-99. Bishop, C. J., C. R. Anderson, D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. 2010. Effectiveness of a redesigned vaginal implant transmitter in mule deer. Colorado Division of Wildlife, Wildlife Research Report July: 63-80. Bishop, C. J., D. P. Walsh, M. W. Alldredge, E. J. Bergman, and C. R. Anderson. 2010. Development of an automated device for collaring and weighing mule deer fawns. Colorado Division of Wildlife, Wildlife Research Report July: 93-100. Bishop, C. J., C. R. Anderson, D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. 2011. Effectiveness of a redesigned vaginal implant transmitter in mule deer. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Bishop, C. J., M. W. Alldredge, D. P. Walsh, E. J. Bergman, and C. R. Anderson. 2011. Development of an automated device for collaring and weighing mule deer fawns. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Presentations at Professional Meetings/Workshops/Symposia: Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Colorado Chapter of The Wildlife Society Annual Meeting, January 17−19, Glenwood Springs, Colorado, USA. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. 7th Western States and Provinces Deer and Elk Workshop, May 13−16, Estes Park, Colorado, USA. Bishop, C. J., M. W. Alldredge, D. P. Walsh, E. J. Bergman, and D. Kilpatrick. 2011. Automated collaring device for mule deer. Colorado Chapter of The Wildlife Society Annual Meeting, February 25, Fort Collins, CO, USA. Objective 6. Evaluate hunting systems that could maintain a balance between hunter opportunity and the quality of hunting experience. Historically, management of big game species has focused on the performance of the female and young of the year components of the population. In the case of mule deer, this has been further refined to the aspects of annual (for adult females) and overwinter (for young of the year) survival. The performance of the male component of populations was deemed less important, primarily due to the fact that it takes relatively few males to provide adequate breeding potential for the population. Additionally, harvest management objectives were to provide maximal hunting opportunity for hunters. Thus, as long as there were adequate numbers of males to breed females there was no need to restrict hunting opportunity. However, during the past 10-15 years, the management of big game populations, and mule deer populations in particular, has started to shift away from the objective of providing maximal opportunity towards providing fewer but higher quality opportunities. High quality opportunities are typically defined by hunters as a combination of the opportunity to see a greater number of male deer during the hunt, the potential to harvest an older age class animal (i.e., an animal with more developed antler morphometry), but also reduced interaction and competition with other hunters. In response to this shift in hunter desires and concerns over declining mule deer numbers, in 1999 CPW implemented a statewide limitation in deer hunting. This statewide limitation gave the CPW the ability to greatly reduce total hunter numbers but also the ability to control the distribution of hunters throughout the state. Since 1999, a few marked changes in Colorado’s deer herd have occurred. First, due to reduced harvest an overall increase in deer numbers has been observed. Second, because the reduction in harvest was primarily focused on adult males, a subsequent increase in the ratio of adult males to adult females has occurred. Stemming from this shift in harvest management and the subsequent changes in herd size and structure, a gap in biological information has been identified. Specifically, Colorado’s deer herds have 48 �become composed of a greater number of males, yet little biological data on them exist. Also stemming from the change in harvest management was a new responsibility for Colorado’s terrestrial biologists and wildlife managers. Prior to 1999, licenses were sold over-the-counter and were not limited in number (i.e., any hunter who wished to purchase one was able to do so). The decision of how many licenses to make available did not need to be considered. Since 1999, the CPW has the added responsibility of deciding how many licenses should be allocated in each Data Analysis Unit (DAU). This decision must further reflect a balance between meeting DAU population performance objectives, but also provide as much hunter opportunity as possible. Big game populations in Colorado are currently modeled using multiple sources of biological data (White and Lubow 2002). Model inputs include harvest, young recruitment to December, and measured rates of survival of adult females and fawns. Also, the ratio of adult males to adult females is estimated and used to align models by minimizing the difference between observed and modeled values. Very rarely have the survival rates of adult males been measured. This gap in knowledge has historically been viewed as trivial and rates have been assumed to not be different from the rates of females. Similarly, it has been assumed that natural survival rates (i.e., post hunt survival) of males do not geographically vary. However, model performance under these assumptions has been poor and the need to measure adult male survival as a parameter has increased. Presently, a number of population models in Colorado suggest that natural adult male survival may be lower than adult female survival, yet empirical data is lacking to verify these suppositions. A different, but not unrelated need in Colorado pertains to the harvest management of adult male mule deer. As discussed above, a large shift in mule deer herd size and structure occurred as a result of the change in harvest management that occurred between 1998 and 1999. Overall, this shift has been viewed as positive by both the CPW as well as the public. However, the CPW still maintains the responsibility of optimally managing the deer of Colorado and providing the maximal amount of hunting opportunity under this new set of constraints. To date, the CPW has had limited biological information and data to guide harvest management decisions. In particular for this issue, as DAUs reach and surpass their adult male: adult female ratio objectives, the CPW typically responds by increasing the number of available hunting licenses. In situations where herds are continually lower than DAU objectives, available hunting licenses are reduced. What remains unknown about survival of adult male deer is at what level natural survival is reduced due to intraspecific competition. If, or when deer herds exceed the adult male: adult female objectives for DAUs, it is often assumed that the surplus of male deer will remain in the population into perpetuity. However, this assumption is based on the premise that compensatory mortality does not occur. Similarly, it assumes that annual variation in survival is negligible. However, this is biologically not realistic. It is very likely that herds with large post-hunt populations of adult males experience higher levels of mortality. Under this scenario, harvest has not been optimized and more hunters could have been afforded the opportunity to hunt with no effect on post hunting season ratios of adult males to adult females. The simplest way to learn about the mortality process is via manipulative experimentation. Our study objective is two-fold. First, we wish to assess annual survival of adult male mule deer. We wish to establish baseline survival estimates, and related estimates of variance, for different age classes of deer. Second, we wish to manipulate hunting license allocation within the Game Management Units (GMUs) of a single DAU such that adult male: adult female ratios become measurably different between two halves of the DAU. Accordingly, we wish to measure and correlate changes in natural survival of adult male deer with this management action. Similarly, as part of this second objective, we will determine if changes in the age structure of harvested animals occur as the sex ratio and age structure of the hunted population changes. We designed the study and wrote a study plan during 2009-10 and initiated field work during 2010-11. 49 �Peer-Reviewed Publications: Bergman, E. J., B. E. Watkins, C. J. Bishop, P. M. Lukacs, and M. Lloyd. 2011. Biological and socioeconomic effects of statewide limitation of deer licenses in Colorado. Journal of Wildlife Management 75:1443−1452. Annual Wildlife Research Reports: Bergman, E. J., C. J. Bishop, K. Oldham, and L. Sidener. 2011. Assessment of survival and optimal harvest strategies of adult male mule deer in Middle Park, Colorado. Colorado Division of Parks and Wildlife, Wildlife Research Report July: in press. Presentations at Professional Meetings/Workshops/Symposia: Bergman, E. J., B. E. Watkins, C. J. Bishop, P. M. Lukacs, and M. Lloyd. 2007. Biological, social, and economic effects of totally limited deer licenses in Colorado. 7th Western States and Provinces Deer and Elk Workshop, May 13−16, Estes Park, Colorado, USA. Bergman, E. J., B. E. Watkins, C. J. Bishop, P. M. Lukacs, and M. Lloyd. 2008. Biological, social, and economic effects of totally limited deer licenses in Colorado. Colorado Chapter of The Wildlife Society Annual Meeting, January 25, Denver, Colorado, USA. Bergman, E. J., C. J. Bishop, L. Sidener, and K. Oldham. 2011. Survival and optimal harvest management of mule deer bucks in Middle Park, CO. Presentation to the Colorado Wildlife Commission, April 7, Meeker, CO, USA. SUMMARY We conducted work on seven research projects addressing mule deer limiting factors, habitat enhancement, mitigation of natural gas development impacts, predator-prey dynamics, buck harvest management, and technique developments. Additionally, funding provided biostatistical support for implementing or maintaining statewide deer harvest surveys, population databases, aerial surveys, population modeling, and research projects. From activities supported by this Grant during this segment, principal investigators published 13 peer-reviewed scientific articles for prominent wildlife research journals, provided 21 annual CPW Wildlife Research Reports summarizing yearly progress of projects, provided 34 presentations at professional meetings, workshops, or symposia, and initiated 2 graduate student projects. The cumulative impact of this programmatic effort provides Colorado the basis to progress and proactively sustain the mule deer resource in an increasingly complex landscape. The relative success of mule deer management in Colorado reflects the positive synergy between the terrestrial research and management sections in sharing expertise, financial resources, staffing, and common goals. LITERATURE CITED Gill, R.B., T.D.I Beck, C.J. Bishop, D.J. Freddy, N.T. Hobbs, R.H. Kahn, M.W. Miller, T.M. Pojar, and G.C. White. 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report 77. Fort Collins, Colorado, USA. White, G.C. and B.C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. Prepared by ______________________________________ Chad J. Bishop, Mammals Research Leader 50 �Colorado Division of Parks and Wildlife July 1, 2010 − June 30, 2011 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 6 Federal Aid Project: W-185-R : Division of Parks and Wildlife : Mammals Research : Deer Conservation : Population Performance of Piceance Basin Mule Deer in Response to Natural Gas Resource Extraction and Mitigation Efforts to Address Human Activity and Habitat Degradation : Period Covered: July 1, 2010 − June 30, 2011 Authors: C. R. Anderson and C. J. Bishop Personnel: E. Bergman, J. Broderick, P. Damm, B. deVergie, D. Finley, L. Gepfert, M. Grode, C. Harty, K. Kaal, T. Knowles, J. Lewis, P. Lukacs, T. Parks, B. Petch, M. Peterson, R. Velarde, L. Wolfe, CPW; E. Hollowed, L. Belmonte, BLM; S. Monsen, Western Ecological Consulting, Inc.; D. Freddy, Hoch Berg Enterprises; T. Graham, Ranch Advisory Partners; M. Wille, T & M Contractors.; H. Sawyer, Western Ecosystems Technology; P. Lendrum, T Bowyer, Idaho State University; P. Doherty, J. Northrup, G. Wittemyer, K. Wilson, G. White, Colorado State University; M. Keech, L. Shelton, M. Shelton, R. Swisher, Quicksilver Air, Inc.; D. Felix, Olathe Spray Service, Inc.; L. Coulter, Coulter Aviation. Project support received from Federal Aid in Wildlife Restoration, Colorado Mule Deer Association, Colorado Mule Deer Foundation, Colorado State Severance Tax Fund, EnCana Corp., ExxonMobil Production Co., Marathon Oil Corp., Shell Petroleum, and Williams Production LMT Co. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the authors. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas within the state. The data presented here represent the first 3 pretreatment years of a long-term study addressing habitat modifications and improved energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. We monitored 4 winter range study areas representing varying levels of development to serve as treatment (Ryan Gulch, North Magnolia, South Magnolia) and control (North Ridge) sites and recorded habitat use and movement patterns using GPS collars (5 location attempts/day), estimated overwinter fawn and annual adult female survival, estimated early and late winter body condition of adult females using ultrasonography, and estimated abundance using helicopter mark-resight surveys. We targeted 250 fawns (50—80/study area) and 100 does (20—40/study area) in early December 2010 for VHF and GPS radiocollar attachment, 51 �respectively, and 80 does in March 2011(20/study area) for late winter body condition assessment and to increase our GPS radiocollar sample in 3 of the 4 areas (10 of 20/area excluding Ryan Gulch). Based on the data collected since January 2008, deer from all areas appear to be in reasonably good condition and exhibited high survival rates the first 2 years, with lower winter fawn survival through mid-June this past winter in 3 of 4 study areas (excluding North Ridge), and winter range deer densities appear to be stable or increasing. Mild winter conditions the first 2 years followed by more severe winter conditions this year likely contributed to the observed survival rates and population trends. Observed differences in winter concentration areas thus far may indicate behavioral modifications to areas of high development activity, but resource selection analyses will be necessary to confirm this supposition. Pilot habitat treatments (126 acres total) were completed January 2011 and moist spring weather conditions have resulted in excellent vegetation response thus far. We will continue to collect the various population and habitat use data across all study sites to evaluate the effectiveness of additional habitat treatments (North and South Magnolia) scheduled for fall/winter 2012—2013 (1,200 acres total). This evaluation will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation dollars toward less or non-impacted areas. In collaboration with Colorado State University, we are also evaluating deer behavioral responses to varying levels of development activity in the Ryan Gulch study area. This will allow us to assess the effectiveness of certain Best Management Practices (BMPs) for reducing disturbance to deer. The study is slated to run through at least 2017, and preferably 2019, to adequately measure mule deer population responses to landscape level manipulations. 52 �WILDLIFE RESEARCH REPORT POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION CHARLES R. ANDERSON, JR and CHAD J. BISHOP PROJECT NARRITIVE OBJECTIVES 1. To determine experimentally whether enhancing mule deer habitat conditions on winter range elicits behavioral responses, improves body condition, increases overwinter fawn survival, or ultimately, population density on mule deer winter ranges exposed to extensive energy development. 2. To determine experimentally to what extent modification of energy development practices enhance habitat selection, body condition, over-winter fawn survival, and winter range mule deer densities. SEGMENT OBJECTIVES 1. Collect and reattach GPS collars to maintain sample sizes for addressing mule deer habitat use and behavior patterns in 4 study areas experiencing varying levels of energy development of the Piceance Basin, northwest Colorado. 2. Estimate early and late winter body condition of adult female mule deer in each of the 4 winter herd segments 3. Monitor over-winter fawn and annual adult female mule deer survival by daily ground tracking and biweekly aerial tracking. 4. Conduct Mark-Resight helicopter surveys to estimate mule deer abundance in each study area. 5. Initiate habitat treatments for assessing efficacy of habitat improvement projects to mitigate energy development disturbances to mule deer. INTRODUCTION Extraction of natural gas from areas throughout western Colorado has raised concerns among many public stakeholders and Colorado Parks and Wildlife that the cumulative impacts associated with this intense industrialization will dramatically and negatively affect the wildlife resources of the region. Concern is especially high for mule deer due to their recreational and economic importance as a principal game species and their ecological importance as one of the primary herbivores of the Colorado Plateau Ecoregion. Extraction of natural gas will directly affect the potential suitability of the landscape used by mule deer through conversion of native habitat vegetation with drill pads, roads, or noxious weeds, by fragmenting habitat because of drill pads and roads, by increasing noise levels via compressor stations and vehicle traffic, and by increasing the year-round presence of human activities. Extraction will indirectly affect deer by increasing the human work-force population of the region resulting in the need for additional landscape for human housing, supporting businesses, and upgraded road/transportation infrastructure. Additionally, increased traffic on rural roads will raise the potential for vehicle-animal collisions and additive direct mortality to mule deer populations. Thus, research documenting these impacts and evaluating the most effective strategies for minimizing and mitigating these activities will 53 �greatly enhance future management efforts to sustain mule deer populations for future recreational and ecological values. The Piceance Basin in northwest Colorado contains one of the largest migratory mule deer populations in North America and also exhibits some of the largest natural gas reserves in North America. Projected energy development throughout northwest Colorado within the next 20 years is expected to reach about 15,000 wells, many of which will occur in the Piceance Basin, which currently supports over 250 active gas well pads (http://cogcc.state.co.us). Anderson and Freddy (2008a) in their long-term research proposal identified 6 primary study objectives to assess measures to offset impacts of energy extraction on mule deer population performance. During the past 4 years, we have gathered baseline habitat utilization data from GPS-collared deer across the Piceance Basin to allow assessment of mitigation approaches that will be implemented over the next 1-2 years and evaluated for another 4-6 years. We are currently monitoring 1 control area without development (North Ridge), 2 areas with relatively high development activity (0.6—0.8 well pads & facilities/km2; Ryan Gulch, South Magnolia), and another area with relatively minor development activity (0.1 well pads & facilities/km2; North Magnolia). In comparison to the un-manipulated control area (North Ridge), the North and South Magnolia areas will receive similar levels of mechanical habitat treatments to evaluate this mitigation technique in relation to differing development intensities, and deer behavior patterns relative to differing development activities in the Ryan Gulch area will be monitored to identify effective Best Management Practices (BMPs) for future application. This progress report describes the previous 3.5 years (Jan 2008—June 2011) of addressing mule deer population performance during the pretreatment phase on 4 winter range herd segments, which includes monitoring habitat selection and behavior patterns of adult female mule deer, overwinter fawn and adult female survival, estimates of adult female body condition during early and late winter, and abundance estimates. STUDY AREAS The Piceance Basin, located between the cities of Rangely, Meeker, and Rifle in northwest Colorado, was selected as the project area due to its ecological importance as one of the largest migratory mule deer populations in North America and because it exhibits one of the highest natural gas reserves in North America (Fig. 1). Historically, mule deer numbers on winter range were estimated between 20,000-30,000 (White and Lubow 2002), and the current number of well pads (Fig.1) and projected number of gas wells in the Piceance Basin over the next 20 years is about 250 and 15,000, respectively. Mule deer winter range in the Piceance Basin is predominantly characterized as a topographically diverse pinion pine (Pinus edulis)-Utah juniper (Juniperus osteosperma; pinion-juniper) shrubland complex ranging from 1,675 m to 2,285 m in elevation (Bartmann and Steinert 1981). Pinion-juniper are the dominant overstory species and major shrub species include Utah serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), big sagebrush (Artemisia tridentata), Gamble’s oak (Quercus gambelii), mountain snowberry (Symphoricarpos oreophilus), and rabbitbrush (Chrysothamnus spp.; Bartmann et al. 1992). The Piceance Basin is segmented by numerous drainages characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainages having been converted to mixedgrass hay fields. Grasses and forbs common to the area consist of wheatgrass (Agropyron spp.), blue grama (Bouteloua gracilis), needle and thread (Stipa comata), Indian rice grass (Oryzopsis hymenoides), arrowleaf balsamroot (Balsamorhiza sagittata), broom snakeweed (Gutierrezia sarothreae), pinnate tansymustard (Descurainia pinnata), milkvetch (Astragalus spp.), Lewis flax (Linum lewisii), evening primrose (Oenothera spp.), skyrocket gilia (Gilia aggregata), buckwheat (Erigonum spp.), Indian paintbrush (Castilleja spp.), and penstemon (Penstemon spp.; Gibbs 1978). The climate of the Piceance Basin is characterized by warm dry summers and cold winters with most of the annual moisture resulting from spring snow melt. 54 �Wintering mule deer population segments we investigated in the Piceance Basin include: North Ridge (53 km2) just north of the Dry Fork of Piceance Creek including the White River in the northeastern portion of the Basin, Ryan Gulch (141 km2) between Ryan Gulch and Dry Gulch in the southwestern portion of the Basin, North Magnolia (79 km2) between the Dry Fork of Piceance Creek and Lee Gulch in the north-central portion of the Basin, and South Magnolia (83 km2) between Lee Gulch and Piceance Creek in the south-central portion of the Basin (Fig. 1). Each of these wintering population segments has received varying levels of natural gas development: no development in North Ridge, light development in North Magnolia (0.14 pads & facilities/km2), and relatively high development in the Ryan Gulch (0.60 pads & facilities/km2) and South Magnolia (0.86 pads & facilities/km2) segments (Fig. 1). Among the 4 study areas, North Ridge will serve as an unmanipulated control site, Ryan Gulch will serve to address human-activity management alternatives (BMPs) that benefit mule deer exposed to energy development, and North and South Magnolia will serve to address the utility of habitat treatments intended to enhance mule deer population performance in areas exposed to light (North Magnolia) and heavy (South Magnolia) energy development activities. METHODS Tasks addressed this period included mule deer capture and collaring efforts, monitoring overwinter fawn and annual adult female survival, estimating adult female body condition during early and late winter using ultrasonography, estimating mule deer abundance applying helicopter mark-resight surveys, and initiating winter range habitat treatments to benefit mule deer in areas experiencing disturbance from energy development activities. We employed helicopter net-gunning techniques (Barrett et al. 1982, van Reenen 1982) to capture 50—80 fawns and 20—40 adult females during early December 2010 and 20 adult females during early March 2011 in each of the 4 study areas. Once netted, all deer were hobbled and blind folded. Fawns were weighed, radio-collared and released on site, and adult females were transported to localized handling sites for collection of body measurements and were fitted with GPS collars (20—40/area during December 2010, 0—10/area during March 2011; 5 or 24 fixes/day; G2110B, Advanced Telemetry Systems, Isanti, MN, USA) and released. To provide direct measures of decline in overwinter body condition, 20 does were recaptured in Ryan Gulch and 10 from the other 3 study areas that were captured the previous December; 10 uncollared does were also captured in North Ridge, North Magnolia, and South Magnolia to increase sample sizes in those areas. Fawn collars were spliced and fitted with rubber surgical tubing to facilitate collar drop during mid-summer— early autumn and GPS collars were supplied with timed drop-off mechanisms scheduled to release early April of the year following deployment. All radio-collars were equipped with mortality sensing options (i.e., increased pulse rate following 4—8 hrs of inactivity). Mule Deer Habitat Use and Movements We downloaded and summarized data from GPS collars deployed March 2010 following collar drop and retrieval in early April 2011. GPS collars deployed early December 2010 maintained the same fix schedule of attempting fixes every 5 hours except in Ryan Gulch where fix rates were increased to 1/hour to increase resolution of GPS data for evaluation of deer behavior patterns in relation to differing development activities. We plotted deer locations and recorded timing and distance of spring and fall 2010 migrations for each study area. Mule deer winter concentration areas were created using composite GPS data (winter locations March 2010—April 2011 from all deer; 5 location attempts/day) from each study area and mapped in ArcGIS (ver. 9.3) using Spatial Analyst (kernel probability density functions separated by quantiles). Mule deer resource selection analyses are pending completion of high resolution habitat data layers currently being developed by BLM. 55 �Mule Deer Survival Mule deer mortality monitoring consisted of daily ground telemetry tracking and aerial monitoring approximately every 2 weeks from fixed-wing aircraft on winter range and bi-weekly aerial monitoring on summer range. Once a mortality signal was detected, deer were located and necropsied to assess cause of death. We estimated weekly survival using the staggered entry Kaplan-Meier procedure (Kaplan and Meier 1958, Pollock et al. 1989). Capture-related mortalities (any mortalities occurring within 10 days of capture) and collar failures were censored from survival rate estimates. We estimated survival rates 1 July 2010—30 June 2011 for adult females and early December 2010—mid June 2011 for fawns. Adult Female Body Measurements We applied ultrasonography techniques described by Stephenson et al. (1998, 2002) and Cook et al. (2001) to measure maximum subcutaneous rump fat (mm), loin depth (longissimus dorsi muscle, mm), and to estimate % body fat. We estimated a body condition score (BCS) for each deer by palpating the rump (Cook et al. 2001, 2007). We examined differences (P < 0.05) in nutritional status among study areas and between years using a two-sample t-test. We considered differences in body condition meaningful when mean rump fat or % body fat differed statistically between comparisons. Other body measurements recorded included pregnancy status (pregnant, barren) via blood samples, weight (kg), chest girth (cm), and hind-foot length (cm). Abundance Estimates We conducted 4 (North Ridge) or 5 (the remaining study areas) helicopter mark-resight surveys (2 observers and the pilot) during late March, 2011 to estimate deer abundance in each of the 4 study areas. We delineated each study area from GPS locations collected during winter from previous years (since Jan 2008) and aerial telemetry locations of radio-collared deer within 1 week of the first markresight survey. Two aerial fixed-wing telemetry surveys/study area were conducted during helicopter mark-resight surveys to determine which marked deer were within each survey area. We delineated flight paths in ArcGIS 9.3 prior to surveys following topographic contours (e.g., drainages, ridges) and approximating 500 m spacing throughout each study area; flight paths during surveys were followed using GPS navigation in the helicopter. Two approximately 12 x 12 cm pieces of Ritchey livestock banding material (Ritchey Livestock ID, Brighton, CO USA) were uniquely marked using color, number, and symbol combinations and attached to each radio-collar to enhance mark-resight estimates. Each deer observed during surveys was recorded as mark ID#, unmarked, or unidentified mark. We used program MARK (White and Burnham 1999) applying the mixed logit-normal model (McClintock et al. 2008) to estimate mule deer abundance and confidence intervals. For mark-resight model evaluations, we examined parameter combinations of varying detection rates with survey occasion and whether individual sighting probabilities (i.e., individual heterogeneity) were constant or varied (σ2 = 0 or ≠ 0). Model selection procedures followed the information-theoretic approach of Burnham and Anderson (2002). RESULTS AND DISCUSSION Deer Captures and Survival The helicopter crew captured 264 fawns and 107 does in December 2010 and 81 does during March 2011. Nine fawn mortalities (ultimate cause = 6 capture myopathy and 3 predation) occurred 56 �within the 10 day myopathy period following the December capture and 1 doe mortality each followed the December and March captures (ultimate cause = 1capture myopathy and 1 predation). Fawn survival from early-December 2010—mid June 2011 was similar (P > 0.05) among 3 of 4 study areas ranging from 0.48 to 0.51, with North Ridge fawns exhibiting marginally higher over-winter survival (0.70; P < 0.10, Table 1). In comparison to previous years, North Ridge fawn survival has been consistent since winter 2008/09, but survival in the other 3 areas was lower than last year and lower than the previous 2 years in Ryan Gulch (Fig. 2). Annual adult female survival was similar among study areas (P > 0.05) ranging from 0.77 (North Ridge) to 0.89 (Ryan Gulch; Table 1) and was comparable to previous years (P > 0.05; Anderson 2009, Anderson and Bishop 2010). The relatively lower fawn survival observed this winter (3 of 4 study areas) was likely due to increased winter severity present through mid February, and doe survival was consistent with other mule deer populations experiencing normal winter conditions in the western US (Unsworth et al. 1999). Seasonal Movement Patterns Migration patterns differed among areas with North Ridge and North Magnolia deer generally migrating east-west and South Magnolia and Ryan Gulch deer migrating south-north (Fig. 3). Median straight-line migration distances were similar ranging from 32.6 km (Ryan Gulch) to 41.3 km (North Magnolia). Similar to seasonal ranges, most deer monitored exhibited strong fidelity to spring and fall migration routes (Fig. 3). Timing of spring migration during 2010 was similar among study areas with median spring migration dates occurring between 8 and 16 May and median fall migration dates occurring between 15 and 23 October. Median migration duration was relatively short among areas ranging from 3 to 8 days in the spring and 2 to 6 days in the fall; these observations were comparable to previous years. More detailed analyses of these migration data investigating the influence of human activity are currently being conducted by Patrick Lendrum and Terry Bowyer of Idaho State University. A final report is scheduled to be completed by spring 2012. Winter concentration areas identified from March 2010—April 2011 (Fig. 4) reasonably followed study area boundaries delineated from previous GPS locations of adult female mule deer (Anderson and Bishop 2010). Winter concentration areas outside study area boundaries primarily resulted from atypical distribution shifts of some North Ridge deer. Within study areas, we noted more continuous distributions from North Magnolia and North Ridge deer, with Ryan Gulch and South Magnolia deer exhibiting more fragmented and concentrated distributions, which may be related to relative development densities and longevity within each study area. Future resource selection analyses will address these differences relative to habitat attributes within each area. Mule Deer Body Condition Body condition measurements of adult female mule deer December 2010 were comparable to last year (Anderson and Bishop 2010) with higher values evident from North and South Magnolia deer, intermediate from Ryan Gulch deer, and lower values from North Ridge deer (Table 2), but differences were only marginal (P < 0.01) between North Ridge and the 2 Magnolia populations (mm rump fat: P = 0.05—0.07). Unlike last year, deer coming into winter range with higher body condition did not maintain improved condition by late winter and all herd segments were similarly low when assessed in March 2011. The similarly low body condition among areas we observed during late winter can likely be attributed to increased winter severity this winter relative to last winter. Overwinter decline in mean % body fat ranged from 3.8% in Ryan Gulch to 4.7% in South Magnolia (Table 2). Pregnancy rates were expectedly high ranging from 95% to 100%/study area (n = 20/area). 57 �Similar to subtle trends in adult female body condition the past 3 years (Table 2), December fawn weights were slightly higher in 2009 than during 2008 and 2010 (Fig. 5). In 2009, male fawns from North and South Magnolia were heavier (P < 0.05) than during 2008 as were Ryan Gulch males when compared to 2010. Similarly, 2009 females were heavier from North Magnolia compared to 2008 and from North Magnolia and Ryan Gulch than during 2010 (Fig. 5). In comparing fawn weights from December 2010, Ryan Gulch fawns were marginally (P = 0.055; South Magnolia females) or significantly lighter (P < 0.05; both sexes from the other 3 study areas and males from South Magnolia) than other fawns. Mule Deer Population Estimates Mark-resight models that best predicted abundance estimates (lowest AICc; Burnham and Anderson 2002) exhibited homogenous individual sightability (σ2 = 0) and constant sightability across surveys (P.) for South Magnolia and Ryan Gulch, homogenous individual sightability and variable sightability with survey period for North Ridge, and heterogeneous individual sightability with variable sightability across surveys for North Magnolia. North Ridge exhibited the highest deer density (22.9/km2), followed by North Magnolia (11.2/km2), with comparably lower deer densities in South Magnolia and Ryan Gulch (7.6 and 8.7/km2; Table 3, Fig. 6). Abundance estimates were similar (P > 0.05) to last year except in North Magnolia where deer numbers increased from 595 to 884. Over the 3 year survey period so far the population trend in North Ridge appears to be increasing with a recent increase in North Magnolia and stability in the other 2 areas (Fig. 6). Abundance estimates from 2011 were similarly precise from all 4 study areas with the mean Confidence Interval Coefficient of Variation (CICV) ranging from 0.14—0.18. SUMMARY AND FUTURE PLANS The goal of this study is to investigate habitat treatments and energy development practices that enhance mule deer populations exposed to extensive energy development activity. The information presented here provide data describing mule deer population parameters from the first 3.5 years of the pre-treatment period of a long-term study intended to address how mule deer react to landscape scale habitat and human activity modifications. The pretreatment period is intended to continue 1 to 2 more winters to provide baseline data to compare against intended improvements in habitat conditions and evaluation of concentration/reduction in human development activities, which will be maintained for 4— 6 years to provide sufficient time to measure how deer respond to these changes. Based on the data collected thus far, deer from all areas appear to be in reasonably good condition and are exhibiting expected survival rates relative to changes in winter severity. Mild winter conditions the first 2 years and more severe winter conditions during the current year likely contributed to the observed mule deer population parameters. Observed differences in winter concentration areas (Fig. 4) may indicate behavioral modifications to areas of prolonged high development activity, but resource selection analyses will be necessary to confirm this supposition. We will continue to collect the various population and habitat use data across all study sites to evaluate the effectiveness of habitat improvements on winter range. This approach will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation dollars toward less or non-impacted areas. In a recent project conducted on the Uncomphahgre Plateau, Bergman et al. (2009) found that habitat treatments implemented in pinyon-juniper habitat in undeveloped areas were effective for deer. We are also evaluating deer behavioral responses to varying levels of development activity. This will allow us to assess the effectiveness of certain BMPs for reducing disturbance to wintering mule deer. We recently implemented a habitat improvement plan and completed our pilot habitat treatments January 2011 (126 acres total) and plan to complete the remaining treatments (~1,080 acres) in the 58 �Magnolia study areas by fall/winter 2012—2013; vegetation response thus far in the pilot treatment sites have been promising, likely due to the moist spring conditions this year. In addition, hay field improvements have been implemented in the North Magnolia area from a collaborative agreement with Williams Production LMT Co. Additional collaboration with Williams Production LMT Co. have produced a clustered development plan to be implemented in the Ryan Gulch study area and new technologies will be implemented to reduce human activity through remote monitoring of well pads and fluid collection systems. Recent collaboration agreements with ExxonMobil Development Co. and Colorado State University have provided graduate research opportunities to enhance data collection and inference about mule deer/energy development interactions. We are continuing to work with Dr. Terry Bowyer and Patrick Lendrum (MS candidate) of Idaho State University to address mule deer migration and potential influences of human activity along migration routes. Additional funding and cooperative agreements will be necessary to sustain this project through completion (through at least 2017 and preferably through 2019). We optimistically anticipate the opportunity to work cooperatively toward developing solutions for allowing the nation’s energy reserves to be developed in a manner that benefits wildlife and the people who value both the wildlife and energy resources of Colorado. LITERATURE CITED Anderson, C. R., Jr. 2009. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and D. J. Freddy. 2008a. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Final Study Plan, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and D. J. Freddy. 2008b. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation—Stage I, Objective 5: Patterns of mule deer distribution & movements. Pilot Study, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and C. J. Bishop. 2010. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, CO, USA. Bartmann, R. M. 1975. Piceance deer study—population density and structure. Job Progress Report, Colorado Divison of Wildlife, Fort Collins, Colorado, USA. Bartmann, R. B., and S. F. Steinert. 1981. Distribution and movements of mule deer in the White River Drainage, Colorado. Special Report No. 51, Colorado Division of Wildlife, Fort Collins, Colorado, USA. Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monograph No. 121. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, USA. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multi-model inference: a practical information-theoretic approach. Second edition. Springer-Verlag, New York, New York, USA. Cook, R. C., J. G. Cook, D. L. Murray, P. Zager, B. K. Johnson, and M. W. Gratson. 2001. Development of predictive models of nutritional condition for rocky mountain elk. Journal of Wildlife Management 65:973-987. Cook, R. C., T. R. Stephenson, W. L. Meyers, J. G. Cook, and L. A. Shipley. 2007. Validating predictive models of nutritional condition for mule deer. Journal of Wildlife Management 71:1934-1943. 59 �Gibbs, H. D. 1978. Nutritional quality of mule deer foods, Piceance Basin, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 52:457-481. McClintock, B. T., G. C. White, K. P. Burnham, and M. A. Pride. 2008. A generalized mixed effects model of abundance for mark—resight data when sampling is without replacement. Pages 271289 in D. L. Thompson, E. G. Cooch, and M. J. Conroy, editors, Modeling demographic processes is marked populations. Springer, New York, New York, USA. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. C. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. Stephenson, T. R., K. J. Hundertmark, C. C. Swartz, and V. Van Ballenberghe. 1998. Predicting body fat and mass in moose with untrasonography. Canadian Journal of Zoology 76:717-722. Unsworth, J. W., D. F. Pack, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked individuals. Bird Study 46:120-139. White, C. C., and B. C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. Prepared by ______________________________________ Chuck R. Anderson, Wildlife Researcher 60 �Table 1. Survival rate estimates (Ŝ) of fawn (1 Dec. 2010—18 June 2011) and adult female (1 July 2010—30 June 2011) mule deer from 4 winter range study areas of the Piceance Basin in northwest Colorado. Cohort Study area Initial sample size (n) Ŝ (95% CI) March doe samplea (n) Fawns Ryan Gulch 50 0.480 (0.342—0.618) South Magnolia 55 0.508 (0.375—0.640) North Magnolia 60 0.481 (0.351—0.610) North Ridge 77 0.697 (0.594—0.080) Adult females Ryan Gulch 31 51 0.892 (0.800—0.983) South Magnolia 28 53 0.832 (0.708—0.955) North Magnolia 32 54 0.783 (0.654—0.912) North Ridge 33 44 0.765 (0.622—0.908) a Adult female sample size following capture and radio-collaring efforts March, 2011. 61 �Table 2. Mean rump fat (mm), Body Condition Score (BCSa), and % body fat (% fat) of adult female mule deer from 4 study areas in the Piceance Basin of northwest Colorado, March and December, 2009—2011. Values in parentheses = SD. March 2009 December 2009 BCS % fat Rump fat BCS March 2010 Study Area Rump fat % fat Ryan Gulch 1.73 (1.78) 2.66 (0.55) 7.54 (1.80) 8.35 (6.36) 4.06 (1.13) 12.96 (4.53) 2.31 (1.44) 2.35 (0.48) 6.69 (1.58) South Magnolia 1.47 (0.68) 2.50 (0.60) 7.26 (1.82) 10.05 (6.19) 4.07 (1.21) 13.46 (4.96) 3.12 (2.20) 2.64 (0.59) 7.70 (2.01) North Magnolia 1.30 (0.79) 2.56 (0.68) 6.96 (2.23) 10.67 (5.76) 4.25 (0.96) 13.92 (3.92) 3.15 (2.34) 2.85 (0.53) 8.28 (1.86) North Ridge 1.57 (1.22) 2.60 (0.56) 7.28 (1.66) 5.25 (5.65) 3.63 (1.11) 11.02 (4.54) 1.77 (1.11) 2.42 (0.49) 6.83 (1.50) Table 2. Continued. December 2010 BCS March 2011 Study Area Rump fat % fat Rump fat BCS % fat Ryan Gulch 7.75 (6.15) 3.34 (0.98) 10.82 (4.32) 1.55 (0.60) 2.53 (0.42) 7.05 (1.20) South Magnolia 9.85 (6.78) 3.30 (0.61) 11.21 (3.32) 1.65 (0.75) 2.35 (0.50) 6.56 (1.49) North Magnolia 9.55 (6.49) 2.56 (0.68) 11.65 (4.86) 1.65 (0.67) 2.53 (0.49) 7.06 (1.35) North Ridge 6.14 (5.29) 3.32 (0.82) 10.32 (3.39) 1.45 (0.76) 2.24 (0.49) 6.24 (1.45) a Body condition score taken from palpations of the rump following Cook et al. (2001). 62 Rump fat BCS % fat �Table 3. Mark-resight abundance (N) and density estimates of mule deer from 4 winter range herd segments in the Piceance Basin, northwest Colorado, 29 March—4 April 2011. Data represent 4 resight surveys from North Ridge and 5 resight surveys from the other 3 study areas. Study area Mean No. sighted Mean No. marked N (95% CI) Density (deer/km2) Ryan Gulch 327 22 1,219 (1,040—1,431) 8.7 South Magnolia 156 21 630 (542—735) 7.6 North Magnolia 239 22 884 (739—1,060) 11.2 North Ridge 409 30 1,221 (1,067—1,399) 22.9 63 �Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, summer 2011(Accessed http://cogcc.state.co.us/ Aug. 8, 2011). 64 �Figure 2. Over-winter (Dec—Mar) mule deer fawn survival (Ŝ) from 4 study areas in the Piceance Basin, northwest Colorado, 2008/09 (red lines), 2009/10 (orange lines) and 20010/11 (blue lines). Solid lines = Ŝ and dashed lines = 95% CI. Comparable data among years December—March due to premature collar drop during 2008 and 2009. 65 �Figure 3. Mule deer migration routes from 4 winter range study areas in the Piceance Basin of northwest Colorado, spring and fall 2010. 66 �Figure 4. Mule deer winter concentration areas (composite kernel Probability Density Functions; PDF) from 4 study areas in the Piceance Basin of northwest Colorado, March 2010—April 2011. Data from composite GPS locations (5 GPS location attempts/day) of adult female mule deer by study area. 67 �Figure 5. Mean male and female fawn weights and 95% CI (error bars) from 4 mule deer study areas in the Piceance Basin, northwest Colorado, December 2008—2010. 68 �Figure 6. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009—2011. 69 �70 �Colorado Division of Parks and Wildlife July 2010 − June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Effectiveness of a Redesigned Vaginal Implant Transmitter in Mule Deer Period Covered: July 1, 2010 − June 30, 2011 Authors: C. J. Bishop, C. R. Anderson, D. P. Walsh, E. J. Bergman, P. Kuechle, and J. Roth. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We completed all field work on this project and prepared draft manuscripts for publication prior to FY 10-11. As explained in our Segment Narrative for FY 10-11, our final objective for this project was to publish results of the study in Journal of Wildlife Management (JWM). Our manuscript was accepted for publication in JWM on March 23, 2011. The manuscript will be published in the November 2011 issue of JWM. 71 �WILDLIFE RESEARCH REPORT EFFECTIVENESS OF A REDESIGNED VAGINAL IMPLANT TRANSMITTER FOR CAPTURING MULE DEER NEONATES FROM TARGETED ADULT FEMALES CHAD J. BISHOP, CHARLES R. ANDERSON, JR., DANIEL P. WALSH, ERIC J. BERGMAN, PETER KUECHLE, AND JOHN ROTH P. N. OBJECTIVE To redesign vaginal implant transmitters (VITs) and evaluate their retention in free-ranging mule deer. SEGMENT OBJECTIVES 6. Publish findings in Journal of Wildlife Management. INTRODUCTION Mule deer (Odocoileus hemionus) fawn production and neonatal survival is influenced by dam characteristics (e.g., body condition, disease status, habitat use). To understand fawn-dam relationships, manipulative field studies are needed that allow fawn production and survival to be estimated as a function of treatments applied to adult females. For example, a study evaluating the effectiveness of winter range habitat treatments on subsequent neonatal survival would require the capture of fawns from marked adult females that verifiably used, or did not use, the habitat treatments the previous winter(s). Such studies depend on a technique that enables newborn fawns to be captured from marked adult females. The most promising technique employed to capture neonates from marked adult females is use of vaginal implant transmitters (VITs), which are placed in the vagina of adult females during early to mid gestation. In theory, adult females retain VITs until parturition, at which point VITs are expelled at birth sites along with newborn fawns. Assuming VITs are routinely monitored, researchers can promptly radiolocate shed VITs and capture the newborn fawns. Recent applications of VITs in white-tailed deer (O. virginianus; Carstensen et al. 2003, Haskell et al. 2007, Saalfeld and Ditchkoff 2007), black-tailed deer (O. hemionus columbianus; Pamplin 2003), mule deer (Bishop et al. 2007, Haskell et al. 2007), and elk (Cervus elaphus; Johnson et al. 2006, Barbknecht et al. 2009) have been moderately successful. Vaginal implant transmitters also permit measurement of fetal survival in free-ranging populations, which has important implications in populations where stillborn mortality occurs (Bishop et al. 2007, 2008, 2009). An additional advantage of using VITs to capture neonates may be a reduction in sampling bias when compared to capture techniques that rely on opportunistic fawn capture (White et al. 1972, Ballard et al. 1998, Pojar and Bowden 2004). Opportunistic techniques are susceptible to bias because of unequal capture success among vegetation types, distances to roads, fawn ages, and stages of fawning. For example, if roads are used to conduct opportunistic searches, fawn capture probability will decline with increasing distance from a road and neonates will be disproportionately sampled in areas with high road densities. When using VITs, the distribution of radio-marked adult females carrying VITs determines where neonates are sampled. Inferences will be less biased with VITs than with opportunistic capture techniques if all VITs are monitored with equal intensity during fawning and the sample of radio-marked adult females was captured with minimal bias. Thus, VITs could have broad applicability regardless of whether study objectives require that fawns be captured from previously marked adult females. The most significant problem associated with VITs has been premature expulsion and subsequent failure to locate birth sites or newborn fawns, especially in mule deer (Johnstone-Yellin et al. 2006, 72 �Bishop et al. 2007, Haskell et al. 2007). The VIT has flexible, plastic wings coated with a soft silicone that induce pressure against the vaginal wall to retain the transmitter. The VIT design facilitates a quick, non-surgical insertion process and is safe for the animal (Johnson et al. 2006), but the current wing design is inadequate with respect to retention. Bishop et al. (2007) found that 43% (SE = 4.7) of VITs in mule deer shed prepartum, although the probability of capturing ≥1 fawn was relatively high (0.792, SE = 0.0847) when VITs shed only 1–3 days prepartum. They noted that 25% (SE = 4.1) of VITs shed >3 days prepartum and that retention probability declined as deer body size increased, indicating the retention wings were too small to be effective in larger deer. Based on these results, considerable oversampling of adult females would be required in the design of future projects to achieve a target sample size of fawns. That is, extra adult females would need to be sampled to offset those adult females that shed VITs prematurely. Oversampling, in this instance, is undesirable from an animal care and use perspective and unnecessarily expensive. Thus, our objective was to redesign the plastic-silicone retention wings of VITs to allow maximum retention in larger deer species. Prior to our study, the wings used to retain VITs had been purchased from a company in New Zealand (Carter Holt Harvey Plastic Products, Hamilton, New Zealand) that originally produced them for an application in the livestock industry (Bowman and Jacobson 1998). The company manufactured 1 large wing and 1 small wing; the former has been used in production of VITs for bison (Bison bison) and elk (Cervus elaphus) whereas the latter has been used in production of VITs for deer (Advanced Telemetry Systems, Isanti, MN). Advanced Telemetry Systems (ATS), in cooperation with wildlife researchers, made an initial effort in 2004 to lengthen the retention wings by adding resin to the wing tips. Using these VITs with antennas cut to the appropriate length, Haskell et al. (2007) reported that 81% of VITs (n = 21) in deer were retained until parturition. Retention improved but the aftermarket wingmodification was problematic because the wing tips were hard and thus not ideal for placement in the vaginal canal. That study provided justification to pursue further wing development. We therefore redesigned retention wings of VITs used in deer and similar-sized ungulates, fabricated a new production mold, and evaluated retention rates of VITs in free-ranging mule deer. STUDY AREA We conducted our research in Piceance Basin and on the Roan Plateau in northwest Colorado (Fig. 1). Our winter range study area comprised 4 study units distributed across much of the Piceance Basin. The 4 units ranged in size from 70 to 130 km2 and are referenced as South Magnolia, StorySprague, Ryan Gulch, and Yellow Creek (Fig. 1). METHODS We prepared and submitted a draft manuscript to Journal of Wildlife Management (JWM). Initial reviews were favorable, and thus, we were invited to submit a revised manuscript for further consideration. We prepared a revised manuscript based on comments submitted by peer reviewers and the associate editor. RESULTS AND DISCUSSION Our revised manuscript was accepted for publication on March 23, 2011. The manuscript will be published in the November 2011 issue of JWM. The abstract from this publication follows: Our understanding of factors that limit mule deer (Odocoileus hemionus) populations may be improved by evaluating neonatal survival as a function of dam characteristics under free-ranging conditions, which generally requires that both neonates and dams are radiocollared. The most viable technique facilitating capture of neonates from radiocollared adult females is use of vaginal implant 73 �transmitters (VITs). To date, VITs have allowed research opportunities that were not previously possible; however, VITs are often expelled from adult females prepartum, which limits their effectiveness. We redesigned an existing VIT manufactured by Advanced Telemetry Systems (ATS; Isanti, MN) by lengthening and widening wings used to retain the VIT in an adult female. Our objective was to increase VIT retention rates and thereby increase the likelihood of locating birth sites and newborn fawns. We placed the newly designed VITs in 59 adult female mule deer and evaluated the probability of retention to parturition and the probability of detecting newborn fawns. We also developed an equation for determining VIT sample size necessary to achieve a specified sample size of neonates. The probability of a VIT being retained until parturition was 0.766 (SE = 0.0605) and the probability of a VIT being retained to within 3 days of parturition was 0.894 (SE = 0.0441). In a similar study using the original VIT wings (Bishop et al. 2007), the probability of a VIT being retained until parturition was 0.447 (SE = 0.0468) and the probability of retention to within 3 days of parturition was 0.623 (SE = 0.0456). Thus, our design modification increased VIT retention to parturition by 0.319 (SE = 0.0765) and VIT retention to within 3 days of parturition by 0.271 (SE = 0.0634). Considering dams that retained VITs to within 3 days of parturition, the probability of detecting at least 1 neonate was 0.952 (SE = 0.0334) and the probability of detecting both fawns from twin litters was 0.588 (SE = 0.0827). We expended approximately 12 personhours per detected neonate. As a guide for researchers planning future studies, we found that VIT sample size should approximately equal the targeted neonate sample size. Our study expands opportunities for conducting research that links adult female attributes to productivity and offspring survival in mule deer. The full text publication can be obtained electronically or in hard copy through JWM and WileyBlackwell Publishers. SUMMARY Use of VITs in well-designed field studies should increase our understanding of factors limiting deer populations by allowing investigators to link fawn production and survival to dam characteristics under free-ranging conditions. A primary drawback of VITs in deer has been the failure of many adult females to retain VITs to parturition. We increased VIT retention in mule deer by lengthening and widening wings used to retain a VIT in the vaginal canal. Researchers employing VITs with our modified wing design should require minimal oversampling to offset failures caused by early expulsion, thereby rendering the technique more cost-effective and reliable. Our findings provide explicit guidance for planning a fetal-neonatal deer study involving VITs. The question remains as to whether premature expulsion of VITs can be eliminated in mule deer. We observed modest evidence that deer expelling VITs >3 days prepartum were older and larger than deer that retained or nearly-retained VITs. We therefore recommend manufacturing slightly larger wings for large, older mule deer (e.g., >65 kg and >5 yrs old) as a possible strategy to further investigate VIT retention. An article documenting our research findings will be published in the November 2011 issue of JWM. 74 �LITERATURE CITED Ballard, W. B., H. A. Whitlaw, D. L. Sabine, R. A. Jenkins, S. J. Young, and G. J. Forbes. 1998. Whitetailed deer, Odocoileus virginianus, capture techniques in yarding and non-yarding populations in New Brunswick. Canadian Field-Naturalist 112:254−261. Barbknecht, A. E., W. S. Fairbanks, J. D. Rogerson, E. J. Maichak, and L. L. Meadows. 2009. Effectiveness of vaginal-implant transmitters for locating elk parturition sites. Journal of Wildlife Management 73:144−148. Bishop, C. J., D. J. Freddy, G. C. White, B. E. Watkins, T. R. Stephenson, and L. L. Wolfe. 2007. Using vaginal implant transmitters to aid in capture of mule deer neonates. Journal of Wildlife Management 71:945−954. Bishop, C. J., G. C. White, D. J. Freddy, B. E. Watkins, and T. R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1−28. Bishop, C. J., G. C. White, and P. M. Lukacs. 2008. Evaluating dependence among mule deer siblings in fetal and neonatal survival analyses. Journal of Wildlife Management 72:1085−1093. Bowman, J. L., and H. A. Jacobson. 1998. An improved vaginal-implant transmitter for locating whitetailed deer birth sites and fawns. Wildlife Society Bulletin 26:295−298. Carstensen, M., G. D. DelGiudice, and B. A. Sampson. 2003. Using doe behavior and vaginal-implant transmitters to capture neonate white-tailed deer in north-central Minnesota. Wildlife Society Bulletin 31:634−641. Haskell, S. P., W. B. Ballard, D. A. Butler, N. M. Tatman, M. C. Wallace, C. O. Kochanny, and O. J. Alcumbrac. 2007. Observations on capturing and aging deer fawns. Journal of Mammalogy 88:1482−1487. Johnson, B. K., T. McCoy, C. O. Kochanny, and R. C. Cook. 2006. Evaluation of vaginal implant transmitters in elk (Cervus elaphus nelsoni). Journal of Zoo and Wildlife Medicine 37:301−305. Johnstone-Yellin, T. L., L. A. Shipley, and W. L. Myers. 2006. Evaluating the effectiveness of vaginal implant transmitters for locating neonatal mule deer fawns. Wildlife Society Bulletin 34:338−344. Pamplin, N. P. 2003. Ecology of Columbian black-tailed deer fawns in western Oregon. Thesis, Oregon State University, Corvallis, USA. Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550−560. Saalfeld, S. T., and S. S. Ditchkoff. 2007. Survival of neonatal white-tailed deer in an exurban population. Journal of Wildlife Management 71:940−944. White, M., F. F. Knowlton, and W. C. Glazener. 1972. Effects of dam-newborn fawn behavior on capture and mortality. Journal of Wildlife Management 36:897−906. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 75 �Figure 1. Location of winter and summer range study areas in Piceance Basin and Roan Plateau, northwest Colorado. Winter range study units where we captured and radio-marked mule deer are noted as: YC = Yellow Creek, RG = Ryan Gulch, SM = South Magnolia, and SS = Story-Sprague. 76 �Colorado Division of Parks and Wildlife July 2010 – June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 2 Federal Aid Project No. W-185-R : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Evaluation of Winter Range Habitat Treatments On Over-winter Survival and Body Condition of Mule Deer Period Covered: July 1, 2010 - June 30, 2011 Author: E.J. Bergman; project cooperators, C.J. Bishop, D.J. Freddy, G.C. White and P. Doherty Personnel: C. Anderson, L. Baeten, D. Baker, B. Banulis, J. Boss, A. Cline, D. Coven, M. Cowardin, K. Crane, R. Del Piccolo, B. deVergie, B. Diamond, K. Duckett, S. Duckett, J. Garner, D. Hale, C. Harty, A. Holland, E. Joyce, D. Kowalski, B. Lamont, R. Lockwood, S. Lockwood, D. Lucchesi, D. Masden, J. McMillan, M. Michaels, G. Miller, Mike Miller, Melody Miller, C. Santana, M. Sirochman, T. Sirochman, M. Stenson, R. Swygman, C. Tucker, D. Walsh, S. Waters, B. Watkins, P. Will, L. Wolfe, V. Yavovich, K. Yeager, M. Zeaman, CPW, L. Carpenter - Wildlife Management Institute, D. Felix, L. Felix - Olathe Spray Service, P. Johnston, M. Keech, D. Rivers, J. Rowe, L. Shelton, M. Shelton, R. Swisher, S. Swisher - Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Between November 2004 and June 2009 we conducted a five year, multi-area study to assess the impacts of landscape level winter range habitat improvement efforts on mule deer population performance. This study took place on the Uncompahgre Plateau and in adjacent valleys in southwestern Colorado. We measured over-winter fawn survival and deer abundance annually on 5 study areas. Four study areas were permanently located, whereas location of the fifth area varied each year to accommodate the variability in habitat treatments over the southern half of the Uncompahgre Plateau. Additionally, on 2 of the study areas we estimated late winter body condition of adult female deer. Compared to results from other research throughout the West, as well as on the Uncompahgre Plateau, survival estimates for 6-month old mule deer fawns were highly variable between areas, and tended to be near published long term averages. Estimated survival rates from this study ranged between 0.359 (SE = 0.0950) and 0.933 (SE = 0.0648). Evidence suggests that areas that have received habitat treatments have higher fawn survival. Based on estimates of total body fat for adult female deer, there was a slight distinction between treatment and reference study areas. Deer abundance on the study areas varied between winters, but in general abundance estimates did not show increasing or decreasing trends. Major fluctuations within abundance estimates are likely attributable to animal movements and winter severity. Final publications will be completed during the fall of 2011 and spring of 2012 and submitted for peer-reviewed publication upon completion. 77 �WILDLIFE RESEARCH REPORT EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER ERIC J. BERGMAN P.N. OBJECTIVES To determine whether mechanical/chemical treatments of native habitat vegetation increases over-winter mule deer fawn survival, adult doe body condition, and localized deer densities on the Uncompahgre Plateau in southwest Colorado and to conduct a simulation based optimization study to determine optimal management strategies of deer under variable environmental, habitat and harvest conditions. SEGMENT OBJECTIVES 1. Complete all portions of academic/coursework requirements of PhD through Colorado State University. 2. Complete final analyses for survival and density components of the study. 3. Initiate preliminary body condition analyses and narrative for mule deer management strategies. INTRODUCTION A common trend among many terrestrial, mammalian systems is a tendency to cycle between population highs and lows (Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001, Clutton-Brock and Pemberton 2004). While the true cause of these cycles is likely a merger of habitat quality, weather, disease, predation, sport hunting, competition and community population dynamics, it is often necessary or intriguing for wildlife managers and ecologists to identify the primary limiting factor to population growth. Without exception, mule deer populations have also demonstrated a tendency to show large fluctuations. Several dramatic declines have been observed since the turn of the 19th century (Connolly 1981, Gill 2001, Hurley and Zager 2004). However, only one period of increase, a general trend during the 1940's and 1950's, has been noted. The most recent and pressing decline took place during the 1990's (Unsworth et al. 1999). Colorado has not escaped these tendencies, with certain parts of the state experiencing population declines by as much as 50% between the 1960's and present time (Gill 2001, B. Watkins personal communication). Primarily due to the value of mule deer as a big game hunting species, wildlife managers' challenges are two-fold: understanding the underlying causes of mule deer population change and managing populations to dampen the effects of these fluctuations. In Colorado, the role of habitat as the limiting factor for mule deer populations was recently tested. Specifically, the role of forage quality and quantity on over-winter fawn survival was tested using a treatment/reference cross-over design with ad libitum pelleted food supplements as a substitute for instantaneous high quality habitat improvements (Bishop et al. 2009). The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e. if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the primary limiting factor on populations. As such, nutrition enhancement treatments increased fawn survival rate by 0.22 (Bishop et al. 2009). This research effectively identified some of the underlying processes in mule deer population regulation, but did not test the effectiveness of acceptable habitat management techniques. Due to the undesirable effects of feeding wildlife (e.g. artificially elevating density, increased potential for disease transmission and cost), a more appropriate technique for achieving a high quality nutrition enhancement needs to be assessed. 78 �We completed a multi-year, multi-area study to assess the impacts of landscape level winter range treatments on mule deer population performance. We conducted the study on the Uncompahgre Plateau and adjacent valleys in southwestern Colorado because this area had an active history of habitat treatments that were implemented in part to enhance deer populations. To assess the impacts of habitat treatments on mule deer in these areas, we measured over-winter fawn survival, mule deer density and late winter body condition. STUDY AREA At the onset of this study (Bergman et al. 2005), we identified 2 pairs of treatment/reference study areas, stratified into historically known high and low deer density areas. The selection process for these pairs of experimental units followed several strict guidelines: 1) Treatment/reference units could not be further than 10km apart, but needed to have adequate buffer to minimize the movement of animals between the treatment and reference areas. 2) Reference study areas could not have received any mechanical treatment during the past 30 years. 3) Strata were defined by winter range type (all experimental units had to be in pinyon/juniper winter range) and deer density. 4) Treatment units needed to have received mechanical treatment in the past, but also had to be capable of receiving further treatments during the study period. Each winter a 5th study area was added to increase the level of inference that could be drawn from this study. For each of the 4 winters covering the study period, this 5th study area shifted between 4 randomly selected areas. The treatment history on each of these additional study areas varied, but was representative of what can be expected of typical winter-range treatments. During the first winter of this study, this 5th study area fell on Shavano Valley. Treatments on Shavano Valley were primarily composed of roller-chopping in the higher pinyon/juniper range and were reseeded with browse species. During the second winter of the study, the 5th study area fell on the Colona Tract (~5km2) of Billy Creek State Wildlife Area (approximately 15km south of Montrose, CO). The treatment history of Colona Tract was primarily composed of brush mowing and chemical control of weeds and dry land fertilization of preferred species. During the third winter of the study, the 5th study area was located at McKenzie Buttes. The treatments at McKenzie Buttes were slightly older (10-15 years) and were also composed of rollerchopping. During the final year of the study, the 5th study area was located at Transfer Road. The treatments available to deer at Transfer were younger (1-2 years) and were composed of hydro-ax and some roller-chopping. The high density treatment area was located on the Billy Creek tract of Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). The high density reference area was located around Beaton Creek (approximately 15km south of Montrose, CO and approximately 5km north of Billy Creek State Wildlife Area). Both of the high density study areas were located in GMU 65 (DAU D-40). The low density treatment area was located on Peach Orchard Point, on/near Escalante State Wildlife Area (approximately 25km southwest of Delta, CO). The low density reference area was located on Sowbelly and Tatum draws (approximately 25km west of Delta, CO and approximately 8km from Peach Orchard Point). Both of the low density study areas were located in GMU 62 (DAU D-19). All of the other study areas, mentioned above, were also located in GMU 62 (DAU D-19) to the west of Montrose, CO. METHODS Twenty-five mule deer fawns were captured and radio-collared in each of the 5 study areas. Fawns were captured via baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) and helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) between mid-November and late- 79 �December. To make fawn collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars after approximately 6 months. On a daily basis, from December through May, we monitored the radioed fawns in order to document live/death status. This allowed us to determine accurately the date of death and estimate the proximate cause of death. Daily monitoring was done from the ground to maximize efficient collection of mortalities and assessment of cause specific mortality. Weekly aerial telemetry flights were conducted to insure that all deer were heard at least once a week, allowing weekly survival estimates for each study area. To estimate body condition, an additional 30 adult female deer were captured via helicopter netgunning and fitted with temporary neckbands, in late-February within each of the 2 high density study areas. For body condition work, we relied on methods that employed the use of ultrasonography to estimate total body fat (Stephenson et al. 1998, Cook 2000, Stephenson et al. 2002). Blood samples were also collected for endocrinology and pregnancy tests. During late winter (early-March) we estimated deer density on each of our study areas. Helicopter based mark-resight techniques were used for density estimation (Gill 1969, Bartmann et al. 1986, Kufeld et al. 1980, Freddy et al. 2004). Survival analyses were conducted on all years of data. In addition to including individual covariates (fawn sex and mass), we tested the role of habitat treatment history on survival. Estimating survival for study areas took place in several different forms. The simplest form was constant survival where all study areas were pooled and survival was estimated using a single parameter. The second simplest form was to estimate survival for each unique study area (i.e., 8 survival estimates were generated, hereafter “Area”). The remaining model structures allowed study areas to be partitioned according to treatment history. Derivations of these models that included year as either an additive or multiplicative effect were then built. All survival models were evaluated in program MARK using the known-fate model type with logit link function (White and Burnham 1999). All models were compared using Akaike's Information Criterion corrected for small sample size (Burnham and Anderson 2003). All abundance and density estimates were also computed using program MARK (White and Burnham 1999). Abundance models varied via the process used to estimate the detection probability of deer, but abundance estimates across areas and years were not pooled. RESULTS AND DISCUSSION Survival models indicate that landscape treatments tend to benefit deer. Model structures that incorporate the landscape treatment history of an area tend to outperform those that do not accommodate treatment history (Table 1). Additionally, the top performing model allowed year to vary as an additive effect and incorporated fawn mass. Fawn sex did not add much additional strength to any given model. Of particular interest to this study is that models incorporating study area treatment level consistently improved the performance of simpler models that had identical structure, save this one aspect. Not surprisingly, allowing survival rates to vary by year was fundamental for a model to receive any model weight. Density estimates were collected during March for all study areas, during the last four years of the study. Abundance estimation was done in program MARK (White and Burnham 1999). Abundance estimates tended to fluctuate by year in each area, but no discernable trends were observed (Table 2). Fluctuations were likely due to localized winter conditions and the concentrating or diluting of deer on 80 �our study areas. Overall, no major changes in abundance, in any of the study areas, are believed to have occurred. Late winter body condition estimates for adult females were consistent during all years of this study, but they tended to be higher than those estimates during previous research on the Uncompahgre Plateau (Bishop et al. 2009 and C.J. Bishop, personal communication). The lowest single total percent body fat estimate for this study was recorded during the final winter, despite the fact that observations of winter severity indicated that body fat estimates likely should have been higher. For the two study areas where body condition estimates were measured, they did have a tendency to reflect the same trends that were observed in survival estimates. However, there was no apparent statistical distinction in total percent body fat between our study areas. This lack of distinction was also observed in the levels of the T3 hormone, whereas T4 hormone (nmol/l) was higher in Billy Creek (mean = 85.72, SD = 10.07) than in Beaton Creek (Mean = 63.01, SD = 13.06) (Table 3). Pregnancy rates were surprisingly variable during this study, with rates ranging between 80% and 97% (Table 3). Progress towards completion of the requirements for a PhD was also made during the 2010-11 year. As of summer 2011, all coursework needed to meet scholastic requirements has been completed. SUMMARY Survival rates for mule deer fawns across our study areas and across years ranged between 36% and 93%. Throughout the course of the study, overall body condition parameter estimates for late-winter adult female deer mirrored estimates collected during different studies (Bishop et al. 2009). Estimates of total deer density across our study areas continued to reflect historical estimates, but annual variation was observed. Overall, a consistent trend of higher survival of fawns was observed in treated study areas, indicating winter range treatments likely have a positive effect on survival. LITERATURE CITED Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M., L.H. Carpenter, R.A. Garrott, and D.C. Bowden. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. —————, G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. Bergman, E.J., C.J. Bishop, D.J. Freddy, G.C. White. 2005. Pilot evaluation of winter range habitat treatments of mule deer fawn over-winter survival. Wildlife Research Report July: 23-35. Colorado Division of Wildlife, Fort Collins, USA. Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172. Burnham, K.P. and D.R. Anderson. 2003. Model selection and multi-model inference. Springer, New York, USA. Clutton-Brock, T., and J. Pemberton, editors. 2004. Soay sheep: dynamics and selection in an island population. Cambridge University Press, UK. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. Cook, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain Elk. Thesis, University of Idaho, Moscow, USA. 81 �Freddy, D.J., G.C. White, M.C. Kneeland, R.H. Kahn, J.W. Unsworth, W.J. DeVergie, V.K. Graham, J.H. Ellenberger, and C.H. Wagner. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. Gill, R.B. 1969. A quadrat count system for estimating game populations. Colorado Division of Game, Fish and Parks, Game Information Leaflet 76. Fort Collins, USA. ————— 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Hurley, M., and P. Zager. 2004. Southeast mule deer ecology - Study I: Influence of predators on mule deer populations. Progress Report, Idaho Department of Fish and Game, Boise, USA. Jedrzejewska, B., and W. Jedrzejewski. 1998. Predation in Vertebrate Communities: the Białowieża Primeval Forest as a case study. Springer-Verlag, Berlin, Germany. Krebs, C.J., S. Boutin, and R. Boonstra, editors. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. Kufeld, R.C., J.H. Olterman, and D.C. Bowden. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. Ramsey, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. Schmidt, R.L., W.H. Rutherford, and F.M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. Stephenson, T.R., V.C. Bleich, B.M. Pierce, and G.P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. ————— , T. R., K. J. Hundertmark, C. C. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717722. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G.C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Prepared by Eric J. Bergman, Wildlife Researcher 82 �Table 1. Survival model results for radio collared fawns on the Uncompahgre Plateau. Model 3Trt Levels + Year + Mass Year + Mass 3Trt Levels + Year + Sex + Mass Year + Sex + Mass 3Trt Levels + Year Area + Mass 3Trt Levels + Year + Sex Year Area + Sex + Mass Year + Sex Area + Year Area * Year 3Trt Levels * Year 3Trt Levels Area Area + Sex Area * Year * Week AICc Delta AICc AICc Weights k 1418.08 1419.05 1419.45 1420.61 1436.06 1436.89 1437.10 1437.59 1438.19 1438.43 1438.59 1441.89 1443.92 1453.32 1456.25 1457.35 2033.12 0.00 0.97 1.37 2.53 17.98 18.81 19.02 19.52 20.11 20.36 20.51 23.81 25.85 35.25 38.17 39.27 615.04 0.4163 0.25626 0.20989 0.11735 0.00005 0.00003 0.00003 0.00002 0.00002 0.00002 0.00001 0 0 0 0 0 0 7 5 8 6 6 9 7 4 10 5 11 20 12 3 8 9 480 83 �Table 2. Abundance estimates with 95% confidence intervals for the 8 study areas, collected during the last 4 years of the study. Study Area Year Abundance Buckhorn Buckhorn Buckhorn Buckhorn Billy Creek SWA Billy Creek SWA Billy Creek SWA Billy Creek SWA Peach Orchard Point Peach Orchard Point Peach Orchard Point Peach Orchard Point Sowbelly/Tatum Sowbelly/Tatum Sowbelly/Tatum Sowbelly/Tatum Shavano Valley Colona McKenzie Butte Transfer Road 2006 2007 2008 2009 2006 2007 2008 2009 2006 2007 2008 2009 2006 2007 2008 2009 2006 2007 2008 2009 1324 780 1675 721 691 536 507 552 429 470 462 361 402 663 461 444 819 528 691 352 95% C.I. on Abundance 794 - 2217 695 - 875 1460 - 1922 548 - 951 483 - 992 479 - 601 458 - 562 449 - 681 307 - 603 340 - 655 340 - 633 215 - 615 294 - 554 534 - 826 356 - 599 296 - 674 586 - 1148 482 - 577 441 - 1089 164 - 784 Table 3. Late-winter body condition estimates for female adult mule deer on the Uncompahgre Plateau. Sample sizes were 30 does in each area. Mean T3 and T4 samples are reported in nmol/l. Parameters marked with an asterisk designate a significant difference between areas at the 0.05 level. Year 2005-2006 2006-2007 2007-2008 2008-2009 Parameter % Body Fat T3* T4 % Body Fat T3 T4 % Body Fat T3 T4* % Body Fat T3 T4* Billy Creek 8.80% (2.02) 1.12 (0.28) 70.69 (20.94) 7.61% (1.94) 1.55 (0.53) 88.23 (19.53) 8.09% (1.10) 1.17 (0.28) 94.30 (20.7) 7.20% (1.85) 1.22 (0.32) 74.63 (14.61) 84 Buckhorn N.A. N.A. N.A. 7.03% (1.80) 1.42 (0.31) 78.07 (22.34) 7.20% (1.69) 1.17 (0.56) 56.20 (23.30) 6.25% (1.63) 1.26 (0.35) 54.77 (19.34) Sowbelly 9.81% (2.88) 1.41 (0.51) 79.97 (15.80) N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. N.A. �Colorado Division of Parks and Wildlife July 2010 − June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2010 − June 30, 2011 Authors: C. J. Bishop, M. W. Alldredge, D. P. Walsh, E. J. Bergman, and C. R. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique should significantly reduce stress that is typically associated with capture and handling and eliminate capturerelated mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fullyfunctional prototype of the device. We conducted an extensive field evaluation of the device with freeranging mule deer during winter 2010-11. We successfully collared, weighed, and identified sex of 6 different mule deer fawns across 4 winter range locations along Colorado’s northern Front Range. Collars were purposefully made to shed from deer within several weeks or months of being collared. Two fawns were successfully re-collared after they shed the first collars they received. Thus, we observed 8 successful collaring events involving 6 different fawns. Most fawns demonstrated minimal response to collaring events, either remaining in the device or calmly exiting. Certain components of the collaring device failed to function optimally when temperatures dropped below approximately −15° C, while other components did not adequately withstand mule deer use under field conditions. Also, certain behaviors of mule deer when approaching and using the device created circumstances where it was possible to collar the same animal twice, which happened on one occasion. We identified a series of device modifications that would be necessary to address these various issues. During 2011-12, we will modify the device accordingly and conduct a follow-up field evaluation. 85 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, MATHEW W. ALLDREDGE, DANIEL P. WALSH, ERIC J. BERGMAN, AND CHARLES R. ANDERSON, JR. P. N. OBJECTIVE To develop and evaluate a trap-like device for mule deer that will automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. SEGMENT OBJECTIVES 7. Evaluate effectiveness and functionality of an automated collaring device for collaring, weighing, and identifying sex of mule deer fawns during winter under free-ranging conditions. INTRODUCTION Colorado Parks and Wildlife (CPW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240−300 deer fawns are captured annually to monitor survival among 4−5 populations distributed across western Colorado and an additional 100−350 deer fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CPW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., >$5,000 ea.) would reduce CPW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should have virtually no potential to cause capture-related mortality. The large-mammal capture techniques described 86 �above place considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CPW’s operating expenses and improve animal welfare. Therefore, we designed, produced, and evaluated an automated device for collaring, weighing, and identifying sex of mule deer fawns during winter under free-ranging conditions. STUDY AREA We conducted all evaluations with captive deer at the Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado. We conducted field evaluations with free-ranging deer at 5 sites along Colorado’s northern Front Range: 1) Horsetooth Reservoir, west of Fort Collins, private land 2) Masonville, southwest of Fort Collins, private land, 3) Red Feather, northwest of Fort Collins, private land, 4) Hall Ranch, west of Lyons, Boulder County Parks and Open Space, and 5) Heil Valley Ranch, southwest of Lyons, Boulder County Parks and Open Space. We plan to conduct additional field evaluations with free-ranging deer in northwest Colorado during 2011-12. METHODS We identified detailed specifications to guide the design and development of an automated collaring device and sought assistance from Colorado State University’s Mechanical Engineering Department. The collaring device became a senior design project for 6 CSU engineering students during the 2008-09 school year. We met with the students weekly and provided them a materials budget of $10,000 to produce a prototype device. We conducted staged evaluations of device components during the year by working with captive deer at FWRF. We also conducted limited evaluations with freeranging deer during spring 2009. Field evaluations focused primarily on how deer utilized and interacted with the device to guide subsequent design and development decisions. We documented utilization and interactions using direct observation and motion-sensor digital cameras. We relied exclusively on digital cameras when we were not on-site during an evaluation. Automation of the collaring device was disabled any time we were not present to prevent any potential harm to deer. Following preliminary field evaluations, we refined our design specifications and developed a contract with Dynamic Group Circuit Design (DGCD), located in Fort Collins, Colorado, to produce a fully-functional prototype device. We routinely met with electrical engineers from DGCD, and a mechanical engineer subcontracted by DGCD, during 2009-10. These meetings ensured that our device specifications were being satisfactorily met from both engineering and deer biology perspectives. Working with DGCD, we produced a fully-functional prototype device in 2010 that met our design specifications as set forth in the contract. The prototype device comprises an aluminum cage attached to a bait compartment (Fig. 1). Deer enter the device through an adjustable opening at the front of the cage. The adjustable opening can be used to deter entry of larger animals by adjusting both width and height. The sides of the cage comprise one-way gates that prevent entry into the device but allow an animal to exit the device at any point. The bait compartment is accessed through an opening positioned at the rear of the cage. An expandable radio collar is placed in this opening by extending it around four rectangular, aluminum plates that hold the collar in the fully-expanded position (Fig. 2). Radio collars are made expandable by attaching springs to each end of the transmitter; that is, springs are used in place of belting on standard radio collars. Clear plexiglass separates the cage from the bait compartment to maximize visibility. A deer is able to extend its head and neck through the expanded radio collar positioned in the rear opening to access the bait in the bait compartment, which is the only access point to the bait (i.e., it cannot be reached by an animal outside of the device). The floor of the cage is a scale that continuously records weight and informs device operation. Only animals in a specified weight range can be collared, which allows the user to 87 �target fawns and avoid collaring adult deer. Specifically, the mechanism that releases the collar around a deer’s neck will not trigger when an animal is too heavy or too light. Also, an actuator moves a plexiglass plate into the space between the rear cage opening and the bait pan, preventing animals outside of the weight range from accessing the bait. Shortly after a non-target animal exits the device, the collar release mechanism is once again able to be released (when triggered) and the actuator lowers the plexiglass plate so that the bait is accessible. To prevent an animal from being collared twice, a loop antenna is placed around the entrance to the cage and connected to a radio frequency identification (RFID) reader. All collars used with the device include a small RFID transponder sewn into the collar material. If a previously-collared fawn enters the cage, the RFID transponder is detected, which in turn prevents the collar from being released and activates the actuator to block access to the bait. If a deer enters the cage that is in the specified weight range and has not been previously collared, the collar will release around the deer’s neck once it accesses the bait. The collar release is triggered when a deer’s head breaks an infrared beam positioned immediately above the bait pan. The collar is released by activating a solenoid, which in turn releases a lever that causes the upper 2 aluminum plates holding the expanded collar in place to collapse (Figs. 3 and 4). The collar is then situated around the deer’s neck. When the collar is released, 2 different cameras are immediately activated to take a series of 3 photographs each. One camera is positioned in the back of the bait compartment and set to take a closeup photo of the top of the deer’s head. The second camera is positioned in the floor of the cage and set to take a photo of the deer’s abdomen and groin. These cameras are activated only when a collar is released and facilitate determination of deer sex. Last, when a collar is released, the device records and stores the weight of the deer. An external computer can be hooked up to the device to change program settings, remotely operate the device, and upload weight data. The device is powered by a 12 volt battery that must be recharged every 2-3 days assuming continuous operation. DGCD prepared a user’s manual that explains device operation and detailed schematics to allow future production. We evaluated effectiveness of the device in the field during winter 2010-11. Initially, we only set the device with a collar in place when we were present and able to directly observe deer interactions with the device. After collaring several animals in this manner and troubleshooting problems with the device, we set the device to operate remotely without an observer on-site, which is how it was intended to be used. RESULTS AND DISCUSSION We began baiting sites at Horsetooth Reservoir and Masonville on October 21, 2010, to attract deer for evaluating the device. We baited sites with alfalfa hay, apple pulp, dried fruit, and cereal. We baited several other sites briefly but discontinued baiting due to lack of deer use. Deer immediately responded to bait at Horsetooth Reservoir and began accessing the bait daily. On October 26, we placed the collaring device on site and began encouraging deer to walk into the device by placing bait on the scale inside the cage. On October 29, we documented a deer accessing the bait pan within the bait compartment for the first time. In the following weeks, we continued to periodically document deer entering the device and accessing the bait pan, although malfunctioning of the device prevented deer from being collared. One malfunction occurred because an electrical signal emitted from a camera placed at the entry of the device interfered with the RFID reader, which ultimately prevented fawns from being collared. It took roughly a week to diagnose the problem, which was corrected by simply removing the camera from the entry of the device. This particular camera was not wired into the device and was not critical to device functioning. We deemed that this camera was unnecessary and would be more useful if placed approximately 5 meters away from the trap to better document deer use and behavior. A second malfunction occurred because the scale did not have adequate support underneath and touched the 88 �ground, thereby giving inaccurate weight readings, which also prevented deer from being collared. We corrected this particular problem by welding an aluminum frame to better support the scale. Once these problems were corrected and other adjustments were made, we remotely collared our first fawn (female) on November 17, 2010. The fawn showed little reaction to the collaring event, calmly exiting the trap shortly after receiving the collar. The fawn’s weight and sex were successfully recorded. Sex was positively confirmed based on a photograph of the fawn’s head taken by the camera positioned in the bait compartment. We continued to monitor the device at Horsetooth Reservoir because there were adequate numbers of uncollared fawns in the area. However, we continued to encounter various problems with the device that affected functionality. Most notably, the collar release mechanism began failing to release the collar when a fawn was in position. We quickly determined that device controls were working properly and that an electrical signal was successfully being sent to the solenoid when an uncollared fawn was in the proper position accessing the bait. The source of the problem was a mechanical failing associated with the release mechanism itself. When an expanded collar was in place (i.e., in a fully-expanded state), the tension of the collar sometimes prevented the release lever from moving enough to release the aluminum plates holding the collar in position. Once aware of the problem, we began making adjustments to the release mechanism to improve its functionality. Another problem we identified was that fawns were placing their front hooves on a piece of metal trim at the front of the cage when accessing the bait, which led to inaccurate weight readings and missed opportunities to collar fawns. We corrected this problem by placing a plastic shield above the metal trim so that deer could no longer place hooves on the metal trim. Following this modification, the entire floor surface of the cage comprised only the scale. We also noted that small fawns accessing the bait sometimes failed to break the infrared beam extending across the center of the bait pan, thereby failing to be collared. Thus, we adjusted the positioning of the bait pan to make sure that fawns successfully broke the infrared beam when accessing the bait, regardless of size. Once these changes were made, we successfully collared two more fawns (1 male and 1 female) on successive days, December 13 and 14, 2010. Also, the female fawn that was collared on November 17 shed its collar on December 13 and was successfully recollared on December 20. On December 21, the actuator that opens and closes the bait door short-circuited in response to cold, snowy weather and damaged the circuit board that controls operation of the device. The actuator was positioned such that moisture could enter it. The moisture, in combination with cold temperatures, caused the failure. It became evident at this point that future device modifications would likely require a heavier-duty actuator. However, until a new actuator could be researched, tested, and installed, DGCD used the same actuator and positioned it differently so that it was less likely to take on moisture. DGCD also replaced the circuit board to restore functionality of the collaring device. Several weeks were required to make these modifications, causing the device to be inoperable from December 21, 2010, through January 15, 2011. On January 20, we recollared the female fawn that was initially collared on December 14 (it shed the first collar on January 13). We then moved the device to the Masonville bait site on January 21, after documenting 5 successful collaring events at Horsetooth Reservoir. The Masonville bait site was regularly visited by 4 bucks, 3 does, and 2 fawns. The fawns were aggressively chased by the 4 bucks once we put the collaring device in place and restricted the amount of bait available outside of the collaring device. We solved this problem by creating a separate bait site for the bucks a short distance away. It took one week before the fawns at Masonville became comfortable entering the collaring device and accessing the bait in the bait pan. We did not put a collar in place initially because we speculated that the fawns would be more likely to access the bait pan for the first time if they were not required to extend their head through the collar. Once one of the fawns became acclimated and we put a collar in the device, the bait door/actuator began malfunctioning again, preventing the fawn from being collared. The malfunctioning was apparently related to cold temperatures. The bait door/actuator began functioning correctly again several days later and we collared 89 �a male fawn on February 4, 2011. The only other fawn on site showed no interest in accessing the bait in the bait pan during the ensuing week. Thus, we stopped baiting the site on February 12 and moved the device to the Red Feather site on February 14. Several of the gate arms that prevent deer entry into the sides of the device had been damaged by deer over the course of the winter. During February 14−20, as deer became accustomed to the collaring device, we replaced all gate arms with a new, more durable hinge system. We then resumed normal operations and collared our 7th fawn (female) on February 27, 2011. Unfortunately, the RFID reader failed to detect this collared fawn the following day, allowing the fawn to receive a second collar on February 28. We suspended collaring efforts for several days evaluating the RFID failure. It became evident that if a collared fawn entered the device quickly, it could go undetected by the RFID reader. This issue was already understood as a potential problem, but this was the first time a fawn was actually double-collared. We documented no ill effects of the second collar on the fawn. Realizing the odds of a double-collaring event were low, we resumed collaring efforts on approximately March 6. Incidentally, the odds of the double-collared fawn receiving a third collar were essentially zero because the fawn now had two RFID transponders. We made note that the RFID problem would need to be resolved with a device modification during the following year. The other couple of fawns routinely visiting the site were reluctant to access the bait pan. On March 17, we moved the collaring device to the Heil Valley Ranch site on Boulder County Parks and Open Space land. Deer regularly visiting the Heil site included 4 bucks, 2 does, and 1 fawn. We were unable to keep the bucks from being aggressive toward the does and fawn around the collaring device, which prevented the fawn from entering the device. In response, we moved the device to the Hall Ranch bait site on March 24, 2011, where 3-4 bucks, 2-3 does, and 1-3 fawns were using the site. Deer acclimated quickly to the collaring device and we collared our 8th fawn on March 28th, immediately after placing the collar in the device. A few days later we concluded the field evaluation because weather was turning warm, green forage was abundant, and bears were coming out of hibernation. During our field evaluation, we documented a number of issues with the collaring device that need resolved in subsequent design modifications: • The solenoid release mechanism occasionally failed to release the collar even when the solenoid was triggered. We plan to evaluate an alternative release mechanism that uses an archery caliper release instead of the existing metal, latch system. • We documented several scenarios that could allow a fawn to receive a second collar. First, if a collared fawn extends its head through the entry to the device and is detected by the RFID reader but fails to move forward onto the scale for ≥30 seconds, the bait door will move back into the open position. Second, if a collared fawn is on the scale for >15 minutes (i.e., beds down on the scale), the scale will rezero and the door will move back into the open position. At this point another fawn could step into the device, which would indicate a correct weight range, and the collared fawn could receive a second collar if it then accessed the bait. Third, as we directly witnessed, if a collared fawn enters the device quickly, it is possible the RFID reader could fail to detect the RFID transponder in the fawn’s collar. These scenarios, albeit unlikely, can be corrected by changing the device programming and increasing sensitivity of the RFID reader/antenna. • The actuator that controls the bait door commonly malfunctioned in cold temperatures (i.e., ≤ −12 °C). We intend for the device to be fully functional at −32 °C. We plan to research other actuators and evaluate them under controlled temperature settings. A number of actuators are available on the market that meet our temperature specifications, but they range in cost from <$100 to >$1000. The actuator we evaluated was the cheapest available and did not meet its 90 �• stated specifications. Our intent is to find the cheapest actuator that will hold up under field conditions. The camera mounted on the floor of the device commonly failed to provide useful images for identifying sex. We therefore plan to remove the floor-mounted camera. In contrast, the camera in the bait compartment positioned to take pictures of a fawn’s head provided conclusive evidence of sex. The only needed adjustment is to more securely attach the “head camera” to the bait compartment. Working with DGCD, we will research and implement the necessary device modifications to address these issues. We plan to incorporate the design modifications during summer-fall 2011 and conduct a follow-up field evaluation during winter 2011-12. SUMMARY We developed a fully-functional prototype of an automated collaring device for mule deer in collaboration with professional engineers. The automated collaring device is designed to allow biologists and researchers to radio-collar portions of their deer samples with minimal time and expense because no animal handling is required and deer can be collared at any time. Primary time commitments include baiting sites, moving device(s) among sites, and adding collars to the devices. The collaring device should also have distinct benefits for studies in urban environments by providing a non-invasive technique for collaring deer. We successfully collared 6 different fawns during Nov−Mar, 2011−12, along Colorado’s northern Front Range. We recollared 2 of these fawns after they shed their initial collars, resulting in 8 successful collaring events. Fawns generally showed minimal reaction to being collared. It was evident that fawns did not experience the type of stress that is associated with typical capture and handling techniques. We documented a number of functional issues with the collaring device, which we plan to resolve through design modifications during summer-fall 2011. We then plan to conduct a follow-up field evaluation during winter 2011-12. LITERATURE CITED Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108−114. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 91 �Figure 1. Automated collaring device for mule deer, comprising an aluminum cage and a bait compartment. Deer become collared by entering the cage and extending their head through an expanded radio collar when accessing bait. 92 �Figure 2. View of the radio collar and bait compartment of an automated collaring device for mule deer. To reach bait, deer must extend their head and neck through the expanded radio collar. 93 �Figure 3. View of the collar release mechanism in an automated collaring device for mule deer. 94 �Figure 4. Female mule deer fawn accessing bait by extending her head through an expanded radiocollar. 95 �96 �Colorado Division of Parks and Wildlife July 2010 – June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 3001 : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Assessment of survival and optimal harvest Strategies of adult male mule deer in Middle Park, Colorado W-185-R Period Covered: July 1, 2010 - June 30, 2011 Author: E.J. Bergman; Project Cooperators; C.J. Bishop, K. Oldham, and L. Sidener Personnel: G. Abram, G. Birch, J. Broderick, M. Crosby, B. Davies, T. Elm, D. Gillham, K. Holinka, A. Holland P. Lukacs, B. Manly, S. Murdoch, S. Schwab, S. Shepherd Colorado Division Parks and Wildlife R. Swisher, S. Swisher, T. McKendrick Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We developed a study plan and initiated field work on a study designed to assess the survival and optimal harvest strategies of adult male mule deer in Middle Park, Colorado. Three years of baseline survival data for adult (≥ 1 yr. old) male deer will be collected before implementing a harvest management action that will redistribute hunters within DAU-9. One hundred adult (1.5 years old and older) male deer were captured and radio collared. The survival rate for these deer was estimated at 0.879 (SE = 0.0326) for the first survival period (January through July). 97 �WILDLIFE RESEARCH REPORT ASSESSMENT OF SURVIVAL AND OPTIMAL HARVEST STRATEGIES OF ADULT MALE MULE DEER IN MIDDLE PARK, COLORADO ERIC J. BERGMAN P.N. OBJECTIVES SEGMENT OBJECTIVES 1. Develop a project study plan to address the lack of knowledge regarding survival and harvest strategies of adult mule deer. 2. Initiate field work in the form of capturing and radio collaring animals. 3. Collect survival data on radio collared deer and provide preliminary survival estimates for adult male mule deer. INTRODUCTION Historically, management of big game species has focused on the performance of adult females and the young of the year segments of the population. In the case of mule deer, this has been further refined to the aspects of annual (for adult females) and overwinter (for young of the year) survival. The performance of the male component of populations was deemed less important because it takes few males to provide adequate breeding coverage for the population, and historic harvest management objectives were set to maximize hunting opportunities. As long as sufficient numbers of males were available to breed females there was no desire to restrict hunting opportunity. However, during the past 10-15 years, the management of big game populations, and mule deer populations in particular, has shifted from the objective of providing maximal opportunity towards providing higher quality opportunities (Bishop et al. 2005b, Bergman et al. 2010). High quality opportunities are typically defined by hunters as a combination of the chance to see a greater number of male deer during the hunt, increased potential to harvest an older age class animal (i.e., an animal with more developed antler morphometry), but also reduced interaction and competition with other hunters. In response to this shift in hunter desires and concerns over declining mule deer numbers, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) implemented a statewide limitation in deer hunting in 1999. This statewide limitation gave CPW the ability to reduce total hunter numbers but also the ability to control the distribution of hunters throughout the state. Since 1999 Colorado’s deer herds have become composed of a greater number of males, yet little biological data on them exist. Also stemming from this change in harvest management was a new responsibility for Colorado’s terrestrial biologists and wildlife managers. Prior to 1999, licenses were sold over-the-counter and were not limited in number (i.e., any hunter who wished to purchase one was able to do so), and the decision of how many licenses to make available did not need to be considered. Since 1999, CPW has the added responsibility of deciding how many licenses should be allocated in each Data Analysis Unit (DAU). This decision must reflect a balance between meeting DAU population performance objectives, but also provide as much hunter opportunity as possible. Big game populations in Colorado are currently modeled using multiple sources of biological data (White and Lubow 2002). Model inputs include harvest estimates, young recruitment to December, and measured rates of survival of adult females and fawns. Also, the ratio of adult males to adult females is estimated and used to align models by minimizing the difference between observed and modeled values. Only rarely have the survival rates of adult males been measured. This gap in knowledge has historically been viewed as trivial and adult male survival rates have been assumed to be similar to the rates of females. Similarly, it has been assumed that natural survival rates (i.e., post hunt survival) of 98 �males do not geographically vary. However, model performance under these assumptions has been poor and the need to measure adult male survival as a parameter has increased. Presently, a number of population models in Colorado suggest that natural adult male survival may be lower than adult female survival, yet empirical data is lacking to verify these suppositions. Despite this apparent lack of information, survival of adult male mule deer and adult male blacktail deer are not completely novel parameters of interest (Pac and White 2007, Bender et al. 2004b, Bleich et al. 2006, Bishop et al. 2005a, McCorquodale 1999). These studies also suggest that adult male mule deer survival tends to be lower than adult female survival when differences occur, further emphasizing the need to rigorously evaluate adult male survival rates. Bishop et al. (2005a) observed lower natural survival rates of adult males than adult females in southwest Idaho: differences were most apparent during winter in 2 of 3 study areas. Pac and White (2007) found that natural survival rates of yearling males in Montana were lower than the average adult female survival rate documented by Unsworth et al. (1999). Finally, Miller et al. (2008) found that adult male survival rates were lower than adult female survival rates in Colorado in response to chronic wasting disease (CWD). In particular to the population modeling interests of Colorado outside the CWD endemic area, the work conducted by Pac and White (2007) has had the greatest utility. This work focused on the survival of males under differing management scenarios and showed a shift in cause-specific mortality of males in areas where harvest was more restricted. It is currently unknown if survival rates would be similar between Montana and Colorado. Similarly, the likelihood of observing shifts in mortality sources is unknown. It has been demonstrated that adult female deer herds in Colorado tend to be habitat limited (Bishop et al. 2009, Bartmann et al. 1992), but the trade-off between harvest, habitat and survival in adult male mule deer has not been explored. An additional need in Colorado pertains to the harvest management of adult male mule deer. As discussed above, a large shift in mule deer herd size and structure occurred as a result of changes in harvest management. Overall, this shift has been viewed as positive by both CPW as well as the public. However, CPW maintains the responsibility of optimally managing the deer of Colorado and maximizing hunting opportunity under this new set of constraints. To date, CPW has had limited biological information and data to guide harvest management decisions. In particular for this issue, as Data Analysis Units (DAUs) reach and surpass their adult male: adult female ratio objectives, CPW typically responds by increasing the number of available hunting licenses. In situations where herds are continually lower than DAU objectives, available hunting licenses are reduced. What remains unknown about survival of adult male deer is at what level natural survival is reduced due to intraspecific competition (i.e., increased density of adult male deer). If, or when deer herds exceed the adult male: adult female objectives for DAUs, it is often assumed that the surplus of male deer remain in the population into perpetuity. However, this assumption is based on the premise that compensatory mortality does not occur. Similarly, it assumes that annual variation in survival is negligible. However, these assumptions are not biologically realistic. It is possible that herds with large post-hunt populations of adult males experience higher levels of non-harvest mortality. Under this scenario, harvest has not been optimized and more hunters could have been afforded the opportunity to hunt with no effect on post hunting season ratios of adult males to adult females. The most effective way to learn about the mortality process is via manipulative experimentation, but to date this topic has not been deemed a high enough priority to pursue. STUDY AREA This study is taking place in Middle Park, Colorado (see Appendix I for discussion of criteria for study area selection). Under the current management structure, Middle Park falls within DAU D-9. Within D-9 are 6 Game Management Units (27,181, 18, 37, 371, and 28; Fig. 1). Due to the geologic and topographical landscape in Middle Park, this area is conducive to splitting the DAU into experimental units (see Appendix I for experimental design). Additionally, from a management perspective, D-9 is 99 �currently managed for 35 adult males per 100 adult females. This ratio objective represents an average “quality” management objective in Colorado (i.e., DAUs with higher or lower objectives exist, thus data from D-9 will be the most universally applicable). Finally, the topography and landscape of Middle Park also makes it prone to periodic, harsh winters. This variability is fundamental to attaining reasonable estimates of process variation in adult male survival. METHODS Capture of adult male deer was initiated in January of 2011. Capture was conducted via helicopter net-gunning (Webb et al. 2008, Potvin and Breton 1988, White and Bartmann 1994, Barrett et al. 1982). All captures occurred after the completion of the 4th rifle hunting season, eliminating conflicts between capture efforts and hunting. Due to the need to generate survival estimates linked to animals of known age, all animals were handled by CPW personnel for aging purposes. Field aging of animals was done by visual inspection of tooth wear patterns (Severinghaus 1949, Robinette et al. 1957, Hamlin et al. 2000). Colorado Parks and Wildlife researchers/biologists were ferried to the general area in which capture was occurring and subsequently ferried the short distance to each capture location after individual animals were captured. Prior to release, all animals had their antlers removed via handsaw to minimize the potential risk of injury as the animal was released. All captures occurred after annual mule deer classification flights had been conducted, alleviating the potential for misclassification of antlerless males as females. All deer were fitted with expandable radio collars (see Appendix I for discussion of radio collar development). All radio collars were equipped with mortality sensors that doubled in pulse rate after remaining motionless for 4 hours. Between the time of capture and mid-June, we used ground based monitoring to determine the live/dead status of deer 3-4 times per week. Additionally, every 5-10 days we conducted a telemetry flight to hear any animals that hadn’t been heard from the ground during the preceding week. A general location was collected for each radio marked deer in early-March to determine if it had departed the GMU in which it had originally been captured. From mid-June through remainder of the summer, deer were monitored from the ground weekly and from the air once per month. When detected, all mortalities were investigated as quickly as possible to determine cause of death and to get an accurate estimate of the date of death. To help evaluate the effects of a changing sex ratio on hunter harvest, we are currently preparing to sample successful hunters to acquire an age of animals harvested in D-9. Ages will be estimated via the cementum aging process of incisors (Hamlin et al. 2000). When possible, a lower incisor was also collected from each radio collared deer that died in order to validate animal ages of captured animals. To acquire teeth for aging purposes, all hunters who have licenses to hunt in any GMU in D-9 will be contacted via mail. Each hunter will be provided with a sampling kit, a pre-posted return envelope and detailed directions on how to extract teeth for aging purposes. These data will help inform terrestrial biologists and wildlife managers if changes in the age of animals harvested occur as populations shift up or down in age structure as sex ratios are increased or decreased. RESULTS AND DISCUSSION In January, 100 deer were captured, aged, weighed, radio collared and released during a 3½ day period. On one occasion, the skull plate of an animal was fractured immediately anterior to the animal’s antler pedestals while being captured. This animal was immediately euthanized via gunshot to the head. No other capture related injuries or mortalities occurred. With the exception of animals falling in the 2 youngest age classes (1½ years old (yearlings) and 2½ years old), the age distribution of captured animals followed the expected age distribution of the 100 �population (Fig. 2). In the case of the 2 youngest age classes, we captured more 2½ year old animals than yearlings. We believe this result was primarily due to misidentification of yearlings as part of the capture process. Small yearlings and particularly those with small antler morphometry had a greater probability of being skipped by the capture crew as they flew over groups of deer. In future years we will make a more concerted effort to increase the number of yearlings in the sample. The mass of adult male deer ranged between 52.3 kg and 106.8 kg, with the average mass being 82.2 kg (Fig. 3). Observationally, the largest animals appeared to be captured in areas in close proximity to irrigated agricultural fields. Survival of adult male deer between the time of capture and the end of July was high. Combined survival for the northern and southern halves of D-9 was 0.879 (SE = 0.0326). When separated, the survival rates for the northern and southern halves of D-9, for the same time period, were 0.858 (SE = 0.0495) and 0.900 (SE = 0.0495). Of the 12 mortalities that occurred, a suite of causes were observed. Six mortalities were attributed to predation (4 coyote, 2 mountain lion), 1 was attributed to starvation, 1 to disease (conjunctivitis that blinded the animal), and 2 were attributed to vehicular collisions (1 automobile and 1 train). The cause of mortality could not be determined for 2 deer. Survival patterns during the winter months during the first year did not demonstrate dramatic swings or mortality pulses during which several animals died. Rather, mortalities tended to occur at a relatively constant interval of approximately 2-3 mortalities per month. However, with the exception of the animal killed by a train, mortalities during the summer months (June and July) were not observed. SUMMARY Project efforts were successful during the first year of the study. Capture and handling of animals was efficient, cost effective and mortality/injury rates were low. The survival rate of adult male mule deer was high. Baseline data collection will continue for 2 additional winters before implementation of the harvest management experiment. LITERATURE CITED Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M., G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1-39. Bender, L.C., J.C. Lewis and D.P. Anderson. 2004a. Population ecology of Columbian black-tailed deer in Urban Vancouver, Washington. Northwestern Naturalist 85:53-59. Bender,L.C., G.A. Schirato, R.D. Spencer, K.R. McAllister, and B.L. Murphie. 2004b. Survival, causespecific mortality, and harvesting of male black-tailed deer in Washington. Journal of Wildlife Management 68:870-878. Bergman, E.J., B.E. Watkins, C.J. Bishop, P.M. Lukacs, and M. Lloyd. 2010. Biological and socioeconomic effects of statewide limitation of deer licenses in Colorado. Journal of Wildlife Management. In Review. Bishop, C.J., J.W. Unsworth and E.O. Garton. 2005a. Mule deer survival among adjacent populations in southwest Idaho. Journal of Wildlife Management 69:311-321. Bishop, C.J., G.C. White, D.J. Freddy and B.E. Watkins. 2005b. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin 33:662-668. Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins, and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1-28. Bleich, V.C., B.M. Pierce, J.L. Jones and R.T. Bowyer. 2006. Variance in survival of young mule deer in the Sierra Nevada, California. California Fish and Game. 92:24-38. 101 �Hamlin, K.L., D.F. Pac, C.A. Sime, R.M. DeSimone, and G.L. Dusek. 2000. Evaluating the accuracy of ages obtained by two methods for Montana ungulates. Journal of Wildlife Management. 64:441449. Miller, M.W., H.M. Swanson, L.L. Wolfe, F.G. Quatarone, S.L. Huwer, C.H. Southwick and P.M. Lukacs. 2008. Lions and prions and deer demise. Plos One 3:1-7. McCorquodale, S.M. 1999. Movements, survival, and mortality of black-tailed deer in the Klickitat Basin of Washington. Journal of Wildlife Management 63:861-871. Pac, D.F., and G.C. White. 2007. Survival and cause-specific mortality of male mule deer under different hunting regulations in the Bridger Mountains, Montana. Journal of Wildlife Management 71:816-827. Potvin, F., and L. Breton. 1988. Use of a net gun for capturing white-tailed deer, Odocoileusvirginianus, on Anticosti Island, Quebec. Canadian Field Naturalist 102:697-700. Robinette, W.L., J.S. Gashwiler, D.A. Jones, and H.S. Crane. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134-153. Severinghaus, C.W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195-216. Underwood, A.J. 1994. On beyond BACI-sampling designs that might reliably detect environmental disturbances. Ecological Applications. 4:3-15. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann. 1999. Mule Deer Survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Webb, S.L., J.S. Lewis, D.G. Wewitt, M.W. Hellickson, and F.C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310-314. White, G.C. and R.M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. White, G.C. and B.C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. Prepared by Eric J. Bergman, Wildlife Researcher 102 �Figure 1. Data Analysis Unit 9 (D-9) encompasses the Middle Park area of central Colorado. D-9 includes 6 Game Management Units (27, 181 and 18 on the northern half and 37, 371 and 28 on the southern). Current management sex ratio management objectives for D-9 are consistent across GMUs with an overall post hunt objective of 35 adult males per 100 adult females. 103 �Figure 2. Frequency of ages of 100 adult male mule deer captured in January (2011) in Middle Park, Colorado. Future capture efforts will be made to increase the frequency of 1½ year old males to accommodate for an expected underrepresentation in the current sample as well as for aging of radio collared animals throughout the study. Figure 3. Frequency of masses of 100 adult male mule deer captured in January (2011) in Middle Park, Colorado. Ages of deer captured ranged between 1½ years old and in excess of 9½ years old. 104 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2010-11 – FY 2015-16 State of: Cost Center: Work Package: Task No. Federal Aid Project No. Colorado 3430 3001 : : : : : Division of Wildlife Mammals Research Deer Conservation Assessment of Survival and Optimal Harvest Strategies of Adult Male Mule Deer in Middle Park, Colorado. W-185-R Assessment of Survival and Optimal Harvest Strategies of Adult Male Mule Deer in Middle Park, Colorado Principal Investigators Eric J. Bergman, Mammals Researcher, Colorado Parks and Wildlife Chad J. Bishop, Mammals Researcher Leader, Colorado Parks and Wildlife Kirk Oldham, Terrestrial Biologist, Colorado Parks and Wildlife Lyle Sidener, Area Wildlife Manager, Colorado Parks and Wildlife Cooperators Andy Holland, Big Game Coordinator, Colorado Parks and Wildlife John Broderick, Terrestrial Management Leader, Colorado Parks and Wildlife Area 9 Personnel, Colorado Parks and Wildlife STUDY PLAN APPROVAL Prepared by: Eric J. Bergman Date: Nov. 2010 Submitted by: Eric J. Bergman Date: Nov. 2010 Reviewed by: Chuck Anderson Date: Nov. 2010 Mike Phillips Date: Biometrician: Paul Lukacs Date: Nov. 2010 Approved by: Chad Bishop Mammals Research Leader Date: Nov. 2010 105 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH ASSESSMENT OF SURVIVAL AND OPTIMAL HARVEST STRATEGIES OF ADULT MALE MULE DEER IN MIDDLE PARK, COLORADO A Study Plan Proposal Submitted by: Eric J. Bergman, Mammals Researcher, Colorado Parks and Wildlife Chad J. Bishop, Mammals Research Leader, Colorado Parks and Wildlife Kirk Oldham, Terrestrial Biologist, Colorado Parks and Wildlife Lyle Sidener, Area Wildlife Manager, Colorado Parks and Wildlife Andy Holland, Big Game Coordinator, Colorado Parks and Wildlife John Broderick, Terrestrial Management Leader, Colorado Parks and Wildlife A. Need Historically, management of big game species has focused on the performance of the female and the young of the year components of the population. In the case of mule deer, this has been further refined to the aspects of annual (for adult females) and overwinter (for young of the year) survival. The performance of the male component of populations was deemed less important, primarily due to the fact that it takes relatively few males to provide adequate breeding potential for the population. Additionally, historic harvest management objectives were set to maximize hunting opportunities. Thus, as long as sufficient numbers of males were available to breed females there was no desire to restrict hunting opportunity. However, during the past 10-15 years, the management of big game populations, and mule deer populations in particular, has started to shift away from the objective of providing maximal opportunity towards providing fewer but higher quality opportunities (Bishop et al. 2005b, Bergman et al. 2010). High quality opportunities are typically defined by hunters as a combination of the chance to see a greater number of male deer during the hunt, and the potential to harvest an older age class animal (i.e., an animal with more developed antler morphometry), but also reduced interaction and competition with other hunters. In response to this shift in hunter desires and concerns over declining mule deer numbers, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) implemented a statewide limitation in deer hunting in 1999. This statewide limitation gave CPW the ability to greatly reduce total hunter numbers but also the ability to control the distribution of hunters throughout the state. Since 1999, a few marked changes in Colorado’s deer herd have occurred. First, due to reduced harvest an overall increase in deer numbers has been observed (Fig. 1). Second, because the reduction in harvest was primarily focused on adult males, a subsequent increase in the ratio of adult males to adult females has resulted (Fig. 2) (Bergman et al. 2010). Stemming from this shift in harvest management and the subsequent changes in herd size and structure, a gap in biological information has been identified. Specifically, Colorado’s deer herds have become composed of a greater number of males, yet little biological data on them exist. Also stemming from this change in harvest management was a new responsibility for Colorado’s terrestrial biologists and wildlife managers. Prior to 1999, licenses were sold over-the-counter and were not limited in number (i.e., any hunter who wished to purchase one was able to do so), and the decision of how many licenses to make available did not need to be considered. Since 1999, CPW has the added responsibility of deciding how many licenses should be allocated in each Data Analysis Unit (DAU). This decision must further reflect a balance between meeting DAU population performance objectives, but also provide as much hunter opportunity as possible. 106 �Figure 1. Colorado’s statewide deer herd estimate covering the past 2+ decades. Between 1998 and 1999 CPW implemented a statewide limitation process on the number of deer licenses sold. Since that time, a marked reversal in population trajectory has occurred, largely due to the increase in survival of adult males from reduced hunting license allocation. Figure 2. Estimates of adult male: adult female ratios, collected via aerial survey, in the DAUs in western Colorado during the past three decades. Of note, between 1998 and 1999, CPW implemented a statewide limitation on the number of deer hunting licenses sold. The harvest management action brought about a marked increase in estimates of the ratio of adult males to adult females. 107 �Big game populations in Colorado are currently modeled using multiple sources of biological data (White and Lubow 2002). Model inputs include harvest, young recruitment to December, and measured rates of survival of adult females and fawns. Also, the ratio of adult males to adult females is estimated and used to align models by minimizing the difference between observed and modeled values. Very rarely have the survival rates of adult males been measured. This gap in knowledge has historically been viewed as trivial and rates have been assumed to be similar to the rates of females. Similarly, it has been assumed that natural survival rates (i.e., post hunt survival) of males do not geographically vary. However, model performance under these assumptions has been poor and the need to measure adult male survival as a parameter has increased. Presently, a number of population models in Colorado suggest that natural adult male survival may be lower than adult female survival, yet empirical data is lacking to verify these suppositions. Despite this apparent lack of information, survival of adult male mule deer and adult male blacktail deer are not completely novel parameters of interest (Pac and White 2007, Bender et al. 2004b, Bleich et al. 2006, Bishop et al. 2005a, McCorquodale 1999). However, rates of adult male survival reported in the literature are often linked to unique management situations such as variation in harvest structure (Pac and White 2007, Bender et al. 2004b), urban settings (Miller et al. 2008, Bender et al. 2004a) or disease management scenarios (Conner and Miller 2004, Miller et al. 2008). Similarly, most of these studies have been constrained by relatively small sample sizes and were of short duration, making the estimation of the process variation of adult male survival unreliable. However, available data suggest that adult male mule deer survival tends to be lower than adult female survival when differences occur, further emphasizing the need to rigorously evaluate adult male survival rates. Bishop et al. (2005a) observed lower natural survival rates of adult males than adult females in southwest Idaho: differences were most apparent during winter in 2 of 3 study areas. Pac and White (2007) found that natural survival rates of yearling males in Montana were lower than the average adult female survival rate documented by Unsworth et al. (1999). Finally, Miller et al. (2008) found that adult male survival rates were lower than adult female survival rates in Colorado in response to chronic wasting disease (CWD). In particular to the population modeling interests of Colorado outside the CWD endemic area, the work conducted by Pac and White (2007) has had the greatest utility. This work focused on the survival of males under differing management objectives and showed a shift in cause-specific mortality of males in areas where harvest was more restricted. It is currently unknown if survival rates would be similar between Montana and Colorado. Similarly, the likelihood of observing shifts in mortality sources is unknown. It has been demonstrated that adult female deer herds in Colorado tend to be habitat limited (Bishop et al. 2009, Bartmann et al. 1992), but the trade-off between harvest, habitat and survival in adult male mule deer has not been explored. A different, but not unrelated need in Colorado pertains to the harvest management of adult male mule deer. As discussed above, a large shift in mule deer herd size and structure occurred as a result of the change in harvest management. Overall, this shift has been viewed as positive by both CPW as well as the public. However, CPW still maintains the responsibility of optimally managing the deer of Colorado and maximizing hunting opportunity under this new set of constraints. To date, CPW has had limited biological information and data to guide harvest management decisions. In particular for this issue, as DAUs reach and surpass their adult male: adult female ratio objectives, CPW typically responds by increasing the number of available hunting licenses. In situations where herds are continually lower than DAU objectives, available hunting licenses are reduced. What remains unknown about survival of adult male deer is at what level natural survival is reduced due to intraspecific competition (i.e., increased density of adult male deer). If, or when deer herds exceed the adult male: adult female objectives for DAUs, it is often assumed that the surplus of male deer will remain in the population into perpetuity. However, this assumption is based on the premise that compensatory mortality does not occur. Similarly, it assumes that annual variation in survival is negligible. However, this is biologically not realistic. It is very likely that herds with large post-hunt populations of adult males experience higher levels of 108 �mortality. Under this scenario, harvest has not been optimized and more hunters could have been afforded the opportunity to hunt with no effect on post hunting season ratios of adult males to adult females. The most effective way to learn about the mortality process is via manipulative experimentation, but to date this topic has not been deemed a high enough priority to pursue. B. Objectives Our study objective is two-fold. First, we wish to assess annual survival of adult male mule deer. We wish to establish baseline survival and variance estimates for different age classes of deer. Second, we wish to manipulate hunting license allocation within the Game Management Units (GMUs) of D-9 such that adult male: adult female ratios become measurably different between the northern and southern halves of the DAU. Accordingly, we wish to measure and correlate changes in natural survival of adult male deer with this management action. Similarly, as part of this second objective, we will determine if changes in the age structure of harvested animals occur as the sex ratio and age structure of the hunted population changes. While not a direct objective of the study, we will also be able to learn if increasing adult male: adult female ratios causes an increase in the emigration rate of animals from populations composed of a greater proportion of adult male deer. C. Expected Results or Benefits Data and information generated from this study will have immediate use to terrestrial biologists and wildlife managers across the state of Colorado. Survival estimates of adult male deer will be immediately incorporated in the annual population modeling process. As measurements are repeated over years, estimates of process variation will be generated, allowing a refinement of how adult male survival is incorporated into the modeling process. From a general ecology perspective, we will measure the direct and indirect effects of a concerted management action on the male component of the deer population. We expect to detect differences in the harvest rates of radio-collared deer under different hunter/license allocation strategies. We also expect to detect differences in the harvest rate of radio collared deer based on age and antler morphometry. Similarly, we expect to detect a difference in natural survival/mortality rates of deer under differing levels of harvest. Ultimately this will provide information about the additive/compensatory relationship of adult male deer, adult female deer and mule deer fawn survival in Colorado. This information will allow us to directly inform tradeoff decisions between hunting opportunity and hunter desires for various quality standards. Additionally, these data will allow us to identify thresholds where further license restrictions would fail to result in more adult males in the population and fail to increase the mean age or antler structure of males harvested. D. Approach 1. Radio Collar Development Radio collars deployed as part of this project will be permanent (i.e., they will not be fitted with any sort of release mechanism). However, utilizing traditional radio collars with a fixed diameter is not ideal due to the seasonal variation in the size of adult male mule deer necks; as adult male deer enter the breeding period, neck swelling occurs. Researchers have historically addressed this issue with several different approaches. The use of loosely-fitted, fixed diameter radio collars has occurred on several hundred white-tailed deer in Texas with no known incidence of mortality or injury (K. VerCauteren – personal communication). It is unknown if a similar result could be expected for mule deer in Colorado. Researchers in Montana used an expandable radio collar that was made of tubular aircraft grade bungee material to measure survival of 136 adult male mule deer (Pac and White 2007, D. Pac – personal communication). When this research was conducted, expandable radio collars were not commercially 109 �available, so the expansion design was developed and installed on a traditional VHF collar that was produced by Telonics, Inc (Mesa, AZ, USA). This radio collar design alleviated concerns over neck constriction during the breeding period and it sufficiently contracted as neck swelling reduced after the breeding period. However, in a few instances (1%-2% of radio collared population) it was documented that deer were able to get a front hoof/leg between the collar and neck (D. Pac – personal communication). On these occasions, deer were either recaptured or euthanized if recapture was not possible. Researchers in Idaho as well as Colorado used a different expandable collar design, fitted with an expansion device that was made of flat elastic encased in Cordura™ to measure survival of 70 (Idaho) and ~100 (Colorado) adult male mule deer, respectively (Bishop et al. 2005a, Conner and Miller 2004). This collar was also made by Telonics, Inc. This design also alleviated constriction around the neck as deer entered the breeding period, but the contraction properties of the elastic were such that as neck diameter reduced as deer exited the breeding period the collar did not adequately contract to the prebreeding period diameter. This was not ideal as loosely fitting collars had a propensity to slide on the necks of animals and to cause hair loss. Additionally, researchers had concerns over the potential for deer to get hooves caught between the collars and their necks. This event occurred on one occasion with a fawn during the Idaho study (subsequently resulting in the animal’s mortality) and on two occasions in Colorado (both animals were recaptured and collars were removed during the Colorado study). To address the issue of expansion collars failing to contract back to pre-breeding period diameters, a third generation expansion collar was developed by CPW (M. Sirochman – personal communication). This new design incorporated nylon sleeved springs as the expansion device. As was the case in Montana, the spring based expansion collar adequately expanded and contracted through the initial breeding periods. However, on a few occasions the springs in these collars did eventually expand beyond their critical limit and ultimately failed to contract after having been deployed. On these occasions, it appeared that springs had snagged on external features, thereby reducing the integrity of the spring itself. Outside of these external factors, resilience of the spring appeared to be sound. The occurrence of deer getting their hooves caught between the collars and their necks was also documented in this study, but due to the tractability of animals, all were recaptured and radio collars were safely removed (M. Sirochman – personal communication). One additional downfall of the spring based expansion collar was that irritation caused by the pressure of the springs on the dorsal portion of the neck was documented in a few cases. While the irritation did not appear to jeopardize the health of the animal, it was undesirable. For our study, what can be considered a fourth generation expandable radio collar has been designed in collaboration with Advanced Telemetry Systems, Inc. (Isanti, MN, USA) (Figs. 3a and 3b). This newly designed collar closely resembles the earlier generation collars that incorporated flat elastic material. The elastic based expansion collar had fairly high success because only on a single occasion was it documented that a deer had its hoof caught between the collar and its neck. The primary weakness of this design was that the contraction properties of the elastic expansion material were inadequate. This new design incorporates a more robust, high quality, flat bungee material that is sheathed between traditional nylon belting material on the outside and nylon webbing on the inside (Fig. 3b). Due to the sheathing design, only a small portion of the bungee material is exposed, reflecting the desired qualities of the elastic based expansion collar and retaining the reduced potential for deer to get hooves caught in the collar. The higher quality bungee is expected to maintain contraction properties far longer than elastic and thus the potential for loose fitting collars during the later years of the study is reduced, minimizing the opportunity for hair breakage. This new collar design was scrutinized by the researchers who represent the bulk of knowledge on the subject of radio collaring adult male mule deer (D. Pac - retired, MT Fish, Wildlife and Parks; C. Bishop, M. Miller, M. Sirochman and L. Wolfe, CPW). The only additional concern pertained to the orientation and potential wear/irritation of the collar on the dorsal portion of deer necks during the breeding period. However, due to the width of the bungee material, it is expected to be less than that of the spring based expansion design. Concern over the orientation of the collar will be addressed by testing the collar design on a captive animal at CPW wildlife health research facility. 110 �Figure 3a. Figure 3b. Figures 3a and 3b. The newly designed, expandable, VHF radio-collar that will be utilized on adult male mule deer during this study. Collars were designed to meet CPW specifications by Advanced Telemetry Systems, INC. (Isanti, MN, USA). The blue banding material seen in figures 3a and 3b is nylon coated bungee that will allow expansion and contraction, as needed, during the breeding period. To allow 111 �maximal expansion, but to help prevent the opportunity for deer to get hooves and legs caught between the neck and collar, the bungee material is sleeved in nylon webbing (red material visible in figure 3a). 2. Capture Capture of adult male deer for this project will be conducted via helicopter net-gunning (Webb et al. 2008, Potvin and Breton 1988, White and Bartmann 1994, Barrett et al. 1982). All captures will occur after the completion of the 4th rifle hunting season, eliminating potential conflicts between capture efforts and hunting. Typically capture will occur between mid-December and mid-January. Exact timing of capture each year will be dependent on availability of the helicopter net-gunning crew. Due to the need to have survival estimates linked to animals of known age, all animals will be handled by CPW personnel for aging purposes. Depending on situation, captured animals will be handled in one of two ways. When feasible, captured deer will be ferried to a processing area staffed by CPW researchers/biologists who are qualified to age animals according to tooth wear (Severinghaus 1949, Robinette et al. 1957, Hamlin et al. 2000). Deer will subsequently be returned to the capture site for release. In situations when capture locations are too far from processing areas to efficiently ferry animals, CPW researchers/biologists will be ferried to the general area in which capture is occurring and subsequently be ferried the short distance to each capture location to process animals at that site. Regardless of situation, it is possible that a single person will be responsible for collaring, aging and releasing animals. As such, prior to release, all animals will have their antlers removed via handsaw to minimize the potential risk of injury as the animal is released. The removal of antlers from animals at this time of year should have no negative impact on survival as all captures will occur post-rut. Similarly, all legal harvest of animals will have occurred and negative response of hunters should not occur. The only exception to the antler removal process will be if post-hunt sex/age class survey flights have not yet occurred and if the captured animal is located near a survey quadrat. If a deer is captured near a survey quadrat, prior to deer classification flights having been conducted and it is still deemed necessary to remove antlers, these deer will be temporarily marked with livestock marking paint on the back and neck. Marking deer in such a manner will allow biologists to accurately classify those individual deer as adult males, thereby removing any potential bias that may stem from capturing deer prior to classification flights. Whenever possible, capture will be conducted after classification flights to alleviate this problem. All deer will be fitted with expandable radio collars (discussed above). All radio collars will be equipped with mortality sensors which will double in pulse rate after remaining motionless for 4 hours. The desired sample size for each year of this study will be a total of 220 adult ( ≥ 1.5 years old) male deer. One hundred deer will be captured and radio collared during the first year of the study as a pilot assessment of the radio collar design and to test underlying assumptions about deer movement (discussed below). During the second year of the study, 120 additional deer, as well replacements for any deer that die during the first year will be captured and radio collared. Thus, not until the second winter of the study will the full sample size be achieved. For every year thereafter, only enough deer to maintain the 220 animal sample size will be captured. The 220 deer sample will be distributed such that 110 of the radio collared deer are located in the northern half and 110 are located in the southern half of the DAU. 3. Survival/Location Monitoring The primary objective of this study is to generate annual natural survival estimates and harvest rates for adult male deer. While most mortality is expected to occur via rifle harvest between October and November, the bulk of natural mortality is expected to occur between December and May of each year. In order to minimize bias of survival estimates during these periods, we will attempt to monitor the live/dead status of each animal 3-4 times per week. Each year, prior to the start of the archery hunting season, all deer will be located to asses in which half (northern versus southern) of the DAU each animal is located. A similar set of locations will be collected after the 4th rifle hunting season. Between each hunting season, a live/dead flight will be conducted to determine if any animals have disappeared, and subsequently assumed to have been harvested, without having been reported to CPW. Once all hunting 112 �seasons have been completed, we will revert to a weekly flight schedule to assess live/dead status of all animals. A field technician will check live/dead status 2-3 times for each animal between flights. All animals will be located 1 additional time during the winter to confirm that animals have not left the DAU and to determine if any animals have switched between the northern and southern halves of the DAU. Based on historical location data for adult female and fawn mule deer, approximately 10% of deer are expected to cross between northern and southern halves of the DAU (K. Oldham – unpublished data). Any animals switching between halves of the DAU will be censored from the optimal harvest management portion of the analysis. During periods when survival is expected to be higher and less dynamic (June through September), the level of effort of to determine live/dead status will be reduced. Flights to determine live/dead status will occur approximately every 14 days and efforts to hear animals from the ground will occur as time allows. A single location will be collected for each animal after it has arrived on summer range (between late-June and late-July). While not ideal, weekly survival estimates for summer months can be computed from bi-monthly estimates via the delta method (Powell 2007). This approach to survival monitoring will allow us to minimize bias but also minimize costs associated with aircraft and temporary personnel. 4. Harvest Management Experiment We will implement a management experiment to evaluate adult male survival rates under different harvest management strategies. Hunting management in Colorado is partitioned into DAUs. The boundaries of DAUs are intended to reflect the biological boundaries of deer such that deer movement between DAUs is non-existent or infrequent enough to be biologically insignificant. Within DAUs are GMUs. GMU boundaries tend to be highly permeable to deer, but serve to partition DAUs for human oriented management purposes such as survey work and hunter distribution. Typically all GMUs within a DAU have the same management objective. However, this study will deviate from this trend by establishing two different harvest objectives within a single DAU. This approach will help ensure that all deer in the study will experience similar environmental conditions and limiting factors except for different harvest objectives. Thus, any survival differences we observe are likely to be a result of differential harvest as opposed to some other factor. This study will take place in Middle Park, Colorado (see below for rationale). Under the current management structure, Middle Park falls within DAU D-9. Within D-9 are 6 GMUs (27,181, 18, 37, 371, and 28; Fig. 4). D-9 is managed for an adult male: adult female ratio of 35 adult males per 100 adult females. As part of this study, the management of D-9 will be temporarily altered such that it will be viewed as two separate populations (one population will be composed of the northern 3 GMUs (27, 181 and 18) and the other population will be the southern 3 GMUs (37, 371 and 28)). During the 4th-7th years of this study we will redistribute hunters within the DAU via hunting license allocation. During the 1st-3rd years of the study we will monitor survival across the DAU to provide baseline data (Fig. 5). The objective behind the redistribution of hunters will be to increase adult male: adult female ratios in one half of D-9 and to decrease adult male: adult female ratios in the other half of D-9. The current DAU objective of 35 adult males: 100 adult females will not change, but one half of the DAU will be managed for 25 adult males: 100 adult females and the other half will be managed for 45 adult males: 100 adult females. The determination of which half of D-9 will experience higher harvest and which half will experience lower harvest has not yet been made. This decision will ultimately be made by Area 9 and Northwest Region personnel. In the event that there are no overwhelming management concerns about this selection process, the selection will be random. 5. Age at Harvest To help evaluate the effects of a changing sex ratio on hunter harvest, we will attempt to acquire an age for animals harvested in D-9 for years 2-7 of the study. Ages will be estimated via the cementum 113 �aging process of incisors (Hamlin et al. 2000). To acquire teeth for aging purposes, all hunters who have licenses to hunt in any GMU in D-9 will be contacted prior to the archery season via mail. Each hunter will be provided with a sampling kit, a pre-posted return envelope and detailed directions on how to extract teeth for aging purposes. These data will help inform terrestrial biologists and wildlife managers if changes in the age of animals harvested occur as populations shift up or down in age structure as sex ratios are increased or decreased. Figure 4. Data Analysis Unit 9 (D-9) encompasses the Middle Park area of central Colorado. D-9 includes 6 Game Management Units (27, 181 and 18 on the northern half and 37, 371 and 28 on the southern). Current management sex ratio management objectives for D-9 are consistent across GMUs with an overall post hunt objective of 35 adult males per 100 adult females. 6. Data Analysis This study can be structured as a multi-state study (Fig. 6). We are primarily interested in deer that exist in three different states: 1) deer that survive, 2) deer that are harvested, and 3) deer that die due to non-harvest causes. While most multi-state studies include survival, detection and transition probabilities for different states, this study is purely focused on the transition probability of deer that transition from the living state to either one of the two non-living states, or back into the living state. Due to the relatively safe assumptions that deer will not leave study area, that use of radio-telemetry is essentially always detectable and the fates of deer can be readily identified, detection probabilities can be fixed at 1.0 and survival can be artificially set at 1.0. Thus, the transition probabilities between states 114 �becomes a surrogate for survival, thereby allowing us to distinguish and easily measure differences between causes of mortality. Figure 5. For this study, the northern and southern halves of D-9 will managed under different harvest management objectives during years 3-7. One half will be managed under less restrictive objectives, with a post hunt sex ratio objective of 25 adult males per 100 adult females. The other half of the DAU will be managed under more restrictive conditions with a post hunt sex ratio objective of 45 adult males per 100 adult females. For this study, we will have numerous response variables of interest. The basic analysis of this study will follow a before-after-control-impact (BACI) design (Green 1979, Hurlbert 1984, Underwood 1994 and Conner et al. 2007) (Fig. 7). Overall, survival of adult male deer will be analyzed using known-fate models in program MARK (White and Burnham 1999). Survival will be modeled using age of deer, GMU/DAU, year and trophy score. For the purposes of this study, we are primarily interested in weekly survival rates throughout the year. Cause specific mortality will be analyzed under a multi-state modeling framework in which detection probabilities will be fixed to 1.0 based on the known-fate properties of the data for the BACI analysis. We will use mixed models to assess the impact of manipulating harvest management. For the mixed model analyses, we will use adult male: adult female ratio as the response variable for one analysis and hunter success as the response variable in a second analysis. 115 �Figure 6. Assessment of survival and mortality causes can be conceptualized as a multi-state analysis with transition rates from the surviving state to the harvest state or the non-harvest related mortality state being the parameters of interest. In this case, transitions represented by black arrows can be estimated via radio collared deer. Transitions represented by gray arrows are not biologically feasible. Deer that are harvested cannot return to the survival state, nor can they enter the non-harvest related mortality. Similarly, deer dying to non-harvest related causes cannot simultaneously survive or be harvested. Under this multi-state framework, all other parameters of interest will be fixed at 1.0. 7. Sample Size Sample size estimates for this study are based on the desire to detect a difference in the nonharvest mortality rates of deer under different harvest management regimes. Best estimates of harvest mortality rates, natural survival rates and the associated variance of each were based on the work published by Pac and White (2007). For our power calculations, baseline/ control harvest rates were set at 0.21 and the associated natural survival was 0.72. For high harvest areas, we set harvest at 0.37 and the associated natural survival at 0.77. For low harvest areas, we set harvest at 0.06 and subsequent natural survival at 0.67. Thus, our power calculation was set up to detect a 10% difference in natural survival under different harvest management regimes. For sample size estimation we chose to fix the number of radio collared deer entering the study each winter at ~200 (~100 animals per area) and then used simulation models to determine the number of releases (i.e., number of winters in the study) that would be needed to detect our desired effect size. Simulations were set up to test the differences in natural survival by comparing survival rates as beta offsets from the expected survival rates under normal conditions (Fig. 8). 116 �Figure 7. The Before-After-Control-Impact design for this study is based on 6 years of a full sample of deer, with an initial build up year to help offset logistic and financial constraints associated with capturing 220 deer for the full sample (110/area). The control period will experience no change to harvest management, whereas the impact period with experience a concerted effort to redistribute hunters across the DAU to impact post hunt sex ratios. Based on these initial conditions, it appears that 6 winters with a full sample of deer will be needed to reliable detect a 10% difference in natural survival rates. Due to the estimated censoring of 10% of the radio-collared deer, due to movement between the northern and southern halves of the study area, we will inflate the total sample size from 100 animals per area to 110 animals for years 2-7 of the study. Duration of the study was determined by comparison of 95% confidence intervals surrounding the expected difference in natural survival (Fig. 9). Confidence intervals that included 0 were indicative of not enough statistical power to detect a difference. While 5 years may adequately meet the needs of the study, our results indicate that 6 years with a full sample of deer will be substantially more robust. E. Location This work will be conducted in Middle Park, Colorado. Middle Park was selected for this work based on several criteria. First, Middle Park is one of CPW’s mule deer winter survival monitoring areas and has ongoing monitoring of the survival of adult females and fawns. Adding estimates of adult male survival in this area will allow us to compute correlation and covariance between the different sexes through time. Similarly, in the event that changing adult male: adult female ratios affects survival of adult females or fawns, we will have all relevant sex and age classes marked and should be able to detect any changes. Additionally, geological and topographical structure of Middle Park is conducive to splitting the DAU into halves such that few deer migrate from one half to the other during the annual movement cycle. Existing data indicate that 10%-15% of deer cross between halves. As such, the number of deer needing to be censored from the management experiment portion of this study should be minimized. 117 �Figure 8. Non-harvest survival will be analyzed using the log scale comparison of beta estimates. The control period will be the baseline survival estimate (ß0) to which natural survival under differing harvest management efforts will be compared (solid black line). Non-harvest related survival in restrictive harvest units (ß1) is expected to be lower than estimates for both the control phase and more liberal harvest units (long dashed line). Non-harvest related survival in liberal harvest units (ß2) is expected to be higher than estimates for both the control phase and more conservative harvest units (short dashed line). Figure 9. Power calculation set up to determine the number of years necessary to detect a 10% difference in non-harvest related moratality rates under differing harvest management regimes. Solid lines depict 95% confidence intervals. Adequate power is achieved once 95% confidence interval estimates do not include 0. While statistical power may be adequate after 5 years, addition of a 6th year will make the study more robust to violations or deviations from the underlying parameter estimates used to structure the analysis. 118 �From a management perspective, D-9 is currently managed for 35 adult males per 100 adult females. The management experiment portion of this study will allow the DAU to be split with half of the DAU being managed for 25 adult males per 100 females and the other half being managed for 45 adult males per 100 females. These ratios are largely representative of objectives throughout the state (i.e., management is not purely trophy or opportunity driven) and should allow adequate inference to be drawn. By not altering the overall DAU population objectives, implementing this research will not require that the D-9 management plan be rewritten. Additionally, Middle Park has historically been prone to periodic, harsh winters which are fundamental to getting reasonable estimates of process variation. Lastly, Middle Park has also been the site of numerous deer research and concerted management efforts over the past several decades. Knowledge and information from these past efforts have greatly facilitated the design of this study and historical data are readily available should refinement of study design or objectives become necessary. F. Schedule Of Work Activity Date Design and Purchase Expandable Radio Collars June 2010−Nov 2010 Purchase Field Supplies June 2010−Nov 2010 Capture ½ of initial sample of deer Dec 2010-Jan 2011 Monitor Survival and Movement of Deer Dec 2010−June 2017 Capture remaining sample of deer Dec 2011−Jan 2012 Capture deer to bring sample back to full size Dec 2012−Jan 2013 Implement change in hunter distribution within DAU Feb 2013-Feb 2016 Capture deer to bring sample back to full size Dec 2013−Jan 2014 Capture deer to bring sample back to full size Dec 2014−Jan 2015 Capture deer to bring sample back to full size Dec 2015−Jan 2016 G. Estimated Costs Category Item or Position FY 10-11 Personnel Eric Bergman 0.25 PFTE Chad Bishop 0.25 PFTE Kirk Oldham 0.05 PFTE Lyle Sidener 0.00 PFTE Field Equipment and Capture $100,000 Operating 119 �H. Related Federal Projects Our research will be conducted on federal (i.e., BLM, USFS) and state lands. The study does not involve formal collaboration with any federal agencies, nor does the work duplicate any ongoing federal projects. I. Literature Cited Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M., G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1-39. Bender, L.C., J.C. Lewis and D.P. Anderson. 2004a. Population ecology of Columbian black-tailed deer in Urban Vancouver, Washington. Northwestern Naturalist 85:53-59. Bender,L.C., G.A. Schirato, R.D. Spencer, K.R. McAllister, and B.L. Murphie. 2004b. Survival, causespecific mortality, and harvesting of male black-tailed deer in Washington. Journal of Wildlife Management 68:870-878. Bergman, E.J., B.E. Watkins, C.J. Bishop, P.M. Lukacs, and M. Lloyd. 2010. Biological and socioeconomic effects of statewide limitation of deer licenses in Colorado. Journal of Wildlife Management. In Review. Bishop, C.J., J.W. Unsworth and E.O. Garton. 2005a. Mule deer survival among adjacent populations in southwest Idaho. Journal of Wildlife Management 69:311-321. Bishop, C.J., G.C. White, D.J. Freddy and B.E. Watkins. 2005b. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin 33:662-668. Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins, and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1-28. Bleich, V.C., B.M. Pierce, J.L. Jones and R.T. Bowyer. 2006. Variance in survival of young mule deer in the Sierra Nevada, California. California Fish and Game. 92:24-38. Conner, M.M., and M.W. Miller. 2004. Movement patterns and spatial epidemiology of a prion disease in mule deer population units. Ecological Applications 14:1870-1881. Conner, M.M., M.W. Miller, M.R. Ebinger and K.P. Burnham. 2007. A meta-BACI approach for evaluating management intervention on chronic wasting disease in mule deer. Ecological Applications 17:140-153. Green, R.H. 1979. Sampling design and statistical methods for environmental biologists. Wiley Interscience, Chichester, England. Hamlin, K.L., D.F. Pac, C.A. Sime, R.M. DeSimone, and G.L. Dusek. 2000. Evaluating the accuracy of ages obtained by two methods for Montana ungulates. Journal of Wildlife Management. 64:441449. Hurlbert, S.H. 1984. Pseudoreplication and the design of ecological field experiments. Ecological Monographs 54:187-211. Miller, M.W., H.M. Swanson, L.L. Wolfe, F.G. Quatarone, S.L. Huwer, C.H. Southwick and P.M. Lukacs. 2008. Lions and prions and deer demise. Plos One 3:1-7. McCorquodale, S.M. 1999. Movements, survival, and mortality of black-tailed deer in the Klickitat Basin of Washington. Journal of Wildlife Management 63:861-871. Pac, D.F., and G.C. White. 2007. Survival and cause-specific mortality of male mule deer under different hunting regulations in the Bridger Mountains, Montana. Journal of Wildlife Management 71:816-827. Potvin, F., and L. Breton. 1988. Use of a net gun for capturing white-tailed deer, Odocoileusvirginianus, on Anticosti Island, Quebec. Canadian Field Naturalist 102:697-700. Powell, L.A. 2007. Approximating variance of demographic parameters using the delta method: a reference for avian biologists. Condor 109:949-954. 120 �Robinette, W.L., J.S. Gashwiler, D.A. Jones, and H.S. Crane. 1957. Notes on tooth development and wear for Rocky Mountain mule deer. Journal of Wildlife Management 21:134-153. Severinghaus, C.W. 1949. Tooth development and wear as criteria of age in white-tailed deer. Journal of Wildlife Management 13:195-216. Underwood, A.J. 1994. On beyond BACI-sampling designs that might reliably detect environmental disturbances. Ecological Applications. 4:3-15. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann. 1999. Mule Deer Survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Webb, S.L., J.S. Lewis, D.G. Wewitt, M.W. Hellickson, and F.C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310-314. White, G.C. and R.M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. White, G.C. and K.P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46:120-139. White, G.C. and B.C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. 121 �122 �Colorado Division of Parks and Wildlife July 2010 – June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3002 : : : : : Division of Parks andWildlife Mammals Research Elk Conservation Evaluating solutions to reduce elk and mule deer damage on agricultural resources Federal Aid Project No. Period Covered: July 1, 2010 – June 30, 2011 Author: H.E. Johnson; project cooperators, P. Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, and C. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Elk and mule deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural environments. This situation has generated significant challenges for wildlife agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage. One of the most severe areas of ungulate damage in Colorado has been the sunflower fields around Dove Creek. In this region, roughly a quarter of million dollars were annually paid to farmers between 2007 and 2009, and kill permits, distribution hunts and private-land-only doe hunts have been routinely distributed to farmers. Pressure from local growers over damage, and frustration from the general public over kill permits, have generated the need for the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) to evaluate other management options for reducing elk and deer crop depredation. As a result, CPW partnered with wildlife damage researchers from the National Wildlife Research Center to find science-based solutions for reducing crop damage. Collaboratively, our goals are to 1) examine elk and mule deer distribution patterns to design public hunting opportunities to reduce depredation, 2) experimentally test a suite of non-lethal fencing techniques to minimize crop damage, and 3) map and model landscape characteristics associated with damage to specify more effective site-specific management practices. During FY10-11 we developed a research proposal for internal review, generated project funding, and initiated the construction of experimental fence plots. Other project activities (i.e., monitoring the effectiveness of the different fence types for minimizing elk and deer damage, deploying telemetry collars, and mapping and modeling ungulate damage) will be initiated between FY11-12 and FY13-14. 123 �WILDLIFE RESEARCH REPORT EVALUATING SOLUTIONS TO REDUCE ELK AND MULE DEER DAMAGE ON AGRICULTURAL RESOURCES HEATHER E. JOHNSON P.N. OBJECTIVES To conduct a study on elk and mule deer around the agricultural fields of Dove Creek that 1) examines wild ungulate distribution patterns to design public hunting opportunities to reduce crop damage, 2) experimentally tests a suite of non-lethal fencing techniques to minimize crop depredation, and 3) maps and models landscape characteristics associated with damage to specify more effective site-specific management practices. SEGMENT OBJECTIVES 1. Work with staff from CPW and the National Wildlife Research Center to develop a research proposal for internal CPW peer review and funding solicitation. 2. Implement the construction of experimental fence plots on sunflower fields south of Dove Creek, Colorado, including electric fences, temporary winged fences, and chemical repellent fences. INTRODUCTION Elk and deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural areas (Austin et al. 1998, Wisdom and Cook 2000). In Colorado, elk and deer damage of crops accounts for a majority of the wildlife damage claims in the state. CPW is obligated to pay eligible wildlife damage claims on agricultural resources, and in recent years, the agency has spent approximately $500,000 on an annual basis to compensate growers. One of the most significant hotspots of elk and mule deer damage has been in the vicinity of Dove Creek, in conjunction with a recent switch in the agricultural crops that are locally grown. Farmers traditionally grew crops such as dry beans, spring and winter wheat, oats, alfalfa and grass hay which had minimal damage by wild ungulates. In recent years, however, local growers have planted sunflowers, a high-value seed oil crop used to produce biofuels, and highly desirable by wild ungulates. The main management tool available to CPW to reduce ungulate sunflower damage has been to increase harvest through the use of kill permits, distribution hunts, and private land only doe hunts, however tolerance for these permits has been low among local sportsman and the general public. Given pressure by farmers over elk and deer crop damage, and frustration by sportsmen and the public over kill permits, CPW wildlife managers were interested in finding alternative management solutions for reducing sunflower depredation. As a result, CPW managers partnered with the CPW research branch and wildlife-damage researchers from the National Wildlife Research Center (NWRC) to find non-lethal science-based solutions for reducing sunflower damage. Collaboratively, our goals are to 1) identify public hunting strategies that reduce crop damage, 2) test a suite of non-lethal fencing techniques to minimize crop depredation, and 3) map and model landscape characteristics associated with damage behavior to specify more effective management practices. Results from this study should enable CPW and local growers to reduce ungulate crop depredation, leading to a decrease in compensation payments, a decrease in kill permits/distribution hunts, and an increase in public hunting opportunities. A detailed research proposal (Johnson et al. 2011) is provided in Appendix I. 124 �STUDY AREA The study will be conducted in the vicinity of Dove Creek, Colorado (Montezuma, San Miguel and Dolores Counties), which is comprised of a mixture of agricultural and public lands. The project will focus on the north half of CPW Game Management Unit 72 and the west half of 711 (the portion west of the Dolores River). The area is generally characterized as mountain shrubland interspersed with irrigated and dryland agricultural fields, ranging from 1,981 to 2,590 m in elevation. The mountain shrub habitat type is primarily composed of serviceberry (Amelanchier alnifolia), bitterbrush (Purshia tridentata), mountain mahogany (Cercocarpus montanus), squaw apple (Peraphyllum ramosissimum) and black sagebrush (Seriphidium novum). Sunflower fields around Dove Creek are spatially juxtaposed to deep canyons that provide refugia for elk, exacerbating ungulate damage on agricultural crops (Fig. 1). METHODS During winter and spring of FY10-11 project collaborators developed a research proposal for internal CPW review and for funding solicitation (Appendix I). We successfully obtained project funds from the Rocky Mountain Elk Foundation, Colorado Statewide Habitat Partnership Program (HPP), Montelores HPP, National Wildlife Research Center and CPW Auction/Raffle Grants. Project grants and in-kind contributions totaled ~$279,000 which was sufficient to fully finance the project. Once project funding was solidified we initiated field logistics: the acquisition of field materials (fencing materials, elk and deer GPS collars, etc), contracting a fence installation company to construct experimental fence plots, hiring a temporary employee to monitor elk and deer damage on experimental fence plots, and scheduling a helicopter capture to deploy elk and deer collars. During FY10-11 we constructed the experimental fence plots based on a randomized block design. We identified 5 replicate fields that have repeatedly suffered high ungulate crop damage. Within each field we specified 4 10-acre plots, one for each experimental fence treatment type (polyrope fence, temporary winged fence, chemical repellent fence) and a control (see Appendix I for detailed descriptions of the fence types and study design). The 4 plots were randomly assigned within each field, such that each field (block) contained one replicate of all treatments (Gotelli and Ellison 2004). Other scheduled project activities will be initiated during FY11-12 such as monitoring the effectiveness of the different fence types for minimizing elk and deer damage, deploying telemetry collars, and mapping and modeling ungulate damage. SUMMARY AND FUTURE PLANS During FY10-11 we successfully developed a research proposal, generated project funding, and constructed the experimental fence plots for the first year of fieldwork. Starting in FY11-12 we will monitor the efficiency of the experimental fence plots in reducing elk and deer damage (July – Oct 2011) and deploy 40 GPS collars; 20 collars on adult female elk and 20 on adult female deer (Oct 2011). Experimental fence plots will also be monitored for elk and deer damage during FY12-13 (July-Oct). Elk and deer collars will collect data for 2 years and then detach in Sept 2013. Once collars are retrieved we will analyze and model elk and deer location data relative to agricultural and wildland habitat (FY13-14) 125 �LITERATURE CITED Austin, D.D., P.J. Urness, and D. Duersch. 1998. Alfalfa hay crop loss due to mule deer depredation. Journal of Range Management 51:29-31. Gotelli, N.J., and A.M. Ellison. 2004. A primer of ecological statistics. Sinauer Associates, Sunderland, Massachusetts. Johnson, H.E., P.Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, and C. Anderson. 2011. Evaluating solutions to reduce elk and mule deer damage on agricultural resources. Study Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Wisdom, M.J., and J.G. Cook. 2000. North American Elk. Pages 694-735 in S. Demarais and P.R. Krausman, editors. Ecology and management of large mammals in North America. Prentice Hall, Upper Saddle River, New Jersey, USA. Prepared by _______________________________________ Heather E. Johnson, Wildlife Researcher 126 �Figure 1. Placement of experimental fence plots within the 5 replicate sunflower fields. Fields are located adjacent to wildland canyons. 127 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2010-11 Evaluating solutions to reduce elk and mule deer damage on agricultural resources A Research Proposal Submitted By Heather Johnson, Mammals Researcher, CPW Patt Dorsey, Area Wildlife Manager, CPW Matt Hammond, District Wildlife Manager, CPW Chad Bishop, Mammals Research Leader, CPW Kurt VerCauteren, Ungulate Damage and Disease Project Leader, National Wildlife Research Center David Walter, Post-Doctoral Researcher, National Wildlife Research Center Charles Anderson, Post-Doctoral Researcher, National Wildlife Research Center A. Need Elk and deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural environments (Austin et al. 1998, Wisdom and Cook 2000). Because crops are typically more digestible and contain higher levels of crude protein than native grasses and browse species, they are often preferentially selected and consumed by wild ungulates (Mould and Robbins 1981). Agricultural producers have reported more damage by elk and deer than any other wildlife species, and damage by deer alone has been projected to exceed 100 million dollars annually in the U.S. (Conover 2002). This situation has generated significant challenges for management agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage (Van Tassell et al. 1999, Wagner et al. 1997, Wilson et al. 2009, Hegel et al. 2009, Walter et al. 2010). Elk and deer crop depredation results from a combination of factors including the seasonal distribution and abundance of local forage resources, landscape configuration, and herd density patterns (Vecellio et al. 1994; Yoder 2002; Hegel et al. 2009). Damage can be highly variable within and among growing seasons, as local precipitation and temperatures will alter the availability of native forage and the motivation of ungulates to feed on agricultural fields (Walter et al. 2010). The juxtaposition of cropland and wildland has also been found to be particularly important in driving damage rates, as those cultivated fields closer to cover experience more damage (Nixon et al. 1989, Hegel et al. 2009). Additionally, studies have found that ungulate damage is often caused by only a subset of individuals in the population, depending on the spatial and social structuring of the herd. These observations have critical implications for wildlife managers, as 1) management practices may be differentially effective based on the variability of native forage and the spatial juxtaposition of other habitat features, and 2) management techniques targeted at specific animals may be more effective than implementing those techniques on the population at large (Blejwas et al. 2002, Hegel et al. 2009). As a result, an understanding of both the spatial configuration of seasonal resources and the resource selection patterns of different segments of local ungulate populations is important to successfully identify strategies to reduce elk and deer crop damage (Hegel et al. 2009). In Colorado, elk and deer damage of crops accounts for a majority of the wildlife damage claims in the state. The Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) is obligated to pay eligible wildlife damage claims on agricultural resources, and in recent years, the agency has spent 128 �approximately $500,000 on an annual basis to compensate growers. One of the most significant hotspots of elk and mule deer damage has been in the vicinity of Dove Creek (Montezuma, San Miguel and Dolores Counties; Fig. 1), where roughly a quarter of million dollars was annually paid to farmers between 2007 and 2009. These extraordinary reimbursements have resulted from a recent switch in the agricultural crops that are locally grown. Farmers around Dove Creek traditionally grew crops such as dry beans, spring and winter wheat, oats, alfalfa and grass hay which had minimal damage by wild ungulates. In recent years, however, local growers have planted sunflowers, a high-value seed oil crop used to produce biofuels. In 2009 growers were paid approximately $.43/lb for organically grown sunflowers and $.28/lb for conventionally grown sunflowers. In that same year, dry land yields averaged 800 lbs/acre in the region. Elk and deer have demonstrated a strong affinity for sunflowers, causing up to 100% crop loss on certain fields, and resulting in high damage claims. Ungulate damage around Dove Creek is exacerbated by the spatial distribution of sunflower fields in relation to the surrounding wildlands (e.g., sagebrush-mixed shrublands and piñon-juniper woodlands). The region is fractured with deep canyons that provide refugia for elk, and fields adjacent to the canyon rims experience the greatest amount of depredation. With the substantial increase in biofuel production in the U.S. (World Resources Institute 2008), the agricultural conversion observed around Dove Creek will likely become common, as highpriced, crops replace more traditionally-grown, lower-cost crops (Walter et al. 2009). The main management tool available to CPW to reduce ungulate sunflower damage has been to increase harvest through the use of kill permits (for males and females), distribution hunts, and private land only (PLO) doe hunts. In response to damage reports, CPW has been allocating these permits to local growers between June and October, with the intent of harvesting resident animals rather than migratory elk and deer. This management strategy has resulted in exceptionally high private land harvests. For example, in 2008, kill permits or distribution hunts were allocated on as many as 25 different fields, with approximately 300 deer and 30 elk harvested. On a single 140-acre sunflower field, 57 female mule deer were harvested, and still the annual damage claim for the field was approximately $40,000 in that year. The CPW, the Bureau of Land Management, Montelores Habitat Partnership Program (HPP) Committee, U.S. Forest Service and Rocky Mountain Elk Foundation have initiated several habitat enhancement projects in the region to draw elk and deer off of agricultural fields, but the benefits of these projects are expected to take several years to fully materialize. Although tolerance for elk and mule deer damage on sunflower crops is low among farmers, tolerance for kill permits and distribution hunts is also low among sportsmen, the general public and some farmers. A majority of the damage occurs during July and August when calves and fawns are still dependent on their mothers, reducing the acceptability of female hunts. Additionally, both elk and deer population numbers in the study area (DAUs D24 and E24) are below or near management objectives creating a paradox where CPW ultimately wants to increase ungulate herds, but reduce crop depredation. Finally, this region is popular with hunters, as large bulls and bucks have been harvested in recent years. Hunting is economically important to Dolores, Montezuma and San Miguel Counties, providing approximately 230 jobs and there is a strong desire to have increased public hunting opportunities. Pressure from local growers over damage, and frustration from the general public over kill permits, have generated the need for CPW to evaluate other management options for reducing elk and mule deer crop depredation. As a result, managers from CPW have partnered with wildlife-damage researchers from the National Wildlife Research Center (NWRC) to find science-based solutions for reducing sunflower damage. Collaboratively, the goals of our study are to design public hunting opportunities to reduce crop damage, test a suite of non-lethal techniques to minimize crop depredation, and map and model landscape characteristics associated with damage behavior to specify more effective management practices. Results from this study should ultimately enable CPW and local growers to reduce ungulate crop depredation, leading to a decrease in compensation payments and kill permits/distribution hunts, and an increase in public hunting opportunities and support from farmers and sportsmen. 129 �B. Objectives Objective 1: Examine the spatial structure, distribution, and migration patterns of local elk and mule deer around agricultural areas. This will enable CPW to design public hunting opportunities that better address crop damage while decreasing the need for kill permits/distribution hunts on private lands. Objective 2: Use treatment and control fields to experimentally test novel methods for reducing elk and mule deer damage to crops including a) the repellent “fence” Plantskydd, b) an electric polyrope fence, and c) a temporary “winged” fence. Objective 3: Map and model the spatial juxtaposition of crop fields, ungulate habitats, human infrastructure and topographic features to assess the predictors of elk and mule deer resource-use and damage. This will allow CPW to explicitly account for landscape configuration when working with landowners to identify best management strategies for reducing damage. C. Expected Results or Benefits Long-Term Benefits  Sustain healthy elk and mule deer populations on public and private lands where they do not cause agricultural damage and can provide quality hunting opportunities.  Reduce elk and deer game damage payments on sunflowers and other crops.  Allow sportsmen to harvest a greater proportion of elk and deer by strategically allocating the number of licenses, the location of those licenses, and the timing of hunts to target conflict animals, reducing the need for kill permits and distribution hunts.  The identification of alternative, non-lethal methods to prevent damage and reduce elk and deer use of crop fields.  The development of a modeling tool that can be used by CPW and growers to select the most appropriate management techniques to minimize damage based on field characteristics, ungulate distribution and landscape configuration.  The application of sound science to on-the-ground wildlife damage management. Short-Term Benefits  Gain knowledge about local elk and deer movements and distribution relative to the location of crop damage.  Help farmers with on-going damage by providing management tools and assistance.  Strengthen CPW’s relationship with the local community (farmers, sportsmen, and the general public) by reducing elk and deer crop damage and increasing public hunting opportunities. D. Approach Examining the spatial distribution of elk and mule deer: To understand ungulate movement patterns and more effectively address damage problems we will capture and collar 20 adult female elk and 20 adult female mule deer. Females cause a majority of the crop depredation and will provide the greatest insight into herd distributions. We will capture animals using a net-gun fired from a helicopter (Krausman et al. 1985), targeting elk and mule deer in the vicinity of high-damage crops. Captured animals will be fitted with global positioning system (GPS) collars, and locations of elk and mule deer will be remotely downloaded, collected once collars are retrieved, and 130 �recorded via ground or aerial telemetry. For both species, GPS collars will be programmed to collect ≥3 locations a day on a revolving schedule for 2 years. Elk and mule deer locations will be tracked yearround so that seasonal resource-use, migration patterns, and distributions can be clearly identified. Due to the elk herd’s close proximity to the Utah border, information on elk locations will be shared with Utah Division of Wildlife, as it is suspected that some animals travel across the Utah border during winter and forage on Colorado sunflower crops during summer. We will use elk and mule deer locations to map seasonal distributions and migration patterns, using kernel density analyses in ArcGIS mapping software (Worton 1989, Worton 1995). This will allow CPW to determine the best timing of special season hunts, kill permits and distribution hunts to avoid the private land harvest of migratory elk at the sportsman’s expense. CPW will also be able use distribution data to design public hunts that will target conflict elk and mule deer. For example, the Utah Division of Wildlife Resources is willing to consider special elk hunts south of Hwy 491 if we find that any or all of the resident elk herds (causing damage) spend portions of the year in Utah. Locations will also allow us to determine the amount of use of crop fields by elk and deer, and the proportion of animals using crop fields (whether it is only certain segments of the population, or the population at large). Testing 3 novel methods to reduce crop damage: In addition to implementing effective harvest practices to reduce crop damage, there is strong public interest in the application of nonlethal techniques for reducing ungulate depredation, generating a need for rigorous evaluation of such techniques by wildlife agencies. Most nonlethal techniques are designed to physically exclude offending animals or reduce the motivation of animals to access protected resources (Nolte 1999). We will test three exclusionary management tools for reducing elk and mule deer crop damage that can be easily implemented by farmers during the growing season: a repellent “fence”, a polyrope electric fence, and a temporary “winged” fence. To test the effectiveness of these methods we will initially select 5 replicate fields that have repeatedly suffered high ungulate crop damage (~160-200 acres), situated along the canyon rims. Within each of those fields we will identify 4 plots, one for each treatment type (repellent, polyrope fence, winged fence) and a control. The 4 plot types will be randomly assigned within each field, utilizing a randomized block study design where each field (block) contains one replicate of all treatments (Gotelli and Ellison 2004). This will allow us to statistically account for environmental heterogeneity, as we expect that damage will be variable among fields. Within the fields, study plots will be spaced as far apart as possible, to account for plot independence, and each plot will be 10 acres2 in size. All study plots will be placed along the agriculture/wildland boundary, where depredation is expected to be concentrated. Plots will be monitored from June through October during the growing seasons of 2011 and 2012. We will quantify the relative success of each nonlethal method by comparing crop depredation and ungulate incursion among treatment and control plots. Plantskydd - Repellents are nonlethal substances used to deter ungulates by decreasing a plant’s palatability, and have had mixed success in deterring ungulate foraging activity (Andelt et al. 1992; Baker et al. 1999). We will test the effectiveness of a relatively new product, Plantskydd, for reducing sunflower damage around Dove Creek. This product was developed in Sweden to reduce mammalian wildlife damage on commercial forests and works by emitting an odor that animals associate with predator activity, repelling the animal before it forages on crop plants. There is great interest in the success of such a technique as it can be easily applied to vegetation by ground and aerial spraying, used on both organic and conventionally grown sunflower crops, and is cost-effective for growers. That said, the effectiveness of Plantskydd has not been experimentally tested, only anecdotally reported. To test this method, the 5 Plantskydd treatment plots will be ground or aerial sprayed around field borders once germination has been begun. We will then re-apply Plantskydd to the treatment plots once/month throughout the 131 �sunflower growing season as the repellent may wash off or decompose over time and will need to be reapplied to new plant material. Polyrope electric fence – Fences provide an effective long-term, nonlethal tool for minimizing ungulate crop damage, providing both a physical and psychological barrier (Walter et al. 2010). While a permanent 2.4 meter woven-wire fence provides a true physical barrier to elk and deer, such a structure is can cost >$20/meter, prohibiting wide-spread use. We will test a novel design of a less expensive polyrope electric fence (approximately $8/meter), which acts primarily as psychological barrier based on learned behavioral, avoidance conditioning (Fig. 2; McKillop and Sibly 1988). These fences consist of conductive wires which are woven into synthetic electric “ropes” that are more durable, visible, and easy to install than traditional electric fences (Hygnstrom and Craven 1988, VerCauteren et al. 2006). Permanent fence posts are placed, and then the polyrope is strung between the posts to provide seasonal crop protection. Avoidance conditioning occurs when an animal contacts the fence, often with the nose or tongue, and receives a powerful electric shock. Training can be expedited by baiting the fence wire with peanut butter or molasses to create a negative stimuli when making contact with the electric charge (Porter 1983, Hygnstrom and Craven 1988, Jordan and Richmond 1992, USDA National Wildlife Research Center, unpublished data). Polyrope fences have had success in reducing deer damage (Hygnstrom and Craven 1988, Seamans and VerCauteren 2006), but have not been experimentally tested for reducing elk damage. For the 5 randomly selected polyrope treatment plots, we will construct a fence that is approximately 1.8 meter tall with 5 strands to discourage passage under, through, or over the fence. We will treat the polyrope with a sweet attractant, designed to facilitate avoidance learning, using a minimum charge of 3,000 volts (Curtis et al. 1994). The polyrope will be powered by a Speedrite™ 3000 energizer (Tru-Test Incorporated, San Antonio, Texas) which has a maximum pulse output of 3.0 joules and will be powered by a 12-volt deep-cycle battery with a solar-panel recharger. Temporary winged fence - For seasonal agricultural resources, such as sunflowers, temporary fences may provide reliable ungulate protection. Temporary fences are inexpensive, lightweight, and easy to erect and remove (Rosenberry et al. 2001, VerCauteren et al. 2006). Recently, investigators have been experimenting with a temporary “winged” fence made of polypropylene mesh. The fence is installed completely on one side of the target field, and partially installed on two other sides having 50-100 meter “wings” that extend perpendicular from the full fence line (see Fig. 3). This design was found to reduce deer damage in corn fields (Hildreth et al. In Review) while requiring limited costs for fence materials and installation. The effectiveness of such a fence has not yet been tested on elk or on deer with other crops than corn, but has potential to be an easily implemented management tool that could reduce crop depredation. On those plots randomly selected to be winged-fence treatments, we will install a fence with a similar design to Hildreth et al. (In Review), where the crop/wildland interface receives complete protection. For increased height and visual deterrence, the fence will be made of 2.4 meter tall orange barrier material (e.g., Guardian Orange Warning Barrier, Tenax Corporation, USA, Baltimore, Maryland). Monitoring the effectiveness of non-lethal treatments: All treatment and control plots will be monitored for 2 response variables: crop damage and elk/deer incursion. To measure damage to sunflower crops, we will monitor fields every 2 weeks between the time of germination and harvest. We will utilize the variable-area-transect (VAT) method for estimation of crop damage, which consists of both low and high intensity area monitoring (Engeman and Sterner 2002, Gilsdorf et al. 2004a, Gilsdorf et al. 2004b). We will randomly place 4 low-intensity sampling areas within each study plot. In each low-intensity sampling area, we will inspect a row of sunflowers, counting the total number of sunflowers including those that are damaged and undamaged. If 5 cervid-damaged sunflowers are tallied in 100 meters, we will record the distance traveled and the total number of sunflowers. If 5 cervid-damaged sunflowers were not tallied in 100 meters, the observer will record the total number of sunflowers and any cervid-damaged sunflowers observed in that distance. We will calculate the percentage of sunflowers damaged per sampling area using the equation ~ damage per area = [number of damaged sunflowers/(number of 132 �damaged sunflowers+number of undamaged sunflowers)] x 100 (Gilsdorf et al. 2004a, Gilsdorf et al. 2004b). We will also randomly locate 2 high-intensity sampling areas along every treatment and control plot edge to measure damage in proximity to places of high cervid pressure. Within the high-intensity sampling areas, we will use 5 VATs within each area. This will result in 12 total sampling areas (4 low intensity, 8 high intensity) per plot. Additionally, at the end of the season, we will evaluate game damage and year-end yields between treatment and control plots, the ultimate measure of success for each management technique. We will also quantify the level of incursion that occurs into treatment and control fields by elk and mule deer. To do this, we will use animal-activated cameras to record the number and frequency of elk and mule deer that pass through repellents or fence designs into sunflower fields. Cameras will be mounted on posts on the corners of treatment and control fields, capturing images of elk and mule deer inside and outside the field boundaries. Cameras will be positioned along field border that is closest to the agriculture/wildland boundary which is most likely to experience depredation. The Camera type is Moultrie® Game Spy Digital I-65 Infrared, 6.0 mega pixel (Moultry Products, LLC, Alabaster, AL, USA). Cameras can capture images up to 50 feet away, are weather-resistant with a built in solar panel and security box, and can wirelessly transmit images to a private web site for download by project personnel. Cameras will be activated for the duration of the growing season, and at the end of the season we will tally the number of elk and mule deer that penetrated each treatment and control plot boundary. Differences in elk and mule deer use of treatment/control fields will then be tested using repeated measures parametric statistics. This will allow us to evaluate the effectiveness of the repellent, polyrope fence, and winged fence in reducing crop depredation, relative to control plots. Mapping and modeling the spatial juxtaposition of ungulate damage within the landscape: To more effectively address ungulate damage problems we will use ArcGIS software to map crop fields, surrounding habitat types, human development, and topography. These variables have been important in explaining rates of ungulate depredation as damage tends to increase closer to cover, further from roads, and depending on crop palatability (Grover and Thompson 1986, Nixon et al. 1989, Hegel et al. 2009). Information about the location of a crop field in the context of the overall landscape will allow CPW to work with local growers to identify the most appropriate tools, and the timing of their implementation, to reduce damage. To meet this objective we will use satellite imagery to digitize agricultural fields and attribute those fields by crop type. We will use existing landcover, infrastructure, and digital elevation model (DEM) coverages to identify non-agricultural vegetation types, distance to human development, and topographic features (i.e. elevation, slope, aspect), respectively. We can then use landscape variables in conjunction with elk and mule deer location data (see Objective 1) to model the probability that a field is depredated by ungulates (Manly et al. 2002). This model can provide a powerful tool for CPW managers, as they will be able to predict the likelihood of depredation, depending on field location, the surrounding environment, and the crop type, and therefore help landowners specify crop choice or management actions that will reduce elk and deer damage. Timeline The study will take 3 years to complete. Non-lethal management techniques to reduce elk and deer damage will be implemented and monitored during the growing seasons of 2011 and 2012 (June – October), and the results of treatment/control plots will be analyzed thereafter. We will collar elk and deer during August or September 2011, and monitor animals for 2 years (the length of battery life of GPS collars). Once the GPS collars have been retrieved, we will analyze elk and deer location data. We will use that data to conduct damage mapping and modeling over the following ~6 months. 133 �Budget We obtained grants from the Colorado Statewide Habitat Partnership Program, the Montelores Committee Habitat Partnership Program, the Rocky Mountain Elk Foundation, the National Wildlife Research Center and from Colorado Division of Parks and Wildlife Auction/Raffle funds to conduct this work. Below is an itemized project budget. Item EQUIPMENT 20 Elk GPS Collars ($1,300 ea) Capture of Elk ($454 ea + per diem) 20 Deer GPS Collars ($2,500 ea) Capture of Mule Deer ($429 ea + per diem) Plantskydd Materials & Application Polyrope Materials & Installation Winged Fence Materials & Installation Animal-Activated Cameras (20 @ $750 ea) Camera Activation/Maintenance GIS Mapping Leased Truck (Jun-Oct/2 yrs) Gas for Leased Truck (Jun-Oct 2 yrs) PERSONNEL Technician for Monitoring (Jun-Oct/2 yrs) CPW Permanent Employee Salary (2 yrs) NWRC Post-doctoral Salary TOTAL Cost $26,000 $9,330 $50,000 $8,830 $16,710 $32,643 $19,042 $15,000 $4,180 $3,000 $12,000 $5,000 $25,583 $40,000 $12,000 $279,318 E. Location The study will be conducted in the vicinity of Dove Creek, Colorado (Montezuma, San Miguel and Dolores Counties), which is comprised of a mixture of agricultural and public lands. The project will focus on the north half of CPW Game Management Unit 72 and the west half of 711 (the portion west of the Dolores River). The area is generally characterized as mountain shrubland interspersed in irrigated and dryland agricultural areas. The mountain shrub habitat type, which occurs on both private and public lands, is composed primarily of serviceberry, antelope bitterbrush, mountain mahogany, squaw apple and black sagebrush. This habitat type is limited to elevations between 6,500 and 8,500 feet. F. Literature Cited Andelt, W.F., K.P. Burnham, and J.A. Manning. 1991. Relative effectiveness of repellents for reducing mule deer damage. Journal of Wildlife Management 55:341-347. Austin, D.D., P.J. Urness, and D. Duersch. 1998. Alfalfa hay crop loss due to mule deer depredation. Journal of Range Management 51:29-31. Baker, D.L., W.F. Andelt, K.P. Burnham, and W.D. Sheppard. 1999. Effectiveness of hot sauce and Deer Away repellents for deterring elk browsing of aspen sprouts. Journal of Wildlife Management 63:1327-1336. Blejwas, K.M., B.J. Sacks, M.M. Jaeger, and D.R. McCullough. 2002. The effectiveness of selective removal of breeding coyotes in reducing sheep predation. Journal of Wildlife Management 66:451-462. Conover, M.R. 2002. Resolving human-wildlife conflicts: the science of wildlife damage management. CRC Press LLC, Boca Raton, Florida, USA. 134 �Curtis, P.D., M.J. Farigone, and M.E. Richmond. 1994. Preventing deer damage with barrier, electrical, and behavioral fencing systems. Proceedings of the Vertebrate Pest Control Conference 16:223227. Engeman, R.M., R.T. Sterner. 2002. A comparison of potential labor-saving sampling methods for assessing large mammal damage in corn. Crop Protection 21:101-105. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004a. Evaluation of a deer-activated bio-acoustic frightening device for reducing deer damage in cornfields. Wildlife Society Bulletin 32:515-523. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004b. Propane exploders and Electronic Guards were ineffective at reducing deer damage in cornfields. Wildlife Society Bulletin 32:524-531. Gotelli, N.J., and A.M. Ellison. 2004. A primer of ecological statistics. Sinauer Associates, Sunderland, Massachusetts. Grover, K.E., and M.J. Thompson. 1986. Factors influencing spring feeding site selection by elk in the Elkhorn Mountains, Montana. Journal of Wildlife Management 50:466-470. Hegel, T.M., C.C. Gates, and D. Eslinger. 2009. The geography of conflict between elk and agricultural values in the Cypress Hills, Canada. Journal of Environmental Management 90:222-235. Hildreth, A.M., S.E. Hygnstrom, E.E. Blankenship, and K.C. VerCauteren. In Review. Efficacy of a partial poly-mesh fence with wings to reduce deer damage to corn. Hygnstrom, S.E. and S.R. Craven. 1988. Electric fences and commercial repellents for reducing deer damage in cornfields. Wildlife Society Bulletin 16:291-296. Jordon, D.M., and M.E. Richmond. 1992. Effectiveness of a vertical 3-wire electric fence modified with attractants or repellents as a deer exclosure. Proceedings of the Eastern Wildlife Damage Control Conference 5:44-47. Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a netgun. Wildlife Society Bulletin 13:71–73. McKillop, I.G., and R.M. Sibly. 1988. Animal behaviour at electric fences and implications for management. Mammal Review 18:91-103. Manly, B.F.J., L.L. McDonald, D.L. Thomas, T.L. McDonald, and W.P. Erickson. 2002. Resource selection by animals; statistical design and analysis for field studies. Second Edition. Kluwer Academic Publishers, Boston, Massachussetts. Mould, E.D., and C.T. Robbins. 1982. Digestive capabilities in elk compared to white-tailed deer. Journal of Wildlife Management 46:22-29. Nixon, C.M., L.P. Hansen, P.A. Brewer, J.E. Chelsvig. 1989. Ecology of white-tailed deer in an intensively farmed region of Illinois. Wildlife Monographs 118:1-77. Nolte, D. 1999. Behavioral approaches for limiting depredation by wild ungulates. Pages 60-69 in K.L. Launchbaugh, K.D. Sanders, and J.C. Mosley, editors. Grazing behavior of livestock and wildlife. Idahor Forest, Wildlife & Range Experimental Station Bulletin #70, University of Idaho, Moscow, USA. Porter, W.F. 1983. A baited electric fence for controlling deer damage to orchard seedlings. Wildlife Society Bulletin 11:325-329. Rosenberry, C.S., L.I. Muller, and M.C. Conner. 2001. Movable, deer-proof fencing. Wildlife Society Bulletin 29:754-757. Seamans, T.W., and K.C. VerCauteren. 2006. Evaluation of ElectroBraid™ fencing as a white-tailed deer barrier. Wildlife Society Bulletin 34:8-15. Van Tassell, L.W., C. Phillips, B. Yang. 1999. Depredation claim settlements in Wyoming. Wildlife Society Bulletin 25:886-894. Vecellio, G.M., R.H. Yahner, and G.L. Storm. 1994. Crop damage by deer at Gettysburg Park. Wildlife Society Bulletin 22:89-93. VerCauteren, K.C., M.J. Lavelle, and S. Hygnstrom. 2006. Fences and deer-damage management: a review of designs and efficacy. Wildlife Society Bulletin 34:191-200. 135 �Wagner, K.K., R.H. Schmidt, and M.R. Conover. 1997. Compensation programs for wildlife damage in North America. Wildlife Society Bulletin 25:312-319. Walter, W.D., M.J. Lavelle, J.W. Fischer, T.L. Johnson, S.E. Hygnstrom, and K.C. VerCauteren. 2010. Management of damage by elk (Cervus elaphus) in North America: a review. Wildlife Research 37:630-646. Walter, W.D., K.C. VerCauteren, J.M. Gilsdorf, and S.E. Hygnstrom. 2009. Crop, native vegetation, and biofuels: response of white-tailed deer to changing management priorities. Journal of Wildlife Management 73:339-344. World Resources Institute. 2008. WRI EarthTrends monthly update page. http://earthtrends.org/updates/node/180. Worton, B.J. 1989. Kernal methods for estimating the utilization distribution in home-range studies. Ecology 70:164-168. Worton, B.J. 1995. Using Monte Carlo simulation to evaluate kernel-based home range estimators. Journal of Wildlife Management 59:794-800. Yoder, J. 2002. Deer-inflicted crop damage and crop choice in Wisconsin. Human Dimensions of Wildlife 7:179-196. 136 �Figure 1. Pink areas delineate zones of high ungulate-crop depredation around Dove Creek, Colorado (Montezuma, San Miguel and Dolores Counties; figure from a Montelores HPP report). DOVE CORT 137 �Figure 2. Photo of a polyrope electric fence constructed in a sunflower field south of Dove Creek, CO. Figure 3. Photo along a wing of a temporary fence constructed in a sunflower field south of Dove Creek, CO. 138 �Colorado Division of Parks and Wildlife July 2010 – June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Federal Aid Project No. Colorado 3430 3003 : : : : : Division of Parks and Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2010 – June 30, 2011 Author: H.E. Johnson; project cooperators, C. Bishop, J. Brodrick, J. Apker, M. Alldredge, S. Breck, J. Beckmann, K. Wilson, M. Reynolds-Hogland, T. Speeze, and P. Dorsey. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Across the country conflicts among people and black bears are increasing in number, frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a unique collaboration that builds on the resources and abilities of personnel from 5 entities: the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]), the National Wildlife Research Center, Colorado State University, Wildlife Conservation Society, and Bear Trust International. Collectively, we are implementing a 5-year study on black bears that 1) tests management strategies for reducing bear-human conflicts, including a large-scale treatment/control urban-food-removal experiment; 2) determines the consequences of bear-use of urban environments on regional bear population dynamics; and 3) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. We initiated this project in FY10-11 by developing a research proposal, selecting a field site for detailed data collection (Durango, CO), coordinating with numerous entities (non-profit organizations, private citizens, and personnel from city, county, state, and federal government agencies) on field logistics, and commencing several aspects of data collection (trapping and collaring bears, monitoring human-related bear mortalities, implementing DNA hair-snare protocols, monitoring garbage-related bear-human conflicts, and conducting mast surveys). Project collaborators will continue to seek additional funding to implement the remaining activities outlined in the research proposal (i.e., conduct an urban-food-removal experiment, increase the sample size of GPS collared bears, and acquire telemetry collars to test a translocation model). Information from this study will provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the country. 139 �WILDLIFE RESEARCH REPORT BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS HEATHER E. JOHNSON P.N. OBJECTIVES To conduct a study on black bears in Colorado that 1) tests management strategies for reducing bearhuman conflicts, including a large-scale treatment/control urban-food-removal experiment; 2) determines the consequences of bear-use of urban environments on regional bear population dynamics; and 3) develops population and habitat models to support the sustainable monitoring and management of bears in the state. SEGMENT OBJECTIVES 1. Develop a research proposal for internal CPW peer review and funding solicitation. 2. Consult with CPW personnel on potential study sites and compile key information about those sites including numbers of reported bear-human conflicts, public land access, urban sanitation practices, harvest data, and urban development statistics. 3. Work with personnel from the City of Durango, La Plata County, the San Juan Public Lands Office (USFS/BLM), the Columbine and Pagosa USFS/BLM Ranger Districts, Bear Smart Durango, CPW Southwest Region, CPW Area 15, and private landowners on logistical field considerations. 4. Initiate black bear capture and GPS collaring efforts to collect data on bear movements, habitatuse patterns, and vital rates. 5. Track human-related bear mortalities and removals around Durango from translocations, vehicle collisions, conflict mortalities and harvest. 6. Deploy bear hair-snares in an “urban” Durango sampling grid and a “wildland” Piedra sampling grid to obtain DNA for genetic mark-recapture analyses. Genotyped hair samples will be used to estimate population densities. 7. Collect data on natural food availability for bears based on the mast abundance of gambel oak, serviceberry, chokecherry, hawthorne, pinyon pine and squaw apple. 8. Monitor the frequency of garbage-related bear-human conflicts within proposed treatment and control areas for an urban-food-removal experiment. 140 �INTRODUCTION Conflicts among people and black bears (Ursus americanus) are increasing nationwide (Hristienko and McDonald 2007), as the human population grows and urban development expands in and around bear habitat. State and federal wildlife agencies are responsible for both minimizing bear-human conflicts and maintaining and monitoring viable bear populations; two mandates that are proving to be incredibly challenging. Conflicts between bears and people can result in human injuries, property damage, and bear mortality (i.e. euthanasia), but despite increasing efforts from wildlife agencies to reduce conflicts, rates have been on the rise (Baruch-Mordo et al. 2008). Meanwhile, bear population parameters have been exceedingly difficult to estimate across large spatial scales (Garshelis and Hristienko 2006), and current population sizes and trends are largely unknown. As a result, management agencies are uncertain whether recent increases in bear-human conflicts reflect increases in the bear population or just bear behavioral shifts to anthropogenic food resources. Without a thorough understanding of the factors that drive nuisance bear behavior, and the relationship between conflict rates and bear dynamics, it has been difficult for wildlife agencies to initiate effective management practices. This issue has generated a pressing need for comprehensive bear research in Colorado, and resulted in the development of a detailed study proposal by Johnson et al. (2011; Appendix I). The proposal outlines a 5-year project on black bears that 1) tests management strategies for reducing bearhuman conflicts, including a large-scale treatment/control urban-food-removal experiment; 2) determines the consequences of bear-use of urban environments on regional bear population dynamics; and 3) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. Overall, this study should explicitly link bear movement and resource-use to population parameters, while rigorously testing an array of management techniques to reduce conflicts. This information should provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the west. During FY10-11 we developed a research proposal, identified a study site, determined the logistics of collecting field data at that site, and initiated data collection. Field efforts focused largely on meeting research objectives 1 and 2, which will yield data that will eventually be used to address objective 3. Specifically, we captured and collared adult female bears, collected data on human-related bear mortalities, deployed and monitored hair-snares to collect DNA for estimating population size, tracked garbage-related bear-human conflicts, and collected data on natural food availability for bears. We report general summary information from recent fieldwork (1 May – 15 Sept 2011) in this progress report; detailed analyses of field data will occur during FY11-12. While we have initiated data collection for several aspects of this project, collaborators will need to generate additional funding to conduct all research activities outlined in the proposal (i.e., conduct the urban-food-removal experiment, increase the sample size of GPS collared bears, and obtain telemetry collars to test a translocation model). STUDY AREA To meet study objectives, a combination of detailed, site-specific field data, and statewide data will be required. For the information presented in this progress report, we focus specifically on the selection of a site for detailed data collection on bear resource-use, demography, and the effectiveness of urban bear-proofing. To make this determination we evaluated a suite of factors. We first identified urban areas in Colorado that reported the highest numbers of conflict-related bear mortalities, translocations, and public calls. From those cities, we then considered the quality and history of bear-human conflict reporting, current bear-proofing infrastructure, the feasibility of conducting a large-scale human-foodremoval experiment (based on current city waste management practices), the size of the urban-wildland interface, harvest management, and public land accessibility. Based on those factors, project collaborators 141 �decided that field efforts should be initiated around the urban center of Durango, Colorado (La Plata County). Durango consistently exhibits some of the highest numbers of bear-human conflicts in the state, conflict reports are regularly monitored by CPW Area 15 and Bear Smart Durango (a local non-profit organization), and unlike other areas experiencing high conflict rates, bear harvest was expected to be maintained at similar levels for the foreseeable future. Durango also had limited bear-proofing infrastructure, was the only city with a coordinated residential waste management system (all residential waste is removed by the city), and is largely surrounded by public land (USFS, BLM, CPW, City of Durango and La Plata County; Fig. 1). The city of Durango contains ~17,000 people (within city limits) and sits at 1,985 m along the Animas river valley. The town is surrounded by mountainous terrain ranging in elevation from ~1,930 to ~3,600 m, and is generally characterized by mild winters and warm summers that experience monsoon rains. Vegetation in the region is dominated by ponderosa pine, oak, pinyon-juniper, aspen, mountain shrub, and agricultural communities. Key forage species for black bears include gambel oak (Quercus gambelii), chokecherry (Padus virginiana), serviceberry (Amelanchier alnifolia), hawthorne (Crataegus spp), squaw apple (Peraphyllum ramosissimum), angelica (Angelica spp), sweet cicily (Osmorhiza spp), cow parsnip (Heracleum sphondylium) and waterleaf (Hydrophyllum spp). Public land in the region is primarily managed by the San Juan National Forest, the Bureau of Land Management, Colorado Parks and Wildlife, La Plata County and the City of Durango. METHODS Logistical Considerations During fall and early winter FY10-11, we developed a research proposal for internal CPW review and identified a field site for collecting detailed bear habitat-use and demography data. In late winter and spring we worked with various entities around Durango to prepare to conduct fieldwork. We presented our research proposal to personnel from the U.S. Forest Service and BLM (San Juan Public Lands Office, Columbine Ranger District, and Pagosa Ranger District) and worked to develop an operating plan for capturing bears and deploying hair-snares on federal land. We also presented our proposal to staff from the City of Durango and La Plata County, and discussed access to their respective lands for meeting research objectives. Within CPW, we worked with personnel from Area 15 and the Southwest Region to identify initial capture and hair-snare sites, create a bear-human conflict mailbox for recording public calls, and clarify the research objectives relative to local management actions. Additionally, we solicited various entities for financial contributions to the project. Bear trapping and collaring, tracking of humanrelated bear mortalities, DNA hair-snare surveys, garbage-related conflict monitoring, and mast surveys were all initiated during summer 2011; the study proposal (Appendix I) provides detailed descriptions of these methods so we only briefly describe them below. Bear Trapping and Collaring To relate the habitat-use patterns of bears to their demographic trends, we captured and collared adult female bears. We specifically targeted adult females as they represent the reproductive segment of the population and should provide reliable inference to general demographic trends. Additionally, we can obtain information on multiple key vital rates from collaring a single sex-stage class, because, in addition to adult female survival (the vital rate with the greatest elasticity), collared females allow us to track fecundity and cub survival from winter den checks. While our long-term goal is to collar ~50 adult females (Appendix I), in the first year of the study we had the resources available to deploy 25 GPS collars (20 new Vectronics collars, 5 used Lotek collars). We targeted our trapping efforts within ~12 km of the center of Durango to capture a cohort of bears that experience similar natural food availability, have anthropogenic food resources readily available, and encompass a range of habitat-use patterns relative to the urban-wildland interface. 142 �From May through 15 September we used a combination of box traps and leg-hold snares to capture black bears (Jonkel 1993). We built smaller box traps than those previously used for bear research in Colorado (previously built traps are 0.91 x 0.91 x 1.83 m and weigh ~205 kg; newly constructed traps are 0.71 x 0.66 x 1.83 m and weigh ~125 kg), allowing for increased mobility and flexibility in placement (Fig. 2). A detailed description of the capture and handling procedures is available in Appendix II. Traps and snares were baited with fish, fruit, human foods (at urban locations) and manufactured scents; they were set in the evening and checked the following morning. Adult female bears were fitted with a GPS collar, marked with a PIT tag, and had a tooth pulled for age verification. All other bears (except cubs) were uniquely marked with a PIT and ear-tag (a single small black tag). Bears were weighed, measured, and sampled for blood and hair. GPS locations from Vectronics collars were programmed to upload 4 locations/day through a satellite system, while locations from Lotek collars were manually downloaded in the field using a hand-held device from the ground or air (fixed-wing aircraft). Monitoring Human-Related Bear Mortalities Between 1 May and 15 September 2011 we recorded all human-related black bear mortalities and removals in the vicinity of Durango. Mortalities and removals occurred from translocations, vehicle collisions, conflict-related euthanasia and harvest. For all bears removed from the study area we collected a hair and tooth sample and recorded the date, mortality/removal cause, location, bear age, sex, weight, and morphological measurements. Tooth samples will be used to age and genotype these bears so they can be incorporated into population density analyses. Hair-Snare Surveys To estimate the density of black bears around Durango we used a DNA hair-snare sampling scheme (Woods et al. 1999, Mowat and Strobeck 2000). We centered a 36 cell grid (576 km2) over Durango where each cell was 4 x 4 km in size and contained one snare. We sampled a total of 31 grid cells, dropping 5 cells along the outer edge of the grid where public or motorized access was prohibited (Fig. 3). Snares consisted of a scented bait hanging high in a tree, surrounded by barbed wire around a cluster of trees encircling the bait; when the bears climbed over or under the wire to investigate the bait, they left a hair sample on the barbed wire. On half of the snares we hung a single strand of barbed wire (50 cm high), and on the other half of the snares we hung two strands (50 and 20 cm high). Our goal with this design was to determine whether the additional strand of wire increased capture probability. Snares were deployed from June 1 to 14, and we conducted 6 weekly sampling occasions thereafter. On each occasion, we re-baited the snare (randomly baited with anise, strawberry, fish, or maple), and collected hair samples off all barbs. Each hair sample was uniquely catalogued according to the site, date, occasion, and barb number. Samples will be sent to the laboratory at Wildlife Genetics International for genotyping during fall 2011 and we will use the pattern of genotypes to estimate density using mark-recapture statistics. In addition to implementing the Durango hair-snare grid, we also conducted a pilot grid in the Piedra watershed (located between Durango and Pagosa Springs; see Appendix I Figure 7). This site was chosen as high quality “wildland” bear habitat, reflecting representative densities of bears in the region in the absence of urban development and human food resources. Initially, we intended to deploy and monitor ~32 snares in both the Durango and Piedra grids, however, lack of motorized access in the Piedra watershed inhibited field crews from constructing and checking all snares in a timely fashion. As a result, we opted to run a subset of 9 snare sites in the Piedra to determine whether twice/month sampling (as opposed to weekly) would have significant impacts on DNA quality, DNA contamination (hair samples from >1 bear/barb), and recapture rate. These samples will be genotyped this fall. Depending on the results, we will design an appropriate sampling scheme to estimate the wildland bear density in FY11-12. 143 �Mast Surveys Bear-human conflicts and bear-use of urban environments may increase when natural foods are in short supply (Zack et al. 2003, Baruch-Mordo 2007, Baruch-Mordo et al. 2010). To quantify the role of natural food availability on bear habitat selection, we initiated weekly surveys of the local soft and hard mast. In the Durango region, the key mast species for bears are gambel oak, chokecherry, serviceberry, hawthorne, squaw apple, and pinyon pine (Beck 1991, Tom Beck, personal communication). Although the phenology of these species is variable throughout the late summer/early fall, they generally reach peak fruit or nut maturation between mid-August and mid-September. We randomly selected 12 transects throughout the 576 km2 hair-snare study area to evaluate bear natural food availability (Fig. 3). Each transect was 1 km in length and ran along an existing public trail or public-accessible stream drainage. Field technicians walked vegetation transects each week between 15 August and 15 September and for each species, recorded the phenological stage and the percentage of plants that exhibited mast in different abundance categories (mast failure, <25% of plants with mast, etc). Conflict Monitoring One management strategy proposed for reducing bear-human conflicts is removing access to human foods for bears (Peine 2001, Spencer et al. 2007). Given the high price to operationally “bearproof” a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. As part of this study we plan on implementing the first rigorous scientific evaluation of the efficiency of widescale urban bear-proofing for minimizing bear-human conflicts. Although this portion of the project has not yet been funded, we conducted pre-treatment monitoring in proposed treatment and control areas (Fig. 4). During July and August, the months that experience the highest numbers of bear-human conflicts (CPW unpublished data) we patrolled each street within proposed treatment/control areas on the day that waste removal was scheduled to occur (when maximum human food was assumed to be available to bears). Patrols were conducted from 06:00 - 07:00 AM; for all locations where there was evidence that bears had obtained garbage we recorded UTM coordinates and the trash container type. RESULTS AND DISCUSSION During the summer 2011 field season we conducted 92 total bear captures; 71 captures were unique individuals and 21 were recaptures (see map of capture locations in Fig. 3). Of the unique individuals captured, there were 30 females, 38 males, and three cubs of unidentified sex (cubs were released without being immobilized and thus, gender was not determined; Table 1). The mean age of captured bears ≥1 year old was 4.9, and the mean weight was 80.9 kg (60.0 kg for females and 97.4 kg for males). In total, we placed traps/snares at 105 different locations and we had 1,253 trap nights. Across all bear captures (new captures and re-captures), 86 bears were captured using box traps (1,119 box trap nights) and 6 with leg-hold snares (134 snare nights). Generally capture success peaked during the first couple weeks of June and again in mid-August; capture success was low during July. We modified our newly constructed, smaller box traps to have a locking mechanism on the door that, once triggered, only allowed the door to close shut and not re-open. This was a critical design element, and allowed us to use the smaller box traps to catch bears ≤ 214 kg. Generally, we found these traps to be convenient to place in the field and successful in safely capturing and holding bears until they were immobilized. We collared a total of 26 female bears, however two bears slipped out of their collars and were not recaptured leaving us with 24 collared bears at the end of the field season. During the trapping season, Vectronics collars successfully uploaded >5,000 GPS locations through the satellite system, and we downloaded an additional 1,500 locations from Lotek collars (Fig. 5). One Vectronics collar prematurely switched to low-battery mode in August; we are currently attempting to recapture the bear to replace the collar. Although we have not yet conducted any formal movement analyses, one collared female moved 144 �~50 km southwest from Perins Peak State Wildlife Area (adjacent to Durango), eventually moving back after several weeks. The second longest movement by a collared bear was ~16 km. Between 1 May and 15 September, 23 bears were removed from the greater Durango area due to human-related causes. Of those bears that were removed, three were translocated due to conflicts with people, seven were killed in vehicle collisions, one was killed during research trapping, and 12 were euthanized due to conflicts with people (breaking into house, killing livestock, etc). There were three cubs, two yearling females, five yearling males, six adult females and nine adult males that were removed. Until bears begin hibernating, additional mortalities and removals are expected to occur. Field crews collected a total of 998 individual bear hair samples, 743 samples from the Durango grid and 255 samples from the pilot Piedra grid. Over the 6 sampling occasions from 31 snares around Durango we collected 224, 167, 138, 77, 68, and 69 hair samples, respectively. Over the three sampling occasions from nine snares in the Piedra we collected 127 samples; 46, 50, and 31 samples/occasion, respectively. We also collected 128 additional samples from snares in the Piedra watershed that were only checked on a single occasion. Samples will be sent to Wildlife Genetics International for genotyping in the fall, and results will allow us to estimate bear density. Within the proposed treatment and control areas for the urban bear-proofing experiment, we observed 129 incidences of bears accessing human garbage during July and August; incidences peaked during the first week of August. Of those events, 10% were wildlife-resistant garbage containers and 90% were regular containers. Bears accessed human food from wildlife-resistant containers when they were not closed properly or could break the locking mechanism on the lid. In assessing the availability of garbage to bears, we recorded the location and container type of 1,167 garbage cans in the proposed treatment and control areas (Fig. 4). Of those containers, 14% were wildlife resistant and 86% were regular (non-wildlife resistant). This demonstrates the limited residential bear-proofing that currently exists in Durango, and the relevance of conducting an experimental test of wide-scale urban bear-proofing in this community. Mast surveys are currently ongoing; results will be in the annual report for FY11-12. SUMMARY AND FUTURE PLANS During FY10-11 we successfully developed a research proposal addressing bear-human conflict issues in Colorado, selected a field site, coordinated with numerous entities (non-profit organizations, private citizens, and personnel from city, county, state, and federal government agencies) on field logistics, and initiated several aspects of data collection (trapping and collaring bears, tracking humanrelated bear mortalities, implementing DNA hair-snare protocols, monitoring garbage-related bear-human conflicts, and conducting mast surveys). We will continue these field activities during summers 20122015. Additionally, we will begin winter den checks in January 2012 to track fecundity and cub survival, and ensure that collars are fitting appropriately. Project collaborators will continue to seek additional funding to implement the remaining activities outlined in the research proposal. These activities include the implementation of an urban bear-proofing experiment, increasing the number of GPS collared female bears, and purchasing telemetry collars for a translocation study. In addressing the objectives of this project we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear population trends, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. 145 �LITERATURE CITED Baruch-Mordo, S. 2007. Black-bear human conflicts in Colorado: spatiotemporal patterns and predictors. Thesis, Colorado State University, Fort Collins, Colorado. Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and D.M. Theobald. 2008. Spatiotemporal distribution of black bear-human conflicts in Colorado, USA. Journal of Wildlife Management 72:1853-1862. Baruch-Mordo, S., K.R. Wilson, D. Lewis, J. Broderick, J. Mao, and S.W. Breck. 2010. Roaring Fork Valley urban black bear ecology study: progress report to the Colorado Division of Wildlife. Contact Sharon Baruch-Mordo for copy. Email: sharonb_m@yahoo.com Beck, T.D.I. 1991. Black bears of west-central Colorado. Technical Publication No. 39, Colorado Division of Wildlife, Colorado. Garshelis, D.L., and H. Hristienko. 2006. State and provincial estimates of American black bear numbers versus agency assessments of population trend. Ursus 17:1-7. Hristienko, H., and J.E. McDonald Jr. 2007. Going into the 21st century: a perspective on trends and controversies in the management of the American black bear. Ursus 18:72-88. Johnson, H.E, C.J. Bishop, M.W. Alldredge, J. Brodrick, J. Apker, S. Breck, K. Wilson, and J. Beckmann. 2011. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Research Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Jonkel, J.J. 1993. A manual for handling bears for managers and researchers. Office of Grizzly Bear Recovery, United States Fish and Wildlife Service, Missoula, Montana. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64:183-193. Peine, J.D. 2001. Nuisance bears in communities: Strategies to reduce conflicts. Human Dimensions of Wildlife 6:223-237. Spencer, R.D., R.A. Beausoleil, and D.A. Martorello. 2007. How agencies respond to human–bear conflicts: a survey of wildlife species in North America. Ursus 18: 217–229. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31:517-520. Prepared by _______________________________________ Heather E. Johnson, Wildlife Researcher 146 �Table 1. Capture information for 65 bears ≥1 year old in the vicinity of Durango, CO. Unique ID B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 B13 B14 B15 B16 B17 B18 B19 B20 B21 B22 B23 B24 B25 B26 B27 B28 B29 B30 B31 B32 B33 B34 B35 B36 B37 B38 B39 B40 B41 B42 B43 B44 B45 B46 B47 Capture Date 5/10/2011 5/12/2011 5/13/2011 5/16/2011 5/16/2011 5/17/2011 5/17/2011 5/18/2011 5/26/2011 5/26/2011 6/3/2011 6/2/2011 6/3/2011 6/6/2011 6/6/2011 6/7/2011 6/7/2011 6/8/2011 6/9/2011 6/9/2011 6/10/2011 6/10/2011 6/13/2011 6/14/2011 6/15/2011 6/15/2011 6/16/2011 6/16/2011 6/21/2011 6/22/2011 6/24/2011 6/24/2011 6/28/2011 6/28/2011 7/5/2011 7/6/2011 7/7/2011 7/13/2011 7/13/2011 7/21/2011 7/22/2011 7/26/2011 8/3/2011 8/3/2011 9/3/2011 9/5/2011 8/8/2011 Sex M M M M M F F F M F M M M F M M F F M M F M M F F M F M M F M F M M F M M M M F M F F M M F F Estimated Age 1 5 5 3 6 3 6 3 1 4 8 5 3 6 3 7 6 6 9 10 7 8 3 8 4 10 10 6 1 4 4 1 1 3 3 4 1 8 6 5 3 6 8 2 6 3 8 Weight (kg) 35 144 130 84 135 63 64 52 35 81 130 103 59 58 58 117 52 62 147 132 69 88 65 65 64 109 75 101 49 60 85 19 35 85 44 67 39 145 150 81 67 70 85 35 176 58 54 147 Capture Location UTM Easting UTM Northing 246233 4142768 271495 4130889 271495 4130894 270950 4127914 270227 4139984 243210 4128716 243225 4133053 271478 4130892 238803 4126790 269869 4139040 252163 4137968 253216 4137387 253216 4138868 252157 4137967 253216 4138868 253216 4138868 256936 4134633 256918 4134625 235193 4128894 243258 4133040 252298 4136435 252163 4137968 246350 4135617 243252 4133030 239003 4134158 252164 4137966 243252 4133030 253233 4138873 239840 4126949 235911 4128916 239840 4126949 243252 4133030 239294 4133260 239001 4134154 246350 4135617 239840 4126949 243252 4133030 243236 4128710 251222 4133120 248550 4131645 237368 4132272 245945 4141391 246183 4142791 756124 4132494 245965 4139587 243435 4128720 251783 4131581 �Table 1-Continued Unique ID Capture Date 8/10/2011 B48 8/11/2011 B49 8/11/2011 B50 8/12/2011 B51 8/12/2011 B52 8/15/2011 B53 8/16/2011 B54 8/18/2011 B55 8/29/2011 B56 8/30/2011 B57 8/31/2011 B58 9/1/2011 B59 9/2/2011 B60 9/3/2011 B61 9/6/2011 B62 9/7/2011 B63 8/6/2011 B64 9/15/2011 B65 9/20/2011 B66 9/21/2011 B67 9/21/2011 B68 Sex F F F F F M M F M F M M F M M M M F F F M Estimated Age 1 3 7 12 4 7 2 3 10 3 3 15 2 7 1 2 1 5 1 3 8 Weight (kg) 26 55 101 62 65 163 53 49 167 46 48 153 35 214 23 37 30 91 41 54 209 148 Capture Location UTM Easting UTM Northing 245914 4139620 243435 4128720 245965 4139587 249049 4130370 245965 4139587 243435 4128720 251898 4130516 251464 4134423 246321 4132993 243374 4135903 243374 4135903 243952 4132935 242187 4133020 244602 4130321 245790 4128530 248612 4131251 245850 4141969 243948 4134848 240731 4130163 256930 4134626 249067 4133006 �Figure. 1. Land ownership in the vicinity of Durango, CO. 149 �Figure 2. Photos of a newly designed box trap to capture black bears. 150 �Figure 3. Location of bear hair-snare sites, mast survey transects, and capture sites around Durango, CO. 151 �Figure 4. Proposed treatment and control areas for an urban bear-proofing experiment and observations of garbage-related conflicts from pre-treatment monitoring. Red stars indicate evidence of bears foraging on human garbage, circles indicate the availability of human food for bears (green circles represent regular garbage containers and yellow circles represent wildlife-resistant containers). 152 �Figure 5. Adult female black bear GPS locations collected between May and September 2011 in the vicinity of Durango, CO (different colored circles represent different individual bears). 153 �APPENDIX I PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH FY 2011-12 – FY 2015-16 State of: Cost Center: Work Package: Task No. Federal Aid Project No. Colorado 3430 3003 : : : : : Division of Parks and Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Principal Investigators Heather Johnson, Mammals Researcher, Colorado Parks and Wildlife Chad Bishop, Mammals Researcher Leader, Colorado Parks and Wildlife Mathew Alldredge, Mammals Researcher, Colorado Parks and Wildlife John Broderick, Terrestrial Programs Leader, Colorado Parks and Wildlife Jerry Apker, Carnivore Coordinator, Colorado Parks and Wildlife Stewart Breck, Research Wildlife Biologist, National Wildlife Research Center Kenneth Wilson, Professor, Colorado State University Jon Beckmann, Associate Conservation Scientist, Wildlife Conservation Society Cooperators Melissa Reynolds-Hogland, Executive Director, Bear Trust International Tom Spezze, Southwest Regional Manager, Colorado Parks and Wildlife Patt Dorsey, Area Wildlife Manager, Colorado Parks and Wildlife STUDY PLAN APPROVAL Prepared by: Heather Johnson Date: 2/15/2011 Submitted by: Heather Johnson Date: 3/12/2011 Reviewed by: Jon Runge Date: 3/25/2011 Chuck Anderson Date: 3/14/2011 Danny Martin 4/4/2011 Biometrician: Paul Lukacs Date: 3/10/2011 Approved by: Chad Bishop Mammals Research Leader Date: 3/10/2011 154 �PROGRAM NARRATIVE STUDY PLAN FOR MAMMALS RESEARCH Black Bear Exploitation of Urban Environments: Finding Management Solutions and Assessing Regional Population Effects A Research Proposal Submitted by: Heather Johnson, Mammals Researcher, Colorado Parks and Wildlife Chad Bishop, Mammals Researcher Leader, Colorado Parks and Wildlife Mathew Alldredge, Mammals Researcher, Colorado Parks and Wildlife John Broderick, Terrestrial Programs Leader, Colorado Parks and Wildlife Jerry Apker, Carnivore Coordinator, Colorado Parks and Wildlife Stewart Breck, Research Wildlife Biologist, National Wildlife Research Center Kenneth Wilson, Professor, Colorado State University Jon Beckmann, Associate Conservation Scientist, Wildlife Conservation Society J. Need Conflicts among people and black bears (Ursus americanus) are increasing nationwide, as the human population grows and urban development expands in and around black bear habitat. In a survey of 41 state wildlife agencies that manage black bears, 30 reported increasing numbers of bear-human conflicts in recent decades (Hristienko and McDonald 2007). While state and federal wildlife agencies are responsible for minimizing bear-human conflicts, they are also responsible for maintaining viable bear populations. Achieving this balance is proving to be difficult, as agencies struggle to find effective management solutions while conflict rates continue to rise, particularly around urban areas (Tavss 2005, Baruch-Mordo et al. 2008). Whether increases in conflicts reflect recent changes in bear population trends or just behavioral shifts to anthropogenic food resources, is largely unknown, as bear population parameters have been exceedingly difficult to estimate (Garshelis and Hristienko 2006). The primary cause of black bear-human conflicts along the urban-wildland interface has been attributed to the availability of anthropogenic food resources to bears (Fig. 1; Spencer et al. 2007, Beckmann et al. 2008, Greenleaf et al. 2009). Urban areas contain a wealth of reliable, high-calorie foods, in the form of garbage, fruit trees, vegetable gardens, pet food, and bird feeders. As opportunistic foragers, bears readily exploit these resources, resulting in negative interactions with people. These interactions, however, have been highly temporally and spatially variable (Baruch-Mordo et al. 2010), generating uncertainty about the relative influence of natural food availability, conflict management, harvest, and bear population trends on driving annual variation in rates of bear-human conflicts. Without a thorough understanding of the factors that exacerbate nuisance bear behavior, and uncertainty about the relationship between conflict rates and bear dynamics, it has been difficult for wildlife agencies to initiate effective management practices. Bear use of the urban environment has serious consequences for people, bears, and wildlife managers. For people, bear-human conflicts lead to increased public safety concerns, property damage, and high management costs, while for bears they lead to increased mortality (Beckmann and Berger 2003, Beckmann et al. 2008, Hostetler et al. 2009). For 155 Figure 1. Black bear foraging on urban food resources. �example, in 2007 Colorado data analysis unit (DAU) B-11 reported >500 public safety and property damage conflicts with bears, resulting in >$500,000 expended by the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) in bear management. This is one of 19 bear DAUs in Colorado, and encompasses the towns of Aspen and Vail, which have been hotspots of bear-human conflicts. That year, in B-11 alone, 44 bears were euthanized for conflict control, 25 were translocated for nuisance behavior, 27 died of road kill, and 30 were legally harvested. Overall, this resulted in >75% of bear mortality attributed to conflicts with people, with unknown consequences for local bear populations. In addition to high management costs, these extreme conflict solutions have critical repercussions for wildlife management agencies. Because managers are obligated to respond to conflict calls, conflict management usurps limited resources and radically reduces those available for other programs. High conflict rates and unpopular management activities (i.e. lethal bear removals) also degrade the credibility of wildlife agencies to the general public, and ultimately reduce the inherent value of black bears in the public eye (Will 1980). Given expected changes in both human development and climate patterns, bear-human conflicts should rise in the future. As the human population grows, development will continue to permeate bear habitat, creating additional opportunities for conflicts with bears (Kretser et al. 2008). This situation will likely be exacerbated by anticipated changes in annual weather patterns. Drought conditions reduce the availability of natural foods for bears and are associated with an increase in bear-human conflicts (Zack et al. 2003, Baruch-Mordo 2007). Drier, warmer weather, as predicted with climate change, is expected to escalate conflicts with bears in the coming years.  Identify management strategies to reduce bear-human conflicts Ultimately, the public will not tolerate ever-increasing conflicts with bears and wildlife agencies must find effective solutions to resolve this pressing problem. Yet, despite the trajectory of increasing black bear-human conflicts, and the severe consequences of those conflicts for both people and bears, best management practices for reducing conflicts remain unclear. Managers commonly employ education (Gore et al. 2008, Baruch-Mordo et al. 2011), aversive conditioning (Beckmann et al. 2004, Mazur 2010), and increased harvest (Treves et al. 2010) to curb conflict rates, yet when the effectiveness of these strategies has been scientifically tested, they have been found to be largely ineffective as implemented. Investigators have suggested alternative approaches for reducing conflicts, such as reducing the availability of anthropogenic food for bears, using models to increase translocation success of nuisance bears, and altering public hunting programs to be spatially or temporally aligned to remove nuisance bears. These techniques may be useful for reducing conflicts, but their efficacy has not been rigorously tested. Removing anthropogenic food - Given that bears are attracted to anthropogenic food it is believed that eliminating the availability of this resource will dramatically reduce nuisance bear behavior (Peine 2001, Beckmann et al. 2004, Gore et al. 2005, Lyons 2005, Spencer et al. 2007). This strategy has had some success within national parks (Greenleaf et al. 2009), and anecdotally in some communities (Mammoth Lakes CA, Juneau AK, Whistler BC), but no research has ever scientifically tested the costs and benefits of “cleaning up” a town. Given the high price to operationally “bear-proof” a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. A thorough, rigorous evaluation of this approach would provide guidance to wildlife agencies and municipalities on the benefit of investing in bear-proofing infrastructure. Translocation Suitability Modeling - Translocation of nuisance black bears is another common management technique that has been applied with varied results (Rogers 1986, Linnell et al. 1997, Landriault et al. 2009). Often bear translocation decisions are handled by field managers without formal guidance. These professionals are knowledgeable on bear capture and transport techniques, but often lack the flexibility to release bears in other management areas without obtaining approvals from different managers, who are often also experiencing nuisance bear problems. Limitations in selecting a 156 �translocation site and the profound movement ability of bears can result in an unsuccessful translocation – where the bear continues to cause conflicts either in its new location or after returning to the capture site. To improve bear management, a strategic translocation approach is needed that applies the best available science on bear habitat quality, conflict potential, and harvest in the selection of bear release sites, while incorporating statewide collaboration among managers. Targeted Bear Hunting - Wildlife managers frequently increase harvest quotas to reduce bearhuman conflicts, but the scientific literature has been equivocal on the effectiveness of this approach (Obbard et al. 1997, Hristienko and McDonald 2007, Treves et al. 2010). Hristienko and McDonald (2007) found that states with higher harvest rates reported fewer conflicts, while other studies evaluating elevated harvest on region-specific spatial scales have concluded either no effect or increases in numbers of conflicts (Obbard et al. 1997, Tavss 2005, Treves et al. 2010). Lack of harvest success has been largely attributed to a mismatch between the timing and location of bear-human conflicts and the timing and location of the hunt, as bear-human conflicts peak during summer months along the urban interface while public hunting occurs during the fall in areas away from development (Treves et al. 2010). As a result, a general increase in harvest likely translates into a reduction in the population at large, not necessarily the removal of nuisance bears. This strategy also inherently assumes that conflict rates reflect bear population sizes, an untested assumption that could potentially lead to overexploitation. To determine whether public harvest can successfully curb conflict rates, hunts need to be spatially and/or temporally coordinated with conflicts as they occur. While this is a strategy that has the potential to reduce management-related conflict mortality, it has yet to be thoroughly evaluated.  Elucidate the dynamics of bear populations along the wildland-urban interface To sustainably manage bear populations in the face of a growing human population and changing landscape conditions, it is critical to elucidate the dynamics and drivers of bear populations. Of those factors that influence bear dynamics, the contribution of urban environments is the least understood, most contentious, and has the greatest potential to elicit major population change. While urban environments offer bears the benefit of anthropogenic food, they also inflict the cost of increased mortality from lethal removals, translocations, and other urban factors (i.e. road kills), yielding uncertainty about whether urban environments contribute to the growth or decline of local bear populations. In the two studies that have evaluated bear populations along the wildland-urban interface, bears experienced reduced survival with population-level consequences (Beckmann and Berger 2003, Hostetler et al. 2009). In Florida, Hostetler et al. (2009) found that reduced adult survival caused the “urban” bear population to decrease in size, while the adjacent “wild” population increased, demonstrating the possibility of source-sink dynamics. Meanwhile, in Nevada, Beckmann and Berger (2003) found that bears around urban development were present at higher densities and had greater reproductive rates, but cubs had exceedingly low survival. The researchers suggested that urban areas did not just operate as a sink but as an ecological “trap” as human food attracted bears into town only to lead to their demise and depopulate the adjacent wildlands. While these studies suggest that urban environments may reduce bear populations, many management agencies have assumed that increasing conflicts reflect increasing populations, and that the availability of anthropogenic foods has bolstered demographic rates. So, do urban areas serve as population sources or sinks for bears, and are these impacts static or do they vary under different conditions? Do urban environments operate as ecological traps, attracting bears into habitat that is maladaptive when suitable conditions exist elsewhere? This question is complicated by the influence of annual variation in natural foods, or environmental stochasticity, on bear behavior and demography. While Beckmann et al. (2004) and McCarthy and Seavoy (1994) report that bears habituated to anthropogenic foods regularly return to them, preliminary data from Aspen, Colorado also suggests that bears increase time spent in urban environments in years of natural food failure and decrease that use when natural foods are readily abundant (Fig. 2; Baruch-Mordo et al. 2010). This pattern implies that bears may avoid urban environments when conditions allow, despite the common assumption that a bear savvy to anthropogenic 157 �Figure 2. Annual distances between the home range and the center of town for a collared adult female bear in a good natural food year when she had no cubs (2005), a bad natural food year when she had no cubs (2007), and a good natural food year when she had cubs (2008; from Baruch-Mordo et al. 2010). foods will consistently be a “conflict bear.” In a state like Colorado, where human development has effectively permeated almost all tracks of prime bear habitat, the consistency of bear foraging behaviors has key implications for managers. For example, if a small subset of bears consistently causes a majority of the conflicts with people, then the removal of a few key individuals should alleviate the problem. If, however, high rates of conflict coincide with years of natural food failure because a large proportion of the population is seeking alternative food resources, such a removal strategy may be ineffective. Or perhaps a combination of these hypotheses are true, that a subset of bears cause a majority of conflicts until a food-failure “teaches” a new group of bears to use human foods, a pattern that is then repeated in subsequent years, despite natural food conditions. Currently, managers have no information about the proportion of bears that cause conflicts, how the use of urban resources varies among individuals, and how variation in the availability of natural foods drives temporal variation in urban resource-use. As agencies struggle to define conflict management practices with minimal information on population trajectories, understanding the effects of urban environments on bear demography is critical. Currently, conflict bear management practices (lethal removal and translocations) are based on several inherent assumptions such that 1) there is a correlation between bear-human conflicts and bear population size, 2) conflicts are caused by a few individual bears and their removal will alleviate local problems, and 3) management removals do not significantly influence regional bear dynamics or local harvest opportunities. The validity of these assumptions have yet to be determined, despite their importance for bear management. To develop sustainable management practices for black bears, we must tease apart the relative influences of annual variation in natural bear foods, the availability of anthropogenic foods, conflict-management (lethal removals and translocations) and harvest on bear dynamics and bear-human conflicts.  Develop better tools to monitor the dynamics and drivers of bear populations Despite the need to understand the drivers and trends of bear populations to direct management, Garshelis and Hristienko (2006) found that most states have limited data from which to make sound decisions. As a result, state agencies rely on coarse harvest indices that yield little power for detecting population change, and no ability to distill the underlying causes of change. New tools that increase the scientific rigor in monitoring bear populations are desperately needed, so that harvest quotas are biologically-based and designed to meet population objectives. Recent advances in wildlife statistics have focused on maximizing the use of traditional age/sexat-harvest data, that which is routinely collected during mandatory harvest reporting. New techniques are available to more effectively extract information about population trend from harvest data (Skalski et al. 158 �2007) and can be augmented with mark-recapture or radio-telemetry data to increase precision in parameter estimation (Fieberg et al. 2010, Johnson et al. 2010). While these approaches hold tremendous promise for supporting biologically-based bear monitoring and management, they are still in their infancy and have yet to be widely implemented. These techniques could be used to identify the value of different data types for tracking populations and to allocate field efforts that most efficiently determine bear population trends across a region of interest. Such information could also be used to inform annual harvest recommendations, elucidate statewide bear dynamics, and reconcile the relationship between bear population trends and conflict rates. K. Objectives 1) Test management strategies to reduce bear-human conflicts. Bear-human conflicts in urban areas of Colorado echo nationwide trends, as they are increasing in number, frequency, and severity, and have become a high priority management issue in all regions of the state (Baruch-Mordo et al. 2008, Colorado Division of Wildlife unpublished data). In evaluating strategies to reduce conflicts we will: 1A) Experimentally reduce the availability of anthropogenic food to bears in an urban environment to assess the effect on bear-human conflicts and bear behavior. 1B) Develop and evaluate a strategic statewide plan for the translocation of nuisance black bears. 1C) Assess a spatially-targeted bear harvest program designed to reduce the number of nuisance animals. 2) Determine the influence of urban environments on regional bear population dynamics. According to the 2010 U.S. Census, Colorado is the ninth fastest growing state in the country, with associated increases in housing and development (Mackun and Wilson 2011). Despite these trends, there is substantial uncertainty about the effects of urban habitats on bear habitat selection and population dynamics. To elucidate the effects of urban environments on bears we will: 2A) Evaluate the role of annual variation in natural foods on bear movement and resource-use. 2B) Estimate vital rates of urban and wildland bears relative to their resource-use patterns. 2C) Quantify the effects of resource-use, conflict bear management (lethal removals and translocations) and harvest on bear demography. 3) Develop population and habitat models to support the sustainable management of black bears in Colorado. Bear populations have been notoriously difficult to monitor for state wildlife agencies (Garshelis and Hristienko 2006). While meeting other project objectives we will obtain key biological data on bears from which we can: 3A) Use multiple data sources (harvest, DNA mark-recapture, and telemetry data) to develop improved bear population models to guide harvest regulations and inform estimates of population size and trend. 3B) Build regional habitat models to better predict bear density, direct the location of future monitoring efforts, and identify key seasonal resource areas. L. Expected Results or Benefits This will be one of the most comprehensive studies to date on bear-human conflicts and the ecology of urban and wildland bears, resulting in crucial information that will be used to manage black bears in Colorado and across the country. Results from this study will: • Quantify the relative effectiveness of different management strategies (anthropogenic food removal, translocations, and spatially-targeted harvest) for reducing bear-human conflicts, information which will be broadly used by wildlife managers. A reduction in bear-human conflicts will ultimately increase public safety, reduce property damage, decrease wildlife management costs, and gain management credibility for collaborating agencies. 159 �• Identify key differences in the demographic and behavioral patterns of urban and wildland bears to better inform managers about the efficacy of conflict-bear management (lethal removals and translocations) on bear behavior and population dynamics. For example, this study will elucidate the proportion of bears using urban food resources, how that proportion varies due to natural food conditions, the relationship between population performance and conflict rates, and whether “town” serves as a source, sink, or ecological trap. • Provide robust, data-driven population and habitat models to guide the monitoring and management of bears in Colorado. These models will be used to inform annual harvest regulations, revise statewide estimates of population size and trend, and direct the location of future data collection efforts. Such information will increase the scientific rigor that is applied to the management of bears in Colorado and ensure that management actions to minimize conflicts are consistent with population objectives. • Advance theory and statistical methodology for linking resource-use patterns of animals to their demographic rates, and ultimately, population growth. To date, habitat and demographic analyses have been largely conducted independently of one another, with a relationship that is often inferred rather than directly measured. Using intensive field population data and GPS collar locations, this study will explicitly link space-use, resource acquisition, and demographic patterns, exploring new conceptual and statistical avenues to elucidate their relationships. M. Approach 1A) Reducing the availability of anthropogenic foods to bears in an urban environment to assess the effect on bear-human conflicts and bear behavior. To test the effectiveness of reducing the availability of human food on reducing bear-human conflicts, we will conduct a large-scale experiment. We will drastically reduce the accessibility of anthropogenic foods known to attract bears (garbage, bird-feeders, pet food, etc) within a designated ‘treatment’ area, while simultaneously monitoring comparable ‘control’ areas where no action will occur. We will perform this experiment in Durango, Colorado, a town with one of the highest bearhuman conflict rates in the state as 200-900 conflicts were annually reported between 2007 and 2010 (see Fig. 3). This town has abundant human food resources available to bears and a definitive urbanwildland interface, where urban development is juxtaposed to high quality bear habitat. Figure 3. Locations of bear-human conflicts in Durango, Colorado from 2007-2010 are shown with yellow circles and proposed treatment and control areas are represented by black boxes. Within Durango we will specify a treatment area and 2 control areas focused on the core zones of bear-human conflicts (Fig. 3). Each area will contain approximately 500 structures (residences and businesses) and be roughly the equivalent in size (0.6 km2). The treatment will occur in northwest section of town, where the highest numbers of conflicts have been reported. In the treatment zone we will provide bear-proof garbage containers, 160 �canvass citizens to discourage food availability outside of secure structures (bird-feeders, pet food, etc), conduct daily patrols to remove human food and provide strict enforcement. Our primary control area will occur on the south side of the Animas River (a moderate barrier to bear movement), to facilitate independence among experimental units. Additionally, we will monitor a second “spillover” control area, adjacent to the treatment (north of the river) to measure the influence of the treatment on human behavior in adjacent neighborhoods. We will monitor treatment and control areas for 1 pre-treatment year and 4 post-treatment years, measuring changes in two key response variables: bear-human conflicts and bear behavior. We will define a “conflict” as any bear-human interaction that results in property damage or a threat to public safety, and compare the number of conflicts and their severity (i.e., a bear in a garbage can versus a bear breaking into a house) between treatment and control areas. Currently, citizens report conflicts to the Colorado Division of Wildlife, the non-profit organization BearSmart Durango, and the city newspaper; we will compile data from all sources for analysis. During the months bears are active, we will also conduct weekly patrols of treatment and control areas. Patrols will occur the morning that residential trash is collected, with an observer recording visible human food resources available to bears and evidence that bears have obtained human foods (i.e. trash cans knocked over and strewn garbage). We will use conflicts from treatment and control areas, and from pre- and post-experiment implementation to measure the effect of bear-proofing on the number and severity of urban bear-human conflicts. Additionally, we will monitor the influence of the food removal treatment on bear behavior. Bears living on the urban-wildland interface will be collared with global positioning system (GPS) satellite technology (see Objective 2 for capture and collaring details). GPS collars will automatically record the location of each bear every 4 hours, and we will use locations to conduct detailed resource selection analyses (Manly et al. 2002). Using selection indices from “in town” bear locations, we will test for differences in bear use among treatment and control areas (Blomquist and Hunter 2010, Boyce et al. 2010), and whether such use varies over the course of the active bear season. By tracking bear locations relative to our treatment and control sites, we should be able to quantify the benefits of ‘cleaning-up’ a community for reducing conflicts and modifying bear behavior in urban environments. 1B) Developing and evaluating a strategic plan for the translocation of nuisance black bears. To develop a strategic, statewide translocation plan, we will use existing information on black bears to map relative habitat quality, resource selection, nuisance potential, and hunter harvest potential across Colorado. These factors will be combined to generate a single layer depicting overall translocation suitability. Nuisance bears will then be allocated to release sites based on this suitability rating and their respective age, sex, reproductive status, management history (i.e. whether the bear was hazed), and distance to capture site. We will compare the success rates of bears translocated using the strategic approach with those of bears translocated following existing procedures, with success defined as a bear that does not engage in new conflict behavior. In all cases, bears will be marked using very high frequency (VHF) or GPS collars to quantify movements and fates following translocation. Additionally, we will augment information from newly captured bears with data from >80 bear translocations that have already occurred in Colorado. Translocation success will be analyzed in a known-fate, time-to-failure framework (Hosmer et al. 2008), where the translocation outcome is modeled as a function of the relevant covariates. If our strategic approach increases translocation success our model will be incorporated into a user-friendly, internet-based tool for wildlife managers to assist with translocation decisions in the field. Specifically, a wildlife manager would enter the bear characteristics and capture site into the internet program and be given a set of optimal release sites. When a bear is released, the wildlife manager would enter the date and location of release into the program, which would be used to update subsequent releasesite decisions. 161 �1C) Assessing a spatially-targeted bear harvest strategy designed to reduce nuisance animals. Managers in southeast Colorado are responding to high numbers of conflicts by increasing harvest rates, however, they are using a novel approach. Rather than implement unit-wide increases in harvest quotas, managers will be spatially targeting hunting pressure in zones adjacent to conflict hotspots. These new harvest management zones are expected to be implemented in fall 2011 with the goal of reducing bear densities in areas bordering the urban interface (see example in Fig. 4). We will measure the success of this strategy for reducing conflicts in the communities of Colorado Springs, Pueblo, and Colorado City; cities which report hundreds of conflicts/year. Using nuisance reports from pre- and postimplementation of this strategy, we will compare the number of conflicts, conflict severity, and numbers of translocated and euthanized bears. Colorado Division of Wildlife has recorded these metrics for the past 16 years, and will continue to collect this data in the future. In addition, we will compare harvested numbers of bears in the DAUs in which these cities are located (B2 and B7) pre- and post-implementation of the new strategy, to determine its effect on meeting annual bear harvest objectives. With ≥3 replications of this approach (around different urban centers) we will examine whether a spatiallytargeted harvest approach, executed by the public, significantly decreases urban bear conflicts while increasing hunting opportunities. 2A) Evaluating the role of annual variation in natural foods on bear movement and resource-use. While anthropogenic food is consistently available to bears in urban environments, the availability of natural foods can dramatically fluctuate based on annual patterns in temperature and precipitation. For example, late frosts and summer droughts can cause failures in the local berry and acorn resources, forcing bears to expand their search for calories and potentially increase their use of urban environments (Zach et al. 2003, Baruch-Mordo 2007, Baruch-Mordo et al. 2010). To determine the influence of annual variation in natural foods, or environmental stochasticity, on bear habitat-use we will evaluate location data from GPS collared adult females. From June through September, we will capture bears using culvert traps, box traps and Aldrich snares following the techniques described in Jonkel (1993, Appendix 2). Captured adult famles will be fitted with a Vectronics collar with a degradable spacer, ear-tagged, weighed, and measured for morphometric characteristics. Additionally, we will pull a tooth for age determination and obtain a blood sample for DNA. See Detailed capture and handling protocols are provided in Appendix 2. Each year we will attempt to maintain a sample of 50 collared females, with approximately half collared in and around the town of Durango (La Plata county), and the other half in the surrounding wildlands (La Plata, Hinsdale, and Archueta counties). This collaring strategy Figure 4. The hatched-blue area represents the proposed bear conflict harvest zone on the wildland-urban interface near Pueblo, CO. 162 �will allow us to track a range of resource-selection patterns of bears, from those that are heavily dependent on human foods to those that rely exclusively on natural foods, quantifying the proportion of bears using urban resources and their frequency of urban habitat-use. We will also use GPS location data to examine resource selection and movement patterns in response to temporal variation in natural food availability (see Figs. 2 and 6). To do this we will partition location data into weekly intervals and use a repeated-measures resource selection function (RSF) approach (Manly et al. 2002, Börger et al. 2006, Kie et al. 2010, McLoughlin et al. 2010). We will determine those factors that drive temporal resource selection, evaluating the availability of natural foods, changes in weather patterns, distance to town, reproductive status, and conflict management history (i.e. whether the animal was hazed, trapped, etc). We will also evaluate the influence of these covariates on the size of bear home-ranges and their rates of seasonal movements (Jonsen et al. 2005, Morales et al. 2010). Additionally, we will employ a time-to-failure analysis to examine those covariates (listed above) that predict when a bear will “fail” and use urban resources (Cook and Lawless 2007, Hosmer et al. 2008). We will work with colleagues in the Remote Sensing/Ecology program at Colorado State University to develop satellite image signatures to track annual vegetation productivity for natural bear foods. To quantify weather patterns, we will use PRISM spatial data (http://www.prism.oregonstate.edu/) which interpolates monthly temperature and precipitation patterns across landscapes, accounting for elevation and topography. All covariates related to human development will be extracted from existing CPW digital data layers. Ultimately, these analyses will not only allow us to summarize patterns of movement and resource-use, but elucidate the underlying drivers of bear behavior, providing insight for the design of better management strategies to minimize conflicts. 2B) Estimating the vital rates of urban and wildland bears relative to their resource-use patterns. To assess differences in the population dynamics of those bears that use urban food resources versus those that do not, we will track the demographic trends of female bears collared in adjacent urban and wildland habitats. We are concerned with the vital rates (survival and reproductive rates) of female bears, as they represent the reproductive segment of the population and should provide reliable inference to the population at large. We will monitor ~50 GPS collared bears each year for their annual survival, fecundity, and the survival of their cubs; collecting this data for a total of 5 years. Survival of adult females will be tracked with real-time GPS locations, and all mortalities will be immediately investigated. To estimate annual fecundity and cub survival, we will inspect the winter natal dens of collared females for the presence of newborn and yearling cubs. If a newborn cub is observed with an adult female in year t, but is not observed in the den with that female in year t+1, we will assume the cub is dead (Obbard and Howe 2008). Based on power analyses, our target sample size and study timeframe should allow us to detect biologically significant differences among the demographic rates of bears that use urban and wildland habitats, while still being logistically feasible (Fig. 5). In conducting power analyses to determine samples Figure 5. Power to detect significant differences (alpha = 0.05) in vital rates between bears using urban habitats and those that do not, based on the sample sizes of each group. 163 �sizes for adult female survival, we assumed a baseline survival rate of 0.90 with a standard deviation of 0.20 (Beck 1991, Koehler and Pierce 2005, Obbard and Howe 2008, Hostetler et al. 2009). The only study that has measured differences in adult female survival between urban and wildland bears found a 20% reduction in the survival of “urban bears” (Hostetler et al. 2009). With a sample of ~50 collared bears/year (~25 in urban habitat and ~25 in wildland habitat) for 5 years, we should have power ≥ 0.8 to detect at least a 15% difference in the survival of those bears that use urban habitats and those that do not. Similarly, assuming that adult female fecundity is 0.44 (Beck 1991) with a standard deviation of 0.25 (Hebblewhite et al. 2003), we expect to observe >150 cubs in dens over the course of the study. This number will yield power ≥ 0.9 to detect a significant difference of ≥30% in the fecundity rates of urban and wildland bears; Beckmann and Berger (2003) reported >60% difference in fecundity rates of bears in these different habitats. Using GPS location data, we will model the demographic rates of individual bears as a continuous function of how they use urban and wildland habitat, explicitly linking habitat-use to population performance (McLoughlin et al. 2007, Gaillard et al. 2010). To estimate annual adult female survival we will use Cox proportional hazard models (Therneau and Grambsch 2000, Murray 2006), which allow for staggered entry, continuous-time data collection, and the evaluation of different covariates. We will use multinomial and binomial logistic regression to model fecundity and cub survival rates, respectively (Obbard and Howe 2008), which will rely on annual counts of juvenile bears in winter dens. In these models, we will insert random effects to account for fecundity rates of individual females measured over multiple years, and for the survival of cubs born in the same litter. With all vital rate models we will use GPS data to specifically test whether time in urban habitats, annual availability of natural foods, or density of urban development influences bear population parameters (McLoughlin et al. 2007, Gaillard et al. 2010). Annual variation in natural foods will be tracked with satellite imagery (Pettorelli et al. 2005) and information on urban development will be obtained from existing digital data layers. We will also test for the covariate effects of year (to account for variation in natural foods), age (for adult survival and fecundity models), season (for adult survival models) and reproductive status (for adult survival models). We will build a set of apriori candidate models for each vital rate from our covariate set, and identify the best models using model selection (Burnham and Anderson 2002). Additionally, for adult female bears, we will evaluate cause-specific mortality. We will use competing risks analyses (Heisey and Patterson 2006) to examine the differential sources of mortality and their relative importance in urban and wildland habitats. 2C) Quantifying the relative influence of resource-use, conflict bear management practices (lethal removals and translocations) and harvest on bear demography. Vital rate means and variances measured from Objective 2B will then be inserted into stagestructured matrix projection models (Caswell 2001, Morris and Doak 2002) to assess differences in the population growth rate among those bears that use urban food resources (“urban”) and those that do not (“wildland”; Hostetler et al. 2009). The wildland model will serve as a baseline, representing bear demography in the absence of urban food or conflict management, and in the presence of natural food variability. Of those bears that use urban environments, we will then simulate a suite of scenarios to tease apart the inherent effects of anthropogenic food, management-related conflict mortality (i.e. lethal removals and translocations), other urban-related mortality (i.e. road kill, electrocution, etc), and harvest on vital rates, and ultimately, population growth (Fig. 6). First, we will project a matrix with vital rates from bears that used town to estimate the actual (or realized) growth rate. This model will allow us to compare harvest rates among bears that use urban versus wildland habitats. Second, we will quantify the inherent benefit of anthropogenic food for bears in the absence of all harvest and urban conflict mortality. To do this we will re-calculate adult female survival censoring all harvest and conflict-related deaths/removals (management and non-management related). We will use the updated values, along with cub survival rates from wildland bears (conservatively assuming that in the absence of human-related mortality “town” cubs would have survival ≥ than those in the wild) to re-project population growth rates (Hostetler et al. 2009). This will allow us to assess the inherent, but hypothetical, benefit of human food 164 �on local bear demography without urban-related mortality. Third, we will isolate the impacts of conflict management removals (lethal removals and translocations) on bear populations. For this scenario, we will re-calculate adult and cub survival by censoring all management-related removals (but maintaining harvest and non-management mortality), and insert these new values into a projection matrix. This will allow us to estimate the change in population growth associated with current conflict management practices and estimate their cumulative impacts on local populations. Additionally, for all scenario matrices, we will identify those vital rates with the highest elasticity and those driving overall growth rates (Wisdom et al. 2000, Caswell 2001). This will allow us to better understand how patterns of population growth respond to vital rate-specific changes in natural and human food availability, conflict management, and harvest. In addition to tracking the drivers of individual bear vital rates, we will also assess changes in population density. Density will be estimated from hair-snare grids using mark-recapture techniques (Woods et al. 1999, Mowat Figure 6. Conceptual model depicting 1) the and Strobeck 2000). Bear DNA will be extracted and different factors that affect bear resourcegenotyped from hair to effectively “mark” individual bears use, 2) that resource-use influences bear and the pattern of “recaptured” animals will be used to susceptibility to harvest and conflict estimate population size. We will set up one hair-snare grid removals, and, 3) how the combined impacts around the town of Durango and another grid in adjacent of resource-use, harvest, and conflict wildland habitat, monitoring each grid for 4 years (Fig. 7). removals determine stage-specific vital Each grid will be composed of 36 cells that are 4km x 4km rates, and ultimately, population growth. in size. We will collect bear hair from two different sampling sources within each cell, a baited scent trap and a natural rub tree. Baited scent stations will be surrounded by barbed wire to collect hair from bears as they climb around the wire to investigate the bait. We will use multiple bait scents, randomly assigned to different traps each sampling occasion to maintain a high hair recapture rate. Additionally, we will attempt to identify 1 natural rub tree/cell. Rub trees will not be baited, but affixed with a piece of barbed wire to facilitate hair collection. By collecting hair from both these sources (baited traps and rub trees) we should increase recapture rates and reduce individual heterogeneity in capture response (Boulanger et al. 2008). We will conduct 6 sampling occasions/summer (mid-June through July), checking baited traps and rub trees for hair once/week, and re-baiting scent traps. At the end of the sampling season hair samples will be sent to the Wildlife Genetics International Laboratory for microsatellite genotyping. We will use genotype data to estimate density using a spatiallyexplicit Bayesian model for open populations (Gardner et al. 2009, Gardner et al. 2010). Additionally, we use the genotype data to interpolate a spatial density surface that will allow us to identify habitat covariates associated with high and low bear densities in both urban and wildland sampling grids. We will compare densities among sites to determine whether the availability of human food increases bear density adjacent to town (Beckmann and Berger 2003). Over the course of the study we will also estimate the annual variability in density among urban and wildland habitats. This will elucidate whether densities in each habitat type vary in association with natural food production, and the reliability of the hair-snare technique for “snapshot” density measures for statewide monitoring purposes. Additionally, hair-snare grids will allow us to infer movement of bears from wildland to urban habitats. For example, if high bear densities are maintained along the urban interface despite negative population growth rates (as projected from individual vital rates), it will be suggestive that bears are moving into 165 �Figure 7. Location of urban and wildand DNA hair snare grids. Red circles represent sampling baited traps sites within each cell. Yellow circles represent conflicts reported around Durango, 2007-2010. town from adjacent wildlands (Robinson et al. 2008). Ultimately, using data on both the vital rates from collared animals and density from hair-snares, we will be able to discriminate whether town serves as source or sink for local bear populations, whether this influence varies under different environmental conditions. 3A) Using multiple data sources to build bear population models to inform annual harvest management and elucidate population trajectories. We will use individual vital rate and mark-recapture data from Objective 2, in conjunction with annual harvest data, to develop more precise population models for the management of black bears in Colorado. Currently, it is mandatory for hunters to report all harvested bears to Colorado Division of Wildlife and submit a tooth for age estimation (Willey 1974, Stoneberg and Jonkel 1996). Combining the three different data types we will have available on bears around Durango (sex/age-at-harvest, individual demography from collared bears, and mark-recapture data) we will first estimate baseline population parameters, dramatically increasing precision in those estimates (Fieberg 2010, Johnson et al. 2010). Then, we will identify the value of each data type (based on sample size and years of data collection) for modeling bear dynamics according to the precision required for making management decisions. This information will be used to generate a parsimonious model that adequately describes changes in bear population trends while minimizing unnecessary field data. In doing this, we hope to provide guidance to the Colorado Division of Wildlife on the allocation of field efforts for effectively monitoring populations, and allow managers to set biologically-based harvest quotas. We will test the accuracy and effectiveness of population models using data collected around Durango, Trinidad, and Aspen (all areas where multiple bear data types are available), and simulated data, allowing us to further validate model structure and precision (Fieberg et al. 2010). These models will be used to inform annual harvest regulations, update population trajectories, and revise statewide estimates of population size. 3B) Developing regional habitat models from GPS collar location data. We will use the wealth of GPS collar data that we will collect around Durango and which is available from ~40 bears around Aspen (CPW, unpublished data) to build detailed regional habitat models. Currently, bear habitat models for Colorado are derived from the perceived value of different vegetation types, as determined by Colorado Division of Wildlife managers. We hope to enhance regional models through analyses of thousands of bear GPS locations, using additional information on elevation, topography, satellite measures of annual primary productivity, and human development variables (i.e. road density, distance to town, etc). We will use a mixed-effects RSF approach to identify habitat characteristics associated with bear occupancy, applying a use-availability design (Manly et al. 2002, Gillies et al. 2006). We will specifically identify second-order habitat selection (Johnson 1980), the 166 �conditions under which bears establish their home-ranges, using established model selection procedures (Burnham and Anderson 2002). To test the predictive power of the habitat model, we will use crossvalidation (Boyce et al. 2002) and then map expected relative probabilities of selection across the landscape. Additionally, we will use harvest locations and bear sightings from other geographic regions to test the validity of our models for application in other parts of the state. These data-driven habitat models can then be used to provide better estimates of statewide bear density, design more efficient monitoring strategies (Allen et al. 2008), and to identify critical seasonal resources and movement corridors for bears. N. Location Data used to meet different objectives of this study will be obtained from various parts of Colorado. The anthropogenic food removal experiment (Objective 1A) and the demography/resource-use portion of the study (Objective 2A-C) will be conducted in the vicinity of Durango, Colorado (La Plata, Hinsdale, and Archuleta counties). Durango was selected as the focal urban environment based on several factors including a history of high bear-human conflicts (Fig. 3), a good record of recent conflict reporting, the feasibility of conducting the food-removal experiment (based on city waste management practices), and minimal city-wide bear-proofing infrastructure. Tracking bear population parameters in this region will require that trapping and hair-snaring will occur on a combination of USFS, BLM, state, city, and private lands.We will test the effectiveness of a spatially-targeted harvest program along the southern Front Range (Objective 1C), and opportunistically throughout the state as changes occur in harvest management. The strategic translocation model will be developed on a statewide basis (Objective 1B), along with population and habitat models (Objectives 3A-B). O. Schedule of Work Activity Trap and collar bears Monitor bear survival Conduct DNA hair-snare grids Genotype hair samples Distribute bear-resistant containers Monitor human-food-removal experiment Translocation modeling and evaluation Implement spatially-targeted harvest program Evaluate spatially-targeted harvest program Conduct winter den checks (reproduction) Estimate population parameters (individual vital rates, and population density) Develop and test population and habitat models 167 Timeline Summer 2011-2015 Summer 2011-2016 Summer 2011-2014 Fall 2011-2014 Spring 2012 Spring-Fall 2012-2015 Summer-Fall 2012-2015 Fall 2012 2012-2015 Winter 2012-2016 Winter 2012-2016 Winter 2013-2017 �P. Estimated Costs NEED INDIVIDUAL DEMOGRAPHY (5 Yrs) 50 GPS Collars (10 Purchased) GPS Battery Replacements (2/ea) Telemetry Receivers/Ant (3) Traps (20) Snares (10) Jab Stick (1) Misc Equipment Snowmobiles Field Technicians Spring Trapping Yr 1 (3.5mo) Spring Trapping Yrs 2-5 (3.5 mo) Winter Dens Yrs 1-5 (3 mo) COST/UNIT FY2011-12 $4,800 $300 $695 $1,000 $100 $800 $192,000 3 & Maintenance TechI (3)/TechII (1) TechI (1)/TechII (1) TechI (3)/TechII (1) 2 DNA HAIR-SNARE GRIDS (4 Yrs) Field Equipment Field Technicians (2.5 mo) TechI (2) Genetic Analysis $20,000/Grid GARBAGE EXPERIMENT (4 Yrs) Bear-resistant containers Residental/Commerical Field Technicians (5 mo) TechI (1) TRANSLOCATION PLAN (4 Yrs) Store-on-Board GPS Collars (50) $1,500 Web Programmer (1 mo) Programmer (1) PROJECT TOTAL FY2012-13 FY2013-14 FY2014-15 FY2015-16 TOTAL $5,000 $5,000 $5,000 $5,000 $5,000 $5,000 $5,000 $5,000 $192,000 $30,000 $2,085 $20,000 $1,000 $800 $30,000 $40,000 $31,984 $19,301 $31,984 $19,301 $31,984 $19,301 $31,984 $19,301 $31,984 $37,209 $77,204 $159,920 $1,200 $12,792 $40,000 $250 $12,792 $40,000 $250 $12,792 $40,000 $250 $12,792 $40,000 $1,950 $51,168 $160,000 $12,792 $250,000 $51,168 $30,000 $2,085 $20,000 $1,000 $800 $10,000 $20,000 $37,209 $250,000 $12,792 $12,792 $12,792 $75,000 $75,000 $3,200 $3,200 $369,070 168 $452,119 $157,119 $130,319 $74,077 $1,182,704 �Q. 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Modeling survival data: extending the Cox model. Springer, 171 �New York, New York. Treves, A., K.J. Knapp, and D.M. MacFarland. 2010. American black bear nuisance complaints and hunter take. Ursus 21:30-42. Will, G.B. 1980. Black bear-human conflicts and management considerations to minimize and correct these problems. Proceedings Eastern Workshop on Black Bear Management and Research 5:7587. Willey, C.H. 1974. Aging black bears from first premolar tooth sections. Journal of Wildlife Management 38:97-100. Wisdom, M.J., L.S. Mills, and D.F. Doak. 2000. Life stage simulation analysis: estimating vital-rate effects on population growth for conservation. Ecology 81:628-641. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31:517-520. 172 �APPENDIX II CAPTURE AND HANDLING PROCEDURES FOR FREE-RANGING BLACK BEARS Black bears will be initially captured and collared during the summer months and annually recaptured in their dens during winter months to obtain reproductive information. Summer We will capture and collar adult female black bears during summer months (May-Sept) using cage traps and foot snares. We will use cage traps in areas close to Durango or with high human activity, and where there is good road access. Snares will be used for more remote trapping locations, away from human activity and where vehicle access is limited. Once a bear has been captured using either method, field crews will use an identical protocol to process animals. Cage Traps We will capture bears with two different trap designs, a cage trap designed and used extensively by Beck (1993), and a newly designed trap to specifically target female bears. The trap developed by Beck is 1.8 m long and 1.0 m in height and width. The frame is constructed of angle iron, all side and top panels are wire mesh of 1.9 x 1.9 in size, and the trap has a floor that is 16-gauge steel. A spring-powered, solid aluminum door is mounted on a full-length hinge at one end and a latching mechanism holds the door closed. The door is triggered via a treadle pedal on the floor, and a standard garage door coil spring provides closing power. A hinged panel along the back of the trap allows access for administering immobilizing drugs via jabpole. In total, the trap weighs approximately 236 kg. In the first study in which these traps were used, only 1 bear in 134 captures was injured, as the individual broke a canine on the wire mesh. Because we are specifically interested in capturing and collaring female black bears, we worked with Mat Alldredge, Tom Davies, Lyel Willmarth and others to design a smaller, lighter trap that would discourage the capture of large males and increase portability in the field. These traps were built to be slightly larger than those that have been successfully used for cougars (Alldredge et al. personal communication) and are 34in high, 60in long, and 25in wide. The frame is built with 1x1in heavy gauge steel, covered with 1x1in heavy gauge, high tinsel, steel mesh. The smaller dimensions of the mesh will reduce the possibility that animals will break their teeth on the cage. The sides of the trap have additional braces to increase overall strength and support. The door of the trap comprises one end of the structure and is designed drop and latch to the bottom of the frame. Bait is hung from a cable attached to an archery trigger, and the door falls shut when the trigger is released. Due to the smaller size of the trap, it only weighs approximately 60 kg. Cage traps will be positioned so they are in the shade, and exposure to sun and precipitation is minimized. All cage traps will be clearly marked with warning signs. Cages will be baited with rotting fish, fruit, or road kill. They will be set in the late afternoon or evening and checked by field crews the following morning to minimize the time an animal spends in a trap. If the bear can be clearly identified as a male in the trap, or the bear is a cub or yearling (too small for a GPS collar), it will be released without being immobilized. If the bear is an adult female, or there is uncertainty in the sex of the adult bear, it will be immobilized following procedures described below. Bears will be immobilized with a jabpole, syringe pole, or syringe (hand injection), with the injection targeted into muscle tissue along the shoulder or thigh. Aldrich Foot Snares Aldrich foot snares were specifically developed to capture bears and have proven to be safe and effective (Jonkel 1993). The spring activated snare secures a ¼ inch steel cable around the foot of the bear, closing tight with the action of a small piece of angle iron fashioned into a sliding lock mechanism. 173 �The inside of the snare loop is wrapped with duct tape to minimize surface abrasion on the skin of the foot. We will modify snares with additional duct tape and/or surgical tubing over the cable to serve as a “cub stopper” such that small bears (cubs and yearlings) have a low probability of being captured (Jonkel 1993). An in-line swivel is placed in the cable to avoid torsion of the foot and a potential bone fracture. A short lead is attached to the snare to further minimize stress to the leg. The lead is then secured to an anchor tree at least 10 inches in diameter with a ¼ in steel cable clamped and stapled to the base of the tree so the bear cannot climb it. Branches of the tree are lopped off with a saw or axe about 8 ft up, so the bear cannot hang itself from a branch by the snare cable. An area of ≥5 meters is cleared around the snare site to eliminate potential that the bear is able to twist the snare loop around any obstacles (saplings, brush, etc). Large branches will be angled over the snare to force ungulates to step over or go around it, minimizing the possibility of catching non-target animals. Additional details of setting snares can be found in Jonkel (1993). A disadvantage of using foot snares is that all bears that are caught (even if they are a male bear or too small to collar) must be immobilized to be released. Other non-target animals that are caught (i.e. mountain lions, coyotes, etc) will be immobilized with Telazol and released. Snares will be set in the evening and checked in the morning, operated when ambient temperatures are between 32 and 90°F. Snared bears will be immobilized using a jabpole or CO2 dart gun with the injection targeted into muscle tissue along the shoulder or thigh. Animal Processing During summer months bears will be anesthetized with butorphanol, azaperone, and medetomidine (BAM), a drug combination that has been successful immobilizing black bears and is reversible with atipamezole (a medetomidine antagonist), allowing a faster and safer release of animals around urban environments (Wolfe et al. 2008). BAM will be administered at a volume of 0.4ml/23kg (50 lbs) with a dosage of 0.26mg/kg for butorphaneol, 0.22mg/kg for azaperone and 0.09mg/kg for medetomidine. We will initially give the recommended dose based on estimated animal weight and boost as necessary by ½ and ¼ of the original dose for the first and second boosters, respectively. To reverse immobilization we will intravenously administer atipamezole. We will dispense a volume of 1ml/1ml at a dosage of 5mg/1mg of medetomidine or 0.45mg/kg. One dose should be sufficient to reverse BAM. Bears immobilized with BAM should not be consumed for 45 days afterward, information which will be printed on collars and ear-tags (see below). Following the injection of BAM, field personnel will approach and gently prod the bear to ensure that the animal is fully anesthetized, administering additional doses as needed. Once anesthetized, the bear will be removed from the trap or snare and placed in a sternally recumbent position with front and rear legs extended. If the bear will not be collared (either because it is a male or too young) it will be subcutaneously injected with a passive integrated transponder (PIT) tag and marked with a single black or brown ear-tag that is labeled with the appropriate consumption date information. Afterwards, the bear will be administered atipamezole and released. Adult female bears will be discriminated from subadults based on weight, and nipple size and coloration (Beck 1991). Adult female bears will be fully processed. They will immediately be treated with eye ointment and blindfolded to reduce visual stimuli and protect the eyes from debris and bright light. Throughout the time a bear is anesthetized, its vital signs (heart rate, respiration and temperature) will be monitored. Normal ranges for vital rates of adult bears: heart rate = 60-90 beats/minute, respiration = 15-20 breaths/minute, and temperature = 99.6 - 101.0°F (Jonkel 1993). If a bear’s body temperature exceeds the normal range, field staff will cool the underside of the bear with water, particularly the arm pits, groin and stomach. If heart rate and respiration values fall outside normal expectations we will reverse the anesthesia and release the bear. 174 �In processing female bears, we will check each animal for any lacerations that occurred in the capture process and treat them with topical antibiotics. Additionally, bears will be given an injection of Oxytetracycline (9mg/lb) or Baytril (7.5 mg/kg) to reduce chances of infection from darting and tooth extraction (described below). Adult female bears will be subcutaneously injected with a PIT tag. If the individual has been identified by CPW Area staff as a “conflict” bear it will be marked in accordance with CPW Administrative Directive W-2. Individuals will be weighed using a portable spring scale and pulley system and their breeding status will be recorded (lactating, cubs present, evidence of suckling, etc). We will take multiple body size measurements including total length, chest girth and neck girth. During winter months we will also use bioelectrical impedance analysis to measure bear body fat (Farley and Robbins 1994, Hilderbrand et al. 1998). Additionally we will draw blood and collect a hair sample. These samples will be used for genetic, stable isotope, and telomere analysis. To age captured bears using tooth cementum annuli counts (Stoneberg and Jonkel 1966, Willey 1974), we will remove the first vestigial premolar (or if unavailable the lower first premolar) using a dental elevator. For tooth extraction, we will topically apply Lidocaine and subcutaneously administer Ketofen for analgesia (1cc/100lb). A piece of foam gel will then be placed on the removal site and left for adhesion and filling of the wound. We will attach a GPS collar (~700 g) with a ~2 year life expectancy. Collars will be programmed to collect ≥3 locations/day, and will be labeled with the appropriate consumption date based on immobilization. The GPS collar will include a VHF transmitter that allows tracking via standard telemetry equipment and the retrieval of collars. We will recapture each collared female each winter to assess fecundity and cub survival. If we are unable to recapture a bear, however, each collar will have a degradable canvas spacer that should break-down within 1-2 years and allow the collar to fall off. GPS collars will upload the location of each individual every day via a satellite system and the location will be available to researchers in real-time. When animal processing procedures are completed, the blindfold will be removed and the immobilization reversal will be administered. Field staff will observe the bear from a safe distance to ensure that the animal recovers to a standing position (Wolfe et al. 2008). Winter Den Checks To assess fecundity and cub survival we will recapture collared female bears each winter. Bears will be tracked to their dens using GPS collar locations, and researchers will dig through the snow as needed to access the den. Adult female bears and accompanying yearlings will be anesthetized with Telazol using a jabpole or CO2 dart gun. Telazol will be administered intramuscularly with a dose of 1.5 – 2.5mg/lb at a lower concentration (5cc at 100mg/ml). Bears will be immobilized at a higher concentration (3cc at 166 mg/ml) if they are particularly agitated or large. We will initially give the recommended dose based on estimated animal weight and boost as necessary by ½ and ¼ of the original dose for the first and second boosters, respectively. Unlike BAM, there is no reversal drug for Telazol. That said, an immobilized bear can be returned to its den for recovery, reducing animal stress and increasing researcher safety. Once immobilized, bears will be removed from the den, placed on blanket, and processed in a similar manner to that described above. Field staff will check the fit of the GPS collar and make any necessary modifications, and clean up any neck wounds with saline solution. Newborn cubs in the den will be tucked inside the jacket of a field crew member, next to their body, so that the cub says warm and quiet. After processing, bears will be returned to the den; adults and yearlings will be positioned on their side and newborn cubs will be placed on their mother’s back. The den entrance will be covered with sticks and boughs and a layer of snow to discourage the bear from leaving the den. We will retain a small opening in the snow to ensure that the bear has a fresh supply of air (Jonkel 1993). 175 �Injuries and Euthanasia If an animal is seriously injured (e.g. fractured or broken appendage, vertebrae, pelvis, or jaw, severe dislocation, laceration or any other injury that severely compromises its ability to survive and/or causes severe pain or distress) during capture, it will be quickly and humanely euthanized. Bears will be deeply anesthetized with BAM or Telazol and euthanized via a intravenous potassium chloride (KCl; 400-800 mEq) injection or gunshot to the head or neck. Carcasses that are euthanized will be disposed of in a landfill or left in an area appropriate for scavengers. LITERATURE CITED Beck, T.D.I. 1991. Black bears of west-central Colorado. Technical Publication 39, Colorado Division of Wildlife, Fort Collins, Colorado. Beck, T.D.I. 1993. Development of black bear inventory techniques; job progress report. Colorado Division of Wildlife, Project Number W-153-R-6. Farley, S.D., and C.T. Robbins. 1994. Development of two methods to estimate body composition of bears. Canadian Journal of Zoology 72:220-226. Hilderbrand, G.V., S.D. Farley, and C.T. Robbins. 1998. Predicting body condition of bears via two field methods. Journal of Wildlife Management 62:406-409. Jonkel, J.J. 1993. A manual for handling bears for managers and researchers. Office of Grizzly Bear Recovery, US Fish and Wildlife Service, University of Montana, Missoula, Montana. Stoneberg, R.P., and C.J. Jonkel. 1966. Age determination of black bears by cementum layers. Journal of Wildlife Management 30:411-414. Willey, C.H. 1974. Aging black bears from first premolar tooth sections. Journal of Wildlife Management 38:97-100. Wolfe, L.L., C.T. Goshorn, and S. Baruch-Mordo. 2008. Immobilization of black bears (Ursus americanus) with a combination of butorphanol, azaperone, and medetomidine. Journal of Wildlife Diseases 44:748-752. 176 �Colorado Division of Parks and Wildlife July 2010 –June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 : : : : Division of Parks and Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates On the Uncompahgre Plateau Federal Aid Project No. Period covered: July 31, 2010−June 30, 2011 Author: K. A. Logan. Personnel: K. Logan, A. Butler, B. Dunne, W. Hollerman, C. Jacobs, W. Jesson, J. Knight, B. Nay, R. Navarrete, J. Waddell, S. Waters, T. Bonacquista, K. Crane, J. Koch, and G. Watson of CPW; volunteers and cooperators including: private landowners, Bureau of Land Management, Ridgway State Park, Colorado State University, and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) initiated a 10-year study on the Uncompahgre Plateau in 2004 to quantify puma population characteristics in the absence (reference period, yrs 1-5) and presence (treatment period, yrs 6-10) of hunting. The purpose of the study is to evaluate assumptions underlying the Colorado Parks and Wildlife’s model-based approach to managing pumas with sport-hunting in Colorado. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 pumas for population research purposes on the Uncompahgre Plateau (Logan 2009). This report informs on the second year of the treatment period (TY2), August 2010 through July 2011, on puma population characteristics and dynamics with hunting as a mortality factor. Puma sport-hunting opened November 22 and closed December 12, 2010 after a quota of 8 independent pumas was harvested. The harvest was designed to test the management assumption that a 15% harvest of independent pumas results in a stable-to-increasing population. A total of 8 pumas were killed: 2 subadult females, 5 adult males, and 1 subadult male. The harvest of 8 independent pumas represented 15.4% of the 52 independent pumas in our minimum count during November 2010 to April 2011. Independent females and males comprised 25.0% and 75.0% of the harvest, respectively. Three other radio-collared independent pumas in the study area population were killed during the Colorado puma hunting season; 2 adult females killed on the study area for depredation control and 1 adult male in a GMU adjacent to the study area. The total mortality of 11 independent pumas during the hunting season represented 21.2% of the minimum count of independent pumas. Eight independent pumas will be the harvest quota for the 2011-12 hunting season (TY3), based on an expectation of a stable-to-increasing population. Sixty-four hunters requested mandatory permits with an 177 �attached voluntary hunter survey in TY2. Fifty-four of the hunters provided responses to written (n = 42) or telephone call follow-up contact (n = 12). An estimated 42 hunters actually hunted on the study area, of which about 19% harvested pumas and 38% captured pumas (i.e., harvested plus treed and released). Thirty-three hunters responded that they were selective hunters, and the capture, tracking, and population data indicated that most hunters practiced selection. Puma tracks < 1 day old encountered by hunters and pumas captured by hunters indicated that independent female pumas were more vulnerable than males to detection by hunters. From August 2010 to July 2011 54-55 individual pumas were captured 70 times. Two capture teams with dogs operated over 81 search days from November 16 and December 14, 2010 through April 22, 2011 to find 291 puma tracks, pursue pumas 99 times, and capture 36-37 pumas 52 times. Capture efforts with cage traps resulted in the capture of 1 adult male and 1 subadult male for the first time and the recapture of 2 adult female pumas. Fourteen cubs were observed for the first time at nurseries. A total of 53 pumas were monitored by radiotelemetry in TY2. Search efforts also revealed the presence of at least 15 other independent pumas. Our minimum count of independent pumas from November 2010 to April 2011 was 52, including 35 females and 17 males. A preliminary minimum estimated density of independent pumas was 3.11/100 km2. The proportion of radio-collared adult females giving birth in the August 2010 to July 2011 biological year was 0.56 (9/16). Six litters that could be dated to month of birth were produced in April (2), July (2), and August (2). Since 2005 a birth peak has occurred from May through August, involving 80% of nursling litters. We monitored 19 female and 9 male adult radio-collared pumas for survival and agent-specific mortality. Survival rates in TY2 for adult females were within the range during the reference period, but substantially lower for males. Causes of mortality were hunting and depredation control. One subadult female was killed and eaten by a male puma during competition for an elk carcass. Of 23 cubs monitored with radiotelemetry, 6 died, 3 from natural causes (including 2 infanticide and cannibalism) and 3 from depredation control. A non-marked female cub was also killed by a vehicle on the boundary of the study area. Puma harvest, capture, and radiotelemetry data provided information on dispersals of 26 pumas initially marked on the study area. Those pumas moved from about 20 to 370 km from initial capture sites. We explored the feasibility of attracting pumas to rub stations to obtain tissue non-invasively for potential use in a genotype markrecapture structure for estimating abundance. Nine sites with trail cameras, rub devices, and 6 scents produced 39 puma visit events. Puma behavior toward the scents was highly variable. Beaver castorium produced the highest maximum detection probability. Data continue to be gathered for other collaborative projects with Mammals Research and CSU investigators on puma behavior, social organization, population dynamics, and habitat use. 178 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction rates of females, age-stage survival rates, and immigration and emigration rates; quantify agent-specific mortality rates; model puma population dynamics; develop and execute the puma harvest manipulation to begin the population-wide test of Colorado Parks and Wildlife (CPW) puma management assumptions in the first year of a five-year Treatment Period of the Uncompahgre Plateau Puma Project― all to improve the CPW model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. Execute the second year of the five-year treatment period by working with CPW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Continue gathering data on puma population sex and age structure. 3. Continue gathering data for estimates of puma reproduction rates. 4. Continue gathering data to estimate puma sex and age-stage survival rates. 5. Continue gathering data on agent-specific mortality. 6. Explore feasibility of attracting pumas to a rub station and obtaining tissue for potential use in a noninvasive genotype mark-recapture structure. INTRODUCTION Colorado Parks and Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CPW objective of actively managing pumas while “achieving healthy, self-sustaining populations”(Colorado Division Of Wildlife 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CPW’s wildlife managers and biologists prior to initiating the project. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CPW employees. In general, CPW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CPW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). 179 �● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CPW to achieve its strategic goal in puma management (Fig.1). This project has been addressing all of the gray-shaded components on the left side of the conceptual model in Figure 1. Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/VHF-radio-collared pumas. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CPW’s model-based management approaches with Colorado-specific data from objectives 1―3. Consider other useful models. Concurrently with the tasks associated with the objectives above, significant progress will be made toward a 5th objective, which will initially be subject to pilot study― develop methods that yield reliable estimates of puma population abundance. A descriptive and manipulative study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in two 5-year periods. A completed 5-year reference period, 2004-09, (i.e., absence of recreational hunting) allowed puma life history traits to interact with the main habitat factors that influenced puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001, Logan 2009). A subsequent 5-year treatment period started in 2009-10 will involve the use of controlled recreational hunting to manipulate the puma population. 180 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CPW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all age stages- adults, subadults, and cubs, J. Apker, CPW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to Data Analysis Units (DAUs) to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado DAUs is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). Basic model parameters are: puma population density, sex and age structure, and annual population growth rate. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e.,λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. The key assumption is that the CPW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ). Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CPW 2007). H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a declining trend of the harvest-age segment of the population. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of 181 �greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a declining trend in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Researchers in Wyoming (Anderson and Lindzey 2005) concluded that sex and age composition of the harvest varies predictably with puma population size because the likelihood of a specific sex or age class of puma being harvested with the use of hounds is a product of the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Results of that study suggest that managers could use sex and age composition of the harvest to infer puma population changes (Anderson and Lindzey 2005). The CPW currently uses this approach as one tool to infer potential DAU puma population dynamics (CDOW 2008). This assumes no purposeful selection by hunters for any particular sex or age-stage other than the puma must be legal (i.e., independent subadult or adult, not a lactating female or a female in association with spotted cubs) and that changes in the sex and age structure of the harvested pumas is due solely to changes in the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Theoretically, pumas that travel longer distances with movements that intercept access routes used by hunters (i.e., roads, trails) should be more exposed to detection by hunters and thus more vulnerable to harvest. A key assumption to this method is that pumas are killed as they are encountered and the harvest sex and age composition will reliably indicate whether a population is stable, increasing, or declining even if harvest intensity does not vary. Thus, an alternate view is that a population segment, such as independent females, may be more abundant and have shorter movement lengths, yet be detected more frequently by hunters. However, because the same intensively studied Wyoming puma population was manipulated over 6 years with varying intensities of harvest (Anderson and Lindzey 2005), variations in harvest structure using the same harvest level over a period of years could not be examined. This is a property we will investigate during the treatment period on the Uncompahgre Plateau puma study. Moreover, we will directly evaluate to what extent puma harvest might be influenced by hunter selection. A hunter survey is intended to reveal puma hunter behavior, detection of different classes of pumas, and lack of or presence of hunter selection. These data should allow us to examine the credibility of the assumption of non-selection by hunters and the robustness of this technique in gauging puma population dynamics relative to harvest. We want to examine the usefulness of this approach in Colorado. CPW managers attempt to weight sport-harvest toward male pumas in GMUs with the stable-to-increasing population objective with an active educational program (i.e., mandatory hunter exam, brochure, workshops). Thus, there is a need to test assumptions associated with the Anderson and Lindzey (2005) method. H6: No hunter selection is practiced so that the sex and age structure of pumas harvested by hunters in this population protected from hunting during a 5-year reference period and subsequently managed for stability or increase with conservative harvest levels will reflect the relative vulnerabilities to detection and capture with dogs during each year in the 5-year treatment 182 �period in this order from high to low vulnerabilities: subadult males, adult males, subadult females, adult females without cubs or with cubs >6 months old, and adult females with cubs ≤6 months old (Barnhurst 1982, Anderson and Lindzey 2005). In each of the 5 years of the treatment period, subadults and adult males should comprise the majority of the harvest and reflect the assumed sex and age structure (Anderson and Lindzey 2005) of a puma population managed for a stable to increasing phase and not hunted for 5 previous years (i.e., a puma population source). Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CPW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed as we learn the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. This information will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. Cattle and domestic sheep are raised on summer ranges on the study area. Year-round human residents live along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of the plateau. A highly developed road system makes the study area highly accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) 183 �involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates are being quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest are being tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma selection pressures in western North America for at least the past 100 years. Hence, the reference period, years 1―5, provided conditions where individual pumas in this population (of estimated sex and age structure) expressed life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor was vulnerable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This allowed researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged pumas that ranged in a buffer zone in the northern halves of GMUs 61 and 62 were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CPW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6―10, recreational puma hunting is occurring on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CPW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas is being influenced mainly by recreational hunting, which is being quantified by agent-specific mortality rates of radio-collared pumas. Dynamics of the puma population are being manipulated to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting). The killing of tagged and collared pumas during the treatment period is not hampering operational needs (as it would have during the start-up years), because a majority of independent pumas in the population have already been marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of the animal(s). In addition, researchers will notify the Area Manager of the CPW if they perceive that an individual puma may be a threat to public safety. 184 �Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Puma capture and handling procedures were approved by the CPW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were fixed via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitated thorough searches for puma tracks and the ability of dogs to follow puma scent. The study area was searched systematically multiple times per winter by four-wheel-drive trucks, all-terrain vehicles, snow-mobiles, and walking. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg estimated body mass (Lisa Wolfe, DVM, CPW, attending veterinarian, pers. comm.). Immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). Pumas that climbed trees too dangerous for the pumas or researchers were released without handling, or we encourage the animals to leave the tree by heaving snowballs toward them. If the pumas climbed a safe tree, then we handled them as described above. A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage and door. Researchers handled captured pumas within 30 minutes of capture. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were 185 �restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers were away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of 30 to 100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas did not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 1998, 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating numbers, vital rates, and gathering movement data relevant to population dynamics (i.e., emigration and Data Analysis Unit boundaries). Adult, subadult, and cub pumas were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were ear-tagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas provided precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPScollars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allowed the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars were not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to determine their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when pumas were immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHFcollared pumas were fixed about once per week (as flight schedules and weather allowed) from light fixed-wing aircraft (e.g., Cessna 185) fitted with radio signal receiving equipment (Logan and Sweanor 2001). GPS- and VHF-collared pumas were located from the ground opportunistically using hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes recorded on standard forms. GPS and aerial locations were mapped using GIS software. 186 �We attempted to collar all cubs in observed litters with small VHF transmitter mounted on an expandable collar that can expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM2160, 47g, Telonics, Inc., Mesa, Arizona MOD 080, 62g, or Telonics MOD 205, 90g,) when cubs weighed 2.3―11 kg (5―25 lb). Cubs could wear these small expandable collars until they were over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Analytical Methods Population Characteristics: Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also called kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months or years. Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the subadult age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) mainly during November to March which corresponds with Colorado’s puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s 187 �rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed in a variety of software (e.g., SYSTAT, R, and MARK). RESULTS AND DISCUSSION Segment Objective 1 Puma harvest: This biological year, August 2010 to July 2011, was the second year of the treatment period (TY2) in this study of puma population dynamics on the Uncompahgre Plateau. The hunting season on the study area began on November 22, 2010 and was scheduled to extend to January 31, 2011, unless the harvest quota was taken before then. The design harvest quota was 8 pumas (i.e., 15% harvest of the estimated minimum number of independent pumas), with the objective to manage for a stable to increasing population. This design harvest tests the CPW’s current assumption that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (Assumption and Hypothesis 3 p.5 this report). The initial quota of 8 pumas for TY1 was based on the projected minimum number of 53 independent pumas expected on the study area in winter 2009-10, modeled from a minimum count of pumas during winter 2007-08 (Table 1; Logan 2010). The quota of 8 pumas for TY2 was based on the observed minimum count of 55 independent pumas during September 2009 to April 2010 in TY1 and that approximately the same number of independent pumas were expected during the puma hunting season for TY2 (an expectation consistent with our observed minimum count of 52 independent pumas for TY2, see later in Segment Objective 2). The hunting structure in TY2 was the same as in TY1. The number of puma hunters on the study area was not limited. Each hunter on the study area was required to obtain a hunting permit from the CPW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date requested a new permit for another 14 days, or until the hunter killed a puma within the season, or the season on the study area closed due to the quota being reached, or the end of the hunting season. This permit system allowed the CPW to monitor the number of hunters on the study area and to contact each hunter for survey information (see later in this section). All pumas harvested on the study area were examined by principal investigator K. Logan or a wildlife research technician and sealed as mandated by Colorado statute. All successful hunters reported their puma kill and presented the puma carcass for inspection by CPW within 48 hours of harvest. Upon inspection data were recorded on the puma harvested, including: sex, age, and location of harvest. In addition, an upper premolar tooth was collected for aging (i.e., mandatory) and a tissue sample was collected for DNA genotyping. Each successful hunter was also asked at that time to complete a one-page hunter survey form. All other hunters that did not report a puma kill on the study area were asked to complete the survey form and return it in a stamped envelope that was provided. An attempt was made to contact other hunters by telephone if they did not mail in surveys. The puma hunting season occurred on the study area from November 22 to December 12, 2010, taking 21 days to fill the quota of 8 pumas. This was 5 days less than it took to harvest 8 pumas in TY1 (i.e., 26 days, Nov. 16 to Dec. 11, 2009). Eight pumas were killed, including: 2 subadult females, 5 adult males, and 1 subadult male (Table 2). Of the 8 harvested pumas, 4 were marked: M32, M55, M90, and F108. In addition to the pumas killed on the study area during the Colorado puma hunting season, adult 188 �male M133 was killed by a hunter in north GMU62 and adult females F25 and F94 were killed for depredation control reasons on the study area (Table 3). The harvest of 8 independent pumas on the study area was 15.4% (8/52*100) of the minimum count of 52 independent pumas, including 31 females and 24 males, determined by the research team during November 2010 to April 2011 (Table 4). Independent females and males comprised 25.0% (2/8*100) and 75.0% (6/8*100) of the harvest, respectively. This harvest structure was 5.7% (2/35*100) of the independent females and 35.3% (6/17*100) of the independent males. Considering the mortality of 3 other radio-collared adults (F25, F94, M133, Table 3), a harvest of 11 independent pumas was 21.2% (11/52*100) of the minimum number of independent pumas. The harvest composition of 4 females and 8 males was comprised of 36.4% (4/11*100) females and 63.6% (7/11*100) males. This harvest structure was 11.4% (4/35*100) of the independent females and 41.2% (7/17*100) of the independent males in the minimum count. The minimum count of 52 independent pumas in TY2 was slightly lower than the minimum count of 55 independent pumas in TY1 (Table 4). Minimum count TY2 = 52 independent pumas, including 35 females and 17 males. This count reflected the relatively high adult female survival rate and low adult male survival rate in TY1 (Logan 2010). Because the harvest quota of 8 independent pumas in TY1 resulted in a minimum count of 52 independent pumas in TY2 and is expected to result in a stable-toincreasing population trend, we decided to set the quota to harvest 8 independent pumas in the TY3 (2011-12) hunting season to emulate an approximate 15% harvest of independent pumas to achieve a stable to increasing population objective while also considering that a number of independent pumas in the study area population might be killed outside of the study area as in the TY1 and TY2 hunting seasons (Fig. 3). It is still too early in this research to tell if this harvest structure is resulting in a declining, stable, or increasing population trend. Hunter permits and survey: In TY2 mandatory permits with the voluntary survey attached were requested by 64 individual hunters, down from 79 individual hunters in TY1. Seventeen of the hunters requested a second permit after the first one expired after 14 days. Fifty-four hunters (84.4%) provided responses to the voluntary survey either by turning in the printed survey (n = 42) or providing information during follow-up telephone calls (n = 12) by principal investigator K. Logan. The remaining 10 hunters could not be contacted because either they did not have working phone numbers or they did not return calls. Of the respondents, 19 hunters indicated that they did not hunt on the study area. The proportion of the 54 respondents that hunted extrapolated to the total of 64 hunters (35/54 = 0.648) indicated that about 42 hunters took to the field for pumas on the study area during the 21-day hunting season. This was down from 67 hunters that probably hunted in TY1 (Logan 2010). Considering that 42 hunters were estimated to be afield, then 19% of the hunters harvested pumas (8/42*100) and 38% of hunters captured pumas (16/42*100; see captured and released pumas below and in Table 5). The 42 puma hunters that turned in the written volunteer survey were asked to answer, “Do you consider yourself a selective or non-selective hunter?” A selective hunter is one that purposely is hunting for a specific type of legal puma, such as a male, large male, or large female. A non-selective hunter is one that intends to take whatever legal puma is first encountered or caught, with no desire for sex or size. Selective hunter was indicated by 33 respondents. Of the remaining 9 hunters, 5 did not answer the question because they indicated that they did not hunt on the study area and 1 was an outfitter that did not hunt on the study area for himself (i.e., he hunted for his clients). One hunter indicated he was nonselective, and he killed a subadult female puma. Another hunter that did not answer the question killed a subadult female puma, too. The volunteer hunter survey also revealed that hunters treed pumas on the study area, but they chose not to kill them (Table 5). Those hunters reported they treed pumas 8 times, including 7 females and 1 subadult male. Of the 7 females 6 were described as adult, including 1 with at 189 �least 1 cub. Two of the adult females were marked with GPS collars (F3, F96). One female was either an adult or subadult. Hunters gave various reasons for not wanting to kill the pumas, including reasons based on puma sex, reproductive status, and size (Table 5). In an effort to better ascertain the vulnerability of sexes and age-stages (i.e., adult, subadult) of independent pumas to detection by puma hunters to address assumption 6 and hypothesis 6 (previously), the survey was changed in TY2 to ask hunters, “What was the sex of the lion that made the first set of tracks you encountered that were less than one day old?”. This question pertained to tracks that could be pursued by dogs and captured with a relatively high probability to allow the hunter an opportunity to harvest the puma. Associated with the question, we asked, “Did you pursue the lion to harvest it?” Hunters responses showed they encountered 30 puma tracks less than one day old. Of those, 20 tracks were of females, and 10 tracks were of males, indicating that during the hunting season females are more detectable than males by a ratio of 2:1, and similar to the sex structure of independent pumas in the minimum count on the study area which was 35 females and 17 males (ratio 2.06:1, Table 4). Of the female tracks, 3 female pumas were pursued by hunters with intent to harvest, of which 2 females were actually killed. Seventeen hunters indicated they did not pursue female tracks with intent to harvest; but, hunters captured and released 7 female pumas. Of the male tracks, 7 were pursued by hunters with intent to harvest, of which 6 were actually killed. Three hunters indicated they did not pursue to harvest 3 male tracks; but, 1 subadult male puma was captured and released. These preliminary survey and harvest data for TY2 indicate independent females were captured by hunters slightly more frequently than independent males by 9 to 7 (i.e., females = 2 harvested + 7 captured and released; males = 6 harvested + 1 captured and released). Moreover, hunters are choosing to kill males more frequently than females. This result is consistent with TY1 where hunters caught females slightly more frequently than males (i.e., 12 females, 10 males; females = 3 harvested + 9 captured and released; males = 5 harvested + 5 captured and released). Also in TY1, hunters indicated a preference to harvest males over females. This preliminary assessment from years TY1 and TY2 puma harvest and hunter survey data suggests that most hunters that captured pumas were selective and influenced harvest sex and age composition and that independent female pumas were detected by hunters at a higher rate than were independent male pumas. Segment Objective 2 After the design quota was filled, puma research teams immediately activated for capture operations with trained dogs. Two fully-staffed capture teams, one each detailed on the east and west slopes, systematically and thoroughly searched the study area to capture, sample, and GPS/VHF radiocollar pumas the remainder of winter and early spring 2010-11. These efforts along with cage trap efforts and hand-capturing cubs at nurseries maintained samples to quantify population sex and age structure, survival, and agent-specific mortality, and allowed determination of minimum population size on the study area. We made 70 puma captures of 54 to 55 individuals from August 2010 to July 2011 (Tables 6-11); 36 to 37 individual pumas were captured with dogs 52 times. Four pumas were captured in cage traps. Cubs were captured at nurseries 14 times. A total of 53 pumas were monitored with radio-telemetry from August 2010 to July 2011 (some of these had been collared in previous years). Trained dogs were used as our main method to capture, sample, and mark pumas on November 16, 2010 and from December 14, 2010 to April 22, 2011. Those efforts resulted in 81 search days, 291 total puma tracks detected of which 157 were ≤1 day old, 99 pursuits, and a total of 52 puma captures of 36-37 individual pumas (Table 6). This was the second year we deployed 2 fully-staffed hound capture teams in the treatment period. Search days with dogs was similar in both TY1 (86) and TY2 (81; Table 12). The frequency of tracks (tracks/day) encountered was higher in TY2 than the previous 6 winters. 190 �Also, pursuits increased over all previous years by 6 to 58, with the lowest number of pursuits occurring in the first year of this study (2004-05) when the puma population was probably at its lowest abundance on the study area. The capture rate was also the highest by 26 to 38 captures. Increased capture efforts and captures were probably the result of using 2 fully-staffed relatively more efficient houndsmen teams in TY2 even though the puma population had been reduced due to harvest just before our capture operations. Researchers in the two hound capture teams on November 16, 2010 and from December 14, 2010 to April 22, 2011 also recorded instances when the first tracks ≤1 day old of independent pumas were encountered on each search route each day to represent encounters with puma tracks that could be detected by houndsmen. The count was: 47 tracks of females, including 11 associated with cubs; 21 tracks of males; 4 tracks of cubs, and 1 track of unspecified sex. Except for 1 female and 1 male track ≤ 1 day old found on November 16, 2010, all other tracks ≤ 1 day old were found after the TY2 puma hunting season when 6 independent males and 2 independent females were harvested. Therefore, the harvested pumas were not present to make tracks for our researchers to observe. The loss of the 6 males and 2 females may reflect the slightly higher ratio of female:male tracks post-hunting season, 2.2:1 than was reported by hunters during the hunting season, 2:1 (previously, Segment Objective 1). Still, the ratios are similar and reflect the greater likelihood of encountering females than males. Puma capture efforts using ungulate carcasses and cage traps was sporadic from November 8, 2010 to April 18, 2011 (Table 10). We used 12 road-killed mule deer at 10 different sites. Two independent male pumas (M133, M153) were captured for the first time, and 2 adult females (F70, F137) were recaptured and re-collared. Pumas scavenged at 5 of 12 (41.66%) sites where deer carcasses were used for bait. We sampled 24 cubs, including 10 females and 14 males (Table 11). Nine females and 14 males were captured by us, of which 21 (7 females, 14 males) were radio-collared to monitor survival and agent-specific mortality (Appendix A). Female cub P1026 was sampled with a bio-dart only because she climbed a dangerous tree. Another female cub, P1030, was found dead, hit by a vehicle on state highway 62 in Leopard Creek. In addition to our direct puma captures with dogs November through April, we detected 18 radiocollared pumas that we were able to identify with GPS or VHF telemetry 28 times, thus, negating the need to capture those pumas directly with dogs (Table 6). Upon detecting puma tracks that were aged at ≤1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with non-functioning GPS- or VHF- radiocollars. Our search efforts throughout the study area from December 2010 to April 2011 also revealed the presence of at least 13 other independent pumas, which we classified as 9 females and 4 males. Three females and 2 males were treed by our hounds, but we could not handle the pumas because they climbed dangerous trees (Table 8). Of those, 2 females and 2 males were sampled with biodarts to obtain a tissue sample for genotyping the individuals. We could separate the activity of the other pumas from the GPSand VHF- collared pumas in time, space, and track size differences between females and males. One puma might have been F75 with a non-functional GPS collar. Moreover, females in association with cubs of different numbers, sizes, and locations enabled us to distinguish 4 adult females followed by 1 to 2 medium-to-large-size cubs. Some tracks we found of these pumas were too old to pursue (i.e., 2+ days old; probability of capture with the dogs was negligible). 191 �Our search and capture efforts during November 2010 through April 2011 and information from the puma hunting season in TY2 enabled us to quantify a minimum count of 52 independent pumas detected on the Uncompahgre Plateau study area, including 35 independent females and 17 independent males (Table 4). This count was based on the number of known radio-collared pumas, non-marked pumas harvested by hunters on the study area, observations of marked and non-marked pumas observed by researchers or treed and released by hunters on the study area, and puma tracks observed by researchers that could not be attributed to pumas with functioning radiocollars. The estimated age structure of independent pumas in November 2010 at the beginning of the puma hunting season in TY2 on the Uncompahgre Plateau study area is depicted in Figure 4. In addition to the independent pumas, we also counted a minimum of 39 cubs. Of the 52 independent pumas, 36 to 37 (69-71%) were marked and 15 to 16 (29-31%) were assumed to be unmarked animals. The abundance and sex structure of independent pumas on the east and west slopes of the study area were similar. The east slope count included 25 independent pumas (18 females, 7 males). The west slope count included 27 independent pumas (17 females, 10 males). Considering the minimum count of 52 independent pumas, a preliminary minimum density for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area was 3.11 independent pumas/100 km2. Segment Objective 3 During the past 6.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado (Table 13). Puma reproduction data (i.e., litter size, sex structure, gestation, birth interval, proportion of females giving birth per year) were summarized for the reference period in Logan (2009). In TY2 we directly observed 6 litters in nurseries which were born in April (2), July (2), and August (2) 2010, each with 1 to 4 cubs, born to radio-collared females. Data on reproduction we observed in TY1 and TY2 were added to Table 13 which gives the reproductive chronology and information on mates of reproducing females. But those data will not be summarized again until the end of the treatment period. The proportion of radio-collared adult females giving birth from August 2010 to July 2011 biological year (TY2) was 0.56 (9/16), similar to TY1 (0.53, 8/15). Considering our 38 total observed litters with cubs 26 to 42 days old and 2 other litters confirmed by nurseries and nursling cub tracks with GPS-collared females (the latter include F111’s cubs caught later when 8.5 months old) (Table 13), the distribution of puma births by month since 2005 indicate births extending from March into September (Fig. 5). Births peak during May, June, July, and August involving 80% of the births (Fig. 5). The data indicate that the large majority of puma breeding activity occurred February through May (i.e., gestation averages about 90-92 days, Logan 2009). In comparison, Anderson et al. (1992:47-48) found on the Uncompahgre Plateau during 1982-1987 that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. The 2 data sets indicated puma births on the Uncompahgre Plateau have occurred in every month except January and November (so far). As we gather more data on the puma births during the treatment period, we will examine the distributions in the reference and treatment periods separately. Segment Objectives 4 & 5 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2011, we radio-monitored 19 adult male and 30 adult female pumas to quantify survival and agent-specific mortality rates (Table 14). Survival and agent-specific mortality of adult pumas were summarized for the reference period in Logan (2009). Preliminary estimates of adult puma survival rates in the absence of sport-hunting during the reference period indicated high survival, with adult male survival generally higher than adult female survival (Table 15). Preliminary adult puma survival for TY1 and TY2 are also shown in Table 15. So far, adult male survival is substantially lower in the treatment period than in the reference period and adult female 192 �survival may be similar in both periods. These characteristics may be indicative of hunter selection for male pumas (previously in Segment Objective 1). But, no conclusions should be drawn with results from only 2 years in the treatment period. The primary research interests include how survival rates influence population growth rates and the strength of factors associated with survival and mortality. This is what ultimately allows us to evaluate the effect of a 15% harvest level on independent pumas for our population management assumptions when the goal is a stable to increasing population. Human-related causes of mortality dominated deaths of marked adult pumas in TY2, including: sport-hunting harvest (4 males- M32, M55, M90, M133) and depredation control (1 male- M134; 2 females- F25, F94) (Table 14). We have radio-monitored 19 pumas, including 6 females and 13 males, in the subadult age-stage (independent pumas <24 months old) (Table 16). Four died before reaching adulthood, indicating a preliminary finite survival rate of 0.789 (i.e., 15/19). All 4 subadults apparently died of natural causes. F66 died at 23 months old of trauma to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer. M99 died at about 16 months old; punctures to his skull were consistent with canine bites from another puma and suggested intra-species strife as cause of death. M115 died at about 14 months old due to complications of a broken left foreleg, cause unknown. This injury probably affected his ability to efficiently kill prey. F143 was killed and eaten by a male puma while in competition for an elk carcass that one of the pumas killed. We need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire reliable estimates of their survival. Harvest data along with our capture and radiotelemetry data provided additional information on fates of 26 marked pumas, 22 males and 4 females. Of those, 21 (2 females, 19 males) were initially captured and marked as cubs, and 5 (2 females, 3 males) were captured and marked as subadults on the Uncompahgre Plateau puma study area (Table 17). Twenty males were killed away from the study area by hunters at linear distances (i.e., from initial capture sites to kill sites) ranging from about 20 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). Female F52 was treed and released by hunters in December 2008 and 2009 south of Powderhorn, Colorado, indicating that she probably established an adult home range there. Three males marked initially as cubs born on the study area (M67, M87, M92) dispersed from their natal ranges and were recaptured as adults on the study area. All were born on the east slope of the Uncompahgre Plateau and moved to the west slope. These pumas represent dispersal moves on and from the Uncompahgre Plateau. Eighteen of the 26 pumas had reached adult ages ranging from 24 to 55 months old. A preliminary estimate of cub survival during the reference period was summarized in Logan 2009 using 36 radio-collared cubs (16 males, 20 females) marked at nurseries when they were 26 to 42 days old. In that summary, estimated survival of cubs to one year of age was 0.53.. The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. In TY2 we monitored the fates of 23 radio-collared cubs (Appendix A). Six of the cubs (3 females, 3 males) were known to have died. Three cubs with their mother F94 were killed for depredation control to protect a commercial domestic elk operation. Three other cubs died of natural causes. M130 died from a cause associated with injury to his right shoulder during the first move away from his nursery with F96 and 3 other siblings. Two cubs, M139 and F148 (offspring of F8), died of infanticide and cannibalism by a female or subadult male puma. A greater number of cubs over a longer period of time must be sampled before estimating cub survival and agent-specific mortality rates in the treatment period. 193 �In addition, a non-marked female puma cub was struck and killed by a vehicle on state highway 62 in Leopard Creek on the south boundary of the study area on February 16, 2011. This mortality made the thirteenth puma death recorded due to vehicle collision on the study area since 2004 (Table 18). Five of the 13 pumas were marked, including 3 adults with GPS/VHF collars. Those 3 adults died during the first year of the treatment period. Thirty-two adult pumas (23 females, 9 males) have worn GPS collars since this project began in 2004 (Table 19). Over 55 thousand GPS locations have been obtained for studies on puma behavior, social organization, population dynamics, movements, habitat use and puma-human relations in collaboration with colleagues in Mammals Research and Colorado State University. Segment Objective 6 As an extension of our pilot puma camera grid project in 2009 (Logan 2010), we decided to explore the feasibility of attracting wild pumas to a rub station to obtain tissue non-invasively for potential use in a genotype mark-recapture structure for estimating abundance. Our question was basic to such a structure. What might be expected detection probabilities for wild pumas at scent/rub stations? This work operated on minimal resources consisting of 9 trail cameras, opportunistically available scents, and the field work was done primarily by volunteer Linda Sweanor. Thus, we consider this work exploratory to inform how we might continue in future efforts. Our approach was simple, reflecting available resources. We placed cameras and scent stations with hair capture devices at sites where we thought we could maximize encounters with pumas. Cameras were Reconyx ™ with passive infrared motion detectors and night time infrared illumination each set to take photos each second after the camera was triggered. Our previous approach to locating stations using only trail cameras in a grid resulted in very high detection probabilities of marked pumas during our pilot camera grid project in 2009 (Logan 2010). This allowed us to photographically record behavior of pumas at scent/rub stations. Scents used included: beaver castorium, catnip oil, MT Lynx ™, Obsession for Men ™, Spotted Fever ™, and one combination of catnip oil and Spotted Fever™. Scent/rub stations, camera operation, and camera digital data were examined at approximately 2 to 4 week intervals. At those times, each rub pad (i.e., rub device and carpet swatch) was treated with a different available scent if a puma had visited the scent/rub station and regardless of the puma’s response to the scent/rub station. If no pumas visited the rub/scent station, then the carpet swatch was re-treated with the same scent used the previous weeks. Our aim was to expose as many individual pumas as possible to different scents and record their behaviors. We defined the sampled population of pumas to include only those pumas recorded by the cameras. All pumas photographed passed ≤5 m of the scent/rub station. We defined a maximum detection probability for a particular scent as the number of individual pumas that were photographically recorded at scent/rub stations with a particular scent that rubbed and deposited hair that could be collected divided by the total number of individual pumas that were photographically recorded at scent/rub stations with a particular scent. We did not have resources to attempt to assess quality of the DNA and individual puma genotype accuracy; thus, detection was considered to be maximum for this exploratory assessment only. In addition, this design did not consider other pumas in the environment that were not detected by the camera/scent/rub stations. Non-detected pumas in the area of the camera/scent/rub stations and DNA that provided inaccurate genotypes would lower the detection probability. Detailed notes were kept on visits and behaviors of all pumas and other wildlife that were recorded by cameras. Camera scent/rub stations were maintained from November 20, 2010 to August 14, 2011. A total of 9 stations were used. All information in Tables 20, 21 and Appendix B should be considered exploratory and preliminary. Thirty-nine puma visit events were photographed, including one family of 4 194 �pumas (i.e., mother with 3 cubs). Beaver castorium produced the highest maximum detection probability, 0.667, (Table 20). Detection was variable among the scents used and among pumas and appeared to be substantially lower for male than for female pumas (Table 21). These results indicate that more work needs to be done in a more structured manner to sample a greater number of known individual wild pumas, a variety of scents, and with an analysis of DNA quality and genotype accuracy. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 6.7 years of effort 153 unique pumas have been captured, sampled, marked, and released. Using these animals, we monitored fates of pumas in all sexes and age stages, including: 30 adult females, 19 adult males, 6 subadult females, 12 subadult males, 39 female cubs, 53 male cubs (some individuals occur in more than one age-stage). Data from the marked animals were used to quantify puma population characteristics and vital rates in a reference period without sport-hunting off-take as a mortality factor from December 2004 to July 2009. Puma population characteristics and vital rates in a reference condition allowed us to develop a puma population model, and to use population data and modeling scenarios to conduct a preliminary assessment of CPW puma management assumptions and guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CPW wildlife biologists and managers for assessing puma harvest strategies. The 5-year treatment period began August 2009 in which sport-hunting is a mortality factor. The treatment period will be a population-wide test of CPW puma management assumptions. Now 2 years of the treatment period are complete (TY1, TY2). Although some data support CPW puma management assumptions, it is still too early in this research to adequately test the assumptions and attendant hypotheses. Although the assumption and hypothesis on harvest structure and hunter selection is not supported with the first 2 years of data in the treatment period, this could change with a substantial change in abundance and sex structure of independent pumas available for hunting in TY3 to TY5. The puma harvest quota for TY3 will be 8 independent pumas, and the hunters will be surveyed again. To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes across the various life stages and sexes. We will continue to explore methods for estimating puma abundance with accurate and affordable methods. Furthermore, we will continue collaboration with colleagues on investigations of puma population parameter estimation, abundance estimation, puma movements, puma habitat modeling and mapping, and puma-human relations. All of these efforts should enhance the Colorado puma research and management programs. 195 �LITERATURE CITED Anderson, A. E. 1983. A critical review of literature on puma (Felis concolor). Colorado Division of Wildlife Special Report No. 54. _____, D. C. Bowden, and D. M. Kattner. 1992. The puma on Uncompahgre Plateau, Colorado. Technical Publication No. 40. Colorado Division of Wildlife, Denver. Anderson, C. R., Jr., and F. G. Lindzey. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. Colorado Division of Wildlife 2002-2007 Strategic Plan. 2002. Colorado Department of Natural Resources, Division of Wildlife. Denver. Colorado Division of Wildlife. 2007. 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Ecology 81:1533-1543. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. D. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. 196 �Pojar, T. M., and D. C. Bowden. 2004. Neonatal mule deer fawn survival in west-central Colorado. Journal of Wildlife Management 68:550-560. Ross, P. I., and M. G. Jalkotzy. 1992. Characteristics of a hunted population of cougars in southwestern Alberta. Journal of Wildlife Management 56:417-426. Seidensticker, J. C., M. G. Hornocker, W. V. Wiles, and J. P. Messick. 1973. Mountain lion social organization in the Idaho Primitive Area. Wildlife Monographs No. 35. Stoner, D. C. 2004. Cougar exploitation levels in Utah: implications for demographic structure, metapopulation dynamics, and population recovery. Master of Science Thesis. Utah State University. Sweanor, L. L., K. A. Logan, J. W. Bauer, B. Milsap, and W. M. Boyce. 2008. Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 197 �Table 1. Projected puma population growth modeled from a minimum count of independent pumas during winter 2007-08 reference period year 4 (RY4). Treatment period year 1 (TY1), shaded in gray, indicates the results used to derive a quota of 8 independent pumas, representing 15% of the independent pumas (from Logan 2009). Harvest Level No harvest. Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 27 17 11 10 32 22 12 11 38 27 15 14 44 32 17 16 Year RY4 RY5 TY1 TY2 TY3 TY4 TY5 Independent Pumas Cub 20 33 42 49 58 69 81 Total 33 45 53 64 77 92 110 Lambda 1.37 1.17 1.22 1.20 1.20 1.19 Table 2. Pumas harvested by sport-hunters in Treatment Year 2 (TY2) on the Uncompahgre Plateau Study Area, Colorado, November 22 to December 12, 2010. Puma sex Age (yr.) Date of kill Location/UTM 1.5 Previous M/F I.D. or specimen P no. if not marked P1020 F 11/22/2010 M 2.3 M90 11/23/2010 M 6.3 M55 11/25/2010 M 3.5 P1023 11/26/2010 F 1.5 F108 11/29/2010 M 3 P1032 12/1/2010 M 9.2 M32 12/2/2010 M 1.5 P1024 12/12/2010 McKenzie Butte/ 13S,255947E,4238054N McKenzie Creek/ 13S,257237E,4238244N Spring Creek Canyon/ 13S,239181E,4248300N San Miguel River Canyon/ 12S,736610E,4230762N Cushman Creek/ 12S,752013E,4263883N San Miguel Canyon (E)/ 12S,729439E,4236264N McKenzie Creek/ 13S,257722E,4239169N Tabeguache Creek/ 12S,735100E,4249600N 198 Hunter/status Micah Brogden/ Resident Jack Flowers/ Resident Dennis Rawley/ Non-resident Michael Compton/ Resident Richard Fischer/ Resident Nathan Nickle/ Non-resident Mat Iverson/ Resident Mark Puerschner/ Non-resident �Table 3. Three other independent GPS-collared adult pumas in the minimum count for the Uncompahgre Plateau Study Area that died during the 2010-11 Colorado puma hunting season. Puma sex (M or F) Date of kill Place of kill/UTM Hunter/status/other cause M133 Age (yr.) 3.5 12/1/2010 F94 5 2/1/2011 F25 10 2/5/2011 Dry Fork Escalante Canyon 12S,731720E,4278128N Happy Canyon 13S,246976E,4255108N Pleasant Valley 13S,252703E,4225101N Trent Schloegel/ Non-resident Killed by A.P.H.I.S.W.S. agent for depredation on domestic elk Killed by ranch-hand because puma was seen in vicinity of cattle Table 4. Minimum count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during September 2009 to April 2010 of Treatment Year 1 (TY1) and November 2010 to April 2011 (TY2), Uncompahgre Plateau study area, Colorado. Treatment Year (TY) Study Area region TY1 East slope West slope subtotals TY2 Adults Female Male Subadults Female Male Female Cubs Male 16 10 1 1 1 4 14 10 0 3 3 3 30 20 1 4 4 7 Total Independent Pumas = 55, including 31 females, 24 males. Cubs = 20-25 East slope 15 5 3 2 7 9 West slope 15 7 2 3 2 5 subtotals 30 12 5 5 9 14 Total Independent Pumas = 52, including 35 females, 17 males. Cubs = 39 Unknown sex 4-8* 5-6 9-14 7 9 16 *One adult non-marked female puma was killed by a hunter in Roubideau Canyon. The female puma was lactating, indicating she had nurslings. Up to 4 cubs were assumed to be in the litter. 199 �Table 5. Pumas captured and released by sport-hunters in Treatment Year 2 (TY2) on the Uncompahgre Plateau Study Area, Colorado, November 22 to December 12, 2010. Data are from puma hunter responses in 54 voluntary surveys, including: 42 original surveys on printed voluntary permits and 12 telephone contacts with hunters that did not return printed surveys on permits. Total response rate from 64 individual hunters was 84.4% (54/64 = 0.894*100). Puma sex/age stage/mark F/adult/F3 by collar, no eartags, confirmed with GPS and VHF data F/adult/F96 by GPS collar, confirmed with GPS data F/adult/none Date of capture 11/25/2010 Capture location Hunter name Spring Creek Canyon Justin Hill 11/27/2010 Dolores Canyon Justin Hill Did not pursue the female puma with intent to harvest it. 11/23 to 27/2010 McKenzie Creek (west) Tommie Buckington guided by Ryan Weimer F /adult and cub/none F/adult or subadult/none 11/22 to 30/2010 11/30/2010 Dolores River Canyon Dolores Creek (east) Ryan Weimer Female puma with evidence of suckling on nipples. Did not want to kill a female puma with cubs. Cubs not actually seen. Not legal to kill a female puma with cubs. Did not pursue the female puma with intent to harvest it. F/adult/none 12/11/2010 F/adult/none 11/22 to 12/12/2010 11/22 to 12/12/2010 Sims Mesa to Happy Canyon Dry Park to Big Bucktail Creek San Miguel Canyon above Goodenough Gulch M/subadult/none John Akerberg & Kris Brown guided by Ben Harris Wade Wilson Sam Sickels Ty Sickels 200 Reason for releasing the puma given by hunter Did not pursue the female puma with intent to harvest it. Did not pursue the female puma with intent to harvest it. Did not pursue the female puma with intent to harvest it. Did not want to harvest a subadult male; guessed weight 125 lb. �Table 6. Summary of puma capture efforts with dogs from November 16, 2010 to April 22, 2011, Uncompahgre Plateau, Colorado. Month November No. Search Days 1 December 11 January 22 February 20 March 21 No. & type of puma tracks founda,b 2 tracks: 1 male, 1female, 0 cub Tracks ≤1 day old: 1 male, 1 female, 0 cub 35 tracks: 7 male, 17 female, 9 cub, 2 undetermined independent pumas Tracks ≤1 day old: 2 male, 3 female, 2 cub 109 tracks: 15 male, 60 female, 30 cub, 4 undetermined independent pumas Tracks ≤1 day old: 5 male, 25 female, 24 cub No. & type of pumas pursued 1 pursuits: 1 male, 0 female , 0 cub No. & I.D. or type of pumas captured, observed, or identified 1 puma captured: M90 recaptured and fit with adult-size VHF collar (cub collar had quit/shed a long time previously). 5 pursuits: 1 male, 3 female, 1 cub 3 pumas captured 3 times: AFP1025 (biodart, dangerous tree), Adult F (not handled due to dangerous tree), M134 cub. In addition, adult female F118, her 3 cubs M126, M127, M128, and adult male M67 were associated with tracks by VHF telemetry. 29 pursuits: 5 male, 14 female, 10 cub 65 tracks: 13 male, 28 female, 24 cub Tracks ≤1 day old: 10 male, 21 female, 22 cub 30 pursuits: 9 male, 11 female, 10 cub 18-19 pumas captured 20 times: F135, F104, AFP1029 (bio-darted, dangerous tree), F136, F137, F28, F23 captured twice, Sub./AMP1028 (possibly M138), M138, and cubs F111's two cubs (not handled, dangerous trees), M112, FP1026, MP1027, M134, M112, F140, M141, M142. In addition, adult females F111, F3 (twice), F96, F136, F116 (twice), and cubs F140, M141, M142 were associated with tracks by VHF telemetry. 14 pumas captured 15 times: F137, F70, F23, F143, adult F (not handled, dangerous tree), F24 (twice), independent M (not handled, dangerous tree), M138, M87, subMP1031 (bio-darted, dangerous tree), and cubs M150 (twice), P1026, M151. In addition, adult females F96, F70 (twice), F23, F118, F143, adult male M67, and cubs M141, M142 were associated with tracks by VHF telemetry. 7 pumas captured 7 times: F111, F3, F72, F145, F146, M144, and cub F152. In addition, subadults M144, F145, and cub M142 were associated with tracks by VHF telemetry. 5 pumas captured 5 times: F24, M92, and cubs F140, M141, F147. In addition, adult M67 was associated with tracks with VHF telemetry. 73 tracks: 26 male, 22 pursuits: 4 male, 30 female, 17 cub 11 female, 7 cub Tracks ≤1 day old: 9 male, 12 female, 7 cub April 6 16 tracks: 3 male, 12 pursuits: 6 female, 7 cub 2 male, 3 female, Tracks ≤1 day old: 7 cub 2 male, 4 female, 7 cub 81 300 tracks: 99 pursuits: 36 to 37 individual pumas were captured 52 TOTALS 65 male, 22 male, times with aid of dogs. In addition, 18 radio142 female, 42 female, collared pumas were detected 28 times by tracks 87 cub, 35 cub and identified with VHF telemetry ≤1 km from 6 undetermined the tracks. Tracks ≤1 day old: 29 male 68 female 62 cub a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Researchers also recorded instances when the first puma tracks ≤1 day old were encountered on each search route each day. The count was: 47 tracks of females, including 11 associated with cubs; 21 tracks of males; 4 tracks of cubs, and 1 track of undetermined sex. 201 �Table 7. Adult and subadult pumas captured for the first time, sampled, tagged, and released from November 2010 to April 2011, Uncompahgre Plateau, Colorado. Puma I.D. M133 F135 F136 F137 M138 F143 M144 F145 F146 M153 Sex M F F F M F M F F M Estimated Age (mo.) 42 27 30 24 18 24 18 18 18 18 Mass (kg) Capture date 11/12/2010 1/1/2011 1/20/2011 1/21/2011 1/26/2011 2/15/2011 3/7/2011 3/8/2011 3/8/2011 4/12/2011 70 38 41 35 50 45 63 42 36 55 Capture method Cage trap Dogs Dogs Dogs Dogs Dogs Dogs Dogs Dogs Cage trap Location Roubideau Canyon Dry Creek Basin McKenzie Creek (east) Dry Creek Basin Spring Creek Canyon San Miguel Canyon Little Big Bucktail Creek North Fork Cottonwood Creek Tomcat Creek McKenzie Mesa Table 8. Pumas that were captured and observed with aid of dogs, some of which were biopsy-darted and given specimen numbers (e.g., P1025), but were not handled at that time for safety reasons, December 2010 to April 2011, Uncompahgre Plateau, Colorado. Puma sex & I.D. F P1025 Age stage or months adult Capture date 12/14/2010 Location Comments Monitor Mesa, Roubideau Canyon Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Apparent mother of cub M134. Puma climbed dangerous tree momentarily, then left the tree and took refuge in a deep narrow hole where we could not gain access to her to change the non-functional GPS collar. Puma climbed dangerous tree. Cub of F111. Two cub tracks found; one was M151 marked 2/24/2011. Puma climbed dangerous tree. Cub of F111. Two cub tracks found; one was M151 marked 2/24/2011. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Probably offspring of F70; sibling of M112 and M150. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Probably M150, offspring of F70; sibling of M112 and P1026. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Possibly M138. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. Puma climbed dangerous tree. Too high to biopsy dart. Puma climbed dangerous trees. Biopsy-darted to obtain tissue sample for genotype. First dart missed puma; puma left tree and evaded dogs on bare ground. Puma climbed dangerous tree. Identified by eartag. F28 adult 1/1/2011 San Miguel Canyon Unknown none cub 7 1/2/2011 Piney Creek Unknown none cub 7 1/2/2011 Piney Creek F P1026 cub 18 1/6/2011 Happy Canyon M P1027 cub 18 1/7/2011 Happy Canyon M P1028 F P1029 M none M P1031 F none M92 adult 1/12/2011 Roubideau Canyon adult 1/15/2011 Dolores Canyon (E) adult 2/3/2011 West Fork Dry Creek Basin subadult 2/17/2011 adult 2/21/2011 adult 4/22/2011 North Fork Cottonwood Creek San Miguel Canyon above Horsefly Creek McKenzie Canyon (W) 202 �Table 9. Pumas recaptured with dogs and cage traps January 2011 to April 2011, Uncompahgre Plateau, Colorado. Puma I.D. F28 Recapture Date 1/1/2011 Mass (kg) Observed Estimated Age (mo.) 94 Capture Method/ Location Dogs/East Fork Dry Creek Basin F23 1/6/2011 Observed 77 Dogs/San Miguel Canyon above Pinyon M112 1/6/2011 Observed 17 Dogs/Happy Canyon M134 F104 M112 1/8/2011 1/11/2011 1/24/2011 Observed 36 42 19 116 17 Dogs/Potter Basin Dogs/Roatcap Canyon Dogs/Horsefly Canyon F23 1/26/2011 45 77 F137 2/1/2011 Observed 25 F23 M87 2/8/2011 2/9/2011 Observed 65 78 31 M138 F70 2/9/2011 2/18/2011 Observed Observed 19 70 F70 2/21/2011 46 70 F24 2/22/2011 38 119 F24 2/24/2011 Observed 119 Dogs/San Miguel Canyon below Pinyon Dogs/East Fork Dry Creek Dogs/Tomcat Creek Dogs/Big Bucktail Creek Dogs/Roatcap Canyon Dogs/Spring Creek Canyon Cage trap/Pinyon Hills, Happy Canyon Dogs/Dry Park, Cottonwood Creek Dogs/San Miguel Canyon above Pinyon F111 3/4/2011 41 41 F3 3/15/2011 Observed 116 F72 3/18/2011 Observed 60 Dogs/Fisher Creek F140 4/1/2011 8 Dogs/Coal Canyon Dogs/Cushman Canyon Dogs/Spring Creek Canyon 22 M141 4/1/2011 Observed 8 Dogs/Coal Canyon F137 4/11/2011 42 27 F24 4/21/2011 Observed 121 Cage trap/Dry Creek Basin Dogs/McKenzie Canyon (west) M92 4/22/2011 Observed 32 Dogs/McKenzie Canyon (west) 203 Process F28 first climbed dangerous tree, left the tree, then entered deep narrow hole; could not be handled to replace non-functional GPS collar. F23 took refuge in elevated crevice on canyon wall; could not be handled to replace non-functional GPS collar. Observed puma bayed on the ground, fighting the dogs. Dogs caught and puma allowed to escape. Not handled. GPS collar replaced with VHF radiocollar. M112 fit with VHF radiocollar with expansion link. Replaced non-functional GPS collar with new VHF radiocollar. Observed and released. Observed and released. M87 fit with VHF radiocollar. Observed and released. F70 climbed dangerous tree; could not be handled. Old GPS collar replaced with new GPS collar. Replaced non-functional GPS collar with new VHF radiocollar. F24 observed and released. Effort to capture 2 cubs failed; lost tracks on bare ground in ledges. Old GPS collar replaced with new GPS collar. F3 climbed dangerous tree. Could not be handled to replace old, working GPS collar. F72 climbed dangerous tree. Could not be handled to replace non-functional GPS collar. Recollared with large expandable cub collar to replace the collar that was shed earlier. M141 left tree before we could handle him; escaped the dogs on bare ground. Replaced VHF radiocollar with GPS collar. F24 observed and released. Captured, sampled, and radio-collared cub F147 (one of two cubs). M92 climbed dangerous tree. Could not be handled to fit with radiocollar. �Table 10. Summary of puma capture efforts with cage traps from November 8, 2010 to April 18, 2011, Uncompahgre Plateau, Colorado.* Month November No. of Sites 6 Carnivore activity & capture effort results Captured adult male puma M133 that scavenged mule deer doe carcass in Roubideau Canyon 11/12/2010. Set cage trap in mouth Linscott Canyon on 11/18/2010 in effort to capture male puma that scavenged mule deer carcass; but, the male puma did not return. January 0 All capture efforts with dogs. February 1 Puma F70 was recaptured at a mule deer kill on 2/21/2011 on Pinyon Hills, Happy Canyon. March 3 No pumas scavenged the mule deer carcasses. April 4 Puma F137 was recaptured when she returned to scavenge on a mule deer buck carcass in Dry Creek Basin on 4/11/2011. Puma M153 was captured when he returned to scavenge a mule deer doe carcass on McKenzie Mesa on 4/12/2011. Puma F70 scavenged a mule deer buck carcass on 4/16-17/2011; no effort was made to recapture her. * We used 12 road-killed mule deer at 10 different sites. Of the road-killed deer baits, 5 of 12 (41.66%) were scavenged by pumas. Table 11. Puma cubs sampled August 2010 to July 2011 on the Uncompahgre Plateau Puma Study area, Colorado. a Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M122b F123 F124 M125 M126 M127 M128 F129 M130 M131 F132 M134 M139 F148 F140 M141 M142 F147c F149 M150d P1026d M151e F152f P1030 M F M M M M M F M M F M M F F M M F F M F M F F 7/8/2010 7/15/2010 7/15/2010 7/15/2010 8/8/2010 8/8/2010 8/8/2010 8/21/2010 8/21/2010 8/21/2010 8/21/2010 6/2009 4/18/2011 4/18/2011 8/2010 8/2010 8/2010 9/2010 4/22/2011 8/31/2009 8/31/2009 6/16/2010 6/16/2010 8/2010 35 29 29 29 28 28 28 35 35 35 35 547 36 36 152 152 152 214 45 547 516 253 261 183 2.2 1.8 1.9 2.0 1.6 1.9 2.0 1.6 1.9 1.8 1.6 64 2.25 2.25 13 15 14 16 2.9 53 NH 23 25 21 F104 F94 F94 F94 F118 F118 F118 F96 F96 F96 F96 Unknown F8 F8 Unknown Unknown Unknown F24 F23 F70 F70 F111 F93 Unknown 110 60 60 60 27 27 27 55 55 55 55 Unknown 95 95 Unknown Unknown Unknown 114 80 52 52 32 90 Unknown Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs caught with mothers without radiocollars or mothers with non-functioning radiocollars. b Three sets of cub tracks (including M122) observed in association with F104 when she was recaptured 1/11/2011 in Roatcap Canyon. c Three sets of cub tracks (including F147) observed in association with F24. d Cubs M150 and P1026 are siblings of M112. F70 had at least 3 cubs in the litter. Birth date based on GPS data on F70’s collar. e Two cubs were observed in association of F111. f F93 had two cubs in this litter. 204 �Table 12. Summary of puma capture efforts with dogs, December 2004 to April 2011, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 Dec. 15, 2009 to April 30, 2010 Nov. 16 and Dec. 14, 2010 to April 22, 2011 Track detection effort 109/78 = 1.40 tracks/day 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 198/71 to 202/71 = 2.79-2.84 tracks/day 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day 266/86 = 3.09 tracks/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 93/86 = 1.08 pursuit/day 300/81 = 3.70 tracks/day 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture 26/86 = 0.30 capture/day 9 pumas captured for first time 9/86 = 0.11 capture/day 86/93 = 0.92 day/pursuit 99/81 = 1.22 pursuit/day 86/26 = 3.31 day/capture 52/81 = 0.64 capture/day 86/9 = 9.56 day/capture 81/99 = 0.82 day/pursuit 81/52 = 1.56 day/capture 205 15 pumas captured for first time 15/81 = 0.18 capture/day 81/15 = 5.40 day/capture �Table 13. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2011. Consort pairs and estimated agesa Female Age Male Age (mo.) (mo.) F2 53 F2 67 F2 89 F3 36 F3 50 M6 37 F3 62 F3 84 M51 60 F3 107 M55 69 F7 67 F7 82 F7 106 F8*e 24 F8 37 F8 60 M73 49 F8 95 F16 32 F16 52 F16 75 M6 80 F23* 21 F23 45 M27 or 78 M29f 107 F23 80 F24 75 M29 92 F24 114 F25 74 F25 94 F25 110 F25 129 F28* 36 F28 48 M29 88 F28 68 F30* 48 M55 34 F50 21 F54 24 F70* 38 M51 60 F70 52 F72* 28 F72 51 F75 32 F75 55 M73 61 F93 56 F93 90 F94* 46 F94 60 M55 70 F96 55 M55 71 F104 110 F111* 32 F116g 36-48 F118 27 F119 66 Dates pairs consortedb 06/22-24/05 03/31/08 03/28-31/10 02/28-29/08 01/13-14/09 02/19-25/08 04/12-15/07 12/27-29/06 04/16-20/07 03/10/08 02/11/09 04/15/10 05/21/10 Estimated birth datec 05/28/05 07/29/06 05/19/08 08/01/04 09/26/05 09/17/06 07/03/08 06/28/10 05/19/05 08/13/06 07/10/08 06/26/05 08/13/06 05/29/08 04/18/11 09/22/05 05/24/07 04/15/09 05/30/06 05/23/08 04/22/11 06/14/07 09/10 08/01/05 04/16/07 08/19/08 3/10 06/09/06 03/30/07 11/08 07/17/07 07/01/06 07/01/06 06/05/08 08/31/09 07/09/08 06/12/10 06/01/07 05/07/09 08/07 06/16/10 05/27/09 07/15/10 08/21/10 07/08/10 06/16/10 2009 08/08/10 08/09 a Estimated birth interval (mo.) Estimated gestation (days) 14.0 22.0 13.8 11.7 21.5 23.8 93-95 94 89-92 14.9 23.9 13.4 22.5 34.7 90-91 19.9 22.7 91-92 23.8 87-93 Non-funct.GPS 90-93 Non-funct.GPS 20.5 16.1 Non-funct.GPS 11.7 92-93 88-92 87 14.8 23.1 23.2 93 13.3 91 Observed number of cubsd 3 2 4 1 2 3 3 2 2 4 3 2 4 2 4 4 3 3 3 1 4 3 1 1 2 3 2 ≥2 tracks 1 3 1 1 3 3 1 2 1 2 2 2 3 3 4 3 2 2 3 2 Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. 206 �d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore nonfunctional GPS collars in that area at the time. g When captured on 1/20/10, puma F116 was in association with 2 large cubs which were not captured. 207 �Table 14. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2011, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 M6 02-18-05 to 05-21-10 M27 03-10-06 to 05-07-09 M29 04-14-06 to 02-25-09 M32 04-26-06 to 12-02-10 M51 01-07-07 to 03-20-09 M55 01-21-07 to 07-31-10 M67 M71 08-23-07 to 07-31-11 01-29-08 to 11-12-09 M73 M87 M90 02-21-08 to 07-31-11 02-09-11 to 07-31-11 11-16-10 to 11-23-10 M100 03-27-09 to 07-31-09 M114 M133 02-27-10 to 06-23-10 11-12-10 to 12-01-10 Status: Alive/Lost contact/Dead; Cause of death Dead. Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. M1 was killed by a puma hunter on 01-02-10 west of Bang’s Canyon, north of Unaweep Canyon, GMU 40. M1 was about 97 months old at death. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Dead. M6 was struck and killed by a vehicle on highway 550 south of Colona, CO on 05-21-10. M6 was about 99 months old at death. Dead. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-22-08 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. M27 was killed by a puma hunter on 12-09-09 in the North Fork Mesa Creek, Uncompahgre Plateau, GMU 61 North. M27 was about 100 months old at death. Dead. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. M29 was killed by a puma hunter on 11-16-09 in Beaver Canyon, GMU 70 East. M29 was about 121 months old at death. Dead. Killed by a puma hunter on 12-02-10 in McKenzie Creek on the Uncompahgre Plateau study area. M32 was about 112 months old at death. Dead. Lost contact− failed GPS/VHF collar after 03-20-09. Killed by a puma hunter on 12-11-09 in Shavano Valley, Uncompahgre Plateau study area. M51 was about 77 months old at death. Dead. Killed by a puma hunter on 11-25-10 in Spring Creek Canyon on the Uncompahgre Plateau study area. M55 was about 77 months old at death. Alive. M67 is offspring of F30. Dead. Lost contact– M71 shed his VHF collar with an expansion link on about 11-1209. He was killed by a puma hunter on 12-09-09 on the west rim of Spring Creek Canyon, Uncompahgre Plateau study area. M71 was about 47 months old at death. Alive. Alive. M87 is offspring of F3. Dead. M90 was killed by a hunter on 11-23-10 on McKenzie Butte. M90 was offspring of F72, born 07-09-08. He was 28 months old at death. Dead. M100 was killed by a puma hunter on 01-16-10 in Naturita Canyon, GMU 70 East. M100 was about 63 months old at death. Lost contact– after 06-23-10. VHF collar may have failed or puma dispersed. Dead. M133 was killed by a puma hunter on 12-01-10 in Dry Fork Escalante Canyon north of the study area. M133 was about 43 months old at death. 208 �Puma I.D. M134 Monitoring span 06-01-11 to 06-10-11 M138 F2 07-01-11 to 07-31-11 01-07-05 to 08-14-08 F3 F7 01-21-05 to 07-31-10 02-24-05 to 08-03-08 F8 F16 03-21-05 to 07-31-11 10-11-05 to 09-11-09 F23 02-05-06 to 07-31-11 F24 01-17-06 to 07-31-11 F25 02-08-06 to 02-03-11 F28 03-23-06 to 01-01-11 F30 04-15-06 to 07-29-08 F50 12-14-06 to 03-26-07 F54 01-12-07 to 08-18-07 F70 F72 01-14-08 to 07-31-11 02-12-08 to 03-18-11 F75 03-26-08 to 02-10-10 F93 F94 12-05-08 to 07-31-11 12-19-08 to 02-01-11 F95 F96 F104 F110 08-01-09 to 07-31-11 01-28-09 to 07-31-11 05-21-09 to 07-31-11 09-21-09 to 02-25-10 F111 01-01-10 to 07-31-11 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Dead. M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Alive. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. F2 was about 92 months old at death. Lost contact− failed GPS/VHF collar. Dead. Killed by U.S. Wildlife.Services agent 08-03-08 for predator control of depredation on domestic sheep. F7 was about 107 months old at death. Alive. Dead. F16 was struck and killed by a vehicle on Ouray County Road 1 southwest of Colona, CO on 09-11-09. F16 was about 80 months old at death. Alive. Lost radio contact after12-02-09. F23 recaptured on the study area 01-26-11; her non-functional GPS collar was replaced with a VHF radiocollar. Alive. Lost radio contact after 09-03-08− failed GPS/VHF collar. F24 recaptured on 0222-11; her non-functional GPS collar was replaced with a VHF radiocollar. Dead. Lost radio contact after 09-04-09– failed GPS/VHF collar. Photographed alive with three ~9 month old cubs on 12-03-10 on Loghill Mesa. F25 shot dead by a ranch hand on 02-03-11 in Pleasant Valley, Dallas Creek because she was seen among cattle. F25 was about 138 months old at death and in excellent physical condition (49 kg). Lost radio contact after 09-25-07− failed GPS/VHF collar. Recaptured F28 on the study area 02-01-10 and 01-01-11, but could not be handled to replace non-functional GPS collar. Dead. Killed by another puma (sex of puma unknown) 07-29-08. F30 was about 60 months old at death. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. F50 was about 30 months old at death. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. F54 was about 49 months old at death. Alive. Lost radio contact after 12-02-10. F72 recaptured in Fisher Creek on 03-18-11, but could not be handled to replace non-functional GPS collar. Lost radio contact after 09-29-09– failed GPS/VHF collar. F75 in association with her cubs M105 and F106 when F106 was recaptured on 02-10-10 on the study area. Alive. Dead. Shot dead on 02-01-11 by USDA, APHIS, WS agent for predation on domestic elk in Happy Canyon. F94 was about 74 months old at death. Alive. Alive. Alive. Dead. Killed by a puma hunter on 02-25-10 in GMU 70 East. F110 was about 41 months old at death. Alive. 209 �Puma I.D. F113 Monitoring span 01-26-10 to 06-06-10 F116 F118 F119 F135 F136 F137 F143 01-20-10 to 07-31-11 02-25-10 to 07-31-11 03-25-10 to 07-31-11 01-01-11 to 07-31-11 01-20-11 to 07-31-11 01-21-11 to 07-31-11 02-15-11 to 07-31-11 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Dead. F113 died 06-06-10 of injuries consistent with being struck by a vehicle. GPS data indicated that F113 had crossed highway 550 and roads on Loghill Mesa north of Ridgway 24-30 hours before she died in McKenzie Creek. F113 was about 42 months old at death. Alive. Alive. Alive. Alive. Alive. Alive. Alive. 210 �Table 15. Preliminary estimated survival rates (S) of adult-age pumas during the 4 years in the reference period (i.e., the study area is closed to puma hunting) and 2 years in the treatment period, Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma survival in the reference period pertained only to pumas that died of natural causes. Pumas that were killed by people in the reference period, a non-natural cause (i.e., two adult pumas: F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. In the treatment period all sources of natural and human-caused mortality are considered in the survival estimates. Biological Year S 1.000 Females SE 0.0000 S 0.667a Males SE 0.2222a n 6a Reference Annual 2 8/1/2005 to 7/31/2006 0.909 0.0867 11 1.000 0.0000 5 Reference Annual 3 8/1/2006 to 7/31/2007 0.831 0.0986 14 1.000 0.0000 7 Reference Annual 4 8/1/2007 to 7/31/2008 0.875 0.1031 13 1.000 0.0000 8 Reference Annual 5 8/1/2008 to 7/31/2009 0.784 0.1011 19 0.667 0.1924 8 Treatment Annual 1 8/1/2009 to 7/31/2010 Treatment Annualb 0.333b 0.1361b 12b 8/1/2009 to 7/31/2010 With mortalities of all marked adult males 0.947c 0.0568 19 0.250 0.1082 9 Treatment Annual 2 8/1/2010 to 7/31/2011 a Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. b This second estimate of adult male puma survival 8/1/2009 to 7/31/2010 includes 5 males that had non-functional (4) or shed (1) radiocollars. All adult males with non-functional or shed radiocollars in this study survived into treatment year 1 (TY1), which was expected considering adult male survival in 3 previous years. All 5 of those adult males were detected and killed by hunters in TY1. c Only 1 of 2 adult female puma mortalities is represented in this survival analysis for 8/1/2010 to 7/31/2011, that of F94 killed for depredation control. One other adult female mortality, F25, is not represented because she wore a nonfunctional GPS collar making it impossible for us to monitor her survival. F25 was shot by a ranch hand on 2/3/2011 when he saw her among cattle. 211 n 10 �Table 16. Summary of subadult puma survival and mortality, December 2004 to July 2011, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 04-19-06 to 04-26-06 31 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 M31 M69 01-11-08 to 04-07-08 7 190 87 Status Survived to adult stage. M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. Survived to adult stage. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Alive. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. Survived to adult stage. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. Survived to adult stage. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old, a young adult. Survived to adult stage. F52 dispersed from study area as a subadult by 01-16-07. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adult-stage home range. GPS collar nonfunctional. Dead. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. Survived to adult stage. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-1908. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. 212 �Table 16 continued Puma I.D. F95 Monitoring span 12-29-08 to 07-31-09 No. days 214 M99 02-27-09 to 04-22-09 54 M112 02-10-11 to 04-18-11 67 M115 01-13-10 to 07-21-10 189 M134 03-28-11 to 06-10-11 74 M138 01-26-11 to 06-30-11 03-07-11 to 07-13-11 03-08-11 to 04-28-11 03-08-11 to 03-23-11 155 M150 03-28-11 to 04-11-11 14 M153 04-12-11 to 07-31-11 110 M144 F145 F146 128 51 15 Status Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location) and an adult by about 24 month old (Aug. 2009). F95 established an adult home range adjacent to and overlapping the northern portion of her natal area. Dead. M99 probably killed by another puma (canine punctures in skull including braincase) in Jan. 2010 when he was about 16 months old. His radiocollar quit after 54 days. M112 was offspring of F70. Lost contact of M112 after 04-18-11; he may have dispersed or radiocollar quit. M112 associated with F96 and her two radio-collared cubs F129 and M130 during 02-10-11 to 04-1811. Dead. M115 was offspring of F28, born in Nov. 2008. He was about 14 months old when first captured on Jan. 13, 2010. When he was recaptured on 03-18-10, he had previously suffered a broken left ulna. M115 was probably independent by 07-15-10 when he was located outside of his natal area on a probably dispersal move. M115 died on about 07-21-10 apparently from complications of his broken left foreleg; probably not allowing him to kill prey sufficiently for survival. M115 was about 20 months old at death. M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Alive on the study area. Entered adult life stage 07-01-11. Dispersed. Last contact on 07-13-11 in Blue Creek, northwest Uncompahgre Plateau. Dispersed. Last contact on 04-28-11 in UC Creek, Deep Canyon, northwest Uncompahgre Plateau. Dead. F146 was killed and eaten by a male puma while in competition for an adult bull elk carcass that one of the pumas killed in Coal Canyon on the study area. F146 was about 19 months old at death. Dispersed. M150 was offspring of F111, born on 08-31-09. He was independent by 03-28-11 when he was 19 months old. Lost contact after 04-11-11 when M150 was in Cow Creek southeast of the study area. Alive on the study area. 213 �Table 17. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2011. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M5 02-04-05 13S,240577E, 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278E, 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M38 09-08-06 12S,746919E, 4225441N→ 13S,500000Ex 4050000N 13S,249200E, 4239703N→ 12S,703371E, 4316856N M39 09-11-06 71.3 M43 09-15-06 12S,724270E, 4243610N→ 12S,709889E, 4313490N 12S,760177E, 4242995N→ 12S,739859E, 4308557N M48 10-18-06 52.0 M49 12-05-06 12S,756676E, 4247777N→ 12S,704982E, 4248998N 12S,757241E, 4258259N→ 12S,693350E, 4274559N M58 06-27-07 13S,258543E, 4238071N→ 13S,274670E, 4309488N 73.2 Estimated linear dispersal distance (km)* 102.2 104.1 68.6 66.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M38 was offspring of F2, born July 29, 2006. Shed his expandable radiocollar by 03-06-07. Photographs by trail camera in McKenzie Cr. of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. M38 was killed by a hunter in Ladder Creek southwest of Grand Junction, CO on 01-07-11. He was 54 months old at death. M39 was offspring of F8, born August 2006. M39 was killed by a puma hunter in Bangs Canyon, GMU 40 on 03-12-10 when he was 43 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29 months old. M48 was the offspring of F3, born September 2006. M48 was killed by a puma hunter in Tabeguache Creek, GMU 61 North on 12-27-09 when he was 39 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 0124-09; he was about 29 months old. M58 was offspring of F16, born May 2007. M58 was killed by a puma hunter on 12-27-09 in the North Fork of the Gunnison River north of Paonia, GMU 521; he was 31 months old. 214 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M63 08-17-07 M65 08-17-07 M67 08-23-07 12S,738144E, 4233628N→ 12S,689111E, 4277908N 12S,738144E, 4233628N→ 12S,684084E, 4314200N 13S,257371E, 4235231N→ 12S,725113E, 4242447N M68 08-23-07 M69 01-11-08 M82 07-05-08 M83 07-05-08 M87 07-31-08 M88 13S,257371E, 4235231N→ 12S,711262E, 4198681N 13S,248191E, 4246810N→ 13T,378900E, 4591990N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 66.1 M63 was offspring of F24, born July 14, 2007. He was not radiocollared as a cub. M63 was killed by a hunter in Calamity Creek on northwest Uncompahgre Plateau on 01-01-11. M63 was 42 months old at death. 97.0 M65 was offspring of F24, born July 2007. M65 was killed by a USDA, APHIS, WS agent for depredation on llamas in the Little Dolores River on 11-07-09. M65 was 28 months old. 57.7 80.7 369.6 12S,726901E, 4243463N→ 13S,255316E, 4216768N 12S,726901E, 4243463N→ 12S,670949E, 4314779N 13S,239006E, 4248601N→ 12S,724325E, 4244118N 60.5 07-31-08 13S,239006E, 4248601N→ 12S,704835E, 4197839N 77.6 M92 09-29-08 13S,246359E, 4226949N→ 12S,750871E, 4222921N 21.9 M107 06-28-09 13S,242359E, 4252618N→ 12S,754886E, 4341330N 89.2 90.7 39.2 M67 was offspring of F30, born July 17, 2007 in Fisher Creek on the east slope of the study area. He was not radiocollared as a cub. M67 dispersed from the natal area and was recaptured in Tomcat Creek on the west slope of the study area on 02-24-10 when he was 31 months old. M67 is a resident adult in that area (07-3111). M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. M82 was offspring of F8, born May 29, 2008; sibling of M83 below. He shed his expandable cub radiocollar after 03-20-09. M82 was killed by a hunter on 12-10-09 in the Beaver Creek fork of East Dallas Creek, GMU 65. M82 was 19 months old. M83 was offspring of F8, born May 29, 2008; sibling of M82 above. He was not radiocollared as a cub. M82 was killed by a hunter on 01-18-11 in Coates Creek west of Glade Park, CO. He was 30 months old at death. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M88 below. He was not radiocollared as a cub. M87 dispersed from the natal area. He was recaptured on the west slope of the study area on 02-09-11 when he was 31 months old. M87 is a resident adult on the west slope of the study area to 07-31-11. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M87 above. He was not radiocollared as a cub. M87 dispersed from the natal area. He was killed by a hunter in Dawson Creek, Disappointment Valley on 11-30-10 when he was 29 months old. M92 was offspring of F25, born August 19, 2008. He was radiocollared as a cub; last contact on 12-12-08. M92 dispersed from the natal area and was recaptured in McKenzie Creek, west slope of the study area on 04-22-11 when he was 32 months old. He could not be handled to fit a new radiocollar because of a dangerous tree. M107 was offspring of F94, born May 25, 2009; sibling of F108 below. He was not radiocollared as a cub. M107 dispersed from the nata area. He was killed by a hunter in Cottonwood Creek near Molina, CO on 12-09-10 when he was 19 months old. 215 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M117 02-05-10 12S,731840E, 4232346N→ 12S,743909E, 4216633N M144 03-07-33 12S,727173E, 4242012N→ 12S,696439E, 4276888N F52 01-10-07 13S,258058E, 4236260N→ 13S,319217E, 4240467N F106 06-14-09 12S,736451E, 4240278N→ 13S,258089E, 4235866N F108 06-28-09 13S,242359E, 4252618N→ 12S,752013E, 4263883N F145 03-18-11 12S,727181E, 4241468N→ 12S,701196E, 4270127N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 19.7 M117 was offspring of F119. He wore an expandable cub collar, but shed the collar by 07-15-10 on the natal area when about 11 months old. M117 was killed by a puma hunter in Beaver Creek, San Miguel River at the southern extreme of his natal area on 0101-11. He was 17 months old at death. It is unknown if M117 was independent from his mother F119 at the time of his death. 46.6 M144 was initially captured as an independent subadult in association with subadults F145 and F146 on the study area. Mother is unknown. He moved off the study area on 03-15-11. M144’s last aerial radio location was in Blue Creek on northwest Uncompahgre Plateau on 07-13-11; he was about 22 months old. 61.1 F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old . F52 was treed again by puma hunters on about 12-16-09 south of Powderhorn: 13S,319480E,4233219N. F52 was about 53-55 months old. This suggests that F52 has an adult home range in that area. 46.9 F106 was offspring of F75, born May 7, 2009. She wore an expandable cub collar, but shed it about 03-23-10. F106 dispersed from the natal area and moved to the east slope of the study area where she was photographed at one of our scent station cameras at the mouth of Fisher Creek from 02-27-11 to 03-03-11. She was identified by her eartag. F106 was 21 months old. F108 was offspring of F94, born May 25, 2009; sibling of M107 18.2 above. She was fitted with an expandable cub collar; but, shed the collar in the original nursery due to failure of the fastener. F108 dispersed from the natal area. She was killed by a hunter on the study area on 11-29-10 when she was 17 months old. 38.6 F145 was originally captured in association of M144 and F146; they may be siblings. Mother unknown. She moved off the study area with M144 on 03-15-11. F145’s last aerial radio location was in UC Creek, Deep Canyon, North Fork Mesa Creek on northwest Uncompahgre Plateau on 04-28-11. She was about 19 months old. *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill, or last recapture, radio location, or observation site. 216 �Table 18. Recorded deaths of non-marked and marked pumas struck by vehicles and other unusual causes, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2011. Puma sex & ID if marked M Estimated age (mo) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870E,4227520N Highway 62 east of Dallas divide 13S,250000E,4222500N F17a 11 08-18-06 F 18-24 11-06-06 F 6 01-30-07 F P1005 36 09-16-08 M 12-24 08-13-08 F61a 18 11-13-08 F 12 08-10-09 F16b 80 09-11-09 M6b 99 05-21-0 F113b 42 06-06-10 Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown, decomposed Good Good Good Good Good Good Not pregnant or lactating M 24 08-25-10 Vehicle Excellent P1018c collision F 6 2/16/2011 Vehicle Good P1030c collision a Subadult marked (i.e., tattoos, eartags), but not radio-collared. b Adult GPS/VHF-collared pumas. c Non-marked puma with P one-thousand number designation. 217 Highway 550 south of Colona 13S,257602E,4242185N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718E,4255277N Highway 145 west of Placerville 13S,756490E,4212336N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 145 east of Norwood 12S,745739E,4222548N Ouray County Road 1 13S,253733E,4240060N Highway 550 south of Colona 13S,258610E,4236805N F113 crossed Highway 550 and roads on Loghill Mesa 24-30 hours before she died in McKenzie Creek 13S,257272E,4238435N Highway 62 Leopard Creek 12S,237747E,4220330N Highway 62 Leopard Creek 12S,760953E,4216683N �Table 19. Numbers of GPS locations and spans of monitoring for pumas captured on the Uncompahgre Plateau, Colorado, December 2004 to August 2011. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 M133 F2 F3 F7 F8 F16 F23 Sex Age stage Dates monitored a M M M M M M M M M F F F F F F No. locations adult 12-08-04 to 07-20-06 1,797 adult 01-28-05 to 01-14-06 958 adult 02-18-05 to 05-14-08 1,035 adult 03-12-06 to 06-21-06 313 adult 04-14-06 to 01-01-08 1,599 adult 01-07-07 to 07-15-08 1,643 adult 01-21-07 to 11-25-10 3,523 adult 03-27-09 to 01-16-10 923 adult 11-12-10 to 12-01-10 45 adult 01-07-05 to 08-14-08 3,516 adult 01-21-05 to 04-19-11 4,862 adult 02-24-05 to 08-03-08 3,922 adult 03-21-05 to 10-10-06 1,541 adult 10-12-05 to 09-10-09 3,801 subadult, 01-04-06 to 02-04-06 113 adult 02-05-06 to 09-04-09 2,281 F24 F adult 01-17-06 to 07-25-07 1,812 F25 F adult 02-09-06 to 09-09-09 3,653 F28 F adult 03-24-06 to 08-15-07 1,499 F30 F adult 03-30-07 to 02-22-08 1,057 F50 F adult 12-14-06 to 03-26-07 352 F52 F subadult 01-10-07 to 05-08-07 383 F54 F adult 01-12-07 to 08-18-08 723 F70 F adult 01-14-08 to 06-09-11 3,359 F72 F adult 02-12-08 to 07-07-10 2,842 F75 F adult 03-26-08 to 06-03-09 1,112 F96 F adult 01-28-09 to 04-20-11 1,619 F104 F adult 05-29-09 to 11-04-10 1,632 F111 F adult 01-01-10 to 07-12-11 1174 F113 F adult 01-27-10 to 06-06-10 445 F135 F adult 01-01-11 to 08-15-11 787 F136 F adult 01-20-11 to 08-08-11 649 F137 F adult 04-12-11 to 08-15-11 235 a GPS collars on pumas were remotely downloaded at approximately 1-month intervals, except during winter 20082009 to summer 2009 due to shortage of technicians during hiring freeze to assist in airplane flights to obtain downloads and to capture pumas to replace GPS collars (lengthening the download interval saved battery power). The last date in Dates monitored includes last location from the last GPS data download acquired for an individual puma. 218 �Table 20. Summary results of exploratory use of scents and hair snags to detect individual wild pumas, November 2010 to August 2011, Uncompahgre Plateau, Colorado. Scent used No times scent used at 9 sites No. puma visits No. individual puma visits . No. times pumas rubbed Beaver castorium Catnip oil 16 8 5 5 2 0 Catnip/Spotted Fever MT Lynx 1 1 7 8 Obsession for Men 11 16 Spotted Fever 7 4 3 (Unm F, F72, F106) 2 (unm M, M153) 1 (unk sex & age) 4-5 (M153, 12 of unk sex & age, 2 unm M) 5-6 (F72, F106, F136, M153, unm M, unidentifiable) 4 (F3, F25 & 3 cubs, F96, M32) No. times hair was collected from device 5 No. individual pumas detected Max. detection probability (defined in text) 0 2 (Unm F, F106) 0 0.667 (2/3) 0.0 0 0 0 0.0 1 1 1 (unm, unk sex and age) 0.200-0.250 (1/5 to 1/4) 3 3 2(F106, F136) 0.333-0.400 (2/6 to 2/5) 1 1 1 (F25 & cubs) 0.250 (1/4) Totals 39 10 10 Table 21. Variation in individual puma response to scents, November 2010 to August 2011, Uncompahgre Plateau, Colorado. Individual F3 F25 (& 3 cubs) F72 F72 F96 F106 F106 F136 Unmarked Female, unk age M32 M153 M153 M153 Unmarked Male, unk age Unmarked Male, unk age Unmarked Male, unk age Unmarked Male, unk age Unmarked, unk sex and age Unmarked, unk sex and age Unmarked, unk sex and age Unknown if marked, unk sex and age Scent Spotted Fever Spotted Fever Beaver Castorium Obsession for Men Spotted Fever Beaver Castorium Obsession for Men Obsession Beaver Castorium Spotted Fever Obsession for Men Catnip MT Lynx Obsession MT Lynx MT Lynx Catnip Spotted Fever & Catnip MT Lynx MT Lynx Obsession 219 No. times rubbed/ No. of visits 0/1 1/1 0/2 0/3 0/1 4/5 1/1 2/7 1/1 0/1 0/2 0/1 0/2 0/2 0/2 0/1 0/1 0/1 0/2 1/1 0/1 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Methods for Monitoring Populations Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 220 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Figure 3. Trends in the population of independent pumas on the Uncompahgre Plateau Puma Study Area, including Reference Years 4 and 5 (RY4, RY5) and Treatment Years 1 and 2 (TY1, TY2). Numbers represent minimum counts that include all pumas from known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during fall to spring hunting and research capture seasons, except RY5 (45), which had to be modeled from RY4 observation data (33) because the hiring freeze that year affected search and capture efforts. The actual minimum count for RY5 was 37 independent pumas. The quota of 8 pumas for TY1 represented a 15% harvest of the model projected 53 independent pumas expected in TY1 and was used to set the quota ahead of the hunting season. Starting in TY1, two capture teams were deployed to 221 �count pumas on the study area because the hunting season shortened our fall-winter-spring research period. We deployed a team on each the east and west sides of the study area. The minimum count for TY1 was actually 55 independent pumas, consistent with the model expected 53. We made further team changes for TY2, which made our efforts more efficient and successful. Yet, in TY2 we counted slightly less (52) independent pumas than in TY1 (55). Post-harvest high trend line represents the population of independent pumas after pumas harvested only on the study area by hunters. This trend line represents 14.5% to 15.4% harvest of independent pumas. Post-harvest low trend line represents the population of independent pumas after pumas harvested on the study area and pumas harvested when they ranged onto adjacent GMUs open to hunting. The TY2 postharvest low also includes 2 adult female pumas killed February 1, 5, 2011 on the study area to protect livestock (F25 killed while seen by a ranch hand among cattle; F94 killed for preying on domestic elk). This trend line represents 21.2% to 21.8% harvest of independent pumas. Figure 4. Estimated age structure of independent pumas in November 2010 at the beginning of the puma hunting season in Treatment Year 2 (TY2) on the Uncompahgre Plateau, Colorado. All these pumas were captured and sampled by researchers or harvested by hunters and examined by researchers. Mean ± SD of female and male ages, respectively: 4.87 ± 3.11 yr. (58.40 ± 37.26 mo.), n = 25; 3.51 ± 2.59 yr. (42.07 ± 31.08 mo.), n = 14. 222 �Figure 5. Puma births (black bars) detected by month from May 19, 2005 to April 22, 2011 (n = 40 litters of 21 females; 38 of the litters were examined at nurseries when cubs were 26-42 days old and 2 litters confirmed by tracks of ≥1 cubs following GPS-collared mothers F28 and F111 when cubs were ≤42 days old). Also shown (gray bars) are results of the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1 to 8 months old), Uncompahgre Plateau, Colorado. 223 �Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2010, Uncompahgre Plateau, Colorado. Puma I.D. M5 Estimated Age at capture (days) 183 Est. Birth date ~8-1-04 Est. survival span from 1st capture to fate or last monitor date 02-04-05 to 04-07-08 Age to last monitor date alive or at death (days, birth to fate) 31 5-28-05 F10 31 5-28-05 M11 31 5-28-05 F12 42 F13 Mother I.D. Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 4.5 years old. Lost contact― shed radiocollar 04-19-06 to 04-26-06. F3 Lost contact― shed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-20-05. F10 disappeared by 12-30-05. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 07-11-06 at 14 mo. old. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old. Lost contact― shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 1208-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Dead; killed and eaten by a puma (sex unspecified) about 828-05. Lost contact― shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Lost contact― shed radiocollar 06-06-06 to 06-14-06. F2 F16 308-314 Dead. Lost contact― shed radiocollar 06-06-06 to 06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Dead; probably killed by another puma. Multiple bite wounds to skull. 10 mo. old. Lost contact― shed radiocollar 07-27-06 to 08-02-06. 244-245 Lost contact― shed radiocollar 05-24-06―05-25-06. F16 Lost contact; radiocollar quit. Last aerial location 8-16-06, live signal. F3 ~1,345 F9 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 06-27-05 to 12-2-07 326-333 5-19-05 07-01-05 to 12-08-05― 01-26-06 203-252 42 5-19-05 101 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 F21 37 9-26-05 176-215 918 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 11-02-05 to 08-16-06 301-308 330 324 224 F2 F2 F7 F7 F8 F8 F16 F16 �Appendix A continued Puma I.D. Estimated Age at capture (days) M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 5-30-06 F35 31 5-30-06 F36 29 6-9-06 M37 29 6-9-06 M38 41 7-29-06 M39 29 8-13-06 Est. Birth date F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 12-21-05― 12-22-05 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 86-87 Dead; killed and eaten by male puma 12-21-05―12-22-05. F3 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 06-30-06 to 07-31-06 ~232-235 Lost contact― shed radiocollar 03-21-06―03-24-06. F25 F23 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 38 Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Dead. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Lost contact― shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. F28 Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 03-12-10 in GMU 40 when 43 months old. Lost contact― shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F8 Assumed dead. Lost Contact― shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 Lost contact− shed radiocollar by 11-7 to 17-06. Treed 0301-07. Killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO at 29 months old. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 01-28-09 in GMU 41 when 29 months old. F7 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 63-65 63-65 74 74 352-353 9 255 9 255 53-61 106 200 225 Mother I.D. F23 F23 F28 F2 F8 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M44 33 Est. Birth date 8-13-06 Est. survival span from 1st capture to fate or last monitor date 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 183 7-1-06 360 89 360 12-05-06 to 07-31-07 to 01-01-07 F53 89 01-12-07 to 02-23-07 ~456 42 ~428 subad. 226 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Lost contact− shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. Killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. He was still dependent on F7. Dead. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 2006. Last date F45 was with F2 was 04-17-07. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Lost contact― shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 61 when 39 months old. M49 was orphaned when his mother died on about 03-2607; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau (GMU 61 N) 01-24-09 when ~29 months old. Lost contact― shed radiocollar 2-23-07. F53 visually observed by P. & F. Star, on 9-2-07, when F53 was ~14 months old and an independent subadult. Mother I.D. F7 F7 F3 F3 F3 F50 F54 �Appendix A continued Puma I.D. Estimated Age at capture (days) M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 200 Lost contact― shed radiocollar 2-27-07. M56 observed 0301-07. Lost contact― shed radiocollar 06-07-07. Live mode 06-0607. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 521 when 31 months old. Alive. Observed alive 11-20-07 with F16, but without siblings M58 & F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. F7 (?) Dead; research-related mortality.d F16 Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11/13/08. Not radio-collared. Not radio-collared. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Survived to adult stage; dispersed from natal area. Killed by Wildlife Services for depredation control on 11-07-09 when 28 months old. F16 52 324 434 F59 34 5-24-07 06-27-07 to 08-21-07 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 08-17-07 262 M65 34 7-14-07 08-17-07 262 227 F25 F16 F16 F24 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) F66 37 Est. Birth date 7-17-07 Est. survival span from 1st capture to fate or last monitor date 08-23-07 to 11-05-07 Age to last monitor date alive or at death (days, birth to fate) Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Dispersed from natal area. Established adult home range on west side of Uncompahgre Plateau. Alive as of 07-31-11. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in Disappointment Valley, CO (GMU 71) 12-30-08 at 17 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 8/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. 111 681 M67 37 7-17-07 08-23-07 M68 37 7-17-07 08-23-07 1475 532 F74 259 6-1-07 5-19-08 03-12-08 to 07-09-08 06-18-08 M76 30 ~87 M77 30 5-19-08 06-18-08 ~87 F78 30 5-19-08 06-18-08 ~87 M79 30 5-19-08 06-18-08 87 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 228 Mother I.D. F30 F30 F30 F75 F2 F2 F2 F2 �Appendix A continued Puma I.D. Estimated Age at capture (days) F80 40 F81 F97 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) 5-23-08 Est. survival span from 1st capture to fate or last monitor date 07-02-08 40 8 ½ mo. 5-23-08 5-23-08 07-02-08 to 07-29-09 02-04-09 424 354 M82 37 5-29-08 07-05-08 to 03-20-09 or 04-02-09 295-308 M83 37 5-29-08 07-05-08 M84 36 6-5-08 07-11-08 to 02-11-09 F85 36 6-5-08 07-11-08 F86 36 6-5-08 07-11-08 to 07-23 to 08-03-08 ~48-59 M87 28 7-3-08 07-31-08 1123 M88 F89 M90 28 28 36 7-3-08 7-3-08 7-9-08 07-31-08 07-31-08 08-14-08 251 867 229 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Not radio-collared. Apparently died before 2-4-09; no tracks found in association with F23 & siblings F81 & F97. Radio-collared. Last live location 7-29-09. Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Radio-collared. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in 12-10-09 GMU 65 when 19 months old. Not radio-collared. Apparently died; no tracks found in association with F8 & sibling M82 2-10-09. Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located here on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 211-09. F23 Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill. Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Dispersed from natal area. Recaptured as adult on west slope of study area on 02-09-11. Alive as of 07-31-11. Not radio-collared. Radio-collared. Radio-collared. Recaptured as young adult on study area, adjacent to natal area, on 11-16-10. Killed by a puma hunter during TY2 on 11-23-10. F70 F23 F23 F8 F8 F70 F70 F3 F3 F3 F72 �Appendix A continued Puma I.D. Estimated Age at capture (days) Male 7A 28-35 7-10-08 Male 7B 28-35 Female 7C Est. Birth date Est. survival span from 1st capture to fate or last monitor date ~08-07-08 to 08-14-08 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 28 to 35 F7 7-10-08 ~08-07-08 to 08-14-08 28 to 35 28-35 7-10-08 28 to 35 M91 M92 35 35 8-19-08 8-19-08 ~08-07-08 to 08-14-08 09-29-08 09-29-08 F95 16 mo. June-07 12-29-08 F98 4-5 mo. 5 mo. 02-12-09 to 03-08-09 2-27-09 to 01-2010 146-176 M99 Sep-Oct08 Sep-Oct08 M101 35 4-15-09 157 M102 35 4-15-09 05-20-09 to 09-19-09 05-20-09 F103 35 4-15-09 159 M105 38 5-7-09 F106 38 5-7-09 05-20-09 to 09-17-09 06-14-09 to 02-09-10 06-14-09 to 02-27-11 Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died of starvation after orphaned. F7 shot on 8-3-08 for killing domestic sheep. Radio-collared. Radio-collared. Lost contact after 12-12-08. Dispersed from natal area. Recaptured in McKenzie Creek, west slope of study area on 04-22-11 when 32 months old. Radio-collared. Survived to adult stage. Established adult home range overlapping mother F93’s home range. Radio-collared. Died, probably killed by male puma (infanticide). Radio-collared. Last location 4-22-09 on Paterson Mt. Died as 16-month old subadult in San Miguel Canyon. Probably killed by another puma. Radio-collared. Died; killed by puma M55 after cub was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 9-4-09. Did not find evidence of M102 associated with deaths of siblings M101 and F103. But M102 probably died. Radio-collared. Died; killed by puma M55 after cub was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 2-9-10 due to shed collar. F75 M107 34 5-25-09 Not radio-collared at nursery; F75 returned to nursery during handling. Radio-collared later on 2-10-10. Lost contact due to shed collar 3-16 to 29-10. F106 dispersed from natal area and was photographed at 21 months old at camera and scent-rub station on east slope of Uncompahgre Plateau on 02-27-11. Not radio-collared; too small. Recaptured 2-24-10; not collared. 06-28-09 to 02-24-10 976 488 278 275 661 241 230 Mother I.D. F7 F7 F25 F25 F93 Unm.F Unm.F F16 F16 F16 F75 F94 �Appendix A continued Puma I.D. Estimated Age at capture (days) F108 34 Est. Birth date 5-25-09 Est. survival span from 1st capture to fate or last monitor date 06-28-09 to 03-05-10 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. M115 14 mo. Nov.-08 07-21-10 610 M117 6 mo. Aug.-09 02-05-10 275 P1016(M) 39 6-12-10 06-12-10 to 07-21-10 39 P1017(M) 39 6-12-10 06-12-10 to 07-21-10 39 M120 30 6-28-10 157 M121 30 6-28-10 273 Radio-collared. Lost radio contact after 03-28-11. F3 M122 35 7-8-10 07-28-10 to 12-02-10 07-28-10 to 03-28-11 08-12-10 to 04-28-11 Shed radiocollar at nursery; fastener failed. Recaptured and re-collared 2-24-10. Shed collar ~3-5-10. Dispersed from natal area. Killed by a puma hunter on the study area during TY2 on 11-29-11. Not radio-collared; too small. Radio-collared. Lost contact after 5-4-10 (last live signal) possibly due to failed transmitter. Recaptured and re-radiocollared on 01-24-11. Independent subadult during 02-10-11 to 04-18-11. Lost contact after 04-18-11; he may have dispersed or radiocollar quit. Radio-collared. M115 died as a subadult (~20 mo. old) due to complications of a broken left foreleg (natural cause). Radio-collared. Lost contact after 5-14-10 (last live signal); shed collar found on 7-15-10 in the natal area. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Radio-collared. Lost radio contact after 12-02-10. 274 F104 F123 29 7-15-10 F124 29 7-15-10 M125 29 7-15-10 M126 28 08-08-10 M127 28 08-08-10 Radio-collared. Lost radio contact after 04-28-11. Tracks of 2 other siblings of M122 observed on 01-11-11 (neither cub marked). Radio-collared. Killed on 02-17-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Killed on 02-16-11 for depredation control on domestic elk by elk farm manager. Radio-collared. Killed on 02-01-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Radio-collared. Lost radio contact after 07-01-11; shed his radiocollar about 07-01-11. 553 M109 M112 34 145 5-25-09 8-31-09 06-28-09 05-04-10 528 595 08-13-10 to 02-17-11 08-13-10 to 02-16-11 08-13-10 to 02-01-11 09-05-10 to 03-17-11 09-05-10 to 07-01-11 217 216 201 221 327 231 F94 F94 F70 F28 F119 F72 F72 F3 F94 F94 F94 F118 F118 �Appendix A continued Puma I.D. Estimated Age at capture (days) M128 28 08-08-10 F129 35 08-21-10 M130 35 08-21-10 09-25-10 to 10-23-10 M131 35 08-21-10 F132 35 08-21-10 09-25-10 to 07-21-11 09-25-10 M134 ~18 mo. ~June-09 12-14-10 to 06-10-11 731 M139 36 04-18-11 05-24-11 to 07-29-11 102 F148 36 04-18-11 05-24-11 to 07-29-11 102 F140 ~5 mo. ~Aug.10 01-02-11 to 04-18-11 258 M141 ~5 mo. ~Aug.10 01-02-11 to 04-01-11 241 M142 ~5 mo. ~ 6 mo. 01-02-11 to 04-18-11 02-16-11 258 P1030 F147 ~7 mo. ~Aug.10 ~Aug.10 ~Sep.-10 F149 45 04-22-11 M150 525 08-31-09 04-21-11 to 07-31-11 06-06-11 to 07-31-11 02-07-11 to 04-11-11 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-05-10 to 02-22-11 09-25-10 to 04-28-11 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 198 F118 315 Radio-collared. Lost radio contact after 02-22-11; radiocollar probably quit. Radio-collared. Fate unknown. Transmitter on mortality mode on 04-28-11. Unable to get to collar until 06-23-11 due to high spring run-off, by then the transmitter had quit. Radio-collared. Died of natural causes associated with injury to right shoulder during first move away from nursery about 10-23-10. Radio-collared. Lost contact after 07-21-11. Shed his radiocollar about 07-27-11. Not radio-collared. Too small for collar design. Fate unknown. Radiocollared as dependent large cub. Independent by about 03-28-11. Dead; killed for depredation control by Wildlife Services agent on 06-10-11. Radio-collared. Dead of infanticide and cannibalism along with sibling F148; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Dead of infanticide and cannibalism along with sibling M139; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Lost contact. Shed first collar about 01-2411. Recaptured and re-collared on 04-01-11. Shed second collar after 04-18-11. Radio-collared. Lost contact; shed radiocollar about 03-2911. Recaptured, but could not be handled safely on 04-0111. Radio-collared. Lost contact after 04-18-11 due to shed collar. Struck by vehicle and killed on state highway 62 in Leopard Creek, south boundary of study area on 02-16-11. Radio-collared. 100 Radio-collared. F23 588 Radio-collared. M151 was independent by 03-28-11 at 19 mo. old. He dispersed from the natal area by 04-11-11 at 19.5 mo. old. Contact lost after 04-11-11. F70 250 63 334 35 183 232 F96 F96 F96 F96 Unm. F F8 F8 Unk./ F28? Unk./ F28? Unk./ F28? Unk. F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) M151 253 06-16-10 F152 06-06-10 271 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 02-24-11 to 03-07-11 03-14-11 to 03-21-11 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 264 Radio-collared. Lost contact after 03-07-11 (GPS location of mother F111 at shed collar of M151). Radio-collared. Lost contact after 03-21-11; shed collar. F111 271 a F93 Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, probably restricted movement. b 233 �Appendix B. Summary of exploratory use of scents and hair snags to detect individual pumas, 2010 to 2011, Uncompahgre Plateau, Colorado. Details on behaviors of pumas and other wildlife that visited the camera-scent stations are not included in this appendix, but are in original data file. Time puma was at site (min.) No. photos of puma Time lapse between scent treatment and puma visit (days) Scent type/name Closest puma distance estimate to scent pad-hair snag (m) Rub response by puma (yes, no) Date MS Time Puma Sex Age stage Female Reproductive Status HS01 11/27/2010 9:39 F96 F Adult Cubs 6 mo. old 1 2 7 Spotted Fever 0.3 no HS01 12/8/2010 16:40 unmarked F Adult Unk 5 114 2 Beaver Castor 0 yes HS02 11/29/2010 15:40 F3 F Adult Cubs 5 mo. old 1 6 9 Spotted Fever 0.6 no HS03 2/27/2011 6:10 F106 F Adult No cubs 3 95 12 Beaver Castor 0 yes yes HS03 2/27/2011 17:45 F106 F Adult No cubs 5 48 12 Beaver Castor 0 yes yes HS03 2/28/2011 18:38 F106 F Adult No cubs 74 572 13 Beaver Castor 0 yes yes HS03 3/1/2011 6:31 F106 F Adult No cubs 1 15 14 Beaver Castor 0 no HS03 3/2/2011 18:37 F106 F Adult No cubs 13 297 15 Beaver Castor 0 yes yes HS03 3/3/2011 18:23 F106 F Adult No cubs 4 107 16 Obsession 0 yes yes HS03 3/7/2011 20:26 F136 F Adult No cubs 1 18 4 Obsession 3 no HS03 3/11/2011 4:41 F136 F No cubs 5 54 8 Obsession 0 yes HS03 4/11/2011 0:31 unmarked M Adult 1 3 3 Catnip 1.5 no HS03 4/13/2011 22:18 M153 M Sub-adult 1 3 5 Catnip 0.6 no HS03 5/16/2011 21:54 unmarked Unk Unk 1 4 4 Catnip/Spotted Fever 0.6 no HS03 6/11/2011 22:56 unmarked M Adult 1 9 2 Obsession 0.3 no HS03 7/6/2011 17:59 unmarked Unk Unk 1 11 0 MT Lynx 0.1 no HSO4 11/22/2010 5:34 M32 M Adult 1 10 4 Spotted Fever 0.6 no HS04 12/3/2010 17:40 F25 & 3 cubs F Adult 7 243 3 Spotted Fever 0 yes Camera site I.D. Cubs 8-9 mo. old 234 Hair on snag collected yes yes yes �Appendix B continued. Time puma was at site (min.) Time lapse between scent treatment and puma visit (days) Closest puma distance estimate to scent pad-hair snag (m) Date MS Time Puma Sex Age stage Female Reproductive Status HS04 2/24/2011 16:04 F72 F Adult No cubs 3 44 9 Beaver Castor 0 no HS04 2/25/2011 15:36 F72 F Adult No cubs 1 15 10 Beaver Castor 0 no HS04 3/8/2011 6:33 F72 F Adult No cubs 1 21 5 Obsession 0 no HS04 3/8/2011 20:51 F72 F Adult No cubs 1 21 5 Obsession 3.5 no HS04 3/16/2011 3:29 F72 F Adult No cubs 1 13 Obsession 3.5 no HS04 3/18/2011 21:32 Not identifiable Unk Unk Unk 1 9 15 Obsession 3 no HS04 4/14/2011 2:03 F136 F Adult No cubs 1 9 6 Obsession 3.5 no HS04 4/15/2011 4:40 F136 F Adult No cubs 1 15 7 Obsession 0.3 no HS04 4/16/2011 4:40 F136 F Adult No cubs 1 6 8 Obsession 3 no HS04 4/18/2011 18:20 F136 F Adult Pregnant 1 15 10 Obsession 0 yes HS04 4/25/2011 23:52 M153 M Sub-adult 1 15 17 Obsession 0.3 no HS04 5/2/2011 19:31 unmarked M Adult 1 27 24 Obsession 0 no M Sub-adult 1 9 31 Obsession 3 no Adult 1 12 32 Obsession 2.3 no MT Lynx 1.5 no Camera site I.D. HS04 5/9/2011 15:36 VHF male 150 or M153 HS04 5/10/2011 1:07 F136 F HS04 7/15/2011 unmarked M HS06 6/29/2011 1:39 M153 M HS06 7/4/2011 18:21 unmarked HS06 7/15/2011 19:36 unmarked M HS07 7/8/2011 3:02 M153 M HS09 7/24/2011 21:01 unmarked Unk Pregnant No. photos of puma 4 Sub-adult Sub-adult Scent type/name Rub response by puma (yes, no) 1 33 7 MT Lynx 0.3 no 1 6 12 MT Lynx 0.3 no 1 3 23 MT Lynx 0.3 no 1 15 16 MT Lynx 0 no 1 9 25 MT Lynx 1.3 no 235 Hair on snag collected yes no �Appendix B continued. Camera site I.D. HS09 Date MS Time Puma Sex 8/6/2011 5:44 unmarked Unk Age stage Female Reproductive Status Time puma was at site (min.) No. photos of puma Time lapse between scent treatment and puma visit (days) 2 21 38 236 Scent type/name Closest puma distance estimate to scent pad-hair snag (m) Rub response by puma (yes, no) Hair on snag collected MT Lynx 0 yes yes �Colorado Division of Parks and Wildlife July 2010 - June 2011 State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 2 Federal Aid Project No. N/A WILDLIFE RESEARCH REPORT : Division of Parks and Wildlife : Mammals Research : Predatory Mammals Conservation : Cougar Demographics and Human Interactions : Along the Urban-Exurban Front-range of : Colorado Period Covered: July 1, 2010 - June 30, 2011 Author: M.W. Alldredge Personnel: E. Joyce, T. Eyk, J. Halseth, G. Coulombe, R. Platte, K. Blecha, K. Yeager, L. Nold, K. Griffin, D. Kilpatrick, M. Paulek, B. Karabensh, D. Wroe, M. Miller, F. Quartarone, M. Sirochman, L. Wolfe, J. Duetsch, C. Solohub, K. Cannon, J. Koehler, L. Rogstad, R. Dewalt, J. Murphy, D. Swanson, T. Schmidt, T. Howard, D. Freddy CPW; B. Posthumus, Jeffco Open Space; D. Hoerath, K. Grady, D. Morris, A. Hatfield Boulder County Open Space; H. Swanson, R. Hatfield, J. Reale Boulder Open Space and Mountain Parks; S. Oyler-McCance, USGS. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Sampling cougar feces in the field may be a feasible non-invasive sampling method to estimate cougar populations. We finished analyzing cougar fecal samples collected from the 3 sibling cougars in captivity at the Foothills Wildlife Research Facility. Feces were stored at controlled temperatures after deposition and sub-sampled at monthly intervals. Genetic material has been found in samples up to 6 months post-deposition, but genotyping error rates have not yet been assessed. We are investigating degradation rates further by sampling feces in natural, uncontrolled, environments deposited at known times from known individuals. All samples have been obtained and genotyped, and final analysis and a summary report is in progress. The use of telomeres as a method to determine the age structure of bear and cougar populations has continued to be examined. Further refinement of the age-to-length relationship for both species is warranted based on preliminary results. We have begun a Ph.D. project with the University of Wisconsin to examine telomeres in detail for bears. This project will also look at stable isotopes to examine foraging ecology and bear use of human food sources. Some pilot work is also being done to examine stable isotopes for cougars relative to predation on domestic animals. Our principal research objective is to assess cougar population ecology, prey use, movements, and interactions with humans along the urban-exurban front-range of Colorado. This year capture efforts focused on re-collaring previously collared cougars, and capturing previously unmarked independent age cougars and cubs. We collared an additional 17 independent age cougars. Mortality remained high over the year with 6 additional mortalities for independent age cougars (predominantly human related). Home- 237 �range patterns remained consistent to previous years. The effectiveness of aversive conditioning is still showing mixed results, which is likely a factor of the opportunistic nature of cougars using urban environments and a lack of habituation to them. Cougar/human interactions were minimal this year compared with previous years. Relocation of cougars as a management tool has had limited assessment, but given some success, still warrants further investigation. Mule deer are the predominant prey in cougar diets, although males will also utilize elk regularly. 238 �WILDLIFE RESEARCH REPORT COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBANEXURBAN FRONT-RANGE OF COLORADO MATHEW W. ALLDREDGE P.N. OBJECTIVE 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban front-range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus) and estimating population densities of cougars for the state of Colorado. SEGMENT OBJECTIVES Section A: Genetics 1. Evaluate differences in DNA quantity from either a scat surface collection or a cross-sectional collection. 2. Evaluate differences in DNA quantity from successive feces depositions to determine the variation in quantities of genetic material in scats. Quantify differences in epithelial shedding rates. 3. Evaluate temporal, environmental, and seasonal effects on fecal DNA quantity and quality for both controlled and uncontrolled conditions. Section B: Telomeres and Stable Isotopes 4. Evaluate the potential to develop a model for estimating age of bears and cougars based on telomere length. 5. Determine diet composition of bears and cougars using stable isotopes. Section C: Front-range cougars 5. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. 6. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets. 7. Continue to assess relocation of cougars as a practical management tool. 8. Assess cougar predation rates and diet composition based on GPS cluster data. 9. Model movement data of cougars to understand how cougars are responding to environmental variables. 10. Develop non-invasive mark-recapture techniques to estimate cougar population size. SECTION A: GENETICS BY M. ALLDREDGE INTRODUCTION Genetic techniques for monitoring or research of rare, elusive, and wide ranging species are of particular interest as other techniques are either impractical or financially prohibitive. Genetic techniques for monitoring and research of cougars in Colorado may be invaluable as alternative techniques are expensive and in many situations may not be possible. Capture and handling of cougars is expensive, time consuming, and may not give representative samples of the population. Large dispersal distances of cougars, especially males, will require impractically large study areas in order to understand demographic 239 �patterns that are affected by immigration. Capture may not even be possible in suburban and exurban areas of Colorado as logistical constraints associated with private land owners will likely prohibit the use of many capture techniques. Noninvasive genetic sampling (Hoss et al. 1992, Taberlet and Bouvet 1992) has the potential to provide a realistic method of sampling a population of interest. Noninvasive sampling techniques include the use of hair snares, and scat collections (Harrison et al. 2004, Smith et al. 2005). The use of scats for sampling cougar populations may be particularly useful and provide a representative sample of the population. Scat collections can either be done by searching transects with human observers (Harrison et al. 2004) or with trained dogs (Smith et al. 2005). Scats could also be collected from kill sites. Kill sites would need to be based on mortalities of radio-collared ungulate populations. Data from noninvasive sampling techniques are useful in describing dispersal patterns and estimating population size. Noninvasive genetic data are error prone, which in many cases is due to the quantity and quality of genetic material collected. Therefore, we developed a study to evaluate degradation rates of DNA in fecal samples with respect to time and temperature. STUDY AREA The genetic degradation study is being conducted at the Foothills Wildlife Research Facility, located in Fort Collins, Colorado. Three sibling cougars have been raised in captivity at this facility and are part of other ongoing research efforts. METHODS Fecal samples were collected from the 3 sibling cougars located at the Foothills Wildlife Research Facility. Sixty feces per cougar were collected and samples were placed at random into one of three treatment groups (-5 C, +5 C, and +15 C). Genetic samples were extracted from feces at the time of initial collection and at 2 weeks, and 1, 2, 3, 4, and 6 months post deposition. DNA was extracted and then stored at -20 C Response variables that are being measured are number of incorrect identifications, allelic dropout rates (actual number of alleles that dropout in any given sample), and number of false alleles. The primary analysis is a logistic regression on the dichotomous identification variable, treating the three temperature regimes as covariates. Additional analyses summarize the rate at which alleles dropout and the occurrence of false alleles. A total of 60 scats have been collected and sub-sampled at each time period within treatment groups. PCR and DNA sequencing is being done at the Rocky Mountain Center for Conservation Genetics and Systematics laboratory. Individual cougars are screened and genotyped using 9 -12 nuclear microsatellite loci isolated from domestic cat (Menotti-Raymond and O’Brien 1995, Menotti-Raymond et al. 1999). Three recent studies have used sets of these primers successfully on mountain lions (Ernest et al. 2000, Sinclair et al. 2001, Anderson et al. 2004). We chose a set of these primers for our work. PCRs were performed using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). Each 12.5μl reaction contained 125μM each dNTP, 1X Taq buffer (Kahn et al. 1998), 0.034μM M13-tailed forward primer, 0.5μM non-tailed reverse primer, 0.5μM M13 dye-labeled primer with Beckman Coulter dyes D2, D3 or D4 (Proligo), and 0.31U Taq polymerase (Promega). The thermal profile for both the forward dye-labeled and the M13 dye-labeled reactions were as follows with the appropriate annealing temperature varying by locus: preheat at 94°C for 1 min, denature at 94 ºC for 1 min, anneal for 1 min, and extend at 72 ºC for 1 min for 35 cycles. The PCR products were diluted and run on the CEQ8000 XL DNA Analysis System (Beckman Coulter). All loci were run with the S400 size standard (Beckman Coulter) and analyzed using the Frag 3 default method. 240 �RESULTS AND DISCUSSION All samples have been collected and samples have been genotyped. Approximately 30 samples were collected in the field from radio-marked cougars over a range of deposition times and these have been genotyped as well. This work is still ongoing so an assessment of genotyping error rates has not been made. However, sufficient genetic material for genotyping has been found in samples up to 6 months old. Genetic degradation appears to occur at a slower rate than initially expected. This would indicate that scat surveys for individual identification of cougars may be a viable non-invasive sampling technique, if an efficient means of finding cougar scat in the field is available. SECTION B: BEAR TELOMERES AND STABLE ISOTOPES BY M. ALLDREDGE OVERVIEW Understanding the age structure of a population is very useful to managers, especially for hunted populations. Age structure can provide indications about the appropriateness of current harvest levels, changes that may need to occur in harvest, and the general health of a population. Typical approaches involve estimating age structure based on sampling harvested animals and obtaining ages based on tooth wear and replacement characteristics or from analyzing tooth annuli. Recently a new approach has been developed for some species that estimates the age of animals based on examining the length of telomeres in relation to the age of the animals. Telomeres are repetitive DNA sequences that cap the ends of eukaryotic chromosomes, whose nucleotide sequence (T2AG3)n is highly conserved across vertebrate species (Meyne et al. 1989). During each cell cycle telomeric repeats are lost because DNA polymerase is unable to completely replicate the 3’ end of linear DNA (Watson 1972). Thus, telomeres progressively shorten with each cell division; past research has demonstrated age-related telomere attrition in a variety of laboratory and wild species and has correlated telomere length with individual age (e.g. Hausmann et al. 2003, Hemann and Greider 2000). Using real-time quantitative polymerase chain reaction (Q-PCR; Cawthon 2002), we have demonstrated the potential for quantifying telomere length for black bears of known-age in Colorado (Alldredge 2010). Understanding diet composition and foraging ecology of bears is also useful to managers, especially in urban areas as bears continually interact with humans and human derived food sources. The dynamics of this interaction and the extent to which bears utilize human food sources is largely unknown. The use of stable isotope analysis is one approach to understanding the amount and timing of utilization of various food sources within a bear’s diet. Examining different tissue types from bears can explain patterns of use for various food sources and will provide managers a better understanding of this problem at a population level. We have initiated a graduate study with the University of Wisconsin and Wisconsin Department of Natural Resources to develop methods of identifying population age structure using telomeres and examining diet composition and foraging ecology using stable isotopes for bears. See attached prospectus for a complete project overview and objectives (Appendix I). 241 �SECTION C: FRONT-RANGE COUGARS BY M. ALLDREDGE INTRODUCTION We have continued the cougar/human interaction study on the Front-Range of Colorado. Given that cougars currently coexist with humans within urban/exurban areas along Colorado’s Front-Range, varying levels of cougar-human interaction are inevitable. The CPW is charged with the management of cougars, with management options ranging from minimal cougar population management, to dealing only with direct cougar-human incidents, to attempted extermination of cougars along the human/cougar spatial interface. Neither inaction nor extermination represents practical options nor would the majority of the human population agree with these strategies. In the 2005 survey of public opinions and perceptions of cougar issues, 96% of the respondents agreed that it was important to know cougars exist in Colorado, and 93% thought it was important that they exist for future generations (CPW, unpublished data). There is a growing voice from the public that CPW do more to mitigate potential conflicts, and the leadership of CPW has requested that research efforts be conducted to help minimize future human/cougar conflicts. In order to meet these goals CPW believes it is necessary to directly test management prescriptions in terms of desired cougar population and individual levels of response. Long-term study objectives for the Front-Range Cougar Research project involve directly testing management responses of cougars at various levels of human interaction, as well as collecting basic information about demographics, movement, habitat use, and prey selection. The Cougar Management Guidelines Working Group (CMGWG) (2005) recommended that part of determining the level of interaction or risk between cougars and humans is to evaluate cougar behavior on a spectrum from natural, to habituated, to overly familiar, to nuisance, to dangerous. The CMGWG (2005) clearly stated that there is no scientific evidence to indicate that cougar habituation to humans affects the risk of attack. As a continuation from the pilot study efforts, we have continued to assess the effectiveness of aversive conditioning as a method to alter interaction rates between cougars and humans. We also continue to monitor relocated cougars to determine the effectiveness of relocation as a management tool. The use of GPS collars obtaining up to 8 locations per day also allows for a detailed examination of demographic rates. We are monitoring cougars that utilize natural habitats and cougars that use a mixture of natural and urban habitats. This allows for an assessment of demographic rates, movement patterns, and habitat use among cougars utilizing these two habitat configurations. We have also begun monitoring cubs (approximately 6 months of age or older), primarily to determine survival but potentially to understand movement patterns and dispersal. The use of GPS collars also allows us to study predator-prey relationships and diet composition. GPS locations are divided into selection sets based on the likelihood of the set of locations (clusters) representing a kill site. A random sample of these clusters is investigated to determine what a cougar was doing at the site, and whether or not it represents a kill site. Kill sites are thoroughly investigated to determine as much information as possible about what was killed at the site. STUDY AREA The original pilot study was conducted in Boulder and Jefferson counties, in an area near Interstate 70 north to approximately Lyons, Colorado, which was also a likely area for addressing longterm research objectives (see Figure 1). The study area for the long term study includes this original area but was expanded south to highway 285. Research efforts in the additional southern portion are generally 242 �limited to capturing cougars that are in the urban setting and/or have interacted directly with humans. The study area is comprised of many land ownerships, including private, Boulder city, Boulder County, Jefferson County, and state and federally owned lands. Therefore, we have been directly involved with Boulder city and Boulder and Jefferson county governments to obtain agreements from these entities on conduct of research and protocols for dealing with potential human/cougar interactions prior to conducting any research efforts. We have also acquired permission to access numerous private properties to investigate cougar clusters and to trap cougars. METHODS Baiting, using deer and elk carcasses, has been conducted throughout the year, with a focus on areas that do not allow the use of hounds. Bait sites are monitored using digital trail cameras to determine bait site activity. Cage traps were generally used for capture when cougars removed the bait and cached it. Beginning in November, 2010 and continuing through January, 2011, hounds were also used several times per week to capture cougars. Snares were used in situations where hounds could not be used and cougars would not enter cage traps. Captured cougars were anesthetized, monitored for vital signs, aged, measured, and ear-tagged. All independent cougars (> 18 months old) were fitted with GPS collars. All cubs greater than 15 kg (approximately 6 months or older) were ear-tagged with 22 g ear-tag transmitters or 22g ear-tag ptt Argos transmitters. When cougars interact with humans and elicit a response from CPW District Wildlife Managers (DWMs) they are potential candidates for aversive conditioning. However, only a subset of these are actually conditioned and the remaining animals are not treated in order to have a control group. At this time, we consider aversive conditioning treatments on cougars to potentially be: multiple captures and handling of cougars, single or multiple treatments using beanbags fired from a shotgun, single or multiple chases using hounds, and potential combinations of capture, hound chases, and beanbags. Initially, we wanted to assess situations and methods that are already being implemented by wildlife managers. Most incidents prompting response from a DWM occur in neighborhoods, where relocating the cougar is necessary prior to any application of an aversive conditioning treatment. For these situations, all treatments require the relocation of the offending individual to an adjacent open-space property or similar area. Following relocation we either chase the cougar off using rubber bullets or beanbag rounds, pepper spray, or hounds. For first time offenders we initially try rubber bullets or beanbag rounds. Second time offenders may be chased with hounds. If rubber bullets or beanbag rounds are not affecting cougar behavior, we consider using pepper spray on first time offenders. In other situations a cougar can be directly conditioned or chased from the area without relocation. We mimic the above approach as much as possible, and use rubber bullets or beanbag rounds on first time offenders. If possible we chase individuals with hounds on their second offense, although this is not always practical. Pepper spray is not practical either in many situations. As a second level treatment where direct hound chases are not practical, we attempt to capture, relocate, and aversive condition the individual. Cougars are only relocated for management purposes, generally in conjunction with human conflict or livestock depredation. Research cougars that have been collared for other purposes of the study may also become part of the relocation group if their levels of human interaction warrant such a management action. Because only a few cougars are relocated each year, we collar and monitor all cougars that are relocated in the northeast region. Cougars are ear-tagged and fitted with a telemetry collar (VHF, or GPS collars may be used depending on the situation). 243 �Release area is critical to the success of any relocation, however, suitable relocation areas may be difficult to find. Such an area must be far enough from the problem area, have suitable prey, and be remote enough so that the individual will not be presented with problem opportunities at or near the release site. Understanding the minimum release distance that has a reasonable chance for relocation success is useful for both logistical reasons and to increase the number of potential release sites. We evaluated cougar diet composition by using GPS location data to identify likely kill sites. Characteristics of clusters of GPS locations representing cougar-killed ungulate sites (Anderson and Lindzey 2003, Logan 2005) were used to develop a standard algorithm to group GPS points together, to provide a sound sampling frame from which statistical inference could be made about clusters that are not physically investigated. GPS collars collected locations 7 to 8 times/day to reflect time periods when cougars are both active and inactive. The clustering routine was designed to identify clusters in five unique selection sets (S1, S2,…, S5) in order to identify clusters containing two or more points, those that contained missing GPS locations, and those that were represented by single points. S1 clusters consist of multiple GPS locations with a 4 day window and within 200 m, while other sets are single points close together in time within varying distance bands. The clustering algorithm was written in Visual Basic and was designed to run within ARCGIS (Alldredge and Schuette, CDOW unpubl. data 2006). The widths of the spatial and temporal sampling windows were user specified, in order to meet multiple applications and research needs. This also enabled adjustment of the sampling frames to improve cluster specifications as needed. We used the following protocol to investigate cougar GPS clusters in the field. For S1 clusters, we investigated each cougar GPS location in the cluster by spiraling out a minimum of 20 m from the GPS waypoint while using the GPS unit as a guide, and visually inspecting overlapping view fields in the area for prey remains. Normally, this was sufficient to detect prey remains and other cougar sign (e.g., tracks, beds, toilets) associated with cougar. If prey remains were not detected within 20 m radius of the cluster waypoints, then we expanded our searches to a minimum of 50 m radius around each waypoint. For S2 through S5 clusters, we went to each cougar GPS location and spiraled out 50 m around each waypoint, while using the GPS unit as a guide. Depending on the number of locations, topography, and vegetation type and density, we spent a minimum of 1 hour and up to 3 hours per cluster to judge whether the cluster was a kill site. RESULTS AND DISCUSSION Collared cougars from the previous year (N=10) were captured and re-collared to replace exhausted batteries throughout the year. An additional 17 independent age cougars were also captured and collared during the year (Table 1). Currently there are 28 independent age cougars in the study with functioning GPS collars. Additionally, 9 cubs between 6 and 10 months old were captured and marked with ear-tags and either ptt or VHF ear-tag transmitters. Home ranges for collared cougars have been determined using minimum convex polygons (MCP) to depict the general pattern of use and potential overlap, but likely over-represent the actual area used by an individual. Home ranges exhibit similar patterns to previous years (Figures 2 and 3), being fairly linear in a north-south direction. Adult male home ranges (Figure 4) are much larger than adult female home ranges (Figure 5). Subadult male home ranges are smaller than adult male home ranges, but are also characterized by large movements and significant overlap with adults. Female home ranges are smaller with sizes between 80 and 120 km2. Female home ranges also have significant overlap, especially among related individuals. We have also seen significant long-range movements and dispersals (Figure 6). Long-range movements are significant movements outside of a cougar’s typical home range with the 244 �individual returning to the original area. Dispersals are similar movements but the individual does not return to its original area. There were a total of 6 mortalities for adult collared cougars during the 2010-11 year (Table 1). Causes of death included vehicle collision, unknown sources, hunting, and management or landowner euthanasia. Cougar-human interaction was comparable to the previous year, which appears to be less interaction than in the first years of the study. This gives us little opportunity to test aversive conditioning techniques. Given the minimal response to aversive conditioning, we are altering our methods of examining it as a management tool. We will now have managers aversively condition any cougar that they encounter interacting with humans and warrants such action. We will then compare the cougar’s responses to this aversive conditioning to events where the cougar was in the same situation but was undetected by humans and therefore not aversively conditioned. Relocation of cougars is also a management technique that we have evaluated in the past and has shown mixed results relative to age, sex and relocation distance. The NE region has expressed renewed interest in this and we will begin pilot work to investigate this in more detail. We will evaluate relocation distance relative to Directive W2 and the distance recommendations made for management as well as some more long-distance relocations. As this proceeds we will develop a more detailed study to thoroughly investigate cougar relocation parameters. From Aug 1, 2008 through September 1, 2011 we have visited ~2800 clusters (S1-S5 types). However, only 1563 of these clusters were considered to be random samples, and thus preliminary inferences have only been drawn from this subset. For this annual report, we focused on summarizing only the field investigations of 29 cougars who had available data for GPS clusters created from November 1, 2010 through September 1, 2011. During this 10 month time period a total of 1032 clusters were visited, with 463 designated as random S1 samples. Of the 463 randomly chosen S1 clusters, pooled over cougars, 44% were determined by field investigations to represent feeding events. This percentage was similar to the mean of 46.4% calculated for the previous two years, and within the range of variability (Table 3). For prey composition, we calculated the frequency of occurrence (percentage) of food items, averaged over the sample of collared cougars. To assess variaion, we calculate 95% confidence intervals assuming a normal distribution. Of the clusters determined to be feeding activities, mule deer were the primary prey item, being represented in 66.5% (±7.7%) of the clusters (Figure 7). Elk were represented in 13.5% (±6.6%) of the feeding event clusters (Figure 7). Non-cervid prey items, which included approximately 15 other species, were represented in 19.9% (±4.6%) (Figure 7). Non-cervid species most frequently observed at these feeding events included raccoon, birds, housecat, and domestic dogs. Species composition estimates calculated during this time period were similar to preliminary estimates calculated in the Aug 1, 2008 – July 31, 2010 time period (Alldredge and Blecha 2010) (Table 3). Kevin Blecha started his Masters of Science degree program at CSU this year, which will incorporate current efforts and data associated with these kill site investigations. Kevin will examine many aspects of cougar predator-prey dynamics in relation to habitat type and human density including prey selection, opportunistic take of livestock, diet composition, and predation rates. For a detailed description of his study see the attached study plan (Appendix II). We have also initiated two additional graduate projects at CSU to focus on other aspects of the Front-range Cougar Study. First we have begun a Ph.D. project with Mevin Hooten at CSU through the 245 �statistics department to develop movement models and examine cougar GPS data for various movement patterns relative to roads, human density/activity, and other landscape/environmental features (Appendix III). The other project that we have begun is a M.S. project with Bill Kendall at CSU through the Fish, Wildlife, and Conservation Biology Department to examine techniques to develop non-invasive population estimation methodology for cougars (Appendix IV). SUMMARY Genetic analysis for cougar feces revealed that DNA is still present in samples after feces have been in controlled temperature environments for up to 6 months. Genotyping error rates still need to be assessed. However, the presence of DNA in these samples suggests that field detection of cougar scats may be a viable non-invasive population sampling technique. We have added known-age samples collected from natural environments from known cougars marked in the front-range cougar project. The use of telomeres as a method to determine the age structure of bear and cougar populations is promising and will be investigated further in the coming year. Further refinement of the age-to-length relationship for both species is warranted. In addition to this, length relationships relative to genetic relatedness and individual stressors will give further insight into interpreting results from future data. The use of stable isotopes from various bear tissue types will also help elucidate the use of human foods by bears. In addition to re-collaring previously collared cougars, an additional 17 independent age cougars were collared during the year. Mortality remained high over the year. Home-range patterns remained consistent to previous years. The effectiveness of aversive conditioning is still showing mixed results, which is likely a factor of the opportunistic nature of cougars using urban environments and a lack of habituation to them. Relocation of cougars as a management tool has had limited assessment, but given some success, still warrants further investigation. Mule deer are the predominant prey in cougar diets, although males also utilize elk regularly. LITERATURE CITED Alldredge, M.W. 2007. Cougar demographics and human interactions along the urban-exurban front range of Colorado. Wildlife Research Report July: 153-202. Colorado Division of Wildlife, Fort Collins, USA. Anderson, C. R., F. G. Lindzey, and D. B. McDonald. 2004. Genetic structure of cougar populations across the Wyoming Basin: metapopulation or megapopulation. Journal of Mammalogy 85:12071214. Boutin-Ganache, I., M. Raposo, M. Raymond, and C. F. Deschepper. 2001. M13-tailed primers improve the readability and usability of microsatellite analyses performed with two different allele-sizing methods. Biotechniques, 31:25-28. Cawthon, R. M. 2002. Telomere measurement by quantitative PCR. Nucleic Acids Research 30:e47. Cougar Management Guidelines Working Group. 2005. Cougar Management Guidelines, 1sted. WildFutures, Bainbridge Island, Washington, USA. Ernest, H. B., M. C. T. Penedo, B. P. May, M. Syvanen, and W. M. Boyce. 2000. Molecular tracking of mountain lions in the Yosemite Valey region in California: genetic analysis using microsatellites and faecal DNA. Molecular Ecology 9:433-441. Harrison, R. L., P. B. S. Clarke, and C. M. Clarke. 2004. Indexing swift fox populations in New Mexico using scats. American Midland Naturalist 151:42-49. Haussmann, M.F., D.W. Winkler, K.M. O’Reilly, C.E. Huntington, I.C.T. Nisbet, and C.M. Vleck. 2003. Telomeres shorten more slowly in long-lived birds and mammals than in short-lived ones. Proceedings of the Royal Society of London Series B 270:1387-1392. 246 �Hemann, M. T., and C. W. Greider. 2000. Wild-derived inbred mouse strains have short telomeres. Nuclei Acids Research 28: 4474-4478. Hoss, M., M. Kohn, S. Paabo, F. Knauer, and W. Schroder. 1992. Excrement analysis by PCR. Nature 359:199. Logan, K.A. 2006. Cougar population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report July:95-122. Colorado Division of Wildlife, Fort Collins, USA. Menotti-Raymond, M. and S. J. O’Brien. 1995. Evolutionary conservation of ten microsatellite loci in four species of Felidae. Journal of Heredity 86:319-322. Menotti-Raymond, M., V. A. David, L. A. Lyons, A. A. Shcaffer, J. F. Tomlin, M. K. Hutton, and S. J. O’Brien. 1999. A genetic linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57:9-23. Meyne, J, R. L. Ratliff, and R. K. Moyzis. 1989. Conservation of the human telomere sequence (TTAGGG)n among vertebrates. Proceedings of the National Academy of Sciences 86: 7049-7053. Nakagawa, S., N.J. Gemmell, and T. Burke. 2004. Measuring vertebrate telomeres: applications and limitations. Molecular Ecology 13:2523-2533. Sinclair, E. A., E. L. Swenson, M. L. Wolfe, D. C. Choate, B. Bates, and K. A. Crandall. 2001. Gene flow estimates in Utah’s cougars imply management beyond Utah. Animal Conservation 4:257-264. Smith, D. A., K. Ralls, B. L. Cypher, and J. E. Maldonado. 2005. Assessment of scat-detection dog surveys to determine kit fox distribution. Wildlife Society Bulletin 33:897-904. Taberlet, P., and J. Bouvet. 1992. Bear conservation genetics. Nature 358:197. Watson, J.D. 1972. Origin of concatameric T4 DNA. Nature-New Biology 239:197-201. Prepared by Mathew W. Alldredge, Wildlife Researcher 247 �Table 1: Capture history, aversive conditioning treatments and current status of all independent age cougars captured as part of the Front-range cougar study. Cougar ID AM02 Sex Age Date Location Occurrence Capture Release Loc M Lacey Prop. White Ranch Coal Creek White Ranch Eldorado Springs Magnolia/Flagstaff South Boulder Baiting Capture effort Intraspecific mortality Baiting Livestock depredation Replace Collar Seen in town On-site On-site M 6/14/07 1/10/08 2/9/08 7/14/07 10/17/07 4/29/08 5/5/08 Cage Hounds AM04 1 1.5 1.5 7 7 8 8 Conditionin g NA NA On-site White Ranch On-site Lindsey NA Beanbag NA Beanbag 8 9 5 6 7 7 4 2 4.5 2 4 5 1.5 8/4/08 2/24/09 11/21/07 12/30/08 2/2/10 2/15/10 11/29/07 12/17/07 12/15/10 12/19/07 12/4/09 4/4/10 12/26/07 4/19/08 12/26/07 6/18/09 North Boulder Boulder Canyon Heil Valley Ranch Heil Valley Ranch Reynolds Ranch White Ranch Flagstaff Table Mesa White Ranch White Ranch White Ranch Golden Heil Valley Ranch Highway 7 Heil Valley Ranch West Horsetooth Centennial Cone Beanbag Hounds Hounds Hounds On-site On-site On-site NA NA NA Cage Cage Hounds Hounds Hounds On-site On-site On-site On-site On-site NA NA NA NA NA Hounds On-site NA Hounds Cage On-site On-site NA NA 12/28/07 12/27/08 1/15/08 2/13/08 Heil Valley Ranch Hwy 34 (mile 70) Apex Open Space I-70 Killed deer in town Punctured intestine Capture effort Replace Collar Replace Collar Hunter Deer kill Deer kill Baiting Capture effort Replace collar Roadkill Capture effort Roadkill Capture effort Deer kill-remove collar Capture effort Roadkill Deer Kill Roadkill Cage Cage Hounds Freedart Cage Hounds On-site NA Cage On-site NA AM06 M AF03 AF01 F F AM05 M AM07 M AF08 F 1.5 3 AM09 M AF10 F 1.5 2.5 7 248 Status Alive Alive Dead Alive Alive Alive Alive Alive Dead Alive Alive Alive Dead Alive Alive Alive Alive Alive Dead Alive Dead Alive Alive Alive Dead Alive Dead �AF19 F 8+ 8+ 8+ AF11 F 1.5 AM20 M 4 AF15 F 6 7 AF17 F 8-9 9+ AF12 F 2 AM13 M 2 AM14 M 3 2 3 AF34 F 1.5 3/4/08 3/18/09 4/13/09 1/20/09 11/5/10 Capture effort Deer Kill Deer Kill Deer Kill Roadkill 3/18/08 4/2/09 3/25/10 2/4/11 3/29/08 5/20/08 5/8/08 Heil Valley Ranch North Boulder Left Hand Canyon Dowe Flats Foothills Hwy, N. Boulder South Table Mesa US-40/Empire White Ranch West of White Ranch Coffin Top Hall Ranch Coffin Tip Hall Ranch Sugarloaf Four-mile Canyon N. Boulder 5/29/08 2/13/09 5/8/08 12/17/08 12/17/09 5/15/08 N. Boulder N. Boulder Sugarloaf Heil Valley Ranch Heil Valley Ranch South Boulder Livestock depredation Deer Kill Livestock depredation Replace Collar Replace Collar Seen under deck 5/20/08 South Boulder 4/14/09 2/16/10 6/21/11 12/5/08 3/18/09 Rollins Pass Left Hand Canyon Allens Park Heil Valley Ranch N. Boulder 3/5/08 8/20/08 3/6/08 5/18/08 Hounds Cage Cage Cage On-site Heil Valley Ranch Heil Valley Ranch On-site NA Beanbag NA NA Alive Alive Alive Alive Dead Deer Kill Cage Roadkill Capture effort Hounds Livestock Depredation Shot On-site NA On-site NA Alive Dead Alive Dead Capture effort Replace Collar Replace Collar Deer Kill Pet depredation Unknown mortality Deer Kill Hounds Hounds Hounds Snare Cage On-site On-site On-site On-site Within 1 mile NA NA NA NA Beanbag Cage US Forest Boulder Canyon Near Ward None On-site On-site On-site Lindsey Beanbag Alive Alive Alive Alive Alive Dead Alive Beanbag Euthanized Beanbag NA NA None Alive Dead Alive Alive Alive Alive West of Rollinsville Beanbag Alive On-site On-site On-site On-site Heil Valley Ranch NA NA NA NA Beanbag Alive Alive Alive Alive Alive Cage Snare Cage Hounds Hounds Freedart Deer kill Freedart Replace Collar Hounds Replace Collar Hounds Elk kill/Replace Collar Cage Capture effort Hounds Deer kill Cage 249 �AM18 M 2.5 3.5 1.5 AF16 F 3 AF45 F 5 AF40 F AF24 F 1.5 2.5 10+ AM31 M 1.5 AF37 F 2.5 1.5 5/31/09 12/31/08 3/29-09 2/16/10 12/31/08 AM21* M 1.5 8/11/09 8/29/09 AF32 F 2 1.5 3.5 3/???/10 Loveland?? 9/28/09 Indian Hills 11/28/10 Golden Livestock depredation Livestock depredation In neighborhood 3.5 12/1/10 9/23/11 11/13/09 3/5/10 11/24/09 In neighborhood Found dead Elk kill Livestock depredation Deer kill AM46 M 2 AF50 F 3 1/4/10 12/31/11 12/24/08 3/14/09 12/29/08 3/20/09 1/2/09 11/24/10 Heil Valley Ranch Hall Ranch Evergreen Evergreen Evergreen Evergreen Gold Hill N.Boulder 1/27/09 2/22/10 2/12/09 2/25/09 4/4/09 White Ranch White Ranch North Boulder Hwy 7 North Boulder Replace Collar Replace Collar Deer kill Livestock depredation Deer Kill Livestock depredation Deer kill Euthanized/Lisa Wolfe Capture effort Replace Collar Deer Kill Replace Collar Raccoon Kill North Boulder Evergreen Conifer Douglas, WY Evergreen Encounter Chicken coop Livestock depredation Hunter Chicken coop I-70 N. Boulder Roadkill Encounter Golden Green Mtn. Res. Evergreen Genesee West of Boulder 250 Hounds Hounds Cage Cage Snare Cage Cage On-site On-site Mt. Evans SWA None Flying J Open Space Mt. Evans SWA On-site NA NA None Euthanized None Beanbag NA NA Alive Alive Alive Dead Alive Alive Alive Dead Hounds Snare Cage Hounds Freedart Shot Hounds Cage On-site On-site Hall Ranch On-site Heil Valley Ranch NA NA None NA None Alive Alive Alive Alive Alive On-site Mt. Evans SWA None None Freedart On-site None Dead Alive Alive Dead Alive Freedart Ward None Dead Alive Cage Freedart Cage Within 1 mile White Ranch None None Dead Alive Alive Radium None Alive Cage Shot Cage On-site None On-site NA Alive Dead Alive �AM44 AM606 M 6 M 7-8 2 AF54 F 4 AF52 F AM51 AF56 AF55 M F F 4 5-6 1.5 1.5 4 AM53 M 4 AM60 AF58 M F 2 1.5 AF62 F AF59 F 5 6 5 AM63 M 5 1 AF57 AF61 F F AF64 AM67 F M 12/15/09 3/18/10 3/20/11 1/6/10 White Ranch White Ranch White Ranch Boulder Capture effort Replace collar Elk kill Seen in town 9/23/11 1/14/10 5/16/11 Laporte White Ranch White Ranch 1/28/10 3/24/11 1/28/10 2/22/10 2/23/10 3/13/10 3/13/10 3/3/11 3/29/10 4/4/10 6/3/10 4/13/10 4/13/11 4/22/10 Hall Ranch Hall Ranch Hall Ranch Conifer Conifer Conifer Genesee Medved property Walker Ranch Table Mesa Shot killing goat Capture effort Deer kill/Replace collar Capture effort Deer Kill Capture effort Livestock depredation Livestock depredation Pet Depredation Elk Kill Shot/hunter Baiting Baiting Roadkill Elk Kill Baiting Deer Kill Walker Ranch Walker Ranch Blue Jay/Jamestown N. Boulder Paradise Park 3 4-5 1/6/11 9/22/10 9/30/10 11/3/10 Lacy Property 11/18/10 Flagstaff Deer Kill Deer Kill Road Kill Baiting Deer Kill 4-5 1.5 1.2 3/2/11 Coal Creek Canyon 1/20/11 Heil Valley Ranch 12/16/10 White Ranch Raccoon Kill Baiting Baiting 251 Hounds Hounds Snare Freedart On-site On-site On-site MacGregor Ranch NA NA NA None Alive Alive Alive Alive Dead Alive Alive Hounds Cage On-site On-site NA NA Hounds Cage Hounds Cage Cage Cage Cage On-site On-site On-site Mt. Evans SWA Mt. Evans SWA Euthanized On-site NA NA NA Beanbag Beanbag Cage Cage On-site On-site NA NA Cage Cage Cage On-site On-site On-site NA NA NA Cage Cage On-site White Ranch NA None Snare Freedart Cage Cage Cage On-site On-site NA NA Alive Alive Dead Alive Alive Walker Ranch On-site On-site None NA NA Alive Alive Alive NA Alive Alive Alive Alive Alive Dead Alive Dead Alive Alive Dead Alive Alive Alive �AF69 F 5 1.5 12/1/10 N. Boulder Deer Kill 2 4/6/11 N.Boulder/Town Deer Kill 1/23/11` 3/2/11 1/27/11 2/6/11 3/6/11 2/23/11 3/6/11 3/9/11 3/18/11 5/12/11 3/18/11 3/18/11 Gold Hill Boulder Heights Heil Valley Ranch Heil Valley Ranch Sunshine Canyon White Ranch Heil Valley Ranch Morrison Mountain W. Evergreen Soda Creel—I-70 Mt. Evans Mt. Evans Deer Kill Dog Kill Baiting Baiting Baiting Baiting Baiting Baiting Deer Kill Road kill Dumpsite Dumpsite 4/9/11 Shield Park HOA AM70 M 3 AM71 AM72 AF73 AM74 AM76 AF77 AM78 M M F M M F M 2 4 4 4 2-3 5 2 AF79 AM80 F M AM84 M 4 1.7 5 2 SW023 F 1 SW026 M 1 SW107 M 1 4/9/09 11/14/09 Lost Valley Ranch 10/20/09 8/20?/11 5/7/10 3/22/11 Freedart Freedart Cage Cage Cage Snare Cage Cage Cage Cage Cage On-site NA Alive Reynolds Ranch None Alive On-site Reynolds Ranch On-site On-site On-site On-site On-site On-site On-site NA None NA NA NA NA NA NA NA Cage Cage On-site On-site NA NA Alive Alive Alive Alive Alive Alive Alive Alive Alive dead Alive Alive Sheep depredation Cage Deer Creek Canyon None Alive Rehab Found dead Rehab Shot/hunter Rehab Shot/hunter Release Pike forest None Release Hermit Park New Mexico Radium NA Alive Dead Alive Dead Unkn Dead 252 Release NA �Table 2: Capture history, maternal relationship, aversive treatment and current status of all cubs capture as part of the Front-range cougar study. Cougar ID AF35 Sex F Age Mothe r 3 AF16 AM36 M 3 AF16 AM30 M 8 AF01 AM38 M 8 AF01 AM29 M 6 Euth. 12 Date Location Occurrence Capture Release Loc 12/29/08 12/31/08 12/29/08 1/8/09 1/30/09 Evergreen Evergreen Evergreen Evergreen S. Boulder Deer Kill Roadkill Deer Kill Starvation Deer Kill Cage Flying J Open Space Cage Flying J Open Space Cage On-site 1/30/09 3/27/09 S. Boulder S. Boulder Deer Kill Encounter On-site Lindsey Beanbag 3/30/09 S. Boulder Pet Depredation Centennial Cone None Alive 4/9/09 Morrison Encounter None Euthanized Dead 2/11/09 N. Boulder Deer Kill Hall Ranch None Alive 6/15/09 N. Boulder Encounter Cage Freedart Freedart Freedart Freedart Freedart Shot Alive Dead Alive Dead Alive dead Alive Alive Masonville Beanbag Alive Cage On-site NA Cage Freedart Freedart Shot Freedart On-site Perforated intestine None On-site None Alive White Ranch None Dead Alive 10/23/09 Big Thompson Goat Depredation Baiting AM21* collared AF25 M 12 Unkn 3/25/09 Table Mesa F 12 Unkn 5/22/09 9/13/09 Indian Hills Deer Kill Raccoon AM41 M 12 Unkn 5/22/09 Indian Hills Deer Kill AM65 M 4-5 AF32 Indian Hills 11/28/10 Golden Encounter In Neighborhood 253 Conditionin g Status Dead Alive dead Alive Dead �AM66 M 4-5 AF32 AM67 AF68 AM70 M F M 15 AF01 10 AF50 3yrs AF59 AM80 AM83 AM85 AF86 M M M F 20 9 9 9 AF79 AF52 AF62 AF62 11/28/10 Golden In Neighborhood 12/1/10 12/16/10 2/9/11 1/23/11 3/2/11 3/18/11 3/24/11 4/13/11 4/13/11 Recapture Baiting Deer Kill Deer Kill Dog Kill Dumpsite Deer Kill Baiting Baiting White Ranch White Ranch Flagstaff Gold Hill Boulder Heights Mt. Evans Hall Ranch Walker Ranch Walker Ranch 254 Freedart Hounds Cage Cage Cage Cage Cage Cage Cage Snare White Ranch None Alive Radium On-site On-site On-site Reynolds Ranch On-site On-site On-site On-site None NA NA NA None NA NA NA NA Alive Alive Alive Alive Alive Alive Alive Alive Alive �Table 3: Comparison between previous two years and current year of the proportion of clusters representing feeding events and the proportion of feeding events represented by deer, non-cervids, and elk. Means and Simple 95% confidence intervals (assuming normal distribution) were calculated by using the collared subject as the sample. 255 �Figure 1: Study area for the main Front-range cougar study where most capture effort and field work is conducted. 256 �Figure 2: MCP home-ranges for male cougars that have previously been collared but are no longer in the study because of mortality or dispersal. 257 �Figure 3: MCP home-ranges for female cougars that have previously been collared but are no longer in the study because of mortality or dispersal. 258 �Figure 4: MCP home-ranges for male cougars that are currently in the study and being monitored. 259 �Figure 5: MCP home-ranges for male cougars that are currently in the study and being monitored. 260 �Figure 6: Dispersal/movement paths for cougars collared within the study area but traveled large distances outside of the study area. 261 �Figure 7: Mean proportion of Deer, Elk, and non-cervid prey remains found at feeding sites. Mean proportion drawn from the mean of 31 subject cougars (n=31). Error bars represent 95% Confidence Limits with an assumed normal distribution. 262 �APPENDIX I Black Bear Telomere and Stable Isotope Research Project Jon Pauli, University of Wisconsin Mat Alldredge, Colorado Parks and Wildlife Dave MacFarland, Wisconsin Department of Natural Resources Background Information: We are pursuing a telomere/stable isotope project in conjunction with the Wisconsin DNR and the University of Wisconsin. We have been working with Dr. Jonathan Pauli (University of Wisconsin) on this project for the last 2 years developing the original telomere age to length relationships for bears and cougars. Our goal is to examine the length to age relationship for telomeres and to investigate the use of stable isotopes to identify consumption of human food sources in the diet of bears. Cursory analyses have been conducted over the past two years for both bears and cougars. These analyses have demonstrated a significant age to length relationship in telomeres for both bears and cougars. In conjunction with John Broderick (Colorado Parks and Wildlife) we have decided to pursue this project in detail for bears because the potential benefits are greater for bears based on current bear projects across the state. If we successfully develop this relationship for bears then we would be able to apply this technique to all bear hair-snag surveys and not only have population size but also have an estimate of the age structure for these populations. The stable isotope analysis will also benefit the urban bear research project recently initiated in Durango and our understanding of bear conflicts by providing valuable information about diet components of bears that are in different areas of the study or state. This project is being conducted through the University of Wisconsin as this is where previous research was done and is one of the only labs in the country that has expertise in this area. Wisconsin DNR is also a collaborator on this project and is helping to fund the research. Costs for this project are reasonable and will involve the cost of analyzing samples from Colorado and support for a Ph.D. student. Telomeres to age black bears: Telomeres are repetitive [(T2AG3)n] and highly conserved DNA sequences that cap eukaryotic chromosomes (Meyne et al. 1989). During each cell cycle telomeric repeats are lost because DNA polymerase is unable to completely replicate the 3’ end of linear DNA (Watson 1972). Thus, telomeres progressively shorten with each cell division. Consequently, telomeres typically become shorter as individuals age (e.g. Hausmann et al. 2003, Hemann and Greider 2000). Recently, Pauli et al. (in press) used telomere lengths, quantified via real-time quantitative polymerase chain reaction (Q-PCR), to age American (Martes americana) and Pacific marten (M. caurina) collected throughout North America. They found that although telomere and age exhibited weak and non-linear relationship, accurate estimates of age class were obtainable when accounting for a few covariates (e.g., geographic location, sex). Indeed, the accuracy of age estimation via telomere length exceeded those obtained from counts of cementum annuli. Thus, quantification of telomere length could be a promising tool to age carnivores and estimate demographic structure for studies collecting hair samples non-invasively for DNA-based analyses (Pauli et al. in press). 0.7 y = 0.34 - 0.021x 0.6 0.5 ln (T/S) Under a previous collaborative effort with the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]), we quantified telomere length for black bears of known-age in Colorado and Wyoming with Q-PCR. We found that high amplification efficiencies and reliable standard curves enabled a robust estimate of relative telomere length, and that relative telomere length declined with increasing animal age (Fig 1). Samples analyzed were obtained from 0.4 0.3 0.2 0.1 0.0 0 263 2 4 6 8 10 Fig 1. Relationship between age and telomere length (T/S) for blood samples of black bears from Wyoming and Colorado, 2008. �blood, hair and muscle tissue of bears; since telomere length varies across tissue-types, preliminary regression analyses were limited to blood samples only. Although we found considerable variation in telomere lengths by age, an interesting and potentially useful relationship between animal age and relative telomere length was observed. Now that quantification of telomere length via Q-PCR is achievable for black bears, we propose to collect tissue samples from a proportion of the hunted bears in Colorado (~800 harvested annually) and Wisconsin (~5,000 harvested annually). From each individual, we will collect deep muscle, coagulated blood and pluck hair from each individual for the quantification of telomere length. We will compare telomere length estimates among the three tissue types and explore tissue-specific differences as well as validate telomere length obtained from externally plucked hair. We will then quantify the relationship between telomere length and age (obtained from counts of cementum annuli) for all individuals using a Bayesian Network approach that accounts for the covariates sex, location (or Game Management Unit), body condition, and structural size (via zygomatic width), all of which will be recorded at the time of sample collection. Upon developing models for aging from telomeres and relevant covariates, we will quantify the telomere length for the 400-500 bear samples already collected for monitoring by the CPW and estimate individual age for the quantification of demographic structure. Assessing the importance of human-derived foods for black bears: The use of stable isotopes, particularly those of nitrogen, carbon and hydrogen, has enabled biologists to quantify a myriad of cryptic ecological processes: trophic interactions and dietary overlap, organismal physiology and nutrient allocation, and animal movement and behavior (Kelly 1999). Stable isotopes analyses have been particularly important in quantifying the proportional contribution of food resources for free-ranging vertebrates (Hobson 1999). Because dietary analysis using stable isotope relies on the abundance of two elements δ13C and δ15N, it avoids pitfalls of traditional methods (e.g., analysis of scat or stomach contents) that fail to detect highly digestible materials, and provide only a snapshot of resource use. Thus, for an array of carnivores, including black bears, the quantification of stable isotope provides a powerful analytical tool to understand diet and resource use. There is growing interest on the importance of humanderived foods on free-ranging animal populations. Particularly for carnivores, managers are seeking to quantify the proportional importance of human-derived food items – agriculture (principally from corn), intentionally deployed baits, or unintentional waste – to better understand the consequent effects on nutritional condition, survival and reproductive success (Partridge et al. 2001). Especially among populations of bears, which can become strongly habituated to these resources (McCarthy and Seavoy 1994), quantifying individual reliance on such items and consequent effects on individual attributes and population dynamics is highly desired. Fig 2. Illustration of carbon and nitrogen isotopic signatures of potential black bear food resources. Human foods, either from cultivation or artificially sweeteners, are highly enriched relative to natural diet items. As such, we can quantify the reliance of bears on human-derived resources via isotopic-based analyses. Because of differences in photosynthetic pathways, corn, sugar cane and artificial sweeteners have distinctly different carbon signature (δ 13C) compared to native plants and heterotrophs that inhabit temperate North America (Fig. 2; Jahren et al. 2006). Consequently, the percent of diet obtained from human-derived foods with unique isotopic signatures can be calculated for black bears (e.g., Noyce 2007). Bears reliant on human-derived foods would exhibit enriched levels of 13C; via isotopic mixing models (Phillips et al. 2005), the percent of diet obtained from native plants, heterotrophs and human- 264 �derived food items will be calculated. Our approach to quantifying the importance of human-derived food for black bears inhabiting Wisconsin and Colorado will coincide with our efforts to quantify telomere lengths. Because the tissue types we are obtaining to quantify telomere lengths possess different metabolic turnover rates, those same tissues also provide different windows into food consumption via stable isotopes. For black bears, plasma represents diet items consumed during the previous 10 days and red blood cells reflect food consumed over the previous two months (Hildebrand et al. 1996). Collagen extracted from bone reflects the isotopic signature of foods consumed over an individual’s lifetime, whereas hair reflects items consumed during active phases of hair growth. Bear underfur reflects autumn diet (Jones et al. 2006), while guard hair can be cut into smaller segments to provide a finer temporal scale within the molt (Pauli et al. 2008). Ultimately, isotopic signatures and percent diet from humanderived foods will be related back to indices of body condition (e.g., Cattet et al. 2002) obtained from bear carcasses. Such an isotopic approach will quantify the importance of human-derived food, in the form of agricultural corn or sweetened foods used in baiting, for black bears. Anticipated Benefits: This project will provide new information on the applicability of a molecular marker, telomere length, to estimate the individual age of black bears. Ultimately, such an aging approach will allow estimation of demographic structure from non-invasively collected hair samples. Further, through the collection of ecologically-relevant covariates (e.g., sex, location, body size and nutritional condition), we will be able to better understand factors driving telomeric attrition in wild vertebrates. Through the use of stable isotopes, it will be the first to quantify the relative importance of human-derived food (agricultural corn, bear baits, and human foods in trash) among black bears across seasons and relate the consequence of these diet items on the nutritional condition of bears. Additionally, through fieldwork and contact with hunters and managers, this project will allow graduate students to interact with local residents on issues of wildlife ecology and management. Ultimately, results will be disseminated via scientific and popular articles, professional meetings, and lectures to the public. Management Benefits for CPW: 1. Ability to estimate age structure to coincide with population estimates from the non-invasive hair snag surveys currently being conducted. 2. Ability to examine regional (state-wide or multiple state) age structure of bear populations from harvested bears. 3. Ability to examine the use of human derived food sources in the diets of bears for ongoing bear research projects. 4. Ability to examine the use of human derived food sources in the diets of bears involved in human conflict across the state and across years as natural foods vary in quantity and quality. Literature Cited: Haussmann, M.F., D.W. Winkler, K.M. O’Reilly, C.E. Huntington, I.C.T. Nisbet, and C.M. Vleck. 2003. Telomeres shorten more slowly in long-lived birds and mammals than in short-lived ones. Proceedings of the Royal Society of London Series B 270:1387-1392. Hemann, M. T., and C. W. Greider. 2000. Wild-derived inbred mouse strains have short telomeres. Nuclei Acids Research 28: 4474-4478. Meyne, J, R. L. Ratliff, and R. K. Moyzis. 1989. Conservation of the human telomere sequence (TTAGGG)n among vertebrates. Proceedings of the National Academy of Sciences 86: 7049-7053. Watson, J.D. 1972. Origin of concatameric T4 DNA. Nature-New Biology 239:197-201. Pauli, J.N., J.P. Whiteman, B.G. Marcot, T.M. McClean and M. Ben-David. in press. A DNA-based approach to age martens (Martes americana and M. caurina). Journal of Mammalogy Pauli, J.N., M. Ben-David, S.W. Buskirk, W.P. Smith, and J.E. DePue. 2009. An isotopic technique to mark mid-sized vertebrates non-invasively. Journal of Zoology 278:141-148. 265 �Hildebrand, G.V., S.D. Farley, C.T. Robbins, T.A. Hanley, K. Titus, and C. Servheen. 1996. Use of stable isotopes to determine diets of living and extinct bears. Canadian Journal of Zoology 74:2080-2088. Partridge, S.T., D.L. Nolte, G.J. Ziegltrum, C.T. Robbins. 2001. Impacts of supplemental feeding on the nutritional ecology of black bears. Journal of Wildlife Management 65:191-199. Jahren, A.H., C. Saudek, E.H. Yeung, W.H.L. Kao, R. A. Kraft, and B. Caballero. 2006. An isotopic method for quantifying sweetners derived from corn and sugar cane. American Journal of Clinical Nutrition 84:1380-1384. McCarthy, T.M., and R.J. Seavoy. 1994. Reducing nonsport losses attributable to food conditioning: human and bear behavior modification in an urban environment. International Conference on Bear Research and Management 9:75-84. Jones, E.S., D.C. Heard, M.P. Gillingham. 2006. Temporal variation in stable carbon and nitrogen isotopes of grizzly bear guardhair and underfur. Wildlife Society Bulletin34:1320-1325. Cattet, M.R.L., N.A. Caulkett, M.E. Obbard, and G.B. Stenhouse. 2002. A body-condition index for ursids. Canadian Journal of Zoology 80:1156-1161. Noyce, K.V. 200. Use of stable isotopes of carbon, nitrogen, and oxygen in studies of diet and nutrition of Minnesota black bears. Summaries of Wildlife Research Findings, 2006, Minnesota Department of Natural Resources. Pp.140-146 Phillips, D.L., S.D. Newsome, J.W. Gregg. 2005. Combining sources in stable isotope mixing models: alternative methods. Oecologia 144:520-527. Kelly, J.F. 1999. Stable isotopes of carbon and nitrogen in the study of avian and mammalian trophic ecology. Canadian Journal of Zoology 78: 1-27. Hobson, K.A. 1999. Stable-carbon and nitrogen isotope ratios of songbird feathers grown in two terrestrial biomes: Implications for evaluating trophic relationships and breeding origins. Oecologia 101:799-805. 266 �APPENDIX II Puma foraging behavior in an urban to rural landscape Kevin Blecha (Study Plan for submission as 2010-2011 Annual CPW Mammals Research Report) Introcuction: The rocky mountain Front Range of Colorado has experienced drastic human population increases in the last two decades, and thus suburban and exurban landscapes are sprawling into areas occupied by cougar (Puma concolor). Some evidence suggests that cougar avoid areas of high human density. However, cougar use of landscapes developed by humans still occurs at some level with conflicts resulting between cougars and humans. This study examines cougar predation characteristics and prey selection in reference to landscape features such as prey availability, anthropogenic development, and hobby livestock. A current paradigm in cougar management revolves around the idea that cougar density, distribution, and habitat use is correlated with densities of primary prey. Front Range cougar use of exurban, suburban, and even urban landscapes still occurs, which sparks human/cougar interactions. Exurban and suburban landscapes of the Front Range are often free of human harvest pressures on deer, which possibly cause elevated levels of cougar’s primary prey (deer). It is in these areas that it is speculated that cougar are being drawn to because cougar are more likely to increase their encounter with potential prey. This idea is supported by other research indicating that landscape features used by a primary prey species may be the primary driver for selection of feeding locations of cougar (Pierce et al. 1999, Pierce et al. 2000, Atwood et al. 2007). However, the idea that increased cougar use of a landscape is a function of increasing prey availability is only grounded partially in theory, as other recent studies have found that cougar exhibit avoidance to/select against areas of high human activity (Mattson 2007, Burdett et al. 2010, Kertson 2011). Therefore, it is unclear which primary factor may drive landscape use by cougar in the Colorado Front Range. Many studies on other vertebrate species point out that an animal forages optimally, in which it may sacrifice hunting in areas with high prey availability for the security provided by areas further away from human disturbance. However, whether or not cougar forage optimally in reference to prey availability and human disturbance factors is untested. Testing whether the likelihood of cougar feeding events on the landscape changes in various combinations of low/high prey encounter probability and low/high human disturbance levels, may: 1) shed light on the degree of optimal foraging behavior in cougar, 2) whether or not cougar are feeding in exurban areas based on high availability of prey. Cougar have the ability to prey on all species of livestock, but with the highest losses in Colorado represented by commercial sheep ranching. In the Front Range region however, hobby livestock depredations represent a majority of the owner losses. Hobby livestock owners inhabiting the sprawling exurban and developing rural areas of the Front Range that live in vicinities adjacent to suitable cougar habitat are at the highest risk of experiencing a hobby livestock depredation (Torres et al. 1996, Michalski et al. 2006). When a cougar is observed or found on property containing livestock, that cougar may be wrongly accused of hunting livestock as prey. Protection of livestock, including hobby livestock, is enough justification for wildlife managers/livestock owners to destroy the cougar. It is unknown whether or not cougar, while hunting, select for areas with hobby livestock or whether cougar hunt on ranched landscapes selectively or opportunistically. Detailed information on whether or not certain classes (sex/age) of cougar are more likely to seek prey near hobby livestock is important for predicting which type of cougar may be more likely to commit a depredation offense. Knowing whether cougar, that have committed a livestock depredation in the past, are more likely to hunt near properties containing hobby livestock will shed light on whether or not individual cougar may behave as specialist toward livestock prey items. 267 �Understanding what biological and environmental factors influence cougar predation is important to the management of cougar and the subsequent prey species. It has been hypothesized that stimuli from human disturbances may increase energetic costs (Frid and Dill 2002), thus a decrease in fitness may occur through decreased mating opportunities (Schoener 1971, Pyke et al. 1977) or through lowered survival of offspring. If human activities increase an animal’s search time for acquiring food, through direct disturbances or alterations in landscape configuration, the energetic demands are increased, and thus changes in foraging characteristics may reflect the disturbance/alteration (Gill and Sutherland 2000, Blumstein et al. 2005). Kertson (2010) did find a shift in prey composition in residential areas toward higher proportions of smaller and/or domestic prey. In addition, cougars are known to show individual differences in predation characteristics based on sex, age, and reproductive status (Ackerman et al. 1986, Murphy 1998, Laundre 2005, Laundre 2008, Cooley et al. 2008, Knopff et al. 2010). To assess how different landscapes, seasons, and individual cougar differences influence prey consumption, I will examine characteristics of cougar dietary composition/overlap and feeding rates. Questions/Objectives: 1. Do cougar feed in landscapes with relatively higher prey occurrence? 2) Do cougar avoid landscapes with higher human density when feeding? 3) Do cougar forage optimally by balancing the acquisition of prey while minimizing risks posed by humans? 2. Do cougar use parcels containing hobby livestock opportunistically or select (or even avoid) for these areas when hunting? Can this selection/opportunism differ between certain cougar sex/age classes and seasons? Are cougar that have a history of committing a depredation on a hobby livestock item more likely to use parcels containing hobby livestock? Prior to killing a hobby livestock prey item, do cougar select for areas known to hold hobby livestock? 3. Does human development influence the composition of prey consumed by cougar? Can human development cause a decrease in cougar foraging rates on primary prey such as ungulates? Segment Objectives: 1. Examine whether cougar select prey resources more frequent than availability suggest (3rd order selection: Johnson 1980) in reference to: (main effect A) landscapes with higher probability of encountering prey, (main effect B) landscape with lower levels of human activity, or (interaction effect C) optimal landscapes with higher prey availability and lower human activity. 2. Assess if cougar are selecting, avoiding, or opportunistically using parcels of land containing hobby livestock when hunting, and assess if any difference in selection occurs between cougars of different: a. Sex/maternal class b. Age class c. Season d. Known livestock depredation history 3. Compare species composition (frequency of occurrence/overlap indices) of cougar diets in reference to: a. Various levels of human population density b. Cougar sex, age, maternal class c. Season d. Other landscape variables 4. Compare predation rates on mule-deer and secondary items in reference to: a. Various levels of human population density b. Cougar sex, age, maternal class c. Season d. Other landscape variables 268 �Methods: This study is an extension of a parent project: Cougar Demographics and Human Interactions Along the Urban-Exurban Front-range of Colorado (see above) project initiated by the Colorado Division of Wildlife ( now Colorado Parks and Wildlife [CPW]), which is charged with managing Colorado’s cougar population. Conflicts between cougar and humans have increased dramatically in the past two decades, thus the FRCP was initiated to address questions regarding cougar natural history, population estimation, response to aversive conditioning, response to relocation, livestock depredation opportunity, and predator/prey relationships. The 2862 km2 extent of the study area, shown in Figure 1, encompasses a majority of Boulder County, north Jefferson County, and portions of Larimer, Clear Creek and Gilpin Counties. This area is characterized by a patchwork of private and publicly owned land held by federal, state, and municipal governing agencies. However, if a subject leaves the study area, standard GPS tracking and field data will be collected on the subject until establishing what appears to be a maintained home range. All objectives listed below require using cougar fitted with GPS radio collars, and thus only subjects captured in the parent project are utilized in this project. The use of GPS radio collars allows us to study predator-prey relationships. The collars collect GPS locations 7 to 8 times/day, at 3 or 4 hour intervals. GPS locations are divided into selection sets based on the likelihood of the set of locations (clusters) representing a kill site. A random sample of these clusters is investigated to determine what a cougar was doing at the site, and whether or not it represents a feeding site. Feeding sites are thoroughly investigated to determine as much information as possible about what was eaten/killed at the site. All of the analysis below is dependent on identifying confirmed or likely kill events from characteristics of GPS location clusters representing cougar feeding sites (Anderson and Lindzey 2003). A standard algorithm was created to group GPS points together into clusters providing a sound sampling frame from which statistical inferences could be made about GPS clusters that are not physically investigated. The clustering routine was designed to identify clusters in five unique selection sets (S1, S2, S3, S4, and S5) in order to identify clusters containing two or more points, those that contained missing GPS locations, and those that were represented by single points. The clustering algorithm was written in Visual Basic and was designed to run within ArcGIS (Alldredge and Schuette, CPW unpubl. Data 2006). The widths of the spatial and temporal sampling windows were user specified, in order to meet multiple applications and research needs. This also enabled adjustment of the sampling frames to improve cluster specifications as needed. The following protocol to investigate cougar GPS clusters is used in the field. For S1 clusters, we investigate each cougar GPS location in the cluster by spiraling out a minimum of 20 m from the GPS waypoint while using the GPS unit as a guide, and visually inspecting overlapping field of view in the area for prey remains. Normally this is sufficient to detect prey remains and other cougar sign, (e.g., tracks, beds, latrines) associated with cougar. If prey remains are not detected within 20 m radius of the cluster waypoints, then we expand our search to a minimum of 50 m radius around each waypoint. For S2 through S5 clusters, we visit each cougar GPS location and spiral out to a maximum of 50 m around each waypoint, while using the GPS unit as a guide. Depending on the number of locations, topography, vegetation type and density, we spend a minimum of 1 hour and up to 3 hours per cluster to judge whether the cluster was a feeding site. 269 �Objective 1 (Examination of cougar selection of prey in reference to prey availability and human activity) Detailed spatial and temporal prey availability data is not attainable for the large spatial and temporal extent of the FRCP, as obtaining abundance estimates for even conspicuous animals is difficult in the exurban areas of the Front Range [i.e., deer (CDOW 2006)]. Therefore, I will use an array of > 111 camera trap units (Reconyx HyperFire, Holmen, Wisconsin) distributed throughout the study area to sample encounter rates of prey across the various landscape types. Estimated photographic rates will be interpreted as the probability of encountering a particular prey species, instead of a direct density or abundance metric. Royle and Nichols (2003) show that heterogeneity in the detection probability parameter of a typical occupancy modeling framework (MacKenzie et al. 2002) is usually most dependent on underlying localized abundance of a surveyed site, especially if all other variables influencing detectability are accounted for. Using camera traps to derive repeated presence-absence data are a novel approach at deriving detection probability estimates that are less influenced by variables other than the localized abundance of a targeted species at a site. Camera traps are less likely to be influenced by observers or sight-ability as the detection of a subject is automated (O’Brien 2010). Although encounter rates derived from camera traps, may be subject to heterogeneity across ambient temperatures, seasons, species, and body mass of a targeted animal (Rowcliff et al. 2011), changes in encounter rates between camera traps/sites reflect relative changes in abundance assuming that detection probabilities are constant among these camera traps/sites (O’Brien 2010). In addition, previous work has shown correlations between camera trapping rates and abundance measures in various ungulate studies (O’Brien et al. 2003, Rowcliffe et al. 2008, Rovero and Marshal 2009). Measures taken to limit inter-site heterogeneity in detection probability will include blocking study periods into shorter discrete seasons, in order to account for differences in ambient temperatures, movement behaviors, and animal congregation behaviors (e.g.: seasonal grouping of deer). Additionally, making cross-species comparisons will be limited to account for inter-species detection heterogeneity. Camera-trap photograph encounter rates (number of independent photographs per unit time), for each particular prey species of interest, will be measured on a localized scale (25x25 m grid resolution) (Figure 2). This high resolution scale was chosen as it fits the fine scale decisions that cougar may make regarding hunting and feeding locations, especially considering cougar are shown to select for edge habitats when killing deer (Laundre and Hernandez 2003). Sunquist & Sunquist (1989) suggest that most large stalking felid species must approach within 30 m of a prey item before attacking. Past work characterizing cougar hunting habits in relation to habitat edge, characterize “edge habitats” as a distance band 15-20 m from the interface of two habitat types (Altendorf et al. 2001, Holmes and Laundre 2006). This high resolution was also chosen based on the resolution of the readily available major land-cover data. A ground-truthed land-cover dataset from the Colorado Vegetation Classification BASINWIDE project (CDOW 2003) was chosen for representing major vegetation types. The temporal extent of this study (Approximately 1 year) will be divided into monthly study periods in order to account for any major changes in animal movement, congregation behavior, or weather (i.e. snow/temperature) (Rowcliffe et al. 2011). The spatial extent of this study consists of Boulder County, Gilpin County, northern Jefferson County, and Clear Creek Counties of the Front Range region of Colorado. The study area extent was chosen to reflect a majority of the home ranges inhabited by cougars fitted with GPS collars. To gather sighting data used to calculate encounter rates, camera traps will be placed on a stratified random sample of 25 m grid cell sites (n > 111). Sites will be defined by single 25x25 m cells, delineated with the boundaries of the 25 m grid cells used in the BASINWIDE project (CDOW 2003) (Figure 2). Because there is potential to model a variety of species potentially preyed upon by cougar, each with differing movement and habitat selection patterns, sites chosen for surveys will be randomly placed (Kays et al. 2010, O’Brien et al. 2010). This is particularly important in multi-species assessments, as placing cameras in habitats targeting certain species with low detection probabilities (as commonly 270 �done) may violate assumptions, thus causing biased results (Tobler et al. 2008). A stratified random design will be utilized in which seven major land-cover types, two non-urban housing density levels, and three levels characterizing the proximity to roofed structures are represented with an approximately equal number of samples (Table 1). Not all combinations of strata are present within the study area. Additionally, some strata levels overlap in describing particular sites (i.e. The “Low” level of the SUBSUBSTRATA, and the “Urban” level of the MAJOR strata) and thus some levels between strata were combined. Examining all 12 categorical descriptions used in the multi-level sampling scheme shows that each category will be represented by a sample size ranging from 6 – 48 sites (Table 2). Some of these categories may eventually be measured as continuous variables when included in final analysis, and thus these levels and strata are only used to guide the placement of cameras to ensure broad and even sampling across a range of possible habitat conditions. Placement of the camera unit within the 25 x 25 m site will be chosen by a randomly generated point location (Figure 2) and a randomly chosen azimuth (0-359º). In forested habitats, or habitats providing a stable structure for mounting a trail camera, the unit will be placed on the tree/structure closest to the randomly generated point. Some pruning of shrubbery/branches is permitted if maximum visibility is limited and if no more than 10% of the camera’s detection zone is obstructed. If maximum visibility range of the camera sensor is limited, and pruning is not an option, the camera’s direction may be adjusted to a new randomly chosen azimuth. If no alternative azimuth is available because of complete 360 º obstruction, then the camera may be moved to an alternative random location within the 25x25 m cell. If moving the camera to alternative random locations still does not allow placement of the camera, then a alternative randomly chosen 25 x 25 m site may be used. Trail cameras will be elevated 50 cm from the ground to standardize the angle and viewing range of the infrared sensor and/or camera lens. However, camera heights may be slightly modified to accommodate snow accumulations and growth of low lying vegetation. Cameras will be positioned so that the unit is parallel with the ground while the planar detection zone is perpendicular to the ground. Camera units will be set to record pictures 1/second, as long as the units trigger is being activated by a subject. Care must be taken to have cameras placed so that vegetation movements in the wind will not give false triggers, as false triggers will consume memory and battery life. A General Linearized Modeling technique will be used to model the encounter rates of each particular prey species across un-sampled sites of the study area, given a-priori selected landscape covariate data such as major land-cover (BASINWIDE vegetation data set), elevation, aspect, hydrology, NDVI, edge proximity, etc. A distribution map of predicted encounter rates for each of the prey species, for each month, will be used to infer spatial relative encounter rate estimates. Relative encounter rate estimates across species may not be readily compared using this technique unless efforts are made to assess the probability of detection among targeted species. Particular focus, sampling effort, and analysis time may be placed on the late winter period and late summer periods. The late winter period (i.e. March – May) is of special interest as this is a period of relative stability in ungulate behaviors, as well as the presumed lowest period of prey availability for cougar. The late summer period (August-Sep), which will initiate after the ungulate birthing pulse, will represent a period of relatively stable ungulate behavior and highest presumed prey availability. Significant covariates with high predictive capabilities will be used to interpolate encounter rates at other non-sampled 25 m cells across the study area of interest, for each monthly time period of interest, for each of the six most common prey species [elk (Cervus elaphus), muledeer, raccoon, housecat (Felis catus), red fox (Vulpes vulpes), coyote (Canis latrans)] of cougar on the front range. Study period lengths and encounter rate definitions (i.e.: change photographs/day to photographs/week) may be manipulated to simplify calculations and modeling. Ultimately, whichever statistical modeling technique is used, the metric shall be interpreted as the probability a cougar could encounter the prey item at that given cell on the landscape within the monthly time period of interest. 271 �Objective 2 (Cougar selection of hunting areas near hobby livestock) Formal knowledge on the distribution of hobby livestock of the Front Range does not exist. This will be countered by creating a thematic presence/absence map of all parcels of land containing hobby livestock items. Any parcel of land with the confirmed presence of hobby livestock items will be verified through roadside observations of all private land containing evidence of hobby livestock enclosures. Information regarding hobby livestock presence/absence in the individual parcels may be also gathered from: - Knowledge from CPW staff working in the study area. - Knowledge from collaborating agency staff in study area. - Communications with local residence and livestock owners. - Specific CPW wildlife/livestock conflict reports. - Kill-site investigators’ knowledge of vicinity of any visited cougar GPS location cluster. Road-side observations and personal landowner visitations may be conducted to verify any presence/absence data collected above. Larger pastures inhabited by commercial stock (cattle/sheep/horses) will be denoted separately, as the amount of area utilized by livestock at any one time may be relatively small compared to the overall aerial coverage of the pasture at hand. I will utilize a use vs. available design (Manley et al. 2002) to assess whether cougar, while carrying out potential hunting behaviors, exhibit 3rd order selection (Johnson 1980) for parcels of land containing commercial/hobby livestock in a Resource Selection Function analysis. This type of analysis requires distinguishing sites used by cougar for hunting behaviors, and sites available for cougar to carry out hunting behaviors. Characteristics of the landscape (presence/absence of livestock) for each USE site will be compared to landscape characteristics of paired AVAILABLE sites to examine whether cougar select for or against landscapes of a given type, when hunting. Sites used by cougar (USE) will be defined as a “path” of GPS locations collected by collared subjects < 24 hours prior to conducting a confirmed feeding event. As aforementioned, confirmed feeding events are randomly sampled, and verified in the field, from all potential feeding events conducted by a subject over each monthly time intervals. Two clusters of GPS points (any two or more GPS points located within 200 m and 4 days of one another) are randomly sampled each month for each subject. If prey remains are not found at these first two randomly sampled clusters, then another cluster is randomly picked and searched. The goal for each monthly sampling interval is to find at least two feeding events, for each subject, that can be reasonably confirmed kill events. I assume that killing behaviors would most likely be carried out when a cougar is hungry and thus searching for a prey item. Scavenging behaviors are not uncommon in Front Range cougar, and can be observed when one subject shares a killed item with another collared cougar, when a subject stumbles across a road/hunter killed ungulate, when a subject acquires a prey item from another predator, or when a subject visits localized area where humans frequently deposit carrion. It is unknown if prey searching behaviors are similar between a feeding event that involves a killing behavior and a feeding event involving a scavenging behavior. Therefore, paths of GPS locations, determined by field investigators, to lead to scavenging behaviors, may not be used in this analysis. To represent areas available to cougar for hunting, a paired set of AVAILABLE locations will be generated based on the “path” of USE locations, by converting these USE points to a contorting line feature. Next, this contorted line feature will be randomly transposed (random azimuth, rotation, and 272 �distance) to a new location within the home range of the subject cougar (Figure 3). This AVAILABLE set of locations must be completely contained by the Minimum Convex Polygon (or 95% fixed kernel) home range of the respective subject cougar. A-priori independent landscape variables that have potential influence on cougar hunting behavior will be attributed to each USE (hunting) and AVAILABLE site. A 50 m buffer will be created around each USE and AVAILABLE site in order to measure the percent coverage of landscape variables of interest. The percentage of the buffer containing the following variables will be measured: - Areal coverage inhabited by hobby livestock (as discussed above) - Distance to specific hobby livestock husbandry structure (if available) - Land-cover - Terrain ruggedness - Human density factors (Exurban/Rural) Each hunting path will consist of 1 - 7 distinct GPS locations, thus the independent variable measures of the landscape will be averaged over all 1-7 locations in the path. Using the data collected on USE and AVAILABLE paths locations, a generalized-linear-mixed model (GLMM) with a random intercept will be used within the RSF framework (Gillies et al. 2006). In this model, individual cougar are random effects that occur as random intercepts (Gelman and Hill 2007). Nesting the hunting path within each individual cougar under this two-level GLMM will give population level inferences, where the primary sampling unit is based on individual subjects, thus avoiding pseudo-replication from using the individual hunting paths. In addition, this approach handles continuous and categorical independent variables, as well as unbalanced data within the subjects. Dependent variable data is described as binomially distributed as 1 or 0 (1=USE, 0=NON-USE) and thus probability of selection is modeled with the equation: w(x)= __exp (β0 + β1x1ij + β2x2ij … βnxnij + γ0j)_ 1+ exp (β0 + β1x1ij + β2x2ij … βnxnij + γ0j) Where i = feeding sites 1,…,n within individual cougar j = 1,…. m The primary independent variables of interest to test for main effects will be the aerial coverage of parcels containing hobby livestock. Maximum likelihood estimation techniques will be used to obtain estimates of slope coefficients of independent variables. Significant positive β estimates will indicate selection for that variable. Separate analysis may be conducted for each respective cougar age/sex class, season, known livestock depredation history (1 = subject has previous known history of preying on domestic species, 0 = no history), and species found in kill event following hunting path (wild/domestic/ungulate/large prey/small prey). Objective 3: Compare species composition of cougar diets This component of the study will utilize the larger long term data set of approximately 800 randomly selected confirmed feeding events by collared cougars spanning 2008-2012. Measures of the relative frequency of occurrence for each prey species will be assessed, utilizing a data set composed of 800 randomly sampled GPS location cluster investigations of confirmed feeding events. For each subject cougar, the number of feeding events for each particular prey species will be divided by the total number of confirmed feeding events. A sample will consist of an individual cougar in order for the variance to represent inter-subject variability. Baseline estimates for the frequency of occurrence of each prey species, and for the reclassified small/large prey, will be calculated by: 273 �1.) Cougar sex and age 2.) Season 3.) Human disturbance measures (human density and distance-to-structure) To test whether human development influences the composition of prey consumed by cougar, I will use niche overlap or dietary breadth overlap (Colwell and Futuyma 1971, Colwell 2006) indices. Significant shifts in diet composition toward smaller species in landscapes with higher human density will indicate that human development could be associated with altered cougar predation behavior. Cougar sex, age, and seasonal differences will be tested in a similar manner. Objective 4: Compare predation rates on mule-deer and secondary items Feeding rates (feeding events/week) will be derived from the data set of randomly sampled GPS location clusters verified in the field as either being “absent, large-prey present, small-prey present”. Using multinomial logistic regression (Hosmer and Lemeshow 2000, Knopff et al. 2009), the probability of a small mammal or large-mammal feeding event, and associated standard errors, will be modeled for each cluster produced by each subject cougar from spatial and temporal characteristics of GPS locations collected within a particular cluster. Using techniques of Anderson and Lindzey (2003), modeled (predicted) probabilities and standard errors associated with all clusters of an individual subject will be summed, by small-prey events and large-prey events. The summed probabilities and summed standard errors will be divided by the total number of days monitored for the subject at hand. Coefficients of variation will be averaged across multiple subjects to obtain 95% confidence intervals, for both smallprey and large-prey feeding rates by: 1.) Cougar sex, age, and maternal status 2.) Season 3.) Human disturbance measure (human density only) Results and Discussion (Anticipated Results): Simultaneously answering questions relating cougar use of the landscape relative to prey distribution and human disturbance will give valuable insights to how a large top tier carnivore fits predictions of optimal foraging theory. Specifically, insight to how a top tier predator perceives its landscape and whether or not tradeoffs are being made between maximizing food intake and reducing risks posed by humans is important to advancing knowledge of how animals use resources and perceive their environment. Applications of optimal foraging theory to large carnivorous species are rare, and thus would add knowledge to whether or not predictions drawn from model species are scalable to the highest trophic levels. In addition, results from this study are important to conservation and management of the landscapes occupied by cougar. A study that simultaneously examines the influences of human development and prey distributions on cougar is important to predicting how well foraging behaviors of cougar may adapt to future urban sprawl. Finally, this study will provide knowledge on speculations regarding whether or not elevated prey resource levels are a driver of cougar use of exurban and suburban landscapes. Currently, analysis in the camera trap portion of this study allows for the assessment of cougar use for a particular prey species on an individual species basis. Much focus will be placed on species most commonly preyed upon by cougar, such as deer and elk. Pending sufficient camera trap detections of other species [i.e., raccoon, fox, coyote, wild turkey (Meliagris gallapova), skunk (Mephitis/Spilogale sp.), and housecat], spatial distributions of these alternative species may be modeled as well. Incorporating a wider range of species, in addition to accounting for detectability differences between species, would potentially allow future analysis to assess the selection of one particular species over other 274 �available species. In addition, fine scale species distribution data are rare, and thus these data may be useful to other wildlife/land managers and researchers. Increasing harvest rates of species involved in human/wildlife conflicts are a common practice for CPW managers. However, increasing the harvest quota may not be a suitable management method to decrease human/cougar conflicts for various reasons. First, increases in the quota for maximum harvest have not resulted in a substantial increase of harvested cougar (CDOW 2004). Second is that other research has found that small areas with high harvest may only exhibit increased immigration rates especially from younger age classes (Cooley et al. 2009), with no significant overall decrease in density. Thus, a population skewed toward a younger age structure may occur (Cooley et al. 2009). If speculations are true that younger cougar, relative to older cougar, are more likely to prey on hobby livestock, then hobby livestock owners may suffer an increased level of losses in the future. Knowing if cougar seek hobby livestock in certain seasons is important to predicting cougar/human conflicts. It is suspected that the spring periods are when livestock depredations are most reported. Speculations exist that cougar are seeking alternative prey sources during the spring months when primary prey sources (ungulates) are at their lowest availability. Results of this study have bearing on the conservation of cougar overlapping hobby livestock owners. Knowing whether or not a cougar may seek hobby livestock while hunting may have bearing on decisions made by agency wildlife managers and hobby livestock owners. Little is known about behaviors of cougar in the proximity of livestock. Nonetheless, decisions are sometimes made based on how the agency wildlife manager or livestock owner perceives the intended behavior of cougar travelling in the vicinity of livestock. For instance, when a cougar is found on a parcel of land containing hobby livestock, the landowner may legally euthanize the cougar if he/she believes that their livestock are endangered. Therefore, any cougar passing through parcels of land containing livestock may be killed if the landowner assumes that the cougar was seeking their livestock. When cougar are caught killing a hobby livestock item, it is unknown if the cougar was selecting for landscapes known to hold hobby livestock items, or if the cougar was hunting opportunistically in regard to hobby livestock distribution. Showing differences in prey-species composition indices and frequency of occurrences of individual species between differing sex and age classes is important to management/conservation of the prey species. Management techniques that change the sex or age structure of the cougar population may impact populations of certain prey species. For instance, if younger cougar are more likely to feed on small prey species, then using techniques that shift the cougar population to a younger age structure may have a large impact on populations of smaller prey. Testing for seasonal differences in prey-species composition indices and frequency of occurrence of individual species may have relevance to prey-switching abilities of cougar. Following these assumptions: - Early spring season (March-May) represents the time period with lowest primary prey (deer) availability. - Late summer season (August – October) represents the highest availability of primary prey. - Energetic demands are equal throughout the year. One may utilize the seasonal differences as a proxy to test whether or not cougar switch from using predominately deer or other natural prey items, to other prey species when faced with lower levels of primary prey availability. 275 �Assessing whether differences exist in cougar dietary composition and feeding rates of deer, between levels of high and low human density may be relevant toward discussions of whether or not suburban/exurban landscapes have an impact on cougar fitness, or on the contrary, how cougar may adapt to these potential human disturbances. Describing feeding rates on certain species such as deer and elk are important to wildlife managers in the Front Range. 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Monitoring wild animal communities with arrays of motion sensitive camera traps. IEEE International Workshop on Practical Issues in Building Sensor Network Applications. Accessed online 4-12-2011 http://arxiv.org/abs/1009.5718 Kertson, B.N. 2010. Cougar ecology, behavior, and interactions with people in a wildland-urban environment in western Washington. Ph.D. Dissertation. University of Washington, Pullman. pp. 149. Kertson, B.N., R.D. Spencer, J.M. Marzluff, J. Hepinstall-Cymerman, and C.E. Grue. 2011. Cougar space use and movements in the wildland-urban landscape of western Washington. Ecological Applications in-press doi:10.1890/11-0947.1. Knopff, K.H., A.A. Knopff, M.B. Warren, and M.S. Boyce. 2009. Evaluating Global Positioning System telemetry techniques for estimating cougar predation parameters. Journal of Wildlife Mangement 73:586-597. Knopff, K.H., A.A. Knopff, A. Kortello, M.S. Boyce. 2010. Cougar kill rate and prey composition in a multiprey system. 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Progress Report: U.S. Geological Survey Open-File Report 2007-1050. Michalsiki, F., R.L.P. Boulhosa, A. Faria, and C.A. Peres. 2006. Human-wildlife conflicts in a fragmented Amazonian forest landscape: determinants of large felid depredation on livestock. Animal Conservation 9:179-188. Murphy, K.M. 1998. Ecology of the cougar (Cougar concolor) in the northern Yellowstone ecosystem: Interactions with prey, bears, and humans. Ph.D. Dissertation, University of Idaho, Moscow. O'Brien, T.G. 2010. Abundance, density, and relative abundnace: a conceptual framework. In O'Connell et al. (eds.), Camera Traps in Animal Ecology: Methods and Analysis., Newyork, Springer. O'Brien, T.G., M.F. Kinnaird, and H.T. Wibisono. 2010. Estimation of species richness of large vertebrates using camera traps: An example from an Indonesian rainforest. In O'Connell et al. (eds.), Camera Traps in Animal Ecology: Methods and Analysis., Newyork, Springer. Pierce B.M., V.C. Bleich, J.D. Wehausen, R.T. Bowyer. 1999. Migratory patterns of mountain lions: Implications for social regulation and conservation. Journal of Mammalogy 80:986-992. Pierce B.M., V.C. Bleich, and , R.T. Bowyer. 2000. Social organization of mountain lions: Does a landtenure system regulate population size? Ecology 81:1533-1543. Pyke, G.H., H.R. Pulliam, and E.L. Charnov. 1977. Optimal foraging: A selective review of theory and tests. The Quarterly Review of Biology. 52:137-154. Rovero, F. and A.R. Marshall. 2009. Camera trapping photographic rate as an index of density in forest ungulates. Journal of Applied Ecology 46:1011-1017. Rowcliffe, J.M., J. Field, S.T. Turvey, and C. Carbone. 2008. Estimating animal density using camera traps without the need for individual recognition. Journal of Applied Ecology 45: 1228-1236. 277 �Rowcliffe, J.M., C. Carbone, P.A. Jansen, R. Kays, and B. Kranstauber. 2011. Quantifying the sensitivity of camera traps: an adapted distance sampling approach. 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Wildlife Society Bulletin 24:451-460. 278 �Figure 1: Proposed study area (2862 km2) (blue polygon), in the Front Range of Colorado. Study is primarily conducted in Boulder, Jefferson, Gilpin, and Clear Creek Counties (red polygons). Actual extent of study area used for analysis of prey distributions will be determined by a minimum convex polygon drawn around all cougar GPS locations collected concurrently with prey distribution camera monitoring component. 279 �Figure 2: Top left pane: NAIP imagery. Top right pane: Colorado Vegetation Classification BASINWIDE project layer overlaid on NAIP imagery. Bottom left: 25x25 m grid overlaid on top of 25x25 m grid cells of BASINWIDE raster layer. Within a habitat strata (forest for example) a site is randomly selected (blue grid cell). Bottom right: Points are randomly generated within a site to ensure random placement of camera trap. 280 �Figure 3: Example of GPS locations and corresponding movement path of a subject cougar. USE sites will be defined by confirmed feeding locations derived from GPS cluster analysis. Paired NON-USE sites will be selected from confirmed or highly probable travelling locations. 281 �Table 1: Sampling of the landscape for potential prey species will be conducted in a # tier multi-level stratification scheme. Major sampling strata, which describe the dominate land-cover of the site (Urban/Suburban included as major habitat type), followed by the substrata that describe the relative housing density (exurban and rural). Lastly, all combinations of substrata and major strata are classified by a distance-to-structure metric (Low = 0 – 200 m, Med = 200 – 700 m, and High = > 700 m). Table 2: List of the tentative number of camera sites sampling each categorical description of a site. Complete descriptions of each site take on 1 – 3 of these categories. 282 �APPENDIX III Front-range Cougar Movement Analysis Mat Alldredge Mevin Hooten Introduction: Despite numerous cougar studies across the Western United States, human understanding of cougar biology/ecology is nascent, largely because of the difficulty and expense of studying such an elusive, wide-ranging, and solitary species (Papouchis 2004). Technological advances, such as GPS telemetry, will increase the ability of researchers to gather valuable information on cougars, but such research has just begun, such as the Uncompahgre Plateau research project (Logan 2005). Even less information is known about cougar biology/ecology within urban/exurban environments. Other studies have documented the impacts of urban environments on cougar temporal and spatial use patterns. Ordenana et al. (2010) documented an overall decrease in cougar occurrence associated with proximity and density of urban landscapes. Other studies have shown that dense housing developments can act as movement barriers to cougars (Orlando et al. 2008) or that cougars will become more nocturnal in urban areas (Kertson 2010). Similarly, studies have shown selection of home ranges, use within home ranges, general movements, and dispersal can be affected by roads, road densities and/or traffic volumes (Van Dyke et al. 1986, Belden and Hagedorn 1993, Beier et al. 1995, Sweanor et al. 2000, Dickson and Beier 2002, Orlando et al. 2008). Preliminary investigations suggest that cougars in the front-range of Colorado are similarly affected by urbanization as nocturnal behaviors and changes in use relative to human density have been observed with GPS collared cougars during the study. One of the main objectives of the Front-range Cougar study is to examine how cougars are using the urban environments. This includes temporal and spatial use patterns, responses to novel environments, and responses to human activity and structures. Historical types of analyses would involve use versus availability and resource selection function (RSF) type analyses. However, with fine scale, highly accurate GPS data there is the potential to look at these use patterns in much more detail. If GPS data are at a fine enough scale it would be possible to know exactly what an animal was using and exactly how an animal moved through the environment. With logistical constraints associated with GPS acquisitions, battery life, and data storage, it is rare that this much detail is obtained. However, with a regular GPS fix interval, such as every 3 hours, it is possible to model the movement paths of an individual through its environment and obtain very detailed information on how an animal is using an area both spatially and temporally (e.g., Johnson et al. 2008, Hooten et al. 2010). Our intent with this project is to perform detailed movement analyses with regard to demographic/population effects, environmental factors, and technological innovations. All of these analyses will provide pertinent information towards better management of cougars, especially in urban areas, or provide information that will improve research techniques for studying cougars. These analyses will also provide valuable information for other analyses being done as part of the ongoing Front-range Cougar research project. Movement patterns of cougars are likely to differ among sex and age classes of cougars and be affected as individual cougars interact with other cougars across the landscape. Sub-adult cougars are likely to have different movement patterns than adults as they are exploring new environments, establishing home ranges and interacting with other cougars. Adult males may also differ as they are defending territories more rigidly, and looking for mates. There may also be seasonal difference in movement patterns with regard to environmental changes, changes in prey distributions, and changes in behavior of individual animals. Adult females may have large differences in movement patterns as they 283 �transition through life stages. For example, movements of an adult female may be very different as she gives birth to cubs, raises young cubs, teaches older cubs to hunt, and then becomes solitary again. An understanding of how movement patterns are affected relative to demographic factors, life stages, and intra-specific interaction will be useful to cougar management and will potentially provide a better understanding of cougar-human interactions. Movement patterns of cougars are also likely to be affected as individuals interact with their environment. At a broad scale it may be possible to examine differences in movement patterns between cougars on the front-range of Colorado and the Uncompahgre Plateau. Finer-scale analyses will be conducted to examine how landscape features, especially those related to human use or development affect movements of cougars. Of interest would be how cougars respond to roads, areas of high human use, and areas of high human density. Mortality of cougars on the front-range is very high with respect to vehicle collisions, yet little is known about how cougars are responding to roads and traffic volumes. Cougars are also utilizing areas with high human use and high housing densities, but it is unknown if they use these areas differently than areas with little human presence. Although we do know that cougars use these urbanized areas, it is not known how they are using these areas with regard to potential avoidance of point sources of human presence. Similar questions can be asked about movement patterns of cougars with regard to human recreation and peaks in human activity on open space or other recreational areas. We also hope to gain some technical knowledge from movement analyses with regards to data collection and the use of activity data to improve movement analyses. Understanding how cougars move through their environment or utilize their home ranges will improve our ability to survey cougar populations in the future. The use of camera traps to survey animals is becoming more common and these analyses will aid our understanding of proper camera placement and expected detection probabilities from the traps. The GPS collars being used in the front-range cougar study are equipped with accelerometers, which provide information on an individual cougar’s behavior. Such information may prove useful in refining more detailed analyses of movement data as the activity between two successive points will be available as well. We also hope to provide some insight into optimal GPS fix rate with regard to balancing the trade-offs between battery life and number of fixes for GPS collars using these movement analyses. Objectives: 1. Demographic/population level movement analyses. a. Relative to age and sex. b. Intra-specific interactions. c. Seasonal patterns. d. Prey distributions. e. Life stage (i.e. caring for offspring). 2. Environmental level movement analyses. a. Comparisons between front-range and Uncompahgre cougars. b. Effect of human related environmental attributes. i. Housing density. ii. Human activity. iii. Roads. iv. Avoidance of humans or human structures within urban areas. v. Reaction to human recreation. 3. Technical applications. a. Information for cougar population surveys i. Placement of camera traps ii. Detection rates b. Use of activity to improve movement models 284 �c. Optimal GPS fix rates relative to animal movement Approach: Our intent is to use existing GPS data from the front-range cougar study and possibly from the Uncompahgre Plateau study to examine cougar movements relative to demographic/population level factors and environmental factors and to provide methodological advances in research techniques. We will also utilize various GIS layers, such as habitat data, housing density, roads, etc, to inform the analyses. No additional field data should be required for the analysis. Formal statistical approaches to studying animal movement as well as the environmental and anthropogenic drivers of animal movement have advanced tremendously in the past 5 years. Specifically, the most important developments have utilized the wealth of recently available fine-scale high-accuracy telemetry data (e.g., GPS) and have constructed hierarchical models that allow for inference on both individual and population-level parameters (Johnson et al. 2008; Hooten et al. 2010; Hanks et al. 2011). For this study, the first 2 objectives dealing with demographic/population level analyses and environmental analyses can both be accomplished using these existing sophisticated modeling approaches in general. However, it should be noted that a few of the sub-objectives will require a generalization of current models. Specifically, no current technology is available to rigorously account for intra-specific interaction between individuals. Similarly, although current methods can account for demographic differences between animals (e.g., Hanks et al., 2011), how to deal with changes in a single individual’s demographic status within a rigorous statistical framework is still an unsolved problem. The existing modeling methodology will need to be extended to accommodate these features. In general, the critical aspects of our modeling efforts are 1.) the ability to “connect the dots” along animal paths while properly accounting for the uncertainty at unobserved locations (Fig. 1), and 2.) to use the continuous information in these “path distributions” to make statistical inference on the desired quantities (e.g., demographics, environmental drivers, intra-species interactions). In order to obtain a distribution for the animal paths, we use the correlated random walk model proposed by Johnson et al. (2008), we then are able to connect the paths to the underlying spatial environment (or other individuals) by incorporating these path distributions into a likelihood for a larger hierarchical model that allows for various influential effects on movement (Fig. 2). Figure 1: Two example paths with the black dots representing telemetry locations and the gray shading representing the uncertainty in the actual continuous path itself. These methods allow us to formally ask questions pertaining to the differences in space use and movement between various demographic components of the population and determine how individuals may be responding to landscape features and human land use (e.g., road corridors, urban open space, suburban neighborhood geometry). Additionally, Hanks et al. (2011) have developed methods that allow us to answer broader synthetic questions about the differences within and between populations of animals. For example, we will be able to assess how front range cougars are using space and interacting with each other differently 285 Figure 2: Example spatial covariates, the effects of which may be of interest for animal movement (e.g., elevation and aspect). �than the Uncompahgre Plateau cougars or, alternatively, if any differences are due mainly to individuallevel variation. Finally, the available cougar telemetry data provide some unique opportunities for advancing methodology pertaining to the collection and use of similar types of data. For example, given that camera trapping can provide a cost-effective alternative to telemetry methods, we can develop methods that fuse the two types of data, where available, to better learn about how to construct camera trapping grids for cougars. Moreover, by reconciling the two forms of data in a single model, we may be able to borrow strength from both forms of data to answer movement-based questions about animals that are not collared, given information from the animals that are both collared and observed on camera. This is a completely novel idea that has not yet been described in the literature, but will be very useful for future monitoring efforts because it could provide a justification for the use of more non-invasive observational approaches. Another example of an area that shows great potential for use is with the duty cycling of telemetry devices. Since these devices (e.g., collars or tags) are often set in an arbitrary fashion to either maximize battery life or minimize the resolution, a tool that could help provide some guidance on the management of the these devices is needed. Further, given recent advances in optimal monitoring methods (Hooten et al. 2008; Hooten et al. 2011) there is an opportunity to translate these types of efficient effort saving approaches for monitoring to help create a dynamic adaptive rule set for managing the duty cycling. That is, on an individual or species-level basis, there may be times when it is most effective (and efficient) to switch the devices back and forth between transmit mode. Current procedures for this are somewhat arbitrary and our methods will allow the data themselves to help inform the duty cycling settings of these telemetry devices. The result would be better scientific inference on the movement processes of interest while maintaining a longer lasting battery life. Literature Cited: Beier, P., D. Choate, and R.H. Barrett. 1995. Movement patterns of mountain lions during different behaviors. Journal of Mammalogy 76:1056-1070. Beldon, B.C. and B.W. Hagedorn. 1993. Feasibility of translocating panthers into northern Florida.Journal of Wildlife Management 57:388-397. Dickson, B.G. and P. Beier. 2002. Home-range and habitat selection by adult cougars in southern California. Journal of Wildlife Management 66:1235-1245. Hanks, E.M., M.B. Hooten, D.S. Johnson, and J. Sterling. (2011). Velocity-based movement modeling for individual and population-level inference. PLOS-One. In Review. Hooten, M.B., C.K. Wikle, S. Sheriff, and J. Rushin (2009). Optimal spatio-temporal hybrid sampling designs for ecological monitoring. Journal of Vegetation Science, 20: 639-649. Hooten, M.B., Johnson, D.S., Hanks, E.M., and J.H. Lowry. (2010). Agent-based inference for animal movement and selection. Journal of Agricultural, Biological and Environmental Statistics, 15: 523-538. Hooten, M.B., B.E. Ross, and C.K. Wikle. (2011). Optimal spatio-temporal monitoring designs for characterizing population trends. Gitzen, R.A., J.J. Millspaugh, A.B. Cooper, and D.S. Licht (eds). In: Design and Analysis of Long-Term Ecological Monitoring Studies. In Press. Johnson, D. S., London, J. M., Lea, M.-A., and Durban, J. W. (2008). Continuous-Time Correlated Random Walk Model for Animal Telemetry Data. Ecology, 89, 1208–1215. Kertson, B. 2010. Cougar ecology, behavior, and interactions with people in a wildland-urban environment in Western Washington, Ph.D. Dissertation, University of Washington. Logan, K.A. 2005. Cougar population structure and vital rates on the Uncompahgre Plateau, Colorado. Wildlife Research Report, July: 105-126. Colorado Division of Wildlife, Fort Collins, USA. Ordenana, M.A., K.R. Crooks, E.E. Boydston, R.N. Fisher, L.M. Lyren, S. Siudyla, C.D. Haas, S. Harris, S.A. Hathaway, G.M. Turschak, A.K. Miles, and D.H. Van Vuren. 2008. Effects of urbanization on carnivore species distribution and richness. Journal of Mammalogy 91:1322-1331. 286 �Orlando, A.M., S.G. Torres, W.M. Boyce, E.H. Girvetz, E.A. Laca, and M.W. Demment. Does rural development fragment cougar habitat? Toweill, D., S. Nadeau, and D. Smith (eds) In: Proceedings of the 9th Mountain Lion Workshop, Cougars: Past, Present and Future Challenges. Papouchis, C.M. 2004. Conserving mountain lions in a changing landscape, in People and Predators: From Conflict to Coexistence, ed. N. Fascione, A. Delach, and M. E. Smith, 219-239. Island Press, Washington, D.C. Sweanor, L.L., K.A. Logan, and M.G. Hornocker. 2000. Cougar dispersal patterns, metapopulation dynamics and conservation. Conservation Biology 13:798-808. Van Dyke, F.G., R.H. Brocke, and H.G. Shaw. 1986. Use of road track counts as indices of mountain lion presence. Journal of Wildlife Management 50:102-109. 287 �APPENDIX IV Colorado Cougar Population Estimation Mat Alldredge Bill Kendall Introduction: In order to set harvest quotas, evaluate management practices and understand the dynamics of predator-prey systems, it is desirable to have reliable estimates of population size. Unfortunately, as with many predators, it can be very difficult and expensive to obtain these estimates. This is especially true with cougars because of their low densities, secretive nature, and unpredictable response to lures, baits and/or calls. Most reliable estimates of population size for cougars have come from intensive capture and monitoring studies, which were expensive and time consuming (Logan 1983, Lindzey et al. 1994, Murphy 1998, Logan and Sweanor 2001). One approach that is used to estimate cougar population size is the two-sample Lincoln Petersen estimator in conjunction with an ongoing marking study (Anderson and Lindzey 2005). However, this method does require a marked population and is subject to all of the Lincoln-Petersen model assumptions, which include constant probability of capture among all individuals and time periods and closure (Williams et al. 2002). To demonstrate the logistics of using this estimator we will assume a cougar population at maximum density [3.6 independent cougars per 100km2 (Hopkins et al. 1986)]. If we survey an area of 1,000 km2 then our true population is 36. If we then assume a capture probability of 0.5 we should capture 18 individuals during each capture period and 27 unique individuals during both periods. To achieve capture of so many individuals during a time period when the closure assumption can be met, capture effort would be extremely high. However, if all of the assumptions were met, the expected value for the population size would be 36 cougars with a 95% CI of ± 10.1 cougars or a range of 26 to 46 cougars. If we double our survey area to 2,000km2 and maintained all of the same assumptions we would capture 36 cougars during each sampling period or 54 unique individuals during the study. The expected values for this survey are a population size of 72 with a 95% CI of ± 15.4 cougars or a range of 67 to 87 cougars. To improve these estimates it would be necessary to use multiple recapture occasions, which would require even greater effort and expense. Additionally, estimates with these techniques are likely to be biased as violations of model assumptions are likely. Because of the difficulty and expense associated with typical mark-recapture techniques for estimating carnivore abundance, alternate techniques have been developed. Many of these techniques involve noninvasive genetic sampling, which is a type of mark-recapture sampling. Noninvasive genetic sampling (Hoss et al. 1992, Taberlet and Bouvet 1992) has the potential to provide a realistic method for sampling a population of interest. Noninvasive sampling techniques include the use of hair snares and scat collections (Ernest et al. 2000, Harrison et al. 2004, Smith et al. 2005). The use of scats for sampling cougar populations may be particularly useful and provide a representative sample of the population. Scat collections can either be done by searching transects with human observers (Harrison et al. 2004) or with trained dogs (Smith et al. 2005). Scats could also be collected from kill sites. Track counts have also been used to assess cougar population trends (Smallwood and Fitzhugh 1991, 1995, Smallwood 1994, Cunningham et al. 1995), but actual relationships to population size are generally weak (Van Dyke et al. 1986, Van Sickle and Lindzey 1992). For example, Cunningham et al. (1995) failed to detect an estimated 33% decline in cougar abundance using track surveys. Based on computer simulations, sampling effort required to detect a change in cougar populations is very high (Beier and Cunningham 1996). Difficulty detecting tracks in dense vegetation or rocky slopes in conjunction with access limitations to some areas may limit the utility of this approach (Anderson 2003). Probability based sampling (Becker 1991) may be a useful alternative to sample snow tracks of cougars 288 �over large areas using aircraft (Van Sickle and Lindzey 1992, Anderson 2003). Either transect based probability sampling (TPS) (Becker 1991) or a sampling block design (BPS) (Becker et al. 1998) can be used, but Anderson (2003) found better accuracy and precision using the TPS approach adjusted for short track sets (cougars at kill sites with near zero probabilities of detection during the survey). Although the use of scats for noninvasive genetic sampling may sound appealing, based on personal experience, the actual encounter rate of scats may be prohibitively low to make this a viable option. Track surveys are also appealing but do require specific tracking conditions and can be dangerous as they involve flying over mountainous terrain at low altitude. The alternative approach would be to collect hair or tissue from cougars that are lured into a site. Although the use of hair snags and lures have proved effective on many species, such as bears, the technique has not been rigorously evaluated for cougars. Lures have been found relatively ineffective at luring cougars to a specific site, even when cougars are known to be in close proximity (Long et al. 2003, Choate et al. 2006). The types of lures that have been tried are various scents, food sources, and animal calls. Having a significant number of cougars GPS collared in an area provides a unique opportunity to evaluate the effectiveness of a variety of lures, because we will be able to map the location of known individuals in relation to various lures and assess detection rates based on evidence found at lure sites. In order to be able to accurately estimate cougar population size using non-invasive sampling techniques, a thorough understanding of the detection process will be required. The detection process is comprised of the probability that an individual is available for detection (pa). This may be the probability that the animal is within a sampling grid or within a given distance of a sampling location. The second part of the detection process is the probability of detecting an individual given that it is available for detection (pd), or the probability that you can lure an individual to a sampling location. The final component of the detection process is the probability of obtaining a non-invasive sample from an individual given that it is available and is lured to the sampling location (ps). Given these components, we could estimate population size ( ) as, . Where n is the number of individuals sampled (Williams et al. 2002). Objectives: 1. Evaluate various lures (scents, baits, and calls) to attract cougars in relation to known cougar locations with regard to: a. Sex and/or age of the individual cougar. b. Temporal effects (season). 2. Investigate the detection process for cougars with regard to: a. Probability of being available for detection (on the grid). b. Probability of being detected given that it is available. 3. Assess methods for obtaining genetic samples given a detection with regard to: a. Various extraction methods. b. Genetic quantity. c. Genetic quality. Expected Benefits: The ability to estimate population size or track population changes is critical to the management of a species, especially when harvest quotas are being set for that species. This study is designed to develop tools that can be implemented in areas where cougars are not actively being studied and marked that will allow biologists/managers to gain a better idea of population size and population response to 289 �management prescriptions. Such estimates, in conjunction with harvest data will allow managers to better understand the cougar populations they manage, set appropriate harvest quotas and defend our management actions to the public. Approach: Our intention with this portion of the study is to gain insight into the detection process in order to develop methods that may be useful to estimating population size. We have no intention of actually estimating population size until the components of this approach have been evaluated. To assess the availability of a cougar to be sampled we will examine existing GPS data with regard to movement within grids. An alternative approach is to examine availability as a function of distance from a sampling location. Movement patterns will be examined as part of a separate study but results may be incorporated here. In order to assess the probability of a cougar being attracted to a lure we will mimic the design of an actual population survey. In an actual population survey the area of interest would likely be sampled using a grid approach with a grid size equal to a quarter of the average home-range size (Otis et al. 1978, White et al. 1982, Williams et al. 2002). Within each grid a lure would be placed by randomly selecting a location that is deemed to be a likely place for the species to occur within the grid based on expert opinion. We will use a grid size equivalent to one quarter of the average female home-range size, because females have significantly smaller home-range sizes than males. This may create heterogeneity in the probability of detection between males and females because of the greater number of lures within a male’s home-range and their larger movement patterns. For the purpose of evaluating the probability of a cougar being attracted to a lure we will not grid the entire study area but will grid individual properties on which we have permission to work. Within each grid we will randomly choose from a set of locations, previously identified by expert opinion, that should optimize our chances of luring a cougar to the location. We will randomly assign lure types (scent, call, bait, etc.) at each location. Trail cameras will be set at each location to verify the presence of a cougar. These pictures will also provide information on how cougars react to various lures, which may provide useful information on how to collect non-invasive genetic samples. The main variable of interest is the probability of detection given that an individual cougar is in the area. GPS information from collared cougars will be used to verify that a cougar was within the sampling grid. Location data will also be used to approximate distance between a cougar and a lure, which could be used as a covariate in estimating the detection rate. Non-detection rates will also be of interest, especially with regard to distance from the lure, as this will provide information on the ability of a lure to attract an individual. For example, an individual cougar may travel very close to a lure but never approach the lure. A repeated measures analysis will also be used to determine if there is any behavioral effect associated with reward versus non-reward lures. Cougars may avoid lures (calls or scents) after the first experience if no reward is provided, or conversely, approach lures more if a reward is provided. We will also examine various methods (hair snags, scratch pads, etc) for obtaining non-invasive genetic samples from individual cougars. Felids have proven difficult to obtain good genetic samples from so we will try to develop an effective approach for obtaining a genetic sample from a free-ranging cougar that provides sufficient quality and quantity of DNA. This work will begin at the Fort Collins Wildlife Research Center where the 3 captive cougars will be used to determine the most effective methods for obtaining these samples. Based on the results of this investigation we will then proceed to examine any methods that were promising in the captive situation in a field setting. 290 �Location of Work: This work will be conducted along Colorado’s front-range, in Boulder, Jefferson, Gilpin and Larimer counties and at the Fort Collins Wildlife Research Center. The study area is defined by the existing boundary for the ongoing cougar research project. Schedule of Work: Time Fall, 2011, ongoing August 2012, ongoing Activity Evaluation of lures & probability sampling Summary report of findings Estimated Costs: Salaries of permanent employees, as well as many other logistical costs (vehicles and lures) will be covered by existing project funds in the CPW carnivore research (approx. $250,000) and terrestrial management programs. Literature Cited: Anderson, C.R., Jr. 2003. Cougar ecology, management and population genetics in Wyoming. Dissertation, University of Wyoming, Laramie, Wyoming, USA. Anderson, C.R., Jr., and F.G. Lindzey. 2005. Experimental evaluation of population trend and harvest composition in a Wyoming cougar population. Wildlife Society Bulletin 33:179-188. Becker, E.F. 1991. A terrestrial furbearer estimator based on probability sampling. Journal of Wildlife Management 55:730-737. Becker, E.F., M.A. Spindler, and T.O. Osborne. 1998. A population estimator based on network sampling of tracks in the snow. Journal of Wildlife Management 62:968-977. Beier, P., and S.C. Cunningham. 1996. Power of track surveys to detect changes in cougar populations. Wildlife Society Bulletin 24:540-546. Choate, D.M., M.L. Wolfe, and D.C. Stoner. 2006. Evaluation of cougar population estimators in Utah. Wildlife Society Bulletin 34:782798. Cunningham, S.C., L.A. Haynes, C. Gustavson, and D.D. Haywood. 1995. Evaluation of the interaction between mountain lions and cattle in the Aravaipa-Klondyke area of southeast Arizona. Arizona Game and Fish Department Technical Report No. 17, Phoenix, Arizona, USA. Ernest, H. B., M. C. T. Penedo, B. P. May, M. Syvanen, and W. M. Boyce. 2000. Molecular tracking of mountain lions in the Yosemite Valley region in California: genetic analysis using microsatellites and faecal DNA. Molecular Ecology 9:433-441. Harrison, R. L., P. B. S. Clarke, and C. M. Clarke. 2004. Indexing swift fox populations in New Mexico using scats. American Midland Naturalist 151:42-49. Hopkins, R.A., M.J. Kutilek, and G.L. Shreve. 1986. The density and home-range characteristics of cougars in the Diablo Range of California. Pages 223-235, in S.D. Miller and D.D. Everett, editors. Cats of the world: Biology, Conservation and Management. National Wildlife Federation, Washington, D.C., USA. Hoss, M., M. Kohn, S. Paabo, F. Knauer, and W. Schroder. 1992. Excrement analysis by PCR. Nature 359:199. Lindzey, F.G., W.D. Vansickle, B.B. Ackerman, D. Barnhurst, T.P. Hemker, and S.P. Laing. 1994. Cougar population dynamics in southern Utah. Journal of Wildlife Management 58:619-624. Logan, K.A. 1983. Mountain lion population and habitat characteristics in the Big Horn Mountains of Wyoming. Thesis, University of Wyoming, Laramie, Wyoming, USA. Logan, K.A. and L.L. Sweanor. 2001. Desert cougar: evolutionary ecology and conservation of an enduring carnivore. Island Press, Washington, D.C. 291 �Long, E.S., D.M. Fecske, R.A. Sweitzer, J.A. Jenks, B.M. Pierce, and V.C. Bleich. 2003. Efficacy of photographic scent stations to detect mountain lions. Western North American Naturalist 63:529532. Murphy, K.M. 1998. The ecology of the cougar (Cougar concolor) in the northern Yellowstone ecosystem: interactions with prey, bears, and humans. Dissertation, University of Idaho, Moscow, Idaho, USA. Otis, D.L., K.P. Burnham, G.C. White, and D.R. Anderson. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. Smallwood, K.S. 1994. Trends in California mountain lion populations. Southwestern Naturalist 39:6772. Smallwood, K.S., and E.L. Fitzhugh. 1991. The use of track counts for mountain lion population census. Pages 59-67 in C.E. Braun, editor, Mountain Lion-Human Interactions Symposium and Workshop. Colorado Division of Wildlife, Denver, Colorado, USA. Smallwood, K.S., and E.L. Fitzhugh. 1995. A track count for estimating mountain lion Felis concolor californica population trend. Biological Conservation 71:251-259. Smith, D. A., K. Ralls, B. L. Cypher, and J. E. Maldonado. 2005. Assessment of scat-detection dog surveys to determine kit fox distribution. Wildlife Society Bulletin 33:897-904. Taberlet, P., and J. Bouvet. 1992. Bear conservation genetics. Nature 358:197. Van Dyke, F.G., R.H. Brocke, and H.G. Shaw. 1986. Use of road track counts as indices of mountain lion presence. Journal of Wildlife Management 50:102-109. Van Sickle, W.D., and F.G. Lindzey. 1992. Evaluation of road track surveys for cougars (Felis concolor). Great Basin Naturalist 52:232-236. White, G.C., D.R. Anderson, K.P. Burnham, and D.L. Otis. 1982. Capture-recapture removal methods for sampling closed populations. Los Alamos National Laboratory Publication LA-8787-NERP. Los Alamos, NM. Williams, B.K., J.D. Nichols and M.J. Conroy. (2002) Analysis and Management of Animal Populations. Academic Press. San Diego, CA. 292 �Colorado Division of Parks and Wildlife July 2010 – June 2011 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 7210 1 : : : : Division of Parks and Wildlife Mammals Research Customer Services/Research Support Library Services N/A Period Covered: July 1, 2010 – June 30, 2011 Author: Kay Horton Knudsen Personnel: Kay Horton Knudsen, Chad Bishop All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) Research Center Library has existed for several decades in the Ft. Collins office. A library housed in the Denver office was moved to Ft. Collins many years ago. Early librarians, Marian Hershcopf and Jackie Boss, can be credited with the physical organization of the Library including seven decades of Federal Aid reports, almost 50 years of Wildlife Commission reports and a unique book and journal collection. Jackie Boss retired in April 2007 and the Library was temporarily closed to all services. Kay Horton Knudsen was hired as the new Research Center Librarian and began employment with CPW on August 30, 2008. The goal, as stated by a former supervisor, was to reopen the Library and expand the electronic and digital capabilities of library services to the entire CPW. Chad Bishop became the Mammals Research Team Leader in July 2009. His duties include supervision of the Research Center Library. A progress report and current status of the Library are detailed below. 293 �WILDLIFE RESEARCH REPORT COLORADO PARKS AND WILDLIFE RESEARCH LIBRARY SERVICES KAY HORTON KNUDSEN P.N. OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Parks and Wildlife (CPW) employees, cooperators and wildlife educators. SEGMENT OBJECTIVES 1. Continue to improve and modernize library services. 2. Continue to develop, improve, and implement the CPW Research Center Library web-site. SUMMARY OF LIBRARY SERVICES The Research Center Library celebrates its third full year of operation since reopening in 2008. Work continues on upgrading website features, filling literature research requests and taking a more longterm view on improving Library services. During the first year, in additional to cleaning and physical organization, a priority task was choosing and implementing a web-based Integrated Library System (ILS) and purchasing statewide access for CPW staff to online research databases. The second year emphasis was on meeting CPW staff and promoting the Library in a series of training demonstrations. Moving into the third year of operation, major projects were purchase of a new federated search feature for the Library website, digitization of CPW publications and continued contact with staff statewide to meet their bibliographic research needs. Since the Library serves as a historic archive for CPW publications, each meeting with staff also includes a request to be included in the dissemination of white papers, journal articles and internal reports. Dayto-day duties continue to be responding to research and document retrieval requests, cataloging newly acquired material and maintaining the serial collection. EOS International is the vendor for the ILS. It was decided to initially purchase the basic modules (a hosted system with library catalog, circulation, cataloging and serials control.) The Library website was released to CPW staff in March 2009. The next module purchased from EOS was Indexer – this feature allows for full-text searching of PDFs linked to bibliographic records and was implemented in December 2009. The latest modules are Knowledge Builder and Classification Management. They will be used to archive and index historic research documents. In addition to the catalog of books and reports housed in the Ft. Collins Library, the Library website also gives CPW staff access to research databases. Current subscriptions include BioOne, four of EBSCO’s specialty databases (Environment Complete, Fish and Fisheries Worldwide, Wildlife and Ecology Studies Worldwide and Criminal Justice with Full Text), SORA (Avian journals) and the JSTOR Life Sciences collection. Through several of the print periodical subscriptions, the Library also has access to the publisher’s full-text online archives. Backfiles of major wildlife and aquatic journals were purchased to expand the full-text capability. CPW staff statewide are authenticated through WildNet (intranet) eliminating the need for individual usernames and passwords. 294 �A federated, or integrated, search feature for the Library website was on the wish-list from day one. Federated searching combines access to the Research Library catalog, all of the third-party databases listed above, as well as most of the online journals into one all-in-one search. It took extensive planning and working with various vendors to finally make this available. EBSCOHost’s Integrated Search (EHIS) was chosen in the fall of 2010 and the link was made available on the Library website in the spring of 2011. Library handouts were updated and a new handout created to explain the features and offer tips on the use of the all-in-one search. The entire federated search industry is evolving and the librarian will continue to work with EBSCO staff to resolve problems and maintain links to all resources. The next major project envisioned at the reopening of the Library was the digitization of CPW publications. Research on various digitization options took place in 2009/2010. An HP printer/scanner with optical character recognition software was purchased, installed and tested by summer 2010. The first document series to be digitized was Outdoor Facts. The resulting PDFs are attached to bibliographic records for each title within the series and are available via the Library catalog for download by CPW staff throughout the state. Following the digitization, the remaining print copies of Outdoor Facts were distributed to staff for their historic collections. The second series digitized was the much larger Special Reports collection. The first report in this collection was published in 1962 and all 82 reports represent the work of terrestrial and aquatic staff. They are available as fully searchable PDFs on the Library website. Other projects in the Library this year included: 1) processing journal subscription renewals and updates to include full-text online access, 2) beginning a project to catalog the backlog of theses/dissertations, 3) sending Colorado Outdoors magazines to bindery to continue long-term archival collection, 4) continuing to add links to PDF formats into the catalog’s bibliographic file, 5) printing and cataloging the Data Analysis Unit (DAU) reports to maintain a historic record in the Library collection, 6) writing a Collection Development policy for the Library and 7) conducting a survey of CPW staff on their impressions and expectations of the Library using Survey Monkey research tool; received 113 responses. NOTE: the Library was physically closed to all staff access from November 2010 through January 2011 due to extensive remodeling of the building’s heating and air conditioning systems. The librarian worked from a borrowed office during this time. The librarian attended the following conferences and workshops: 1) Cyber Infrastructure workshop at CSU, August 2010, 2) Colorado Association of Libraries annual conference in Loveland, October 2010, 3) Presentation Skills workshop in Denver CPW office, December 2010, 4) the American Fisheries Society/The Wildlife Society, Colorado chapters meeting in Ft. Collins, February 2011, 5) InterLibrary Loan conference, CSU, April 2011, 6) Data Curation Profile workshop, CSU, April 2011, 7) Financial Planning workshop in Denver CPW office, June 2011. There was also the opportunity throughout the year to participate in several online “webinars” sponsored by various vendors and library agencies to expand knowledge on trends in the library field. With expanded library services, the number of requests for documents or research assistance has grown. Most questions received in the Library are from CPW staff or from outside researchers (generally consultants and out-of-state natural resources employees). The Library is not open on a walk-in basis to the general public but the librarian does assist the Help Desk at the Denver office with questions they receive. CPW employees generally request journal articles or items from the Library collection; outside researchers most often want a copy of a CPW publication. The chart below shows the number of reference questions and document requests handled by the librarian during the past 3 years. Please note that one request from a CPW staff member may be for multiple journal or book titles. 295 �Reference Requests August 2008 September 2008 October 2008 November 2008 December 2008 January 2009 February 2009 March 2009 April 2009 May 2009 June 2009 15 21 33 14 28 33 30 35 24 13 20 July 2009 August 2009 September 2009 October 2009 November 2009 December 2009 January 2010 February 2010 March 2010 April 2010 May 2010 June 2010 Reference Requests 20 25 30 38 28 32 62 43 36 23 17 26 July 2010 August 2010 September 2010 October 2010 November 2010 December 2010 January 2011 February 2011 March 2011 April 2011 May 2011 June 2011 Reference Requests 45 34 37 41 46 34 48 43 46 30 51 27 STATISTICS: As of June 30, 2011, the Research Center Library holds 18,572 titles and 24,174 items (these are the multiple copies of a title) and has 126 registered patrons (CPW staff). There were 2,314 searches conducted in the Library catalog during the year. Usage statistics for the research databases are given in the chart below. For BioOne and EBSCO the numbers are for the total searches run; for JSTOR the statistics are for the number of successful full-text article requests. July 2010 August 2010 September 2010 October 2010 November 2010 December 2010 January 2011 February 2011 March 2011 April 2011 May 2011 June 2011 TOTAL BioOne 37 98 107 62 57 73 151 230 157 197 259 141 1569 EBSCO searches 138 147 637 585 465 1221 1855 2675 1616 1405 2562 1169 14,475 Prepared by ___________________________ Kay Horton Knudsen 296 JSTOR 148 97 203 195 115 203 277 358 174 217 339 192 2518 � https://cpw.cvlcollections.org/files/original/04d288e61cd933182906c4b7075b8f95.pdf 6ae2ec8ec24c2918fed1d49e1f0a5290 PDF Text Text MAMMALS - JULY 2012 �1 �WILDLIFE RESEARCH REPORTS JULY 2011 – JUNE 2012 MAMMALS PROGRAM COLORADO DIVISION OF PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). 2 �STATE OF COLORADO John Hickenlooper, Governor DEPARTMENT OF NATURAL RESOURCES Mike King, Executive Director PARKS AND WILDLIFE COMMISSION Tim Glenn, Chair……………………………………………….………..………………….……......Salida Gary Butterworth, Vice Chair…………………………………………………………….Colorado Springs Mark Smith, Secretary…………………………………………………………………………….….Center David Brougham………………………………………………………………………………….Lakewood Chris Castilian ……………………………………………….………….….……………….............Denver Dorothea Farris………………………………………………………………………….….……Carbondale Allan Jones………………………………………………………………………………………...…Meeker Bill Kane………………………………………………………………………………………………Basalt Gaspar Perricone………………………………………………………………………………….….Denver James Pribyl…………………………………………………………………………………………Boulder John Singletary……………………………………………………………………..………………Vineland Robert Streeter…………….……………………………….……………………………………Fort Collins Lenna Watson……………………………………………………………………………….Grand Junction Dean Wingfield………………………………………………………………………..……………..Vernon Mike King, Executive Director, Ex-officio………….…………………...………………….…….....Denver John Salazar, Dept. of Agriculture, Ex-officio….………………………………..…….………... Lakewood DIRECTOR’S LEADERSHIP TEAM Rick Cables, Director Ken Brink, Steve Cassin, Marilyn Gallegos Ramirez, Heather Dugan, Gary Thorson, Jeff Ver Steeg, Craig McLaughlin (acting) Ron Velarde, Steve Yamashita, Tom Speeze, John Geerdes Kurt Mill, Dan Prenzlow MAMMALS RESEARCH STAFF Chad Bishop, Mammals Research Leader Mat Alldredge, Wildlife Researcher Chuck Anderson, Wildlife Researcher Eric Bergman, Wildlife Researcher Jake Ivan, Wildlife Researcher Heather Johnson, Wildlife Researcher Ken Logan, Wildlife Researcher Kay Knudsen, Librarian Margie Michaels, Program Assistant 3 �Colorado Division of Parks and Wildlife July 1, 2011 − June 30, 2012 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS LYNX / WOLVERINE CONSERVATION WP 0638 ASSESSING THE EFFECACY OF MONITORING WOLVERINE ON A REGIONAL SCALE USING OCCUPANCY AND ABUNDANCE ESTIMATION by J. Ivan……………………………………………………………...…6 WP 0670 MONITORING CANADA LYNX IN COLORADO USING OCCUPANCY ESTIMATION: INITIAL IMPLEMENTATION IN THE CORE LYNX RESEARCH AREA by J. Ivan……………………………….………………………...26 WP 0670 PREDICTED LYNX HABITAT IN COLORADO by J. Ivan………………………….36 WP 0670 DENSITY, DEMOGRAPHY, AND SEASONAL MOVEMENTS OF SNOWSHOE HARES IN CENTRAL COLORADO by J.Ivan………………………………………..40 DEER / ELK CONSERVATION WP 3001 POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson……………………………………………………..48 WP 3001 EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER by E. Bergman.................................................................................................................68 WP 3001 DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS by C. Bishop….………………………………....80 WP 3001 ASSESSMENT OF SURVIVAL AND OPTIMAL HARVEST STATEGIES OF ADULT MALE MULE DEER IN MIDDLE PARK, COLORADO by E. Bergman…………………………………………………………………………..94 WP 3002 EVALUATING SOLUTIONS TO REDUCE ELK AND MULE DEER DAMAGE ON AGRICULTURAL RESOURCES by H. Johnson………………………………..100 PREDATORY MAMMALS CONSERVATION WP 3003 BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS by H. Johnson………………………………………………………………114 WP 3003 PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU by K. Logan………………………………………….134 4 �WP 3003 COUGAR DEMOGRAPHICS AND HUMAN INTERACTIONS ALONG THE URBAN-EXURBAN FRONT-RANGE OF COLORADO by M. Alldredge………..196 SUPPORT SERVICES WP 7210 LIBRARY SERVICES by K. Knudsen……..……………………………...………….322 5 �Colorado Division of Parks and Wildlife July 2011–June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0638 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Wolverine Conservation Assessing the efficacy of monitoring wolverine on a regional scale using occupancy and abundance estimation Period Covered: July 1, 2011 – June 30, 2012 Author: J. S. Ivan* Personnel: M. Schwartz, USFS Rocky Mountain Research Station; M. Ellis, University of Montana *(J. S. Ivan was the sole Colorado Parks and Wildlife contributor for this work and is thus listed as “author.” However, the draft manuscript included here was a collaborative effort and all personnel listed are co-authors on the manuscript. M. Ellis is the first author.) All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Conservation biologists and resource managers are often faced with the task of designing monitoring programs for species that are rare, diffuse, or patchily distributed across large landscapes. These efforts are frequently very expensive and seldom can be conducted by one entity. It is essential that a power analysis is undertaken to ensure stated goals are feasible. We developed a spatial-based simulation, which accounts for natural history, habitat use, and sampling scheme, to investigate power for monitoring wolverines in two areas of the U.S. Rocky Mountains. The first area is a well-established metapopulation of wolverine in the northern Rocky Mountain states of Montana, Idaho, and Wyoming, where the current population is approximately 350 individuals and there are concerns of population decline. Based on current population size estimates and detection probabilities in the northern U.S. Rockies, most sampling schemes are likely to only detect large declines in population sizes (i.e. 50% decline over 10 years). In general, increasing the number of grids sampled or the per visit detection probability had a much greater effect on power than increasing the number of visits per year. For small populations, we found very low power to detect declines. The second analysis was a forecast of the effort required to monitor an increasing population in the southern U.S. Rockies, given recolonization or reintroduction. Occupancy-based methods can only produce enough power to detect population trends if populations are increasing dramatically (i.e. doubling or tripling in 10 years), regardless of the sampling effort. In sum, our approach provides a spatially based framework to evaluate monitoring protocols and objectives by explicitly incorporating the link between changes in population size and estimated occupancy, all while accounting for natural history of the species in question. These analyses were specific to wolverines, but our approach could easily be adapted to other species. 6 �WILDLIFE RESEARCH REPORT ASSESSING THE EFFICACY OF MONITORING WOLVERINE ON A REGIONAL SCALE USING OCCUPANCY AND ABUNDANCE ESTIMATION. JACOB S. IVAN P. N. OBJECTIVE Assess power for detecting trends in wolverine population growth using occupancy. SEGMENT OBJECTIVES 1. Build code to simulate realistic distribution and space use of wolverine on the landscape. 2. Build code to realistically simulate sampling the wolverine population using an occupancy framework. 3. Build code to analyze data “collected” via occupancy surveys. 4. Summarize results of 1000s of iterations of randomly generated wolverine distributions and subsequent occupancy surveys; plot power to detect trends against various scenarios intended to reflect the range of conditions expected for both the sampling and process portions of the simulation. 5. Prepare manuscript for publication INTRODUCTION Wildlife populations worldwide have faced major population reductions in abundance and geographic range due to both natural and anthropogenic causes (Butchart et al. 2010, Hoffmann et al. 2010, Rands et al. 2010, Inman et al. 2011). Currently, many populations are facing multiple threats including habitat fragmentation and loss, climate change, direct and indirect exploitation, disease, invasive species, and the interaction among these threats (Primack 2006, Laurance et al. 2008, Povilitis and Suckling 2010). Responding to these major threats to wildlife and fish populations worldwide, many countries have adopted legislations aimed at affording protection to species of conservation concern (Hutchins et al. In Press, Waples et al. In Review). Two of the more powerful pieces of legislation are Canada’s Species at Risk Act (SARA) and the United States’ Endangered Species Act (ESA). These acts not only identify species at risk and aim to protect them from additional harm, but also stipulate and provide mechanisms for recovery. For example, in the United States approximately half of the annual budget spent on threatened and endangered species is designated for recovery (GAO 2005, Male and Bean 2005). However, determining when a species of concern is declining or subsequently recovering requires information about trend. The majority of studies that have examined trends in fish and wildlife were historically based in assessments of population abundance (Dennis et al. 1991, Bart et al. 2007, Foster et al. 2009, Broms et al. 2010). While estimates of abundance are important, other measures such as changes in genetic or demographic parameters or changes in geographic range size have been used to infer trend (Gaston 1991, Schwartz et al. 2007, Marucco et al. 2009, Broms et al. 2010). Recently, more attention has been placed on estimating changes in occupancy of a species geographic range (Joseph et al. 2006, MacKenzie et al. 2006). Occupancy estimation generally requires multiple surveys to a set of sample units, noting on each survey whether the species of interest was detected or not. Subsequently, these repeat-visit data are used to estimate the probability of detecting the species of interest if it was present, and then adjusting the raw presence-absence data in light of this probability to estimate the proportion of area occupied (MacKenzie 7 �et al. 2006). If occupancy estimation is conducted over multiple time intervals, trend in occupancy is obtained (Field et al. 2005, MacKenzie 2005, Marsh and Trenham 2008). Before launching an occupancy study, power analysis should be conducted to allocate monitoring effort efficiently (Field et al. 2005, MacKenzie 2005, Rhodes et al. 2006). Most studies base power analyses for occupancy estimation on detecting declines in occupancy over time; however, these simulations rarely consider spatial dynamics. Also, monitoring trends in occupancy is often used as a surrogate for trends in abundance, but this link is rarely evaluated (e.g. Field et al. 2005, Finley et al. 2005, Otto and Roloff 2011). Rhodes et al. (2006) and Rhodes and Jonzén (2011) modeled spatial and temporal correlations in population dynamics to account for spatial structure in populations and provide allocation recommendations in occupancy studies. They find, when spatial correlation is low and temporal correlation is high, it is most efficient to sample many sites infrequently. In the opposite situation, when spatial correlation among population dynamics is high and temporal correlation is low, they recommend sampling few sites often. Finally, when there is a decoupling of abundance and space, they suggest maximizing spatial replication (Rhodes and Jonzén 2011). Furthermore, if interest is in detecting declines in occupancy, they suggest sampling high quality habitats, whereas if the objective is to detect an increase, sampling intermediate-quality habitats is the best strategy. We extended their work by building a species-specific model of a population changing over time. We then sampled from this population using a multi-season occupancy framework to determine power to detect population trends under various scenarios. This approach allows us to optimally allocate scarce monitoring resources for designing an occupancy-based monitoring effort. Our model was designed to optimize sampling allocation for a large-scale wolverine monitoring effort. Wolverines are a Holarctic carnivore species known for their large home ranges, low densities, and occasional long distance movements (Lofroth and Krebs 2007, Squires et al. 2007, Inman et al. 2012). The species is currently under consideration for listing under the ESA (USFWS 2010) largely due to the fact that their numbers were greatly reduced (possibly eliminated) in the contiguous United States in the early 20th century. Wolverine populations have recolonized Idaho, Montana, Washington, and Wyoming and single male wolverines have recently dispersed to California and Colorado (Aubry et al. 2007, Moriarty et al. 2009). Yet, they are still absent from significant portions of their historical range and their current abundance in the contiguous United States is still likely to be at most 500 individuals. Recent research by Aubry et al. (2007) and Copeland et al. (2011) has shown that the historical distribution of wolverine was consistent with the distribution of persistent spring snow. Copeland et al. (2011) characterized persistent spring snow cover in the entire northern hemisphere based on a 21-day composite (24 April–15 May) of images from 2000-2006 at a 0.5km2 resolution using moderate resolution imaging spectroradiometer (MODIS) satellite images (Hall et al. 2006). They found that >99% of wolverine den sites and >89% year-round telemetry locations were located within areas that were classified as having persistent spring snow in at least one of the seven years for which data were available. Schwartz et al. (2009) demonstrated that wolverine gene flow was facilitated by areas with persistent spring snow compared to areas that were snow free. In this paper we use habitat (i.e., persistent spring snow), movement, and home range data to build a spatially based model for assessing the power for monitoring wolverine in their current range and in areas where they may eventually recolonize either naturally or through reintroduction. METHODS Study area There are two study areas for this project. The primary study area consists of the U.S. Rocky Mountains in northern and central Idaho, western Montana, and northwest Wyoming (“Northern 8 �Rockies”, Figure 1). The area is composed of individual mountain ranges each characterized by high alpine areas (maximum elevation 3900 m) and surrounded by wide areas of semiarid grasslands and irrigated agriculture (elevation ~1400 m). This area is known to be occupied by wolverines, with current population estimates ranging from 200-500 individuals (USFWS 2010). We removed from our analyses mountain ranges on the edge of this range, including the Wallowa Mountains of Eastern Oregon, the Bighorn Mountains of Eastern Montana and Wyoming, and the Bear River Range on the Idaho/Utah border; all three of which have no historical records of wolverines (Aubry et al. 2007) and do not contain continuous patches of persistent spring snow cover (Schwartz et al. 2009, Copeland et al. 2011). We allowed areas ‘used’ by simulated wolverines to extend up to 50 km into Alberta and British Columbia, Canada to account for continuous wolverine populations in the Northern Rockies, but excluded these areas from occupancy analyses. The second study area is the mountainous region of the Southern U.S. Rockies (“Southern Rockies”). This area is characterized by high, steep mountains (max elevation 4,400 m). As a result, there are strong gradients in physical attributes of the landscape, which lead to heavily dissected vegetation types. In the Southern Rockies, alpine and subalpine zones can be relatively narrow and give way to montane forests, montane shrublands, and semiarid grassland or sagebrush communities over relatively short distances. This area does not currently have a population of wolverines, although wolverines are thought to have occurred there historically (Aubry et al. 2007), and there seems to be adequate habitat, including persistent spring snow (Aubry et al. 2007, McKelvey et al. 2011). Areas of persistent spring snow are more patchily distributed in the Southern Rockies landscape, and separated from areas of persistent spring snow in the Northern U.S. Rockies by >200km. Most mountain ranges in this study area occur in Colorado, but we included the Medicine Bow and Sierra Madre ranges in southern Wyoming, as well as the southern San Juan Mountains in northern New Mexico. Individual Utilization Distributions We randomly selected points within areas of persistent spring snow (using Copeland et al. 2010) for the center of individual home ranges for adult female, adult male, and transient male wolverines. Among these three groups, locations were chosen independently to allow for overlapping home ranges (Copeland 1996, Inman et al. 2011); however, within each group, selection of home range centers was constrained to reflect territoriality. The buffer distances required between home ranges centers were at least 16 km for adult females, reflecting a 225 km2 home range, and at least 25.2 km for adult and transient males, reflecting 500 km2 home ranges (Banci 1994, Krebs et al. 2007, Schwartz et al. 2009). We also required that all home range centers were located in snow patches large enough to support at least one resident female wolverine (Krebs et al. 2007). Within each group (adult females, adult/resident males, adult/transient males), locations for home range centers were randomly selected in an iterative fashion until no additional individuals could be placed in the landscape or until the desired number of individuals was met. Once home range centers were established for a given simulated landscape, we assigned a bivariate normal utilization distribution for each individual. For resident females, we assumed that an individual spends 90% of her time within their 225 km2 home range (radius = 8.5 km). For resident males, we assumed individuals spend 90% of their time within their 12.6 km home range radius, but we allowed for larger sizes and greater overlap among transient male home ranges by assuming individuals only spend 70% of their time in the original 500 km2 home range. Each of these distributions produced a surface with decreasing probability of use with increasing distance from the home range center. To make these bivariate normal utilization distributions more realistic, we overlaid them on the persistent spring snow layer and multiplied the layers together. In the persistent spring snow layer, areas of non-snow were weighted as having 1/20 the probability of use compared to snow areas, based on resistance values found for models of genetic least cost paths (Schwartz et al. 2009). We standardized the product of the 9 �two layers to transform it back into a probability density. Thus, each individual utilization distribution takes a unique shape based on availability of snow. In this approach, it is possible for individuals to make short term, long distance movements during a given study period. The tails of the bivariate normal utilization distribution allow for a very small, but non-zero, probability of reaching any point on the landscape. In preliminary analyses, we tested for the effect of excluding these long distance movement events by cutting off the tails of the bivariate normal, such that the probability of an individual being more than 1-2 standard deviations away from its home range center was set to 0, compared to a situation with no limit on movement. Although allowing short-term, long-distance movements did affect the estimated occupancy of the landscape, the effect on power was minor. Occasional long-distance movements are possible in wolverine ecology, especially by males and transients (Moriarty et al. 2009). For territorial males and females, we would expect these movements to be less likely over the course of the relatively short survey period. Thus we based our power analyses on a ‘mixed’ scenario in which long distance movements were possible for transient males (i.e. no limit), resident males were allowed some larger movement events (limited to within 2 s.d. of home range center), and movements of females, which may have dens, were limited 1 sd from their home range center. Following the rules state above, our program, SPACE (Spatially-based Power Analyses for Conservation and Ecology), created 1000 surfaces for N=500 or N=200 individuals on the Northern Rockies landscape, reflecting high and low estimates of wolverine population size in the study area. We then simulated 10%, 20%, or 50% declines in our simulated populations over a decade (λ = 0.989, 0.977, 0.933) by randomly removing an appropriate number of individuals at each time step. We also simulated scenarios (nsim = 1000) for a hypothetical reintroduced or recolonizing population in the Southern Rockies. These populations were started with N=30 individuals then allowed to increase by 50%, 100%, or 200% over a decade (λ = 1.041, 1.072, 1.0116). We initiated all populations with a 2:1:2 ratio of females:resident males:transient males. Sampling To estimate occupancy, we sampled from our simulated landscapes during each time step or “year” of the simulation. We divided the study area into 225km2 sample units (cells), matching home range sizes for resident females, a strategy widely used for monitoring carnivores (e.g., Zielinski and Stauffer 1996). We excluded cells that did not overlap the persistent snow layer by ≥50%. This resulted in 388 cells for the main Northern Rockies study region, and 128 cells for the Southern Rockies. For each cell, the probability of at least one wolverine being present (hereafter, ‘probability of presence’ was Eqn 3): N   Ρ(# wolverines ≥ 1) j = 1 − Ρ( wolverines absent ) j = 1 − ∏ 1 − ∫∫ f i ( x, y ) dx dy    ( x , y )∈Ω i =1 j   where N is the number of wolverines in the simulated study area, fi(x,y) is the probability density function (i.e., utilization distribution) describing the use surface for the ith wolverine, and Ωj represents the area included in the jth grid. We approximated integral values by summing pixel values in the raster, assuming equal pixel areas. To construct a simulated encounter history (i.e., the data necessary for occupancy estimation) for cell j in year k, we assigned a 1 (present) or 0 (absent) for each visit by comparing a random draw from Uniform (0,1) with the probability of presence for that cell (draws less than the probability of presence resulted in a detection, and a 1 in the encounter history for that visit). Thus, a cell with simulated encounter history “010” indicates that 3 visits were made to the cell in a given year, and wolverines were 10 �detected on the second visit only. After initial construction, we used progressively reduced versions of the encounter histories to explore the effect of changes in parameters associated with sampling on power to detect population changes. For example, we omitted data from even numbered years (i.e., inserted “.” for each “0” or “1” of the omitted years) to examine the effect of sampling every other year; we tested the effects of smaller sample sizes by reducing the number of cells or visits included in the encounter histories; and we reduced the number of detections to simulate imperfect detection (See Table 1). To create encounter histories with lower detection probability, we randomly removed an appropriate proportion of 1s from each encounter history. Thus, to go from a detection probability of 1.0 to 0.8, we retained 0.8/1.0 = 80% of the 1s; for each 1 (wolverine detected) in a given encounter history, we conducted a random draw from uniform (0,1) and compared this draw against 0.8. We retained the 1 if the draw was ≤0.8, and changed it to a 0 (wolverine not detected) otherwise. Similarly, to go from encounter histories reflecting detection probability = 0.8 to detection probability = 0.2, we evaluated each 1 in a given history, retaining it if the random draw was ≤0.25 (0.2/0.8), changing it to 0 otherwise. We used these encounter histories to obtain annual estimates of occupancy and detection probability for each simulated landscape and parameter set. Note that the subject of our simulations is a mobile carnivore capable of moving freely between sample cells, and our simulation setup reflected this reality. Therefore, interpretation of estimated occupancy parameters was different than the usual context in which the status (occupied or not) of a given cell is assumed static over the course of a survey. Specifically, the estimate of occupancy (Ψ) generated under this context is the probability that any given cell is used rather than occupied, and any reference to Ψ or “occupancy” from here forward refers to probability of use. Furthermore, the estimate of detection probability generated in this context is actually the product of true detection probability (i.e., probability of detection given that the species of interest is present; this quantity is specified directly for any given simulation) and a landscape-wide probability that an individual is present and available for detection (i.e., probability of presence; see above). We refer to the detection probability estimated by the model as pest, and the actual detection probability specified for the simulations as psim, such that pest = psim × probability of presence. We used the R (R Development Core Team 2011) package RMark to input the encounter histories and construct models to fit in Program MARK (White and Burnham 1999). Specifically, we employed the ‘Robust Design Occupancy‘ data type (MacKenzie et al. 2006) in which colonization (γ) could vary through time but was constrained to be the complement of extinction (ε; i.e., changes in occupancy were considered random rather than Markovian or static) and detection probability (p) varied with time. This model structure is appropriate because: 1) we were interested primarily in the occupancy estimates themselves; we had no interest in modeling occupancy dynamics (colonization, extinction) explicitly, 2) the simulation specifications allowed “movement” in and out of adjacent cells, thus mimicking random changes in occupancy, and 3) “movement” between adjacent cells forced pest to be a function of probability of presence, which changed through time depending on the simulated landscape and birth/death of individuals. Thus, pest should have varied through time as well. We extracted the 10 occupancy estimates and the variance-covariance matrix for these estimates from each simulation, then used the variance components procedure in RMark to fit a linear random effects trend model to the estimates. A trend was ‘detected’ if the 95% confidence interval of the trend parameter (on the logit scale) from the random effects model excluded zero and was in the correct direction (e.g., <0 for declining trends; Tallmon et al. 2010). Thus, we computed the statistical power produced by a sampling scenario, i.e. the probability that we detect a significant trend given that there is a trend in the underlying data, as the percentage of simulations in which a trend was detected. For datasets in which we simulated sampling every other year, we fit models in which we fixed γ =γ , γ =γ4, etc. such that the product of these parameters were estimated, and we bridged years in which no data were collected to produce valid estimates of occupancy for those years where data were collected. 1 2 3 11 �In these scenarios, only 5 occupancy estimates were generated, and we fit random effects models to those 5 estimates. We repeated these analyses for each combination of population growth or decline, simulated detection probability (psim), number of visits, cell size, number of cells sampled, and annual or alternating year sampling schemes that were applied to the 1000 simulated landscapes of N = 30, 200, or 500 (Table 1). Where applicable, all sampling was cumulative to facilitate the most meaningful contrasts between levels of a parameter; for example, a sample of n = 50 cells would include the same cells as an n = 25 sample with 25 additional cells included. Similarly, an encounter history with 4 visits would include the same string of 0s and 1s as a 3-visit history, with one additional visit included. Our simulations were designed to be generalizations in that we do not attempt to define when a sampling season might begin, what the sampling mechanism was, or what constitutes a visit. Thus, these simulations could represent flying over selected cells in the study area to search for tracks in the snow, in which case a ‘visit’ is a single flight (Gardner et al. 2010), or they could reflect the use of hair snag devices in which a ‘visit’ is 1 month of continuous sampling (Magoun et al. 2011). We bracketed the sampling parameters (cell size, detection probability, visits) based on previous efforts described in the literature (Magoun et al. 2007, Gardner et al. 2010, Magoun et al. 2011). RESULTS Effects of home range parameters Due to the spacing rules among individuals that we used to reflect wolverine territoriality, the Northern Rockies landscape becomes saturated with approximately 850 individuals (420 ± 6 females, 219 ± 4 resident males, 219 ± 4 transient males; mean ± s.d. across 100 simulated landscapes). For N=800, the median probability of at least one wolverine per cell across the landscape was 0.47. This value reflects the availability of individuals on the landscape, yielding on average 280.4 cells in which wolverine were available for detection per sampling occasion across the 388 cells in the grid. As the population size decreased, the average probability of at least one wolverine per cell fell to 0.74 (212.4 detections per occasion) for N=500 and 0.05 (18.9 detections per occasion) for N=30 across simulations. With perfect detection associated with sampling (psim = 1), these cell-based probabilities for use translate to an estimated occupancy (Ψ) of 0.99±0.01 for the entire landscape for populations with N = 500 individuals and 0.06±0.01 for N = 30. Effects of population size and trend We investigated the upper limits of power with occupancy estimation by examining the ability to detect trends when the simulated detection probability was perfect (psim = 1) and with a large number of visits (5) to each unit. We focused these analyses on the U.S. Northern Rockies landscape and a quickly declining population (λ = 0.933). Even with perfect detection and intense sampling, detecting a large decline (50% over 10 years) in a large starting population (N = 500) with adequate power (>80% chance of detecting the trend) required a sample of 50 out of 388 cells (Figure 2). As the population size decreased, the amount of sampling needed to detect a 50% decline even under this ‘best case’ scenario with perfect detection increased dramatically. For example, when N=200, achieving 80% power required sampling approximately 75 to 150 cells. Detecting trends in small populations (N=30) was difficult; even if we included the entire grid (388 cells) in the sample and assumed perfect detection, we had less than 70% power to detect a trend. Regardless of the starting sample size, power to detect trends was lower for increasing populations compared to the decreasing scenarios described above. For example, to detect a 50% increase (λ = 1.041) with >80% confidence, the amount of the total sampling grid that would need to be included in the sample increased to ~25% of the grid (ncells≈60) for N=500 or ~ 50% (ncells≈125) for 12 �N=200. For N=30, sampling the entire grid, assuming perfect detection probability, and with an intense sampling effort (5 visits), we were able to detect a 50% increase in <40% of the simulations. With current population sizes (N=500) in the Northern Rockies, the ability to detect declines fell dramatically as the strength of the decline decreased (Figure 3). We found a reasonable chance ( ≥80%) of detecting a 50% decline in population size over a 10-year period, depending on the combination of sample size and detection probability. However, for a 10% decline in population size over the 10 year period, no amount of sampling could yield enough power to detect the trend. Similarly, even with a large sample size and high detection probability, a 20% decline was detected in <60% of the simulations (Figure 3). With either population increases or declines, sampling every other year substantially increased the number of cells and visits that would need to be sampled. Trade-offs in sampling methodology After the strength of the population decline or increase, the parameter that most influences power to detect change was the simulation detection probability (psim). In nearly all scenarios relatively large gains in power were realized when psim increased from 0.2 to 0.8. For instance, a monitoring scheme that called for 2 visits to each of 100 sample units would have ~25% chance of detecting a 50% decline over 10 years when psim = 0.2. Power for detecting that same decline under the same sampling regime increased to 80% when psim = 0.8 (Figure 3, upper left panel). By comparison, an increase in sample size from ncells = 50 to ncells = 300 resulted in only a doubling in power (25% to ~50%). In fact, when psim = 0.2, 80% power cannot be achieved even if the entire grid is sampled. Similar gains in power relative to simulation detection probability and sample were realized in other scenarios we simulated. The exceptions to this result were when the goal was to detect a 10% decline over 10 years or to detect a 20% decline when sampling was only conducted every other year. Both scenarios yield very low power and negligible improvement with increased psim or sample size (Figure 3, middle panels). The number of visits to each sample unit influenced power as well, although generally to a lesser degree than magnitude of population change, simulation detection probability, and sample size. Even with perfect simulation detection probability (psim = 1), the power to detect a trend increased with the number of visits at each grid cell due to the number of opportunities for an individual to be present. When simulation detection probability is high but imperfect (i.e., psim = 0.8), some gain in power could be realized by visiting each sampled cell 3 times vs. visiting them only twice (Figure 3, separation between the two lightest dotted lines). However, the gain realized for making 4 visits rather than 3 is small, and there is no appreciable difference in power for 4, 5, 6, or 7 visits under the scenarios we simulated. When simulated detection probability was low (i.e., psim = 0.2), potentially greater gains in power could be realized by making more visits, but it depends on the scenario (Figure 3, in some cases there is a moderate amount of separation in the solid lines, in other cases there is not). Note that at low detection probabilities (psim = 0.2), it is often inadvisable to make more visits to each sampled cell because such an approach actually decreases power (See discussion). Effect of Cell Size In order to achieve the threshold of 80% power to detect a 50% population decline, changing cell sizes in the grid had implications for both the number of cells and the total area that would need to be sampled. (Figure 5). Grids of 100km2 and 225km2 cells yielded similar power in terms of the percent of the grid that would need to be included in the sample, although the smaller cell size requires sampling more cells (i.e., the total grids were comprised of 887 100km2 cells versus 388 225km2 cells). Assuming 3 visits and high detection, getting 80% power for detecting a 50% decline required 120 cells (12,000km2) from the small grid versus 70 cells (15,750km2) for the medium sized grid. As the size of the grid increased, the power to detect trends in occupancy decreased. The 1000km2 grid produced very low power to detect population trends. In this case, the grid in the Northern Rockies comprised only 76 cells. Including every cell in the sample, with seven visits and high detection probability, we detected a 50% 13 �population decline in <20% of the runs. The phenomenon in which power is actually reduced with a high number of visits occurs for the 225km2 cell size at low psim, and for the 500km2 and 1000km2 size at high psim. Power to detect increases in small populations For small populations (N=30), power for detecting population trends was limited except for situations with large population increases and high detection probability (Figure 4). For the purposes of comparison, there was greater power for detecting trends in the Southern Rockies landscape than in the Northern Rockies, although the total sampling area in the Southern Rockies landscape is approximately only a third of the Northern Rockies. For both landscapes, a doubling of the population over ten years (λ = 1.072) could be detected with >80% power in scenarios where a large proportion of the landscape was included with relatively high capture probability. If simulation detection probability is low, then adequate power can only be achieved via sampling a large portion of the available landscape, and making a large number (≥5) of visits to each sampled cell. DISCUSSION Monitoring population trends over time is one of the most common goals for management of endangered species. Using a spatially explicit simulation for wolverine in the U.S. Rocky Mountains, we were able to test the ability of occupancy-based approaches to detect trends in population size under a range of monitoring scenarios. Even for large changes in population size (e.g. 50% declines over 10 years), we found that detecting population trends required large-scale, intensive sampling. In many scenarios, no amount of sampling could produce sufficient power to achieve monitoring goals. Our results highlight the importance of analyzing the statistical power of monitoring schemes and using approaches that incorporate the effect of sampling and power over the course of multiple steps in a monitoring protocol. In the case of the wolverine, work has commenced to evaluate the effectiveness of various approaches for detecting presence. These range from using fix-winged aircraft to find tracks in 100-km2 (Magoun et al. 2007) or 1000-km2 (Gardner et al. 2010) sampling cells, to using cameras at bait stations (Mulders et al. 2007, Magoun et al. 2011), to the use of non-invasive genetic sampling (Ulizio et al. 2006, Schwartz and Monfort 2008, Magoun et al. 2011). These efforts produce varying detection probabilities from 0.2 to 0.8 as bracketed in our simulations. However, matching estimates from field studies to our results, is not straightforward. It is important to note that detection probability estimated from pilot analysesis not the same as the psim input in our analyses. Due to the ‘mobile animal’ phenomenon, animals are capable of moving freely between sample cells and therefore can be detected in multiple cells during one sampling occasion. As a result, occupancy models cannot separate the effects of true detection probability (psim) and probability of presence (See Methods). Consequently, pest returned from pilot studies will be smaller than the detection probabilities used in our simulations (psim). For example, if pilot work indicates that pest = 0.2, power can be assumed to be slightly better than the curves shown for psim = 0.2 in our figures. The exact correspondence between pest and psim is dependent on cell size, population size, and home range size of the species in question. Thus, no rule of thumb holds for converting between the two. However, matching pest derived from pilot work to curves for psim can still be useful as it will result in conservative estimates of power, which would be a prudent way to design monitoring schemes. In the case of wolverines, pilot work specific to occupancy monitoring in the Northern Rockies has been carried out using camera stations (B. Inman, Wildlife Conservation Society, unpublished data) and hair snags (J. Waller, Glacier National Park, unpublished data) in 100-km2 sample units. Initial results from this work suggest pest is approximately 0.25 – 0.3, which in our simulations corresponded to 14 �psim ≈0.8 (i.e., pest = psim × probability of presence, where our mean probability of presence was 0.33; thus 0.25/0.33 ≈ 0.8). It’s important to note that the mean probability of presence depends on assumptions about the number of animals, the landscape, and home range configurations. Based on this estimate, and assuming 3-4 visits to each sample unit (sampling occurred during 3-4 months over winter for each pilot study), our research suggests that roughly 100-150 100-km2 cells would need to be sampled per year to attain an 80% probability of detecting a 50% decline in the Northern Rockies population (Figure 5). Thus, intensive sampling over a small area is unlikely to be a viable solution for detecting population trends. To accomplish anything meaningful, monitoring will require well-coordinated surveys across multiple entities and jurisdictions. Anything less than a large-scale, coordinated effort will likely be of limited or no value. The spatially explicit nature of our approach is especially important in linking changes in occupancy to population trends. Our results demonstrate that the underlying landscape can influence power to detect population changes. Specifically, in the comparison of power for populations with N=30 in the Northern versus Southern Rockies, power to detect trends in occupancy was similar in terms of percent of the total study area included in the sample, but very different in terms of the absolute area that needs to be sampled. For example, to detect a 3x increase of the N=30 populations with a 225km2 grid and >80% power required sampling ~20% of either landscape, which translates to sampling 16000km2 in the northern landscape versus 6000km2 in the south. Note, however, that the scenarios in this comparison, populations of N=30 in the Northern versus Southern U.S. Rockies, are intended to illustrate the effect of underlying landscape for a fixed population size. In reality, changing the size of a study area would generally also change the size of the population included, which we found to substantially affect power to detect trends. Previous recommendations for selecting cell sizes have been ad hoc. In some cases, our results indicate a relatively straightforward relationship between cell size and the number of cells needed or the total area sampled to achieve a given power threshold. Between a 100km2 grid and a 225km2 grid, with high detection probability, 80% power can be obtained either by sampling many small cells or fewer of the larger cells. However, by the time cell sizes reach 1000km2 for wolverine, the home ranges for multiple individuals are included in the cell, such that occupancy-based methods alone will only pick up changes once a much larger population decline has occurred. The point at which this switch occurs will likely depend on an interaction of the population size, landscape, home range sizes, and cell size. We also discovered a counterintuitive anomaly when computing power under scenarios in which cell size is equal to home range size, as is often advised for occupancy surveys of mobile carnivores. Specifically, we noted that when detection probability is low, power generally increases with increasing visits to each sample unit, but there is a point at which conducting more visits actually decreases power. We offer the following explanation for this phenomenon: When the cell size is equal to the home range size, the interplay between psim (i.e., 0.2) and availability is such that the pest is fairly low and makes a substantial upward adjustment on the count of cells (c) in which wolverines were actually detected. As we make more visits we detect wolverine use in cells that are seldom used, so c increases, but pest from the model does not (only the precision on pest improves). After about 6 or 7 visits c increases enough that the occupancy estimates resulting from upward adjustments on c approach 1.0. If estimates for all years are at or near 1.0, then there is no trend and we have no power to detect declines. This does not occur when cell sizes are small, because c will also be small, and any upward adjustments will not approach 1.0. A similar phenomenon occurs if cells are large and psim is high. In that case, most cells are used, and c will be large, especially with a large number of visits. Thus, even a small upward adjustment on c pushes the estimates to close to 1.0, which again makes detecting trends difficult. Thus, if maximizing power is a goal, increasing visits beyond a certain threshold may not be helpful depending on cell size, availability of animals, and the probability of detecting them given their presence. 15 �Our simulations currently do not include cost functions, so trade-offs between cell size, number of cells to sample, number of visits at each cell, and detection probability have been conducted absent an important real-world consideration. For instance, in a given situation, it may be easy to complete more visits to a site (e.g., leave camera sets out 1 more month), but extremely costly to improve capture probability (e.g, purchase an entire set of new cameras with improved functionality). Therefore, managers may opt to make more visits to improve power even though intensifying effort (visits) by a given percent may be inferior to improving detection probability by a similar percentage. Future simulation work should include cost as a factor in weighing the importance of the design factors we considered here. Most studies base power analyses for occupancy estimation solely on detecting various simulated declines in occupancy. Here, we employed a more mechanistic, spatially-based approach in which we simulated animals on a landscape, accounted for their natural history (territoriality, difference between sexes), tied their space use to key habitat features (persistent spring snow), and forced declines or increases in the real parameter of interest (abundance) to determine whether occupancy estimation could detect those changes. Thus, our approach is a direct test of the link between occupancy and abundance, providing a more meaningful examination of whether real-world changes of interest in population size can actually be detected using occupancy estimation. It also sets the stage for direct comparisons between occupancy and estimation of other metrics (e.g., abundance) that could potentially be used to monitor populations. That is, we have established the machinery necessary to simulate ‘truth’ (the configuration of animals on the landscape and changes in that configuration and/or number) and can then sample from that true population in various ways to simulate data gathering under different monitoring approaches. While results from this analysis can be used directly to guide the monitoring of wolverine or similar species, the largest contribution is the framework which can be used for making decisions about the design of a large scale monitoring effort provided information on movement and habitat use is available. Our goals were to establish this framework to encourage cost-effective decisions in designing monitoring programs and to inspire well-coordinated surveys across multiple entities and jurisdictions. Without such coordination our analyses convincingly show that most efforts for species like wolverine will be wasted. ACKNOWLEDGMENTS We thank Paul Lukacs, Gary White, and Larissa Bailey for providing invaluable technical advice, and Jeff Laake for implementing the “random occupancy dynamics” model into RMark so it could be used in this analysis. We thank the RMRS and a PECASE award to MKS for providing the initial funding for this effort. LITERATURE CITED Aubry, K. B., K. S. McKelvey, and J. P. Copeland. 2007. Distribution and broadscale habitat relations of the wolverine in the contiguous United States. Journal of Wildlife Management 71:2147–2158. Banci, V. 1994. Wolverine. Pages 99–122 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, L. J. Lyone, andW. J. Zielinski, editors. The scientific basis for conserving forest carnivores in the western United States. U.S. Forest Service, General Technical Report, RM-254. Bart, J., S. Brown, B. Harrington, and R. I. G. Morrison. 2007. Survey trends of North American shorebirds: Population declines or shifting distributions? . Journal of Avian Biology 38:73–82. 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Variable Population size Population growth rates Limit on movement Simulated detection probability Number of cells sampled Number of visits Cell size Sampling Values tested N = 30, 200, 500 0.933, 1.041, 1.072, 1.116 N = 30 λ = 0.933, 1.041 N=200 0.933, 0.977, 0.989, 1.041 N=500 none; 1, 2 s.d. from home range center 0.2, 0.8 10 - 90% of grid 2-7 100, 225, 500, 1000 km2 Annual or alternating years (every other year) 20 �Figure 1. Map of study area. Distribution of persistent spring snow in the U.S. Rocky Mountains. Two separate landscapes were included in this study: one corresponding to fairly continuous habitat in the U.S. Northern Rockies, which is currently occupied by wolverines, and a second area in the Southern Rockies, where wolverines may recolonize or be reintroduced. 21 �Figure 2. Effect of population size. Effect of population size on power to detect trends in the Northern U.S. Rockies. Assumes perfect detection associated with sampling for a 50% decline (λ = 0.933) or a 50% increase (λ = 1.041) from initial population sizes of 30, 200, and 500 individuals in the Northern Rockies. Simulated populations were sampled using a grid of 225km2 cells overlaid on the landscape. 22 �Figure 3. Power for detecting trends in the U.S. Northern Rockies. Results from a power analysis for assessing the feasibility of using occupancy to monitor trend in the population of wolverines in the U.S. Northern Rockies, assuming N=500 individuals and a cells size of 225km2. Results are parsed by population growth rate (λ = 0.933, 0.977, 0.989, 1.041 corresponding to 50%, 20%, and 10% declines over 10 years or a 50% increase), sampling effort (whether sampling occurred annually or every other year), detection probability for sampling, number of visits per year, and number of grid cells sampled from a total of 388. Power is based on number of detected trends in 1,000 simulated populations. 23 �Figure 4. Comparison of N=30 populations in Northern and Southern Rockies. Power to detect population trends for populations of 30 wolverines in U.S. Northern Rockies compared to the same population size in the Southern Rockies landscape. Ability to detect a population decline depends on population growth rate (λ = 0.933, 1.041, 1.072, 1.116 corresponding to a 50% decline over 10 years or 50%, 2-fold, or 3-fold increases in population size over 10 years) and sampling effort (detection probability for sampling, number of visits per year, number of grid cells sampled from a total of 388 for the Northern Rockies or 128 for Colorado). Power is based on number of detected trends from 1,000 simulated populations. 24 �Figure 5. Effect of cell size on power. Effect of grid size on power to detect population trends in the wolverine population (N=500) in the Northern Rockies using occupancy. As grid size changes, the total number of grid cells on the landscape also changes from 887 for a 100km2 grid, 388 for a 225 km2 grid, to 76 for a 1000km2 grid. 25 �Colorado Division of Parks and Wildlife July 2011–June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Monitoring Canada Lynx in Colorado Using Occupancy Estimation: Initial Implementation in the Core Lynx Research Area Period Covered: July 1, 2011 – June 30, 2012 Author: J. S. Ivan Personnel: T. Shenk, G. Merrill, E. Newkirk All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 (Devineau et al. 2010). In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that a viable, selfsustaining population of Canada lynx had been established. The purpose of this project was to develop a scientifically rigorous statewide plan to monitor this newly established population. Occupancy estimation, the use of presence/absence data to estimate the proportion of sample units used by a species within a study area, is appropriate for such a program. To evaluate this approach and provide initial estimates of occupancy and detection probability for planning purposes, we conducted a pilot occupancy estimation project in the core reintroduction area in the San Juan Mountains of southwestern Colorado. Lynx habitat in the study area was divided into 75-km2 sample units (8.66 km x 8.66 km cells), and we stratified the units into those accessible for snow tracking and “inaccessible” units, which were sampled via remote cameras. We randomly sampled 30 units from each stratum. A summary of snow tracking results can be found in Ivan (2011). Of the 120 cameras we deployed in late fall to survey the 30 inaccessible units, 113 were still operational when retrieved in early summer; 6 had memory cards that reached capacity in either May or June; 1 was stolen. We obtained 151,191 photos (min = 90, max = 6,948 per camera) from this effort. We determined species for each photo and checked our work using multiple observers. Average agreement between observers was 96%. We estimated that approximately 25% of inaccessible cells were used by lynx. Detection probability was 0.43. These pilot data are currently being used to conduct simulations and power analyses to determine how many sample units will be required to detect population changes of interest in Colorado. 26 �WILDLIFE RESEARCH REPORT MONITORING CANADA LYNX IN COLORADO USING OCCUPANCY ESTIMATION: INITIAL IMPLEMENTATION IN THE CORE LYNX RESEARCH AREA JACOB S. IVAN P. N. OBJECTIVE Assess the use of occupancy estimation as a means of monitoring Canada lynx in Colorado using the Core Research Area in the San Juan Mountains as a test site. SEGMENT OBJECTIVES 1. Obtain initial estimates of occupancy and detection probability from units where remote cameras were the primary detection method. 2. Determine covariates and covariate structures that will be most useful for modeling occupancy and detection probability for camera surveys. 3. Combine these results with those obtained via previous work (snow tracking) to inform simulation work aimed at determining the number of sample units, and visits to each unit, required to detect changes of interest in the lynx population in Colorado. INTRODUCTION The Canada lynx (Lynx canadensis) occurs throughout the boreal forests of northern North America. While Canada and Alaska support healthy populations of the species, the lynx is currently listed as threatened under the Endangered Species Act (ESA) of 1973, as amended (16 U. S. C. 1531 et. seq.; U. S. Fish and Wildlife Service 2000) in the conterminous United States. Colorado represents the southern-most historical distribution of naturally occurring lynx, where the species occupied the higher elevation, montane forests in the state (U. S. Fish and Wildlife Service 2000). Lynx were extirpated or reduced to a few animals in Colorado, however, by the late 1970’s (U. S. Fish and Wildlife Service 2000), most likely due to multiple human-associated factors, including predator control efforts such as poisoning and trapping (Meaney 2002). Given the isolation of and distance from Colorado to the nearest northern populations of lynx, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) considered reintroduction as the best option to reestablish the species in the state. Therefore, a reintroduction effort was begun in 1997, and 218 lynx were released into Colorado from 1999 – 2006 (Devineau et al. 2010). The goal of the Colorado lynx reintroduction program was to establish a selfsustaining, viable population of lynx. Progress toward this goal was tracked via evaluation of critical criteria related to lynx survival, fidelity, and recruitment. Recently, CPW determined that the criteria had been met and a viable Canada lynx population currently exists in Colorado (Shenk and Kahn 2010). In order to track the distribution, stability, and persistence of this new lynx population, a minimally-invasive, long-term, statewide monitoring program is required. Abundance estimation is not feasible logistically and presents statistical difficulties even when field logistics can be managed. However, occupancy estimation, which uses detection/non-detection survey data to estimate the proportion of area occupied in a study area, is appropriate and feasible. In short, such a monitoring scheme requires multiple visits to a sample of survey units, and on each visit observers record whether a lynx was detected or not. Such information can be used to compute the probability of detecting a lynx given that it is present on a unit, which can in turn be used to estimate the proportion (ψ) of all survey units that are occupied. This metric can be tracked through time and is assumed to be closely tied to the 27 �size and extent of the lynx population. That is, if the proportion of survey units occupied by lynx declines through time, we assume this is due to a decline in the lynx population itself. Additionally, occupancy surveys can provide information relative to the distribution of lynx in the state. CPW initiated work to evaluate detection methods for occupancy estimation in 2009-2010 (Shenk 2009). Three methods of detecting lynx were tested in sample units where lynx were known to occur: snow tracking surveys, remote camera surveillance, and hair snags. The best method for detecting lynx was snow-tracking (daily detection probability = 0.70). Camera surveillance was far less efficient (daily detection probability = 0.085), and hair snares were ineffective (daily detection probability = 0.0; Ivan and Shenk 2010). Snow tracking, however, requires safe and extensive access to a survey unit via truck and/or snowmobile. Therefore, it cannot be used in roadless or wilderness areas, which may provide important lynx habitat. Here we build on this work to test occupancy estimation on a large scale using snow tracking where accessibility permitted it, and remote cameras in areas that were not accessible. METHODS Study Area The study area consisted of the 20,684 km2 “Lynx Core Research Area” in southwest Colorado. The Core Research Area is defined as areas >2591 m (>8500 ft) in elevation within the area bounded by New Mexico to the south, Taylor Mesa to the west, and Monarch Pass on the north and east (Figure 1). Topography in this area is characterized by wide plateaus, river valleys, and rugged mountains that reach elevations over 4200 m. Engelmann spruce (Picea engelmanii) - subalpine fir (Abies lasiocarpa) is the most widely distributed coniferous forest type at elevations most typically used by lynx (2591-3353 m, 8500-11,000 ft). Sampling The study area was divided into 75 km2 (8.66 km × 8.66 km) sample units, which reflects the mean annual home range size of reproductively active female lynx in Colorado (Shenk 2007) and Montana (Squires and Laurion 1999). Sample units that did not meet the following criteria were discarded as they did not represent potential lynx habitat that could be surveyed. ≥50 % of the cell contained conifer or montane/alpine habitat, as identified by the SWReGAP LandCover Dataset ( http://earth.gis.usu.edu/swgap/swregap_landcover_report.pdf) and 2. ≥ 50 % of the cell was located on public land (tribal, NGO, city, and county lands were considered private) as determined by COMaP (Theobald, D.M., G. Wilcox, S.E. Linn, N. Peterson, and M. Lineal. 2008. Colorado Ownership, Management, and Protection v7 database. Human Dimensions of Natural Resources and Natural Resource Ecology Lab, Colorado State University, Fort Collins, CO, www.nrel.colostate.edu/projects/comap). 1. Each of the remaining sample units was assigned a random number resulting from a spatially balanced sampling scheme (RRQRR; Theobald et al. 2007) and units were stratified by accessibility for snow tracking or camera surveys. The cells with the lowest 30 random numbers for each stratum were selected for sampling during the pilot work. A few cells in both strata were discarded once field work began due to access issues and these were replaced with cells 31, 32, etc. 28 �Snow tracking Surveys A detailed discussion of the methods and results associated with snow tracking surveys appears in Ivan (2011). We do not repeat that discussion here. Instead we focus on methods and results from the remote cameras, as those data were unavailable for the 2011 report. Camera Surveys Four remote camera sets (RECONYX RapidFireTM Professional PC85) were placed within each selected “inaccessible” sample unit during September and October. Placement of camera sets was not random within the unit; they were placed strategically on the landscape to maximize coverage of the sample unit and exploit microsites most likely to be used by lynx. Camera sets consisted of 1) a remote camera mounted to a tree using a Master Lock TM PythonTM cable lock, 2) a target tree at which the camera was pointed, generally about 5–10m away, 3) a compact disc strung from a nearby branch to visually attract lynx from a distance, 4) 2 feathers strung up in such a manner as to entice lynx to walk between the camera and the target tree, and 5) wool soaked in commercial scent lure that was packed into the bark of the target tree to hold lynx in front of the camera (Figure 2). Cameras were placed higher than usual, about head-height, and pointed slightly downward at the target tree so photos could be obtained during both snow-free periods and during periods of accumulating snow. Cameras were collected during June and July at which time the number of photos, percent of memory card used, percent battery life remaining, and condition of visual/scent lures was recorded. All photo attributes were imported into a database and species was assessed for each photo based on review by at least 2 observers. Analysis Assumptions inherent in occupancy estimation are 1) surveyed sites are either occupied or not occupied by the species of interest throughout the duration of the study; no sites change status during the survey period (i.e., the system is closed), 2) the probability of occupancy is constant across sites or can be modeled using covariates, 3) the probability of detection is constant across sites or can be modeled using site-specific covariates, and 4) species detection at a site is assumed to be independent of species detection at other sites (MacKenzie et al. 2006). Sampling mobile carnivores such as lynx presents a clear violation of the first assumption as individuals undoubtedly move into and out of sample units routinely. Fortunately, estimation can proceed, but the quantities estimated are different from traditional occupancy estimation. Rather than estimating the probability that a unit is occupied by lynx, we now estimate the probability that a sample unit is used by lynx. Also, the estimated detection parameter is not the probability of detection given a site is occupied, it is the product of a) the probability of detection given the species is available for detection, and b) the probability that the species was available. These subtleties aside, the procedure still gives a metric (use) that can be monitored through time to detect trends. We used the “Occupancy Estimation” data type in Program MARK to produce initial estimates of occupancy (i.e., use, ψ) and detection probability (p) for the camera stratum. Photos were grouped by month (November to March) for each sample unit such that encounter histories included 5 “visits.” Due to this grouping, there were no meaningful covariates for p. Individual cameras recorded moon phase and temperature for each photo, but aggregated over a month, these data were not helpful. Some camera sets used different scent lures than others, but aggregating by unit negates the utility of this information as well. We hypothesized that the proportion of spruce/fir and/or willow (Salix spp.) cover in each unit may affect the probability of use and/or probability of detection. Thus, we considered these covariates as potentially important for explaining variability in ψ and p. We held ψ constant and built an additive model for each detection covariate (one at a time) to determine the best structure for p. We then held p at the best structure as determined by AICc (Burnham and Anderson 2002) and fit additive models using the 29 �covariates for ψ. We also ran a model where both p and ψ were held constant as a baseline for comparison. We report estimates of p and ψ from the AICc top model. RESULTS Of the 120 cameras deployed during Fall 2010, 113 were still operational when retrieved in Summer 2011 after 234-309 days of deployment. Six had memory cards that reached capacity in either May or June, and one camera was stolen. On average, we obtained 1,260 photos per camera (min = 90, max = 6,948) for a total of 151,191 photos. At the time of retrieval, compact discs were still operational for 46% of camera sets, feathers were operational at 64% of sets, and remnants of scent lure were detected at 55% of sets. We obtained 445 photos of lynx and detected them in 7 of the 30 units sampled (Figure 1). Average agreement between photo reviewers was 96%. Of the model structures we fit, none was clearly better than the others as AICc weight was distributed fairly evenly (Table 1). Beta estimates for fitted models suggested that ψ was positively associated with both percent spruce/fir and percent willow in a given unit. Spruce/fir was also positively associated with detection probability, whereas willow was negative associated with detection probability. However none of these models were as well supported by the data as the null model in which ψ and p were considered constant across cells. Thus, results generally followed our expectations, but the null model came out on top likely due to sparse data and small samples in this pilot study. Model-averaged estimates for ψ and p were 0.25 and 0.42, respectively. Detection probability using cameras was about the same as for snowtracking (Ivan 2011), but estimated probability of use for inaccessible sampling units was about half that estimated for accessible cells sampled via snow tracking. DISCUSSION Initial results indicate that occupancy (use) can be adequately modeled using data collected via snow tracking. Precision on estimates of ψ and p was relatively poor, but this can be addressed by sampling more units and/or making more visits. Modeling p and ψ as functions of the covariates (spruce/fir and willow) was not as well supported as specifying them to be constant across units. However, we recommend continuing to record and use these covariates and others in future surveys as it seems reasonable that these covariates should impact detection probability and/or use, and their effects may be important as sample size increases. We estimated that lynx used approximately 25% of the sample units available in the Core Research Area. However, for this pilot study, lynx habitat was coarsely defined as units with >50% conifer and/or montane cover and >50% public land. In several cases, sampled units met these criteria, but field crews that actually made visits indicated these units did not appear to include much lynx habitat. CPW recently finished an analysis to produce a map of predicted lynx habitat throughout the state. In the future, we expect to use this map to frame the population of units to sample for lynx monitoring. This more refined population of sample units should reduce time wasted surveying units that do not include good lynx habitat, and will result in an increased estimate of probability of use. Indeed, re-running the analysis using only those cells (n = 24) within the top 40% of predicted lynx habitat in the state increased the occupancy estimate to 0.31. Roughly half of the visual attractants we used did not operate through the entirety of the study. These attractants are important for drawing lynx to the set from a distance and their failure diminishes the utility of the cameras for detecting lynx. If cameras are to be used in the future, design changes will be necessary to ensure that most of these visual attractants operate throughout the sampling season. We suggest that attractants be attached via wire rather than fishing line. We also suggest that auditory 30 �attractants may be helpful. In a recent study on cougars (Puma concolor) in the Front Range of Colorado, visitation rates at camera sites increased dramatically when auditory attractants were used in addition to scent lures and visual attractants (Kirstie Yeager, personal communication). ACKNOWLEDGMENTS We thank Britta Schielke, Cate Brown, Wendy Lanier, Joan Meiners, Shane McKenzie, Nick Burgmeier, Doug Clark, Bob Peterson, Tim Hanks, Kei Yasuda, Ashley Bies, Tyler Kelly, Alyssa Winkler, and Carolyn Shores for their efforts in the field. Dale Gomez and Rhandy Ghormley (USFS) graciously coordinated housing for seasonal crews. We thank various personnel from both the Rio Grande and San Juan National Forests for logistical help in the field. Funding was provided by a U.S. Fish and Wildlife Service Section 6 Grant. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model Selection and Multimodel Inference: A practical information-theoretic approach. Springer, New York, New York, USA. Devineau, O., T. M. Shenk, G. C. White, P. F. Doherty Jr., P. M. Lukacs, and R. H. Kahn. 2010. Evaluating the Canada lynx reintroduction programme in Colorado: patterns in mortality. Journal of Applied Ecology 47:524–531. Ivan, J. S., and T. M. Shenk. 2010. Estimating the Extent, Stability and Potential Distribution of Canada Lynx (Lynx canadensis) in Colorado: initial implementation in the core lynx research area. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. Ivan, J. S. 2011. Monitoring Canada lynx in Colorado using occupancy estimation: Initial implementation in the Core Lynx Research Area. Wildlife Research Report. Colorado Division of Parks and Wildlife, Fort Collins, CO, USA. Pages 11–20. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Elsevier Academic Press, Oxford, UK. McKelvey, K. S., J. von Kienast; K.B. Aubry; G. M. Koehler; B. T. Maletzke; J. R. Squires; E. L. Lindquist; S. Loch; M. K. Schwartz. 2006. DNA analysis of hair and scat collected along snow tracks to document the presence of Canada lynx. Wildlife Society Bulletin 34: 451-455. Meaney C. 2002. A review of Canada lynx (Lynx canadensis) abundance records from Colorado in the first quarter of the 20Th century. Colorado Department of Transportation Report. Shenk, T. M. 2005. Post-release monitoring of lynx reintroduced to Colorado. Job Progress Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2007. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2009. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. Shenk, T.M., and R. H. Kahn. 2003. Post-release monitoring of lynx reintroduced to Colorado. Wildlife Research Report, Colorado Division of Wildlife, Fort Collins, Colorado. __________. 2010. The Colorado lynx reintroduction program. Report to the Colorado Division of Wildlife, Fort Collins, Colorado. Squires, J. R. and T. Laurion. 1999. Lynx home range and movements in Montana and Wyoming: preliminary results. Pages 337–349 in L. F. Ruggiero, K. B. Aubry, S. W. Buskirk, G. M. Koehler, C. J. Krebs, K. S McKelvey, and J. R. Squires, editors. Ecology and Conservation of Lynx in the United States. General Technical Report for U. S. D. A. Rocky Mountain Research Station. University Press of Colorado, Boulder, Colorado. 31 �Theobald, D.M., D.L. Stevens, Jr., D. White, N.S. Urquhart, A.R. Olsen, and J.B. Norman. 2007. Using GIS to generate spatially balanced random survey designs for natural resource applications. Environmental Management 40(1): 134–146. U. S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: final rule to list the contiguous United States distinct population segment of the Canada lynx as a threatened species. Federal Register 65, Number 58. Prepared by ___________________________ Jacob S. Ivan 32 �Table 1. Model selection results for estimating lynx occupancy of sample units surveyed via remote camera in the Core Research Area, San Juan Mountains, Colorado, Winter 2010–2011. Model ψ(.)p(.) ψ(.)p(willow) ψ(.)p(SprFir) ψ(SprFir)p(.) ψ(willow)p(.) AICc 84.54 85.06 85.37 85.73 85.92 ΔAICc 0.00 0.52 0.83 1.19 1.38 AICc Wt 0.29 0.22 0.19 0.16 0.14 Num Par 2 3 3 3 3 Figure 1. Canada lynx Core Research Area in southwest Colorado. Squares are 75km2 sample units available for occupancy surveys. Blue represents the sample of 30 “accessible” units selected for snow tracking surveys. Orange are “inaccessible” units selected for surveys using remote cameras. Crosshatching indicates units where lynx were detected. 33 �Figure 2. General configuration of remote camera sets for detecting Canada lynx. Four such sets were deployed in each of 30 inaccessible sample units from Fall 2010 to Summer 2011. 34 �35 �Colorado Division of Parks and Wildlife July 2011–June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 0670 N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Predicted lynx habitat in Colorado N/A Period Covered: July 1, 2011 – June 30, 2012 Author: J. S. Ivan Personnel: M. Rice, P. Lukacs, T. Shenk (National Park Service), D. Theobald (Colorado State University), E. Odell All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 (Devineau et al. 2010). In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established (Shenk and Kahn 2010). The purpose of this project was to develop a statewide predictive map of relative lynx use based upon location data collected during the reintroduction period. To build the map, we divided the state into 1.5 km × 1.5 km cells and tallied the number of locations in each cell. We then fit models to these count data using vegetation, elevation, slope, wetness, and degree of human development in each cell as predictor variables. We produced models for both summer and winter habitat use. We found that regardless of season, lynx were positively associated with spruce/fir (Picea engelmannii/Abies lasiocarpa), mixed spruce/fir, aspen (Populus tremuloides), elevation and slope; they were negatively associated with distance to large forest patches. During summer, lynx use of lodgepole pine (Pinus contorta) stands was predicted to increase. Lynx were predicted to avoid montane forest (Douglas-fir [Pseudotsuga menziesii], Ponderosa pine [Pinus ponderosa]), and areas near high traffic volume road segments, especially during summer. These maps of predicted lynx use should aid land managers in prioritizing areas for conservation, development, and resource extraction with respect to potential impacts to lynx and lynx habitat. 36 �WILDLIFE RESEARCH REPORT PREDICTED LYNX HABITAT IN COLORADO JACOB S. IVAN P. N. OBJECTIVE Use location data collected during Canada lynx (Lynx canadensis) reintroduction to build a model of relative use, then apply this model statewide to produce a predictive map of relative lynx use for Colorado. SEGMENT OBJECTIVES 1. Prepare manuscript for submission to Journal of Wildlife Management. INTRODUCTION In an effort to restore a viable population of federally threatened Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006 by the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW], Devineau et al. 2010). In 2010, CPW determined that the reintroduction effort met all benchmarks of success, and that a viable, self-sustaining population of Canada lynx had been established (Shenk and Kahn 2010). Attainment of this goal is a conservation success, but it has also created a series of issues for land management agencies to consider as they plan changes to the landscape. These issues require knowledge of the types of landscapes and forest stands important for reproduction, movement, dispersal, and general home range use by lynx. As a first step toward providing this information, Theobald and Shenk (2011) conducted an analysis to describe the types of areas that were known to be used by re-introduced lynx. Specifically, they used LoCoH (Getz and Wilmers 2004, Getz et al. 2007) methods to create a population-level utilization distribution (UD, a probability surface of lynx occurrence) for lynx in Colorado. They then summarized landscape attributes within the 90% isopleth (i.e., polygon(s) containing 90% of the probability surface) of this UD. This work provides valuable information regarding the types of areas that were known to be used by lynx from 1999 to 2010. By nature of the data collection and research focus, most of this “use” information was derived from core areas in the San Juan Mountains of southwest Colorado and Sawatch Range in the central part of the state. The purpose of the current project is to extend the work of Theobald and Shenk (2011) by producing a map of predicted lynx use on a statewide scale. Such an exercise will identify areas within Colorado that should contain high quality lynx habitat, regardless of whether or not it was used by the sample of radio-telemetered individuals tracked during reintroduction research. Both works have strengths and weaknesses, but together they provide tools for prioritizing areas for conservation, development, and resource extraction with respect to potential impacts to lynx. METHODS While this worked was completed in January 2012, the final report was included in revisions to the previous annual report and is not repeated here. We refer the reader to Ivan (2011) for details regarding methods and results from this work. Our intent is to work this report into a manuscript submission to Journal of Wildlife Management by Fall 2012. 37 �SUMMARY As expected, relative predicted use by lynx during winter months was negatively associated with distance to large patches of conifer (D50HA) and positively associated with spruce/fir (SF), mixed spruce/fir (MIXSF), elevation (ELEV) and slope . Of these associations, the relationship with spruce/fir was strongest. Predicted use was also positively associated with topographic wetness and aspen cover. We projected these associations (and other more minor associations included in competing models) onto a map of the state and arbitrarily defined the top 20% of predictions as high quality lynx habitat. There are 1,869,975 ha of such habitat in Colorado. Most of this high quality habitat was predicted to occur in the southern part of the state in the San Juan, Culebra, and Wet Mountain Ranges. In the central portion of the state, high predicted use is expected in the northern Sawatch and West Elk Ranges, along with Grand Mesa. The Park Range and Flat Tops comprised the best predicted winter lynx habitat farther north Associations between relative predicted summer use and SF, MIXSF, ELEV, slope, and D50HA were similar to those observed during winter. However, the associations with D50HA and slope were stronger during summer. We also found positive associations between lodgepole pine, aspen, and distance to high volume road segments. The summer predictive map reflects more dispersed predicted use by lynx with the lodgepole playing a larger role, especially farther north. The central and southern Sawatch Range in central Colorado is predicted to have more use than during winter, whereas use on Grand Mesa is predicted to decline. In the northern part of the state, lynx use was predicted to shift more toward the Medicine Bow and Front Ranges. LITERATURE CITED Ivan, J. S. 2011. Predicted lynx habitat in Colorado. Wildlife Research Report. Colorado Division of Parks and Wildlife, Fort Collins, CO, USA. Pages 21–35. Prepared by ___________________________ Jacob S. Ivan 38 �39 �Colorado Division of Parks and Wildlife July 2011–June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 0670 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Mammals Research Lynx Conservation Density, demography, and seasonal movements of snowshoe hares in central Colorado. Period Covered: July 1, 2011 – June 30, 2012 Author: J. S. Ivan Personnel: G. White, T. Shenk All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT To improve understanding of snowshoe hare ecology in the southern portion of their range, and enhance the ability of agency personnel to manage subalpine landscapes for snowshoe hares (Lepus americanus) and lynx (Lynx canadensis) in Colorado, we estimated snowshoe hare density, survival, recruitment, and movement in west-central Colorado, USA from July 2006−March 2009. We sampled 3 types of forest stands that purportedly provide good habitat for hares: 1) mature Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), 2) early seral, even-aged lodgepole pine (Pinus contorta), and 3) mid-seral, even-aged lodgepole pine that had been pre-commercially thinned. In all stand types and all seasons, snowshoe hare densities were <1.0 hares/ha. During summer, hare densities [±SE] were highest in early seral lodgepole pine (0.20 [0.01] to 0.66 [0.07] hares/ha), lowest in mid-seral lodgepole pine (0.01 [0.04] to 0.03 [0.03] hares/ha), and intermediate in mature spruce-fir (0.01 [0.002] to 0.26 [0.08] hares/ha). During winter, densities were similar among the 3 stand types. Annual survival of hares was highest in mature spruce-fir (0.14 [0.05] to 0.20 [0.07]) and similar between the 2 lodgepole stand types (0.10 [0.03] to 0.16 [0.06]). Stand attributes indicative of dense cover were positively correlated with density estimates and explain relatively more process variance in hare densities than other attributes. These same attributes were not positively correlated with hare survival. Both density and survival of hares in early seral lodgepole stands were positively correlated with the occurrence of similar stands in the surrounding landscape. Recruitment of juvenile hares occurred during all 3 summers in early seral lodgepole stands, 2 of 3 summers in mature spruce-fir stands, and in only 1 of 3 summers in mid-seral lodgepole. Within-season movements of hares were larger during winter than during summer and tended to be larger in early seral lodgepole stands. Hares in both early and mid-seral lodgepole stands tended to make larger movements between seasons than hares in spruce-fir stands, possibly reflecting the variable value of these stands as mediated by snow depth. Based on stand-specific estimates of density, demography, and movement, we conclude that thinned, mid-seral lodgepole stands are less important than mature spruce-fir and small lodgepole stand types. Management for snowshoe hares (and lynx) in central 40 �Colorado should focus on maintaining the latter. Given the more persistent nature of spruce-fir compared to early seral lodgepole, and the fact that such stands cover considerably more area, mature spruce-fir may be the most valuable stand type for snowshoe hares in the region. We used simulation to compare relative performance of the method we developed to estimate density for this project (TELEM) to other contemporary methods that are widely used (i.e., spatially explicit capture-recapture (SECR), and mean maximum distance moved (MMDM)). We evaluated performance (percent error) under all combinations of 3 levels of detection probability (0.2, 0.4, 0.6), 3 levels of occasions (5, 7, 10), and 3 levels of abundance (10, 20, 40 animals). We also tested each estimator using 5 different models for animal home ranges. TELEM performed best across most combinations of capture probabilities, sampling occasions, true densities, and home range configurations, and performance was unaffected by home range shape. SECR outperformed MMDM estimators in nearly all comparisons and may be preferable to TELEM at low capture probabilities, but performance varied with home range configuration. MMDM estimators exhibited substantial positive bias for most simulations, but performance improved for elongated or infinite home ranges. 41 �WILDLIFE RESEARCH REPORT DENSITY, DEMOGRAPY, AND SEASONAL MOVEMENTS OF SNOWSHOE HARES IN CENTRAL COLORADO JACOB S. IVAN P. N. OBJECTIVE Assess the relative value of 3 stand types (mature spruce/fir, early seral lodgepole pine, and thinned, midseral lodgepole pine) that purportedly provide high quality hare habitat by estimating density, survival, recruitment, and movements of hares in such stands during summer and winter. SEGMENT OBJECTIVES 1. Publish manuscripts in peer-reviewed scientific journals. INTRODUCTION Snowshoe hares (Lepus americanus), their famous 10-year population cycle, and close association with Canada lynx (Lynx canadensis) have been well-studied in boreal Canada for decades. Snowshoe hare range, however, extends south into the Sierra Nevada, Southern Rockies, upper Lake States, and Appalachian Mountains. Ecology of snowshoe hares in these more southerly regions is not as well understood, though hare research in the U.S. Rocky Mountains has accelerated over the past decade. Through this recent work, biologists have identified stands of young, densely-stocked conifers and those of mature, uneven-aged conifers as primary hare habitat in the region. Both stand types are characterized by dense understory vegetation that provides both browse and protection from elements and predators. From 1999 to 2006, Canada lynx were reintroduced into Colorado in an effort to restore a viable population to the southern portion of their former range. Snow tracking of released individuals and their progeny indicated that the majority of lynx winter diet in Colorado was comprised of snowshoe hares. Thus, long-term success of the lynx reintroduction effort hinges, at least partly, on maintaining adequate and widespread populations of snowshoe hares in the state. To improve our understanding of snowshoe hare ecology in the southern portion of their range, and enhance the ability of agency personnel to manage subalpine landscapes for snowshoe hares and lynx in Colorado, we conducted an observational study to evaluate purported primary hare habitat in the state. Specifically, we estimated snowshoe hare density, survival, recruitment, and movement indices in mature, uneven-aged spruce/fir (Picea engelmannii/Abies lasiocarpa) and 2 classes of young, even-aged lodgepole pine: 1) “small” lodgepole pine (Pinus contorta) stands, which were clear cut 20−25 years prior to this study and had regenerated into densely stocked stands with trees 2.54−12.69 cm in diameter, and 2) “medium” lodgepole pine stands (tree diameter = 12.70−22.85 cm) which were clear cut 40-60 years prior to this study and pre-commercially thinned ~20 years prior. Animal density is one of the most common and fundamental parameters in wildlife ecology and was the first metric we used to evaluate the stand types. However, density can be difficult to estimate from mark-recapture data because animals move on and off of a trapping grid during a sampling session (i.e., lack of geographic closure). Thus, we first developed a density estimator that uses ancillary radio telemetry locations, in addition to mark-recapture information, to account for lack of geographic closure resulting in relatively unbiased estimates of density. We also completed a series of simulations to test the performance of this “telemetry” estimator over a range of sampling parameters (i.e., capture probabilities, sampling occasions, densities, and home range configurations) likely to be encountered in the field, and 42 �compared its performance to two other commonly used, contemporary estimators: spatially explicit capture-recapture (SECR), and mean maximum distance moved (MMDM). STUDY AREA The study area encompassed roughly 1200 km2 around Taylor Park and Pitkin, Colorado, USA (39°50'N, 106°34'W; Figure 1), and included a portion of the “Core Reintroduction Area” occupied by reintroduced Canada lynx (Shenk 2009). Open sagebrush (Artemisia tridentata) parks dissected by narrow riparian zones of willow (Salix spp.) and potentilla (Potentilla spp.) dominated the relatively low elevation (~2800−3000 m) parts of the study area. Extensive stands of lodgepole pine occupied low and mid-elevation slopes (~3000−3300 m), giving way to narrow bands of Engelmann spruce/subalpine fir in the sub-alpine zone (~3200−3600 m). Alpine tundra topped the highest parts of the study area (~3300−4200 m). Moist spruce-fir forests also occurred on north-facing slopes at mid-elevations. Climate was typical of continental, high-elevation zones with relatively short, mild summers and long, harsh winters. Mean July temperature was 14 °C; mean January temperature was −11 °C (Ivan 2011). Maximum snow depth on the study area averaged 80 cm but ranged from 22−163 cm depending on year, elevation, and aspect (Ivan 2011). Snowpack generally persisted from November through May (low elevations) or June (high elevations and north-facing slopes). Some human habitation occurred in the study area, mostly in the form of seasonal residences. Considerable recreational use occurred during summer in the form of dispersed camping and off-highway vehicle traffic. A suite of native predators were present within the study area including lynx, cougar (Puma concolor), coyote (Canis latrans), red fox (Vulpes vulpes), pine marten (Martes Americana), Great Horned Owl (Bubo virginianus) and Northern Goshawk (Accipiter gentilis). METHODS Refer to Ivan (2011) for methods associated with fieldwork conducted during 2006–2009 and subsequent statistical analyses. During fiscal year 2011–2012 we completed work on 2 manuscripts submitted as a pair to the journal Ecology. The first of these manuscripts lays out an approach to estimating animal density using auxiliary telemetry information to improve estimates. The second manuscript uses simulation to compare performance of this new estimator to other contemporary estimators. We have just completed what we believe to be final revisions to these papers. Additionally, we spent much of year combining the demography and movement chapters of the primary author’s dissertation into a single, comprehensive treatment of snowshoe hare ecology in central Colorado that includes analyses on hare density, survival, recruitment, and movement. This manuscript was recently submitted to the Journal of Wildlife Management for consideration as either a research article or monograph. RESULTS AND DISCUSSION A comprehensive treatment of the results is widely available in dissertation form (Ivan 2011), so we do not repeat that here. We are currently in the process of publishing results in the peer-reviewed literature. Below is list of manuscripts that have been submitted for publication (abstracts are provided in Appendix I): Ivan, J. S., G. C. White, and T. M. Shenk. In Review. Using auxiliary telemetry information to estimate animal density from capture-recapture data. Ecology. 43 �Ivan, J. S., G. C. White, and T. M. Shenk. In Review. Using simulation to compare methods for estimating density from capture-recapture data. Ecology. Ivan, J. S., G. C. White, and T. M. Shenk. In Review. Density, Demography, and Seasonal Movements of Snowshoe Hares in Central Colorado. Journal of Wildlife Management. SUMMARY In all stand types and all seasons, snowshoe hare densities were <1.0 hares/ha. During summer, hare densities [±SE] were highest in early seral lodgepole pine (0.20 [0.01] to 0.66 [0.07] hares/ha), lowest in mid-seral lodgepole pine (0.01 [0.04] to 0.03 [0.03] hares/ha), and intermediate in mature spruce-fir (0.01 [0.002] to 0.26 [0.08] hares/ha). During winter, densities were similar among the 3 stand types. Annual survival of hares was highest in mature spruce-fir (0.14 [0.05] to 0.20 [0.07]) and similar between the 2 lodgepole stand types (0.10 [0.03] to 0.16 [0.06]). Stand attributes indicative of dense cover were positively correlated with density estimates and explain relatively more process variance in hare densities than other attributes. These same attributes were not positively correlated with hare survival. Both density and survival of hares in early seral lodgepole stands were positively correlated with the occurrence of similar stands in the surrounding landscape. Recruitment of juvenile hares occurred during all 3 summers in early seral lodgepole stands, 2 of 3 summers in mature spruce-fir stands, and in only 1 of 3 summers in mid-seral lodgepole. Within-season movements of hares were larger during winter than during summer and tended to be larger in early seral lodgepole stands. Hares in both early and mid-seral lodgepole stands tended to make larger movements between seasons than hares in spruce-fir stands, possibly reflecting the variable value of these stands as mediated by snow depth. Based on stand-specific estimates of density, demography, and movement, we conclude that thinned, mid-seral lodgepole stands are less important than mature spruce-fir and small lodgepole stand types. Management for snowshoe hares (and lynx) in central Colorado should focus on maintaining the latter. Given the more persistent nature of spruce-fir compared to early seral lodgepole, and the fact that such stands cover considerably more area, mature spruce-fir may be the most valuable stand type for snowshoe hares in the region. The estimator we developed is based on a modified Huggins closed capture estimator. It directly accounts for lack of geographic closure (animals moving on and off of the sampling grid during the sampling period) using telemetry data, and this auxiliary information is used to compute estimates of density. Contrary to other approaches, this method is free from assumptions regarding the distribution of animals on the landscape, the stationarity of their home ranges, and biases induced by abnormal movements in response to baited detectors. The estimator is freely available in Program MARK. We found that our approach performed best across most combinations of capture probabilities, sampling occasions, true densities, and home range configurations, and performance was unaffected by home range shape. Spatially explicit capture-recapture methods outperformed “mean maximum distance moved” (MMDM) estimators in nearly all comparisons and may be preferable to our telemetry estimator at low capture probabilities, but performance varied with home range configuration. MMDM estimators exhibited substantial positive bias for most simulations, but performance improved for elongated or infinite home ranges. LITERATURE CITED Ivan, J. S. 2011. Density, demography, and seasonal movement of snowshoe hares in central Colorado. Dissertation, Colorado State University, Fort Collins, Colorado, USA. Prepared by ___________________________ Jacob S. Ivan 44 �Figure 1. Study area near Taylor Park and Pitkin, central Colorado. We estimated snowshoe density, demography, and movement in 3 late-seral Engelmann spruce/subalpine fir stands (circles), 3 mid-seral lodgepole stands (squares), and 6 early-seral lodgepole stands (triangles) from summer 2006 through winter 2009. 45 �APPENDIX I PROJECT PAPERS The following manuscript (referenced here by abstract) is currently in review at the journal Ecology. USING AUXILIARY TELEMETRY INFORMATION TO ESTIMATE ANIMAL DENSITY FROM CAPTURE-RECAPTURE DATA JACOB S. IVAN, GARY C. WHITE, AND TANYA M. SHENK ABSTRACT Estimation of animal density is fundamental to ecology, and ecologists often pursue density estimates using grids of detectors (e.g., cameras, traps, hair snags) to sample animals. However, under such a framework, reliable estimates can be difficult to obtain because animals move on and off of the study site during the sampling session (i.e., the site is not closed geographically). Generally, practioners address lack of geographic closure by a) inflating the area sampled by the detectors based on the mean distance individuals moved between trapping events, or b) invoking hierarchical models in which animal density is assumed to be a spatial point process, and detection is modeled as a declining function of distance to a detector. We provide an alternative in which lack of geographic closure is sampled directly using telemetry, and this auxiliary information is used to compute estimates of density based on a modified Huggins closed capture estimator. Contrary to other approaches, this method is free from assumptions regarding the distribution of animals on the landscape, the stationarity of their home ranges, and biases induced by abnormal movements in response to baited detectors. The estimator is freely available in Program MARK. The following manuscript (referenced here by abstract) is currently in review at the journal Ecology. USING SIMULATION TO COMPARE METHODS FOR ESTIMATING DENSITY FROM CAPTURE-RECAPTURE DATA JACOB S. IVAN, GARY C. WHITE, TANYA M. SHENK Estimation of animal density is fundamental to wildlife research and management, but estimation is often complicated by lack of geographic closure of sampling grids. Contemporary methods for estimating density using mark–recapture data include: 1) approximating the effective area sampled by an array of detectors based on the mean maximum distance moved (MMDM) by animals during the sampling session, 2) spatially explicit capture–recapture (SECR) methods that formulate the problem hierarchically with a process model for animal density and an observation model in which detection probability declines with distance from a detector, and 3) a telemetry estimator (TELEM) that uses auxiliary telemetry information to estimate the proportion of animals on the study site. We used simulation to compare relative performance (percent error) of these methods under all combinations of 3 levels of detection probability (0.2, 0.4, 0.6), 3 levels of occasions (5, 7, 10), and 3 levels of abundance (10, 20, 40 animals). We also tested each estimator using 5 different models for animal home ranges. TELEM performed best across most combinations of capture probabilities, sampling occasions, true densities, and home range configurations, and performance was unaffected by home range shape. SECR outperformed MMDM estimators in nearly all comparisons and may be preferable to TELEM at low capture probabilities, but performance varied with home range configuration. MMDM estimators 46 �exhibited substantial positive bias for most simulations, but performance improved for elongated or infinite home ranges. The following manuscript (referenced here by abstract) is currently in review at the Journal of Wildlife Management. Density, Demography, and Seasonal Movements of Snowshoe Hares in Central Colorado JACOB S. IVAN, GARY C. WHITE, TANYA M. SHENK ABSTRACT To improve understanding of snowshoe hare ecology in the southern portion of their range, and enhance the ability of agency personnel to manage subalpine landscapes for snowshoe hares (Lepus americanus) and lynx (Lynx canadensis) in Colorado, we estimated snowshoe hare density, survival, recruitment, and movement in west-central Colorado, USA from July 2006−March 2009. We sampled 3 types of forest stands that purportedly provide good habitat for hares: 1) mature Engelmann spruce (Picea engelmannii)/subalpine fir (Abies lasiocarpa), 2) early seral, even-aged lodgepole pine (Pinus contorta), and 3) mid-seral, even-aged lodgepole pine that had been pre-commercially thinned. In all stand types and all seasons, snowshoe hare densities were <1.0 hares/ha. During summer, hare densities [±SE] were highest in early seral lodgepole pine (0.20 [0.01] to 0.66 [0.07] hares/ha), lowest in mid-seral lodgepole pine (0.01 [0.04] to 0.03 [0.03] hares/ha), and intermediate in mature spruce-fir (0.01 [0.002] to 0.26 [0.08] hares/ha). During winter, densities were similar among the 3 stand types. Annual survival of hares was highest in mature spruce-fir (0.14 [0.05] to 0.20 [0.07]) and similar between the 2 lodgepole stand types (0.10 [0.03] to 0.16 [0.06]). Stand attributes indicative of dense cover were positively correlated with density estimates and explain relatively more process variance in hare densities than other attributes. These same attributes were not positively correlated with hare survival. Both density and survival of hares in early seral lodgepole stands were positively correlated with the occurrence of similar stands in the surrounding landscape. Recruitment of juvenile hares occurred during all 3 summers in early seral lodgepole stands, 2 of 3 summers in mature spruce-fir stands, and in only 1 of 3 summers in mid-seral lodgepole. Within-season movements of hares were larger during winter than during summer and tended to be larger in early seral lodgepole stands. Hares in both early and mid-seral lodgepole stands tended to make larger movements between seasons than hares in spruce-fir stands, possibly reflecting the variable value of these stands as mediated by snow depth. Based on stand-specific estimates of density, demography, and movement, we conclude that thinned, mid-seral lodgepole stands are less important than mature spruce-fir and small lodgepole stand types. Management for snowshoe hares (and lynx) in central Colorado should focus on maintaining the latter. Given the more persistent nature of spruce-fir compared to early seral lodgepole, and the fact that such stands cover considerably more area, mature spruce-fir may be the most valuable stand type for snowshoe hares in the region. 47 �Colorado Division of Parks and Wildlife July 1, 2011 − June 30, 2012 WILDLIFE RESEARCH REPORT State of Cost Center Work Package Task No. Colorado 3430 3001 6 Federal Aid Project: W-185-R : Division of Parks and Wildlife : Mammals Research : Deer Conservation : Population Performance of Piceance Basin Mule Deer in Response to Natural Gas Resource Extraction and Mitigation Efforts to Address Human Activity and Habitat Degradation : Period Covered: July 1, 2011 − June 30, 2012 Authors: C. R. Anderson and C. J. Bishop Personnel: E. Bergman, T. Bryan, A. Burleson, B. deVergie, D. Finley, M. Fisher, L. Gepfert, C. Harty, D. Johnston, A. Jones, T. Knowles, J. Lewis, H. MacIntyre, J. Matijas, B. Panting, T. Parks, B. Petch, J. Rivale, J. Simpson, S. Singleton, M. Trump, B. Tycz, R. Velarde, L. Wolfe, CPW; E. Hollowed, L. Belmonte, BLM; S. Monsen, Western Ecological Consulting, Inc.; D. Freddy, Hoch Berg Enterprises; T. Graham, Ranch Advisory Partners; M. Wille, T & M Contractors.; P. Lendrum, T. Bowyer, Idaho State University; P. Doherty, J. Northrup, M. Peterson, G. Wittemyer, K. Wilson, G. White, Colorado State University; R. Swisher, S. Swisher, Quicksilver Air, Inc.; D. Felix, Olathe Spray Service, Inc.; L. Coulter, Coulter Aviation. Project support received from Federal Aid in Wildlife Restoration, Colorado Mule Deer Association, Colorado Mule Deer Foundation, Colorado State Severance Tax Fund, EnCana Corp., ExxonMobil Production Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, and Williams Production LMT Co. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the authors. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent the first 4 pretreatment years of a long-term study addressing habitat improvements and evaluation of energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. We monitored 4 winter range study areas representing varying levels of development to serve as treatment (Ryan Gulch, North Magnolia, South Magnolia) and control (North Ridge) sites and recorded habitat use and movement patterns using GPS collars (≥5 location attempts/day), estimated overwinter fawn and annual adult female survival, estimated early and late winter body condition of adult females using ultrasonography, and estimated abundance using helicopter mark-resight surveys. We targeted 260 fawns (60–80/study area) and 140 does (30–40/study area) in early December 2011 for VHF and GPS radiocollar attachment, respectively, and 140 does in March 2012 (30–40/study area) for late winter body condition assessment and to increase our GPS radiocollar sample in 1 of the 4 areas (24 in Ryan Gulch) to address neonate 48 �survival. Based on the data collected since January 2008, deer from all areas appear to be in reasonably good condition and have exhibited relatively high survival rates 3 of the 4 years (mean fawn Ŝ > 0.65) with lower winter fawn survival during 2010/11 in 3 of 4 study areas (mean Ŝ = 0.49 excluding North Ridge), and winter range deer densities appear to be stable. More extreme winter conditions during 2010/11 likely contributed to the observed decline in fawn survival rates. Pilot habitat treatments in North and South Magnolia (116 acres total) were completed January 2011 (Anderson and Bishop 2011), another 54 acres were treated January 2012 to assess mechanical treatment methods (hydro-ax, rollerchop, chain), and all required NEPA surveys were completed this summer for the remaining sites (Fig. 6). The Biological Assessment should be completed during September 2012 allowing the remaining 1,030 acres to be treated using hydro-ax this winter. We will continue to collect the various population and habitat use data across all study sites to evaluate the effectiveness of habitat treatments (North and South Magnolia) scheduled for fall/winter 2012–2013 (1,200 acres total). This evaluation will allow us to determine whether it is possible to effectively mitigate development disturbance in highly developed areas, or whether it is better to allocate mitigation dollars toward less or non-impacted areas. In collaboration with Colorado State University, we are also evaluating deer behavioral responses to varying levels of development activity in the Ryan Gulch study area and neonate survival in relation to energy development from all study areas. This will allow us to assess the effectiveness of certain Best Management Practices (BMPs) for reducing disturbance to deer and include neonatal data to other demographic parameters for evaluation of mule deer/energy development interactions. The study is slated to run through at least 2017, and preferably 2019, to adequately measure mule deer population responses to landscape level manipulations. 49 �WILDLIFE RESEARCH REPORT POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION CHARLES R. ANDERSON, JR and CHAD J. BISHOP PROJECT NARRITIVE OBJECTIVES 1. To determine experimentally whether enhancing mule deer habitat conditions on winter range elicits behavioral responses, improves body condition, increases fawn survival, or ultimately, population density on mule deer winter ranges exposed to extensive energy development. 2. To determine experimentally to what extent modification of energy development practices enhance habitat selection, body condition, fawn survival, and winter range mule deer densities. SEGMENT OBJECTIVES 1. Collect and reattach GPS collars to maintain sample sizes for addressing mule deer habitat use and behavior patterns in 4 study areas experiencing varying levels of energy development of the Piceance Basin, northwest Colorado. 2. Estimate early and late winter body condition of adult female mule deer in each of the 4 winter herd segments using ultrasound techniques. 3. Monitor over-winter fawn and annual adult female mule deer survival by daily ground tracking and biweekly aerial tracking. 4. Conduct Mark-Resight helicopter surveys to estimate mule deer abundance in each study area. 5. Complete NEPA surveys to allow future habitat treatments for assessing efficacy of habitat improvement projects to mitigate energy development disturbances to mule deer. 6. Initiate neonate survival evaluations to complete demographic parameters for assessing mule deer/energy development interactions. INTRODUCTION Extraction of natural gas from areas throughout western Colorado has raised concerns among many public stakeholders and Colorado Parks and Wildlife (CPW) that the cumulative impacts associated with this intense industrialization will dramatically and negatively affect the wildlife resources of the region. Concern is especially high for mule deer due to their recreational and economic importance as a principal game species and their ecological importance as one of the primary herbivores of the Colorado Plateau Ecoregion. Extraction of natural gas will directly affect the potential suitability of the landscape used by mule deer through conversion of native habitat vegetation with drill pads, roads, or noxious weeds, by fragmenting habitat because of drill pads and roads, by increasing noise levels via compressor stations and vehicle traffic, and by increasing the year-round presence of human activities. Extraction will indirectly affect deer by increasing the human work-force population of the region resulting in the need for additional landscape for human housing, supporting businesses, and upgraded road/transportation infrastructure. Additionally, increased traffic on rural roads will raise the potential for vehicle-animal collisions and additive direct mortality to mule deer populations. Thus, research documenting these relationships and evaluating the most effective strategies for minimizing and mitigating these activities will greatly enhance future management efforts to sustain mule deer populations for future recreational and ecological values. 50 �The Piceance Basin in northwest Colorado contains one of the largest migratory mule deer populations in North America and also exhibits some of the largest natural gas reserves in North America. Projected energy development throughout northwest Colorado within the next 20 years is expected to reach about 15,000 wells, many of which will occur in the Piceance Basin, which currently supports over 250 active gas well pads (http://cogcc.state.co.us; Fig. 1). Anderson and Freddy (2008a) in their longterm research proposal identified 6 primary study objectives to assess measures to offset impacts of energy extraction on mule deer population performance. During the past 4 years, we have gathered baseline habitat utilization data from GPS-collared deer across the Piceance Basin to allow assessment of mitigation approaches that will be implemented over the next 1–2 years and evaluated for another 4-6 years. We are currently monitoring 1 control area without development (North Ridge), 2 areas with relatively high development activity (0.6–0.9 well pads & facilities/km2; Ryan Gulch and South Magnolia), and another area with relatively minor development activity (0.1 well pads & facilities/km2; North Magnolia). In comparison to the un-manipulated control area (North Ridge), the North and South Magnolia areas will receive similar levels of mechanical habitat treatments to evaluate this mitigation strategy relative to differing development intensities, and deer behavior patterns relative to differing development activities in the Ryan Gulch area will be monitored to identify effective Best Management Practices (BMPs) for future application. This progress report describes the previous 4.5 years (Jan 2008– June 2011) of addressing mule deer population performance during the pretreatment phase on 4 winter range herd segments, which includes monitoring habitat selection and behavior patterns of adult female mule deer; spring/summer neonate, overwinter fawn and adult female survival; estimates of adult female body condition during early and late winter, and annual late-winter abundance estimates. STUDY AREAS The Piceance Basin, located between the cities of Rangely, Meeker, and Rifle in northwest Colorado, was selected as the project area due to its ecological importance as one of the largest migratory mule deer populations in North America and because it exhibits one of the highest natural gas reserves in North America (Fig. 1). Historically, mule deer numbers on winter range were estimated between 20,000–30,000 (White and Lubow 2002), and the current number of well pads (Fig.1) and projected number of gas wells in the Piceance Basin over the next 20 years is about 250 and 15,000, respectively. Mule deer winter range in the Piceance Basin is predominantly characterized as a topographically diverse pinion pine (Pinus edulis)-Utah juniper (Juniperus osteosperma; pinion-juniper) shrubland complex ranging from 1,675 m to 2,285 m in elevation (Bartmann and Steinert 1981). Pinion-juniper are the dominant overstory species and major shrub species include Utah serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), big sagebrush (Artemisia tridentata), Gamble’s oak (Quercus gambelii), mountain snowberry (Symphoricarpos oreophilus), and rabbitbrush (Chrysothamnus spp.; Bartmann et al. 1992). The Piceance Basin is segmented by numerous drainages characterized by stands of big sagebrush, saltbush (Atriplex spp.), and black greasewood (Sarcobatus vermiculatus), with the majority of the primary drainages having been converted to mixedgrass hay fields. Grasses and forbs common to the area consist of wheatgrass (Agropyron spp.), blue grama (Bouteloua gracilis), needle and thread (Stipa comata), Indian rice grass (Oryzopsis hymenoides), arrowleaf balsamroot (Balsamorhiza sagittata), broom snakeweed (Gutierrezia sarothreae), pinnate tansymustard (Descurainia pinnata), milkvetch (Astragalus spp.), Lewis flax (Linum lewisii), evening primrose (Oenothera spp.), skyrocket gilia (Gilia aggregata), buckwheat (Erigonum spp.), Indian paintbrush (Castilleja spp.), and penstemon (Penstemon spp.; Gibbs 1978). The climate of the Piceance Basin is characterized by warm dry summers and cold winters with most of the annual moisture resulting from spring snow melt. Wintering mule deer population segments we investigated in the Piceance Basin include: North Ridge (53 km2) just north of the Dry Fork of Piceance Creek including the White River in the northeastern portion of the Basin, Ryan Gulch (141 km2) between Ryan Gulch and Dry Gulch in the 51 �southwestern portion of the Basin, North Magnolia (79 km2) between the Dry Fork of Piceance Creek and Lee Gulch in the north-central portion of the Basin, and South Magnolia (83 km2) between Lee Gulch and Piceance Creek in the south-central portion of the Basin (Fig. 1). Each of these wintering population segments has received varying levels of natural gas development: no development in North Ridge, light development in North Magnolia (0.14 pads & facilities/km2), and relatively high development in the Ryan Gulch (0.60 pads & facilities/km2) and South Magnolia (0.86 pads & facilities/km2) segments (Fig. 1). Among the 4 study areas, North Ridge will serve as an unmanipulated control site, Ryan Gulch will serve to address human-activity management alternatives (BMPs) that benefit mule deer exposed to energy development, and North and South Magnolia will serve to address the utility of habitat treatments intended to enhance mule deer population performance in areas exposed to light (North Magnolia) and heavy (South Magnolia) energy development activities. METHODS Tasks addressed this period included mule deer capture and collaring efforts, monitoring overwinter fawn and annual adult female survival, estimating adult female body condition during early and late winter using ultrasonography, estimating mule deer abundance applying helicopter mark-resight surveys, working with BLM to complete NEPA surveys to proceed with mechanical habitat treatments fall/winter 2012, and initiation of evaluating neonate survival in developed and undeveloped landscapes. We employed helicopter net-gunning techniques (Barrett et al. 1982, van Reenen 1982) to capture 60–80 fawns and 30–40 adult females during early December 2011 and early March 2012 in each of the 4 study areas. Once netted, all deer were hobbled and blind folded. Fawns were weighed, radio-collared and released on site, and adult females were transported to localized handling sites for recording body measurements and fitted with GPS collars (30–40/area during December 2011, primarily recaptures during March 2012; 5 or 24 fixes/day; G2110D, Advanced Telemetry Systems, Isanti, MN, USA) and released. To provide direct measures of decline in overwinter body condition, 30 does were recaptured in each study area that were captured the previous December; 24 uncollared does were also captured in Ryan Gulch to achieve a desired sample size of 30/study area for monitoring neonate survival. Fawn collars were spliced and fitted with rubber surgical tubing to facilitate collar drop between mid-summer and early autumn, and GPS collars were supplied with timed drop-off mechanisms scheduled to release early in April of the year following deployment. All radio-collars were equipped with mortality sensing options (i.e., increased pulse rate following 4–8 hrs of inactivity). Mule Deer Habitat Use and Movements We downloaded and summarized data from GPS collars deployed December 2010 following collar drop and retrieval in early April 2012. GPS collars deployed maintained the same fix schedule of attempting fixes every 5 hours except in Ryan Gulch where fix rates were programmed for 1/hour to increase resolution of GPS data for evaluation of deer behavior patterns in relation to differing development activities. We plotted deer locations and recorded timing and distance of spring and fall 2011 migrations for each study area. Mule deer winter concentration areas were created using composite GPS data (March 2010 through April 2011 from all deer; 5 location attempts/day) from each study area and mapped in ArcGIS (ver. 9.3) using Spatial Analyst (kernel probability density functions separated by quantiles). Mule deer resource selection analyses are pending completion of high resolution habitat data layers currently being developed by BLM. Mule Deer Survival Mule deer mortality monitoring consisted of daily ground telemetry tracking and aerial monitoring approximately every 2 weeks from fixed-wing aircraft on winter range and bi-weekly aerial monitoring on summer range. Once a mortality signal was detected, deer were located and necropsied to assess cause of death. We estimated weekly survival using the staggered entry Kaplan-Meier procedure (Kaplan and Meier 1958, Pollock et al. 1989). Capture-related mortalities (any mortalities occurring 52 �within 10 days of capture) and collar failures were censored from survival rate estimates. We estimated survival rates from 1 July 2011 through 30 June 2012 for adult females and from early December 2011– mid June 2012 for fawns. Adult Female Body Measurements We applied ultrasonography techniques described by Stephenson et al. (1998, 2002) and Cook et al. (2001) to measure maximum subcutaneous rump fat (mm), loin depth (longissimus dorsi muscle, mm), and to estimate % body fat. We estimated a body condition score (BCS) for each deer by palpating the rump (Cook et al. 2001, 2007, 2009). We examined differences (P < 0.05) in nutritional status among study areas and between years using a two-sample t-test. We considered differences in body condition meaningful when mean rump fat or % body fat differed statistically between comparisons. Other body measurements recorded included pregnancy status (pregnant, barren) via blood samples, weight (kg), chest girth (cm), and hind-foot length (cm). Abundance Estimates We conducted 4 (North Ridge, North Magnolia) or 5 (Ryan Gulch, South Magnolia) helicopter mark-resight surveys (2 observers and the pilot) during late March/early April, 2012 to estimate deer abundance in each of the 4 study areas. We delineated each study area from GPS locations collected on winter range during the first 3 years of the study (Jan 2008 through April 2011). Two aerial fixed-wing telemetry surveys/study area were conducted during helicopter mark-resight surveys to determine which marked deer were within each survey area, and we confirmed adult female locations during surveys from GPS data acquired April 2012. We delineated flight paths in ArcGIS 9.3 prior to surveys following topographic contours (e.g., drainages, ridges) and approximating 500–600 m spacing throughout each study area; flight paths during surveys were followed using GPS navigation in the helicopter. Two approximately 12 x 12 cm pieces of Ritchey livestock banding material (Ritchey Livestock ID, Brighton, CO USA) were uniquely marked using color, number, and symbol combinations and attached to each radio-collar to enhance mark-resight estimates. Each deer observed during surveys was recorded as mark ID#, unmarked, or unidentified mark. We used program MARK (White and Burnham 1999), applying the immigration-emigration mixed logit-normal model (McClintock et al. 2008), to estimate mule deer abundance and confidence intervals. For mark-resight model evaluations, we examined parameter combinations of varying detection rates with survey occasion and whether individual sighting probabilities (i.e., individual heterogeneity) were constant or varied (σ2 = 0 or ≠ 0). Model selection procedures followed the information-theoretic approach of Burnham and Anderson (2002). RESULTS AND DISCUSSION Deer Captures and Survival The helicopter crew captured 264 fawns and 138 does in Dec and Jan 2011 and 142 does during March 2012. Seventeen fawn mortalities (6.4%; ultimate cause = 6 capture myopathy, 10 predation, 1 vehicle collision) occurred within the 10 day myopathy period. Doe mortalities totaled 5 (3.1%; ultimate cause = 4 capture myopathy, 1 vehicle collision) and 7 (4.9%; all capture myopathy) within 10 days of the Dec and Jan and March capture periods, respectively. Mortality rates 10 days post capture have varied between 2–3% for fawns and 0–3% for does since Jan 2008, but were higher this year. Dry conditions and abnormally high dust from pipeline construction relative to previous years may be related. Fawn survival from early December 2010 through mid June 2011 was similar (P > 0.05) among study areas ranging from 0.60 to 0.75 (Table 1; all areas combined = 0.69, 95% CI = 0.63–0.74, n = 247). General comparisons to previous years suggest relatively high fawn survival during winter 2009–2010 and relatively low survival during winter 2010–2011 (Fig. 2), which correlates to some degree to winter 53 �severity. Exceptions include North Ridge, which has been stable throughout, and Ryan Gulch where relatively low precision of estimates do not allow statistical discrimination (Fig. 2). Annual adult female survival varied from 0.68 (North Magnolia) to 0.93 (Ryan Gulch; Table 1) this year and was comparable among study areas during 2011/12 and to previous years (P > 0.05) with the exception of North Magnolia deer exhibiting lower survival this year than during 2009/10 (Anderson and Bishop 2010) and lower than Ryan Gulch this year. The relatively low adult female survival from North Magnolia may result in declining population trends if low survival persists. Spring Migration Patterns Collaboration with Idaho State University to direct a graduate student to address mule deer migration patterns in developed and undeveloped landscapes (funded from energy company contributions) has recently been completed. Two manuscripts have been prepared for publication; one is in review and the second has recently been accepted for publication (Lendrum et al. 2012). In addressing habitat selection during spring migration, Lendrum et al. (2012; Fig. 3) noted that mule deer migrating through the most developed landscapes exhibited longer step lengths (straight line distance between GPS locations) and selected habitats providing greater security cover versus more open areas with increased foraging opportunities through undeveloped landscapes. Migrating deer also selected areas closer to well pads, but avoided roads except in the highest developed areas where road densities may be too high for avoidance without significant deviations from traditional migration routes. These results suggest that deer may avoid disturbance where feasible or increase their rate of travel through highly developed landscapes where the energetic cost of avoidance may be too high. Mule Deer Body Condition Early-winter body condition measurements of adult female mule deer December 2011 were higher for deer from Ryan Gulch and North Ridge than previous years (P < 0.05), but were comparable for the North and South Magnolia deer (P > 0.05; Table 2). Comparisons among study areas in December suggested Ryan Gulch deer were in better condition that the other 3 areas. By late winter, however, body condition declined and deer from all study areas exhibited similar condition (Table 2). Improved condition of deer arriving on winter range was expected in December because of improved moisture conditions during spring and summer 2011. We were surprised that condition of North and South Magnolia deer did not mimic deer from the other 2 study areas, especially since there is summer ranges overlap with North Ridge and North Magnolia and Ryan Gulch and South Magnolia, respectively (Fig. 3). It was also surprising that deer from all study areas did not maintain higher condition by late winter given the mild winter conditions that were evident during 2011–2012, as was the case for North and South Magnolia deer during the mild winter of 2009–2010 (Table 2). Slightly higher late winter condition estimates were evident from all areas compared to 2009 and 2011, but these differences were not statistically significant (P > 0.05). December fawn weights were comparable to previous years and among study areas last year, with the exception of Ryan Gulch females which showed improvement over the previous year (Fig. 4). More detailed analyses will be conducted to identify factors potentially attributing to these observations. Neonate Survival To complete demographic parameters addressing mule deer–energy development interactions, CPW, Colorado State University, and ExxonMobil Production entered into a collaborative agreement to investigate neonate mule deer survival in developed and undeveloped landscapes (funded by ExxonMobil Production Co.). Mark Peterson (GRA) and Paul Doherty (CSU professor) will be assisting with this research, which began March 2012 and will continue for 3 years. To initiate this component of the study, we targeted 30 adult female mule deer/study area to receive Vaginal Implant Transmitters (VITs) during March 2012. Pregnancy rates during March were normal ranging from 96% to 98%/study area (n = 28– 46/area). March fetal counts ranged from 1.54 in South Magnolia to 1.92 in North Magnolia. We located 100 does with VITs and 97 neonates at parturition sites, with 85 neonates receiving radiocollars. Neonate 54 �survival will be monitored from June through December each year and compared among study areas relative to energy development activities. Mule Deer Population Estimates Mark-resight models that best predicted abundance estimates (lowest AICc; Burnham and Anderson 2002) exhibited variable sightability across surveys (Pt) for all study areas and homogenous individual sightability (σ2 = 0) for North Ridge and South Magnolia deer and variable individual sightability (σ2 ≠ 0) for North Magnolia and Ryan Gulch deer. North Ridge exhibited the highest deer density (18.3/km2), with comparably lower deer densities in the other 3 areas (7.4–9.2/km2; Table 3, Fig. 5). Populations appear stable over the 4 year monitoring period exhibiting annual variation less than the error around point estimates, with the exception of North Magnolia which exhibited a positive increase in 2011 from the previous 2 years (Fig. 5). Abundance estimates from 2012 were similarly precise from all 4 study areas with the mean Confidence Interval Coefficient of Variation (CICV) ranging from 0.13–0.17. Magnolia Habitat Treatments In proceeding with mule deer habitat improvements in heavy (South Magnolia) and light developed areas (North Magnolia), we completed pilot habitat treatments in January 2011 (116 acres total; Anderson and Bishop 2011) and January 2012 (54 acres) to assess mechanical treatment methods (hydro-ax, roller-chop, chain). All required NEPA surveys were completed this summer for the remaining sites (Fig. 6). The Biological Assessment should be completed by September 2012, allowing the remaining 1,030 acres to be treated using hydro-ax during fall–winter 2012–2013. Vegetation response in the pilot treatment sites was promising by fall 2011 (Fig. 6), likely due to the moist conditions present during the previous spring and summer. Dryer conditions this spring inhibited a similar response, but treatments completed last January exhibited surprisingly good grass and forb growth; shrub response wasn’t as vigorous as the previous year. All expenses addressing these habitat treatments will be covered through a Wildlife Management Plan agreement between CPW and ExxonMobil Production/XTO energy. SUMMARY AND COLLABORATIONS The goal of this study is to investigate habitat treatments and energy development practices that enhance mule deer populations exposed to extensive energy development activity. The information presented here provides data describing mule deer population parameters from the first 4.5 years of the pre-treatment period of a long-term study intended to address how mule deer react to landscape scale habitat and human activity modifications. The pretreatment period will continue through this fall to provide baseline data to compare against intended improvements in habitat conditions and evaluation of concentration and/or reduction in human development activities. Post-treatment monitoring will continue for 4–6 years to provide sufficient time to measure how deer respond to these changes. Based on the data collected thus far, deer from all areas appear to be in reasonably good condition and are exhibiting expected survival rates relative to changes in winter severity. We will continue to collect the various population and habitat use data across all study sites to evaluate the effectiveness of habitat improvements on winter range. This approach will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation dollars toward less or non-impacted areas. In a recent project conducted on the Uncomphahgre Plateau, Bergman et al. (2009) found that habitat treatments implemented in pinyon-juniper habitat in undeveloped areas were effective for deer. We are also evaluating deer behavioral responses to varying levels of development activity. This will allow us to assess the effectiveness of certain BMPs for reducing disturbance to wintering mule deer. Hay field improvements have been completed in the North Magnolia study area by Williams Production LMT Co. to fulfill a Wildlife Management Plan agreement with CPW; elk response has already been evident and mule deer response will continue to be monitored. Additional collaboration 55 �with Williams Production LMT Co. has produced a clustered development plan recently implemented in the Ryan Gulch study area and new technologies will be implemented to reduce human activity through remote monitoring of well pads and fluid collection systems. Recent collaboration agreements with ExxonMobil Production Co. and Colorado State University have provided graduate research opportunities to enhance data collection and inference about mule deer–energy development interactions. Additional funding and cooperative agreements will be necessary to sustain this project through completion (at least 2017 and preferably through 2019). We optimistically anticipate the opportunity to work cooperatively toward developing solutions for allowing the nation’s energy reserves to be developed in a manner that benefits wildlife and the people who value both the wildlife and energy resources of Colorado. LITERATURE CITED Anderson, C. R., Jr. 2009. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and D. J. Freddy. 2008a. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Final Study Plan, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and D. J. Freddy. 2008b. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation—Stage I, Objective 5: Patterns of mule deer distribution & movements. Pilot Study, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and C. J. Bishop. 2010. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, CO, USA. Anderson, C. R., Jr., and C. J. Bishop. 2011. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, CO, USA. Bartmann, R. M. 1975. Piceance deer study—population density and structure. Job Progress Report, Colorado Divison of Wildlife, Fort Collins, Colorado, USA. Bartmann, R. B., and S. F. Steinert. 1981. Distribution and movements of mule deer in the White River Drainage, Colorado. Special Report No. 51, Colorado Division of Wildlife, Fort Collins, Colorado, USA. Bartmann, R. M., G. C. White, and L. H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monograph No. 121. Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bergman, E. J., C. J. Bishop, D. J. Freddy, and G. C. White. 2009. Evaluation of winter range habitat treatments on over-winter survival and body condition of mule deer. Job Progress Report, Colorado Division of Wildlife, Ft. Collins, USA. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multi-model inference: a practical information-theoretic approach. Second edition. Springer-Verlag, New York, New York, USA. Cook, R. C., J. G. Cook, D. L. Murray, P. Zager, B. K. Johnson, and M. W. Gratson. 2001. Development of predictive models of nutritional condition for rocky mountain elk. Journal of Wildlife Management 65:973-987. Cook, R. C., T. R. Stephenson, W. L. Meyers, J. G. Cook, and L. A. Shipley. 2007. Validating predictive models of nutritional condition for mule deer. Journal of Wildlife Management 71:1934-1943. Cook, R. C., J. G. Cook, T. R. Stephenson, W. L. Meyers, S. M. McCorquodale, D. J. Vales, L. L. Irwin, P. Briggs Hall, R. D. Spencer, S. L. Murphie, K. A. Schoenecker, P. J. Miller. 2009. Revisions of rump fat and body scoring indices for deer, elk, and moose. Journal of Wildlife Management 74:880-896. 56 �Gibbs, H. D. 1978. Nutritional quality of mule deer foods, Piceance Basin, Colorado. Thesis, Colorado State University, Fort Collins, Colorado, USA. Kaplan, E. L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 52:457-481. Lendrum, P. E., C. R. Anderson, Jr., R. A. Long, J. K. Kie, and R. T. Bowyer. 2012. Habitat selection by mule deer during migration: effects of landscape structure and natural gas development. Ecosphere In press. McClintock, B. T., G. C. White, K. P. Burnham, and M. A. Pride. 2008. A generalized mixed effects model of abundance for mark—resight data when sampling is without replacement. Pages 271289 in D. L. Thompson, E. G. Cooch, and M. J. Conroy, editors, Modeling demographic processes is marked populations. Springer, New York, New York, USA. Pollock, K. H., S. R. Winterstein, C. M. Bunck, and P. C. Curtis. 1989. Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management 53:7-15. Stephenson, T. R., V. C. Bleich, B. M. Pierce, and G. P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. Stephenson, T. R., K. J. Hundertmark, C. C. Swartz, and V. Van Ballenberghe. 1998. Predicting body fat and mass in moose with untrasonography. Canadian Journal of Zoology 76:717-722. Unsworth, J. W., D. F. Pack, G. C. White, and R. M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked individuals. Bird Study 46:120-139. White, C. C., and B. C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. Prepared by Charles R. Anderson, Jr., Wildlife Researcher 57 �Table 1. Survival rate estimates (Ŝ) of fawn (3 Dec. 2011–18 June 2012) and adult female (1 July 2011– 30 June 2012) mule deer from 4 winter range study areas of the Piceance Basin in northwest Colorado. Cohort Study area Initial sample size (n) March doe samplea (n) Ŝ (95% CI) Fawns Ryan Gulch 57 0.600 (0.466–0.734) South Magnolia 55 0.745 (0.630–0.861) North Magnolia 56 0.721 (0.601–0.842) North Ridge 73 0.681 (0.578–0.784) Adult females Ryan Gulch 44 67 0.927 (0.858–0.997) South Magnolia 30 45 0.903 (0.810–0.997) North Magnolia 31 49 0.683 (0.536–0.830) North Ridge 35 60 0.803 (0.698–0.908) a Adult female sample sizes following capture and radio-collaring efforts March, 2012. 58 �Table 2. Mean rump fat (mm), Body Condition Score (BCSa), and % body fat (% fat) of adult female mule deer from 4 study areas in the Piceance Basin of northwest Colorado, March and December, 2009–2012. Values in parentheses = SD. March 2009 December 2009 BCS % fat Rump fat BCS March 2010 Study Area Rump fat % fat Rump fat BCS % fat Ryan Gulch 1.73 (1.78) 2.66 (0.55) 7.54 (1.80) 8.35 (6.36) 4.06 (1.13) 12.96 (4.53) 2.31 (1.44) 2.35 (0.48) 6.69 (1.58) South Magnolia 1.47 (0.68) 2.50 (0.60) 7.26 (1.82) 10.05 (6.19) 4.07 (1.21) 13.46 (4.96) 3.12 (2.20) 2.64 (0.59) 7.70 (2.01) North Magnolia 1.30 (0.79) 2.56 (0.68) 6.96 (2.23) 10.67 (5.76) 4.25 (0.96) 13.92 (3.92) 3.15 (2.34) 2.85 (0.53) 8.28 (1.86) North Ridge 1.57 (1.22) 2.60 (0.56) 7.28 (1.66) 5.25 (5.65) 3.63 (1.11) 11.02 (4.54) 1.77 (1.11) 2.42 (0.49) 6.83 (1.50) March 2011 December 2011 Table 2. Continued. December 2010 Study Area Rump fat BCS % fat Rump fat Ryan Gulch 7.75 (6.15) 3.34 (0.98) 10.82 (4.32) 1.55 (0.60) 2.53 (0.42) 7.05 (1.20) 13.41 (6.93) 4.21 (1.17) 13.17 (3.64) South Magnolia 9.85 (6.78) 3.30 (0.61) 11.21 (3.32) 1.65 (0.75) 2.35 (0.50) 6.56 (1.49) 7.53 (4.66) 3.37 (0.76) North Magnolia 9.55 (6.49) 2.56 (0.68) 11.65 (4.86) 1.65 (0.67) 2.53 (0.49) 7.06 (1.35) 9.43 (6.41) 3.79 (0.93) 11.15 (3.57) North Ridge 6.14 (5.29) 3.32 (0.82) 10.32 (3.39) 1.45 (0.76) 2.24 (0.49) 6.24 (1.45) 9.81 (5.81) 3.62 (1.00) 11.22 (3.38) 59 BCS % fat Rump fat BCS % fat 9.95 (2.73) �Table 2. Continued. March 2012 Study Area Rump fat Ryan Gulch 2.15 (1.44) 2.74 (0.44) 7.22 (1.16) South Magnolia 1.71 (0.76) 2.58 (0.36) 6.97 (1.12) North Magnolia 1.87 (0.78) 2.85 (0.33) 7.65 (0.94) North Ridge 2.24 (1.58) 2.70 (0.35) 7.26 (1.05) a BCS % fat Body condition score taken from palpations of the rump following Cook et al. (2009). 60 �Table 3. Mark-resight abundance (N) and density estimates of mule deer from 4 winter range herd segments in the Piceance Basin, northwest Colorado, 27 March–4 April 2012. Data represent 4 helicopter resight surveys from North Ridge and North Magnolia and 5 resight surveys from Ryan Gulch and South Magnolia. Study area Mean No. sighted Mean No. marked N (95% CI) Density (deer/km2) Ryan Gulch 268 24 1,048 (897–1,243) 7.4 South Magnolia 161 25 630 (556–724) 7.6 North Magnolia 267 32 727 (648–840) 9.2 North Ridge 319 34 972 (862–1,113) 18.3 61 �Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, summer 2012 (Accessed http://cogcc.state.co.us/ Aug. 8, 2012). 62 �Figure 2. Over-winter (Dec–Mar & June) mule deer fawn survival (Ŝ) from 4 study areas in the Piceance Basin, northwest Colorado, 2008/09 (red lines), 2009/10 (orange lines), 2010/11 (blue lines), and 2011/12 (black lines). Solid lines = Ŝ and dashed lines = 95% CI. Comparable data among years December– March 2008–2009 and 2009–2010 due to premature collar drop and December–mid-June 2010–2011 and 2011–2012. 63 �Figure 3. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012). 64 �Figure 4. Mean male and female fawn weights and 95% CI (error bars) from 4 mule deer study areas in the Piceance Basin, northwest Colorado, December 2008–2011. 65 �Figure 5. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2012. 66 �Figure 6. Habitat treatment site delineations in 2 mule deer study areas (600 acres each) of the Piceance Basin, northwest Colorado (Top; cyan and yellow polygons have been completed and remaining sites are scheduled for treatment fall/winter 2012/13). January 2011 hydro-ax treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 67 �Colorado Parks and Wildlife July 2011 – June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 2 Federal Aid Project No. W-185-R : : : : Parks and Wildlife Mammals Research Deer Conservation Evaluation of Winter Range Habitat Treatments On Over-winter Survival and Body Condition of Mule Deer Period Covered: July 1, 2011 - June 30, 2012 Author: E.J. Bergman; project cooperators, C.J. Bishop, D.J. Freddy, G.C. White and P. Doherty Personnel: C. Anderson, L. Baeten, D. Baker, B. Banulis, J. Boss, A. Cline, D. Coven, M. Cowardin, K. Crane, R. Del Piccolo, B. deVergie, B. Diamond, K. Duckett, S. Duckett, J. Garner, D. Hale, C. Harty, A. Holland, E. Joyce, D. Kowalski, B. Lamont, R. Lockwood, S. Lockwood, D. Lucchesi, D. Masden, J. McMillan, M. Michaels, G. Miller, Mike Miller, Melody Miller, C. Santana, M. Sirochman, T. Sirochman, M. Stenson, R. Swygman, C. Tucker, D. Walsh, S. Waters, B. Watkins, P. Will, L. Wolfe, V. Yavovich, K. Yeager, M. Zeaman, CPW, L. Carpenter - Wildlife Management Institute, D. Felix, L. Felix - Olathe Spray Service, P. Johnston, M. Keech, D. Rivers, J. Rowe, L. Shelton, M. Shelton, R. Swisher, S. Swisher - Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Between November 2004 and June 2009 we conducted a five year, multi-area study to assess the impacts of landscape level winter range habitat improvement efforts on mule deer population performance. This study took place on the Uncompahgre Plateau and in adjacent valleys in southwest Colorado. We measured over-winter fawn survival and deer abundance annually on 5 study areas. Four study areas were permanently located, whereas location of the fifth area varied each year to accommodate the variability in habitat treatments over the southern half of the Uncompahgre Plateau. Additionally, on 2 of the study areas we estimated late winter body condition of adult female deer. Compared to results from other research throughout the West, as well as on the Uncompahgre Plateau, survival estimates for 6-month old mule deer fawns were highly variable between areas, and tended to be near published long term averages. Estimated survival rates from this study ranged between 0.359 (SE = 0.0950) and 0.933 (SE = 0.0648). Survival models confirmed that areas that have received advanced habitat treatments have higher fawn survival. Deer abundance on the study areas varied between winters, but in general abundance estimates did not show increasing trends. A slight decrease in density between the first and last years of the study was observed in reference study units. Major fluctuations within abundance and density estimates were attributed to animal movements and winter severity. Based on estimates of total body fat for adult female deer, a distinction between treatment and reference study areas did occur, with body condition parameters indicating that late winter body condition of adult female deer on the treated 68 �study area was higher. Results from overwinter fawn survival work have been submitted to the Journal of Wildlife Management for peer review. Final revisions of density and abundance results will be completed during the fall of 2012 and spring of 2013 and submitted for peer-reviewed publication upon completion. 69 �WILDLIFE RESEARCH REPORT EVALUATION OF WINTER RANGE HABITAT TREATMENTS ON OVER-WINTER SURVIVAL AND BODY CONDITION OF MULE DEER ERIC J. BERGMAN P. N. OBJECTIVES To determine whether mechanical/chemical treatments of native habitat vegetation increases over-winter mule deer fawn survival, adult doe body condition, and localized deer densities on the Uncompahgre Plateau in southwest Colorado and to conduct a simulation based optimization study to determine optimal management strategies of deer under variable environmental, habitat and harvest conditions. SEGMENT OBJECTIVES 1. Complete all portions of dissertation requirements of PhD through Colorado State University. 2. Complete revision for density and body condition components of the study. 3. Submit and revise 3 chapters of dissertation work as part of the professional peer review process. INTRODUCTION A common trend among many terrestrial, mammalian systems is a tendency to cycle between population highs and lows (Jedrzejewska and Jedrzejewski 1998, Krebs et al. 2001, Clutton-Brock and Pemberton 2004). While the true cause of these cycles is likely a merger of habitat quality, weather, disease, predation, hunting, competition and community population dynamics, it is often necessary or intriguing for wildlife managers and ecologists to identify the primary limiting factor to population growth. Without exception, mule deer populations have also demonstrated a tendency to show large fluctuations. Several dramatic declines have been observed since the turn of the 19th century (Connolly 1981, Gill 2001, Hurley and Zager 2004). However, only one period of increase, a general trend during the 1940's and 1950's, has been noted. The most recent and pressing decline took place during the 1990's (Unsworth et al. 1999). Colorado has not escaped these tendencies, with certain parts of the state experiencing population declines by as much as 50% between the 1960's and present time (Gill 2001, B. Watkins personal communication). Primarily due to the value of mule deer as a big game hunting species, wildlife managers' challenges are two-fold: understanding the underlying causes of mule deer population change and managing populations to dampen the effects of these fluctuations. In Colorado, the role of habitat as the limiting factor for mule deer populations was recently tested. Specifically, the role of forage quality and quantity on over-winter fawn survival was tested using a treatment/reference cross-over design with ad libitum pelleted food supplements as a substitute for instantaneous high quality habitat improvements (Bishop et al. 2009). The primary hypothesis behind this research concerned the interaction between predation and nutrition. If supplemental forage treatments improved over-winter fawn survival (i.e., if predation did not prevent an increase), then it could be concluded that over-winter nutrition was the primary limiting factor on populations. As such, nutrition enhancement treatments increased the fawn survival rate by 0.22 (Bishop et al. 2009). This research effectively identified some of the underlying processes in mule deer population regulation, but did not test the effectiveness of acceptable habitat management techniques. Due to the undesirable effects of feeding wildlife (e.g., artificially elevating density, increased potential for disease transmission and cost), a more appropriate technique for achieving a high quality nutrition enhancement needed to be assessed. 70 �We completed a multi-year, multi-area study to assess the impacts of landscape level winter range treatments on mule deer population performance. We conducted the study on the Uncompahgre Plateau and adjacent valleys in southwest Colorado because this area had an active history of habitat treatments that were implemented in part to enhance deer populations. To assess the impacts of habitat treatments on mule deer in these areas, we measured over-winter fawn survival, mule deer density and late winter body condition. STUDY AREA At the onset of this study (Bergman et al. 2005), we identified 2 pairs of treatment/reference study areas, stratified into historically known high and low deer density areas. The selection process for these pairs of experimental units followed several strict guidelines: 1) Treatment/reference units could not be further than 10km apart, but needed to have adequate buffer to minimize the movement of animals between the treatment and reference areas. 2) Reference study areas could not have received any mechanical treatment during the past 30 years. 3) Strata were defined by winter range type (all experimental units had to be in pinyon/juniper winter range) and deer density. 4) Treatment units needed to have received mechanical treatment in the past, but also had to be capable of receiving further treatments during the study period. Each winter a 5th study area was added to increase the level of inference that could be drawn from this study. For each of the 4 winters covering the study period, this 5th study area shifted between 4 randomly selected areas. The treatment history on each of these additional study areas varied, but was representative of what can be expected of typical winter-range treatments. During the first winter of this study, this 5th study area fell on Shavano Valley. Treatments on Shavano Valley were primarily composed of roller-chopping in the higher pinyon/juniper range and were reseeded with browse species. During the second winter of the study, the 5th study area fell on the Colona Tract (~5km2) of Billy Creek State Wildlife Area (approximately 15km south of Montrose, CO). The treatment history of Colona Tract was primarily composed of brush mowing and chemical control of weeds and dry land fertilization of preferred species. During the third winter of the study, the 5th study area was located at McKenzie Buttes. The treatments at McKenzie Buttes were slightly older (10-15 years) and were also composed of rollerchopping. During the final year of the study, the 5th study area was located at Transfer Road. The treatments available to deer at Transfer Road were younger (1-2 years) and were composed of hydro-ax and some roller-chopping. The high density treatment area was located on the Billy Creek tract of Billy Creek State Wildlife Area (approximately 20km south of Montrose, CO). The high density reference area was located around Beaton Creek (approximately 15km south of Montrose, CO and approximately 5km north of Billy Creek State Wildlife Area). Both of the high density study areas were located in GMU 65 (DAU D-40). The low density treatment area was located on Peach Orchard Point, on/near Escalante State Wildlife Area (approximately 25km southwest of Delta, CO). The low density reference area was located on Sowbelly and Tatum draws (approximately 25km west of Delta, CO and approximately 8km from Peach Orchard Point). Both of the low density study areas were located in GMU 62 (DAU D-19). All of the other study areas, mentioned above, were also located in GMU 62 (DAU D-19) to the west of Montrose, CO. METHODS Twenty-five mule deer fawns were captured and radio-collared in each of the 5 study areas. Fawns were captured via baited drop-nets (Ramsey 1968, Schmidt et al. 1978, Bartmann et al. 1992) and helicopter net-gunning (Barrett et al. 1982, van Reenen 1982) between mid-November and late- 71 �December. To make fawn collars temporary, one end of the collar was cut in half and reattached using rubber surgical tubing; fawns shed the collars after approximately 6 months. On a daily basis, from December through May, we monitored the radioed fawns in order to document live/death status. This allowed us to determine accurately the date of death and estimate the proximate cause of death. Daily monitoring was done from the ground to maximize efficient collection of mortalities and assessment of cause specific mortality. Weekly aerial telemetry flights were conducted to insure that all deer were heard at least once a week, allowing weekly survival estimates for each study area. To estimate body condition, an additional 30 adult female deer were captured via helicopter netgunning and fitted with temporary neckbands in late-February within each of the 2 high density study areas. For body condition work, we relied on methods that employed the use of ultrasonography to estimate total body fat (Stephenson et al. 1998, Cook 2000, Stephenson et al. 2002). Blood samples were also collected for endocrinology and pregnancy tests. During late winter (early-March) we estimated deer density on each of our study areas. Helicopter based mark-resight techniques were used for density estimation (Gill 1969, Bartmann et al. 1986, Kufeld et al. 1980, Freddy et al. 2004). Survival analyses were conducted on all years of data. In addition to including individual covariates (fawn sex and mass), we tested the role of habitat treatment history on survival. Estimating survival for study areas took place in several different forms. The simplest form was constant survival where all study areas were pooled and survival was estimated using a single parameter. The second simplest form was to estimate survival for each unique study area (i.e., 8 survival estimates were generated, hereafter “Area”). The remaining model structures allowed study areas to be partitioned according to treatment history. Derivations of these models that included year as either an additive or multiplicative effect were then built. All survival models were evaluated in program MARK using the known-fate model type with logit link function (White and Burnham 1999). All models were compared using Akaike's Information Criterion corrected for small sample size (Burnham and Anderson 2003). All abundance and density estimates were also computed using program MARK (White and Burnham 1999). Abundance models varied via the process used to estimate the detection probability of deer, but abundance estimates across areas and years were not pooled. RESULTS AND DISCUSSION Survival models indicate that advanced landscape treatments do benefit deer. Model structures that incorporate the landscape treatment history of an area outperformed those that did not accommodate treatment history (Table 1, Appendix 1). The top performing model allowed year and week to vary as an additive effect and incorporated fawn mass. Fawn sex did not add much additional strength to any given model. Of particular interest to this study is that models incorporating study area treatment level consistently improved the performance of simpler models that had identical structure, save this one aspect. Not surprisingly, allowing survival rates to vary by year was fundamental for a model to receive any model weight. Density and abundance estimates were collected during March for all study areas during the last four years of the study. Abundance estimates tended to fluctuate by year in each area, but no discernable trends were observed (Fig. 1, Appendix 1). Fluctuations were likely due to localized winter conditions and the concentrating or diluting of deer on our study areas. Overall, no major changes in density were 72 �overwhelmingly evident, although habitat treatments may have arrested population declines that were observed in reference areas (Fig. 1). Late winter body condition estimates for adult females were consistent during all years of this study. For the two study areas where body condition estimates were measured, multiple linear regression model results reflected the same trends that were observed in survival estimates. A distinction between treatment and reference study areas, based on body condition parameters, indicated that late winter body condition of adult female deer on the treated study area was higher (Table 2, Fig. 2). Progress towards completion of the requirements for a PhD was also made during the 2011-12 year. As of summer 2012, all coursework needed to meet scholastic requirements has been completed. Additionally, 1 dissertation chapter has been submitted to a peer reviewed journal and 2 additional chapters are in the internal review process. SUMMARY Survival rates for mule deer fawns across our study areas and across years ranged between 36% and 93%. Estimates of total deer density across our study areas continued to reflect historical estimates, but annual variation was observed. Overall, a consistent trend of higher survival of fawns and higher body condition of adult female deer was observed in treated study areas, indicating winter range treatments have a positive effect on survival. LITERATURE CITED Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M., L.H. Carpenter, R.A. Garrott, and D.C. Bowden. 1986. Accuracy of helicopter counts of mule deer in pinyon-juniper woodland. Wildlife Society Bulletin 14:356-363. —————, G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:5-39. Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172. Burnham, K.P. and D.R. Anderson. 2003. Model selection and multi-model inference. Springer, New York, USA. Clutton-Brock, T., and J. Pemberton, editors. 2004. Soay sheep: dynamics and selection in an island population. Cambridge University Press, UK. Connolly, G. E. 1981. Limiting factors and population regulation. Pages 245-285 in O. C. Wallmo, editor. Mule and black-tailed deer of North America. University of Nebraska Press, Lincoln, USA. Cook, R. C. 2000. Studies of body condition and reproductive physiology in Rocky Mountain Elk. Thesis, University of Idaho, Moscow, USA. Freddy, D.J., G.C. White, M.C. Kneeland, R.H. Kahn, J.W. Unsworth, W.J. DeVergie, V.K. Graham, J.H. Ellenberger, and C.H. Wagner. 2004. How many mule deer are there? Challenges of credibility in Colorado. Wildlife Society Bulletin 32:916-927. Gill, R.B. 1969. A quadrat count system for estimating game populations. Colorado Division of Game, Fish and Parks, Game Information Leaflet 76. Fort Collins, USA. ————— 2001. Declining mule deer populations in Colorado: reasons and responses. Colorado Division of Wildlife Special Report Number 77. Hurley, M., and P. Zager. 2004. Southeast mule deer ecology - Study I: Influence of predators on mule deer populations. Progress Report, Idaho Department of Fish and Game, Boise, USA. 73 �Jedrzejewska, B., and W. Jedrzejewski. 1998. Predation in Vertebrate Communities: the Białowieża Primeval Forest as a case study. Springer-Verlag, Berlin, Germany. Krebs, C.J., S. Boutin, and R. Boonstra, editors. 2001. Ecosystem dynamics of the boreal forest: the Kluane project. Oxford University Press, New York, New York, USA. Kufeld, R.C., J.H. Olterman, and D.C. Bowden. 1980. A helicopter quadrat census for mule deer on Uncompahgre Plateau, Colorado. Journal of Wildlife Management 44:632-639. Ramsey, C.W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187-190. Schmidt, R.L., W.H. Rutherford, and F.M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159-163. Stephenson, T.R., V.C. Bleich, B.M. Pierce, and G.P. Mulcahy. 2002. Validation of mule deer body composition using in vivo and post-mortem indices of nutritional condition. Wildlife Society Bulletin 30:557-564. ————— , T. R., K. J. Hundertmark, C. C. Schwartz, and V. Van Ballenberghe. 1998. Predicting body fat and body mass in moose with ultrasonography. Canadian Journal of Zoology 76:717722. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann. 1999. Mule deer survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408-421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. White, G.C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Prepared by Eric J. Bergman, Wildlife Researcher 74 �Table 1. Model selection results of overwinter survival analysis of 6-month old mule deer fawns from different study units in southwestern Colorado. Model selection is based on Akaike’s Information Criterion corrected for small sample size (AICc). Models were constructed with an intercept (Int) and year (Yr) as a 3-parameter offset. Models could be comprised of effects including year, week, mass, traditional treatments (Trt), advanced treatments (Ad. Trt) and individual study units (Area). Model # Model Structure Δ AICc AICc Weight Model Likelihood ka 1 Int + Yr + Week + Mass + Ad. Trt 0.00b 0.376 1.00 29 2 Int + Yr + Week + Mass + Sex + Ad. Trt 1.34 0.193 0.51 30 3 Int + Yr + Week + Mass + Trt + Ad. Trt 1.91 0.145 0.38 30 4 Int + Yr + Week + Mass + Sex + Trt + Ad. Trt 3.17 0.077 0.21 31 5 Int + Yr + Week + Mass 3.18 0.077 0.20 28 6 Int + Yr + Week + Mass + Sex 4.66 0.037 0.10 29 7 Int + Yr + Week + Mass + Trt 4.83 0.034 0.09 29 8 Int + Yr + Week + Mass + Area 5.16 0.028 0.08 35 9 Int + Yr + Week + Mass + Sex + Trt 6.39 0.015 0.04 30 10 Int + Yr + Week + Mass + Sex + Area 6.73 0.013 0.03 36 a Accounting for parameters is as follows: Int = 1, Yr = 3, Week = 23, Mass = 1, Trt = 1, Ad. Trt = 1, Sex = 1, Area = 7 b AICc value for the top model was 1404.77 Table 2. Cumulative model weights for body condition response variables from multiple linear regression models for adult female mule deer. Data from southwest Colorado during early March, 2007–2009. Model weights are based on Akaike’s Information Criterion corrected for small sample size (AICc). Response Variable %IFBF TT4 FT4 TT3 FT3 Cumulative Covariate AICc Weight Unit Year Chest Age Foot Pregnant 0.722 0.823 0.966 0.363 0.293 0.260 0.998 0.998 0.511 0.998 0.489 0.802 1.000 1.000 0.412 0.890 0.533 0.827 0.278 1.000 0.271 0.989 0.633 0.274 0.265 0.999 0.317 0.982 0.504 0.452 75 �Figure 1. Mule deer density estimates, with 95% confidence intervals, for 8 study units on the Uncompahgre Plateau in southwest Colorado. Northern study units (Sowbelly, Peach and Transfer) are depicted in panel A, whereas southern study units (Shavano, Colona, McKenzie, Buckhorn and BCSWA) are depicted in panel B. 76 �Figure 2. Scaled estimates of late winter percent ingest free body fat (%IFBF), with 95% confidence intervals, for adult female mule deer in southwest Colorado. Solid gray bars reflect estimates for my treatment study area (Billy Cree State Wildlife Area) and white bars reflect estimates for my reference study area (Buckhorn). Estimates and projection intervals were generated according to the model in which chest girth was held constant at the observed mean of 95.476 cm. 77 �APPENDIX I ABSTRACTS FROM DISSERTATION CHAPTERS EXPECTED FOR PUBLICATION The following abstracts have either been submitted to the Journal of Wildlife Management for publication, or they will be submitted during FY 2012-2013. EFFECT OF HABITAT MANAGEMENT ON OVERWINTER SURVIVAL OF MULE DEER FAWNS IN COLORADO Eric J. Bergman, Chad J. Bishop, David J. Freddy, Gary C. White, and Paul F. Doherty, Jr. ABSTRACT Wildlife managers and ecologists are often compelled to identify the primary limiting factor to population growth in order to facilitate population management. Due to their iconic status and economic value, mule deer (Odocoileus hemionus) are not exempt from this need. Habitat management, in the form of mechanical or chemical manipulation of the vegetative landscape, has been utilized as a population management strategy to bolster mule deer populations. Yet evaluation of this strategy in the form of deer population response has been lacking. To address a knowledge gap and to evaluate the effectiveness of habitat management as a deer population management strategy, we conducted a 4-year study that measured the overwinter survival of mule deer fawns on study units that had experienced different levels of habitat management efforts. Mule deer fawns that overwintered on areas that received both a traditional treatment as well as follow-up treatments experienced increased survival ( = 0.768, SE = 0.0851) over fawns on winter range that had only received traditional treatments or no habitat treatments at all ( = 0.675, SE = 0.112). When partitioned into different levels of treatment intensity, mule deer fawns inhabiting winter range that received both traditional treatments and follow-up treatments experienced higher survival ( = 0.768, SE = 0.0849) than fawns on units that experienced only traditional treatments ( = 0.687, SE = 0.108), which in turn experienced higher survival than fawns in areas that had received no habitat treatments ( = 0.669, SE = 0.113). Our study provides evidence supporting the long-held view that habitat management is a viable and economically feasible population management strategy for mule deer in pinyon pine (Pinyon edulis) - Utah juniper (Juniperus osteosperma) ecosystems. 78 �RESPONSE OF MULE DEER DENSITY TO HABITAT MANAGEMENT IN COLORADO Eric J. Bergman, Chad J. Bishop, David J. Freddy, Gary C. White, and Paul F. Doherty, Jr. ABSTRACT The suite of demands competing for wildlife management funds necessitates direct assessment of management decisions, especially when these decisions have direct costs, as well as tangible opportunity costs. A specific example of such a decision includes habitat management for mule deer (Odocoileus hemionus), for which estimating direct effects on abundance has been difficult. However, recent advancements in abundance estimation methodologies have made estimating abundance more possible than in the past. We conducted a mark-resight study that estimated mule deer abundance and density across multiple study units that had been exposed to different intensities of habitat treatments on the eastern slope of the Uncompahgre Plateau and in neighboring drainages of the San Juan mountain range in SW Colorado. Our treatments were comprised on common habitat management techniques including hyrdo-axe and roller-chopper disturbances, as well chemical control of weeds and reseeding of desirable mule deer browse species. Reference study units received no habitat management treatments. Based on model selection strategies, resighting probabilities (range 0.070–0.567) were best modeled as an interactive function of study unit and year, although sampling method proved to also be important in estimating resight probabilities. Abundance estimates across study areas were variable, although annual variation in estimates was greatest in reference study units. Total deer densities varied between 20–84 deer/km2 in southern study units and 4–12 deer/km2 in northern study units. A consistent pattern of higher deer density on advanced treatment study units was not observed despite its being the primary hypothesis of the study. We recommend that if population abundance and density are to be used as population response variables, they only be used in tandem with other, more sensitive parameters such as overwinter survival or late winter body condition. 79 �Colorado Division of Parks and Wildlife July 2011 − June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3001 4 Federal Aid Project No. W-185-R : : : : : Division of Parks and Wildlife Mammals Research Deer Conservation Development of an Automated Device for Collaring and Weighing Mule Deer Fawns Period Covered: July 1, 2011 − June 30, 2012 Authors: C. J. Bishop, M. W. Alldredge, D. P. Walsh, E. J. Bergman, and C. R. Anderson. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We designed and produced a trap-like device for mule deer that would automatically attach a radio collar to a ≥6-month-old fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. Our passive collaring device is designed to allow biologists and researchers to radio-collar, weigh, and identify sex of ≥6-month-old mule deer fawns with minimal expense and labor when compared to traditional mule deer capture techniques. This technique should significantly reduce stress that is typically associated with capture and handling and eliminate capturerelated mortality. We collaborated with students and faculty in the Mechanical Engineering Department at Colorado State University to produce a conceptual model and early prototype. We then worked with professional engineers at Dynamic Group Circuit Design in Fort Collins, Colorado, to produce a fullyfunctional prototype of the device. We conducted an extensive field evaluation of the device with freeranging mule deer during October-March, 2010-11, and January-March, 2012. We successfully collared, weighed, and identified sex of 6 different mule deer fawns across 4 winter range locations along Colorado’s northern Front Range during winter 2010-11. Collars were purposefully made to shed from deer within several weeks or months of being collared. Two fawns were successfully re-collared after they shed the first collars they received. Thus, we observed 8 successful collaring events involving 6 different fawns in 2010-11. Most fawns demonstrated minimal response to collaring events, either remaining in the device or calmly exiting. We successfully collared, weighed, and identified sex of 2 different mule deer fawns in the Piceance Basin of northwest Colorado during February-March 2012. We collared fewer fawns in winter 2011-12 than the previous winter in part because of a shortened evaluation period (i.e., 3 instead of 6 months). Winter conditions were mild overall during 2011-12, which likely contributed to the lower collaring rate since deer had ample foraging options and may not have been as strongly attracted to bait. During 2010-11, certain components of the collaring device failed to function optimally when temperatures dropped below approximately −15° C, while other components did not adequately withstand mule deer use under field conditions. Also, certain behaviors of mule deer when approaching and using the device created circumstances where it was possible to collar the same animal twice, which happened on one occasion. We incorporated a series of device modifications during summer-fall 2011 necessary to address these various issues. The device functioned well under field 80 �conditions during January-March 2012, indicating the modifications were effective. Our automated collaring device allowed mule deer fawns to be remotely collared, weighed, and sexed with minimal or no stress to the animals. However, fawns typically required one or more weeks of exposure to the device before they entered and accessed the bait. This slow acclimation period limited utility of the device when compared to traditional capture techniques used to collar fawns. Future work will focus on additional device modifications and altered baiting strategies that decrease fawn acclimation period, and in turn, increase collaring rates. 81 �WILDLIFE RESEARCH REPORT DEVELOPMENT OF AN AUTOMATED DEVICE FOR COLLARING AND WEIGHING MULE DEER FAWNS CHAD J. BISHOP, MATHEW W. ALLDREDGE, ERIC J. BERGMAN, DANIEL P. WALSH, AND CHARLES R. ANDERSON, JR. P. N. OBJECTIVE To develop and evaluate a trap-like device for mule deer that will automatically attach a radio collar to a ≥6-month-old deer fawn and record the fawn’s weight and sex, without requiring physical restraint or handling of the animal. SEGMENT OBJECTIVES 1. Evaluate effectiveness and functionality of an automated collaring device for collaring, weighing, and identifying sex of mule deer fawns during winter under free-ranging conditions. INTRODUCTION Colorado Parks and Wildlife (CPW) captures and radio-marks 6-month-old mule deer (Odocoileus hemionus) fawns each year to support research and management of mule deer. Approximately 240−300 fawns are captured annually to monitor survival among 4−5 populations distributed across western Colorado and an additional 100−350 fawns are captured as part of ongoing research studies. Other state agencies in the western United States capture large numbers of mule deer fawns annually also. Most capture is accomplished with net-guns fired from helicopters (Barrett et al. 1982, van Reenen 1982, Webb et al. 2008), which is becoming increasingly expensive (i.e., >$500 per captured deer). Also, net gunning is inherently dangerous with a small market, which at times limits availability of contractors. Drop nets (Ramsey 1968, Schmidt et al. 1978), clover traps (Clover 1956), drive nets (Beasom et al. 1980), and darting (Wolfe et al. 2004) are used occasionally in the western United States to capture deer, but these techniques can be time consuming and labor intensive. Many biologists lack time and resources given other job requirements to conduct such capture operations for any length of time. The increasing cost of helicopter net-gun capture coupled with increasing demand for capturing and radio-collaring 6-month-old fawns has created a need for another capture alternative. Specifically, there is need for a capture technique that is relatively inexpensive to employ considering both operating and personnel costs. In response to CPW’s capture needs, we conceived the idea of an automated marking device for ≥6-month-old deer fawns that would attach a radio collar and record weight and sex without physically restraining the animal or requiring handling. The idea of automatically attaching radio transmitters to animals is not new, although to our knowledge, there are no proven methods or devices for use on deer or other ungulates. Even a relatively expensive trap or device (e.g., >$5,000 ea.) would reduce CPW’s capture costs assuming the device could be reused over time with few maintenance expenses. Such a device would enable seasonal wildlife technicians or graduate students to radio-collar samples of deer fawns independently or with little assistance from researchers and biologists because no animal handling would be required. We want the device to record weight and sex because these variables are useful covariates in survival analyses and are typically measured when fawns are captured and handled. A passive marking device would minimize animal stress associated with capture and should not cause capture-related mortality. The large-mammal capture techniques described above place 82 �considerable, temporary stress on animals as part of netting and handling. Roughly 2-3% of animals typically die from capture-related injuries or stresses under routine capture conditions. Thus, successful development of a passive marking system would reduce CPW’s operating expenses and improve animal welfare. Therefore, we designed, produced, and evaluated an automated device for collaring, weighing, and identifying sex of mule deer fawns during winter under free-ranging conditions. STUDY AREA We worked with captive deer at the Foothills Wildlife Research Facility (FWRF) in Fort Collins, Colorado, when designing the device and evaluating initial prototypes. We conducted subsequent evaluations of the collaring device with free-ranging deer in various field locations. During 2010-11, we conducted field evaluations with free-ranging deer at 5 sites along Colorado’s northern Front Range: 1) Horsetooth Reservoir, west of Fort Collins, private land 2) Masonville, southwest of Fort Collins, private land, 3) Red Feather, northwest of Fort Collins, private land, 4) Hall Ranch, west of Lyons, Boulder County Parks and Open Space, and 5) Heil Valley Ranch, southwest of Lyons, Boulder County Parks and Open Space. During 2012, we conducted field evaluations with free-ranging deer at Hall Ranch (Jan) and in the Piceance Basin southwest of Meeker, Colorado (Feb-Mar). METHODS We identified detailed specifications to guide the design and development of an automated collaring device and sought assistance from Colorado State University’s Mechanical Engineering Department. The collaring device became a senior design project for 6 CSU engineering students during the 2008-09 school year. We met with the students weekly and provided them a materials budget of $10,000 to produce a prototype device. We conducted staged evaluations of device components during the year by working with captive deer at FWRF. We also conducted limited evaluations with freeranging deer during spring 2009. Field evaluations focused primarily on how deer utilized and interacted with the device to guide subsequent design and development decisions. We documented utilization and interactions using direct observation and motion-sensor digital cameras. We relied exclusively on digital cameras when we were not on-site during an evaluation. Automation of the collaring device was disabled any time we were not present to prevent any potential harm to deer. Following preliminary field evaluations, we refined our design specifications and developed a contract with Dynamic Group Circuit Design (DGCD), Fort Collins, Colorado, to produce a fullyfunctional prototype device. We routinely met with electrical engineers from DGCD, and a mechanical engineer subcontracted by DGCD, during 2009-10. These meetings ensured that our device specifications were being satisfactorily met from both engineering and deer biology perspectives. Working with DGCD, we produced a fully-functional prototype device in 2010 that met our design specifications as set forth in the contract. The prototype device comprises an aluminum cage attached to a bait compartment (Fig. 1). Deer enter the device through an adjustable opening at the front of the cage. The adjustable opening can be used to deter entry of larger animals by adjusting both width and height. The sides of the cage comprise one-way gates that prevent entry into the device but allow an animal to exit the device at any point. The bait compartment is accessed through an opening positioned at the rear of the cage. An expandable radio collar is placed in this opening by extending it around four rectangular, aluminum plates that hold the collar in the fully-expanded position (Fig. 2). Radio collars are made expandable by attaching springs to each end of the transmitter; that is, springs are used in place of belting on standard radio collars. Clear plexiglass separates the cage from the bait compartment to maximize visibility. A deer is able to extend its head and neck through the expanded radio collar positioned in the rear opening to access the bait in the bait compartment, which is the only access point to the bait (i.e., it cannot be reached by an animal 83 �outside of the device). The floor of the cage is a scale that continuously records weight and informs device operation. Only animals in a specified weight range can be collared, which allows the user to target fawns and avoid collaring adult deer. Specifically, the mechanism that releases the collar around a deer’s neck will not trigger when an animal is too heavy or too light. Also, an actuator moves a plexiglass plate into the space between the rear cage opening and the bait pan, preventing animals outside of the weight range from accessing the bait. Shortly after a non-target animal exits the device, the collar release mechanism is once again able to be released (when triggered) and the actuator lowers the plexiglass plate so that the bait is accessible. To prevent an animal from being collared twice, a loop antenna is placed around the entrance to the cage and connected to a radio frequency identification (RFID) reader. All collars used with the device include a small RFID transponder sewn into the collar material. If a previously-collared fawn enters the cage, the RFID transponder is detected, which in turn prevents the collar from being released and activates the actuator to block access to the bait. If a deer enters the cage that is in the specified weight range and has not been previously collared, the collar will release around the deer’s neck once it accesses the bait. The collar release is triggered when a deer’s head breaks an infrared beam positioned immediately above the bait pan. The collar is released by activating a solenoid, which in turn releases a lever or trigger that causes the upper 2 aluminum plates holding the expanded collar in place to collapse (Figs. 3 and 4). The collar is then situated around the deer’s neck. In 2011, we replaced the release lever with an archery caliper release in an attempt to improve the release mechanism. When the collar is released, 2 different cameras are immediately activated to take a series of 3 photographs each. One camera is positioned in the back of the bait compartment and set to take a close-up photo of the top of the deer’s head. The second camera is positioned in the floor of the cage and set to take a photo of the deer’s abdomen and groin. These cameras are activated only when a collar is released and facilitate determination of deer sex. In 2011, we removed the floor camera after determining it was not necessary or effective for identifying deer sex. Last, when a collar is released, the device records and stores the weight of the deer. An external computer can be hooked up to the device to change program settings, remotely operate the device, and upload weight data. The device is powered by a 12 volt battery that must be recharged every 2-3 days assuming continuous operation. DGCD prepared a user’s manual that explains device operation and detailed schematics to allow future production. We evaluated effectiveness of the device in the field during October-March 2010-11 and JanuaryMarch 2012. Initially, we only set the device with a collar in place when we were present and able to directly observe deer interactions with the device. After collaring several animals in this manner and troubleshooting problems with the device, we set the device to operate remotely without an observer onsite, which is how it was intended to be used. RESULTS AND DISCUSSION 2010-2011 Field Evaluation We began baiting sites at Horsetooth Reservoir and Masonville on October 21, 2010, to attract deer for evaluating the device. We baited sites with alfalfa hay, apple pulp, dried fruit, and cereal. We baited several other sites briefly but discontinued baiting due to lack of deer use. Deer immediately responded to bait at Horsetooth Reservoir and began accessing the bait daily. On October 26, we placed the collaring device on site and began encouraging deer to walk into the device by placing bait on the scale inside the cage. On October 29, we documented a deer accessing the bait pan within the bait compartment for the first time. In the following weeks, we continued to periodically document deer entering the device and accessing the bait pan, although malfunctioning of the device prevented deer from being collared. One malfunction occurred because an electrical signal emitted from a camera placed at the entry of the device interfered with the RFID reader, which ultimately prevented fawns from being 84 �collared. It took roughly a week to diagnose the problem, which was corrected by simply removing the camera from the entry of the device. This particular camera was not wired into the device and was not critical to device functioning. We deemed that this camera was unnecessary and would be more useful if placed approximately 5 meters away from the trap to better document deer use and behavior. A second malfunction occurred because the scale did not have adequate support underneath and touched the ground, thereby giving inaccurate weight readings, which also prevented deer from being collared. We corrected this particular problem by welding an aluminum frame to better support the scale. Once these problems were corrected and other adjustments were made, we remotely collared our first fawn (female) on November 17, 2010. The fawn showed little reaction to the collaring event, calmly exiting the trap shortly after receiving the collar. The fawn’s weight and sex were successfully recorded. Sex was positively confirmed based on a photograph of the fawn’s head taken by the camera positioned in the bait compartment. We continued to monitor the device at Horsetooth Reservoir because there were adequate numbers of uncollared fawns in the area. However, we continued to encounter various problems with the device that affected functionality. Most notably, the collar release mechanism began failing to release the collar when a fawn was in position. We quickly determined that device controls were working properly and that an electrical signal was successfully being sent to the solenoid when an uncollared fawn was in position accessing the bait. The source of the problem was a mechanical failing associated with the release mechanism itself. When an expanded collar was in place (i.e., in a fully-expanded state), the tension of the collar sometimes prevented the release lever from moving enough to release the aluminum plates holding the collar in position. Once aware of the problem, we began making adjustments to the release mechanism to improve its functionality. Another problem we identified was that fawns were placing their front hooves on a piece of metal trim at the front of the cage when accessing the bait, which led to inaccurate weight readings and missed opportunities to collar fawns. We corrected this problem by placing a plastic shield above the metal trim so that deer could no longer place hooves on the metal trim. Following this modification, the entire floor surface of the cage comprised only the scale. We also noted that small fawns accessing the bait sometimes failed to break the infrared beam extending across the center of the bait pan, thereby failing to be collared. Thus, we adjusted the positioning of the bait pan to make sure that fawns successfully broke the infrared beam when accessing the bait, regardless of size. Once these changes were made, we successfully collared two more fawns (1 male and 1 female) on successive days, December 13 and 14, 2010. Also, the female fawn that was collared on November 17 shed its collar on December 13 and was successfully recollared on December 20. On December 21, the actuator that opens and closes the bait door short-circuited in response to cold, snowy weather and damaged the circuit board that controls operation of the device. The actuator was positioned such that moisture could enter it. The moisture, in combination with cold temperatures, caused the failure. It became evident at this point that future device modifications would likely require a heavier-duty actuator. However, until a new actuator could be researched, tested, and installed, DGCD used the same actuator and positioned it differently so that it was less likely to take on moisture. DGCD also replaced the circuit board to restore functionality of the collaring device. Several weeks were required to make these modifications, causing the device to be inoperable from December 21, 2010, through January 15, 2011. On January 20, we recollared the female fawn that was initially collared on December 14 (it shed the first collar on January 13). We then moved the device to the Masonville bait site on January 21, after documenting 5 successful collaring events at Horsetooth Reservoir. The Masonville bait site was regularly visited by 4 bucks, 3 does, and 2 fawns. The fawns were aggressively chased by the 4 bucks once we put the collaring device in place and restricted the amount of bait available outside of the collaring device. We solved this problem by creating a separate bait site for the bucks a short distance away. It took one week before the fawns at Masonville became comfortable entering the collaring device and accessing the bait in the bait pan. We did not put a collar in place 85 �initially because we speculated that the fawns would be more likely to access the bait pan for the first time if they were not required to extend their head through the collar. Once one of the fawns became acclimated and we put a collar in the device, the bait door/actuator began malfunctioning again, preventing the fawn from being collared. The malfunctioning was apparently related to cold temperatures. The bait door/actuator began functioning correctly again several days later and we collared a male fawn on February 4, 2011. The only other fawn on site showed no interest in accessing the bait in the bait pan during the ensuing week. Thus, we stopped baiting the site on February 12 and moved the device to the Red Feather site on February 14. Several of the gate arms that prevent deer entry into the sides of the device had been damaged by deer over the course of the winter. During February 14−20, as deer became accustomed to the collaring device, we replaced all gate arms with a new, more durable hinge system. We then resumed normal operations and collared our 7th fawn (female) on February 27, 2011. Unfortunately, the RFID reader failed to detect this collared fawn the following day, allowing the fawn to receive a second collar on February 28. We suspended collaring efforts for several days evaluating the RFID failure. It became evident that if a collared fawn entered the device quickly, it could go undetected by the RFID reader. We were aware of this potential problem, but this was the first time it actually occurred. We documented no ill effects of the second collar on the fawn. Realizing the odds of a double-collaring event were low, we resumed collaring efforts on approximately March 6. Incidentally, the odds of the double-collared fawn receiving a third collar were essentially zero because the fawn now had two RFID transponders. We made note that the RFID problem would need to be resolved with a device modification during the following year. The other couple of fawns routinely visiting the site were reluctant to access the bait pan. On March 17, we moved the collaring device to the Heil Valley Ranch site on Boulder County Parks and Open Space land. Deer regularly visiting the Heil site included 4 bucks, 2 does, and 1 fawn. We were unable to keep the bucks from being aggressive toward the does and fawn around the collaring device, which prevented the fawn from entering the device. In response, we moved the device to the Hall Ranch bait site on March 24, 2011, where 3-4 bucks, 2-3 does, and 1-3 fawns were using the site. Deer acclimated quickly to the collaring device and we collared our 8th fawn on March 28th, immediately after placing the collar in the device. A few days later we concluded the field evaluation because weather was turning warm, green forage was abundant, and bears were coming out of hibernation. 2011 Device Modifications During our 2010-11 winter field evaluation, we documented a number of issues with the collaring device that needed resolved. During summer-fall 2011, working with DGCD, we made several modifications to the device to address these issues. • Issue: The solenoid release mechanism occasionally failed to release the collar even when the solenoid was triggered. Modification: We evaluated and incorporated an alternative release mechanism that used an archery caliper release instead of the existing metal, latch system. • Issue: We documented several scenarios that could allow a fawn to receive a second collar. First, if a collared fawn extended its head through the entry to the device and was detected by the RFID reader but failed to move forward onto the scale for ≥30 seconds, the bait door moved back into the open position. Second, if a collared fawn was on the scale for >15 minutes (i.e., bedded down on the scale), the scale re-zeroed and the door moved back into the open position. At this point another fawn could step into the device, which would indicate a correct weight range, and the collared fawn could receive a second collar if it then accessed the bait. Third, as we directly witnessed, if a collared fawn entered the device quickly, the RFID reader sometimes failed to detect the RFID transponder in the fawn’s collar. Modifications: We resolved these issues by reprogramming the device and increasing sensitivity of the RFID reader/antenna. 86 �• • Issue: The actuator that controls the bait door commonly malfunctioned in cold temperatures (i.e., ≤ −12 °C). We intend for the device to be fully functional at −32 °C. Modification: We researched other actuators and selected a higher quality unit that would be more likely to perform adequately under the desired conditions. We then evaluated the actuator under controlled temperature settings in a freezer to confirm functionality before installation in the collaring device. Issue: The camera mounted on the floor of the device commonly failed to provide useful images for identifying sex. The camera in the bait compartment positioned to take pictures of a fawn’s head provided conclusive evidence of sex, indicating the floor camera was unnecessary. Modification: We removed the floor-mounted camera from the device and eliminated the associated wiring and programming. 2012 Field Evaluation We made considerable progress evaluating and subsequently modifying the collaring device during 2010-2011, and therefore, we believed that a 3-month evaluation period during January-March 2012 would be sufficient for a follow-up field evaluation. We initially evaluated the collaring device during January 2012 at Hall Ranch near Lyons, Colorado. We began evaluating the collaring device on January 10. Unfortunately, the bait sites were visited primarily by adult males, limiting any opportunities to collar fawns. These adult males also appeared to prevent regular attendance at the bait site/collaring device by adult females and fawns that were in the area. The problem of adult males dominating a bait site is not unique to this study and has been documented over time when attempting to capture fawns where bait is used to attract animals to a trap (Colorado Parks and Wildlife, unpublished data). Given the challenges posed by adult males near Lyons, we moved the collaring device at the end of January to Piceance Basin, southwest of Meeker, Colorado, where a separate deer study was underway and could benefit from additional collared fawns. We also believed deer densities would be higher near our bait sites in Piceance Basin than our sites along Colorado’s northern Front Range, potentially offering more opportunities to collar fawns. We initiated our evaluation of the collaring device in Piceance Basin on February 5, 2012. We were unable to monitor the collaring device in the field on a daily basis given the distance from the original study area along the northern Front Range. Our first monitoring period occurred during February 5-10. We collared a male fawn weighing 66 lbs on February 7 during early evening. During February 1118, we baited the collaring device but did not monitor deer activity on site. We resumed direct field monitoring of the device during February 19-24. During this time, we consistently observed a mixture of does, fawns, and bucks on site but did not successfully collar a fawn. The previously collared fawn was routinely on site and often entered the collaring device. During February 25-March 3, we again baited the collaring device but did not conduct field observations. We resumed field monitoring during March 4-9. Deer consistently accessed the bait site during this period, typically with a group size of 6-7 deer that included 3-4 fawns. On March 9, we collared a female fawn weighing 63 lbs. We once again ceased direct field monitoring during March 10-18 and completed our final monitoring period during March 1921. Deer were active on site during this final evaluation period, including the previously collared fawns, although we were unable to collar any new fawns. We then ceased our evaluation of the collaring device for 2012, having collared 2 fawns during an approximately 1.5-month evaluation period in Piceance Basin. Our modifications to the collaring device in 2011 appeared to have improved functionality of the device. The only problem we documented during our field evaluation in 2012 was that the bait door often remained open when the first collared fawn reentered the device on subsequent occasions. While initially of concern, the bait door always closed when tested with other collars. Additionally, the bait door closed each time the second collared fawn reentered the device after having been collared. Thus, we concluded 87 �there was a problem with the RFID transponder placed in the first collar rather than a problem with the collaring device itself. Although the device functioned well, the rate at which deer were collared was particularly slow. Our field observations indicate that fawns typically required one or more weeks of exposure before they entered the device and accessed the bait in the bait pan. Some fawns were reluctant to enter the device even after days or weeks of exposure. We tried various baiting strategies in an attempt to maximally encourage fawns to enter the device to access bait in the bait pan. If bait were only placed in the bait pan inside the device, deer groups were not attracted and retained at the site, and therefore, no fawns were present. If too much bait were placed outside the device, there was no incentive for fawns to enter the device and extend their head through the expanded collar to access bait in the bait pan. Generally speaking, we learned that some bait has to be placed outside the device to attract deer groups to the site and that some bait should be placed on the floor/scale to lure fawns into the device. We also tried placing all bait external to the device in buckets to limit the number of animals accessing bait at any given time and to make them more accustomed to placing their heads in an enclosed area to obtain the bait. However, our observations did not suggest this technique was any more effective at encouraging fawns to enter the device and extend their heads through the expanded collar to access bait in the pan. Winter weather conditions were overall mild during our study, particularly during winter 2011-12, which may partly explain the slow rate at which fawns were collared. During winter conditions exhibiting greater snow depths and lower temperatures with less forage available, we would expect fawns to have greater incentive to enter the device and extend their head through the expanded collar to access bait. SUMMARY We developed a fully-functional prototype of an automated collaring device for mule deer in collaboration with professional engineers. The automated collaring device is designed to allow biologists and researchers to radio-collar portions of their deer samples with minimal time and expense because no animal handling is required and deer can be collared at any time. Primary time commitments include baiting sites, moving the device(s) among sites, and adding collars to the device. The collaring device should also have distinct benefits for studies in urban environments by providing a non-invasive technique for collaring deer. We successfully collared 6 different fawns during Nov−Mar, 2011−12, along Colorado’s northern Front Range. We recollared 2 of these fawns after they shed their initial collars, resulting in 8 successful collaring events. Fawns generally showed minimal reaction to being collared. It was evident that fawns did not experience the type of stress that is associated with typical capture and handling techniques. We documented a number of functional issues with the collaring device in 2010-11, which we resolved through design modifications during summer-fall 2011. We conducted a follow-up field evaluation during January-March 2012 and collared 2 additional fawns during February and March in Piceance Basin. The largest drawback of the collaring device is the slow rate at which fawns were collared. Fawns typically required one or more weeks of exposure to the device before fully entering the device and extending their head through the expanded collar to access bait in the bait pan. This slow acclimation period limited utility of the device when compared to traditional capture techniques used to collar fawns. In the future, additional design modifications or more clever baiting strategies will be necessary to improve collaring rates. We also plan to evaluate placement of ≥2 collaring devices at the same site once a second collaring device is produced. With more collaring devices, potentially less bait would need to be placed external to the devices and deer might be more inclined to access bait in the bait pans within the collaring devices. 88 �LITERATURE CITED Barrett, M. W., J. W. Nolan, and L. D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108−114. Beasom, S. L., W. Evans, and L. Temple. 1980. The drive net for capturing western big game. Journal of Wildlife Management 44:478−480. Clover, M. R. 1956. Single-gate deer trap. California Fish and Game 42:199−201. Ramsey, C. W. 1968. A drop-net deer trap. Journal of Wildlife Management 32:187−190. Schmidt, R. L., W. H. Rutherford, and F. M. Bodenham. 1978. Colorado bighorn sheep-trapping techniques. Wildlife Society Bulletin 6:159−163. van Reenen, G. 1982. Field experience in the capture of red deer by helicopter in New Zealand with reference to post-capture sequela and management. Pages 408−421 in L. Nielsen, J. C. Haigh, and M. E. Fowler, editors. Chemical immobilization of North American wildlife. Wisconsin Humane Society, Milwaukee, USA. Webb, S. L., J. S. Lewis, D. G. Hewitt, M. W. Hellickson, and F. C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310−314. Wolfe, L. L., M. W. Miller, and E. S. Williams. 2004. Feasibility of “test-and-cull” for managing chronic wasting disease in urban mule deer. Wildlife Society Bulletin 32:500−505. Prepared by _______________________ Chad J. Bishop, Mammals Research Leader 89 �Figure 1. Automated collaring device for mule deer, comprising an aluminum cage and a bait compartment. Deer become collared by entering the cage and extending their head through an expanded radio collar when accessing bait. 90 �Figure 2. View of the radio collar and bait compartment of an automated collaring device for mule deer. To reach bait, deer must extend their head and neck through the expanded radio collar. 91 �Figure 3. View of the collar release mechanism in an automated collaring device for mule deer. 92 �Figure 4. Female mule deer fawn accessing bait by extending her head through an expanded radiocollar. 93 �Colorado Parks and Wildlife July 2011 – June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 3001 : : : : Parks and Wildlife Mammals Research Deer Conservation Assessment of survival and optimal harvest Strategies of adult male mule deer in Middle Park, Colorado W-185-R Period Covered: July 1, 2011 - June 30, 2012 Author: E.J. Bergman; Project Cooperators; C.J. Bishop, K. Oldham, and L. Sidener Personnel: G. Abram, G. Birch, J. Broderick, M. Crosby, B. Davies, T. Elm, D. Gillham, K. Holinka, A. Holland P. Lukacs, B. Manly, S. Murdoch, S. Schwab, S. Shepherd Colorado Parks and Wildlife R. Swisher, S. Swisher, T. McKendrick Quicksilver Air All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT We continued field work on a study designed to assess the survival and optimal harvest strategies of adult male mule deer in Middle Park, Colorado. Two years of baseline survival data for adult (≥ 1 yr. old) male deer were collected prior to termination of this project. During December (2011), 49 additional adult (≥ 1.5 years old) male deer were captured and radio collared, returning the radio collared sample to 100 animals at the start of the 2012 calendar year. The natural, annual survival rate for all deer for the period ending on the 14th of December (2011) was estimated at 0.820 (SE = 0.0394). From the 15th of December (2011) through the 31st of July (2012), survival was estimated at 0.919 (SE = 0.0275). Due to consternation expressed by a very select group of trophy hunters, the project was terminated in July of 2012. 94 �WILDLIFE RESEARCH REPORT ASSESSMENT OF SURVIVAL AND OPTIMAL HARVEST STRATEGIES OF ADULT MALE MULE DEER IN MIDDLE PARK, COLORADO ERIC J. BERGMAN P.N. OBJECTIVES SEGMENT OBJECTIVES 1. Continue field work in the form of capturing and radio collaring animals. 2. Collect survival data on radio collared deer and provide preliminary survival estimates for adult male mule deer. INTRODUCTION Historically, management of big game species has focused on the performance of adult females and the young of the year segments of the population. In the case of mule deer, this has been further refined to the aspects of annual (for adult females) and overwinter (for young of the year) survival. The performance of the male component of populations was deemed less important because it takes few males to provide adequate breeding coverage for the population, and historic harvest management objectives were set to maximize hunting opportunities. As long as sufficient numbers of males were available to breed females there was no desire to restrict hunting opportunity. However, during the past 10-15 years, the management of big game populations, and mule deer populations in particular, has shifted from the objective of providing maximal opportunity towards providing higher quality opportunities (Bishop et al. 2005b, Bergman et al. 2010). High quality opportunities are typically defined by hunters as a combination of the chance to see a greater number of male deer during the hunt, increased potential to harvest an older age class animal (i.e., an animal with more developed antler morphometry), but also reduced interaction and competition with other hunters. In response to this shift in hunter desires and concerns over declining mule deer numbers, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) implemented a statewide limitation in deer hunting in 1999. This statewide limitation gave CPW the ability to reduce total hunter numbers and to control the distribution of hunters throughout the state. Since 1999 Colorado’s deer herds have become composed of a greater number of males, yet little biological data on them exist. Also stemming from this change in harvest management was a new responsibility for Colorado’s terrestrial biologists and wildlife managers. Prior to 1999, licenses were sold over-the-counter and were not limited in number (i.e., any hunter who wished to purchase one was able to do so), and the decision of how many licenses to make available did not need to be considered. Since 1999, CPW has the added responsibility of deciding how many licenses should be allocated in each Data Analysis Unit (DAU). This decision must reflect a balance between meeting DAU population performance objectives, and maximizing hunter opportunity. Big game populations in Colorado are currently modeled using multiple sources of biological data (White and Lubow 2002). Model inputs include harvest estimates, young recruitment to December, and measured rates of survival of adult females and fawns. Also, the ratio of adult males to adult females is estimated and used to align models by minimizing the difference between observed and modeled values. Only rarely have the survival rates of adult males been measured. This gap in knowledge has historically been viewed as trivial and adult male survival rates have been assumed to be similar to the rates of females. Similarly, it has been assumed that natural survival rates (i.e., post hunt survival) of males do not geographically vary. However, model performance under these assumptions has been poor and the need to measure adult male survival as a parameter has increased. Presently, a number of 95 �population models in Colorado suggest that natural adult male survival may be lower than adult female survival, yet empirical data is lacking to verify these suppositions. Despite this apparent lack of information, survival of adult male mule deer and adult male blacktail deer are not completely novel parameters of interest (Pac and White 2007, Bender et al. 2004, Bleich et al. 2006, Bishop et al. 2005a, McCorquodale 1999). These studies also suggest that adult male mule deer survival tends to be lower than adult female survival when differences occur, further emphasizing the need to rigorously evaluate adult male survival rates. Bishop et al. (2005a) observed lower natural survival rates of adult males than adult females in southwest Idaho: differences were most apparent during winter in 2 of 3 study areas. Pac and White (2007) found that natural survival rates of yearling males in Montana were lower than the average adult female survival rate documented by Unsworth et al. (1999). Finally, Miller et al. (2008) found that adult male survival rates were lower than adult female survival rates in Colorado in response to chronic wasting disease (CWD). In particular to the population modeling interests of Colorado outside the CWD endemic area, the work conducted by Pac and White (2007) has had the greatest utility. This work focused on the survival of males under differing management scenarios and showed a shift in cause-specific mortality of males in areas where harvest was more restricted. It is currently unknown if survival rates would be similar between Montana and Colorado. Similarly, the likelihood of observing shifts in mortality sources is unknown. It has been demonstrated that adult female deer herds in Colorado tend to be habitat limited (Bishop et al. 2009, Bartmann et al. 1992), but the trade-off between harvest, habitat and survival in adult male mule deer has not been explored. An additional need in Colorado pertains to the harvest management of adult male mule deer. As discussed above, a large shift in mule deer herd size and structure occurred as a result of changes in harvest management. Overall, this shift has been viewed as positive by both CPW as well as the public. However, CPW maintains the responsibility of optimally managing the deer of Colorado and maximizing hunting opportunity under this new set of constraints. To date, CPW has had limited biological information and data to guide harvest management decisions. In particular for this issue, as Data Analysis Units (DAUs) reach and surpass their adult male: adult female ratio objectives, CPW typically responds by increasing the number of available hunting licenses. In situations where herds are continually lower than DAU objectives, available hunting licenses are reduced. What remains unknown about survival of adult male deer is at what level natural survival is reduced due to intraspecific competition (i.e., increased density of adult male deer). If, or when deer herds exceed the adult male: adult female objectives for DAUs, it is often assumed that the surplus of male deer remain in the population into perpetuity. However, this assumption is based on the premise that compensatory mortality does not occur. Similarly, it assumes that annual variation in survival is negligible. However, these assumptions are not biologically realistic. It is possible that herds with large post-hunt populations of adult males experience higher levels of non-harvest mortality. Under this scenario, harvest has not been optimized and more hunters could have been afforded the opportunity to hunt with no effect on post hunting season ratios of adult males to adult females. The most effective way to learn about the mortality process is via manipulative experimentation, but to date this topic has not been deemed a high enough priority to pursue. STUDY AREA This study took place in Middle Park, Colorado, within DAU D-9. Within D-9 are 6 Game Management Units (27,181, 18, 37, 371, and 28; Fig. 1). METHODS Capture of adult male deer was conducted in January and December of 2011. Capture was conducted via helicopter net-gunning (Webb et al. 2008, Potvin and Breton 1988, White and Bartmann 96 �1994, Barrett et al. 1982). All captures occurred after the completion of the 4th rifle hunting season, eliminating conflicts between capture efforts and hunting. All deer were fitted with expandable radio collars. All radio collars were equipped with mortality sensors that doubled in pulse rate after remaining motionless for 4 hours. Between the time of capture and mid-June, we used ground-based monitoring to determine the live/dead status of deer 3-4 times per week. Additionally, every 5-10 days we conducted a telemetry flight to detect any animals that hadn’t been heard from the ground during the preceding week. A general location was collected for each radio marked deer in early-March to determine if it had departed the GMU in which it had originally been captured. From mid-June through remainder of the summer, deer were monitored from the ground weekly and from the air once per month. When detected, all mortalities were investigated as quickly as possible to determine cause of death and to get an accurate estimate of the date of death. RESULTS AND DISCUSSION In December (2011), 49 deer were captured and radio collared. On one occasion, an animal suffered a fractured leg as part of the capture process and was subsequently euthanized at the capture site via gunshot to the head. No other capture related injuries or mortalities occurred, although one animal was killed via vehicular collision 2 days post capture. This animal was subsequently censored from survival analysis due to uncertainty if stress related to the capture process had influenced its fate. Survival of adult male deer between January 2011 and the 14th of December (2011) was estimated to be 0.820 (SE = 0.0394). There was no apparent difference between the north half the D-9 and the south half of D-9 (Table 1), validating the assumptions of the original study plan design. During the 2011 hunting seasons, a total of 31 radio collared bucks were harvested (Fig. 1). Due to mild winter conditions, survival from the 15th of December (2011) through the 31st of July (2012) was very high (0.909, SE = 0.0275). SUMMARY Project efforts were successful during the first two years of the study, although local resistance to the project remained high. Based on public meetings, the majority of hunters in the Middle Park area supported the project, although a very select group of trophy hunters remained opposed. Ultimately, CPW leadership determined that it “could not overcome the current opposition” and the study should not proceed. Thus, this research project has been terminated as of 7/12/2012. LITERATURE CITED Barrett, M.W., J.W. Nolan, and L.D. Roy. 1982. Evaluation of a hand-held net-gun to capture large mammals. Wildlife Society Bulletin 10:108-114. Bartmann, R.M., G.C. White, and L.H. Carpenter. 1992. Compensatory mortality in a Colorado mule deer population. Wildlife Monographs 121:1-39. Bender,L.C., G.A. Schirato, R.D. Spencer, K.R. McAllister, and B.L. Murphie. 2004. Survival, causespecific mortality, and harvesting of male black-tailed deer in Washington. Journal of Wildlife Management 68:870-878. Bergman, E.J., B.E. Watkins, C.J. Bishop, P.M. Lukacs, and M. Lloyd. 2010. Biological and socioeconomic effects of statewide limitation of deer licenses in Colorado. Journal of Wildlife Management. In Review. Bishop, C.J., J.W. Unsworth and E.O. Garton. 2005a. Mule deer survival among adjacent populations in southwest Idaho. Journal of Wildlife Management 69:311-321. Bishop, C.J., G.C. White, D.J. Freddy and B.E. Watkins. 2005b. Effect of limited antlered harvest on mule deer sex and age ratios. Wildlife Society Bulletin 33:662-668. 97 �Bishop, C.J., G.C. White, D.J. Freddy, B.E. Watkins, and T.R. Stephenson. 2009. Effect of enhanced nutrition on mule deer population rate of change. Wildlife Monographs 172:1-28. Bleich, V.C., B.M. Pierce, J.L. Jones and R.T. Bowyer. 2006. Variance in survival of young mule deer in the Sierra Nevada, California. California Fish and Game. 92:24-38. Miller, M.W., H.M. Swanson, L.L. Wolfe, F.G. Quatarone, S.L. Huwer, C.H. Southwick and P.M. Lukacs. 2008. Lions and prions and deer demise. Plos One 3:1-7. McCorquodale, S.M. 1999. Movements, survival, and mortality of black-tailed deer in the Klickitat Basin of Washington. Journal of Wildlife Management 63:861-871. Pac, D.F., and G.C. White. 2007. Survival and cause-specific mortality of male mule deer under different hunting regulations in the Bridger Mountains, Montana. Journal of Wildlife Management 71:816-827. Potvin, F., and L. Breton. 1988. Use of a net gun for capturing white-tailed deer, Odocoileusvirginianus, on Anticosti Island, Quebec. Canadian Field Naturalist 102:697-700. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann. 1999. Mule Deer Survival in Colorado, Idaho, and Montana. Journal of Wildlife Management 63:315-326. Webb, S.L., J.S. Lewis, D.G. Wewitt, M.W. Hellickson, and F.C. Bryant. 2008. Assessing the helicopter and net gun as a capture technique for white-tailed deer. Journal of Wildlife Management 72:310-314. White, G.C. and R.M. Bartmann. 1994. Drop nets versus helicopter net guns for capturing mule deer fawns. Wildlife Society Bulletin 22:248-252. White, G.C. and B.C. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife Management 66:300-309. Prepared by Eric J. Bergman, Wildlife Researcher 98 �Table 1. Model results for known-fate survival models based on mule deer buck data collected in Middle Park, Colorado. Model comparison is made via Akaike’s Information Criterion corrected for small sample size (AICc). Of interest to the original study design, there was no strong evidence that there was a difference in survival between the northern and southern halves (Area) of the study area. Model ∆AICc AICc Weight Likelihood Parameters Ŝ (Constant) 0.00 0.69 1.00 1 Ŝ (Area) 1.56 0.31 0.46 2 Ŝ (Week) 49.77 0.00 0.00 48 Ŝ (Area + Week) 51.37 0.00 0.00 49 Ŝ (Area*Week) 131.16 0.00 0.00 96 Figure 1. Fate and associated cause of death of 100 mule deer bucks between January 2011 and December 2011 in Middle Park, Colorado. 99 �Colorado Division of Parks and Wildlife July 2011 – June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3002 : : : : Division of Parks andWildlife Mammals Research Elk Conservation Evaluating solutions to reduce elk and mule deer damage on agricultural resources. Federal Aid Project No. Period Covered: July 1, 2011 – June 30, 2012 Author: H.E. Johnson; project cooperators, P. Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, C. Anderson, and J. Fischer. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Elk and mule deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural environments. This situation has generated significant challenges for wildlife agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage. One of the most severe areas of ungulate damage in Colorado has been the sunflower fields around Dove Creek. In this region, roughly a quarter of million dollars were annually paid to farmers between 2007 and 2009 for depredation caused by elk and deer. The main management tool used by Colorado Parks and Wildlife (CPW) to reduce ungulate damage has been the allocation of kill permits, distribution hunts, and private land only doe/cow hunts; however, tolerance for these permits has been low among local sportsman and the general public. Pressure from local sunflower growers over crop damage, and frustration from the general public over kill permits, generated the need for CPW to evaluate other management options for reducing elk and deer crop depredation. As a result, CPW partnered with wildlife damage researchers from the National Wildlife Research Center to find science-based solutions for reducing crop damage. Collaboratively, our goals are to 1) examine elk and deer distribution and migration patterns around agricultural areas to design public hunting opportunities to reduce depredation, 2) experimentally test a suite of non-lethal fencing techniques to minimize crop damage, and 3) map and model landscape characteristics associated with ungulate damage to specify more effective site-specific management techniques to minimize depredation. During FY11-12 we focused on collecting field data to meet project objectives. Specifically, we constructed experimental fence plots and monitored their effectiveness in reducing elk and deer damage (objective 2) and collared elk and deer to collect information about local movement and distribution patterns (data required to meet objectives 1 and 3). 100 �WILDLIFE RESEARCH REPORT EVALUATING SOLUTIONS TO REDUCE ELK AND MULE DEER DAMAGE ON AGRICULTURAL RESOURCES HEATHER E. JOHNSON P.N. OBJECTIVES To conduct a study on elk and mule deer around the agricultural fields of Dove Creek that 1) examines wild ungulate distribution patterns to design public hunting opportunities to reduce crop damage, 2) experimentally tests a suite of non-lethal fencing techniques to minimize crop depredation, and 3) maps and models landscape characteristics associated with damage to specify more effective site-specific management practices. SEGMENT OBJECTIVES 1. Implement the construction of experimental fence plots on sunflower fields in the vicinity of Dove Creek, including electric fences, temporary winged fences, and chemical repellent fences. 2. Collect field data on elk and deer damage to sunflowers in experimental fence plots throughout the growing season. 3. Capture and collar adult female elk and mule deer around agricultural fields in the vicinity of Dove Creek. INTRODUCTION Elk and deer provide important recreational, ecological, and economic benefits, but they can also cause substantial damage to agricultural resources in rural areas (Austin et al. 1998, Wisdom and Cook 2000). In Colorado, elk and deer crop depredation accounts for a majority of the wildlife damage claims in the state, and CPW is obligated to pay for those lost resources. In recent years, the agency has spent approximately $500,000 on an annual statewide basis to compensate farmers for ungulate depredation. This situation has generated significant challenges for CPW and other wildlife agencies that are responsible for maintaining viable ungulate populations while also minimizing crop damage (Van Tassell et al. 1999, Wagner et al. 1997, Hegel et al. 2009, Walter et al. 2010). Elk and deer crop depredation results from a combination of factors including the seasonal distribution and abundance of local forage resources, landscape configuration, and herd density patterns (Vecellio et al. 1994; Yoder 2002; Hegel et al. 2009). Damage can be highly variable within and among growing seasons, as local patterns in precipitation and temperature will alter the availability of native forage and the motivation of ungulates to feed on agricultural fields (Walter et al. 2010). The juxtaposition of cropland and wildland has also been found to be particularly important in driving damage rates, as those cultivated fields closer to cover experience more damage (Nixon et al. 1989, Hegel et al. 2009). Additionally, studies have found that ungulate damage is often caused by only a subset of individuals in the population, depending on the spatial and social structuring of the herd. These observations have critical implications for wildlife managers, as 1) management practices may be differentially effective based on the variability of native forage conditions and the spatial juxtaposition of other habitat features, and 2) management techniques targeted at specific animals may be more effective than implementing those techniques on the population at large (Blejwas et al. 2002, Hegel et al. 2009). As a result, it is important to understand both the spatial configuration of seasonal resources and the resource selection patterns of different segments of local ungulate populations to successfully identify strategies to reduce elk and deer crop damage (Hegel et al. 2009). 101 �One of the most significant hotspots of elk and mule deer depredation in Colorado has been in the vicinity of Dove Creek, where CPW paid roughly a quarter of million dollars annually to farmers between 2007 and 2009. High damage in this region has been primarily attributed to a recent switch in the crops that are locally grown. Farmers traditionally grew beans, spring and winter wheat, oats, alfalfa and grass hay which had minimal damage by wild ungulates. In recent years, however, local growers have planted sunflowers, a high-value seed oil crop used to produce biofuels, and a crop that is highly desirable to wild ungulates. In addition to this recent switch in crops, ungulate damage around Dove Creek is exacerbated by the spatial distribution of sunflower fields in relation to the surrounding wildlands (e.g., sagebrushmixed shrublands and piñon-juniper woodlands). The region is fractured with deep canyons that provide refugia for elk and deer, and fields adjacent to the canyon rims experience the greatest amount of depredation. With the substantial increase in biofuel production in the U.S. (World Resources Institute 2008), the agricultural conversion observed around Dove Creek will likely become common, as highpriced, crops replace more traditionally-grown, lower-cost crops (Walter et al. 2009). The main management tool available to CPW to reduce ungulate sunflower damage has been to increase harvest through the use of kill permits, distribution hunts, and private land only (PLO) doe/cow hunts, however tolerance for these permits has been low among local sportsman and the general public. Permits are typically allocated to farmers between June and August, when calves and fawns are still dependent on their mothers, reducing the acceptability of female hunts. Additionally, local elk and deer populations are near or below management objectives, creating a paradox where CPW ultimately wants to increase ungulate herds, but reduce crop depredation. Hunting is also economically important around Dove Creek, so there is a strong desire in the local community to have increased public hunting opportunities and reduced PLO damage hunts. Given pressure by farmers over elk and deer sunflower damage, and frustration by sportsmen and the public over kill permits, CPW wildlife managers were interested in finding alternative solutions for reducing sunflower depredation. As a result, personnel from CPW partnered with wildlife-damage researchers from the National Wildlife Research Center (NWRC) to find non-lethal science-based solutions for reducing sunflower depredation. Collaboratively, we developed a proposal to 1) identify public hunting strategies that reduce crop damage, 2) test a suite of non-lethal fencing techniques to minimize crop depredation, and 3) map and model landscape characteristics associated with damage behavior to specify more effective management practices (Johnson et al. 2011). Results from this study should enable CPW and local growers to reduce ungulate crop depredation, leading to a decrease in compensation payments, a decrease in kill permits/distribution hunts, and an increase in public hunting opportunities. In FY11-12 we focused on collecting field data to meet project objectives. Specifically, we constructed experimental fence plots and monitored their effectiveness in reducing elk and deer damage (objective 2) and collared elk and deer to collect information about local movement and distribution patterns (data required to meet objectives 1 and 3). STUDY AREA The area around Dove Creek, Colorado (Montezuma, San Miguel and Dolores counties) is comprised of a mixture of agricultural and public lands. This project focuses on the north half of CPW Game Management Unit 72 and the west half of 711 (the portion west of the Dolores River). The area is generally characterized as mountain shrubland interspersed with irrigated and dryland agricultural fields, ranging from 1,981 to 2,590 m in elevation. The mountain shrub habitat type is primarily composed of serviceberry (Amelanchier alnifolia), bitterbrush (Purshia tridentata), mountain mahogany (Cercocarpus montanus), squaw apple (Peraphyllum ramosissimum) and black sagebrush (Seriphidium novum). 102 �Sunflower fields around Dove Creek are spatially juxtaposed to deep canyons that provide refugia for elk, exacerbating ungulate damage on agricultural crops (Figure 1). METHODS Testing the effectiveness of different fence types for reducing ungulate damage During FY11-12 we constructed experimental fence plots to test the effectiveness of three nonlethal exclusionary fences for reducing elk and deer damage: a polyrope electric fence, a temporary “winged” fence, and an organic repellent “fence.” These differ from traditional exclusionary fencing for elk and deer, in that they are cheaper to construct and can be easily moved among fields over time, as farmers grow sunflowers on a rotational basis. Each fence type is described below: • Polyrope electric fence – The polyrope electric fence acts primarily as psychological barrier for elk and deer based on learned behavioral, avoidance conditioning (McKillop and Sibly 1988). The fences consists of conductive wires which are woven into synthetic electric “ropes” that are more durable, visible, and easy to install than traditional electric fences (Figure 2; Hygnstrom and Craven 1988, VerCauteren et al. 2006). Avoidance conditioning occurs when an animal contacts the fence, often with the nose or tongue, and receives a powerful electric shock. Polyrope fences have had success in reducing deer damage (Hygnstrom and Craven 1988, Seamans and VerCauteren 2006), but have not been experimentally tested for reducing elk damage. For the 5 randomly selected polyrope treatment plots, we constructed a fence approximately 1.8 meter tall with 5 strands to discourage passage under, through, or over the fence. The polyrope was powered by a Speedrite™ 3000 energizer (Tru-Test Incorporated, San Antonio, Texas) using a 12-volt deep-cycle battery with a solar-panel recharger. • Temporary winged fence - For seasonal agricultural resources, such as sunflowers, temporary fences may be sufficient to provide protection from wild ungulates and are inexpensive, lightweight, and easy to erect and remove (Rosenberry et al. 2001, VerCauteren et al. 2006). We tested the effectiveness of a temporary “winged” fence made of polypropylene mesh (Figure 3). The fence is installed completely on one side of the target field, and partially installed on two other sides having 50-100 meter “wings” that extend perpendicular from the full fence line. This design was found to reduce deer damage in corn fields (Hildreth et al. In Review) but has not yet been tested on elk or on deer with crops other than corn. On those plots receiving winged-fence treatments, we installed the fence such that the side receiving complete protection was along the crop/wildland interface. The fence was made of 2.4 meter tall black barrier material (e.g., Guardian Warning Barrier, Tenax Corporation, USA, Baltimore, Maryland) for increased height and visual deterrence. • Plantskydd - Repellents are nonlethal substances that can be used to deter ungulates by decreasing a plant’s palatability (Walter et al. 2010). We will test the effectiveness of a relatively new product, Plantskydd, for reducing sunflower damage around Dove Creek. This product was developed in Sweden to decrease mammalian wildlife damage on commercial forests. It works by emitting an odor that animals associate with predator activity, repelling the animal before it forages on crop plants. There is great interest in the success of this product as it can be easily applied to vegetation by ground and aerial spraying, used on both organic and conventionally grown sunflowers, and is cost-effective for growers. That said, the effectiveness of Plantskydd has not been experimentally tested, only anecdotally reported. To test this method, 5 Plantskydd treatment plots were ground sprayed in a ~20 ft swath around the plot perimeters after germination had begun (as directed by the manufacturer). Plantskydd was reapplied to treatment plots once/month throughout the growing season as the repellent may wash off or decompose over time and needs to be reapplied to new plant material. We constructed the fence plots based on a randomized block design. We identified 5 different sunflower fields to serve as replicates (~160-200 acres in size); all fields had previously suffered high 103 �ungulate crop damage. Within each field we specified 4 10-acre plots, one for each experimental fence treatment type (polyrope fence, temporary winged fence, chemical repellent fence) and a control (Figure 1). The 4 plots were randomly assigned within each field, such that each field (block) contained one replicate of all treatments (Gotelli and Ellison 2004). This design allows us to statistically account for environmental heterogeneity, as we expect that damage will be variable among fields. Within the fields, study plots were spaced as far apart as possible, to account for plot independence. Plots were also placed along the agriculture/wildland boundary, where depredation is expected to be concentrated. Fences were installed by Dillon Fencing (Naturita, CO) during the end of June and early July 2011, after sunflowers had germinated. The 20 plots (experimental and control plots) were delineated were monitored from mid-July through mid-October (time of harvest). Treatment and control plots were examined for 2 key response variables: elk/deer incursion and sunflower damage. We quantified incursion by elk and deer into our plots on a biweekly basis, assessing the permeability of the different fence types. To do this, an observer walked the perimeter of each plot, counting the number of elk and deer tracks entering and exiting the field. Tracks were raked out between observations so they were not double-counted. Differences in the number of elk and mule deer tracks into treatment/control fields were tested using repeated measures ANOVA. In addition to quantifying incursion into experimental plots, we also quantified direct damage to sunflower plants. We assessed damage every 2 weeks using the variable-area-transect (VAT) method for estimation of crop depredation (Engeman and Sterner 2002, Gilsdorf et al. 2004a, Gilsdorf et al. 2004b). In each plot, we conducted 15 VAT transects at random starting points, inspecting a row of sunflowers, and counting the total number of sunflowers that were damaged and undamaged. If 5 cervid-damaged sunflowers were tallied in 100 meters, we recorded the distance traveled and the total number of sunflowers on the transect. If 5 cervid-damaged sunflowers were not tallied in 100 meters, the observer recorded the total number of sunflowers and any cervid-damaged sunflowers observed in that distance. We calculated the percentage of sunflowers damaged per transect using the equation ~ damage = (number of damaged sunflowers) / (number of damaged sunflowers+number of undamaged sunflowers) (Gilsdorf et al. 2004a, Gilsdorf et al. 2004b). Additionally, at the end of the season, we had an agricultural assessor evaluate game damage and year-end yields between treatment and control plots, the ultimate measure of success for each management technique. Just prior to the sunflower harvest in mid-October 2011, we removed all fencing materials from our study fields. The materials were stored over the winter by CPW and re-deployed to 4 different sunflower fields in June 2012 for the second year of testing. Collaring elk and deer to collect information on movement and distribution To obtain data on ungulate movement and distribution patterns we contracted Quicksilver Air to capture and collar 20 adult female elk and 20 adult female deer using a net gun from a helicopter (Krausman et al. 1985). Females were the target of collaring efforts because they cause a majority of the crop depredation and should provide valuable insight into herd distributions. Helicopter captures were scheduled from 11-13 October 2011, just prior to the start of first rifle season. There was a narrow window in which to capture animals, as helicopter operations could only occur after the heat of the summer had passed, but before rifle season had begun (to minimize impacts to hunters). Captured elk and deer were hobbled and blindfolded, fitted with a global positioning system (GPS) collar, aged, measured and released. GPS collars were programmed to collect a location every 4 hours for 2 years, and then drop off the animals in fall 2013. The collars are “store-on-board,” meaning that the data can only be downloaded once the collar is retrieved from the field. Until collars drop-off, we are conducting monthly aerial telemetry flights to monitor survival and obtain some general location information. 104 �Once GPS collar data has been retrieved, elk and mule deer locations will be used to map seasonal distribution and migration patterns in ArcGIS. This should allow CPW to design public hunts that will target conflict elk and mule deer, while minimizing the need for PLO hunts and kill permits. For example, the Utah Division of Wildlife Resources is willing to consider special elk hunts south of Hwy 491 if we find that any or all of the resident elk herds (causing damage) spend portions of the year in Utah. Locations will also allow us to determine the amount of use of crop fields by elk and deer, and the proportion of animals using crop fields (whether it is only certain segments of the population, or the population at large). Animal location data will also be used to model ungulate damage potential in relation to field locations, surrounding habitat types, human development, and topography. These variables have been important in explaining rates of ungulate depredation, as damage tends to increase closer to cover, further from roads, and depending on crop palatability (Grover and Thompson 1986, Nixon et al. 1989, Hegel et al. 2009). Information about the location of a crop field in the context of the overall landscape will allow CPW to work with local growers to identify appropriate management tools, and the timing of their implementation, to reduce game damage. Such a model will serve as a powerful tool for CPW managers, as they will be able to predict the likelihood of depredation for different fields, depending on location, the surrounding environment, and the crop type, and therefore help landowners specify crop choice or management actions to reduce damage. RESULTS AND DISCUSSION Between 20 July 2011 and 20 October 2011 we conducted 137 incursion surveys of the 20 fence plots and 2,100 sunflower ungulate damage assessments. We used repeated measures ANOVA to determine whether there were statistically significant differences in elk and deer incursion into each fence treatment type. We found that incursion varied by treatment for both elk and deer (Elk: F20, 116 = 6.84, P < 0.001; Deer: F20, 116 = 6.24, P < 0.001) such that the electric fence plots had the fewest elk and deer tracks entering the plot, followed by the winged fences, the Plantskydd repellant fences, and the control plots (Figure 4). Biweekly damage assessments of the sunflower fields showed that crop damage followed the same general trends as the frequency of elk and deer entering the treatment plots. Generally, the electric fence plots received the least elk and deer damage, followed by the winged fence, and then by the Plantskydd treatment; the control fields had the highest levels of ungulate damage (Table 1, Figure 5). As expected, the percentage of damaged plants/plot generally increased throughout the growing season, except during the last two assessments. This pattern may have resulted from differences in an observer’s ability to detect damage at different stages of sunflower growth. At the end of the growing season, when the plants are dry and sunflower heads are bent over, damage may be harder to detect than at earlier stages of growth (i.e., when the heads are upright and the leaves are erect). Damage, however, was generally minimal in 2011 across all fields and plots (<1% in plots with electric fences and ~4% in control plots). We suspect that minimal damage was the result of abundant natural forage for elk and deer, as late spring rains in 2011 generated more forage than is typically observed in the vicinity of Dove Creek during summer. Indeed, CPW did not pay out any damage claims to farmers for elk and deer crop depredation in 2011, as wild ungulates were not readily observed on fields. We plan on constructing and monitoring experimental fence plots for a second year in 2012, to test the effectiveness of these treatments when sunflower fields experience more typical rates of damage. Quicksilver Air captured and collared 20 adult female deer and 9 adult female elk. Although deer were readily available for capture throughout the study area, the helicopter crew had a difficult time finding elk in the study area. Wildlife managers suspect that the elk had already left the agriculture areas 105 �around Dove Creek, and had potentially crossed the Utah border by that point in the fall. We plan on trying to ground dart elk during summer 2012 to deploy the remaining elk collars. We conducted monthly aerial telemetry flights for collared animals to track survival and general movement patterns. Four deer died during winter 2011. One deer died in late October, likely due to capture related causes (D12). The other 3 mortalities occurred in February and March 2011, one from a vehicle collision (D4) and the other two from unknown causes (D8 and D19). GPS collars were retrieved from all mortalities so that the data could be downloaded and processed (Figure 6). This information will be used during FY13-14 to map and model seasonal ungulate distributions, game damage potential, and management options for farmers. SUMMARY AND FUTURE PLANS During FY11-12 we constructed the experimental fence plots for the first year of fieldwork, quantified elk and deer damage across our different fencing treatment types, and collared elk and deer in the study area. In FY12-13 we will conduct the fencing experiments for a second field season, and attempt to deploy our remaining elk collars via ground darting. We will continue to monitor the survival and movements of collared animals on a monthly basis using aerial telemetry, until collars detach from the animals in fall 2013. The benefits of this project include gaining knowledge about local elk and deer movements and distribution relative to agricultural fields, identifying non-lethal techniques for reducing ungulate damage to sunflowers and other crops, the development of models to identify areas highly susceptible to damage based on landscape characteristics, and the potential to redesign public hunting opportunities to increase opportunity while reducing those resident animals causing a majority of the damage. LITERATURE CITED Austin, D.D., P.J. Urness, and D. Duersch. 1998. Alfalfa hay crop loss due to mule deer depredation. Journal of Range Management 51:29-31. Blejwas, K.M., B.J. Sacks, M.M. Jaeger, and D.R. McCullough. 2002. The effectiveness of selective removal of breeding coyotes in reducing sheep predation. Journal of Wildlife Management 66:451-462. Engeman, R.M., R.T. Sterner. 2002. A comparison of potential labor-saving sampling methods for assessing large mammal damage in corn. Crop Protection 21:101-105. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004a. Evaluation of a deer-activated bio-acoustic frightening device for reducing deer damage in cornfields. Wildlife Society Bulletin 32:515-523. Gilsdorf, J.M., S.E. Hygnstrom, K.C. VerCauteren, G.M. Clements, E.E. Blankenship, and R.M. Engeman. 2004b. Propane exploders and Electronic Guards were ineffective at reducing deer damage in cornfields. Wildlife Society Bulletin 32:524-531. Gotelli, N.J., and A.M. Ellison. 2004. A primer of ecological statistics. Sinauer Associates, Sunderland, Massachusetts. Hegel, T.M., C.C. Gates, and D. Eslinger. 2009. The geography of conflict between elk and agricultural values in the Cypress Hills, Canada. Journal of Environmental Management 90:222-235. Hildreth, A.M., S.E. Hygnstrom, E.E. Blankenship, and K.C. VerCauteren. In Review. Efficacy of a partial poly-mesh fence with wings to reduce deer damage to corn. Hygnstrom, S.E. and S.R. Craven. 1988. Electric fences and commercial repellents for reducing deer damage in cornfields. Wildlife Society Bulletin 16:291-296. Johnson, H.E., P.Dorsey, M. Hammond, C. Bishop, K. VerCauteren, D. Walter, and C. Anderson. 2011. Evaluating solutions to reduce elk and mule deer damage on agricultural resources. Study Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. 106 �Krausman, P. R., J. J. Hervert, and L. L. Ordway. 1985. Capturing deer and mountain sheep with a netgun. Wildlife Society Bulletin 13:71–73. McKillop, I.G., and R.M. Sibly. 1988. Animal behaviour at electric fences and implications for management. Mammal Review 18:91-103. Nixon, C.M., L.P. Hansen, P.A. Brewer, J.E. Chelsvig. 1989. Ecology of white-tailed deer in an intensively farmed region of Illinois. Wildlife Monographs 118:1-77. Rosenberry, C.S., L.I. Muller, and M.C. Conner. 2001. Movable, deer-proof fencing. Wildlife Society Bulletin 29:754-757. Seamans, T.W., and K.C. VerCauteren. 2006. Evaluation of ElectroBraid™ fencing as a white-tailed deer barrier. Wildlife Society Bulletin 34:8-15. Van Tassell, L.W., C. Phillips, B. Yang. 1999. Depredation claim settlements in Wyoming. Wildlife Society Bulletin 25:886-894. Vecellio, G.M., R.H. Yahner, and G.L. Storm. 1994. Crop damage by deer at Gettysburg Park. Wildlife Society Bulletin 22:89-93. VerCauteren, K.C., M.J. Lavelle, and S. Hygnstrom. 2006. Fences and deer-damage management: a review of designs and efficacy. Wildlife Society Bulletin 34:191-200. Wagner, K.K., R.H. Schmidt, and M.R. Conover. 1997. Compensation programs for wildlife damage in North America. Wildlife Society Bulletin 25:312-319. Walter, W.D., M.J. Lavelle, J.W. Fischer, T.L. Johnson, S.E. Hygnstrom, and K.C. VerCauteren. 2010. Management of damage by elk (Cervus elaphus) in North America: a review. Wildlife Research 37:630-646. Walter, W.D., K.C. VerCauteren, J.M. Gilsdorf, and S.E. Hygnstrom. 2009. Crop, native vegetation, and biofuels: response of white-tailed deer to changing management priorities. Journal of Wildlife Management 73:339-344. World Resources Institute. 2008. WRI EarthTrends monthly update page. http://earthtrends.org/updates/node/180. Wisdom, M.J., and J.G. Cook. 2000. North American Elk. Pages 694-735 in S. Demarais and P.R. Krausman, editors. Ecology and management of large mammals in North America. Prentice Hall, Upper Saddle River, New Jersey, USA. Yoder, J. 2002. Deer-inflicted crop damage and crop choice in Wisconsin. Human Dimensions of Wildlife 7:179-196. Prepared by _______________________________________ Heather E. Johnson, Wildlife Researcher 107 �Table 1. Average percentage of damaged plants/transect during successive damage assessments across the 2011 sunflower growing season. Averages are displayed by field and treatment plot. FIELD/PLOT Guynes Control Electric Plantskydd Winged Schear-Brewer Control Electric Plantskydd Winged Schear-Homestead Control Electric Plantskydd Winged Schear-Hudgeons Control Electric Plantskydd Winged Warren Control Electric Plantskydd Winged 1 2 3 ASSESSMENT 4 5 6 7 1.7 0.0 0.8 0.0 5.2 0.1 4.5 0.3 5.6 0.1 6.6 0.9 6.9 0.2 2.5 0.6 9.2 0.4 3.9 1.0 8.9 0.2 7.4 1.0 1.5 0.2 1.5 0.7 0.3 0.0 0.0 0.0 1.1 0.1 6.5 0.3 0.7 0.7 2.3 1.8 1.0 0.4 1.9 0.7 2.6 0.6 4.5 1.1 1.2 0.6 1.0 1.5 1.4 0.4 2.2 1.1 0.0 0.0 0.0 0.1 7.1 0.1 0.4 0.3 3.0 0.2 3.2 5.6 7.7 0.1 2.4 3.1 3.1 0.2 9.4 8.1 7.5 0.1 5.3 5.6 2.5 0.2 1.6 2.1 0.1 0.0 0.0 0.1 0.6 0.5 0.3 0.5 0.7 0.9 0.4 1.1 1.3 0.8 0.6 0.5 0.5 0.8 0.4 2.5 0.7 0.5 0.3 1.1 0.6 0.7 0.4 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.0 0.1 0.1 0.0 0.1 0.2 0.1 0.1 0.2 0.3 0.2 0.0 0.1 108 �Figure 1. Placement of experimental fence plots within the 5 replicate sunflower fields during the 2011 growing season (July – October). Fields are located adjacent to wildland canyons. 109 �Figure 2. Photo of a polyrope electric fence constructed in a sunflower field south of Dove Creek. Figure 3. Photo along a winged temporary fence constructed in a sunflower field south of Dove Creek. 110 �Figure 4. Mean number of deer and elk that crossed into experimental fence plots on a biweekly basis, by treatment type, during damage surveys throughout the growing season (results generated from a repeated measures ANOVA). Mean Number of Ungulates 7 Deer Elk 6 5 4 3 2 1 0 control electric plantskydd winged Treatment Figure 5. Average percentage of damaged plants/transect for biweekly assessments across all fields for different treatment types. 111 �Figure 6. GPS collar locations from deer mortalities during FY11-12 in the vicinity of Dove Creek, CO. 112 �113 �Colorado Division of Parks and Wildlife July 2011 – June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No. Colorado 3430 3003 : : : : : Division of Wildlife Mammals Research Predatory Mammal Conservation Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Federal Aid Project No. Period Covered: July 1, 2011 – June 30, 2012 Author: H.E. Johnson; project cooperators, C. Bishop, J. Broderick, J. Apker, S. Lischke, M. Alldredge, S. Breck, J. Beckmann, K. Wilson, M. Reynolds-Hogland, T. Spezze, and P. Dorsey. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a unique collaboration that builds on the resources and abilities of personnel from 5 entities: the Colorado Parks and Wildlife (CPW), the USDA National Wildlife Research Center, Colorado State University, Wildlife Conservation Society, and Bear Trust International. Collectively, we completed year 1 of a 5-year study on black bears that 1) tests management strategies for reducing bear-human conflicts, 2) determines the influence of urban environments on bear habitat-use patterns and demography, 3) identifies public attitudes and perceptions about bears, bear management and bear-human encounters, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. This project was initiated in FY10-11; during this past fiscal year we have primarily focused on coordinating research logistics and collecting field data in the vicinity of Durango, Colorado. Specifically, we obtained data on garbage-related bear-human conflicts, trapped and marked black bears, monitored the vital rates of collared bears (survival, fecundity and cub survival) through telemetry and winter den visits, collected data on the availability of late summer/fall mast, tracked human-related bear mortalities and removals, performed non-invasive genetic mark-recapture surveys, and conducted a survey of public attitudes and perceptions about bear-human encounters. Project collaborators will continue to seek additional funding to implement the remaining activities outlined in the research proposal (i.e., purchase additional containers for an urban-food-removal experiment, increase the sample size of collared bears, and acquire telemetry collars to test a translocation model). Information from this study will provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the country. 114 �WILDLIFE RESEARCH REPORT BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS HEATHER E. JOHNSON P.N. OBJECTIVES To conduct a study on black bears in Colorado that 1) tests management strategies for reducing bearhuman conflicts, 2) determines the influence of urban environments on bear habitat-use patterns and demography, 3) identifies public attitudes and perceptions about bears, bear management and bear-human encounters, and 4) develops population and habitat models to support the sustainable monitoring and management of bears. SEGMENT OBJECTIVES 1. Work with personnel from CPW Area 15, CPW Southwest Region, the City of Durango, La Plata County, US Forest Service (Columbine and Pagosa Ranger Districts), Bureau of Land Management (BLM; Tres Rio Field Office), and private landowners on field research logistics. 2. Collect pre-treatment data on the frequency of bears accessing human garbage in preparation for an urban bear-proofing experiment. 3. Trap and collar adult female black bears in the vicinity of Durango to collect data on bear habitatuse patterns and demography. 4. Monitor bear survival via global position system (GPS) collar locations. 5. Obtain data on summer/fall natural food availability for bears based on the phenology and abundance of gambel oak, serviceberry, chokecherry, hawthorne, pinyon pine and squaw apple. 6. Investigate the winter dens of collared female bears to collect data on fecundity and cub survival, inspect collar fit, and replace collar spacers and batteries. 7. Track human-related bear mortalities and removals around Durango from lethal conflict mortalities, vehicle collisions, harvest, and translocations. 8. Perform non-invasive genetic mark-recapture surveys to estimate bear density and population size around Durango (urban site) and in the Piedra watershed (wildland site). 9. Conduct a survey of public attitudes and perceptions about bears, the local bear population, bear management and bear-human encounters. INTRODUCTION In Colorado and across the country, conflicts among people and black bears (Ursus americanus) appear to be increasing in number and severity (Hristienko and McDonald 2007, Baruch-Mordo et al. 2008, CPW unpublished data). Bear-human conflicts can result in public safety concerns, property damage, bear mortality (i.e. euthanasia), and high management costs, and thus, have become a critical wildlife management issue. While wildlife agencies have used a variety of tools to try to minimize bearhuman conflicts (i.e., education, aversive conditioning of bears, and modifications to harvest), conflict rates have continued to rise. Whether increases in bear-human conflicts reflect recent changes in the bear population or just behavioral shifts to anthropogenic food resources, is largely unknown, as bear population parameters have been exceeding difficult to estimate (Garshelis and Hristienko 2006). Without a thorough understanding of the relationship between conflict rates and bear behavior and population dynamics, it has been difficult for wildlife agencies to successfully reduce conflicts through bear management. 115 �While there is uncertainty about how to reduce bear-human conflicts, two key factors thought to exacerbate this problem are expanding human development and climatic variation. Colorado has had one of the highest rates of exurban development in the nation (Theobald and Romme 2007), and this development has resulted in additional human food on the landscape in the form of garbage, agricultural resources, fruit trees, etc. The availability of human food to bears has been identified as the primary cause of bear-human conflicts (Spencer et al. 2007, Beckmann et al. 2008, Greenleaf et al. 2009), as bears are opportunistic foragers that will readily take advantage of this resource. Bear-use of human food not only increases interactions between bears and people but has been found to alter bear activity patterns, foraging behavior, movement rates, and even survival and reproductive rates (Beckmann and Berger 2003a, Beckmann and Berger 2003b, Hostetler et al. 2009), having the potential to significantly alter both bear behavior and demography. This phenomenon is further complicated by variation in annual weather patterns, as bear-use of human development appears to increase when natural foods are in short supply (Zack et al. 2003, Baruch-Mordo et al. 2010). Because bears predominately consume vegetation, recent patterns of drought in Colorado have caused natural food failures in some years. As a result, bears may be increasing their reliance on human foods, with associated behavioral and demographic impacts. While the effects of urbanization and climate have critical implications for modifying bear-habitat relationships, they also have critical implications for increasing rates of bear-human conflicts. To develop successful strategies to reduce conflicts while maintaining viable bear populations, wildlife agencies must understand how factors such as climate, natural food availability, human food ability, and management influence the behavior and dynamics of bear populations. To address these questions, Colorado Parks and Wildlife has partnered with the USDA National Wildlife Research Center, Wildlife Conservation Society, Colorado State University, and Bear Trust International. Collectively, we initiated a project in FY10-11 to 1) test management strategies for reducing bear-human conflicts, 2) determine the influence of urban environments on bear habitat-use patterns and demography, 3) identify public attitudes and perceptions about bears, bear management and bear-human encounters, and 4) develop population and habitat models to support the sustainable monitoring and management of bears in Colorado (Johnson et al. 2011). This information should provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the west. During FY11-12 we worked with internal and external stakeholders on field research logistics, obtained data on garbage-related bear-human conflicts, trapped and marked black bears, monitored the vital rates of collared bears (survival, fecundity and cub survival) through telemetry and winter den visits, collected data on the availability of late summer/fall mast, tracked human-related bear mortalities and removals, performed non-invasive genetic mark-recapture surveys, and conducted a survey of public attitudes and perceptions about bear-human encounters. Our efforts focused largely on collecting field data to meet research objectives 1-3, information which will eventually be used to address objective 4. We report general summary information from field activities over the past year; detailed analyses of field data will occur in future years. STUDY AREA To meet study objectives, a combination of site-specific field data and statewide data will be required. Site-specific field data is being collected in the vicinity of Durango, and is the focus of this progress report. Regional and statewide analyses will be conducted in future years. The town of Durango contains ~17,000 people (within city limits) and sits at 1,985 m along the Animas river valley. The town is surrounded by mountainous terrain ranging in elevation from ~1,930 to ~3,600 m, and is generally characterized by mild winters and warm summers that experience monsoon rains. Vegetation in the region is dominated by ponderosa pine, oak, pinyon-juniper, aspen, mountain shrub, and agricultural 116 �communities. Key forage species for black bears include gambel oak (Quercus gambelii), chokecherry (Padus virginiana), serviceberry (Amelanchier alnifolia), hawthorne (Crataegus spp), squaw apple (Peraphyllum ramosissimum), angelica (Angelica spp), sweet cicily (Osmorhiza spp), cow parsnip (Heracleum sphondylium) and waterleaf (Hydrophyllum spp). Durango is predominately surrounded by public land managed by the San Juan National Forest, BLM, CPW, La Plata County and the City of Durango. The vicinity of Durango is considered high quality bear habitat, and the town has consistently experienced high rates of bear-human conflicts. METHODS Objective 1: Testing management strategies to reduce bear-human conflicts Given that the primary cause of black bear-human conflicts has been attributed to the availability of human foods to bears, it has been suggested that the most effective strategy to reduce conflicts is to reduce the availability of that food source (Peine 2001, Beckmann et al. 2004, Gore et al. 2005, Spencer et al. 2007). This strategy has had some success within national parks (Greenleaf et al. 2009), and anecdotally in some communities (Mammoth Lakes CA, Juneau AK, Whistler BC), but no research has ever scientifically tested the benefits of “cleaning up” a town. Given the high price to operationally “bearproof” a community, municipalities must have definitive evidence that such an effort would significantly decrease conflict activity before initiating major changes to waste storage and collection practices. As part of this project we will be implementing the first experimental test of wide-scale urban bear-proofing for reducing bear-human conflicts. To do this, we will drastically reduce the accessibility of anthropogenic foods known to attract bears (garbage, bird-feeders, pet food, etc) within 2 designated ‘treatment’ areas, while simultaneously monitoring 2 comparable ‘control’ areas where no action will occur. In the treatment areas we will provide bear-proof garbage containers, canvass citizens to discourage food outside of secure structures (bird-feeders, pet food, etc), conduct daily patrols to remove human foods, and provide strict enforcement. Each area will contain approximately 500 homes in residential neighborhoods. Treatment and control areas will be monitored for 3 years after the experiment has commenced, and we will track the number of conflicts and their severity among our experimental units. Conflicts will be recorded from weekly monitoring and from calls received by CPW, the City of Durango, and Bear Smart Durango (local non-profit organization). During summer 2011 project personnel collected pre-treatment data (data collection for 2012 is ongoing) on bears accessing garbage in Durango. In July and August, months that experience the highest numbers of bear-human conflicts (CPW unpublished data), technicians patrolled each street within proposed treatment/control areas on the day waste removal was scheduled to occur (when maximum human food was assumed to be available to bears). Technicians conducted patrols from ~05:30 - 06:30 AM and recorded the locations where there was evidence that bears had obtained garbage or other human food sources. Additionally, during late July, we quantified the “availability” of garbage to bears, by documenting the location and container type (wildlife-resistant or regular) of every garbage receptacle in the survey area. These data will allow us to track changes in the number of wildlife-resistant containers over the course of the study, and provide an estimate of the amount of human food available to bears in town. In addition to collecting pre-treatment data, we worked with the City of Durango to coordinate the logistics of implementing the bear-proofing experiment in spring 2013. Objective 2: Determining the influence of urban environments on bear behavior and demography To sustainably manage bears in the face of a growing human population and changing landscape conditions, it is critical to elucidate the drivers and dynamics of bear populations. Of those factors that influence bear populations, the expansion of human development is the least understood, most contentious, and has the greatest potential to elicit major population change. To elucidate the influence of human development on bear habitat-use patterns and demography, we are collecting a suite of data types 117 �including locations from collared bears on the urban-wildland interface, survival and reproductive rates of those bears in conjunction with their habitat-use patterns, information on annual summer/fall mast production, and genetic data to estimate bear density in urban and wildland habitat types. We briefly describe data collection methods for this portion of the study below; detailed information is available in Johnson et al. (2011). Collaring and Marking Bears – To assess bear movement and habitat-use patterns with respect to human development, we are capturing and collaring adult female bears. We are specifically targeting adult females as they represent the reproductive segment of the population and allow us to obtain information on multiple key vital rates. For example, in addition to being able to track adult female survival, the vital rate with the highest elasticity (Beston 2011), we can use collared females to track fecundity and cub survival, vital rates that are often associated with variation in bear population growth rates (Mitchell et al. 2009, Beston 2011). We have targeted summer trapping efforts within ~10 km of the center of Durango to collar a cohort of bears that experience similar natural food availability, have anthropogenic food resources readily available, and encompass a range of behaviors and habitat-use patterns relative to the urbanwildland interface. Bears are trapped with box traps, which are baited with fish, fruit, human foods (at urban locations) and manufactured scents. Traps are set in the evening and checked the following morning. Adult female bears are fitted with a GPS collar manufactured by Vectronics, and a tooth is pulled for age verification. A collar records a bear’s location every hour, and uploads a location to a central database via satellite system every 6 hours. Although trapping efforts are focused on adult females, all bears that are trapped (i.e., males, subadults, yearlings) are uniquely marked with a PIT and ear-tag and are weighed, measured, and sampled for blood and hair. Evaluating Bear Movement and Habitat-Use Relative to the Urban-Wildland Interface – To examine movement and habitat-use patterns of bears along the urban-wildland interface we will use GPS collar location data from adult female bears. We will assess the influence of factors such as natural food availability, human food availability, weather, habitat covariates, and individual bear attributes (i.e., age, reproductive status) on bear behavior. During winter 2012, we downloaded hourly GPS location data from the collars during winter den checks, and will continue to download and process this data on an annual basis. We will use locations in conjunction with various types of spatial data to conduct a suite of movement and resource selection analyses (Manly et al. 2002, McLoughlin et al. 2010, Morales et al. 2010). In terms of spatial data, we will use satellite imagery to track annual spring/early summer forage availability, and ground surveys to track late summer/fall mast availability (see details below). Weather information will be modeled using PRISM spatial data (www.prism.oregonstate.edu/) which interpolates monthly temperature and precipitation patterns across landscapes, accounting for elevation and topography. Covariates related to human development will be derived from existing CPW digital data layers such as parcel density, road density, and census population size. While most habitat and human development information can be extracted from existing spatial data sources, there is no existing data layer that tracks annual variation in late summer/fall hard and soft mast for bears. The abundance of acorn and berry resources for bears is known to be highly variable, depending on annual trends in precipitation and temperature (Noyce and Coy 1989). To account for variation in the availability of natural forage for bears around Durango we conducted weekly mast surveys. Surveys were performed between mid-August and mid-September in 2011, when fruits and nuts should reach peak maturation. In the Durango region, the key mast species for bears are gambel oak, chokecherry, serviceberry, hawthorne, squaw apple, and pinyon pine (Beck 1991, Tom Beck, personal communication). We randomly selected 12 transects on public lands to evaluate bear natural food availability. Each transect was 1 km in length and was situated along an existing trail or stream drainage. For each transect, field technicians recorded the phenological stage and the percentage of plants of each 118 �species that exhibited mast in different abundance categories (mast failure, <25% of plants with mast, 25 – 50% of plants with mast, etc). Estimating Demographic Rates – To assess the influence of human development on bear demographic rates and population trends we are using the following data types: 1) survival and reproduction of collared adult female bears, 2) mortalities and removals from marked and unmarked bears in the vicinity of Durango, and 2) samples from non-invasive genetic surveys of bears around Durango and in the Piedra watershed. Collared female bears allow us to track annual survival, fecundity and cub survival, parameters we monitored in FY11-12 and which we will continue to monitor for the next 4 years. We used real-time GPS collar locations to assess adult female survival, investigating mortalities and slipped collars when GPS locations were stationary for multiple sampling points. Fecundity and cub survival were monitored from den checks of collared females. Numbers of newborn cubs provide information to estimate fecundity rates, while repeated annual den checks of collared females allow us to estimate cub survival. Yearlings hibernate with their mothers, so we can observe the number of cubs alive in the den in year t that have survived their first year of life to t+1. Adult female survival, fecundity and cub survival will be collectively used in projection models to assess population performance in future analyses (Caswell 2001). In addition to tracking survival and reproduction of collared bears, we are also tracking survival and cause-specific mortality of marked and unmarked bears in the study area. All bears that are trapped are marked with an ear-tag and PIT tag, unique identifiers that we are using to collect data on humanrelated bear mortalities and removals. Mortalities and removals primarily occur from translocations, vehicle collisions, conflict-related euthanasia and harvest. For all bears removed from the study area we collected a hair and tooth sample and recorded the date, mortality/removal cause, location, bear age, sex, weight, and morphological measurements. We will use mark-recapture and recovery analyses to estimate adult male survival and subadult survival, while also gaining valuable information on cause-specific bear mortality around human development. To better understand the influence of urban environments on bear density and population sizes, we are employing non-invasive genetic sampling (Woods et al. 1999, Mowat and Strobeck 2000) to compare these parameters between a bear population around the urban center of Durango and in a nearby “wildland” area. For each area we identified a 36 cell grid (576 km2) where each cell was 4 x 4 km in size; we constructed 1 snare in each cell. Snares consisted of a scented bait hanging high in a tree, surrounded barbed wire around a cluster of trees encircling the bait. When the bears climbed over or under the wire to investigate the bait, they left a hair sample on the barbed wire. In summer 2011 we hung a single strand of barbed wire (50 cm high), and on the other half of the snares we hung two strands (50 and 20 cm high). Our goal with this design was to determine whether the additional strand of wire increased capture probability. In summer 2012 all sites were strung with a single strand of wire. Snares were deployed during the first 2 weeks of June, and we conducted 6 weekly sampling occasions thereafter. On each occasion, we randomly re-baited the snare with anise, strawberry, fish, maple or bacon scent, and collected hair samples off all barbs. Each hair sample was uniquely catalogued according to the site, date, occasion, and barb number. In 2011, we sampled a total of 31 grid cells in Durango (dropping 5 cells where public or motorized access was prohibited) and 9 cells in the Piedra watershed. We did not have the logistical capability to sample both grids in their entirety, so we ran a pilot study on the Piedra to determine whether twice/month sampling (as opposed to weekly) would have significant impacts on DNA quality, DNA contamination (hair samples from >1 bear/barb), and recapture rate. In 2012, we constructed 35 snares in the Durango grid and 34 snares in the Piedra grid. The layout of the Piedra grid had to be modified in 119 �2012 to account for closures associated with the Little Sand fire, which began burning on May 13th 2012 (Figure 1). This modification can be easily accounted for in future analyses with spatially-explicit mark recapture statistics (Efford et al. 2009, Gardner et al. 2010). In fall 2011, all hair samples were sent to the laboratory at Wildlife Genetics International for genotyping; genetic results were returned at the end of June 2012. Summary data from the Durango grid is provided, and the remainder of the analyses will occur during FY12-13. Samples collected in 2012 will be sent to the laboratory this fall. Objective 3: Identifying public attitudes about bear-human encounters Wildlife management agencies must identify the biological factors driving increases in bearhuman conflicts, but they also must identify and incorporate human attitudes and perceptions about this issue into management strategies. This is particularly critical for black bears, as increasing bear-human conflicts around urban development have simulated significant public interest and concern. It is also critical because bear-human conflicts typically arise over bear-use of human foods, prompting investigators to suggest that a critical component of reducing conflicts is managing human behavior (Beckmann et al. 2004, Gore et al. 2008, Baruch-Mordo et al. 2011). Thus, in conjunction with Stacy Lischka, Human Dimensions Specialist for CPW, we have initiated a public survey to 1) better understand public perceptions about bears, bear management, and bear-human encounters and 2) explore motivations for compliance and non-compliance with wildlife ordinances designed to reduce bear-human conflicts. To meet those objectives, we developed a three part public mail survey to be conducted in conjunction with our urban bear-proofing experiment. Residents will be surveyed pre-, during, and postimplementation of the experiment, in treatment and control areas, as well as across a larger portion of the community. Surveys will be mailed to all residents within Durango city limits, and a subset of La Plata county residents within the study area. Survey responses will allow us to quantify current public attitudes and perceptions about bears, and how those perceptions change over time in association with a management effort such as wide-scale urban bear-proofing. The survey will also determine the number of residents that have had interactions with bears, the acceptability of management actions by CPW, and factors that promote or inhibit residents from complying with wildlife ordinances. The pre-treatment survey was mailed to 5,852 residents; 4,352 residents in Durango city limits and 1,500 in surrounding areas of La Plata county (Appendix 1). The total valid sample, once surveys mailed to incorrect addresses were returned, was 5,329. Surveys were mailed on January 17th 2012, a reminder postcard was mailed on February 2nd 2012, and a second survey was mailed to non-respondents on February 29th 2012. For those people that did not send back a completed survey, we mailed a nonresponse postcard on May 18th 2012. The postcard had a few background questions so that any systematic biases in respondents could be assessed and incorporated into analyses (Appendix 2). RESULTS AND DISCUSSION Objective 1: Testing management strategies to reduce bear-human conflicts During summer 2011 we collected pre-treatment data for the proposed bear-proofing experiment. We observed 129 instances of bears accessing garbage during our weekly surveys in July and August; observations peaked the first week of August. Of those garbage containers accessed by bears, 10% were wildlife-resistant and 90% were regular containers. Bears accessed human food from wildlife-resistant containers when they were not closed properly or the locking mechanism on the lid was broken. In quantifying the availability of garbage to bears, we recorded the location and container type of 1,167 garbage cans in the proposed treatment and control areas. Of those containers, 14% were wildlife resistant and 86% were regular (non-wildlife resistant). This demonstrates the limited residential bear-proofing that currently exists in Durango, and the relevance of conducting an experimental test of wide-scale urban bear-proofing in this community. 120 �This past year, we have worked on the logistics of conducting a wide-scale urban bear-proofing experiment that should commence in spring 2013. A majority of the necessary funds were secured through CPW and the Summerlee Foundation; we are still seeking funds to complete project needs. With funds currently dedicated to the project, we purchased 760 wildlife-resistant containers from Solid Waste Systems (Parker, CO), a company that manufactures products certified by the Living with Wildlife Foundation. This fall, those containers will be fitted with electronic chips and entered into the Durango’s Solid Waste Program database. Because all residential waste is removed by the City of Durango, city staff will replace regular garbage containers with the newly purchased wildlife-resistant containers according to CPW’s study design. The wildlife-resistant containers will be distributed in late fall and winter after the bears have hibernated so that they are in place for the experiment in spring 2013. Objective 2: Determining the influence of urban environments on bear behavior and demography Between May 15th 2011 and August 15th 2012, a total of 162 different bears were marked as part of this study, during 287 bear captures. Information about these captures is described below for each discrete capture season: summer 2011, winter 2012, and summer 2012 (ongoing; Table 1). During summer 2011 we conducted 92 total bear captures; 71 captures were unique individuals and 21 were recaptures. Of the unique individuals captured, there were 30 females, 38 males, and 3 cubs of unidentified sex (cubs were released without being immobilized and thus, gender was not determined; Table 1). We collared a total of 26 adult females, however two bears slipped out of their collars and were not recaptured, leaving 24 collared bears at the end of the field season. The mean estimated age of bears ≥1 year-old on their initial capture date was 5.3 (5.7 for females and 5.1 for males), and the mean weight was 80.8 kg (59.9 kg for females and 97.4 kg for males). The mean age of collared females, based on tooth cementum, was 6 years, and estimated ages ranged from 2.5 to 23. In total, we placed traps/snares at 102 different locations (26 on public land and 76 on private land) and we had 1,253 trap nights. Capture success generally peaked during the first couple weeks of June and was highly variable throughout the remainder of the summer (Figure 2). We visited the winter dens of 22 collared females between January and March 2012. Although we had 24 adult female bears collared in fall 2011, 1 female was harvested (B49), and we could not locate the den of 1 bear wearing a Lotek collar (B51). Nine females did not have any cubs or yearlings, 3 bears had yearlings (6 yearlings in total) and 10 had newborn cubs (21 cubs in total; 11 females and 10 males). Of those females with yearlings, 1 bear had 1 yearling, 1 bear had 2 yearlings, and 1 bear had 3 yearlings. Of those females with newborn cubs, 1 had only 1 cub, 7 bears had twins, and 2 bears had triplets. We PIT and ear-tagged yearlings in the den, recorded information on weight and body size, and collected hair and blood samples. We also PIT tagged newborn cubs, and recorded their sex and weight. One collared bear (B43) died during the immobilization process in the den. Between May 15th and August 15th 2012, we conducted summer captures to obtain a sample of 40 GPS collared adult females (captures are currently ongoing). During that time there were 153 total captures; 74 were unique individuals and 79 were recaptures (Table 1). Of the unique individuals captures, 33 bears were females, 37 were males, and 4 cubs were of unidentified sex (cubs were not immobilized). The mean estimated age of bears ≥1 year-old on their initial capture date was 4.7 (5.3 for females and 4.3 for males) and the mean weight was 72.3 kg (58.3 kg for females and 83.5 kg for males). This summer, to date, 22 new adult females have been collared. Given mortalities and slipped collars (3 collars were slipped in spring/summer 2012), 37 females were collared as of August 15th, and trapping will continue through mid-September or until 40 GPS collars have been deployed. To date, traps have been placed in ~78 different trap locations (26 on public land and 52 on private land) for approximately 1,024 trap nights. Capture success generally climbed each week until the second week of July, and has remained high (Figure 2). The increase in capture success in 2012 is likely due to extra trapping effort, as 121 �we increased our weekly trap nights from 5 nights/week to 7 nights/week and had a higher number of traps that were baited and set on a consistent basis. Although we are still working to deploy collars for the study, the Vectronics GPS technology has been highly efficient at tracking collared bears for movement rates, habitat-use patterns, den site locations, and daily survival. To date, we have obtained >60,000 locations from 48 different female bears (Figure 3). Additionally, the GPS collar technology has allowed us to observed long-distance movements by females, particularly during the estrous period; data which has been rarely collected and reported. For example, this past June, 3 different collared bears traveled between ~60 and ~320 km in different directions from the study area (Figure 4). Two of the bears returned to their original home ranges, and 1 died in a vehicle collision as she appeared to be returning to Durango (B35). In 2011, mast surveys revealed that the peak timing for serviceberry maturation was in midAugust, for chokecherries it was during the last week of August and first week of September, for squaw apples it was around September 1st, and for acorns it was during in the first two weeks of September. Hawthorne berries and pinyon cones were only observed on 2 of 12 transects; neither had reached peak maturation by mid-September. Across the transects, on average, <25% of gambel oak, chokecherry, squaw apple, and hawthorn plants had mast production. Serviceberry and pinyon production was categorized as a complete failure for the year. Between 1 May 2011 and August 15th 2012, 25 bears were removed from the vicinity of Durango due to non-harvest, human-related causes. Of those bears that were removed, 9 were lethally removed due to nuisance behavior (breaking into houses, killing livestock, etc), 10 were killed in vehicle collisions (including 2 collared females), 4 were translocated due to conflicts with people (including 1 collared female), and 2 died from research activities (including 1 collared female). Of those mortalities and removals, 17 bears were unmarked and 8 were marked/collared for the research project (1 marked bear was a lethal conflict removal outside the study area); there were 8 adult females, 4 adult males, 2 subadult females, 7 subadult males, and 4 cubs. In addition, approximately 20 bears were harvested in the greater Durango area (GMUs 74, 75, and 751), three of which were marked by the research project (1 collared female and 2 adult males). In summer 2011, we collected 998 hair samples from the Durango and Piedra hair-snare grids; 743 samples from Durango and 255 from Piedra. Over the 6 sampling occasions from 31 snares around Durango we collected 224, 167, 138, 77, 68, and 69 hair samples, respectively. Over the 3 sampling occasions from 9 snares in the Piedra we collected 127 samples; 46, 50, and 31 samples/occasion, respectively. We also collected 128 additional samples from 10 snares in the Piedra watershed that were only checked on a single occasion. We received the genetic results back from Wildlife Genetics International at the end of June 2012, and have summarized the Durango data. Of the 743 hair samples submitted to the laboratory, good genotypes were obtained for 438 samples. Of the remaining samples that did not produce a valid genotype, 193 did not contain enough genetic material, 104 failed during analyses for other reasons, 4 samples were not black bear, and 2 were contaminated (hair from >1 bear in the sample). Across the 438 valid samples there were 107 different individuals (61 females and 47 males) detected during 192 “captures” (multiple hair samples from a single bear during 1 sampling occasion were considered 1 “capture”). Of the different individuals, 21 were only detected in 1 sampling occasion and 86 were detected in >1 occasion (recaptures). The probability of detecting a bear within any single sampling occasion was ~0.21, and across all sampling occasions was ~0.76. More detailed analyses of these data will be included in the FY12-13 report. In summer 2012, we collected 1,367 hair samples from the Durango and Piedra grids; 586 samples from Durango and 781 samples from Piedra. Over the 6 sampling occasions from 35 snares around Durango we collected 92, 136, 59, 55, 142, and 102 samples, respectively. Over the 6 sampling 122 �occasions from 34 sites in the Piedra watershed we collected 73, 135, 142, 118, 144, and 169 samples respectively. Samples will be sent to Wildlife Genetics International this fall for genetic analysis. Objective 3: Identifying public attitudes about bear-human encounters Of the 5,334 valid surveys that were mailed to residents, we received 2,947 completed surveys; 2,170 from Durango residents and 777 from La Plata county residents. The overall response rate was 55%. Non-response postcards were mailed to 2,375 residents and 354 postcards were returned (15%). Survey results are being electronically recorded so this data can be analyzed in FY12-13. SUMMARY AND FUTURE PLANS During FY11-12 we successfully coordinated field logistics and conducted several aspects of data collection (monitoring garbage-related bear-human conflicts, trapping and collaring bears, tracking human-related bear mortalities, assessing summer/fall forage availability, implementing DNA hair-snare surveys, and conducting a public survey). We will continue these field activities through 2015, and begin data analyses as field data are compiled. Project collaborators will continue to seek additional funding to implement the remaining activities outlined in the research proposal. These activities include the implementation of an urban bear-proofing experiment, increasing the number of GPS collared female bears, and purchasing telemetry collars for a translocation study. In addressing the objectives of this project we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear behavior and population trends, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. LITERATURE CITED Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and J. Broderick. 2011. The carrot or the stick? Evaluation of education and enforcement as management tools for human-wildlife conflicts. Plos One 6: e15681. Baruch-Mordo, S., S.W. Breck, K.R. Wilson, and D.M. Theobald. 2008. Spatiotemporal distribution of black bear-human conflicts in Colorado, USA. Journal of Wildlife Management 72:1853-1862. Baruch-Mordo, S., K.R. Wilson, D. Lewis, J. Broderick, J. Mao, and S.W. Breck. 2010. Roaring Fork Valley urban black bear ecology study: progress report to the Colorado Division of Wildlife. Contact Sharon Baruch-Mordo for copy. Email: sharonb_m@yahoo.com Beck, T.D.I. 1991. Black bears of west-central Colorado. Technical Publication No. 39, Colorado Division of Wildlife, Colorado. Beckmann, J.P., and J. Berger. 2003a. Using black bears to test ideal-free distribution models experimentally. Journal of Mammalogy 84:594-606. Beckmann, J.P., and J. Berger. 2003b. Rapid ecological and behavioural changes in carnivores: the response of black bears (Ursus americanus) to altered food. Journal of Zoology 261:207-212. Beckmann, J.P., L. Karasin, C. Costello, S. Matthews, and Zoë Smith. 2008. Coexisting with black bears: perspectives from four case studies across North America. Wildlife Conservation Society Working Paper No 33. Beckmann, J.P., C.W. Lackey, and J. Berger. 2004. Evaluation of deterrent techniques and dogs to alter behavior of “nuisance” black bears. Wildlife Society Bulletin 32: 1141-1146. Beston, J.A. 2011. Variation in life history and demography of the American black bear. Journal of Wildlife Management 75:1588-1596. Caswell, H. 2001. Matrix population models: construction, analysis, and interpretation. Second Edition, Sinauer Associates, Sunderland, Massachussetts. Efford, M.G., D.K. Dawson, and D.L. Borchers. 2009. Population density estimated from locations of individuals on a passive dector array. Ecology 90:2676-2682. 123 �Garshelis, D.L., and H. Hristienko. 2006. State and provincial estimates of American black bear numbers versus agency assessments of population trend. Ursus 17:1-7. Gardner, B., J.A. Royle, M.T. Wegan, R.E. Rainbolt, P.D. Curtis. 2010. Estimating black bear density using DNA data from hair snares. Journal of Wildlife Management 74:318-325. Gore, M.L., W.F. Siemer, J.E. Shanahan, D. Schuefele, and D.J. Decker. 2005. Effects on risk perception of media coverage of a black bear-related human fatality. Wildlife Society Bulletin 33:507-516. Gore, M.L., B.A. Knuth, C.W. Scherer, and P.D. Curtis. 2008. Evaluating a conservation investment designed to reduce human-wildlife conflicts. Conservation Letters 1:136–145. Greenleaf, S.S., S.M. Matthews, R.G. Wright, J.J. Beecham, and H.M. Leithead. 2009. Food habitat of American black bears as a metric for direct management of human-bear conflict in Yosemite Valley, Yosemite National Park, California. Ursus 20:94-101. Hostetler, J.A., J.W. McCown, E.P. Garrison, A.M Neils, M.A. Barrett, M.E. Sunquist, S.L. Simek, and M.K. Oli. 2009. Demographic consequences of anthropogenic influences: Florida black bears in north-central Florida. Biological Conservation 142:2456-2463. Hristienko, H., and J.E. McDonald Jr. 2007. Going into the 21st century: a perspective on trends and controversies in the management of the American black bear. Ursus 18:72-88. Johnson, H.E, C.J. Bishop, M.W. Alldredge, J. Brodrick, J. Apker, S. Breck, K. Wilson, and J. Beckmann. 2011. Black bear exploitation of urban environments: finding management solutions and assessing regional population effects. Research Proposal, Colorado Division of Parks and Wildlife, Fort Collins, USA. Manly, B.F.J., L.L. McDonald, D.L. Thomas, T.L. McDonald, and W.P. Erickson. 2002. Resource selection by animals; statistical design and analysis for field studies. Second Edition. Kluwer Academic Publishers, Boston, Massachussetts. McLoughlin, P.D., D.W. Morris, D. Fortin, E. Vander Wal, and A.L. Contasti. 2010. Considering ecological dynamics in resource selection functions. Journal of Animal Ecology 79:4-12. Mitchell, M.S., L.B. Pacifici, J.B. Grand, and R.A. Powell. 2009. Contributions of vital rates to growth of a protected population of American black bears. Ursus 20:77-84. Morales, J.M., P.R. Moorcroft, J. Matthiopoulos, J.L. Frair, J.G. Kie, R.A. Powell, E.H. Merrill, and D.T. Haydon. 2010. Building the bridge between animal movement and population dynamics. Philosophical Transactions of the Royal Society Series B 365:2289-2301. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64:183-193. Noyce, K.V., and P.L. Coy. 1989. Abundance and productivity of bear food species in different forest types of northcentral Minnesota. International Conference on Bear Research and Management 8:169-181. Peine, J.D. 2001. Nuisance bears in communities: Strategies to reduce conflicts. Human Dimensions of Wildlife 6:223-237. Spencer, R.D., R.A. Beausoleil, and D.A. Martorello. 2007. How agencies respond to human–bear conflicts: a survey of wildlife species in North America. Ursus 18: 217–229. Theobald, D.M., and W.H. Romme. 2007. Expansion of the US wildland-urban interface. Landscape and Urban Planning 83:340-354. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616-627. Zack, C.S., B.T. Milne, and W.C. Dunn. 2003. Southern oscillation index as an indicator of encounters between humans and black bears in New Mexico. Wildlife Society Bulletin 31:517-520. Prepared by _______________________________________ Heather E. Johnson, Wildlife Researcher 124 �Table 1. Capture information for black bears that have been marked in the vicinity of Durango, CO (collared adult females are identified with an “*”). Only information from the initial capture of each individual is shown (no recaptures). Bear ID B1 B2 B3 B4 B5 B6* B7* B8* B9 B10* B11 B12 B13 B14* B15 B16 B17* B18* B19 B20 B21* B22 B23 B24* B25* B26 B27* B28 B29 B30* B31 B32 B33 B34 B35* B36 B37 B38 B39 B40* Capture Date 5/10/2011 5/12/2011 5/13/2011 5/16/2011 5/16/2011 5/17/2011 5/17/2011 5/18/2011 5/26/2011 5/26/2011 6/3/2011 6/2/2011 6/3/2011 6/6/2011 6/6/2011 6/7/2011 6/7/2011 6/8/2011 6/9/2011 6/9/2011 6/10/2011 6/10/2011 6/13/2011 6/14/2011 6/15/2011 6/15/2011 6/16/2011 6/16/2011 6/21/2011 6/22/2011 6/24/2011 6/24/2011 6/28/2011 6/28/2011 7/5/2011 7/6/2011 7/7/2011 7/13/2011 7/13/2011 7/21/2011 UTM Easting 246233 271495 271495 270950 270227 243210 243225 271478 238803 269869 252163 253216 253216 252157 253216 253216 256936 256918 235193 243258 252298 252163 246350 243252 239003 252164 243252 253233 239840 235911 239840 243252 239294 239001 246350 239840 243252 243236 251222 248550 UTM Northing 4142768 4130889 4130894 4127914 4139984 4128716 4133053 4130892 4126790 4139040 4137968 4137387 4138868 4137967 4138868 4138868 4134633 4134625 4128894 4133040 4136435 4137968 4135617 4133030 4134158 4137966 4133030 4138873 4126949 4128916 4126949 4133030 4133260 4134154 4135617 4126949 4133030 4128710 4133120 4131645 125 Sex M M M M M F F F M F M M M F M M F F M M F M M F F M F M M F M F M M F M M M M F Age 1 9 6 3 6 4 4 4 1 7 8 5 3 7 3 7 4 8 9 10 8 8 3 7 4 10 23 6 1 6 4 1 1 3 3 4 1 8 6 4 Kg 35.4 144.2 130.2 84.4 135.2 62.6 63.5 51.7 34.9 80.7 130.2 103.4 59.0 58.1 58.1 117.0 51.7 61.7 146.5 131.5 69.4 87.5 64.9 64.9 63.5 108.9 75.3 101.2 49.0 60.3 85.3 19.1 34.9 85.3 44.5 67.1 39.0 145.1 149.7 80.7 �B41 B42* B43* B44 B45 B46* B47* B48 B49* B50* B51* B52* B53 B54 B55* B56 B57* B58 B59 B60 B61 B62 B63 B64 B65* B66 B67* B68 B95 B96 B97 B98 B99 B100 B101 B102 B103 B104 B105 B106 B107 B108 B109 B110 B111 7/22/2011 7/26/2011 8/3/2011 8/3/2011 9/3/2011 8/5/2011 8/8/2011 8/10/2011 8/11/2011 8/11/2011 8/12/2011 8/12/2011 8/15/2011 8/16/2011 8/18/2011 8/29/2011 8/30/2011 8/31/2011 9/1/2011 9/2/2011 9/3/2011 9/6/2011 9/7/2011 8/6/2011 9/15/2011 9/20/2011 9/21/2011 9/21/2011 1/19/2012 1/19/2012 1/19/2012 1/26/2012 2/27/2012 2/27/2012 2/29/2012 2/29/2012 3/1/2012 3/1/2012 3/6/2012 3/8/2012 3/8/2012 3/14/2012 3/14/2012 3/15/2012 3/15/2012 237368 245945 246183 765141 245965 243435 251783 245914 243435 245965 249049 245965 243435 251898 251464 246321 243374 243374 243952 242187 244602 245790 248612 245850 243948 240731 256930 249067 247647 247647 247647 257183 249929 249929 248090 248090 243713 243713 240146 268055 268055 245785 245785 244547 244547 4132272 4141391 4142791 4132487 4139587 4128720 4131581 4139620 4128720 4139587 4130370 4139587 4128720 4130516 4134423 4132993 4135903 4135903 4132935 4133020 4130321 4128530 4131251 4141969 4134848 4130163 4134626 4133006 4142276 4142276 4142276 4134879 4137615 4137615 4126214 4126214 4120831 4120831 4132714 4139774 4139774 4138519 4138519 4140021 4140021 126 M F F M M F F F F F F F M M F M F M M F M M M M F F F M M M M M M F M F M M F F F F M M F 3 8 11 1 6 4 6 1 4 11 12 4 7 2 3 10 3 3 15 2 7 1 2 1 4 1 3 8 1 1 1 1 cub cub cub cub cub cub cub cub cub cub cub cub cub 67.1 69.9 85.3 35.4 176.0 58.1 53.5 26.3 55.3 101.2 61.7 65.3 163.3 52.6 49.0 166.9 46.3 48.1 153.3 35.4 213.6 22.7 37.2 28.6 89.8 39.9 52.6 207.7 44.0 44.0 49.0 20.9 1.1 1.2 1.8 1.7 1.9 1.7 2.0 2.7 2.7 1.4 1.4 2.5 2.5 �B112 B113 B114 B115 B116 B117 B118 B119 B120 B121* B122* B123 B124* B125* B126 B127* B128* B129* B130 B131 B132 B133* B134* B135 B136 B137 B138 B139 B140 B141* B142 B143* B144* B145* B146 B147 B148 B149 B150 B151 B152* B153 B154 B155 B156 3/15/2012 3/17/2012 3/17/2012 3/17/2012 3/20/2012 3/20/2012 3/22/2012 3/22/2012 5/27/2012 5/29/2012 5/30/2012 6/5/2012 6/6/2012 6/8/2012 6/8/2012 6/10/2012 6/11/2012 6/14/2012 6/22/2012 6/23/2012 6/28/2012 6/29/2012 6/30/2012 6/30/2012 7/1/2012 7/5/2012 7/5/2012 7/5/2012 7/5/2012 7/5/2012 7/6/2012 7/6/2012 7/7/2012 7/7/2012 7/7/2012 7/10/2012 7/11/2012 7/15/2012 7/16/2012 7/26/2012 7/17/2012 7/17/2012 7/17/2012 7/19/2012 7/19/2012 244547 245228 245228 245228 240909 240909 243524 243524 254732 251670 249059 240102 249158 244618 251670 239005 239005 254576 250152 765047 765047 765932 765932 252014 765047 249059 254997 238245 763921 765132 254997 241210 238245 763921 254739 241334 255983 244618 241334 243888 241210 249059 253439 241334 252621 4140021 4143164 4143164 4143164 4134002 4134002 4146585 4146585 4133249 4132767 4132998 4128939 4127065 4132132 4132767 4134459 4134159 4135043 4127691 4131635 4131635 4127651 4127651 4133509 4131635 4132998 4135825 4131204 4132873 4132506 4135825 4137115 4131204 4132873 4133234 4138018 4135921 4132132 4138018 4129546 4137114 4132998 4134693 4138018 4130532 127 F F M M M F M F F F F M F F F F F F M M M F F M F M F M M F M F F F M M M M M M F M M F F cub cub cub cub cub cub cub cub 1 4 5 2 7 8 1 10 8 6 1 6 1 3 8 1 2 2 2 1 3 3 3 3 9 6 5 1 3 1 2 3 8 2 3 2 1 2.6 2.5 2.0 2.0 2.0 2.0 2.5 2.9 20.9 76.2 66.2 48.1 80.7 98.9 15.9 58.1 56.2 54.4 12.7 111.6 20.4 49.0 90.7 20.9 46.3 26.8 30.8 30.4 67.1 55.3 37.2 45.4 72.6 70.3 110.2 43.5 73.9 45.4 53.5 60.3 99.8 49.9 63.5 30.8 26.3 �B157 B158 B159 B160 B161* B162 B163 B164 B165* B166 B167* B168 B169 B170 B171 B172 B173* B174* B175* B176 B177 B178 B179 B180* B181* B182 B190 B191 B192 B193 B194 B195 B196 7/19/2012 7/20/2012 7/21/2012 7/24/2012 7/25/2012 7/25/2012 7/26/2012 7/28/2012 7/29/2012 7/29/2012 7/31/2012 7/31/2012 7/31/2012 8/1/2012 8/2/2012 8/2/2012 8/3/2012 8/3/2012 8/3/2012 8/3/2012 8/4/2012 8/4/2012 8/5/2012 8/5/2012 8/5/2012 8/8/2012 8/9/2012 8/11/2012 8/11/2012 8/12/2012 8/12/2012 8/13/2012 8/14/2012 248417 252546 242236 249059 242546 249059 243954 242611 251815 252621 248578 253439 249059 249059 248192 248578 248578 253341 254916 252621 248578 249059 248578 248939 247127 259049 245293 249059 245293 243652 243218 259049 249059 4144294 4134789 4127920 4132998 4134789 4132998 4134875 4133863 4133706 4130532 4139143 4134693 4132998 4132998 4137051 4139143 4139143 4128740 4128609 4130532 4139143 4132988 4139143 4141533 4138557 4132998 4128959 4132998 4128959 4129360 4128712 4132998 4132998 128 M M F M F M F M F M F M F M M F F F F M M M M F F M M M M M M M F 6 3 2 2 5 10 1 6 12 8 18 4 2 4 2 2 5 3 10 2 7 2 1 3 3 2 12 4 9 5 5 6 2 136.1 50.8 39.9 64.0 76.2 108.0 37.6 117.0 85.3 121.6 58.1 87.5 44.5 119.3 26.8 28.1 73.9 43.5 76.2 54.4 93.9 35.4 35.4 71.7 58.1 70.8 153.3 60.3 148.8 87.5 137.0 151.0 42.2 �Figure 1. Map of the locations of the 2012 hair snare sites for the Durango and Piedra non-invasive genetic sampling grids. 129 �Figure 2. Number of black bear captures by week from May 15th through September 3rd for the 2011 and 2012 summer trapping seasons (2012 is currently ongoing). 130 �Figure 3. Locations from 48 adult female black bears collected with GPS collars from May 2011 to present in the vicinity of Durango, CO (different colored clusters of points represent different individual bears). 131 �Figure 4. Long distance movements of three collared adult female bears during the breeding season in June 2012. 132 �Appendix 1 Living with Black Bears in Colorado: A survey of your views �COLORADO PARKS & WILDLIFE 6060 Broadway • Denver, Colorado 80216 Phone (303) 297-1192 • FAX (303) 291-7109 wildlife.state.co.us • parks.state.co.us Living with Black Bears in Colorado: A survey of your views THANK YOU FOR YOUR COOPERATION! All of your responses will be kept confidential. Please return this survey in the postage-paid return envelope provided. STATE OF COLORADO John W. Hickenlooper, Governor  Mike King, Executive Director, Department of Natural Resources Rick D. Cables, Director, Colorado Parks and Wildlife Parks and Wildlife Commission: David R. Brougham  Gary Butterworth, Vice-Chair  Chris Castilian Dorothea Farris  Tim Glenn, Chair  Allan Jones  Bill Kane  Gaspar Perricone  Jim Pribyl  John Singletary Mark Smith, Secretary  Robert Streeter  Lenna Watson  Dean Wingfield Ex Officio Members: Mike King and John Salazar �Living with Black Bears in Colorado This questionnaire is part of a study to help wildlife managers learn what residents think about black bears in Colorado. This survey is your chance to tell Colorado Parks and Wildlife (CPW) how you interact with black bears and how you would like to see black bear populations managed. Results of this study will be used to help wildlife managers address black bear-human interactions while sustaining Colorado’s black bear populations. Your views are important and give us a better understanding of how residents feel about this issue. Please keep in mind that we are interested in everyone’s responses, because the opinions of all Colorado residents living in black bear country are important. You are part of a sample of Durango residents we have selected to provide opinions about black bear management. Your input is crucial for this evaluation. Even if you do not see black bears regularly or hold strong opinions about black bears, we still need to hear from you. Please complete this survey as soon as possible. When you are finished, please return it in the postage-paid envelope provided, no later than March 30, 2012. The survey should take about 20 minutes to complete. The final question provides you with an opportunity to share with us any additional comments you may have about black bears in Colorado. Your responses will remain confidential and at no time will your name be associated with any of your responses. If you have any questions or comments about this study, please contact Stacy Lischka at 303/291-7279 or by email at stacy.lischka@state.co.us. THANK YOU FOR YOUR ASSISTANCE! If you choose not to complete the questionnaire, please make a note in question 28 and return the survey in the postage-paid envelope included. �Wildlife and You. In its efforts to improve management of black bears in Colorado, Colorado Parks and Wildlife (CPW) wants to learn about how black bears affect the lives of Coloradans. In this section, please tell us a little about ways you interact with wildlife, black bears and land in Colorado. 1. The following are some ways that Coloradans interact with bears and other wildlife. Have you participated in these activities in the past 3 years? (Please check one for each item.) Yes No Yes No a. Read about bears or other wildlife b. Photographed bears or other wildlife c. Closely observed or tried to identify birds or other wildlife d. Hiked, biked, camped or backpacked in a natural area [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 e. Hunted any species of wildlife f. Grew food or flowers in a garden g. Worked on a farm or ranch [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 2. Have you ever hunted black bears in Colorado? (Please check one.) [ ]1 Yes [ ]0 No 3. Based on your experience, how has the number of black bears in the area where you live changed over the last 3 years? (Please circle only one.) Increased greatly 1 Stayed the same 2 3 4 Decreased greatly Not sure No opinion 5 6 7 4. How would you like to see the number of black bears in the area where you live change in the next 3 years? (Please circle only one.) Increase greatly 1 Stay the same 2 3 4 Decrease greatly Not sure No opinion 5 6 7 5. How important is it to you that the change in black bear populations you indicated in Question 4 occur over the next 3 years? (Please circle only one.) Very important 1 Slightly important 2 3 4 Not at all important Not sure No opinion 5 6 7 �6. People relate to wildlife in many ways; some of these relationships are listed below. Please indicate how strongly you agree or disagree with the following statements by checking one box for each item. a. I tolerate most wildlife nuisance problems. b. It is important to me to hunt game animals for recreation. c. It is important to me to observe or photograph wildlife. d. I appreciate the role wildlife plays in the environment. e. I express opinions about wildlife and their management to wildlife managers or public officials. f. It is important to me to know wildlife exist in Colorado. g. It is important to me that wildlife are included in educational materials to learn about nature. h. It is important to me to understand the behavior of wildlife. i. It is important to me to hunt game animals for food. j. I tolerate personal safety hazards associated with some wildlife. k. It is important to me to talk about wildlife with family and friends. l. Local economies benefit from the sale of equipment, supplies, or services related to wildlife recreation. m. It is important to me to see wildlife in books and movies. n. It is important to me that game animals are managed for harvest without risking the future of populations. Strongly agree Agree Neither agree, nor disagree Disagree Strongly I am disagree not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 �Your Experiences with Black Bears. Coloradans come into contact with black bears in many ways and these interactions mean different things to each person. Please tell us about your interactions with black bears and what they mean to you. 7. How important is it to you to know that that bears live in this area and that their populations will continue to exist in the future? (Please circle only one.) Very important Slightly important 1 2 3 4 Not at all important Not sure No opinion 5 6 7 8. In your opinion, how important of an issue are negative interactions between humans and black bears where you live? (Please circle only one.) Very important Slightly important 1 2 3 4 Not at all important Not sure No opinion 5 6 7 9. Overall, how would you rate management of black bears and bear-human interactions in the area where you live? (Please circle only one.) Above average Excellent 1 2 Below average Average 3 4 Not sure Poor 5 6 No opinion 7 10. How often have you experienced the following interactions with black bears in the past 3 years in the area where you live? (Please check one for each item.) a. Saw black bears in the wild, parks or preserves b. Saw black bears in urban or suburban areas of town c. Saw black bears near home d. Had a black bear break in to or attempt to break into my garbage e. Had a black bear damage my garden or fruit trees f. Had a black bear damage my bird feeder, pet feeder, or grill g. Had a black bear cause damage to other property (e.g. fences, car, garage, etc.) h. Had a black bear attack or harass my pets or livestock i. Had a black bear enter or attempt to enter my home j. Knew someone who was attacked or harassed by a black bear k. Was attacked or harassed by a black bear myself 0 times 1-2 times 3-4 times More than 5 times I am not sure. [ ]1 [ ]1 [ ]1 [ ]2 [ ]2 [ ]2 [ ]3 [ ]3 [ ]3 [ ]4 [ ]4 [ ]4 [ ]5 [ ]5 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 �11. For those interactions you have experienced, how acceptable was it to you that these events occurred? (Please check one for each item that you have experienced in the last 3 years. Please skip any items you have not experienced.) a. Saw black bears in the wild, parks or preserves b. Saw black bears in urban or suburban areas of town c. Saw black bears near home d. Had a black bear break in to or attempt to break into my garbage e. Had a black bear damage my garden or fruit trees f. Had a bear damage my bird feeder, pet feeder, or grill g. Had a black bear cause damage to property (e.g. fences, car, garage, etc.) h. Had a black bear attack or harass my pets or livestock i. Had a black bear enter or attempt to enter my home j. Knew someone who was attacked or harassed by a black bear k. Was attacked or harassed by a black bear myself Very acceptable Somewhat acceptable Neither acceptable, nor unacceptable Somewhat unacceptable Very unacceptable I am not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 12. Did you report negative interactions with bears you’ve experienced in the past 3 years to any authorities? (Please check one.) [ ]1 Yes [ ]0 No Please skip to question 14. 13. To whom did you report your negative interactions with black bears in or around Durango? (Please check all that apply.) [ ]1 Durango police department or LaPlata County sherriff’s department [ ]2 City of Durango [ ]3 Colorado Parks and Wildlife [ ]4 Bearsmart Durango [ ]5 USDA Wildlife Services �14. How likely do you believe it is that you will experience the following interactions with black bears next year where you live? (Please check one for each item.) a. See black bears in the wild, parks or preserves b. See black bears in urban or suburban areas of town c. See black bears near my home d. Have a black bear break in to or attempt to break into my garbage e. have a black bear damage my garden or fruit trees f. Have a black bear damage my bird feeder, pet feeder, or grill g. Have a black bear cause damage to other property (e.g. fences, car, garage, etc.) h. Have a black bear attack or harass my pets or livestock i. Have a black bear enter or attempt to enter my home j. Know someone who will be attacked or harassed by a black bear k. Be attacked or harassed by a black bear myself Very likely Somewhat likely Neither likely, nor unlikely Somewhat unlikely Very unlikely I am not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 15. Who do you believe is most responsible for limiting the number of negative interactions between humans and black bears in this area? (Please check only one.) [ ]1 Individual residents and landowners [ ]2 Durango police department [ ]3 City of Durango and the City Council [ ]4 Citizens’ groups or other non-profit organizations [ ]5 Colorado Parks and Wildlife [ ]6 Another Colorado state agency [ ]7 USDA Wildlife Services [ ]8 U.S. Fish and Wildlife Service or another federal agency [ ]9 Other (Please indicate.________________________________________) �Addressing Human-Black Bear Interactions. CPW is dedicated to working to address interactions between black bears and people, for the good of both the human and black bear populations. Please tell us about what you do to address bear-human interactions in your life and why you choose to take those actions. 16. The number of interactions between humans and black bears has been increasing in Colorado. Please tell us how much of a role you believe each of the following items play in this increase. (Please rank the following items from most to least important, where 1 is the most important item and 5 is the least important.) _____ The number of black bears is increasing. _____ The number of humans is increasing. _____ Individual black bears have lost their fear of humans. _____ Human development is expanding in bear habitat. _____ Black bears live in a larger area of Colorado than they did in the past. 17. Do you take any of the following actions yourself to attempt to minimize your risk of having a negative interaction with black bears in the area where you live? (Please check one for each item.) Yes No a. Use a wildlife-resistant garbage container or dumpster b. Fence my garden and/or fruit trees c. Carry bear spray when walking or recreating d. Avoid hiking or recreating in areas where bears have been seen e. Put my garbage out on the morning of pickup day, rather than the night before f. Feed my pets indoors [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 g. Not using composters, planting gardens or fruit trees h. Remove bird, squirrel and other wildlife feeders i. Fence beehives, chickens or other livestock j. Keep my pets indoors k. Keep the doors and windows of my house and car closed l. Other (Please indicate. _____________________) Yes No [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 [ ]1 [ ]2 �18. Individuals decide whether to invest their time, effort and money to reduce their chance of having an encounter with a black bear for many reasons. Which of the following is the most important reason you would decide to take action to prevent or reduce your risk of negative interactions with black bears? (Please check only one.) [ ]1 I want to protect my property (e.g. sheds, fences, etc.) from bears. [ ]2 I want to protect my pets and livestock from bears. [ ]3 I want to protect myself and my family from bears. [ ]4 It is easy to prevent or reduce negative interactions with bears. [ ]5 I want to keep bears acting wild and eating natural foods. [ ]6 City ordinances require me to take action. [ ]7 I can receive financial assistance to take actions to prevent or reduce conflicts. [ ]8 I want to prevent bears from being killed or re-located because they caused conflicts. [ ]9 My neighbors expect me to take action. [ ]10 Other (Please indicate. ____________________________________________) 19. Similarly, some individuals decide it is not worth their time, effort and money to take actions to prevent or reduce their risk of negative interactions with black bears. Which of the following items is the most important reason you decide not to take actions to prevent or reduce your risk of negative interactions with black bears? (Please check only one.) [ ]1 I have never experienced negative interactions with bears. [ ]2 I believe bear conflicts are part of the cost of living where I do. [ ]3 I do not believe my actions will prevent bear conflicts at my home. [ ]4 I do not believe I am at risk for bear conflicts. [ ]5 I believe bears that come into areas where people live should be removed or killed. [ ]6 I do not think it will harm bears to eat human food or other waste. [ ]7 It is too difficult for me to take actions to prevent or reduce conflicts. [ ]8 It is too expensive for me to take actions to prevent or reduce conflicts. [ ]9 I believe someone else (e.g. the city, CPW, etc.) is responsible for preventing bear conflicts. [ ]10 I believe bears are being well managed by someone else (e.g. the city, CPW, etc.). [ ]11 No one else in my area takes action to prevent bear conflicts. [ ]12 Black bears only cause problems during a short period of the year. [ ]13 Other (Please indicate. _______________________________________________) �20. Which of the following events would motivate you to take actions to reduce your risk of future negative interactions with bears? (Please check all that apply.) [ ]1 Receiving educational materials telling me how to avoid interactions with bears [ ]2 Knowing that I may recieve a fine for not bear-proofing my garbage, yard or home [ ]3 Feeling that my neighbors and community expect me to bear-proof my garbage, yard and home [ ]4 Having access to cheap or free materials for bear-proofing [ ]5 Having a bear break in or attempt to break in to my car or home [ ]6 Being threatened by a bear or having a friend or family member threatened by a bear [ ]7 Other (Please indicate. ________________________________________________) 21. CPW takes actions to attempt to reduce or prevent negative interactions between black bears and people. How acceptable is it to you that CPW takes the following actions to manage black bears in the area where you live? (Please check one for each item.) a. Educate citizens about how to coexist with bears in their area b. Support city ordinances that require citizens to use bearresistant garbage containers c. Provide financial assistance to residents for bear-proofing garbage, gardens and fruit trees d. Increase hunting licenses to increase bear harvest in areas with conflicts e. Fine individuals who are feeding bears intentionally or unintentionally f. Trap and relocate bears that cause conflict g. Kill bears that cause multiple conflicts h. Other (Please indicate. __________________________) Acceptable Neither acceptable, nor unacceptable Unacceptable I am not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]1 [ ]2 [ ]3 [ ]4 [ ]1 [ ]2 [ ]3 [ ]4 [ ]1 [ ]2 [ ]3 [ ]4 [ ]1 [ ]2 [ ]3 [ ]4 [ ]1 [ ]2 [ ]3 [ ]4 [ ]1 [ ]2 [ ]3 [ ]4 [ ]1 [ ]2 [ ]3 [ ]4 �22. How effective do you believe the following actions taken by government agencies can be to reduce or prevent negative interactions with bears? (Please check one for each item.) a. Educate citizens about how to coexist with bears in their area b. Back city ordinances that require bear-resistant garbage containers c. Provide financial assistance to residents for bear-proofing garbage, gardens and fruit trees d. Increase hunting licenses to increase bear harvest e. Fine individuals who fee bears intentionally or unintentionally f. Trap and relocate bears that cause conflict g. Kill bears that cause multiple conflicts h. Other (Please indicate._________________) Very effective Somewhat effective Neither effective, nor ineffective Somewhat ineffective Very ineffective I am not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 23. How effective do you believe the following actions taken by private citizens can be in reducing or preventing negative interactions with bears? (Please check one for each item.) a. Use wildlife-resistant garbage containers or dumpsters b. Fence gardens or fruit trees c. Put garbage out on the morning of pickup, rather than the night before d. Feed pets indoors e. Not use a composter, planting gardens or fruit trees f. Remove bird, squirrel and other wildlife feeders g. Fence beehives, chickens or other livestock h. Keep the doors and windows of houses and cars closed Very effective Somewhat effective Neither effective, nor ineffective Somewhat ineffective Very ineffective I am not sure. [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 [ ]1 [ ]2 [ ]3 [ ]4 [ ]5 [ ]6 �Background Information. The following questions will help us understand more about the people affected by black bear management in Colorado. All responses are confidential. 24. For how many years have you lived in Colorado? (Please indicate.) ______________ years 25. Are you [ ]1 male or [ ]2 female? (Please check one.) 26. In what year were you born? (Please indicate.) 19 _______ 27. How would you describe the area where you currently live? (Please check one.) [ ]1 Rural setting, on a farm/ranch [ ]2 Rural setting, not on a farm/ranch [ ]3 Rural subdivision [ ]4 Residential area at the edge of Durango or adjacent to a natural area [ ]5 Residential Durango, not near a natural area 28. Please use the space below to provide any additional comments you may have about black bears and their management in this area. THANK YOU FOR YOUR TIME AND ASSISTANCE! Please return this survey in the postage-paid envelope provided. �Appendix 2 Bear Survey NRS �April 18, 2012 Recently you were mailed a questionnaire seeking your views about your interactions with black bears in Durango. Our response rate to this survey was lower than we needed to be meaningful. We would like to ask you a few questions so we can understand the nature of this non-response. We are not asking you to fill out anything like the survey we previously sent you. Rather, we have attached a postage-paid, addressed postcard for you to fill out, detach, and drop in the mail. It should take no more than a minute or two to fill out the postcard. We would sincerely appreciate your taking the time to get this back to us soon, as it will provide valuable information for our study. As before, your response to this is voluntary. Nevertheless, your input is important to ensuring wildlife managers have the very best information on which to base decisions. You may be assured of complete confidentiality. The postcard has an identification number for mailing purposes only. Your name will never be linked to your responses. Your cooperation is greatly appreciated. Thank you in advance for taking the time to help us in this matter. Sincerely, Stacy Lischka Human Dimensions Specialist Colorado Parks and Wildlife Tear here and return the bottom half. ------------------------------------------------------------------- Colorado Parks and Wildlife Public Involvement Unit 6060 Broadway Denver, CO 80216 DIVISION OF CENTRAL SERVICES 1001 E 62nd Ave DENVER, CO 80216-9914 �Colorado Parks and Wildlife Public Involvement Unit 6060 Broadway Denver, CO 80216 1. How do you believe the number of black bears in the area where you live has changed over the last 3 years? (Circle one.) n=351 Increased Stayed the greatly same 5% 13% 46% 10% Decreased greatly 3% Not sure 19% No opinion 5% 2. How would you like to see the number of black bears in the area where you live change in the next 3 years? (Circle one.) n=352 Increase greatly 5% 8% Stay the same 42% 13% Decrease greatly 15% Not sure 12% No opinion 6% 3. How important is it to you to know that bears live in this area and that their populations will continue to exist in the future? (Circle one.) n=354 Very Important 51% Neither important, nor unimportant 19% 10% 2% Very unimportant 12% Not sure 1% No opinion 2% 4. How important to you are negative interactions between humans and black bears where you live? (Circle one.) n=347 Very Important 41% Neither important, nor unimportant 20% 15% 7% Very unimportant 10% Not sure 6% No opinion 2% 5. Do you take any of the following actions to minimize your risk of a negative interaction with black bears? (Check one for each item.) a. Use a wildlife-resistant garbage container or dumpster b. Fence my garden and/or fruit trees c. Carry bear spray when walking or recreating d. Avoid hiking or recreating in areas where bears have been seen e. Put my garbage out on the morning of pickup day, rather than the night before f. Feed my pets indoors g. Not using composters, planting gardens or fruit trees h. Remove bird, squirrel and other feeders n Yes No 354 47% 53% 314 49% 50% 328 10% 90% 335 34% 65% 344 84% 16% 304 89% 12% 321 42% 57% 328 63% 34% 6. Do you currently own or rent the home that you live in? (Please check one.) n=347 76% Own 24% Rent 7. In what year were you born? n=341 19 _ x = 61_ 8. Are you male or female? 47% Male n=344 53% Female �133 �Colorado Division of Parks and Wildlife July 2011 –June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 1 Federal Aid Project No. W-204-R1 : : : : : Division of Parks and Wildlife Mammals Research Carnivore Conservation Puma Population Structure and Vital Rates on the Uncompahgre Plateau Period covered: July 31, 2011−June 30, 2012 Author: Kenneth A. Logan. Personnel: K. Logan, S. Bard, B. Dunne, W. Hollerman, W. Jesson, R. Navarrete, B. Nay, H. Taylor, S. Waters, B. Banulis, T. Bonacquista, K. Crane, J. Koch, E. Phillips, and G. Watson of CPW; volunteers and cooperators including: private landowners, Bureau of Land Management, Ridgway State Park, Colorado State University, Oklahoma State University, and U.S. Forest Service. Supplemental financial support received in previous years from The Howard G. Buffett Foundation and Safari Club International Foundation. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) initiated a 10-year study on the Uncompahgre Plateau in 2004 to quantify puma population characteristics in the absence (reference period, years 1-5) and presence (treatment period, years 6-10) of sport-hunting. The purpose of the study is to evaluate assumptions underlying the Colorado Parks and Wildlife model-based approach to managing pumas with sport-hunting in Colorado. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 pumas for population research purposes on the Uncompahgre Plateau (Logan 2009). This report provides information on the third year of the treatment period (TY3), August 2011 through July 2012, on puma population characteristics and dynamics with hunting as a mortality factor. Puma sport-hunting opened November 21 and closed December 23, 2011 after a quota of 8 independent pumas was harvested. The harvest was designed to test the management assumption that a 15% harvest of independent pumas results in a stable-to-increasing population. A total of 8 pumas were killed: 3 adult females, 1 adult male, and 4 subadult males. The harvest of 8 independent pumas represented 16.7% of the 48 independent pumas in our minimum count during November 2011 to April 2012. Independent females and males comprised 37.5% and 62.5% of the harvest, respectively. Four other radio-collared independent pumas (2 adult females, 2 adult males) and 3 non-collared adults (1 female, 2 males) in the study area population died during the Colorado puma hunting season. Of those, 2 adult females died of natural causes and the remainder was killed by puma hunters in GMUs adjacent to 134 �the study area. The total mortality of 15 independent pumas during the TY3 hunting season represented 31.2% of the 48 minimum count of independent pumas on the study area. Seventy-four hunters requested mandatory permits with an attached voluntary hunter survey in TY3. Thirty-six of the hunters provided responses to written (n = 31) or telephone call follow-up contact (n = 5). An estimated 49 hunters actually hunted on the study area, of which about 16.3% harvested pumas and 26.5% captured pumas (i.e., harvested plus treed and released). Twenty-four of 26 answering hunters responded that they were selective hunters, and the capture, tracking, and population data indicated that most hunters practiced selection. Puma tracks < 1 day old encountered by hunters and pumas captured by hunters indicated that independent female pumas were detected more frequently than males by hunters. From August 2011 to July 2012 twenty-eight individual pumas were captured 35 times by research teams. Two capture teams with dogs operated over 79 search days from December 27, 2011 through April 12, 2012 to find 268 puma tracks, pursue pumas 89 times, and capture 21 pumas 26 times. Capture efforts with cage traps resulted in the capture of 1 adult female for the first time. Nine new cubs were captured and radio-collared. A total of 42 pumas were monitored by radio-telemetry in TY3. Search efforts also revealed the presence of at least 26 other independent pumas. Our minimum count of 48 independent pumas from November 2011 to April 2012 included: 31 females and 17 males. The minimum count of 48 independent pumas in TY3 was lower than 52 in TY2 and 55 in TY1. A preliminary minimum estimated density of independent pumas was 2.87/100 km2. The proportion of radio-collared adult females giving birth in the August 2011 to July 2012 biological year was 0.19 (3/16). Three litters that could be dated to month of birth were produced in August. Since 2005 a birth peak has occurred from May through August, involving 86% of births. We monitored 20 female and 7 male adult radio-collared pumas for survival and agent-specific mortality. Survival rates in TY3 for adult females (0.548, SE=0.1063) and males (0.167, SE=0.1076) were lower than in TY1 and TY2. A preliminary assessment is that hunting mortality is additive to natural mortality. Of 12 cubs monitored with radiotelemetry in TY3, 6 died. Three died of starvation after their mothers were killed by puma hunters. Three others died of natural-related causes, including 2 that starved after their mother died of a natural cause. One non-marked male cub was struck and killed by a vehicle on state highway 62. Puma harvest, capture, and radio-telemetry data from the beginning of this study to the present provided information on dispersals of 33 pumas initially marked on the study area. Those pumas moved from about 18.2 to 370 km from initial capture sites. We investigated the prevalence of Trichinella spp. in pumas killed in southwest Colorado in collaboration with Dr. Mason Reichard, Oklahoma State University. Twelve of 14 (85.7%) puma tongues were infected with Trichinella. The apparent decline in the puma population on the study area during TY1 to TY3 necessitates a reduction in the harvest quota to continue to test the harvest assumption for a stable-to-increasing puma population. This change will be pursued for TY4 and the results of the harvest monitored through the end of the treatment period. 135 �WILDLIFE RESEARCH REPORT PUMA POPULATION STRUCTURE AND VITAL RATES ON THE UNCOMPAHGRE PLATEAU, COLORADO KENNETH A. LOGAN P. N. OBJECTIVE Quantify puma population sex and age structure; estimate puma population vital rates, including: reproduction of females, stage-specific survival, and immigration and emigration; quantify agent-specific mortality rates; model puma population dynamics; develop and execute the puma harvest manipulation to begin the population-wide test of Colorado Parks and Wildlife (CPW) puma management assumptions in the third year of a five-year Treatment Period of the Uncompahgre Plateau Puma Project― all to improve the CPW model-based approach to managing pumas in Colorado. SEGMENT OBJECTIVES 1. Execute the third year of the five-year treatment period by working with CPW biologists and managers to manipulate the puma population with sport-hunting and to survey hunters. 2. Continue gathering data on puma population sex and age structure. 3. Continue gathering data for estimates of puma reproduction rates. 4. Continue gathering data to estimate puma sex and stage-specific survival rates. 5. Continue gathering data on agent-specific mortality. 6. Explore frequency of Trichinella ssp. in pumas harvested in southwest Colorado in collaboration with Dr. Mason Reichard, Veterinary Health Science, Oklahoma State University. INTRODUCTION Colorado Parks and Wildlife managers need reliable information on puma biology and ecology in Colorado to develop sound management strategies that address diverse public values and the CPW objective of “achieving healthy, self-sustaining populations” through management (Colorado Division Of Wildlife 2002-2007 Strategic Plan:9). Although 4 puma research efforts have been made in Colorado since the early 1970s and puma harvest data is compiled annually, reliable information on certain aspects of puma biology and ecology, and management tools that may guide managers toward effective puma management is lacking. Mammals Research staff held scoping sessions with a number of the CPW’s wildlife managers and biologists prior to initiating the project. In addition, we consulted with other agencies, organizations, and interested publics either directly or through other CPW employees. In general, CPW staff in western Colorado highlighted concern about puma population dynamics, especially as they relate to their abilities to manage puma populations through regulated sport-hunting. Secondarily, they expressed interest in puma―prey interactions. Staff on the Front Range placed greater emphasis on puma―human interactions. Staff in both eastern and western Colorado cited information needs regarding effects of puma harvest, puma population monitoring methods, and identifying puma habitat and landscape linkages. Management needs identified by CPW staff and public stakeholders form the basis of Colorado’s puma research program, with multiple lines of inquiry (i.e., projects): Improve our ability to manage puma hunting with enhanced scientific bases, strategies, and tools― ● Puma population characteristics (i.e., density, sex and age structure). ● Puma population dynamics and vital rates (i.e., birth rates, survival rates, emigration rates, immigration rates, population growth rates). 136 �● Field methods and models for assessing and tracking changes in puma populations. ● Relative vulnerability of puma sex and age classes to hunter harvest. Improve our understanding of puma habitat needs and interrelationships of puma management units― ● Puma habitat use, movements, and use of landscape linkages. ● Puma recruitment patterns (i.e., progeny, immigration, emigration). ● Models for identifying puma habitat and landscape linkages. Improve our understanding of the puma’s role in the ecology of other species ● Relationships of puma to mule deer, elk, and other natural prey. ● Relationships of puma to species of special concern, e.g., desert bighorn sheep. Improve our understanding of puma-human interactions and abilities to manage them ● Behavior of puma in relation to people and human facilities. ● Puma predation on domestic animals. ● Effects of translocating nuisance pumas. ● Effects of aversive conditioning on pumas. While all projects cannot be addressed concurrently, understanding their relationships to one another is expected to help individual projects maximize their benefits to other projects that will assist the CPW to achieve its strategic goal in puma management (Fig.1). This project has been addressing all of the grayshaded components on the left side of the conceptual model in Figure 1. Management issues identified by managers translate into researchable objectives, requiring descriptive studies and field manipulations. Our goal is to provide managers with reliable information on puma population biology and to develop useful tools for their efforts to adaptively manage puma in Colorado to maintain healthy, self-sustaining populations. The highest-priority management needs are being addressed with this intensive population study that focuses on puma population dynamics using sampled, tagged, and GPS/VHF-radio-collared pumas to investigate the effects of sport-hunting and other causes of mortality on puma population dynamics. Those objectives include: Describe and quantify puma population sex and age structure. Estimate puma population vital rates, including: reproduction rates, age-stage survival rates, emigration rates, immigration rates. Estimate agent-specific mortality rates. Improve the CPW’s puma model-based management and attendant assumptions with Coloradospecific data from objectives 1―3. Consider other useful models. Conduct a pilot study to develop methods that yield reliable estimates of puma population abundance. Investigate diseases in pumas. A descriptive and manipulative study will estimate population parameters in an area that appears typical of puma habitat in western Colorado and will yield defensible population parameters based upon contemporary Colorado data. This study will be conducted in two 5-year periods. A completed 5-year reference period, 2004-09, (i.e., absence of recreational hunting) allowed puma life history traits to interact with the main habitat factors that influenced puma population growth (e.g., prey availability and vulnerability, Pierce et al. 2000, Logan and Sweanor 2001, Logan 2009). A subsequent 5-year treatment period started in 2009-10 which involves the use of controlled recreational hunting to manipulate the puma population. 137 �TESTING ASSUMPTIONS AND HYPOTHESES Hypotheses associated with main objectives 1―5 of this puma population research are structured to test assumptions guiding puma management in Colorado. 1. Considering limitations (i.e., methods, number of years, assumption violations) to the previous Colorado-specific studies on puma populations (Currier et al. 1977, Anderson et al. 1992, Koloski 2002), managers assume that puma population densities in Colorado are within the range of those quantified in more intensively studied populations in Wyoming (Logan et al. 1986), Idaho (Seidensticker et al. 1973), Alberta (Ross and Jalkotzy 1992, and New Mexico (Logan and Sweanor 2001). The CPW assumes density ranges of 2.0−4.6 puma/100 km2 (i.e., includes pumas of all stage classes - adults, subadults, and cubs, J. Apker, CPW Carnivore Biologist, person. commun. Nov. 19, 2003) to extrapolate to Data Analysis Units (DAUs) to guide the model-based quota-setting process. Likewise, managers assume that the population sex and age structure is similar to puma populations described in the intensive studies. Using intensive efforts to capture, mark, and estimate non-marked animals developed and refined during the study to estimate the puma population, the following will be tested: H1: Puma densities during the 5-year reference period (absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will vary within the range of 2.0 to 4.6 puma/100 km2 and will exhibit a sex and age structure similar to puma populations in Wyoming, Idaho, Alberta, and New Mexico. 2. Recreational puma hunting management in Colorado DAUs is guided by a model to estimate allowable harvest quotas to achieve one of two puma population objectives: 1) maintain puma population stability or growth, or 2) cause puma population decline (CDOW, Draft L-DAU Plans, 2004, CDOW 2007). These objectives are expected to provide both the capacity for puma population resiliency to achieve a state-wide goal of a healthy, self-sustaining puma population while managing the puma population to provide sport-hunting opportunity and population control in some DAUs (even though puma population dynamics in any DAUs are not known). Basic model parameters are: puma population density, sex and age structure, annual population growth rate, and relative puma habitat quality and quantity. Parameter estimates are currently chosen from literature on studies in western states that are judged to provide reliable information. Background material used in the model assumes a moderate annual rate of growth of 15% (i.e., λ = 1.15) for the adult and subadult puma population (CDOW 2007). This assumption is based upon information with variable levels of uncertainty (e.g., small sample sizes, data from habitats dissimilar to Colorado). Parameters influencing λ include population density, sex and age structure, female age-at-first-breeding, reproduction rates, sex- and age-specific survival, immigration and emigration. H2: Population parameters estimated during a 5-year reference period (in absence of recreational puma hunting) in conifer and oak communities with deer, elk and other prey populations typical of those communities in Colorado will yield an estimated annual adult plus subadult population growth rate that will match or exceed λ = 1.15. 3. An assumption is that the CPW can manage puma population growth through recreational hunting on the basis that for a stable puma population hunting removes the annual increment of population growth (i.e., from current judgments on population density, structure, and λ) Puma harvest rate formulations for DAUs assumes that total mortality (i.e., harvest plus other detected deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (CDOW 2007). This assumption is 138 �vital to providing the capacity for resiliency in the state-wide puma population which is hunted by applying this assumption to about three-quarters of the puma GMUs in the state. H3: Total mortality of an estimated 15% of the adults and subadults with no more than 45% of the total mortality comprised of females will not result in a declining trend of the harvest-age segment of the population. 4. To reduce a puma population, hunting must remove more than the annual increment of population growth. For DAUs with the objective to suppress the puma population, the total mortality guide of greater than 15 to 28% of the harvest-age population with greater than 45% comprised of females is suggested (CDOW 2007). This assumption is applied to about one-quarter of the GMUs in the state. H4: Total mortality of an estimated 16% or greater of the harvestable population with greater than 45% females will cause a declining trend in the abundance of harvest-age pumas (i.e., adults and subadults). 5. The increase and decline phases of the puma population make it possible to test hypotheses related to shifts in the age structure of the population which have been linked to harvest intensity in Wyoming and Utah. H5: The puma population on the Uncompahgre Plateau study area will exhibit a young age structure after hunting prohibition at the beginning of the reference period. During the 5 years of hunting prohibition, greater survival of independent pumas will cause an older age structure in harvest-age pumas (i.e., adults and subadults) as suggested by the work of Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. As hunting is re-instated in the treatment period, the age structure of harvested pumas and the harvest-age pumas in the population will decline as observed by Anderson and Lindzey (2005) in Wyoming and Stoner (2004) in Utah. Researchers in Wyoming (Anderson and Lindzey 2005) concluded that sex and age composition of the harvest varies predictably with puma population size because the likelihood of a specific sex or age class of puma being harvested with the use of hounds is a product of the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Results of that study suggest that managers could use sex and age composition of the harvest to infer puma population changes (Anderson and Lindzey 2005). The CPW currently uses this approach as one tool to infer potential DAU puma population dynamics (CDOW 2007). This assumes no purposeful selection by hunters for any particular sex or age-stage other than the puma must be legal (i.e., independent subadult or adult, not a lactating female or a female in association with spotted cubs) and that changes in the sex and age structure of the harvested pumas is due solely to changes in the relative abundance of particular sex and age classes in the population and their relative vulnerability to harvest. Theoretically, pumas that travel longer distances with movements that intercept access routes used by hunters (i.e., roads, trails) should be more exposed to detection by hunters and thus more vulnerable to harvest. A key assumption to this method is that pumas are killed as they are encountered and the harvest sex and age composition will reliably indicate whether a population is stable, increasing, or declining even if harvest intensity does not vary. Thus, an alternate view is that a population segment, such as independent females, may be more abundant and have shorter movement lengths, yet be detected more frequently by hunters. However, because the same intensively studied Wyoming puma population was manipulated over 6 years with varying intensities of harvest (Anderson and Lindzey 2005), variations in harvest structure using the same harvest level over a period of years could not be examined. This is a property we will investigate during the treatment period on the Uncompahgre Plateau puma study. Moreover, we will directly evaluate to what extent puma harvest might be influenced by hunter selection. A hunter survey is intended to reveal puma hunter behavior, detection of different classes of pumas, and lack of or presence of hunter selection. These data should allow us to examine the credibility of the assumption of non-selection by hunters and the robustness of this technique in gauging puma population dynamics relative to harvest. 139 �We want to examine the usefulness of this approach in Colorado. CPW managers attempt to weight sport-harvest toward male pumas in GMUs with the stable-to-increasing population objective with an active educational program (i.e., mandatory hunter exam, brochure, workshops). Thus, there is a need to test assumptions associated with the Anderson and Lindzey (2005) method. H6: No hunter selection is practiced so that the sex and age structure of pumas harvested by hunters in this population protected from hunting during a 5-year reference period and subsequently managed for stability or increase with conservative harvest levels will reflect the relative vulnerabilities to detection and capture with dogs during each year in the 5-year treatment period in this order from high to low vulnerabilities: subadult males, adult males, subadult females, adult females without cubs or with cubs >6 months old, and adult females with cubs ≤6 months old (Barnhurst 1986, Anderson and Lindzey 2005). In each of the 5 years of the treatment period, subadults and adult males should comprise the majority of the harvest and reflect the assumed sex and age structure (Anderson and Lindzey 2005) of a puma population managed for a stable to increasing phase and not hunted for 5 previous years (i.e., a puma population source). Desired outcomes and management applications of this research include: 1. Quantification of variations in puma population density, sex and age structure, growth rates, vital rates, and an understanding of factors affecting them will aid adaptive puma management by yielding population parameters and tools useful for assessing puma population dynamics, evaluation of management alternatives, and effects of management prescriptions. 2. Testing assumptions about puma populations, currently used by CPW managers, will help managers to biologically support and adapt puma management based on Colorado-specific estimated puma population characteristics, parameters, and dynamics. 3. Methods for assessing puma population dynamics will allow managers to evaluate modeled populations and estimate effects of management prescriptions designed to achieve specified puma population objectives in targeted areas of Colorado. Ascertaining puma numbers and densities during the project will allow assessment of monitoring techniques. Potential methods include use of harvest sex and age structure and photographic and DNA genotype capture-recapture. Study plans to develop and test feasible field and analytical methods will be developed as we learn the logistics of performing those methods, after we have preliminary data on puma demographics and movements which will inform suitable sampling designs, and if we have adequate funding. 4. Information which will be disseminated to citizen stakeholders interested in pumas in Colorado, and thus contribute to informed public participation in puma management. STUDY AREA The study area for the puma population research is on the Uncompahgre Plateau (in Mesa, Montrose, Ouray, and San Miguel Counties; Fig. 2). The study area includes about 2,253 km2 (870 mi.2) of the southern halves of Game Management Units (GMUs) 61 and 62, and about 155 km2 (60 mi.2) of the northern edge of GMU 70 (between state highway 145 and San Miguel River). The area is bounded by state highway 348 at Delta, 25 Mesa road and Forest Service road FS503 to Nucla, state highway 97 to state highway 141 to state highway 145 to Placerville, state highway 62 to Ridgeway, U.S. highway 550 to Montrose, and U.S. highway 50 to Delta. The study area seems typical of puma habitat in Colorado that has vegetation cover that varies from the pinion-juniper covered foothills starting from about 1,700 m elevation to the spruce-fir and aspen forests growing to the highest elevations of about 3,000 m. Mule deer (Odocoileus hemionus) and elk (Cervus elaphus) are the most abundant wild ungulates available for puma prey. Cattle and domestic sheep are raised on summer ranges on the study area. People reside year-round along the eastern and western fringe of the area, and there is a growing residential presence especially on the southern end of 140 �the plateau. A highly developed road system makes the study area easily accessible for puma research efforts. A detailed description of the Uncompahgre Plateau is in Pojar and Bowden (2004). METHODS Reference and Treatment Periods This research was structured in two 5-year periods: a reference period (years 1―5) and a treatment period (years 6―10). The reference period was closed to puma hunting on the study area and was expected to cause a population increase phase. The treatment period (starting in November 2009) involves manipulation of the puma population with sport-hunting structured to achieve a management objective for a stable to increasing population. In both phases, puma population structure, and vital rates are being quantified, and management assumptions and hypotheses regarding population dynamics and effects of harvest are being tested. Contingent upon results of pilot studies, we will also assess enumeration methods for estimating puma population abundance. The reference period, without recreational puma hunting as a major limiting factor, was consistent with the natural history of the current puma species in North America which evolved life history traits during the past 10,000 to 12,000 years (Culver et al. 2000) that enable pumas to survive and reproduce (Logan and Sweanor 2001). In contrast, puma hunting, with its modern intensity and ingenuity, might have influenced puma populations in western North America for at least the past 100 years. Hence, the reference period, years 1 to 5, provided conditions where individual pumas in this population expressed life history traits interacting with the environment without recreational hunting as a limiting factor. Theoretically, the main limiting factor was vulnerable prey abundance (Pierce et al. 2000, Logan and Sweanor 2001). This allowed researchers to understand basic system dynamics before manipulating the population with controlled recreational hunting. In the reference period, all pumas in the study area were protected, except for individual pumas involved in depredation on livestock or human safety incidents. In addition, all radio-collared and ear-tagged pumas that ranged in a buffer zone in the northern halves of GMUs 61 and 62 were protected from recreational hunting mortality. The reference period allowed researchers to quantify baseline demographic data on the puma population to estimate parameters useful for assessing the CPW’s assumptions for its model-based approach to puma management. The reference period also facilitated other operational needs (because hunters did not kill the animals) including the marking of a large proportion of the puma population for parameter estimates and gathering movement data from GPS-collared pumas. During the treatment period, years 6 to10, recreational puma hunting is occurring on the same study area using management prescriptions structured from information learned during previous years. Using recreational hunting for the treatment is consistent with the CPW’s objectives of manipulating natural tendencies of puma populations, particularly survival, to maintain either population stability or increase or suppression (CDOW, Draft L-DAU Plans, 2004). Theoretically, survival of independent pumas is being influenced mainly by recreational hunting, which is being quantified by agent-specific mortality rates of radio-collared pumas. Dynamics of the puma population are being manipulated to evaluate hypotheses that are related to effects of hunting (i.e.,: effects of harvest rates, relative vulnerability of puma sex and age classes to hunting, variations in puma population structure due to hunting). The killing of tagged and collared pumas during the treatment period is not hampering operational needs (as it would have during the start-up years), because a majority of independent pumas in the population have already been marked, and sampling methods formalized. Pumas on the study area that may be involved in depredation of livestock or human safety incidences may be lethally controlled. Researchers that find that GPS-collared pumas have killed domestic livestock will record such incidents to facilitate reimbursement to the property owner for loss of 141 �the animal(s). In addition, researchers will notify the Area Manager of the CPW if they perceive that an individual puma may be a threat to public safety. Field Methods Puma Capture: Realizing that pumas live at low densities and capturing pumas is difficult, as a starting point, our logistical aim was to have a minimum of 6 puma in each of 6 categories (36 total) radio-tagged in any year of the study if those or greater numbers are present. The 6 categories are: adult female, adult male, subadult female, subadult male, female cub, male cub. Our aim was to provide more quantitative and precise estimates of puma demographics than were achieved in earlier Colorado puma studies. This relatively large number of pumas might represent the majority of the puma population on the study area, and would provide the basic data for age- and sex-specific reproductive rates, survival rates, agent-specific mortality rates, emigration, and other movement data. Puma capture and handling procedures were approved by the CPW Animal Care and Use Committee (file #08-2004). All captured pumas were examined thoroughly to ascertain sex and describe physical condition and diagnostic markings. Ages of adult pumas were estimated initially by the gum-line recession method (Laundre et al. 2000) and dental characteristics of known-age puma (Logan and Sweanor, unpubl. data). Ages of subadult and cub pumas were estimated initially based on dental and physical characteristics of known-age pumas (Logan and Sweanor unpubl. data). Body measurements recorded for each puma included at a minimum: mass, pinna length, hind foot length, plantar pad dimensions. Tissue collections included: skin biopsy (from the pinna receiving the 6 mm biopsy punch for the ear-tags), and blood (30 ml from the saphenous or cephalic veins) for genotyping individuals, parentage and relatedness analyses, and disease screening; hair (from various body regions) for genotyping tests of field gathered samples. Universal Transverse Mercator Grid Coordinates on each captured puma were recorded via Global Positioning System (GPS, North American Datum 27). Pumas were captured year-round using 4 methods: trained dogs, cage traps, foot-hold snares, and by hand (for small cubs). Capture efforts with dogs were conducted mainly during the winter when snow facilitated thorough searches for puma tracks and enabled dogs to follow puma scent. The study area was searched systematically multiple times per winter by four-wheel-drive trucks, all-terrain vehicles, snowmobiles, and on foot. When puma tracks ≤1 day old were detected, trained dogs were released to pursue pumas for capture. Pumas usually climbed trees to take refuge from the dogs. Adult and subadult pumas captured for the first time or requiring a change in telemetry collar were immobilized with Telazol (tiletamine hydrochloride/zolazepam hydrochloride) dosed at 5 mg/kg based on estimated body mass (Lisa Wolfe, DVM, CPW, attending veterinarian, pers. comm.). The immobilizing agent was delivered into the caudal thigh muscles via a Pneu-Dart® shot from a CO2-powered pistol. Immediately, a 3m-by-3m square nylon net was deployed beneath the puma to catch it in case it fell from the tree. A researcher climbed the tree, fixed a Y-rope to two legs of the puma and lowered the cat to the ground with an attached climbing rope. Once the puma was on the ground, its head was covered, its legs tethered, and vital signs monitored (Logan et al. 1986). Normal signs include: pulse ~70 to 80 bpm, respiration ~20 bpm, capillary refill time ≤2 sec., rectal temperature ~101oF average, range = 95 to 104oF (Kreeger 1996). Pumas that climbed trees too dangerous for the pumas or researchers for capture were released without handling, or we encourage the animals to leave the tree by heaving snowballs toward them. If the pumas climbed a safe tree, then we handled them as described above. A cage trap was used to capture adults, subadults, and large cubs when pumas were lured into the trap using road-killed or puma-killed ungulates (Sweanor et al. 2008). A cage trap was set only if a target puma scavenged on the lure (i.e., an unmarked puma, or a puma requiring a collar change). Researchers continuously monitored the set cage trap from about 1 km distance by using VHF beacons on the cage 142 �and door. Researchers handled captured pumas within 30 minutes of capture. Puma were immobilized with Telazol injected into the caudal thigh muscles with a pole syringe. Immobilized pumas were restrained and monitored as described previously. If non-target animals were caught in the cage trap, we opened the door and allowed the animal to leave the trap. Small cubs (≤10 weeks old) were captured using our hands (covered with clean leather gloves) or with a capture pole. Cubs were restrained inside new burlap bags during the handling process and were not administered immobilizing drugs. Cubs at nurseries were approached when mothers were away from nurseries (as determined by radio-telemetry). Cubs captured at nurseries were removed from the nursery a distance of 30 to 100 m to minimize disturbance and human scent at nurseries. Immediately after handling processes were completed, cubs were returned to the exact nurseries where they were found (Logan and Sweanor 2001). Marking, Global Positioning System- and Radio-telemetry: Pumas did not possess easily identifiable natural marking, such as tigers (see Karanth and Nichols 2002), therefore, the capture, marking, and GPS- or VHF- collaring of individual pumas was essential to a number of project objectives, including estimating numbers, vital rates, and gathering movement data relevant to population dynamics (i.e., emigration and movement across Data Analysis Unit boundaries). Adults, subadults, and cubs were marked 3 ways: GPS/VHF- or VHF-collar, ear-tag, and tattoo. The identification number tattooed in the pinna was permanent and could not be lost unless the pinna was severed. A colored (bright yellow or orange), numbered rectangular (5 cm x 1.5 cm) ear-tag (Allflex USA, Inc., DFW Airport, TX) was inserted into each pinna to facilitate individual identification during direct recaptures. Cubs ≤10 weeks old were ear-tagged in only one pinna. Adult and subadult female pumas were fitted with GPS collars (approximately 400 g each, Lotek Wireless, Canada) if available. Initially, GPS-collars were programmed to fix and store puma locations at 4 times per day to sample daytime, nighttime, and crepuscular locations (i.e., 0:00, 06:00, 12:00, 19:00). GPS locations for pumas provided precise, quantitative data on movements to assess the relevance of puma DAU boundaries, our search efforts, and to evaluate puma behavior and social structure. The GPScollars also provided basic information on puma movements and locations to design other pilot studies in this program on vulnerability of puma to sport-harvest, habitat use, and enumeration methods (e.g., photographic or DNA mark-recapture). Subadult male pumas were fitted initially with conventional VHF collars (Lotek, LMRT-3, ~400 g each) with expansion joints fastened to the collars, which allowed the collar to expand to the average adult male neck circumference (~46 cm). If subadult male pumas reached adulthood on the study area, we would recapture them and fit them with GPS collars. In addition, other adult and female subadult pumas were fitted with VHF collars when GPS collars were not available. VHF radio transmitters on GPS collars enabled researchers to find those pumas on the ground in real time to acquire remote GPS data reports, facilitate recaptures for re-collaring, and to determine their reproductive and survival status. VHF transmitters on GPS- and VHF-collars had a mortality mode set to alert researchers when pumas were immobile for 3 to 24 hours so that dead pumas could be found to quantify survival rates and agent-specific mortality rates by gender and age. Locations of GPS- and VHFcollared pumas were identified about once per week (as flight schedules and weather allowed) from light fixed-wing aircraft (e.g., Cessna 185) fitted with radio signal receiving equipment (Logan and Sweanor 2001). GPS- and VHF-collared pumas were located from the ground opportunistically using a hand-held yagi antenna. At least 3 bearings on peak aural signals were mapped to fix locations and estimate location error around those locations (Logan and Sweanor 2001). Aerial and ground locations were plotted on 7.5 minute USGS maps (NAD 27) and UTMs along with location attributes were recorded on standard forms. GPS and aerial locations were mapped using GIS software. 143 �We attempted to collar all cubs in observed litters. Cubs were fit with small VHF transmitters mounted on expandable collars that expand to adult neck size (Wildlife Materials, Murphysboro, Illinois, HLPM-2160, 47g, Telonics, Inc., Mesa, Arizona MOD 080, 62g, or Telonics MOD 205, 90g,) when cubs weighed 2.3―11 kg (5―25 lb). Cubs could wear these small expandable collars until they were over 12 months old. Cubs were recaptured to replace collars as opportunities allowed. Monitoring radio-collared cubs allowed quantification of survival rates and agent-specific mortality rates (Logan and Sweanor 2001). Analytical Methods Population characteristics each year were tabulated with the number of individuals in each sex and age category. Age categories, as mentioned, include: adult (puma ≥24 months old, or younger breeders), subadults (young puma independent of mothers, <24 months old that do not breed), cubs (young dependent on mothers, also called kittens) (Logan and Sweanor 2001). When data allowed, age categories were further partitioned into months or years. Reproductive Rates: Reproductive rates were estimated for GPS- and VHF-collared female pumas directly (Logan and Sweanor 2001). Genetic paternity analysis will be used to ascertain paternity for adult male pumas (Murphy et al. 1998). Survival and Agent-specific Mortality Rates: Radio-collared pumas provided known fate data used to estimate survival rates for each age stage using the Kaplan-Meier procedure to staggered entry (Pollock et al. 1989). A binomial survival model was also used for crude estimates of survival during the subadult age stage (Williams et al. 2001:343-344). In addition, when data collection is complete, survival rates will be modeled in program MARK (White and Burnham 1999, Cooch and White 2004) where effects of individual (e.g., sex, age stage, reproductive stage) and temporal (i.e., reference period, treatment period) covariates to survival can be examined. Agent-specific mortality rates can also be analyzed using proportions and Trent and Rongstad procedures (Micromort software, Heisey and Fuller 1985). Population Inventory: The population of interest was independent pumas (i.e., adults and subadults) mainly during November to March which corresponds with the Colorado puma hunting season. Independent pumas were those that could be legally killed by recreational hunters. Initially, we estimated the minimum number of independent pumas and puma density (i.e., number of independent puma/100 km2) each winter. The minimum number of independent pumas included all marked pumas known to be present on the study area during the period, plus individuals thought to be non-marked and detected by visual observation or tracks that were separated from locations of radio-collared pumas. Furthermore, adults comprised the breeding segment of the population and subadults were non-breeders that are potential recruits into the adult population in ≤1 year. The sampling unit was the individual independent puma (~≥1 yr. old). Puma Population Dynamics: A deterministic, discrete time model parameterized with population characteristics and vital rates from this research was used to assess puma population dynamics (Logan 2008). Functional Relationships: Once data collection is complete, a variety of analyses will be conducted to estimate parameters and examine functional relationships. Graphical methods will be used to initially examine functional relationships among puma population parameters. Linear regression procedures and coefficients of determination will be used to assess functional relationships if data for the response variable are normally distributed and the variance is the same at each level. If the relationship is not linear, data is non-normal, and variances are unequal, we will consider appropriate transformations of 144 �the data for regression procedures (Ott 1993). Non-parametric correlation methods, such as Spearman’s rank correlation coefficient, will also be used where appropriate to test for monotonic relationships between puma abundance and other parameters of interest (Conover 1999). Relationships of explanatory variables to survival parameters will be modeled in MARK. Statistical analyses can be performed in a variety of software (e.g., SYSTAT, R, and MARK). RESULTS AND DISCUSSION Segment Objective 1 Puma harvest: This biological year, August 2011 to July 2012, was the third year of the treatment period (TY3) in this study of puma population dynamics on the Uncompahgre Plateau. The hunting season on the study area began on November 21, 2011 and was scheduled to extend to January 31, 2011, unless the harvest quota was taken before then. The harvest design quota was 8 pumas (i.e., 15% harvest of the estimated minimum number of independent pumas), with the objective to manage for a stable to increasing population. This harvest design tests the CPW’s current assumption that total mortality (i.e., harvest plus other natural deaths) in the range of 8 to 15% of the harvest-age population (i.e., independent pumas comprised of adults plus subadults) with the total mortality comprised of 35 to 45% females (i.e., adults and subadults) is acceptable to manage for a stable-to-increasing puma population (Assumption and Hypothesis 3 p.5-6 this report). The initial quota of 8 pumas for TY1 was based on the projected minimum number of 53 independent pumas expected on the study area in winter 2009-10, modeled from a minimum count of pumas during winter 2007-08 (Table 1; Logan 2010). The quota of 8 pumas for TY3 was based on the observed minimum count of 52 independent pumas during November 2010 to April 2011 in TY2 and that approximately the same number of independent pumas was expected during the puma hunting season for TY3. The hunting structure in TY3 was the same as in TY1 and TY2. The number of puma hunters on the study area was not limited. Each hunter on the study area was required to obtain a hunting permit from the CPW Montrose Service Center. Permits were free and unlimited. Each permit allowed the individual hunter with a legal puma hunting license in Colorado to hunt in the puma study area for up to 14 days from the issue date. Unsuccessful hunters that wanted to continue hunting past the permit expiration date requested a new permit for another 14 days, or until the hunter killed a puma within the season, or the season on the study area closed due to the quota being reached, or the end of the hunting season. This permit system allowed the CPW to monitor the number of hunters on the study area and to contact each hunter for survey information (see later in this section). All pumas harvested on the study area were examined by principal investigator K. Logan or a wildlife research technician and sealed as mandated by Colorado statute. All successful hunters reported their puma kill and presented the puma carcass for inspection by CPW within 48 hours of harvest. Upon inspection, the following data were recorded: sex, age, and location of harvest. In addition, an upper premolar tooth was collected for aging (i.e., mandatory) and a tissue sample was collected for DNA genotyping. Each successful hunter was also asked at that time to complete a one-page hunter survey form. All other hunters that did not report a puma kill on the study area were asked to complete the survey form and return it in a stamped envelope that was provided. An attempt was made to contact other hunters by telephone if they did not mail in surveys. The puma hunting season occurred on the study area from November 21 to December 23, 2011, taking 33 days to fill the quota of 8 pumas. This was 12 days more than it took to harvest 8 pumas in TY2 (i.e., 21 days, Nov. 22 to Dec. 12, 2010) and 7 more days than it took to harvest 8 pumas in TY1 (i.e., 26 days, Nov. 16 to Dec. 11, 2009). Eight pumas were killed on the study area, including: 3 adult females, 1 adult male, and 4 subadult males (Table 2). Of the 8 harvested pumas, 6 were marked: F3, F70, F75, M120, M138, and M141. In addition to the pumas killed on the study area during the Colorado puma 145 �hunting season, adult males M67 and M87 were killed by hunters in north GMU61, and adult females F104 and F119 died of natural causes. In addition, 3 non-marked adult pumas that apparently ranged on the study area were killed by hunters (Table 3). Of those, one adult male was pursued across 25 Mesa Road, the north study area boundary, and killed in north GMU62; another adult male was snow-tracked across Colorado state highway 145, a south study area boundary, and was killed in east GMU70; and an adult female with a radio-collared cub that ranged on the study area was killed adjacent to the study area in north GMU61. All these pumas were included in the minimum count of pumas for TY3. The harvest of 8 independent pumas on the study area was 16.7% (8/48*100) of the minimum count of 48 independent pumas counted on the study area, including 31 females and 17 males, determined by the research team during November 2011 to April 2012 (Table 4). Independent females and males comprised 37.5% (3/8*100) and 62.5% (5/8*100) of the harvest, respectively. This harvest structure was 9.7% (3/31*100) of the independent females and 29.4% (5/17*100) of the independent males. Considering the mortality of 4 other radio-collared adults (F104, F119, M67, M87) and 3 noncollared adults (1 female, 2 males) (Table 3), the mortality of 15 independent pumas was 31.2% (15/48*100) of the minimum number of independent pumas. The mortality composition of 6 females and 9 males was comprised of 40.0% (6/15*100) females and 60.0% (9/15*100) males. This harvest structure was 19.4% (6/31*100) of the independent females and 52.9% (9/17*100) of the independent males in the minimum count. The minimum count of 48 independent pumas in TY3 was lower than the minimum count of 52 independent pumas in TY2 and 55 independent pumas in TY1 (Table 4, Fig.3.). Minimum count TY3 = 48 independent pumas, including 31 females and 17 males. This count reflected the relatively low adult female and low adult male survival rates (see Table 15, later). Because the harvest quota of 8 independent pumas in TY1 resulted in a minimum count of 52 independent pumas in TY2 and was expected to result in a stable-to-increasing population trend, we decided to set the quota to harvest 8 independent pumas in the TY3 (2011-12) hunting season to emulate an approximate 15% harvest of independent pumas to achieve a stable to increasing population objective while also considering that a number of independent pumas in the study area population might be killed outside of the study area as in the TY1 and TY2 hunting seasons. However, the additional pumas killed by hunters outside of the study area and natural mortality occurring during the hunting season and other parts of the biological year has apparently resulted in a declining population trend (Fig. 3). Hunter permits and survey: In TY3 mandatory permits with the voluntary survey attached were requested by 74 individual puma hunters. This number is up from 64 hunters in TY2 and down from 79 individual hunters in TY1. Twenty-three of the hunters requested a second permit, 13 hunters requested a third permit, and one hunter requested a fourth permit after a previous permit expired after 14 days. Thirty-six hunters (48.6%) provided responses to the voluntary survey either by turning in the printed survey (n = 31) or providing information during follow-up telephone calls (n = 5) by principal investigator K. Logan. The remaining 38 hunters could not be contacted because either they did not have working phone numbers or they did not return calls. Of the respondents, 12 hunters indicated that they did not hunt on the study area. The proportion of the 36 respondents that hunted extrapolated to the total of 74 hunters (24/36 = 0.666) indicated that about 49 hunters took to the field for pumas on the study area during the 33-day TY3 hunting season. This was up from 42 hunters in TY2, but down from 67 hunters in TY1 (Logan 2010, 2011). Considering that 49 hunters were estimated to be afield, then 16.3% of the hunters harvested pumas (8/49*100) and 26.5% of hunters captured pumas (13/49*100; see captured and released pumas below and in Table 5). The 31 puma hunters that turned in the written volunteer survey were asked to answer, “Do you consider yourself a selective or non-selective hunter?” A selective hunter is one that purposely is hunting 146 �for a specific type of legal puma, such as a male, large male, or large female. A non-selective hunter is one that intends to take whatever legal puma is first encountered or caught, with no desire for sex or size. Selective hunter was indicated by 24 respondents (92.3%; 24/26 = 0.923). Of the remaining 7 hunters, 2 indicated they were non-selective (7.7%), and 5 did not answer the question because they indicated that they did not hunt on the study area. The volunteer hunter survey also revealed that hunters treed pumas on the study area, but they chose not to kill them (Table 5). Those hunters reported they treed pumas 4 times and observed one, including 2 adult females (1 of them twice), 1 female of unspecified age-class, and 2 “young” males (1 male treed by 2 hunters). Two of the females were marked with collars and ear-tags. Hunters gave various reasons for not wanting to kill the pumas, including reasons based on puma sex, size, and one hunter did not want to kill a puma (Table 5). In an effort to better ascertain the vulnerability of sexes and age-stages (i.e., adult, subadult) of independent pumas to detection by puma hunters and hunter selection to address assumption 6 and hypothesis 6 (previously), the survey was changed in TY2 to ask hunters, “What was the sex of the lion that made the first set of tracks you encountered that were less than one day old?”. This question pertained to pumas that could be pursued by dogs and captured with a relatively high probability to allow the hunter an opportunity to harvest the puma. Associated with the question, we asked, “Did you pursue the lion to harvest it?” Hunters’ responses in TY3 showed they encountered 21 puma tracks less than one day old. Of those, 15 tracks were of females, and 6 tracks were of males, indicating that during the hunting season females are more detectable than males by a ratio of 2.5:1, consistent with the sex structure of independent pumas in the minimum count on the study area which was 31 females and 17 males (Table 4). Of the 15 female tracks, 1 female puma was pursued by a hunter with intent to harvest it, and that female was killed. Nine hunters indicated they observed female tracks as their first tracks <1day old, but did not pursue the puma with intent to harvest it. Another 4 hunters did not answer the question, “Did you pursue the lion to harvest it?” Six hunters indicated they observed male tracks as their first track <1 day old; 4 indicated they pursued the puma to harvest it, and 3 male pumas were killed. Two hunters indicated they did not pursue male pumas to harvest them. These preliminary survey and harvest data for TY3 indicate that hunters detect independent females more frequently than male pumas and females were captured by hunters slightly less than or about the same frequency as independent males by 6 to 7 (i.e., females = 3 harvested + 3 captured and released; males = 5 harvested + 2 captured and released). Moreover, hunters were choosing to kill males more frequently than females. Results in TY3 indicated selection for male pumas by hunters was consistent with TY1 and TY2 results where hunters caught females slightly more frequently than males, yet the males were selected for harvest. This preliminary assessment from years TY1, TY2, and TY3 puma harvest and hunter survey data suggests that female pumas were detected by hunters more frequently than male pumas, most puma hunters were selective, and hunter choices influenced harvest sex and age composition. Segment Objective 2 After the harvest quota was filled, puma research teams immediately initiated capture operations with trained dogs. Two fully-staffed capture teams, one each detailed on the east and west slopes, systematically and thoroughly searched the study area to capture, sample, and GPS/VHF radio-collar pumas the remainder of winter and early spring 2011-12. These efforts along with cage trap efforts and hand-capturing cubs at nurseries maintained samples to quantify population sex and age structure, survival, and agent-specific mortality, and allowed determination of minimum population size on the study area. We made 35 puma captures of 28 individuals from August 2011 to July 2012 (Tables 6-11); 21 individual pumas were captured with dogs 26 times. One puma was captured in a cage trap. Six cubs were captured at nurseries by hand. A total of 42 individual pumas were monitored with radio-telemetry from 147 �August 2011 to July 2012 (some of these had been collared in previous years), representing sex and age classes including: 19 adult females, 7 adult males, 4 subadult females, 4 subadult males, and 12 cubs (i.e., 1 cub and 2 subadult males survived to older age classes during the biological year). Trained dogs were used as our main method to capture, sample, and mark pumas from December 27, 2011 to April 12, 2012. Those efforts resulted in 79 search days, 268 total puma tracks detected of which 138 were ≤1 day old, 89 pursuits, and a total of 26 puma captures of 21 individual pumas (Table 6). This was the third year we deployed 2 fully-staffed hound capture teams in the treatment period. Search days with dogs in TY3 (79 days) were similar to TY2 (81 days), but slightly lower than TY1 (86 days) (Table 12). The frequency of tracks (tracks/day) encountered in TY3 was slightly lower than TY2, but slightly higher than TY1. The number of pursuits in TY3 was 10 less than in TY2 and 4 less than in TY1. The capture rate in TY3 was less than half that in TY2, but similar to TY1. The number of new pumas captured for the first time in TY3 was 4 less than TY2, but 2 more than TY1 (Table 12). Researchers in the two hound capture teams from December 27, 2011 to April 12, 2012 also recorded instances when the first tracks ≤1 day old of independent pumas were encountered on each search route each day to represent encounters with puma tracks that could be detected and pursued by puma hunters. The count was: 70 tracks of females, including 17 associated with cubs; 2 of 2 orphaned cubs; 12 tracks of males; and 2 tracks of unspecified sex. These tracks ≤ 1 day old were found after the TY3 puma hunting season when 3 independent females and 5 independent males were harvested (Table 2). Therefore, the harvested pumas were not present to make tracks for our researchers to observe. The loss of the 3females and 5 males may be reflected in the substantially higher ratio of female:male tracks post-hunting season. By comparison, the number of female to male tracks reported by puma hunters in TY3 was 15 females and 6 males (Segment Objective 1 above). Puma capture efforts using ungulate carcasses and cage traps was sporadic from October 5, 2011 to April 11, 2012 (Table 10). We used 21 road-killed mule deer at 18 different sites. One independent adult female puma, F172, was captured for the first time. Pumas scavenged at 3 of 21 (14.29%) sites where deer carcasses were used for bait. We sampled 9 new cubs, including 2 females and 7 males (Table 11). All were radio-collared to monitor survival and agent-specific mortality (Appendix A). In addition to our direct puma captures with dogs December through April, we detected 17 radiocollared pumas that we were able to identify with GPS or VHF telemetry 40 times, thus, negating the need to capture those pumas directly with dogs (Table 6). Upon detecting puma tracks that were aged at ≤1 day old, we followed the tracks with a radio receiver in an effort to detect if the tracks might be of a puma wearing a functional collar. We assigned tracks to a collared individual if we received radio signals from a puma that we judged to be <1 km from the tracks and in direction of travel of the tracks. This approach allowed us to more efficiently allocate our capture efforts toward pumas of unknown identity on the study area, particularly unmarked pumas or pumas with non-functioning GPS- or VHF- radiocollars. In addition to the harvest and capture data (previously), our search efforts also revealed the presence of at least 26 other pumas which we included in our minimum count November 2011 through April 2012 (Table 4). We classified those pumas as: 10 adult females, 4 adult males, 1 subadult female, 1 subadult male, and 10 cubs. Two adult females and 2 cubs were treed by our hounds, but we could not handle the pumas because they climbed dangerous trees (Table 8). Of those, 2 adult females were sampled with biopsy darts to obtain a tissue sample for genotyping the individuals. We could separate the activity of the other pumas from the GPS- and VHF- collared pumas in time, space, and track size differences between females, males, and numbers of cubs with females. Moreover, of the 26, 4 non- 148 �marked independent pumas (3 females, 1 male) and 4 non-marked cubs were confirmed with photographs from digital trail cameras. Our search and capture efforts during December 2011 through April 2012 and information from the puma hunting season in TY3 enabled us to quantify a minimum count of 48 independent pumas detected on the Uncompahgre Plateau study area, including 31 independent females and 17 independent males (Table 4). This count was based on the number of known radio-collared pumas, non-marked pumas harvested by hunters on the study area, observations of marked and non-marked pumas observed by researchers or pursued, treed and released by hunters on and adjacent to the study area, and puma tracks observed by researchers that could not be attributed to pumas with functioning radiocollars. Of the 48 independent pumas, 27 (56%) were marked and 21 (44%) were assumed to be non-marked animals (i.e., some may have ear-tags and tattoos). The abundance and sex structure of independent pumas on the east and west slopes of the study area were similar. The east slope count included 21 independent pumas (14 females, 7 males). The west slope count included 27 independent pumas (17 females, 10 males). A decline in the study area puma population is evident on the east slope. Considering the minimum count of 48 independent pumas, a preliminary minimum density for the winter puma habitat area estimated at 1,671 km2 on the Uncompahgre Plateau study area was 2.87 independent pumas/100 km2. The TY3 minimum count of 48 independent pumas is lower than the two previous treatment years TY1 and TY2 and appears to signal a declining trend in the puma population on the Uncompahgre Plateau study area (Fig. 3). The declining trend is further supported by declining survival rates of adult pumas on the study area (see Segment Objective 4&5 below). Taking into account the apparent declining trend in the number of independent pumas, a simple linear regression model of minimum counts of independent pumas in TY1, TY2, and TY3 on year projected that a minimum of 45 independent pumas could be expected in TY4 if the population decline continues. The recommended puma harvest for TY4 will be 5 pumas, representing 11.1% of the 45 expected number of independent pumas. This harvest rate is in the mid-range of the 8-15% test assumption for a stable to increasing population. The estimated age structure of independent pumas in November 2011 at the beginning of the puma hunting season in TY3 on the Uncompahgre Plateau study area is depicted in Figure 4. The male age structure has declined when compared with TY1 and TY2 (Logan 2010, 2011). The female age structure is more evenly distributed and does not yet reflect a decline in survival rates of adult females in TY3 (Logan 2010, 2011). In addition to the independent pumas, we counted a minimum of 19 cubs in TY3 (Table 4). Segment Objective 3 During the past 7.7 years of this work we compiled data on puma reproduction that was not previously available on pumas in Colorado (Table 13). Puma reproduction data (i.e., litter size, sex structure, gestation, birth interval, proportion of females giving birth per year) were summarized for the reference period in Logan (2009). In TY3 we directly observed 4 litters in nurseries which were born in June 2012 (1; F118’s cub not marked), July 2011 (1) and August 2011 (2), each with 1 to 3 cubs born to radio-collared females. Data on reproduction we observed in TY1, TY2, and TY3 were added to Table 13 which gives the reproductive chronology and information on mates of reproducing females. But those data will not be summarized again until the end of the treatment period. The proportion of radio-collared adult females giving birth from August 2011 to July 2012 biological year (TY3) was 0.19 (3/16), substantially lower than TY1 (0.53, 8/15) and TY2 (0.56, 9/16), further evidence for a declining puma population. 149 �Considering our 46 total litters from 24 females, including 44 observed with cubs 26 to 42 days old and 2 other litters confirmed by nurseries and nursling cub tracks with GPS-collared females (the latter include F111’s cubs caught later when 8.5 months old) (Table 13), the distribution of puma births by month since 2005 indicate births extending from March into September (Fig. 5). Births are high in May and June, peak in July, and decline in August and September. Births during late spring to late summer (May to August) involve 86% of the births (Fig. 5). The data indicate that the large majority of puma breeding activity occurred February through May (i.e., gestation averages about 90-92 days, Logan 2009). In comparison, Anderson et al. (1992:47-48) found on the Uncompahgre Plateau during 19821987 that of 10 puma birth dates 7 were during July, August, and September, 2 in October, and 1 in December, with most breeding occurring April through June. The 2 data sets indicated puma births on the Uncompahgre Plateau have occurred in every month except January and November (so far). As we gather more data on the puma births during the treatment period, we will examine the distributions of births in the reference and treatment periods separately for a treatment effect on timing of breeding and births. Segment Objectives 4 & 5 From December 8, 2004 (capture and collaring of the first adult puma M1) to July 31, 2012, we radio-monitored 21 adult male and 34 adult female pumas to quantify survival and agent-specific mortality rates (Table 14). Survival and agent-specific mortality of adult pumas were summarized for the reference period in Logan (2009). Preliminary estimates of adult puma survival rates in the absence of sport-hunting during the reference period indicated high survival, with adult male survival generally higher than adult female survival (Table 15). We monitored 20 adult females and 7 adult males for annual survival and agent-specific mortality in TY3. Annual survival rate for adult females was 0.548 (SE=0.1063) and for males was 0.167 (SE=0.1076). Preliminary adult puma survival for TY1, TY2, and TY3 are also shown in Table 15. So far, adult male survival is substantially lower in the treatment period than in the reference period. Adult female survival is lower in TY1 and TY3, with marked decline in TY3. Yet, female survival is generally higher than male survival. These characteristics are probably indicative of hunter selection for male pumas (previously in Segment Objective 1). The lower adult puma survival rates were consistent with an observed decline in the puma population on the study area (see Segment Objective 2, previously). Human-related factors caused 8 deaths of radio-marked adult pumas in TY3, including: sporthunting harvest (3 males- M67, M87, M138; 3 females- F3, F70, F75), illegal shooting (M73), and depredation control (1 male- M153) (Tables 2, 3, 14). In addition, 6 adult female pumas died of natural causes: F23 and F24 were killed by a male puma; F104 apparently died of starvation associated with senescence; F116 apparently died of complications associated with pregnancy and parturition; F119 died of a ruptured uterus and internal bleeding associated with pregnancy, and F135 died of unknown natural cause (Table 14). The occurrence of an increasing frequency of natural deaths and declining adult survival rates in this hunted puma population suggests that sport-hunting causes additive mortality. We have radio-monitored 27 subadult pumas (i.e., independent pumas <24 months old), including 11 females and 16 males (Table 16). We lost contact with 2 males that probably dispersed from the study area unknown distances. Of the remaining 25 subadults (females and males combined), 6 (2 females, 4 males) died before reaching adulthood, indicating a preliminary binomial survival rate of 0.76 (i.e., 19/25). F66 died at 23 months old of trauma to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer. M99 died at about 16 months old; punctures to his skull were consistent with canine bites from another puma and suggested intra-species strife as cause of death. M115 died at about 14 months old due to complications of a broken left foreleg, cause unknown. This injury probably affected his ability to efficiently kill prey. F143 was killed and eaten by a male puma while in competition for an elk carcass that one of the pumas killed. Two subadult males were killed by puma hunters. We 150 �need to increase our efforts to acquire larger samples of male and female radio-monitored subadult pumas to acquire reliable estimates of their survival. Harvest data along with our capture and radiotelemetry data provided dispersal and fate information on 33 marked pumas, 25 males and 8 females. Of those, 25 (4 females, 21 males) were initially captured and marked as cubs, and 8 (4 females, 4 males) were captured and marked in the subadult life-stage on the Uncompahgre Plateau puma study area (Table 17). Twenty males were killed away from the study area by hunters at linear distances (i.e., from initial capture sites to kill sites) ranging from about 20 to 370 km. Two males with extreme moves were killed in the Snowy Range of southeastern Wyoming (369.6 km) and the Cimarron Range of north-central New Mexico (329.8 km). Four females were killed by puma hunters; 3 off the study area ranging from 24.0 to 74.5 km from initial capture sites; 1 on the study area 18.2 km from her initial capture site. Female F52 was treed and released by hunters in December 2008 and 2009 south of Powderhorn, Colorado, indicating that she established an adult home range there before she was killed by a puma hunter in that area on Jan. 9, 2012. Three males marked initially as cubs born on the study area (M67, M87, M92) dispersed from their natal ranges and were recaptured as adults on the study area. All were born on the east slope of the Uncompahgre Plateau and moved to the west slope. Twenty-three of the 33 pumas had reached adult ages ranging from 24 to 79 months old. A preliminary estimate of cub survival during the reference period was summarized in Logan 2009 using 36 radio-collared cubs (16 males, 20 females) marked at nurseries when they were 26 to 42 days old. In that summary, estimated survival of cubs to one year of age was 0.53. [The estimated minimum survival rate using the Kaplan-Meier procedure was 0.5285 (SE = 0.1623). The maximum estimated cub survival was practically the same, 0.5328 (SE = 0.1629).] The major natural cause of death in cubs, where cause could be determined, was infanticide and cannibalism by other, especially male, pumas. In TY3 we monitored the fates of 12 radio-collared cubs (Appendix A). We lost contact with one (M156) after he shed his expandable radio-collar; he was 59 days old. Of the remaining 11 collared cubs, 6 died. Cubs M154 and M155 died probably of starvation after their mother died of an unknown natural cause; they were 77-81 days old. M159 died of an unknown natural cause when he was about 105 days old. His siblings F157 and F158 died of starvation after their mother F70 was killed by a puma hunter; they were 150 days old. M162 died of starvation after his mother was killed by a puma hunter; he was about 10.6 months old. Three other cubs that were orphaned at older ages survived to the subadult life stage. F147 was orphaned at 12 months old when her mother F24 was killed by a male puma. F147 continued to range on her natal area until her radiocollar quit functioning when she was 19 months old. Siblings F149 and M161 were orphaned at 13.5 months old when their mother F23 was killed by a male puma. Both siblings dispersed to the east slope of the study area when they were 14 to 15 months old. Another cub, F152, offspring of F93, survived to at least 25 month old in July 2012 and ranged on her natal area. A greater number of cubs over a longer period of time must be sampled before estimating cub survival and agent-specific mortality rates in the treatment period. In addition, a non-marked male puma cub was struck and killed by a vehicle on state highway 62 in Leopard Creek on the south boundary of the study area on October 7, 2011. This mortality made the fourteenth puma death recorded due to vehicle collision on the study area since 2004 (Table 18). Five of the 14 pumas were marked, including 3 adults with GPS/VHF collars. Those 3 adults died during the first year of the treatment period. Thirty-five adult pumas (26 females, 9 males) have worn GPS collars since this project began in 2004 (Table 19). Over 60 thousand GPS locations have been obtained and will be used for studies on 151 �puma behavior, social organization, population dynamics, movements, habitat use and puma-human relations in collaboration with colleagues in Mammals Research and Colorado State University. Segment Objective 6 A pilot survey of prevalence of Trichinella spp. in puma from southwest Colorado was initiated by Mammals Researcher Ken Logan and Dr. Mason Reichard of Center for Veterinary Health Science, Oklahoma State University, Stillwater, OK. Summary: The current pilot study documented the occurrence and high prevalence of Trichinella spp. in Puma concolor from Colorado. Twelve of 14 (85.7%) puma tongues were infected with Trichinella. The high prevalence of the zoonotic nematode in Colorado pumas justifies expansion of the sampling area to include pumas from a broader geographical scale. Background: Trichinella spp. are zoonotic nematodes capable of infecting humans and other animals. Wild animals and humans throughout the world become infected when they ingest infected tissue containing the parasite. Infection in humans of Trichinella spp. may result in nausea, diarrhea, vomiting, fatigue, fever, abdominal discomfort, headaches, chills, cough, eye swelling, and may even lead to heart and breathing problems. In severe cases, infection of Trichinella spp. may result in death. Hunting of pumas in Colorado has substantial historical, cultural, recreational, and economic importance. However, little current research and literature (either public or peer-reviewed) is available regarding the prevalence of Trichinella in Colorado puma and the potential for human infection. In 1995, an outbreak of trichinellosis in 10 people from Idaho County, Idaho was reported from the consumption of improperly prepared cougar jerky (Vollbrecht et al. 1996). The outbreak of trichinellosis in Idaho stresses the importance of wild carnivores as reservoirs of Trichinella spp. infections to humans (Kennedy et al. 2009). In addition to Idaho, pumas infected with Trichinella spp. have been reported from Montana (Worley et al. 1974; Winters 1969), Oregon (Rausch et al. 1983), Wyoming (Worley et al. 1974), and British Columbia, Canada (Gajadhar and Forbes 2010). The purpose of the current pilot study was to determine if puma from southwest Colorado were infected with Trichinella spp. The specific objectives were to: 1. Determine the prevalence of Trichinella spp. in P. concolor from southwest Colorado. 2. Determine which species of Trichinella is/are present in P. concolor from southwest Colorado. 3. Establish baseline data on the occurrence, prevalence, and distribution of Trichinella spp. in southwest Colorado. Pilot Project Design: Tongues from hunter-killed pumas were artificially digested to detect Trichinella spp. larvae. Infection with Trichinella spp. was assessed according to sex, age class, and geographic location of capture. Collection of Tissue from Pumas Tongues from dead pumas were collected by Mammals Researcher Ken Logan from pumas that were killed by sport-hunters (n = 12) and for depredation control (n = 2) in GMUs 61, 62, 64, 65, 66, and 521 representing Delta, Gunnison, Montrose, and Ouray counties in southwest Colorado. Jaws of the cats were opened, tongue firmly grasped, and pulled out of the mouth. One-half to three-quarters of the puma’s tongue was cut from the carcass using a clean knife or sterile scalpel. Excised tongues were placed in zip-top bags, labelled with sex, age estimate, and unique identifiers according to the host puma and location of where and when the sample was collected. Tongues samples were then frozen (-20 C) until they were shipped to Oklahoma State University for analysis. 152 �Determination of Trichinella Infection Infection with Trichinella sp. was determined by tissue digestion of tongues from puma (Webster et al., 2006). Puma tongues were weighed and homogenized in a Polytron (Kinematica GmbH, Kriens-Luzern, Switzerland). Ground samples were mixed with 10 ml of artificial digestive fluid (1% pepsin [1:3,000 IU] and 1% hydrochloric acid) per 1 gram of tissue. Digests were then mixed vigorously on magnetic stir plats at 37° C for 3 hours. Digests were allowed to settle for 20 min and the sediment containing Trichinella larvae were washed with tap water and enumerated under 40x magnification. Results were recorded as the number of larvae recovered per gram of tongue tissue digested. Results: Fourteen pumas were tested for infection with Trichinella. Twelve of the 14 (85.7%) were infected with Trichinella (Table 20). Because the prevalence of Trichinella infection was high and the sample size was relatively small, additional statistical comparisons of sex and age classes were not made as they were unlikely to yield useful information. Based on previously published data on the prevalence of Trichinella spp. in pumas from other locations (Winters 1969; Worley et al. 1974; Vollbrecht et al. 1996), we anticipated that approximately 50% of the pumas from southwest Colorado would have been infected. However, the prevalence of Trichinella in pumas was much higher than originally thought. The common occurrence of the zoonotic parasites in pumas from southwest Colorado coupled with the fact that consumption of improperly prepared meat from wild felids can infect humans (Vollbrecht et al. 1996) necessitates continued sampling from a broader geographical area in Colorado to determine infection risk to humans. Project Continuation: Trichinella larvae recovered from these twelve pumas will be submitted to the International Trichinella Reference Center (ITRC, www.iss.it/site/Trichinella/) in Rome, Italy for genotyping to identify the species of Trichinella. Individual Trichinella larvae will be identified by a multiplex PCR analysis following the protocol described by Zarlenga et al. (1999) and modified by Pozio and La Rosa (2003). Briefly, DNA will be extracted from individual worms and PCR will be performed using ExTaq DNA polymerase (Takara) in 50 ml containing 1.5 mM MgCl2, 200 mM dNTPs, 50 pmol of each primer and 0.5 unit of ExTaq DNA polymerase. The PCR-amplified fragments from purified DNA will be visualised by agarose gel electrophoresis (2.0% standard agarose). When Trichinella larvae were counted from infected pumas, we noticed that the majority of the worms were still alive after being frozen for at least 6 months or longer. The trait of freeze resistance suggests the Trichinella in pumas from southwestern Colorado are either T. nativa or Trichinella genotype T6 (i.e., the two freeze resistant species in North America). However, T. murrelli, not freeze resistant, is the species of Trichinella most commonly recovered from wild animals in temperate areas across North America. Fifteen additional puma tongues from southwest Colorado were collected to accumulate a larger sample size during the 2011 to 2012 puma hunting season. Those tissues will be analyzed for prevalence of Trichinella by Dr. Mason’s laboratory in 2013. SUMMARY Manipulative, long-term research on puma population dynamics, effects of sport-hunting, and development and testing of puma enumeration methods began in December 2004. After 7.7 years of effort 168 unique pumas have been captured, sampled, marked, and released. Using these animals, we monitored fates of pumas in all sexes and age stages, including: 34 adult females, 21 adult males, 11 subadult females, 16 subadult males, 45 female cubs, 71 male cubs, and 1 cub of undetermined sex (some individuals occur in more than one stage class). Data from marked animals were used to quantify puma population characteristics and vital rates in a reference period without sport-hunting off-take as a mortality factor from December 2004 to July 2009. Puma population characteristics and vital rates in a 153 �reference condition allowed us to develop a puma population model, and to use population data and modeling scenarios to conduct a preliminary assessment of CPW puma management assumptions and guide directions for the remainder of the puma research on the Uncompahgre Plateau. Moreover, our data and model provide tools currently useful to CPW wildlife biologists and managers for assessing puma harvest strategies. The 5-year treatment period began August 2009 in which sport-hunting is a mortality factor. The treatment period will be a population-wide test of CPW puma management assumptions. Now 3 years of the treatment period are complete (TY1, TY2, TY3). Although data support some CPW puma management assumptions (e.g., population structure, density, how sport-harvest can cause population decline), it is still too early in this research to adequately test all the assumptions and attendant hypotheses. Although the assumption and hypothesis on harvest structure and hunter selection is not supported with the first 3 years of data in the treatment period, this could change with a substantial change in abundance and sex structure of independent pumas available for hunting in TY4 and TY5. The puma harvest quota for TY4 is recommended to be 5 independent pumas to align with the research design and harvest objective, and the hunters will be surveyed again. To improve data on puma population vital rates, attention will be given to increasing radio-collared sample sizes across the various life stages and sexes. We will continue to explore methods for estimating puma abundance with accurate and affordable methods. 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Puma and human spatial and temporal use of a popular California state park. Journal of Wildlife Management 72:10761084. Vollbrecht, A., D. Sokolowski, W. Hollipeter, R. Sigler, J. Greenblatt, D. E. Anderson, P. J. Tennican, H. R. Gamble, and D. Zarlenga. 1996. Oubreak of trichinellosis associated with eating cougar jerky – Idaho, 1995. Morbidity and Mortality Weekly Report 45: 205-206. Webster, P., C. Maddox-Hyttel, K. Nockler, A. Malajauskas, J. van der Giessen, E. Pozio, P. Boireau, C. M. O. Kapel. 2006. Meat inspection for Trichinella in pork, horsemeat and game within the EU: available technology and its present implementation. Eurosurveillance 11:50-55. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2001. Combining closed and open mark-recapture models: the robust design. Pages 523-554 In Analysis and management of animal populations. Academic Press, New York. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 (Suppl):S120-S139. Winters, J. B. 1969. Trichiniasis in Montana mountain lions. Bulletin of the Wildlife Disease Association 5: 400. Worley, D. E., J. C. Fox, J. B. Winters, and K. R. Greer. 1974. Prevalence and distribution of Trichinella spiralis in carnivorous mammals in the United States northern Rocky Mountain region. Proceedings of the 3rd International Conference on Trichinellosis, Florida, USA, November 2-4, 1972. Zarlenga, D.S., Chute, M.B., Martin, A. and Kapel, C.M. 1999. A multiplex PCR for unequivocal differentiation of all encapsulated and nonencapsulated genotypes of Trichinella. International Journal for Parasitology 29:1859–1867. Prepared by: ________________________ Kenneth A. Logan, Wildlife Researcher 156 �Table 1. Projected puma population growth modeled from a minimum count of independent pumas during winter 2007-08 reference period year 4 (RY4). Treatment period year 1 (TY1), shaded in gray, indicates the results used to derive a quota of 8 independent pumas, representing 15% of the independent pumas (from Logan 2009). Harvest Level No harvest. Year RY4 RY5 TY1 Projected Minimum Puma Population Size Adult Subadult Female Male Female Male 16 8 5 4 18 10 9 8 23 14 8 8 Independent Pumas Cub 20 33 42 Total 33 45 53 Lambda 1.37 1.17 Table 2. Pumas harvested by sport-hunters in Treatment Year 3 (TY3) on the Uncompahgre Plateau Study Area, Colorado, November 21 to December 23, 2011. Puma sex Age (yr.) Date of kill Location/UTM NAD27 Zone, Easting, Northing 1.6 Previous M/F I.D. or specimen P no. if not marked P1038 M 12/5/2011 M 1.4 M120 12/6/2011 F 9.5 F3 12/11/2011 F 8 F75 12/14/2011 F 7 F70 12/22/2011 M 1.1 P1049 12/23/2011 M 2.5 M138 12/23/2011 M 1.3 M141 12/23/2011 Cottonwood Fork of Dry Creek 12, 756280, 4250547 Spring Creek 13, 238681, 4249866 Lindsay Creek 13, 238911, 4252542 Cottonwood Creek (W) 12, 732894, 4239423 Spring Creek, Puma Fork 13, 239323, 4243719 Hills west of Colona, CO 13, 256132, 4245751 Horsefly Creek (E) 13, 249592, 4240770 Little Bucktail Creek 12, 752201, 4239371 157 Hunter/status Ray David/resident Gary Gleason/resident Kari McClanahan/ resident Joe Gray/non-resident Dustin Gleason/resident Dawson Flowers/ resident Darren Reed/resident Kenneth Sowell/ resident �Table 3. Four other independent VHF/GPS-collared and 3 non-collared adult pumas in the minimum count for the Uncompahgre Plateau Study Area that died during the 2011-2012 Colorado puma hunting season. Puma sex (M or F) M87 Age (yr.) 3.4 Date of kill/death 12/6/2011 M67 4.4 12/18/2011 F119 7.5 1/28/2012 F104 11 1/31/2012 M 5.5 12/6/2011 M 3 1/17/2012 F 6 1/18/2012 Place of kill/UTM NAD27 Zone, Easting, Northing Forty-seven Canyon, Tabaguache Canyon 6.5 km N of study area Lower Tabaguache Canyon 12.61 km NW of study area 12, 707031, 4247827 Clay Creek 12, 743719, 4228535 Lower Roubideau Creek, died 1.73 km N of study area 12, 748282, 4288223 Cottonwood Creek north of Roubideau Canyon 0.66 km N of study area 12, 736764, 4274349 Specie Creek 1.65 km S of study area 12, 752861, 4211534 Pinto Mesa 1.02 km N of study area 12, 721658, 4247479 Hunter/status/other cause John Elmer/rresident/S. Garvey Outfitter Karl Red/resident Ruptured uterus and blood loss associated with pregnancy Starvation, probably associated with senescence Brett Merritt/non-resident Trailed from study area/R. Navarrete Outfitter Alan Hatfield/resident Trailed from study area James Williams/nonresident/S. Garvey Outfitter Radio-collared cub M162 ranged on study area Table 4. Minimum count of pumas based on numbers of known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected non-marked pumas on the study area during September 2009 to April 2010 of Treatment Year 1 (TY1), November 2010 to April 2011 (TY2), and November 2011 to April 2012 (TY3) Uncompahgre Plateau study area, Colorado. Treatment Year (TY) Study Area region TY1 East slope West slope subtotals TY2 TY3 Adults Female Male Subadults Female Male Female Cubs Male 16 10 1 1 1 4 14 10 0 3 3 3 30 20 1 4 4 7 Total Independent Pumas = 55, including 31 females, 24 males. Cubs = 20-25 East slope 15 5 3 2 7 9 West slope 15 7 2 3 2 5 subtotals 30 12 5 5 9 14 Total Independent Pumas = 52, including 35 females, 17 males. Cubs = 39 East slope 13 4 1 3 4 2 West slope 14 5 3 5 1 2 subtotals 27 9 4 8 5 4 Total Independent Pumas = 48, including 31 females, 17 males. Cubs = 19 Unknown sex 4-8* 5-6 9-14 7 9 16 4 6 10 *One adult non-marked female puma was killed by a hunter in Roubideau Canyon. The female puma was lactating, indicating she had nurslings. Up to 4 cubs were assumed to be in the litter. 158 �Table 5. Pumas captured and released by sport-hunters in Treatment Year 3 (TY3) on the Uncompahgre Plateau Study Area, Colorado, November 21 to December 23, 2011. Data are from puma hunter responses in 36 voluntary surveys, including: 31 original surveys on printed voluntary permits and 5 telephone contacts with hunters that did not return printed surveys on permits. Total response rate from 74 individual permitted hunters was 48.6 % (36/74 = 0.486*100). Puma sex/age stage/mark F/adult/collar/eartags Date of capture 12/4/2011 M/young/no marks 11/30/2011 to 12/5/2011 12/14 to 16/2011 F/adult/F75/ collar/eartags/caught twice M/young/no marks F/no marks 11/30/2011 to 12/5/2011 12/20 to 23/2011 Capture location Hunter name Transfer Rd., Roubideau Cyn. Dry Park. George Quintana Cottonwood Cr. Thomas Barnes Dry Park. Ross Ward Loghill Mesa Zachary Prock Eric Franklin 159 Reason for releasing the puma given by hunter Did not want to kill a female. Observed the puma on the road. Did not want to kill a small male. Caught F75 twice. Did not want to kill a puma. Wanted to take photos. Did not want to kill a small male. Same male caught with Eric Franklin (above). Did not want to kill a female. �Table 6. Summary of puma capture efforts with dogs from December 27, 2011 to April 12, 2012, Uncompahgre Plateau, Colorado. Month December No. Search Days 4 January 25 February 20 March 22 No. & type of puma tracks founda,b 16 tracks: 4 male, 10 female, 1 cub, 1 undetermined independent puma Tracks ≤1 day old: 2 male, 8 female, 0 cub 103 tracks: 12 male, 56 female, 31 cub, 4 undetermined independent pumas Tracks ≤1 day old: 4 male, 31 female, 23 cub, 1 undetermined 71 tracks: 9 male, 44 female, 17 cub, 1 undetermined independent puma Tracks ≤1 day old: 7 male, 26 female, 9 cub, 1 undetermined No. & type of pumas pursued 4 pursuits: 2 male, 2 female, 0 cub No. & I.D. or type of pumas captured, observed, or identified 2 pumas captured 2 times: adult female F137 and dependent young F152 (of F93). In addition, adult females F93 and F111 were associated with tracks by VHF telemetry. 39 pursuits: 3 male, 19 female, 16 cub, 1 undetermined 12 pumas captured 14 times: F93, F96, M170 (cub of F171), F171, cub (not handled, of F171), F8, F140, F149 (cub of F23), M160, M161 twice (cub of F23), F163 twice, M162 (orphaned cub). In addition, adult females F23 (3 times), F93 (2 times), F136, F137, F149 (2 times), F152 (2 times), M170, and F171 were located by VHF telemetry in association with tracks. 9 pumas captured 9 times: F28 (not handled in hole), F129 (not handled, dangerous tree), M131 (not handled, dangerous tree), F163, M164, M165, PF1051 (biodarted, not handled in dangerous tree), PF1052 (biodarted, not handled in dangerous tree), cub (not handled in dangerous tree, of non-marked female). In addition, adult females F23 (2 times), F93, F95, F96 (2 times), F136, F137, F171, adult male M164, subadult females F147 and F163 (3 times), and cubs F152 and M162 (2 times) were associated with tracks by VHF telemetry. 2 pumas captured 2 times: F149, M161. In addition, adult females F23, F95, F96, F171, subadult females F140 and F149, cubs M161 and M170 were associated with tracks by VHF telemetry. 27 pursuits: 6 male, 13 female, 8 cub 66 tracks: 12 male, 18 pursuits: 2 male, 39 female, 14 cub, 1 12 female, 4 cub undetermined independent puma Tracks ≤1 day old: 2 male, 16 female, 4 cub April 8 12 tracks: 6 male, 1 pursuit: 0 pumas captured. None associated with tracks 5 female, 1 cub 1 male with VHF telemetry. Tracks ≤1 day old: 1 male, 2 female, 1 cub 79 268 tracks: 89 pursuits: 21 individual pumas were captured 26 times with TOTALS 43 male, 14 male, aid of dogs. In addition, 17 radio-collared pumas 154 female, 46 female, were detected 40 times by tracks and identified 64 cub, 28 cub with VHF telemetry ≤1 km from the tracks. 7 undetermined 1 undetermined Tracks ≤1 day old: 16 male 83 female 37 cub 2 undetermined a Puma hind-foot tracks with plantar pad widths >50 mm wide are assumed to be male; ≤50 mm are assumed to be female (Logan and Sweanor 2001:399-412). b Each capture season researchers also recorded instances when the first puma tracks ≤1 day old were encountered on each search route each day to gather data on vulnerability to detection using methods similar to puma hunters. For 2011-2012 (TY3) the count was: 70 tracks of females, including 17 of those associated with cubs; 2 tracks of 2 orphaned cubs; 12 tracks of males; and 2 tracks of undetermined sex. 160 �Table 7. Adult and subadult pumas captured for the first time, sampled, tagged, and released from December 2011 to April 2012, Uncompahgre Plateau, Colorado. Puma I.D. M160 F163 M164 M165 F171 F172 Sex Estimated Age (mo.) 19 18 19 19 27 33 M F M M F F Mass (kg) 46 43 56 56 45 NM* Capture date 1/18/2012 1/26/2012 2/14/2012 2/24/2012 1/20/2012 3/28/2012 Capture method Dogs Dogs Dogs Dogs Dogs Cage trap Location Sanborn Park, head of Albin Draw San Miguel Canyon E of Pinyon Pinto Mesa, moved from Big Bucktail Canyon Head of Coal Canyon McKenzie Butte Monitor Canyon, Roubideau Canyon *Not measured. Table 8. Pumas that were captured and observed with aid of dogs, some of which were biopsy-darted and given specimen numbers (e.g., P1051), but were not handled at that time for safety reasons, and a puma killed for depredation control, December 2011 to April 2012, Uncompahgre Plateau, Colorado. Puma sex & I.D. F P1035 F P1051 Age stage or months 18 Capture date 10/22/2011 adult 2/13/2012 F P1052 Unknown none Unknown none adult 2/29/2012 cub 4 to 5 cub 8 to 10 1/12/2012 2/29/2012 Location Comments Dallas Creek, Pleasant Valley. Potter Canyon, Roubideau Canyon. Puma killed by Wildlife Services agent for killing a domestic llama. Puma not previously marked. Puma climbed dangerous tree. Biopsy-darted to obtain tissue sample for genotype. In association with a single cub about 8 to 10 months old, which also could not be handled due to dangerous tree. Puma climbed dangerous tree Biopsy-darted to obtain tissue sample for genotype. Puma cub climbed high in dangerous tree. Probably 1 of 2 cubs of F171. Puma cub climbed high in dangerous tree. Not handled. In association with P1051 above. Monitor Canyon, Roubideau Canyon. E Loghill Mesa. Monitor Canyon, Roubideau Canyon. Table 9. Pumas recaptured with dogs (none in cage traps) December 2011 to April 2012, Uncompahgre Plateau, Colorado. Puma I.D. F152 Recapture Date 12/27/2011 Mass (kg) Observed Estimated Age (mo.) 18 Capture Method/ Location Dogs/Dry Cr. Basin F137 F96 F140 F93 12/28/2011 1/9/2012 1/13/2012 1/17/2012 Observed 44 47 Observed 35 72 17 109 F8 F152 F149 M161 F163 F129 1/17/2012 1/18/2012 1/24/2012 1/24/2012 1/27/2012 2/2/2012 Observed 43 Observed Observed Observed Observed 104 19 9 9 18 18 Dogs/W Fk. Dry Cr. Dogs/lower Delores Cr. Dogs/Tomcat Cr. Dogs/Lower Linscott Cyn. Dogs/Coal Canyon Dogs/Shavano Mesa Dogs/Big Bucktail Cyn. Dogs/Big Bucktail Cyn. Dogs/Maverick Draw Dogs/Dolores Cyn. M131 2/2/2012 Observed 18 Dogs/Dolores Cyn. F163 F28 2/9/2012 2/16/2012 Observed Observed 19 107 Dogs/San Miguel Cyn. Dogs/San Miguel Cyn. F149 M161 3/5/2012 3/5/2012 29 Observed 11 11 Dogs/Tomcat Cr. Dogs/Tomcat Cr. 161 Process F152 climbed dangerous tree. Could not be handled to fit with radiocollar. None. Replaced faulty GPS collar. Fitted with VHF collar. None. None. Fitted with GPS collar. None. None. None. F129 climbed dangerous tree. Could not be handled to fit with radiocollar. M131 climbed dangerous tree. Could not be handled to fit with radiocollar. None. F28 took refuge in hole. Could not be handled. Replaced VHF collar on F149. None. �Table 10. Summary of puma capture efforts with cage traps from October 5, 2011 to April 11, 2012, Uncompahgre Plateau, Colorado.* Month October November No. of Sites 6 7 March 2 April 5 Carnivore activity & capture effort results No pumas scavenged 7 mule deer carcasses used at the sites. Unknown male puma scavenged deer carcass on SE Loghill Rim 11/9/2011; attempted capture with cage trap; male puma did not return. Unknown male puma walked ~100 m from deer carcass at same bait site above 11/22/2011, but did not scavenge the bait. Unknown male puma walked ~1.5 m from a deer carcass at same bait site as above 11/29/2012, but did not scavenge the bait. Puma F172 captured in cage trap baited with mule deer carcass 3/28/2012. Unknown female puma and lone cub scavenged mule deer carcass at another bait site 4/68/2012. The pumas were pursued with dogs on 4/9/2012, but were not captured. No pumas scavenged 5 mule deer carcasses used at the sites. * We used 21 road-killed mule deer at 18 different sites. Of the road-killed deer baits, 3 of 21 (14.29%) were scavenged by pumas. Table 11. Puma cubs sampled August 2011 to July 2012 on the Uncompahgre Plateau Puma Study area, Colorado. Cub I.D. Sex Estimated birth datea Estimated age at capture (days) Mass (kg) Mother Estimated age of mother at birth of this litter (mo) M154 M155 M156b F157 F158 M159 M161c M162d M170e M M M F F M M M M 7/6/2011 7/6/2011 8/20/2011 8/18/2011 8/18/2011 8/18/2011 4/22/2011 7/2011 8/2011 42 42 43 40 40 40 276 183 137 2.6 3.0 3.25 2.5 2.5 2.5 24 12 9 F135 F135 F137 F70 F70 F70 F23 Nonmarked F171 33 33 30 76 76 76 80 Adult 22 a Estimated age of cubs sampled at nurseries is based on the starting date for GPS location and radio-telemetry foci for mothers at nurseries, and development characteristics of cubs caught with mothers without radiocollars or mothers with non-functioning radiocollars. b Probably more than one cub in F137’s litter; others probably hiding in a hole at the nursery. c M161 is sibling of F149; birth date known from radio-telemetry on mother F23. d M162 was observed with one non-marked sibling on 2/7/2012. Both cubs were orphans; their mother non-marked mother apparently killed by a hunter on 1/18/ 2012 on Pinto Mesa. e M170 was observed with one sibling on 1/12,13/2012. Mother F171 was captured for first time on 1/20/2012. 162 �Table 12. Summary of puma capture efforts with dogs, December 2004 to April 2012, Uncompahgre Plateau, Colorado. Period Dec. 2, 2004 to May 12, 2005 Nov. 21, 2005 to May 26, 2006 Nov. 13, 2006 to May 11, 2007 Nov. 19, 2007 to April 24, 2008 Dec. 9, 2008 to April 30, 2009 Track detection effort 109/78 = 1.40 tracks/day 35/78 = 0.45 pursuit/day Puma capture effort 14/78 = 0.18 capture/day Effort to capture an independent puma for the first time 11 pumas captured for first time 11/78 = 0.14 capture/day 78/14 = 5.57 day/capture 14/82 = 0.17 capture/day 78/11 = 7.09 day/capture 149/82 = 1.82 tracks/day 78/35 = 2.23 day/pursuit 43/82 = 0.52 pursuit/day 177/78 to 182/78 = 2.27-2.33 tracks/day 82/43 = 1.91 day/pursuit 45/78 to 47/78 = 0.58-0.60 pursuit/day 82/14 = 5.86 day/capture 22/78 = 0.28 capture/day 78/47 to 78/45 = 1.66-1.73 day/pursuit 49/77 = 0.64 pursuit/day 78/22 = 3.54 day/capture 78/7 = 11.14 day/capture 20/77 = 0.26 capture/day 7 pumas captured for first time 7/77 = 0.09 capture/day 77/20 = 3.85 day/capture 24/71 = 0.34 capture/day 77/7 = 11.00 day/capture 217/77 to 218/77 = 2.82-2.83 tracks/day Pursuit effort 198/71 to 202/71 = 2.79-2.84 tracks/day 77/49 = 1.57 day/pursuit 75/71 to 78/71 = 1.06-1.10 pursuit/day Dec. 15, 2009 to April 30, 2010 Nov. 16 and Dec. 14, 2010 to April 22, 2011 266/86 = 3.09 tracks/day 71/75 to 71/78 = 0.91-0.95 day/pursuit 93/86 = 1.08 pursuit/day 300/81 = 3.70 tracks/day Dec. 27, 2011 To April 12, 2012 268/79 = 3.39 tracks/day 7 pumas captured for first time 7/82 = 0.08 capture/day 82/7 = 11.71 day/capture 7 pumas captured for first time 7/78 = 0.09 capture/day 9 pumas captured for first time 9/71 = 0.13 capture/day 71/24 = 2.96 day/capture 71/9 = 7.89 day/capture 26/86 = 0.30 capture/day 9 pumas captured for first time 9/86 = 0.11 capture/day 86/93 = 0.92 day/pursuit 99/81 = 1.22 pursuit/day 86/26 = 3.31 day/capture 52/81 = 0.64 capture/day 86/9 = 9.56 day/capture 81/99 = 0.82 day/pursuit 81/52 = 1.56 day/capture 81/15 = 5.40 day/capture 89/79 = 1.13 pursuit/day 26/79 = 0.28 capture/day 11 pumas captured for first time 11/79 = 0.14 capture/day 79/89 = 0.89 day/pursuit 79/26 = 3.04 day/capture 79/11 = 7.18 day/capture 163 15 pumas captured for first time 15/81 = 0.18 capture/day �Table 13. Individual puma reproduction histories, Uncompahgre Plateau, Colorado, 2005-2012. Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) F2 F2 F2 F3 F3 F3 F3 F3 F7 F7 F7 F8*e F8 F8 F8 F16 F16 F16 F23* F23 53 67 89 36 50 62 84 107 67 82 106 24 37 60 95 32 52 75 21 45 F23 80 F24 F24 75 114 F25 F25 F25 F25 74 94 110 129 F28* F28 F28 F30* F50 F54 F70* F70 F70 F72* F72 F72 36 48 68 48 21 24 38 52 76 28 51 64 F75 F75 F93 F93 F94* F94 F96 F104 F111* F116g 32 55 56 90 46 60 55 110 32 36 Dates pairs consortedb Estimated birth datec M73 49 02/28-29/08 M6 80 01/13-14/09 M27 or M29f M67 78 107 53 02/19-25/08 05/28/05 07/29/06 05/19/08 08/01/04 09/26/05 09/17/06 07/03/08 06/28/10 05/19/05 08/13/06 07/10/08 06/26/05 08/13/06 05/29/08 04/18/11 09/22/05 05/24/07 04/15/09 05/30/06 05/23/08 01/28-31/11 04/22/11 M29 92 04/12-15/07 06/14/07 09/10 M6 37 06/22-24/05 M51 M55 60 69 03/31/08 03/28-31/10 08/01/05 04/16/07 08/19/08 3/10 M29 88 12/27-29/06 M55 34 04/16-20/07 M51 60 03/10/08 M73 61 02/11/09 M55 M55 70 71 04/15/10 05/21/10 164 06/09/06 03/30/07 11/08 07/17/07 07/01/06 07/01/06 06/05/08 08/31/09 08/18/11 07/09/08 06/12/10 07/15/11 06/01/07 05/07/09 08/07 06/16/10 05/27/09 07/15/10 08/21/10 07/08/10 06/16/10 2009 Estimated birth interval (mo.) Estimated gestation (days) Observed number of cubsd 19.9 22.7 91-92 23.8 87-93 3 2 4 1 2 3 3 2 2 4 3 2 4 2 2 4 4 3 3 3 Nonfunct.GPS 84-86 2 90-93 4 3 14.0 22.0 13.8 11.7 21.5 23.8 93-95 94 89-92 14.9 23.9 13.4 22.5 34.7 90-91 Nonfunct.GPS 1 1 2 3 20.5 16.1 Nonfunct.GPS 11.7 92-93 88-92 87 14.8 23.6 23.1 13 23.2 93 13.3 91 2 ≥2 tracks 1 3 1 1 3 3 3 1 2 3 photographed 1 2 2 2 3 3 4 3 2 2 �Consort pairs and estimated agesa Female Age (mo.) Male Age (mo.) Table 13 continued. Dates pairs Estimated consortedb birth datec Estimated birth interval (mo.) 23 Estimated gestation (days) Observed number of cubsd ≥1 observed F119 66 08/09 2 F119i 96 02/12 29 1 plus 1-2 expected expected expected uterine scars F135 33 07/06/11 2 F136j 39 07/10/11 ≥1 remains F136 51 07/05/12 12 2 F137 30 07/08/11 ≥1 F171 22 08/11 2 a Ages of females were estimated at litter birth dates. Ages of males were estimated around the dates the pairs consorted. b Consort pairs indicate pumas that were observed together based on GPS data or VHF location data. c Estimated birth dates were indicated by GPS data of mothers at nurseries or by back-aging cubs to approximate birth date. d Observed number of cubs do not represent litter sizes as some cubs were observed when they were 5 to 16 months old after postnatal mortality could have occurred in siblings. Only cub tracks were observed with F28. e Asterisk (*) indicates first probable litter of the female, based on nipple characteristics noted at first capture of the female. f A radio-collared, ear-tagged male puma was visually observed with F23 on 2/25/08. Both M27 and M29 wore non-functional GPS collars in that area at the time. g When captured on 1/20/10, puma F116 was in association with 2 large cubs which were not captured. h One cub observed with F118 in Maverick Draw 7/19/2012. i F119 died of a ruptured uterus and internal bleeding on 1/28/12. Cub in uterus in third trimester; 1-2 uterine scars indicated expulsion of 1-2 fetuses. j Remains of F136’s cubs found 8/9/11. Cause of death predation by puma or black bear. F118h 50 06/20/2012 165 �Table 14. Summary for individual adult puma survival and mortality, December 8, 2004 to July 31, 2012, Uncompahgre Plateau, Colorado. Puma I.D. M1 Monitoring span 12-08-04 to 08-16-06 M4 M5 01-28-05 to 12-28-05 08-01-06 to 02-20-09 M6 02-18-05 to 05-21-10 M27 03-10-06 to 05-07-09 M29 04-14-06 to 02-25-09 M32 04-26-06 to 12-02-10 M51 01-07-07 to 03-20-09 M55 01-21-07 to 07-31-10 M67 08-23-07 to 12-18-11 M71 01-29-08 to 11-12-09 M73 02-21-08 to 10-26-11 M87 02-09-11 to 12-06-11 M90 11-16-10 to 11-23-10 M100 03-27-09 to 07-31-09 M114 02-27-10 to 03-10-12 M133 11-12-10 to 12-01-10 Status: Alive/Lost contact/Dead; Cause of death Dead. Lost contact− failed GPS/VHF collar. M1 ranged principally north of the study area as far as Unaweep Canyon. M1 was killed by a puma hunter on 01-02-10 west of Bang’s Canyon, north of Unaweep Canyon, GMU 40. M1 was about 97 months old at death. Dead; killed by a male puma. Estimated age at death 37−45 months. Dead. Born on study area; offspring of F3. M5 was independent of F3 by 13 months old, and dispersed from his natal area at about 14 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at age 54 months. Dead. M6 was struck and killed by a vehicle on highway 550 south of Colona, CO on 05-21-10. M6 was about 99 months old at death. Dead. Lost contact− failed GPS/VHF collar. Recaptured 12-02-07 & 01-22-08 by puma hunter/outfitter north of the study area. Possibly visually observed on study area with F23 on 02-25-08. Recaptured by a puma hunter/outfitter 12-11-08 & 12-28-08 north of the study area. Photographed by a trail camera on the study area (Big Bucktail Canyon) on 5 occasions: 03-27-09, 04-02-09, 04-15-09, 04-24-09, & 05-07-09. M27 was killed by a puma hunter on 12-09-09 in the North Fork Mesa Creek, Uncompahgre Plateau, GMU 61 North. M27 was about 100 months old at death. Dead. Lost contact− failed GPS/VHF collar. Possibly visually observed on study area with F23 on 02-25-08. Recaptured on study area 02-25-09, but could not be safely handled to change faulty GPS collar. M29 was killed by a puma hunter on 11-16-09 in Beaver Canyon, GMU 70 East. M29 was about 121 months old at death. Dead. Killed by a puma hunter on 12-02-10 in McKenzie Creek on the Uncompahgre Plateau study area. M32 was about 112 months old at death. Dead. Lost contact− failed GPS/VHF collar after 03-20-09. Killed by a puma hunter on 12-11-09 in Shavano Valley, Uncompahgre Plateau study area. M51 was about 77 months old at death. Dead. Killed by a puma hunter on 11-25-10 in Spring Creek Canyon on the Uncompahgre Plateau study area. M55 was about 77 months old at death. Dead. M67 is offspring of F30. Dispersed natal area. Established territory on W side U.P. study area. Killed by a puma hunter in Tabaguache Creek 12-18-2011 at age 52.9 months. Dead. Lost contact– M71 shed his VHF collar with an expansion link on about 11-1209. He was killed by a puma hunter on 12-09-09 on the west rim of Spring Creek Canyon, Uncompahgre Plateau study area. M71 was about 47 months old at death. Dead. Illegally killed 10-26-2011 in Bear Pen Gulch, upper East Fork Escalante Canyon; shot through abdomen during second rifle season. M73 was about 80 months old at death. Dead. M87 is offspring of F3. Dispersed from natal area. Established territory on W side of U.P. study area. Killed by a puma hunter in 47 Canyon, Tabaguache Canyon 12-06-2011. M87 was 41 months old at death. Dead. M90 was killed by a hunter on 11-23-10 on McKenzie Butte. M90 was offspring of F72, born 07-09-08. He was 28 months old at death. Dead. M100 was killed by a puma hunter on 01-16-10 in Naturita Canyon, GMU 70 East. M100 was about 63 months old at death. Dispersed from U.P. study area after 06-23-10. Killed by a puma hunter in Beaver Creek, NE of Canyon City, GMU59, 03-10-12. M114 was about 55 months old at death. Dead. M133 was killed by a puma hunter on 12-01-10 in Dry Fork Escalante Canyon north of the study area. M133 was about 43 months old at death. 166 �Puma I.D. M134 Monitoring span 06-01-11 to 06-10-11 M138 07-01-11 to 12-23-11 M144 09-01-11 to 07-31-12 M153 M165 09-01-11 to 09-13-11 07-01-12 to 07-31-12 F2 01-07-05 to 08-14-08 F3 01-21-05 to 12-11-11 F7 02-24-05 to 08-03-08 F8 F16 03-21-05 to 07-31-12 10-11-05 to 09-11-09 F23 02-05-06 to 06-06-12 F24 01-17-06 to 07-31-11 F25 02-08-06 to 02-03-11 F28 03-23-06 to 02-16-12 F30 04-15-06 to 07-29-08 F50 12-14-06 to 03-26-07 F54 01-12-07 to 08-18-07 F70 01-14-08 to 12-22-11 F72 02-12-08 to 12-21-11 F75 03-26-08 to 12-13-11 F93 F94 12-05-08 to 07-31-12 12-19-08 to 02-01-11 F95 F96 F104 08-01-09 to 07-31-12 01-28-09 to 07-31-12 05-21-09 to 01-31-12 Table 14. Continued. Status: Alive/Lost contact/Dead; Cause of death Dead. M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Dead. Killed by a puma hunter in Horsefly Canyon (E) 12/23/11. M138 was about 29 months old at death. Alive. Initially captured as 18 mo. old subadult on W side U.P. study area 03-07-11. Established adult territory on NW U.P. Dead. Killed for depredation control; killed an alpaca in Pleasant Valley 09-13-11. Alive. Initially captured as 19 mo. old subadult on W side U.P. study area 02-24-12. Moved to Escalante Creek drainage by adult age 07-31-12. Dead; killed by another puma (sex of puma unknown; male suspected) 08-14-08. F2 was about 92 months old at death. Dead. Killed by a puma hunter in Lindsay Creek 12-11-11. F3 was about 120 months old at death. Dead. Killed by U.S. Wildlife.Services agent 08-03-08 for predator control of depredation on domestic sheep. F7 was about 107 months old at death. Alive. Dead. F16 was struck and killed by a vehicle on Ouray County Road 1 southwest of Colona, CO on 09-11-09. F16 was about 80 months old at death. Dead. Killed by a male puma about 06-06-12. F23 was about 94 months old at death. F23 may have attempted to defend 2 cubs (F149, M161; 13.5 months old) and/or calf elk kill. Dead. Killed by a male puma in Logging Camp Draw about 09-16-11. F24 was about 126 months old at death. F24 may have attempted to defend ≥2 cubs (F147, nonmarked siblings; 12 mo. old). Dead. Lost radio contact after 09-04-09– failed GPS/VHF collar. Photographed alive with three ~9 month old cubs on 12-03-10 on Loghill Mesa. F25 shot dead by a ranch hand on 02-03-11 in Pleasant Valley, Dallas Creek because she was seen among cattle. F25 was about 138 months old at death and in excellent physical condition (49 kg). Lost radio contact after 09-25-07− failed GPS/VHF collar. Recaptured F28 on the study area 02-01-10 and 01-01-11 and 02-16-12, but could not be handled to replace non-functional GPS collar. Dead. Killed by another puma (sex of puma unknown) 07-29-08. F30 was about 60 months old at death. Dead of natural causes 03-26-07; probably injury or illness-related; exact agent unknown. F50 was about 30 months old at death. Dead; killed by a male puma while in direct competition for prey (i.e., mule deer fawn) 08-18-07. F54 was about 49 months old at death. Dead. Killed by a puma hunter Spring Creek 12-22-11. F70 was 80 months old at death. Her death orphaned 2 cubs, F157 and F158, at 4 months old; both starved to death about 01-15-12 at about 5 months old. Lost radio contact after 12-02-10. F72 recaptured in Fisher Creek on 03-18-11, but could not be handled to replace non-functional GPS collar. Photographed on Miller Mesa S of U.P. study area on 12-18 to 21-11 with 3 new cubs born about July 2012. Dead. Killed by a puma hunter in North Fork Cottonwood Creek 12-13-11. F75 was about 98 months old at death. Alive. Dead. Shot dead on 02-01-11 by USDA, APHIS, WS agent for predation on domestic elk in Happy Canyon. F94 was about 74 months old at death. Alive. Alive. Dead. Died probably of starvation associated with senescence in lower Roubideau Creek 01-31-12. F104 was about 132 months old at death. 167 �Puma I.D. F110 Monitoring span 09-21-09 to 02-25-10 F111 F113 01-01-10 to 07-31-12 01-26-10 to 06-06-10 F116 01-20-10 to 09-20-11 F118 F119 02-25-10 to 07-31-12 03-25-10 to 01-28-12 F135 01-01-11 to 09-20-11 F136 F137 F143 F152 F163 F171 F172 01-20-11 to 07-31-12 01-21-11 to 07-31-12 02-15-11 to 07-31-12 06-16-12 to 07-31-12 07-01-12 to 07-31-12 01-20-12 to 07-31-12 03-28-12 to 07-31-12 Table 14 continued. Status: Alive/Lost contact/Dead; Cause of death Dead. Killed by a puma hunter on 02-25-10 in GMU 70 East. F110 was about 41 months old at death. Alive. Dead. F113 died 06-06-10 of injuries consistent with being struck by a vehicle. GPS data indicated that F113 had crossed highway 550 and roads on Loghill Mesa north of Ridgway 24-30 hours before she died in McKenzie Creek. F113 was about 42 months old at death. Dead. Died about 09-20-11 of unknown natural cause associated with pregnancy and birth of new litter of cubs. F116 was about 60 months old at death. Alive. Dead. Died of ruptured uterus and internal bleeding associated with pregnancy in Clay Creek Canyon 01-28-12. F119 was about 95 months old at death. Dead. Died of unknown natural cause in E Fork Dry Creek 09-20-11. Her death orphaned cubs M154 and M155 at 76 days old; both died of starvation or disease when 77 (M154) and 81 (M155) days old. Alive. Alive. Alive. Alive. Alive. Alive. Alive. 168 �Table 15. Preliminary estimated survival rates (S) of adult-age pumas during the 4 years in the reference period (i.e., the study area is closed to puma hunting) and 2 years in the treatment period, Uncompahgre Plateau, Colorado. Survival rates of pumas estimated with the Kaplan-Meier procedure to staggered entry of animals (Pollock et al. 1989). Survival rates are for an annual survival period defined as the biological year (August 1 to July 31). Survival rates were estimated only for periods when n ≥ 5 individual pumas were monitored in the interval. Puma survival in the reference period pertained only to pumas that died of natural causes. Pumas that were killed by people in the reference period, a non-natural cause (i.e., two adult pumas: F7 for depredation control 8/3/2008 and M5 killed by a puma hunter off the protected study area and buffer zone 2/20/2009) were right censored. In the treatment period all sources of natural and human-caused mortality are considered in the survival estimates. Biological Year S 1.000 Females SE 0.0000 S 0.667a Males SE 0.2222a n 6a Reference Annual 2 8/1/2005 to 7/31/2006 0.909 0.0867 11 1.000 0.0000 5 Reference Annual 3 8/1/2006 to 7/31/2007 0.831 0.0986 14 1.000 0.0000 7 Reference Annual 4 8/1/2007 to 7/31/2008 0.875 0.1031 13 1.000 0.0000 8 Reference Annual 5 8/1/2008 to 7/31/2009 0.784 0.1011 19 0.667 0.1924 8 Treatment Annual 1 8/1/2009 to 7/31/2010 Treatment Annual 1b 0.333b 0.1361b 12b 8/1/2009 to 7/31/2010 With mortalities of all marked adult males 0.947c 0.0568 19 0.250 0.1082 9 Treatment Annual 2 8/1/2010 to 7/31/2011 0.548d 0.1063 20 0.167 0.1076 7d Treatment Annual 3 8/1/2011 to 7/31/2012 a Adult male annual S 2005 to 2006 is probably underestimated with poor precision because 3 of the 6 pumas were GPS/VHF-monitored for 4 to 5 months at the end of the interval; 1 of 6 adult males died. b This second estimate of adult male puma survival 8/1/2009 to 7/31/2010 includes 5 males that had non-functional (4) or shed (1) radiocollars. All adult males with non-functional or shed radiocollars in this study survived into treatment year 1 (TY1), which was expected considering adult male survival in 3 previous years. All 5 of those adult males were detected and killed by hunters in TY1. c Only 1 of 2 adult female puma mortalities is represented in this survival analysis for 8/1/2010 to 7/31/2011, that of F94 killed for depredation control. One other adult female mortality, F25, is not represented because she wore a nonfunctional GPS collar making it impossible for us to monitor her survival. F25 was shot by a ranch hand on 2/3/2011 when he saw her among cattle. d Sample includes M144, ranges on NW Uncompahgre Plateau N of the study area but not on the U.P. study area, vulnerable to annual hunting. 169 n 10 �Table 16. Summary of subadult puma survival and mortality, December 2004 to July 2012, Uncompahgre Plateau, Colorado. Puma I.D. M5 Monitoring span 09-16-05 to 06-30-06 No. days 308 M11 06-21-06 to 12-02-07 529 F23 01-04-06 to 02-04-06 31 M31 04-19-06 to 04-26-06 7 M49 03-26-07 to 10-01-07 189 F52 01-10-07 to 05-15-07 125 F66 08-23-07 to 11-05-07 11-25-08 to 06-03-09 74 Status Survived to adult stage. M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. Survived to adult stage. M11 was offspring of F2, born May 2005. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. Survived to adult stage. Captured on the study area when about 17 months old. Survived to adult stage; gave birth to first litter at about 21 months old. Killed by a male puma about 06-06-12. F23 was about 94 months old at death. M69 01-11-08 to 04-07-08 190 87 Survived to adult stage. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-11-08 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. Survived to adult stage. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old, a young adult. Survived to adult stage. F52 dispersed from study area as a subadult by 01-16-07. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old and could have been in her adult-stage home range. GPS collar nonfunctional. F52 was killed by a puma hunter on 01-09-12 in North Beaver Creek SE of Powederhorn, CO. She was about 79 months old at death. Died in subadult stage. F66 was offspring of F30, born July 2007. Lost contact; her cub collar quit after 11-05-07. Recaptured as an independent subadult on her natal area 11-25-08 when 16 months old. Mother F30 was killed by a puma when F66 was 12 months old, within the age range of normal independence. F66 died of injuries to internal organs that caused massive bleeding attributed to trampling by an elk or mule deer on about 05-28-09 when she was 23 months old. Her range partially overlapped her natal area. Survived to adult stage. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-1908. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. 170 �Table 16 continued Puma I.D. F95 Monitoring span 12-29-08 to 07-31-12 No. days 214 M99 02-27-09 to 04-22-09 54 M112 02-10-11 to 04-18-11 67 M115 01-13-10 to 07-21-10 189 M120 12-06-12 1 M134 03-28-11 to 06-10-11 74 M138 01-26-11 to 06-30-11 155 F140 01-13-12 to 07- 31-12 200 M141 12-23-11 1 M144 03-07-11 to 09-08-11 185 F145 03-08-11 to 09-08-11 184 F146 03-08-11 to 03-23-11 15 F147 09-16-11 to 04-12-12 209 Status Alive. F95 is the offspring of F93, born about August 2007. She became an independent subadult by about 18 months old (02-11-09 aerial location) and an adult by about 24 month old (Aug. 2009). F95 established an adult home range adjacent to and overlapping the northern portion of her natal area. Died in subadult stage. M99 probably killed by another puma (canine punctures in skull including braincase) in Jan. 2010 when he was about 16 months old. His radiocollar quit after 54 days. M112 was offspring of F70. Lost contact of M112 after 04-18-11; he may have dispersed or radiocollar quit. M112 associated with F96 and her two radio-collared cubs F129 and M130 during 02-10-11 to 04-1811. Died in subadult stage. M115 was offspring of F28, born in Nov. 2008. He was about 14 months old when first captured on Jan. 13, 2010. When he was recaptured on 03-18-10, he had previously suffered a broken left ulna. M115 was probably independent by 07-15-10 when he was located outside of his natal area on a probably dispersal move. M115 died on about 07-21-10 apparently from complications of his broken left foreleg; probably not allowing him to kill prey sufficiently for survival. M115 was about 20 months old at death. Died in subadult stage. M120 was offspring of F3. M120 was killed by a puma hunter 12-06-12 in his natal area in Spring Creek. He was 17 months old at death. Survived to adult stage (barely). M134 was offspring of unmarked female puma in Roubideau Canyon. Independent by about 03-28-11. Shot dead by USDA, APHIS, WS agent while in the act of attacking domestic sheep on 06-10-11 when he was 24 months old at start of adult life stage. Survived to adult stage. Entered adult life stage 07-01-11. Killed by a puma hunter 12-23-11 in Horsefly Canyon. M138 was about 29 months old at death. Survived to late subadult stage. Will turn adult in Aug. 2012. Probably offspring of F28. Has established a home range adjacent to natal area where she was initially captured at 5 months old on 01-02-11. Died in subadult stage. M141 was killed by a puma hunter on 12-23-11 in Little Bucktail Creek. He was 16 months old at death. Survived to adult stage. Emigrated from U.P. study area. Established adult territory on northwest Uncompahgre Plateau. M144 is sibling of F145 below. Survived to adult stage. Emigrated from U.P. study area and to Colorado Mesa. Killed by a puma hunter 01-23-12 in West Bangs Canyon. F145 was 28 months old at death. Died in subadult stage. F146 was killed and eaten by a male puma while in competition for an adult bull elk carcass that one of the pumas killed in Coal Canyon on the study area. F146 was about 19 months old at death. Lost contact; radiocollar quit after 04-12-12. F147 orphaned at about 12 months old when her mother F24 was killed by a male puma on 09-1611. 171 �Table 16 continued. Puma I.D. F149 Monitoring span 06-06-12 to 07-31-12 No. days 55 M150 03-28-11 to 04-11-11 14 F152 05-04-12 to 06-16-12 44 M153 04-12-11 to 09-06-11 147 M161 06-06-12 to 07-31-12 55 F163 01-26-12 to 07-01-12 157 Status F149 (sibling of M161 below) was orphaned at 13.5 months old when her mother F23 was killed by a male puma. F149 dispersed from the natal area by 07-16-12 to E side U.P. study area when she was 14.8 months old. Dispersed. M150 was offspring of F111, born on 08-31-09. He was independent by 03-28-11 when he was 19 months old. Lost contact after 04-11-11 when M150 was in Cow Creek southeast of the study area. Survived to adult stage. F152 was independent from her mother F93 by 05-04-12 when about 23 months old. She ranged as a subadult and adult on the natal area (07-31-12). Survived to adult stage. Consorted with F137 when 23 months old on 09-07-2011. Killed by Wildlife Services agent for depredation on an alpaca in Dallas Creek on 09-13-11. M153 was 23 months old at death. M161 (sibling of F149 above) was orphaned at 13.5 months old when his mother F23 was killed by a male puma. M161 dispersed from the natal area by 06-29-12 to E side U.P. study area when he was 14 months old. F163 was captured at about 18 months old on the study area. She emigrated from the study area and may have established an adult home range on the N portion of the Uncompahgre Plateau as of July 2012 (07-16-12 most recent location). 172 �Table 17. Records of pumas that dispersed from the Uncompahgre Plateau study area, December 2004 to July 2012. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M5 02-04-05 13S,240577E, 4251037N→ 12S,665853Ex 4277125N M11 06-27-05 13S,248278E, 4239858N→ 12S,741882Ex 4161575N 84.8 M31 04-19-06 329.8 M38 09-08-06 12S,746919E, 4225441N→ 13S,500000Ex 4050000N 13S,249200E, 4239703N→ 12S,703371E, 4316856N M39 09-11-06 71.3 M43 09-15-06 12S,724270E, 4243610N→ 12S,709889E, 4313490N 12S,760177E, 4242995N→ 12S,739859E, 4308557N M48 10-18-06 52.0 M49 12-05-06 12S,756676E, 4247777N→ 12S,704982E, 4248998N 12S,757241E, 4258259N→ 12S,693350E, 4274559N M58 06-27-07 13S,258543E, 4238071N→ 13S,274670E, 4309488N 73.2 Estimated linear dispersal distance (km)* 102.2 104.1 68.6 66.1 Puma Information M5 was offspring of F3, born August 2004. Independent and dispersed from natal area at 13 months old. Established adult territory on northwest slope of Uncompahgre Plateau at the age of 24 months (protected from hunting mortality in buffer area) and ranged into the eastern edge of Utah (vulnerable to hunting). Killed by a puma hunter on 02-20-09 in Beaver Creek, Utah at about 54 months old. M11 was offspring of F2, born May 2005. Shed expandable radiocollar 10-24 to 11-08-05. Recaptured and re-collared 04-0206. Independent at 13 months old. Dispersed from natal area at 14 months old. Moved to Dolores River valley, CO, by 12-14-06. Killed by a puma hunter on 12-02-07 when about 30 months old. M31’s estimated age at capture was 20 months. Dispersed to northern New Mexico and was killed by a puma hunter on 12-1108 in Middle Ponil Creek, Cimarron Range. He was about 52 months old. M38 was offspring of F2, born July 29, 2006. Shed his expandable radiocollar by 03-06-07. Photographs by trail camera in McKenzie Cr. of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. M38 was killed by a puma hunter in Ladder Creek southwest of Grand Junction, CO on 01-07-11. He was 53.2 months old at death. M39 was offspring of F8, born August 2006. M39 was killed by a puma hunter in Bangs Canyon, GMU 40 on 03-12-10 when he was 42.8 months old. M43 was offspring of F7, born August 2006. He shed the expandable radiocollar 11-7 to 17-06, after which direct contact was lost. M43 was killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO when he was 29.5 months old. M48 was the offspring of F3, born September 2006. M48 was killed by a puma hunter in Tabeguache Creek, GMU 61N on 1227-09 when he was 38.9 months old. M49 was offspring of F50, born July 2006. Orphaned at about 9 months old, when F50 died of natural causes. Dispersed from his natal area at about 10 months old and ranged on the northeast slope of the Uncompahgre Plateau. When M49 was about 15 months old, he shed his expandable radiocollar on about 10-01-07 at a yearling cow elk kill on the northeast slope of the Uncompahgre Plateau. He was killed by a puma hunter in Blue Creek GMU 61N in the protected buffer zone north of the study area on 01-24-09; he was about 29 months old. M58 was offspring of F16, born May 2007. M58 was killed by a puma hunter on 12-27-09 in the North Fork of the Gunnison River north of Paonia, GMU 521; he was 31 months old. 173 �Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 66.1 M63 was offspring of F24, born July 14, 2007. He was not radiocollared as a cub. M63 was killed by a puma hunter in Calamity Creek on northwest Uncompahgre Plateau on 01-01-11. M63 was 41.5 months old at death. 97.0 M65 was offspring of F24, born July 2007. M65 was killed by a USDA, APHIS, WS agent for depredation on llamas in the Little Dolores River on 11-07-09. M65 was 27.8 months old. Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M63 08-17-07 M65 08-17-07 M67 08-23-07 12S,738144E, 4233628N→ 12S,689111E, 4277908N 12S,738144E, 4233628N→ 12S,684084E, 4314200N 13S,257371E, 4235231N→ 12S,725113E, 4242447N M68 08-23-07 M69 01-11-08 M82 07-05-08 12S,726901E, 4243463N→ 13S,255316E, 4216768N 60.5 M83 07-05-08 90.7 M87 07-31-08 12S,726901E, 4243463N→ 12S,670949E, 4314779N 13S,239006E, 4248601N→ 12S,724325E, 4244118N M88 07-31-08 13S,239006E, 4248601N→ 12S,704835E, 4197839N 77.6 M92 09-29-08 13S,246359E, 4226949N→ 12S,750871E, 4222921N 21.9 13S,257371E, 4235231N→ 12S,711262E, 4198681N 13S,248191E, 4246810N→ 13T,378900E, 4591990N 57.7 80.7 369.6 39.2 M67 was offspring of F30, born July 17, 2007 in Fisher Creek on the east slope of the study area. He was not radiocollared as a cub. M67 dispersed from the natal area and was recaptured in Tomcat Creek on the west slope of the study area on 02-24-10 when he was 31 months old. M67 is a resident adult in that area (07-3111). Killed by puma hunter in GMU61N on 12-18-11 when 52.9 months old. M68 was offspring of F30, born July 2007. He was orphaned at 12 months old when his mother was killed by a puma. He was killed by a puma hunter in the Disappointment Valley in southwest CO on 12-30-08; he was 17 months old. M69 was captured on the study area when about 14-18 months old. Emigrated from the study area as subadult by 03-19-08. Last VHF aerial location was southwest of Waterdog Peak, east side of Uncompahgre River Valley on 04-07-08. M69 was killed by a puma hunter on 11-06-08 in Pass Creek in the Snowy Range, WY when he was 24 to 28 months old. M82 was offspring of F8, born May 29, 2008; sibling of M83 below. He shed his expandable cub radiocollar after 03-20-09. M82 was killed by a puma hunter on 12-10-09 in the Beaver Creek fork of East Dallas Creek, GMU 65. M82 was 19 months old. M83 was offspring of F8, born May 29, 2008; sibling of M82 above. He was not radiocollared as a cub. M82 was killed by a puma hunter on 01-18-11 in Coates Creek west of Glade Park, CO. He was 30 months old at death. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M88 below. He was not radiocollared as a cub. M87 dispersed from the natal area. He was recaptured on the west slope of the study area on 02-09-11 when he was 31 months old. M87 is was resident adult on the west slope of the study area. He was killed by a puma hunter on 12-06-11 at 41 months old north of the study area. M87 was offspring of F3, born July 3, 2008 on the east slope of the study area; sibling of M87 above. He was not radiocollared as a cub. M87 dispersed from the natal area. He was killed by a puma hunter in Dawson Creek, Disappointment Valley on 11-3010 when he was 29 months old. M92 was offspring of F25, born August 19, 2008. He was radiocollared as a cub; last contact on 12-12-08. M92 dispersed from the natal area and was recaptured in McKenzie Creek, west slope of the study area on 04-22-11 when he was 32 months old. He could not be handled to fit a new radiocollar because of a dangerous tree. 174 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) M107 06-28-09 M114 02-27-10 M117 02-05-10 13S,242359E, 4252618N→ 12S,754886E, 4341330N 13S,256933E, 4237862N→ 13S,492615E, 4266192N 12S,731840E, 4232346N→ 12S,743909E, 4216633N M126 09-05-10 M144 03-07-33 M161 01-23-12 F52 01-10-07 F97 02-04-09 12S,727529E, 4237648N→ 12S,705930E, 4227299N F106 06-14-09 12S,736451E, 4240278N→ 13S,258089E, 4235866N 12S,734503E, 4224636N→ 12S, 710850E, 4239350N 12S,727173E, 4242012N→ 12S,696439E, 4276888N 12S,727932E, 4239430N→ 12S,750473E, 4247250N 13S,258058E, 4236260N→ 13S,319217E, 4240467N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 89.2 M107 was offspring of F94, born May 25, 2009; sibling of F108 below. He was not radiocollared as a cub. M107 dispersed from the nata area. He was killed by a puma hunter in Cottonwood Creek near Molina, CO on 12-09-10 when he was 19 months old. 237.5 M114 was initially captured at about 30 months old. Emigrated from the U.P. study area. He was killed by a puma hunter on 0310-12 in Beaver Creek, GMU59. He was about 55 months old at death. 19.7 M117 was offspring of F119. He wore an expandable cub collar, but shed the collar by 07-15-10 on the natal area when about 11 months old. M117 was killed by a puma hunter in Beaver Creek, San Miguel River at the southern extreme of his natal area on 0101-11. He was 17 months old at death. It is unknown if M117 was independent from his mother F119 at the time of his death. 27.7 M126 was offspring of F118, born Aug. 8, 2010. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Dispersed from natal area. Killed by a puma hunter on 01-08-12 in Tuttle Draw WNW of Nucla, CO as 17-month-old subadult. 46.6 M144 was initially captured as an independent subadult in association with subadults F145 and F146 on the study area. Mother is unknown. He moved off the study area on 03-15-11. M144’s last aerial radio location was in Blue Creek on northwest Uncompahgre Plateau on 07-13-11; he was about 22 months old. M144 established his adult territory on northwest Uncompahgre Plateau and upper Unaweep Canyon from Sep. 2011 to July 2012. 23.9 M161 (sibling of F149) was orphaned when his mother F23 was killed by a male puma on 06-06-12; he was 411 days (13.5 mo.) old. M161 dispersed from the natal area by 06-29-12 when he was 14 months old and moved to the east slope of the U.P. study area. 61.1 F52 was captured on the study area when about 18-20 months old. Dispersed from study area as a subadult by Jan. 16, 2007. F52’s last VHF aerial location was Crystal Creek, a tributary of the Gunnison River east of the Black Canyon 05-15-07. She was treed by puma hunters on 12-29-08 on east Huntsman Mesa, southeast of Powderhorn, CO. She was about 41-43 months old . F52 was treed again by puma hunters on about 12-16-09 south of Powderhorn: 13S,319480E,4233219N. F52 was about 53-55 months old. This suggests that F52 has an adult home range in that area. F52 was killed by a puma hunter on 01-09-12 in North Beaver Creek SE of Powederhorn, CO. She was about 79 months old at death. 24.0 F97 was offspring of F23, born May 23, 2008. She was radiocollared at 8.5 month old in San Miguel Canyon; but, lost contact on 05-12-09 after F97 shed the radiocollar at an elk cache. F97 dispersed from the U.P. study area. She was killed by a puma hunter on 01-22-12 in Dry Creek west of the U.P. study area when she was 43.9 months old. 46.9 F106 was offspring of F75, born May 7, 2009. She wore an expandable cub collar, but shed it about 03-23-10. F106 dispersed from the natal area and moved to the east slope of the study area where she was photographed at one of our scent station cameras at the mouth of Fisher Creek from 02-27-11 to 03-03-11. She was identified by her eartag. F106 was 21 months old. 175 �Puma I.D. 1st capture date on study area 1st capture location→kill or resight location (UTM, NAD27) F108 06-28-09 13S,242359E, 4252618N→ 12S,752013E, 4263883N F143 02-15-11 F145 03-18-11 12S,723748E, 4238579N→ 12S,721795, 4264246 12S,727181E, 4241468N→ 12S,705833E, 4312909N F149 06-06-11 F163 01-26-12 12S,729993E, 4242329N→ 12S,715551E, 4285489N 12S,732153E, 4232452N→ 12S,695407E, 4280753N Table 17 continued. Estimated Puma Information linear dispersal distance (km)* 18.2 F108 was offspring of F94, born May 25, 2009; sibling of M107 above. She was fitted with an expandable cub collar; but, shed the collar in the original nursery due to failure of the fastener. F108 dispersed from the natal area. She was killed by a puma hunter on the study area on 11-29-10 when she was 17 months old. 25.7 F143 was captured on the study area when about 24 months old. Dispersed N on the Uncompahgre Plateau and established an adult home range on the NW portion of the Uncompahgre Plateau (most recent location 07-16-12). 74.5 F145 was originally captured in association of M144 and F146; they may be siblings. Mother unknown. She moved off the study area with M144 on 03-15-11. F145 emigrated to Colorado Mesa. She was killed by a puma hunter 01-23-12 in West Bangs Canyon. F145 was 28 months old at death. 45.5 F149 (sibling of M161) was orphaned when her mother F23 was killed by a male puma on 06-06-12; she was 411 days (13.5 mo.) old. F149 dispersed from the natal area by 07-16-12 when she was 14.8 months old and moved to the NE Uncompahgre Plateau. 60.7 F163 was initially captured at about 18 months old. She emigrated from the study area and may have established an adult home range on the N portion of the Uncompahgre Plateau as of July 2012 (0716-12 most recent location). *Estimated linear dispersal distance (km) from initial capture site on Uncompahgre Plateau study area to hunter kill, or last recapture, radio location, or observation site. 176 �Table 18. Recorded deaths of non-marked and marked pumas struck by vehicles and other unusual causes, in chronological order, on the Uncompahgre Plateau puma study area, Colorado, from 2004 to 2012. Puma sex & ID if marked M Estimated age (mo.) Date recorded Cause of death General physical condition Location & UTM NAD27 12 09-24-04 Good F 49 07-28-05 Vehicle collision Vehicle collision Pleasant Valley, County Road 24 13S,252870E,4227520N Highway 62 east of Dallas divide 13S,250000E,4222500N F17a 11 08-18-06 F 18-24 11-06-06 F 6 01-30-07 F P1005 36 09-16-08 M 12-24 08-13-08 F61a 18 11-13-08 F 12 08-10-09 F16b 80 09-11-09 M6b 99 05-21-0 F113b 42 06-06-10 Vehicle collision Vehicle collision Vehicle collision Asphyxia, lodged in fork of tree Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Vehicle collision Good Not pregnant or lactating Good Good Good Unknown, decomposed Good Good Good Good Good Good Not pregnant or lactating M 24 08-25-10 Vehicle Excellent P1018c collision F 6 02-16-11 Vehicle Good P1030c collision M 4 10-07-11 Vehicle Fair P1034 collision a Subadult marked (i.e., tattoos, eartags), but not radio-collared. b Adult GPS/VHF-collared pumas. c Non-marked puma with P one-thousand number designation. 177 Highway 550 south of Colona 13S,257602E,4242185N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 62 west of Dallas divide 12S,762286Ex4218992N Davis Point, Roubideau Canyon 12S, 743718E,4255277N Highway 145 west of Placerville 13S,756490E,4212336N Highway 550 east of Ridgway State Park 13S,259843E,4235985N Highway 145 east of Norwood 12S,745739E,4222548N Ouray County Road 1 13S,253733E,4240060N Highway 550 south of Colona 13S,258610E,4236805N F113 crossed Highway 550 and roads on Loghill Mesa 24-30 hours before she died in McKenzie Creek 13S,257272E,4238435N Highway 62 Leopard Creek 12S,237747E,4220330N Highway 62 Leopard Creek 12S,760953E,4216683N Highway 62 Leopard Creek 12S,762806E,4219531N �Table 19. Pumas monitored with GPS collars on the Uncompahgre Plateau, Colorado, December 2004 to July 2012. Puma I.D. M1 M4 M6 M27 M29 M51 M55 M100 M133 F2 F3 F7 F8 F16 F23 Sex M M M M M M M M M F F F F F F F24 F25 F28 F30 F50 F52 F54 F70 F72 F75 F96 F104 F111 F113 F135 F136 F137 F152 F F F F F F F F F F F F F F F F F F F171 F172 F F Age stage adult adult adult adult adult adult adult adult adult adult adult adult adult adult subadult adult adult adult adult adult adult subadult adult adult adult adult adult adult adult adult adult adult adult subadult adult adult adult Dates monitored 12-08-04 to 07-20-06 01-28-05 to 01-14-06 02-18-05 to 05-14-08 03-12-06 to 06-21-06 04-14-06 to 01-01-08 01-07-07 to 07-15-08 01-21-07 to 11-25-10 03-27-09 to 01-16-10 11-12-10 to 12-01-10 01-07-05 to 08-14-08 01-21-05 to 12-11-11 02-24-05 to 08-03-08 03-21-05 to 10-10-06 10-12-05 to 09-10-09 01-04-06 to 02-04-06 02-05-06 to 09-04-09 01-17-06 to 07-25-07 02-09-06 to 09-09-09 03-24-06 to 08-15-07 03-30-07 to 02-22-08 12-14-06 to 03-26-07 01-10-07 to 05-08-07 01-12-07 to 08-18-08 01-14-08 to 12-22-11 02-12-08 to 07-07-10 03-26-08 to 06-03-09 01-28-09 to 07-31-12 05-29-09 to 01-31-12 01-01-10 to 07-31-12 01-27-10 to 06-06-10 01-01-11 to 09-20-11 01-20-11 to 07-31-12 04-12-11 to 07-31-12 01-18-12 to 06-15-12 06-16-12 to 07-31-12 01-20-12 to 07-31-12 03-28-12 to 07-31-12 178 �Table 20. Number of Trichinella larvae recovered from puma tongues, southwest Colorado, 2010-2011. Sex Puma Seal and/or I.D. Estimate Date Location: UTM Trichinella Larvae d Age collected NAD27 Per Gram (LPG) of Zone, Easting, Tongue Tissue (years) Number Northing F94 F 5 2/1/2011 13S,246976E,4255108N 1.2 12301 M 1.5 12/12/2010 12S,735100E,4249600N 5.1 6266 F 11-12 2/3/2011 13S,252703E,4225101N 0.4 (F25) 12039 F 4-5 11/22/2010 13S,283349E,4234088N 2.0 12042 M 3-4 11/26/2010 12S,736610E,4230762N 3.2 12045 M 2-3 12/1/2010 13S,283888E,4310965N 8.4 12046 M 3 12/1/2010 12S,729439E,4236264N 5.4 12047 M 9-10 12/2/2010 13S,257722E,4239169N 12048 M 2 12/3/2010 13S,261946E,4241911N 7.6 12302 M 2.5 12/17/2010 13S,316520E,4228320N 5.1 12314 F 5 1/13/2011 13S,305193E,4247057N 1.4 12317 M 1.5 1/17/2011 12044 F 1.5 11/29/2010 12S,752013E,4263883N M 6-7 11/25/2010 13S,239181E,4248300N (M32) 2.8 (F108) 12041 1.0 (M55) 179 0.0 0.0 �GOAL: Strategies, Information, & Tools for Managing Healthy, Self-sustaining Puma Populations in Colorado Puma Habitat Puma Population Effects of Harvest & Other Mortality Movements & Corridors Population Dynamics: Sex & Age, Vital Rates, Mortality, Population Growth Rates Vulnerability to Harvest Human Development Habitat Use Effects of Translocation Domestic Animals Puma― Human Relationships Deer, Elk, Other Natural Prey & Species of Concern Effects of Predation Effects of Evasive Conditioning Map Prey Distribution Habitat Models Population Models Puma Prey Puma―Prey Relationships Models Methods for Monitoring Populations Habitat Maps Figure. 1. An ecologically-based conceptual model of the Colorado Puma Research Program that provides the contextual framework for this and proposed puma research in Colorado. Gray-shaded shapes identify areas of research addressed by this puma research on the Uncompahgre Plateau for the puma management goal in Colorado (at top). 180 �Figure 2. The puma study area on the southern half of the Uncompahgre Plateau, Colorado (shaded in gray) comprising the southern portions of Game Management Units (GMUs) 61 and 62 and a northern portion of GMU 70. Figure 3. Trends in the population of independent pumas on the Uncompahgre Plateau Puma Study Area, including Reference Years 4 and 5 (RY4, RY5) and Treatment Years 1, 2, and 3 (TY1, TY2, TY3). Numbers represent minimum counts that include all pumas from known radio-collared pumas, visual observations of non-marked pumas, harvested non-marked pumas, and track counts of suspected nonmarked pumas on the study area during fall to spring hunting and research capture seasons, except RY5 (45), which had to be modeled from RY4 observation data (33) because the state government hiring freeze that year affected search and capture efforts. The actual minimum count for RY5 was 37 independent pumas. The quota of 8 pumas for TY1 represented a 15% harvest of the model projected 53 181 �independent pumas expected in TY1 and was used to set the quota ahead of the hunting season. Starting in TY1, two capture teams were deployed to count pumas on the study area because the hunting season shortened our fall-winter-spring research period. We deployed a team on each the east and west sides of the study area. The minimum count for TY1 was actually 55 independent pumas, consistent with the model expected 53. Post-harvest high trend line represents the population of independent pumas after pumas harvested only on the study area by hunters. This trend line represents 14.5% to 16.7% harvest of independent pumas. Post-harvest low trend line represents the population of independent pumas after pumas harvested on the study area and pumas harvested when they ranged onto adjacent GMUs open to hunting and other mortalities are subtracted from the minimum count. TY1 post-harvest low includes 1 adult female and 3 adult males killed off the study area. The TY2 post- harvest low includes 1 adult male killed off the study area and 2 adult female pumas killed in February 2011 on the study area to protect livestock. The TY3 post-harvest low includes 1 adult female and 4 adult males harvested off the study area and 2 adult females that died of natural causes on the study area. This trend line represents 21.2% to 31.2% harvest of independent pumas. Figure 4. Estimated age structure of independent pumas in November 2011 at the beginning of the puma hunting season in Treatment Year 3 (TY3) on the Uncompahgre Plateau study area, Colorado. All these pumas were captured and sampled by researchers or harvested by hunters and examined by researchers. Mean ± SD of female and male ages, respectively: 5.85 ± 3.05 yr. (70.19 ± 36.57 mo.), n = 16; 2.25 ± 1.58 yr. (27.00 ± 18.95 mo.), n = 10. 182 �Figure 5. Puma births (black bars) detected by month from May 19, 2005 to July 5, 2012 (n = 46 litters of 24 females; 44 of the litters were examined at nurseries when cubs were 26-42 days old and 2 litters confirmed by tracks of ≥1 cubs following GPS-collared mothers F28 and F111 when cubs were ≤42 days old). Also shown (gray bars) are results of the earlier effort by Anderson et al. (1992:48; 1982 to 1987, n = 10 litters of 8 females, examined when cubs were <1 to 8 months old), Uncompahgre Plateau, Colorado. 183 �Appendix A. Summary of individual puma cub survival and mortality, 2005 to 2012, Uncompahgre Plateau, Colorado. Puma I.D. M5 Estimated Age at capture (days) 183 Est. Birth date ~8-1-04 Est. survival span from 1st capture to fate or last monitor date 02-04-05 to 04-07-08 Age to last monitor date alive or at death (days, birth to fate) ~1,664 F9 31 5-28-05 06-27-05 to 4-19-06 06-27-05 to 11-20-05― 12-29-05 06-27-05 to 12-2-07 326-333 F10 31 5-28-05 M11 31 5-28-05 F12 42 5-19-05 07-01-05 to 12-08-05― 01-26-06 203-252 F13 42 5-19-05 101 F14 26 6-26-05 07-01-05 to 08-28-05 07-22-05 to 02-07-06― 03-10-06 M15 26 6-26-05 F17 34 9-22-05 F18 34 9-22-05 M19 34 9-22-05 M20 34 9-22-05 F21 37 9-26-05 176-215 918 226-257 07-22-05 to 06-06 to 14-06 10-26-05 to 08-18-06 345-353 10-26-05 to 07-20 to 27-06 10-26-05 to 07-27 to 08-02-06 10-26-05 to 05-24-06 11-02-05 to 08-16-06 301-308 330 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Radio-collared. Survived to subadult stage by 09-16-05; independent at ~13 mo. old. Dispersed from natal area by 09-29-05 at 14 mo. old. Established territory on NW U.P. Killed by hunter in Beaver Creek, UT 02-20-09 at 54.6 months old. Radio-collared. Shed radiocollar 04-19-06 to 04-26-06. F3 Radio-collared. Dhed radiocollar 08-10-05; last tracks of F10 with mother F2 & siblings F9 & M11 observed 11-2005. F10 disappeared by 12-30-05. Radio-collared. Shed collar 10-24 to 11-08-05. Recollared on 04-02-06. Survived to subadult stage by 06-21-06, independent at 13 mo. old. Dispersed from natal area by 0711-06 at 14 mo. old. Killed by a hunter in SW CO 12-2-07 at 918 days (30 mo.) old. Radio-collared. Shed radiocollar 07-28-05―08-01-05. Tracks of F12 found in association with mother F7 on 1208-05. F12 disappeared by 01-27-06 when she was not visually observed with F7, and her tracks were not seen in association with F7’s tracks. Radio-collared. Killed and eaten by a puma possibly M5 (13 mo. old) about 08-28-05. Radio-collared. Shed radiocollar 01-20-06 to 01-25-06. Tracks of F14 were observed with tracks of mother F8 & sibling M15 on 02-07-06. Disappeared by 03-11-06, only tracks of F8 & M15 were found. Radio-collared. Shed radiocollar 06-06-06 to 06-14-06. F2 F2 F2 F7 F7 F8 F8 F16 308-314 Radio-collared. Shed radiocollar 06-06-06 to 06-14-06. Killed by a car on highway 550 on 08-18-06. Probably dependent on F16. Died at 10.8 months old Radio-collared. Probably killed by another puma. Multiple bite wounds to skull. Died at 10 months old. Radio-collared. Shed radiocollar 07-27-06 to 08-02-06. 244-245 Radio-collared. Shed radiocollar 05-24-06―05-25-06. F16 324 Radio-collared. Lost contact; radiocollar quit. Last aerial location 8-16-06, live signal. F3 184 F16 F16 �Appendix A continued Puma I.D. Estimated Age at capture (days) M22 37 9-26-05 M26 183 8-1-05 F33 31 5-30-06 F34 31 F35 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 11-02-05 to 12-21-05― 12-22-05 02-08-06 to 03-21 to 24-06 06-30-06 to 07-31-06 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 86-87 Radio-collared. Killed and eaten by male puma 12-21-05 to 12-22-05. F3 ~232-235 Radio-collared. Shed radiocollar 03-21-06 to 03-24-06. F25 63-65 F23 5-30-06 06-30-06 to 07-31-06 63-65 31 5-30-06 38 F36 29 6-9-06 29 6-9-06 M38 41 7-29-06 Radio-collared. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Radio-collared. Killed and eaten by a male puma 08-22-06. GPS data on M29 indicate he was not involved. Radio-collared. Shed radiocollar found 03-06-07. Photo (trail camera in McKenzie Cr.) of M38 & Unm. F sibling with F2 on 07-16 to 17-07 at 352-353 days old. Killed by puma hunter 01-07-11 in GMU40 Ladder Creek when he was 53.2 months old. Radio-collared. Shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 03-12-10 in GMU 40 when 42.8 months old. Radio-collared. Shed radiocollar by 09-20-06, but seen alive on that date. Tracks of 2 cubs following F8 on 04-25-07. F28 M37 06-30-06 to 07-07-06 07-08-06 to 07-28-06 07-08-06 to 07-28-06 09-08-06 to 07-16 to 17-07 Radio-collared. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Radio-collared. Probably killed and eaten by a male puma 08-01 to 03-06. GPS data on M29 indicate he was not involved. Dead; research-related fatality.a Radio-collared. Assumed dead. Shed radiocollar or died (blood on collar) between 10-05-06 (last live signal) & 1013-06 (collar found). Dead; research-related fatality.b F8 Radio-collared. Shed radiocollar by 11-7 to 17-06. Killed by a puma hunter 01-28-09 in Deer Creek, west slope of Grand Mesa, CO GMU41 at 29.5 months old. F7 74 74 352-353 M39 29 8-13-06 F40 29 8-13-06 F41 29 8-13-06 M42 29 8-13-06 M43 33 8-13-06 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 09-20-06 to 04-25-07 09-11-06 to 10-05-06 09-11-06 to 11-27-06 09-15-06 03-01-07 1623 9 255 1307 9 Mother I.D. F23 F23 F28 F2 F8 F8 255 53-61 106 200 899 185 F8 �Appendix A continued Puma I.D. Estimated Age at capture (days) M44 33 Est. Birth date 8-13-06 Est. survival span from 1st capture to fate or last monitor date 09-15-06 to 02-14-07 Age to last monitor date alive or at death (days, birth to fate) 479 F45 33 8-13-06 09-15-06 to 5-20 to 23-07 280-283 M46 31 9-17-06 10-18-06 to 12-15-06 89 360 M47 M48 M49 31 31 153 9-17-06 9-17-06 7-1-06 10-18-06 to 12-15-06 to 09-12-07 10-18-06 to 12-15-06 to 09-12-07 to 12-27-09 89 360 89 360 1187 12-05-06 to 07-31-07 to 01-01-07 ~456 186 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Radio-collared. Shed radiocollar by 10-27-06. Treed, visually observed 02-14-07; sibling (?) M56 also captured, sampled, & marked for 1st time. M44 killed by Wildlife Services for depredation control on 12-05-07, for killing 4 domestic sheep. He was still dependent on F7. He was 15.7 months old. Radio-collared. Multiple puncture wounds on braincase― parietal & occipital regions; consistent with bites from coyote. F45 switched families, moving from F7 to F2 about 12-19 to 20-06. Last date F45 was with F2 was 04-17-07. Died 05-20 to 23-07 when she was 9.2 months old. Radio-collared. Shed collar by 12-14-06. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Radio-collared. Shed collar . Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Radio-collared. Shed radiocollar. Tracks of all cubs observed following F3 12-15-06. Tracks & GPS data indicated that F3 apparently with ≥1 of her male cubs (M46, M47, M48) at 360 days old on 09-1207 in Puma Canyon. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 61N when 38.9 months old. Radio-collared. M49 was orphaned when his mother died on about 03-26-07; he was ~268 days old. M49 dispersed from natal area and onto NE slope of U.P. Shed radiocollar at a yearling cow elk kill about 10-01-07; he was ~428 days old. Killed by a puma hunter in Blue Creek, northwest Uncompahgre Plateau (GMU 61N) 01-24-09 when ~29 months old. Mother I.D. F7 F7 F3 F3 F3 F50 �Appendix A continued Puma I.D. Estimated Age at capture (days) F53 183 Est. Birth date 7-1-06 M56c 183 ~8-13-06 F57 35 4-16-07 M58 34 5-24-07 Est. survival span from 1st capture to fate or last monitor date 01-12-07 to 02-23-07 to 09-02-07 02-14-07 to 03-01-07 05-21-07 to 06-06-07 06-27-07 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 42 Radio-collared. Shed radiocollar 02-23-07. F53 visually observed by P. & F. Star (Loghill Mesa), on 09-02-07, when F53 was ~14 months old and an independent subadult. F54 Radio-collared. Shed radiocollar 2-27-07. M56 observed 0301-07. Radio-collared. Shed radiocollar 06-07-07. Live mode 0606-07. Not radio-collared. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Survived to adult stage; dispersed from natal area. Killed by a puma hunter 12-27-09 in GMU 521 when 31 months old. Radio-collared. Shed collar about 02-14-08. Observed with 11-20-07 with F16, but without siblings M58 and F61. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. Three cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead; research-related mortality.d F7 (?) Radio-collared. Radiocollar malfunction. Tracks of 3 cubs observed with F16’s tracks on 04-12-08, McKenzie Butte-Pinon Ridge Pass. 3 cubs observed with F16 on 08-08-08 by B. & T. Traegde. Dead. Died probably as independent subadult at 538 days old; struck by car on Hwy 550 mi. marker 111 N. of Ridgway, CO, euthanized by gunshot on 11-13-08. Not radio-collared. Not radio-collared. Dispersed from study area. Killed by a puma hunter 01-01-11 in Calamity Creek, GMU61N when he was 41.5 months old. Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. F16 ~428 subad. 200 52 324 434 F59 34 5-24-07 06-27-07 to 08-21-07 55 324 M60 34 5-24-07 F61 34 5-24-07 06-27-07 to 07-11 to 12-07 06-27-07 to 06-29-07 434 48-49 324 434 538 M62 M63 M64 34 34 34 7-14-07 7-14-07 7-14-07 08-17-07 08-17-07 to 01-01-11 1267 08-17-07 262 187 Mother I.D. F25 F16 F16 F16 F24 F24 F24 �Appendix A continued Puma I.D. Estimated Age at capture (days) M65 34 Est. Birth date 7-14-07 Est. survival span from 1st capture to fate or last monitor date 08-17-07 to 11-07-09 Age to last monitor date alive or at death (days, birth to fate) Not radio-collared. Two out of potential of 4 of F24’s male cubs were visually observed with her on 4/1/08. Assume that 2 male cubs died before the age of 8.5 mo. Eartags were seen on both cubs, but the numbers were not. Survived to adult stage; dispersed from natal area. Killed by Wildlife Services for depredation control on 11-07-09 when 27.8 months old. Radio-collared. Lost contact; last location 11/5/07. No signals after that date. F66 was photographed with one male sibling, either M67 or M68, & F30 on 5/31-6/1/08. F66 was recaptured and radio-collared as a subadult on 11/25/08. She died from massive trauma & bleeding of internal organs possibly resulting from being trampled by an elk or mule deer on about 05-28-09 as an independent subadult 23 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 5/31-6/1/08. Dispersed from natal area. Established adult home range on west side of Uncompahgre Plateau. Killed by puma hunter in GMU61N on 12-18-11 when 52.9 months old. Not radio-collared. M67 or M68 was photographed with sibling F66 & mother F30 on 05-31 to 06-01-08. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in Disappointment Valley, CO (GMU 71) 12-30-08 at 17.5 months old. Radio-collared. Shed radiocollar between 7-9-08 and 7-1508, probably while still dependent on mother F75. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. Not radio-collared. Probably dead; if not killed when sibling M79 was killed, then probably would starve to death. 262 847 F66 37 7-17-07 08-23-07 to 11-05-07 111 681 M67 37 7-17-07 08-23-07 to 12-18-11 M68 37 7-17-07 08-23-07 to 12-30-08 1615 532 F74 259 6-1-07 5-19-08 03-12-08 to 07-09-08 06-18-08 M76 30 ~87 M77 30 5-19-08 06-18-08 ~87 F78 30 5-19-08 06-18-08 ~87 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 403 188 Mother I.D. F24 F30 F30 F30 F75 F2 F2 F2 �Appendix A continued Puma I.D. Estimated Age at capture (days) M79 30 5-19-08 Est. survival span from 1st capture to fate or last monitor date 06-18-08 F80 40 5-23-08 07-02-08 F81 40 5-23-08 F97 257 5-23-08 07-02-08 to 07-29-09 02-04-09 to 01-22-12 M82 37 5-29-08 07-05-08 to 12-10-09 560 M83 37 5-29-08 07-05-08 to 01-18-11 964 M84 36 6-5-08 07-11-08 to 02-11-09 251 F85 36 6-5-08 07-11-08 to 10-01-08 118 Est. Birth date Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 87 Not radio-collared. Dead. Chewed-off anterior portions of the nasals, maxilla, palate, dentaries, and pieces of the braincase, with 6 or 9 portion of yellow ear-tag and intestines and bits of skin found ~45 m from mother F2’s death site on 08/14/08. Cub death probably due to puma-caused infanticide with cannibalism at ~87 days old. Male puma scrapes, about 8, under a rock rim ~50m distance from cub remains, and made ~ time of pumas’ deaths. Not radio-collared. Apparently died before 02-04-09; no tracks found in association with F23 & siblings F81 & F97. Radio-collared. Last live location 7-29-09. 424 1339 Radio-collared. Lost contact after 05-12-09; shed collar at elk kill cache on Mailbox Park. Dispersed from study area. Killed by a puma hunter 01-22-12 in Dry Creek when 43.9 months old. Radio-collared. Survived to subadult stage; dispersed from natal area. Killed by a puma hunter in 12-10-09 GMU 65 when 18.4 months old. Not radio-collared. Survived; dispersed from study area. Killed by a puma hunter 01-18-11 on Glade Park, GMU40. He was 31.6 months old. Radio-collared 7-11-08 to 7-22-08; collar removed because of malfunction. Not radio-collared after 7-22-08. Eartag of M84 was found by E. Phillips on 8-25-08 when mother F70’s GPS locations located her on either side of the eartag in the East fork Dolores Cyn. M84 recaptured radiocollared again 1-29-09 in Dolores Cyn. in association with F70 & F96’s family. Shed radiocollar again about 0214-09. Radio-collared. Dead. Probably died of predation or infanticide about 10-108 near elk calf kill at age 3.9 months. 189 Mother I.D. F2 F23 F23 F23 F8 F8 F70 F70 �Appendix A continued Puma I.D. Estimated Age at capture (days) F86 36 6-5-08 M87 28 M88 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 07-11-08 to 07-23 to 08-03-08 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death ~48-59 7-3-08 07-31-08 to 12-06-11 1251 28 7-3-08 07-31-08 to 11-30-10 880 F89 M90 28 36 7-3-08 7-9-08 07-31-08 08-14-08 Male 7A 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Male 7B 28-35 7-10-08 ~08-07-08 to 08-14-08 28 to 35 Female 7C 28-35 7-10-08 28 to 35 M91 35 8-19-08 ~08-07-08 to 08-14-08 09-29-08 M92 35 8-19-08 09-29-08 976 F95 16 mo. June-07 12-29-08 F98 4-5 mo. Sep-Oct08 02-12-09 to 03-08-09 Radio-collared 7-22-08. Dead. Radio-collar, orange ear-tag #86 with pinna with green tattoo #86 found by J. Timmer 9-1-08. F86 died ~7-23 to 8-3-08 when mother F70’s GPS locations located her at F86 remains. Probable predation. Not radio-collared. Dispersed from natal area. Recaptured as adult on west slope of study area on 02-09-11. Alive as of 07-31-11. Killed by puma hunter on 12-06-11 at 41 months old north of the study area. Not radio-collared. Dispersed. Killed by a puma hunter in Disappointment Valley, GMU711 on 11-30-10 when 28.9 months old. Radio-collared. Radio-collared. Recaptured as young adult on study area, adjacent to natal area, on 11-16-10. Killed by a puma hunter during TY2 on 11-23-10. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 was shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died from starvation after they were orphaned. F7 shot on 8-3-08 for killing domestic sheep. Not radio-collared. F7’s cubs died of starvation after orphaned. F7 shot on 8-3-08 for killing domestic sheep. Radio-collared. Killed by a puma hunter on study area during TY1 as dependent cub on 11-17-09 at age 14.9 months. Radio-collared. Lost contact after 12-12-08. Dispersed from natal area. Recaptured in McKenzie Creek, west slope of study area on 04-22-11 when 32 months old. Radio-collared. Survived to adult stage. Established adult home range overlapping mother F93’s home range. To date, July 2012, F95’s home range mainly adjacent to N side of natal area. Radio-collared. Died; probably killed by male puma (infanticide). 867 455 146-176 190 Mother I.D. F70 F3 F3 F3 F72 F7 F7 F7 F25 F25 F93 Unm.F �Appendix A continued Puma I.D. Estimated Age at capture (days) M99 5 mo. Est. Birth date Sep-Oct08 M101 35 4-15-09 M102 35 4-15-09 F103 35 4-15-09 M105 38 5-7-09 F106 38 5-7-09 M107 34 5-25-09 F108 34 5-25-09 Est. survival span from 1st capture to fate or last monitor date 2-27-09 to 01-2010 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. 488 Unm.F 05-20-09 to 09-19-09 05-20-09 157 05-20-09 to 09-17-09 06-14-09 to 02-09-10 06-14-09 to 02-27-11 159 Radio-collared. Last location 4-22-09 on Paterson Mt. Died as 16-month old subadult in San Miguel Canyon. Probably killed by another puma. Radio-collared. Died; killed by puma M55 after he was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 09-04-09. Did not find evidence of M102 associated with deaths of siblings M101 and F103. But M102 probably died. Radio-collared. Died; killed by puma M55 after she was orphaned due to death of mother F16 by vehicle strike. Radio-collared. Lost contact after 02-09-10 due to shed collar. Not radio-collared at nursery; F75 returned to nursery during handling. Radio-collared later on 2-10-10. Lost contact due to shed collar 3-16 to 29-10. F106 dispersed from natal area and was photographed at 21 months old at camera and scent-rub station on east slope of Uncompahgre Plateau on 02-27-11. Not radio-collared; too small. Recaptured 2-24-10; not collared. Shed radiocollar at nursery; fastener failed. Recaptured and re-collared 2-24-10. Shed collar ~3-5-10. Dispersed from natal area. Killed by a puma hunter on the study area during TY2 on 11-29-11 at 18.1 months old. Not radio-collared; too small. Radio-collared. Lost contact after 5-4-10 (last live signal) possibly due to failed transmitter. Recaptured and re-radiocollared on 01-24-11. Independent subadult during 02-10-11 to 04-18-11. Lost contact after 04-18-11; he may have dispersed or radiocollar quit. Radio-collared. M115 died as a subadult (~20 mo. old) due to complications of a broken left foreleg (natural cause). Radio-collared. Lost contact after 5-14-10 (last live signal); shed collar found on 7-15-10 in the natal area. Killed by a puma hunter on the natal area in Beaver Creek, off the U.P. study area on 01-01-11 when he was 17 months old. Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. 06-28-09 to 02-24-10 06-28-09 to 03-05-10 278 275 661 241 553 M109 M112 34 145 5-25-09 8-31-09 06-28-09 05-04-10 528 595 M115 14 mo. Nov.-08 07-21-10 610 M117 6 mo. Aug.-09 02-05-10 to 01-01-11 518 P1016(M) 39 6-12-10 06-12-10 to 07-21-10 39 191 F16 F16 F16 F75 F75 F94 F94 F94 F70 F28 F119 F72 �Appendix A continued Puma I.D. Estimated Age at capture (days) P1017(M) 39 6-12-10 M120 30 M121 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 06-12-10 to 07-21-10 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 39 F72 6-28-10 07-28-10 to 12-02-10 526 30 6-28-10 273 M122 35 7-8-10 07-28-10 to 03-28-11 08-12-10 to 04-28-11 Not radio-collared. Monitored at nursery via mother’s GPS/VHF collar. Found dead at nursery due to infanticide by puma M32 on same day as our investigation of nursery. Radio-collared. Lost radio contact after 12-02-10. Killed by a puma hunter on his natal area on 12-06-11 when he was 17.2 months old. Radio-collared. Lost radio contact after 03-28-11. F104 F123 29 7-15-10 217 F124 29 7-15-10 M125 29 7-15-10 M126 28 08-08-10 08-13-10 to 02-17-11 08-13-10 to 02-16-11 08-13-10 to 02-01-11 09-05-10 to 01-08-12 M127 28 08-08-10 09-05-10 to 09-10-11 398 M128 28 08-08-10 198 F129 35 08-21-10 09-05-10 to 02-22-11 09-25-10 to 02-02-12 M130 35 08-21-10 09-25-10 to 02-02-12 M131 35 08-21-10 09-25-10 to 07-21-11 Radio-collared. Lost radio contact after 04-28-11. Tracks of 2 other siblings of M122 observed on 01-11-11 (neither cub marked). Radio-collared. Killed on 02-17-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Killed on 02-16-11 for depredation control on domestic elk by elk farm manager. Radio-collared. Killed on 02-01-11 for depredation control on domestic elk by Wildlife Services agent. Radio-collared. Lost radio contact after 03-17-11; shed his radiocollar at a mule deer cache. Dispersed from natal area. Killed by a puma hunter on 01-08-12 in Tuttle Draw WNW of Nucla, CO as 17-month-old subadult. Radio-collared. Lost radio contact after 07-01-11; shed his radiocollar about 07-01-11. Found dead 09-14-11 on natal area; killed by another puma on about 09-10-11 at age 13 months. Radio-collared. Lost radio contact after 02-22-11; radiocollar probably quit. Radio-collared. Fate unknown. Transmitter on mortality mode on 04-28-11. Unable to get to collar until 06-23-11 due to high spring run-off, by then the transmitter had quit. Survived to recapture on 02-02-12 at 17.4 months old, with sibling M131; neither handled due to dangerous trees. Radio-collared. Died of natural causes associated with injury to right shoulder during first move away from nursery about 10-23-10. Radio-collared. Lost contact after 07-21-11. Shed his radiocollar about 07-27-11. Survived to recapture on 02-0212 at 17.4 months old, with sibling F129; neither handled due to dangerous trees. 274 216 201 221 530 530 334 192 Mother I.D. F3 F3 F94 F94 F94 F118 F118 F118 F96 F96 F96 �Appendix A continued Puma I.D. Estimated Age at capture (days) F132 35 08-21-10 M134 ~18 mo. M139 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 09-25-10 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 35 ~June-09 12-14-10 to 06-10-11 731 36 04-18-11 05-24-11 to 07-29-11 102 F148 36 04-18-11 05-24-11 to 07-29-11 102 F140 ~5 mo. ~Aug.10 01-02-11 to 04-18-11 258 M141 ~5 mo. ~Aug.10 01-02-11 to 04-01-11 241 M142 ~5 mo. ~ 6 mo. 01-02-11 to 04-18-11 02-16-11 258 P1030 F147 ~7 mo. ~Aug.10 ~Aug.10 ~Sep.-10 04-21-11 to 07-31-11 315 F149 45 04-22-11 06-06-11 to 07-16-12 451 M150 525 08-31-09 02-07-11 to 04-11-11 588 M151 253 06-16-10 02-24-11 to 03-07-11 264 Not radio-collared. Too small for collar design. Fate unknown. Apparently died; not with F96 and siblings F129 and M130 on 02-02-12. Radiocollared as dependent large cub. Independent by about 03-28-11. Dead; killed for depredation control by Wildlife Services agent on 06-10-11. Radio-collared. Dead of infanticide and cannibalism along with sibling F148; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Dead of infanticide and cannibalism along with sibling M139; killed and eaten by female or subadult male puma about 07-29-11. Radio-collared. Lost contact. Shed first collar about 01-2411. Recaptured and re-collared on 04-01-11. Shed second collar after 04-18-11. Recaptured and re-collared 01-12-12 as 17-month-old subadult on natal range. Radio-collared. Lost contact; shed radiocollar about 03-2911. Recaptured, but could not be handled safely on 04-0111. Radio-collared. Lost contact after 04-18-11 due to shed collar. Struck by vehicle and killed on state highway 62 in Leopard Creek, south boundary of study area on 02-16-11. Radio-collared. Orphaned at about 12 months old when her mother F24 was killed by a male puma on 09-16-11. She ranged in her natal area until her radiocollar quit after 0412-12. Radio-collared. F149 (sibling of M161) was orphaned when her mother F23 was killed by a male puma on 06-06-12; she was 411 days (13.5 mo.) old. F149 dispersed from the natal area by 07-16-12 when she was 14.8 months old. Radio-collared. M151 was independent by 03-28-11 at 19 mo. old. He dispersed from the natal area by 04-11-11 at 19.5 mo. old. Contact lost after 04-11-11. Radio-collared. Lost contact after 03-07-11 (GPS location of mother F111 at shed collar of M151). 183 193 Mother I.D. F96 Unm. F F8 F8 Unk./ F28? Unk./ F28? Unk./ F28? Unk. F24 F23 F70 F111 �Appendix A continued Puma I.D. Estimated Age at capture (days) F152 271 06-16-10 M154 42 07-06-11 M155 42 07-06-11 M156 43 07-08-11 F157 40 08-18-11 F158 40 08-18-11 09-27-11 to 01-15-12 150 M159 40 08-18-11 09-27-11 to 12-01-11 105 M161 276 04-22-11 01-23-12 to 07-16-12 451 M162 183 07-25-11 01-25-12 to 06-11-12 322 M170 137 08-29-11 01-13-12 to 03-12-12 199 Est. Birth date Est. survival span from 1st capture to fate or last monitor date 03-14-11 to 07-31-12 Age to last monitor date alive or at death (days, birth to fate) Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death 776 08-16-11 to 09-21-11 08-16-11 to 09-25-11 08-20-11 to 09-05-11 09-27-11 to 01-15-12 77 Radio-collared. Lost contact after 03-21-11; shed collar. Recaptured 01-18-12; fit with GPS collar at 19 months old; currently (July 31, 2012) a 25-month-old adult ranging on her natal area (philopatric). Radio-collared. M154 probably died of starvation following natural death of his mother F135. Sibling M155 also died. Radio-collared. M155 died of starvation following death of his mother F135. Sibling M154 also died. Radio-collared. M156 shed the collar about 09-05-11. He was 59 days old. F157 with sibling F158 died of starvation following death of his mother F70 due to hunter harvest on 12-22-11. Cubs died 24 days after their mother died. The cubs were 150 days old. F158 with sibling F157 died of starvation following death of his mother F70 due to hunter harvest on 12-22-11. Cubs died 24 days after their mother died. The cubs were 150 days old. M159 probably died about 12-01-11 when he was located with his family (F70, siblings F157, F158). He was not located with them on 12-12-11 and was not observed with them on 12-13-11. He was 105 days old on 12-01-11. M161 (sibling of F149) was orphaned when his mother F23 was killed by a male puma on 06-06-12; he was 411 days (13.5 mo.) old. M161 dispersed from the natal area by 0629-12 when he was 14 months old. M162 probably was orphaned cub of non-marked adult female puma killed on Pinto Mesa 01-18-12. M162 died of starvation on 06-11-12 when he was 322 days (10.6 mo.) old. M170 died about 03-15-12 of unknown natural cause. He was 199 days (6.5 mo.) old. 81 56 150 194 Mother I.D. F93 F135 F135 F137 F70 F70 F70 F23 F171 �Appendix A continued Puma I.D. Estimated Age at capture (days) P1033 22 Est. Birth date 07-10-11 Est. survival span from 1st capture to fate or last monitor date NA Age to last monitor date alive or at death (days, birth to fate) 22 Status: Alive/Survived to subadult stage/ Lost contact/Disappeared/ Dead; Cause of death Mother I.D. Cub P1033 was offspring of F136. It died of predation, F136 probably killed by a puma or black bear in the nursery when about 22 days old, before researchers could examine the entire litter to sample and mark the cubs. a Cub F35 probably starved between 06-30-06 & 07-07-06 after the transmitter on the expandable collar got in its mouth. b Cub M42 died after being captured by dogs, probably from stress of capture associated with severe infection of laceration under right foreleg caused by expandable radiocollar. c Cub M56 was captured in association with F7 and her cubs M43 and M44. He may have been missed at the nursery when M43 and M44 were initially sampled and marked. d Cub M60 died probably of starvation. The expandable radiocollar was around the neck and right shoulder, probably restricted movement. 195 �Colorado Division of Parks and Wildlife July 2011 - June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3430 3003 2 Federal Aid Project No. W-204-R1 : : : : : : Division of Parks and Wildlife Mammals Research Predatory Mammals Conservation Cougar Demographics and Human Interactions Along the Urban-Exurban Front Range of Colorado Period Covered: July 1, 2011 - June 30, 2012 Author: M.W. Alldredge Personnel: M. Strauser, E. Newkirk, W. Moss, B. Kirby, P. Lundberg, E. Joyce, T. Eyk, J. Halseth, G. Coulombe, R. Platte, K. Blecha, K. Yeager, L. Nold, K. Griffin, D. Kilpatrick, M. Paulek, B. Karabensh, D. Wroe, M. Miller, F. Quartarone, M. Sirochman, L. Wolfe, J. Duetsch, C. Solohub, K. Cannon, J. Koehler, L. Rogstad, R. Dewalt, J. Murphy, D. Swanson, T. Schmidt, T. Howard, D. Freddy CPW; B. Posthumus, Jeffco Open Space; D. Hoerath, K. Grady, D. Morris, A. Hatfield Boulder County Open Space; H. Swanson, R. Hatfield, J. Reale Boulder Open Space and Mountain Parks; S. Oyler-McCance, USGS. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The use of telomeres as a method to determine the age structure of bear and cougar populations has continued to be examined. Further refinement of the age-to-length relationship for both species is warranted based on preliminary results. We have begun a Ph.D. project with the University of Wisconsin to examine telomeres in detail for bears. This project will also look at stable isotopes to examine foraging ecology and bear use of human food sources. We have also begun an M.S. project with the University of Wisconsin to examine stable isotopes for cougars relative to predation on domestic animals and cougar foraging ecology. Our principal research objective is to assess cougar population ecology, prey use, movements, and interactions with humans along the urban-exurban Front Range of Colorado. This year capture efforts focused on re-collaring previously collared cougars, and capturing previously unmarked independent age cougars and cubs. In addition to recollaring cougars we collared 6 new independent age cougars. Mortality was very high over the year with 14 mortalities for independent age cougars (predominantly human related, unknown causes and vehicle collisions) (Table 1). Home-range patterns remained consistent to previous years. The effectiveness of aversive conditioning is still showing mixed results, which is likely a factor of the opportunistic nature of cougars using urban environments and a lack of habituation to them. Removing caches does appear to be effective to get cougars to leave urban areas. Cougar/human interactions were minimal this year compared with previous years. Relocation of cougars 196 �as a management tool has had limited assessment, but given some success, still warrants further investigation. Mule deer are the predominant prey in cougar diets, although males will also utilize elk regularly. WILDLIFE RESEARCH REPORT COUGAR AND BEAR DEMOGRAPHICS AND HUMAN INTERACTIONS IN COLORADO MATHEW W. ALLDREDGE P.N. OBJECTIVE 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban Front Range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus), assessing diet composition and estimating population densities of cougars for the state of Colorado. SEGMENT OBJECTIVES Section A: Telomeres and Stable Isotopes 1. Evaluate the potential to develop a model for estimating age of bears and cougars based on telomere length. 2. Determine diet composition of bears and cougars using stable isotopes. Section B: Front Range cougars 3. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. 4. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets. 5. Continue to assess relocation of cougars as a practical management tool. 6. Assess cougar predation rates and diet composition based on GPS cluster data. 7. Model movement data of cougars to understand how cougars are responding to environmental variables. 8. Develop non-invasive mark-recapture techniques to estimate cougar population size. SECTION A: BEAR AND COUGAR TELOMERES AND STABLE ISOTOPES BY M. ALLDREDGE OVERVIEW Understanding the age structure of a population is very useful to managers, especially for hunted populations. Age structure can provide indications about the appropriateness of current harvest levels, changes that may need to occur in harvest, and the general health of a population. Typical approaches involve estimating age structure based on sampling harvested animals and obtaining ages based on tooth wear and replacement characteristics or from analyzing tooth annuli. Recently a new approach has been developed for some species that estimates the age of animals based on examining the length of telomeres in relation to the age of the animals. Telomeres are repetitive DNA sequences that cap the ends of eukaryotic chromosomes, whose nucleotide sequence (T2AG3)n is highly conserved across vertebrate species (Meyne et al. 1989). During 197 �each cell cycle telomeric repeats are lost because DNA polymerase is unable to completely replicate the 3’ end of linear DNA (Watson 1972). Thus, telomeres progressively shorten with each cell division; past research has demonstrated age-related telomere attrition in a variety of laboratory and wild species and has correlated telomere length with individual age (e.g. Hausmann et al. 2003, Hemann and Greider 2000). Using real-time quantitative polymerase chain reaction (Q-PCR; Cawthon 2002), we have demonstrated the potential for quantifying telomere length for black bears of known-age in Colorado (Alldredge 2010). Understanding diet composition and foraging ecology of bears is also useful to managers, especially in urban areas as bears continually interact with humans and human derived food sources. The dynamics of this interaction and the extent to which bears utilize human food sources is largely unknown. The use of stable isotope analysis is one approach to understanding the amount and timing of utilization of various food sources within a bear’s diet. Examining different tissue types from bears can explain patterns of use for various food sources and will provide managers a better understanding of this problem at a population level. We have initiated a graduate study with the University of Wisconsin and Wisconsin Department of Natural Resources to develop methods of identifying population age structure using telomeres and examining diet composition and foraging ecology using stable isotopes for bears. See attached study plan for a complete project overview and objectives (Appendix I). During 2011 we collected blood, tissue, hair, and bone samples from 400 bears across the state. These bears were either nuisance bears or hunter harvested bears. Samples from these bears are being utilized for both the telomere and stable isotope components of this project. Preliminary assessments indicate high genetic quality from samples for use in the telomere work. Initial data from stable isotope analyses indicate significant variation in δ13C and δ15N (Figure 1) among bears which suggests that differentiation in diets based on stable isotope analysis will be possible. Additional work has also begun in collaboration with the University of Wisconsin to further examine stable isotope techniques for bears and cougars. This work is specifically designed to look at diet composition of bears within specific temporal windows relevant to current management issues. Similarly, stable isotope analyses for cougars is focused on identifying cougar predation on specific species guilds, identifying the use of small prey items, and determining factors associated with differences in prey utilization. For a complete project description and objectives see the attached study plan (Appendix II). As an initial step to investigate the utility of using stable isotopes to assess cougar diets we collected hair samples from prey species found at cougar kills. Additionally hair samples were collected from domestic animals (llamas, goats, cats, dogs, etc.) that could potentially be preyed on by cougars. Stable isotope analysis has been done on these prey items and initial findings suggest that examining prey by species guilds does result in significant differences in δ13C and δ15N content (Figure 2). A final component of this project is to develop hair growth curves for black bears, assess how meat is assimilated into tissues (hair) and specifically examine proportional contributions of meat in bear diets in the state of Colorado (See Appendix II for further details). Part of this work will involve working with captive bears at the Wild Animal Sanctuary located in Keensburg, CO. This will involve adding Rhodamine B to their food once per month and pulling hair. The Rhodamine B will appear as a UV mark on the hair and provide a time stamp so that growth curves for hair can be developed. Diets will also be controlled so that assimilation of various diet components into the consumer’s tissues can be assessed with known controls. Finally, hair samples will be collected from harvested bears across the state. These 198 �hairs will then be segmented into time periods based on the growth curves and examined for time specific diet composition. SECTION B: FRONT RANGE COUGARS BY M. ALLDREDGE INTRODUCTION We have continued the cougar/human interaction study on the Front Range of Colorado. Given that cougars currently coexist with humans within urban/exurban areas along Colorado’s Front Range, varying levels of cougar-human interaction are inevitable. The CPW is charged with the management of cougars, with management options ranging from minimal cougar population management, to dealing only with direct cougar-human incidents, to attempted extermination of cougars along the human/cougar spatial interface. Neither inaction nor extermination represent practical options nor would the majority of the human population agree with these strategies. In the 2005 survey of public opinions and perceptions of cougar issues, 96% of the respondents agreed that it was important to know cougars exist in Colorado, and 93% thought it was important that they exist for future generations (CPW, unpublished data). There is a growing voice from the public that CPW do more to mitigate potential conflicts, and the leadership of CPW has requested that research efforts be conducted to help minimize future human/cougar conflicts. In order to meet these goals CPW believes it is necessary to directly test management prescriptions in terms of desired cougar population and individual levels of response. Long-term study objectives for the Front Range Cougar Research project involve directly testing management responses of cougars at various levels of human interaction, as well as collecting basic information about demographics, movement, habitat use, and prey selection. The Cougar Management Guidelines Working Group (CMGWG) (2005) recommended that part of determining the level of interaction or risk between cougars and humans is to evaluate cougar behavior on a spectrum from natural, to habituated, to overly familiar, to nuisance, to dangerous. The CMGWG (2005) clearly stated that there is no scientific evidence to indicate that cougar habituation to humans affects the risk of attack. As a continuation from the pilot study efforts, we have continued to assess the effectiveness of aversive conditioning as a method to alter interaction rates between cougars and humans. We also continue to monitor relocated cougars to determine the effectiveness of relocation as a management tool. The use of GPS collars obtaining up to 8 locations per day also allows for a detailed examination of demographic rates. We are monitoring cougars that utilize natural habitats and cougars that use a mixture of natural and urban habitats. This allows for an assessment of demographic rates, movement patterns, and habitat use among cougars utilizing these two habitat configurations. We have also begun monitoring cubs (approximately 6 months of age or older), primarily to determine survival but potentially to understand movement patterns and dispersal. The use of GPS collars also allows us to study predator-prey relationships and diet composition. GPS locations are divided into selection sets based on the likelihood of the set of locations (clusters) representing a kill site. A random sample of these clusters is investigated to determine what a cougar was doing at the site, and whether or not it represents a kill site. Kill sites are thoroughly investigated to determine as much information as possible about what was killed at the site. STUDY AREA The original pilot study was conducted in Boulder and Jefferson counties, in an area near Interstate 70 north to approximately Lyons, Colorado, which was also a likely area for addressing long- 199 �term research objectives (see Figure 3). The study area for the long term study includes this original area but was expanded south to highway 285. Research efforts in the additional southern portion are generally limited to capturing cougars that are in the urban setting and/or have interacted directly with humans. The study area is comprised of many land ownerships, including private, Boulder city, Boulder County, Jefferson County, and state and federally owned lands. Therefore, we have been directly involved with Boulder city and Boulder and Jefferson county governments to obtain agreements from these entities on conduct of research and protocols for dealing with potential human/cougar interactions prior to conducting any research efforts. We have also acquired permission to access numerous private properties to investigate cougar clusters and to trap cougars. METHODS Baiting, using deer and elk carcasses, has been conducted throughout the year, with a focus on areas that do not allow the use of hounds. Bait sites are monitored using digital trail cameras to determine bait site activity. Cage traps were generally used for capture when cougars removed the bait and cached it. Beginning in November, 2011 and continuing through February, 2012, hounds were also used when snow conditions were favorable to capture cougars. Snares were used in situations where hounds could not be used and cougars would not enter cage traps. Captured cougars were anesthetized, monitored for vital signs, aged, measured, and ear-tagged. All independent cougars (> 18 months old) were fitted with GPS collars. All cubs greater than 15 kg (approximately 6 months or older) were ear-tagged with 22 g ear-tag VHF transmitters or 22g ear-tag ptt Argos transmitters. When cougars interact with humans and elicit a response from CPW District Wildlife Managers (DWMs) they are potential candidates for aversive conditioning. Most incidents prompting response from a DWM occur in neighborhoods, where relocating the cougar is necessary prior to any application of an aversive conditioning treatment. For these situations, all treatments require the relocation of the offending individual to an adjacent open-space property or similar area. In other situations a cougar can be directly conditioned or chased from the area without relocation. Initial data suggested aversive conditioning had mixed results. Here we compare cougar behavior between situations when the cougar is undetected in urban areas versus situations when they are detected and hazed or their kills are removed. Interactions have been limited so we have limited data to assess these activities. Cougars are only relocated for management purposes, generally in conjunction with human conflict or livestock depredation. Research cougars that have been collared for other purposes of the study may also become part of the relocation group if their levels of human interaction warrant such a management action. Because only a few cougars are relocated each year, we collar and monitor all cougars that are relocated in the northeast region. Cougars are ear-tagged and fitted with a telemetry collar (VHF, or GPS collars may be used depending on the situation). Release area is critical to the success of any relocation, however, suitable relocation areas may be difficult to find. Such an area must be far enough from the problem area, have suitable prey, and be remote enough so that the individual will not be presented with problem opportunities at or near the release site. Understanding the minimum release distance that has a reasonable chance for relocation success is useful for both logistical reasons and to increase the number of potential release sites. We evaluated cougar diet composition by using GPS location data to identify likely kill sites. Characteristics of clusters of GPS locations representing cougar-killed ungulate sites (Anderson and Lindzey 2003, Logan 2005) were used to develop a standard algorithm to group GPS points together, to provide a sound sampling frame from which statistical inference could be made about clusters that are not physically investigated. GPS collars collected locations 7 to 8 times/day to reflect time periods when cougars are both active and inactive. 200 �The clustering routine was designed to identify clusters in five unique selection sets (S1, S2,…, S5) in order to identify clusters containing two or more points, those that contained missing GPS locations, and those that were represented by single points. S1 clusters consist of multiple GPS locations with a 4 day window and within 200 m, while other sets are single points close together in time within varying distance bands. The clustering algorithm was written in Visual Basic and was designed to run within ARCGIS (Alldredge and Schuette, CDOW unpubl. data 2006). The widths of the spatial and temporal sampling windows were user specified, in order to meet multiple applications and research needs. This also enabled adjustment of the sampling frames to improve cluster specifications as needed. We used the following protocol to investigate cougar GPS clusters in the field. For S1 clusters, we investigated each cougar GPS location in the cluster by spiraling out a minimum of 20 m from the GPS waypoint while using the GPS unit as a guide, and visually inspecting overlapping view fields in the area for prey remains. Normally, this was sufficient to detect prey remains and other cougar sign (e.g., tracks, beds, toilets) associated with cougar. If prey remains were not detected within 20 m radius of the cluster waypoints, then we expanded our searches to a minimum of 50 m radius around each waypoint. For S2 through S5 clusters, we went to each cougar GPS location and spiraled out 50 m around each waypoint, while using the GPS unit as a guide. Depending on the number of locations, topography, and vegetation type and density, we spent a minimum of 1 hour and up to 3 hours per cluster to judge whether the cluster was a kill site. Kevin Blecha is currently conducting his M.S. research on predator-prey dynamics related to the sampling described above. He is specifically looking at predator-prey relationships relative to various habitat types and levels of human density across the landscape. An assessment of prey availability or reliability is also being made through the use of camera traps within these habitat types and levels of human density. Finally, an assessment of cougar use on domestic animals (livestock and pets) is being made (see Appendix III for more details). Joe Halseth has also initiated a study to examine prey selection and kill site dynamics with regard to conspecifics and scavenging. Kill sites are being investigated within 24 hours of the kill to determine prey species, to place cameras and to sample ungulates for age and to test for CWD. Some work has indicated that cougars may select for CWD positive animals but sample sizes have been limited. We intend to sample a large number of ungulates and address this topic further. Additionally we have documented significant amounts of prey sharing among cougars and significant amounts of scavenging from cougar kills. Understanding these kill site dynamics will provide information on kill rates, consumption rates and intra/interspecific interactions (see Appendix IV for more details). We have also initiated two additional graduate projects at CSU to focus on other aspects of the Front Range Cougar Study. First we have begun a Ph.D. project with Mevin Hooten at CSU through the statistics department to develop movement models and examine cougar GPS data for various movement patterns relative to roads, human density/activity, and other landscape/environmental features (Appendix V). The other project that we have begun is a M.S. project with Bill Kendall at CSU through the Fish, Wildlife, and Conservation Biology Department to examine techniques to develop non-invasive population estimation methodology for cougars (Appendix VI). RESULTS AND DISCUSSION Collared cougars from the previous year were captured and re-collared to replace exhausted batteries throughout the year. An additional 6 independent age cougars were also captured and collared during the year (Table 1). Currently there are 18 independent age cougars in the study with functioning GPS collars. 201 �Home ranges for collared cougars have been determined using minimum convex polygons (MCP) to depict the general pattern of use and potential overlap, but likely over-represent the actual area used by an individual. Home ranges exhibit similar patterns to previous years (Figures 4 and 5), being fairly linear in a north-south direction. Adult male home ranges (Figure 6) were much larger than adult female home ranges (Figure 7). Subadult male home ranges were smaller than adult male home ranges, but were also characterized by large movements and significant overlap with adults. Female home ranges were smaller with sizes between 80 and 120 km2. Female home ranges also had significant overlap, especially among related individuals. We have also seen significant long-range movements and dispersals (Figure 8). Long-range movements are significant movements outside of a cougar’s typical home range with the individual returning to the original area. Dispersals are similar movements but the individual does not return to its original area. There were a total of 14 mortalities for adult collared cougars during the 2011-12 year (Table 1). Causes of death included vehicle collision (3), unknown sources (5), hunting (1), intraspecific (1) and management or landowner related death (4). Cougar-human interaction was comparable to the previous year, which appears to be less interaction than in the first years of the study. This gives us little opportunity to test aversive conditioning techniques. Given the minimal response to aversive conditioning, we are altering our methods of examining it as a management tool. We will now have managers aversively condition any cougar that they encounter interacting with humans and that warrants such action. We will then compare the cougar’s responses to this aversive conditioning to events where the cougar was in the same situation but was undetected by humans and therefore not aversively conditioned. Relocation of cougars is also a management technique that we have evaluated in the past and has shown mixed results relative to age, sex and relocation distance. The NE region has expressed renewed interest in this and we will begin pilot work to investigate this in more detail. We will evaluate relocation distance relative to Directive W2 and the distance recommendations made for management as well as some more long-distance relocations. As this proceeds we will develop a more detailed study to thoroughly investigate cougar relocation parameters. From Aug 1, 2008 through September 1, 2012 we have visited ~3700 clusters (S1-S5 types). However, not all of these clusters were considered to be random samples, and thus preliminary inferences have only been drawn from this subset. Starting in January, 130 cameras were deployed in random locations representing the range of habitat types and human densities. Cameras have been checked as needed and results appear to be promising with regard to the number of species that have been detected and the perfromance of the cameras. For a detailed summary of the predator-prey component of the project, prelimary results and prey composition in cougar diets see Appendix III. The prey selection and kill site dynamics study was initiated in January (see Appendix IV for study objectives and methods). To date, we have collected 50 individual samples from deer killed by cougars and tested these for CWD. A small proportion of these have been positive for CWD. We have investigated numerous potential kill sites and placed cameras on 68 fresh kill sites to document the activity. We have documented 5 occasions when multiple cougars shared a kill and several scavenging events. Many scavenging events occur after the cougar has consumed the prey and has left. Other scavenging events have occurred while the cougar was still consuming the prey item, including cases where bears have usurped the prey item killed by the cougar. Starting in November we began investigating snow tracking and lures as potential techniques to estimate cougar abundance. Snow tracking proved to be very difficult because there was limited snow 202 �throughout the winter and snow conditions were poor. When snow tracking was feasible tracks of collared cougars were followed and samples (primarily hair) were collected. This approach is highly dependent on environmental conditions and therefore may not be broadly applicable. Efforts documented in the literature to lure cougars to specific locations and capture and individual with either a photograph or genetic sample have been limited and relatively unsuccessful. We have begun to rigorously test various options to lure cougars to specific locations and extract genetic samples. One option that has not been tested in other studies is the use of game calls to attract cougars. We placed 4 different types of sites at random locations to determine which types of lures or combinations of lures (bait, bait and scent, bait and call, bait, scent and call) would be the most reliable method of attracting cougars. We found that calls were significantly more effective (21 detections at sites with calls compared to 2 detections at sites without calls) at attracting cougars to a site (see Appendix VI for a detailed summary). Although we were relatively effective at luring cougars to a specific location with calls, we were not successful in extracting genetic samples at these locations. Cougars appeared to ignore scratch pads and were hesitant to take any meat reward left at the site. Cougars did seem interested in the calls and on several occasions investigated the call or stole the call from the site. In the coming year we will investigate methods of extracting genetic samples from cougars approaching the call, likely this will involve barbed wire as a hair snag (see Appendix VI for a summary and study plan for continued research). Throughout the year we have also been analyzing cougar GPS collar data to examine habitat use and movement patterns. Much of this has been geared towards the development of new statistical methods or refinement of statistical methods. A resource selection function (RSF) was run and we found that cougars are selecting for forest and shrub cover types and selecting against agriculture, city, and bare cover types. Additionally, we found little evidence to suggest cougars are avoiding roads. Finally, we have been working on a continuous-time discrete-space model of cougar movement. For more details of this approach see Appendix V. SUMMARY The use of telomeres as a method to determine the age structure of bear and cougar populations is promising and will be investigated further in the coming year. Further refinement of the age-to-length relationship for both species is warranted. In addition to this, length relationships relative to genetic relatedness and individual stressors will give further insight into interpreting results from future data. We will also be investigating the effects of hibernation on telomere length using both captive and wild bears. The use of stable isotopes from bears and cougars is beginning to show some very interesting results. Examining stable isotopes from various bear tissue types will help elucidate temporal patterns in diet composition, including the use of human foods by bears. It has also become clear that stable isotopes will be a useful tool in examining cougar diets, especially in the use of small prey items that are likely overlooked with other traditional techniques. In addition to re-collaring previously collared cougars, an additional 6 independent age cougars were collared during the year. Mortality remained high over the year with 14 cougars dying during the year. Home-range patterns remained consistent to previous years. The effectiveness of aversive conditioning is still showing mixed results, which is likely a factor of the opportunistic nature of cougars using urban environments and a lack of habituation to them. Relocation of cougars as a management tool has had limited assessment, but given some success, still warrants further investigation. Mule deer are the 203 �predominant prey in cougar diets, although males also utilize elk regularly. We will continue to assess predator-prey dynamics, population estimation techniques, and movement patters during the coming year. LITERATURE CITED Alldredge, M.W. 2007. Cougar demographics and human interactions along the urban-exurban front range of Colorado. Wildlife Research Report July: 153-202. Colorado Division of Wildlife, Fort Collins, USA. Anderson, C.R., and F.G. Lindzey. 2003. Estimating cougar predation rates from GPS location clusters. Journal of Wildlife Management 67:307-316. Boutin-Ganache, I., M. Raposo, M. Raymond, and C. F. Deschepper. 2001. M13-tailed primers improve the readability and usability of microsatellite analyses performed with two different allele-sizing methods. Biotechniques, 31:25-28. Cawthon, R. M. 2002. Telomere measurement by quantitative PCR. Nucleic Acids Research 30:e47. Cougar Management Guidelines Working Group. 2005. Cougar Management Guidelines, 1sted. WildFutures, Bainbridge Island, Washington, USA. Ernest, H. B., M. C. T. Penedo, B. P. May, M. Syvanen, and W. M. Boyce. 2000. Molecular tracking of mountain lions in the Yosemite Valey region in California: genetic analysis using microsatellites and faecal DNA. Molecular Ecology 9:433-441. Harrison, R. L., P. B. S. Clarke, and C. M. Clarke. 2004. 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Shcaffer, J. F. Tomlin, M. K. Hutton, and S. J. O’Brien. 1999. A genetic linkage map of microsatellites in the domestic cat (Felis catus). Genomics 57:9-23. Meyne, J, R. L. Ratliff, and R. K. Moyzis. 1989. Conservation of the human telomere sequence (TTAGGG)n among vertebrates. Proceedings of the National Academy of Sciences 86: 7049-7053. Nakagawa, S., N.J. Gemmell, and T. Burke. 2004. Measuring vertebrate telomeres: applications and limitations. Molecular Ecology 13:2523-2533. Sinclair, E. A., E. L. Swenson, M. L. Wolfe, D. C. Choate, B. Bates, and K. A. Crandall. 2001. Gene flow estimates in Utah’s cougars imply management beyond Utah. Animal Conservation 4:257-264. Smith, D. A., K. Ralls, B. L. Cypher, and J. E. Maldonado. 2005. Assessment of scat-detection dog surveys to determine kit fox distribution. Wildlife Society Bulletin 33:897-904. Taberlet, P., and J. Bouvet. 1992. Bear conservation genetics. Nature 358:197. Watson, J.D. 1972. Origin of concatameric T4 DNA. Nature-New Biology 239:197-201. Prepared by Mathew W. Alldredge, Wildlife Researcher 204 �Table 1: Capture history, aversive conditioning treatments and current status of all independent age cougars captured as part of the Front Range cougar study. Cougar ID AM02 Sex Age Date Location Occurrence Capture Release Loc M On-site White Ranch On-site Lindsey Centennial Cone NA Beanbag NA Beanbag Beanbag M Hounds Hounds Hounds On-site On-site On-site NA NA NA AF03 AF01 F F AM05 M Cage Cage Hounds Free-dart Hounds Hounds On-site On-site On-site On-site On-site On-site NA NA NA NA NA NA AM07 M Hounds On-site NA AF08 F 1.5 3 Hounds Cage On-site On-site NA NA AM09 M On-site NA F 12/28/07 Heil Valley Ranch 12/27/08 Hwy 34 (mile 70) 1/15/08 Apex Open Space Hounds AF10 1.5 2.5 7 Baiting Capture effort Intraspecific mortality Baiting Livestock depredation Replace Collar Seen in town Killed deer in town Punctured intestine Capture effort Replace Collar Replace Collar Hunter Deer kill Deer kill Replace Collar Deer kill Capture effort Replace collar Roadkill Capture effort Roadkill Capture effort Deer kill-remove collar Capture effort Roadkill Deer Kill Cage Cage Hounds Free-dart Cage AM06 Lacey Prop. White Ranch Coal Creek White Ranch Eldorado Springs Magnolia/Flagstaff South Boulder North Boulder Boulder Canyon Heil Valley Ranch Heil Valley Ranch Reynolds Ranch White Ranch Flagstaff Table Mesa White Ranch BCOS Lindsey White Ranch White Ranch Golden Heil Valley Ranch Highway 7 Heil Valley Ranch West Horsetooth On-site On-site M 6/14/07 1/10/08 2/9/08 7/14/07 10/17/07 4/29/08 5/5/08 8/4/08 2/24/09 11/21/07 12/30/08 2/2/10 2/15/10 11/29/07 12/17/07 12/15/10 3/12/12 12/19/07 12/4/09 4/4/10 12/26/07 4/19/08 12/26/07 6/18/09 Cage Hounds AM04 1 1.5 1.5 7 7 8 8 8 9 5 6 7 7 4 2 4.5 Conditionin g NA NA Cage On-site NA 2 4 5 1.5 205 Status Alive Alive Dead Alive Alive Alive Alive Alive Dead Alive Alive Alive Dead Alive Alive Alive Alive Alive Alive Dead Alive Dead Alive Alive Alive Dead Alive �AF19 F 8+ 8+ 8+ AF11 F 1.5 AM20 M 4 AF15 F 6 7 AF17 F 8-9 9+ 9+ AF12 F 2 AM13 M 2 3 AM14 M 2 3 4.5 4-5 2/13/08 3/4/08 3/18/09 4/13/09 1/20/09 11/5/10 Roadkill Capture effort Deer Kill Deer Kill Deer Kill Roadkill 3/18/08 4/2/09 3/25/10 2/4/11 2/2/12 3/29/08 5/20/08 5/8/08 I-70 Heil Valley Ranch North Boulder Left Hand Canyon Dowe Flats Foothills Hwy, N. Boulder South Table Mesa US-40/Empire White Ranch West of White Ranch Coffin Top Hall Ranch Coffin Tip Hall Ranch Longmont Dam Rd Sugarloaf Four-mile Canyon N. Boulder 5/29/08 2/13/09 5/8/08 12/17/08 12/17/09 3/27/12 5/15/08 5/20/08 4/14/09 2/16/10 6/22/11 11/9/11 N. Boulder N. Boulder Sugarloaf Heil Valley Ranch Heil Valley Ranch Hall Ranch South Boulder South Boulder Rollins Pass Left Hand Canyon Allenspark Hwy 72 3/5/08 8/20/08 3/6/08 5/18/08 On-site Heil Valley Ranch Heil Valley Ranch On-site NA Beanbag NA NA Deer Kill Cage Roadkill Capture effort Hounds Livestock Depredation Shot On-site NA On-site NA Capture effort Replace Collar Replace Collar Deer Kill Deer Kill Pet depredation Unknown mortality Deer Kill Hounds Hounds Hounds Snare Snare Cage On-site On-site On-site On-site On-site Within 1 mile NA NA NA NA NA Beanbag Cage Beanbag Livestock depredation Deer Kill Livestock depredation Replace Collar Replace Collar Detected by camera Seen under deck Deer kill Replace Collar Replace Collar Elk Kill Raccoon Kill Cage Snare Cage Hounds Hounds US Forest Boulder Canyon Near Ward None On-site On-site On-site Free-dart Free-dart Hounds Hounds Cage Free-dart Lindsey West of Rollinsville On-site On-site On-site On-site None Beanbag NA NA NA NA 206 Hounds Cage Cage Cage Beanbag Beanbag NA NA Dead Alive Alive Alive Alive Dead Alive Dead Alive Dead Alive Alive Alive Alive Alive Alive Dead Alive Alive Dead Alive Alive Alive Alive Alive Alive Alive Alive Alive Alive �F 4-5 1.5 AM18 M 2.5 3.5 4.5 5.5 1.5 AF16 F 3 AF45 F 5 AF40 F AF24 F 1.5 1.5 2.5 4-5 10+ AM31 M 1.5 AF37 F 2.5 1.5 AM21* M AF32 F AF34 1.5 2 1.5 3.5 3.5 12/4/11 12/5/08 3/18/09 1/4/10 12/31/10 12/28/11 2/13/12 12/24/08 3/14/09 12/29/08 3/20/09 1/2/09 11/24/10 Allenspark Heil Valley Ranch N. Boulder Heil Valley Ranch Hall Ranch Hall Ranch W of Hall Ranch Evergreen Evergreen Evergreen Evergreen Gold Hill N.Boulder 1/27/09 1/28/09 2/22/10 3/4/12 2/12/09 2/25/09 4/4/09 5/31/09 12/31/08 3/29-09 2/16/10 12/31/08 8/11/09 8/29/09 3/???/10 9/28/09 11/28/10 12/1/10 9/23/11 White Ranch White Ranch White Ranch Idaho Springs North Boulder Hwy 7 North Boulder North Boulder Evergreen Conifer Douglas, WY Evergreen I-70 N. Boulder Loveland Indian Hills Golden Golden Green Mtn. Res. Shot/depredation Capture effort Deer kill Replace Collar Replace Collar Replace Collar Unknown mortality Deer kill Livestock depredation Deer Kill Livestock depredation Deer kill Euthanized/Lisa Wolfe Capture effort Replace Collar Replace Collar Fawn Kill Deer Kill Replace Collar Raccoon Kill Encounter Chicken coop Livestock depredation Hunter Chicken coop Roadkill Encounter Livestock depredation Livestock depredation In neighborhood In neighborhood Found dead 207 Hounds Cage Hounds Hounds Hounds On-site Heil Valley Ranch On-site On-site On-site NA Beanbag NA NA NA Cage Cage Snare Cage Cage Mt. Evans SWA None Flying J Open Space Mt. Evans SWA On-site None Hounds Hounds Snare Snare Cage Hounds Free-dart Shot Hounds Cage On-site On-site On-site On-site Hall Ranch On-site Heil Valley Ranch NA NA NA NA None NA None On-site Mt. Evans SWA None None Free-dart On-site None Free-dart Ward None Cage Free-dart Cage Within 1 mile White Ranch Radium None None None None Beanbag NA NA Dead Alive Alive Alive Alive Alive Dead Alive Dead Alive Alive Alive Dead Alive Alive Alive Alive Alive Alive Alive Dead Alive Alive Dead Alive Dead Alive Dead Alive Alive Alive Dead �AM46 M 2 AF50 AM44 F M 3 6 AM606 M 7-8 9 2 AF54 F 4 AF52 F AM51 AF56 AF55 M F F 4 5-6 1.5 1.5 4 AM53 M 4 AM60 AF58 M F 2 1.5 AF62 F 5 6 AF59 F 5 M 5 5-6 6 1 AM63 11/13/09 Evergreen Genesee 11/24/09 West of Boulder 12/15/09 White Ranch 3/18/10 White Ranch 3/20/11 White Ranch 5/30/12 SW of White Ranch 1/6/10 Boulder 9/23/11 Laporte 1/14/10 White Ranch 5/16/11 White Ranch 1/28/10 3/24/11 1/28/10 2/22/10 2/23/10 3/13/10 3/13/10 3/3/11 3/29/10 4/4/10 6/3/10 4/13/10 4/13/11 12/10/11 4/22/10 Hall Ranch Hall Ranch Hall Ranch Conifer Conifer Conifer Genesee Medved property Walker Ranch Table Mesa Walker Ranch Walker Ranch Gross Dam Blue Jay/Jamestown 1/6/11 N. Boulder 12/29/11 Sunshine Canyon 3/6/12 NW of Boulder 9/22/10 Paradise Park 9/30/10 Elk kill Livestock depredation Deer kill Capture effort Replace collar Elk kill Shot/depredation Seen in town Shot killing goat Capture effort Deer Kill/Replace Collar Capture effort Deer Kill Capture effort Livestock depredation Livestock depredation Pet Depredation Elk Kill Shot/hunter Baiting Baiting Roadkill Elk Kill Baiting Non-target/released Deer Kill Cage Shot Cage Hounds Hounds Snare On-site None On-site On-site On-site On-site NA NA NA NA Free-dart MacGregor Ranch None Hounds Cage On-site On-site NA NA Hounds Cage Hounds Cage Cage Cage Cage On-site On-site On-site Mt. Evans SWA Mt. Evans SWA On-site NA NA NA Beanbag Beanbag Euthanized NA Cage Cage On-site On-site NA NA Cage Cage Cage Cage On-site On-site On-site On-site NA NA NA NA Deer Kill Deer Kill Unknown mortality Deer Kill Road Kill Cage Free-dart On-site On-site NA NA Cage White Ranch None 208 Alive Dead Alive Alive Alive Alive Dead Alive Dead Alive Alive Alive Alive Alive Alive Alive Dead Alive Dead Alive Alive Dead Alive Alive Alive Alive Alive Alive Dead Alive Dead �AF57 F 3 4-5 AF61 F AF64 F AM67 M 4-5 4-5 5 1.5 3-4 1.2 5 AF69 F Lacy Property JCOS Ralston Buttes 11/18/10 Flagstaff 3/2/11 Coal Creek Canyon 12/10/11 Gross Dam Rd 1/20/11 Heil Valley Ranch 7/19/12 N of Nugget Hill 12/16/10 White Ranch Baiting Replace Collar Snare Hounds On-site On-site NA NA Alive Alive Deer Kill Raccoon Kill Baiting Baiting Kill Baiting Free-dart Cage Snare Cage Snare Cage On-site Walker Ranch On-site On-site On-site On-site NA None NA NA NA NA Alive Alive Alive Alive Alive Alive Shot/Depredation Deer Kill Deer Kill Deer Kill Deer Kill Dog Kill Unknown mortality Snare Free-dart Free-dart Cage Cage Cage On-site Reynolds Ranch On-site On-site Reynolds Ranch NA None NA NA None 3 3/4/12 12/1/10 4/6/11 3/31/12 1/23/11 3/2/11 2/26/12 Dead Alive Alive Alive Alive Alive Dead AM70 M 2 3 4 5 4 3-4 4 5 1/27/11 12/23/11 2/6/11 5/2/12 3/6/11 10/28/11 2/23/11 3/7/12 Baiting Shot/hunter Baiting Unknown mortality Baiting Deer Kill Baiting Deer Kill Cage Hounds Snare On-site NA On-site NA Cage Cage Cage Snare On-site On-site On-site On-site NA NA NA NA Baiting Replace collar Baiting Deer Kill Road Kill Dumpsite Cage Hounds Cage Cage On-site On-site On-site On-site NA NA NA NA Cage On-site NA 1.5 2 4 2 AM71 M AM72 M AF73 F AM74 M AM76 M AF77 AM78 F M 2-3 3 5 2 AF79 F 4 11/3/10 2/4/12 Big Thompson N. Boulder N.Boulder/Town Wonderland Gold Hill Boulder Heights Buckhorn Rd Heil Valley Ranch Casper, WY Heil Valley Ranch Heil Valley Ranch Sunshine Canyon Four Mile Canyon White Ranch Golden Gate Canyon 3/6/11 Heil Valley Ranch 12/27/11 Heil Ranch 3/9/11 Morrison Mountain 3/18/11 W. Evergreen 5/12/11 Soda Creel/I-70 3/18/11 Mt. Evans 209 Alive Dead Alive Dead Alive Alive Alive Alive Alive Alive Alive Alive Dead Alive �4-5 1.7 5 2 3 1.5 2 1.5 1.5 4-5 4 1.5 2 2/17/12 3/18/11 Mt. Evans Mt. Evans Replace Collar Dumpsite Hounds Cage On-site On-site NA NA Alive Alive 4/9/11 5/4/12 2/4/12 7/20/12 3/13/12 2/29/12 11/18/11 12/7/11 10/14/11 1/11/12 Shield Park HOA S. Deer Creek Cotter Mine I-70 Gross Dam Rd. Golden Heil Ranch Hall Ranch N. Boulder White Ranch Sheep depredation Shot/depredation Capture effort Road Kill Collared Baiting Baiting Deer Kill Deer Kill Possible Intraspecific Cage Deer Creek Canyon None Hounds On-site NA Snare Cage Snare Cage Cage On-site On-site On-site On-site On-site NA NA NA NA NA Alive Dead Alive Dead Alive Alive Alive Alive Alive Dead 4/9/09 11/14/09 Lost Valley Ranch 10/20/09 8/19/11 New Mexico 5/7/10 3/22/11 8/25/11 6/23/12 Sunshine Canyon Rehab Found dead Rehab Shot/hunter Rehab Shot/hunter Rehab Road Kill Release Pike forest None Release Hermit Park NA Release Radium NA Release Wonderland NA AM80 M AM84 M AF91 F AF86* AF22 AF87 F F F AF88 F SW023 F 1 SW026 M SW107 M 1 3 1 AF995 F 1 2 210 Alive Dead Alive Dead Unkn Dead Alive Dead �Table 2: Capture history, aversive conditioning treatments and current status of all cougar cubs captured as part of the Front Range cougar study. Cougar ID AF35 Sex Age Mother Date Location Occurrence Capture Release Loc F 3 AF16 3 AF16 Cage Flying J Open Space AM30 M 8 AF01 Deer Kill Roadkill Deer Kill Starvation Deer Kill Flying J Open Space M Evergreen Evergreen Evergreen Evergreen S. Boulder Cage AM36 12/29/08 12/31/08 12/29/08 1/8/09 1/30/09 Cage On-site AM38 M 8 AF01 1/30/09 3/27/09 S. Boulder S. Boulder Deer Kill Encounter 3/30/09 S. Boulder Pet Depredation 4/9/09 Morrison Encounter 2/11/09 N. Boulder Deer Kill 6/15/09 N. Boulder Encounter Cage Freedart Freedart Freedart Freedart Freedart Shot Cage On-site NA Cage Freedart Freedart Shot Free- On-site Perforated intestine None On-site None Alive White Ranch None Dead Alive AM29 M 6 Euth. 12 10/23/09 Big Thompson Goat Depredation Baiting AM21* collared AM25 M 12 Unkn 3/25/09 Table Mesa M 12 Unkn 5/22/09 9/13/09 Indian Hills Deer Kill Raccoon AM41 M 12 Unkn 5/22/09 Indian Hills Deer Kill AM65 M 4-5 AF32 Indian Hills 11/28/10 Golden Encounter In Neighborhood 211 Conditioning Status On-site Lindsey Beanbag Alive Dead Alive Dead Alive Dead Alive Alive Centennial Cone None Alive None Euthanized Dead Hall Ranch None Alive Masonville Beanbag Alive Dead Alive Dead Alive Dead �AM66 M 4-5 AF32 11/28/10 Golden In Neighborhood AF68 AM83 AM85 AF86* collared F M M F 10 9 9 9 AF50 AF52 AF62 AF62 12/1/10 2/9/11 3/24/11 4/13/11 4/13/11 Recapture Deer Kill Deer Kill Baiting Baiting White Ranch Flagstaff Hall Ranch Walker Ranch Walker Ranch 212 dart Freedart Hounds Cage Cage Cage Snare White Ranch None Alive Radium On-site On-site On-site On-site None NA NA NA NA Alive Alive Alive Alive Alive Alive �Figure 1: Carbon and nitrogen in hair from 60 bears harvested in Colorado during the 2011 hunting season showing the variability in concentrations reflecting dietary differences. 213 �Figure 2: Carbon and nitrogen content in hair samples from cougar prey items found in the Front Range of Colorado. Prey items grouped into guilds demonstrates differences in carbon and nitrogen content based on similarities in prey species diet. 214 �Figure 3: Study area for the main Front Range cougar study where most capture effort and field work is conducted. 215 �Figure 4: MCP home-ranges for male cougars that have previously been collared but are no longer in the study because of mortality or dispersal. 216 �Figure 5: MCP home-ranges for female cougars that have previously been collared but are no longer in the study because of mortality or dispersal. 217 �Figure 6: MCP home-ranges for male cougars that are currently in the study and being monitored. 218 �Figure 7: MCP home-ranges for male cougars that are currently in the study and being monitored. 219 �Figure 8: Dispersal/movement paths for cougars collared within the study area but traveled large distances outside of the study area. 220 �APPENDIX I Front Range Cougar Research 2011-2012 & 2012-2013 SPATIO-TEMPORAL PATTERNS OF DIET AND TELOMERE LENGTH IN COLORADO BLACK BEARS UW-Wisconsin & Colorado Parks and Wildlife Becky Kirby Jonathan Pauli Mat Alldredge Research Proposal 221 �SPATIO-TEMPORAL PATTERNS OF DIET AND TELOMERE LENGTH IN COLORADO BLACK BEARS (Study Plan Draft for submission to CPW August 2012) Becky Kirby, Ph.D. student, UW-Madison Background and Need Diet and foraging ecology The effect of human-derived food on free-ranging wildlife populations is recognized as a growing problem across North America. This has been particularly evident among carnivore populations and especially related to human-wildlife conflict. In the past twenty years, American black bear (Ursus americanus) conflicts have expanded along the wildland-urban interface, and are generally attributed to access to human foods (Beckmann et al. 2008; Greenleaf et al. 2009). In Colorado, by the early 2000s, a third of bear mortalities resulted from conflicts with humans (Baruch-Mordo et al. 2008). Being opportunistic omnivores, black bears vary their food intake widely throughout seasons (Robbins et al. 2004) and can become habituated to human resources they encounter (McCarthy and Seavoy 1994; Beckman and Berger 2003), but reliance on such resources and subsequent effects on individual and population dynamics remains largely unknown. Bear-human conflicts in Colorado and bear population dynamics exhibit high geographical and temporal variation (Baruch-Mordo et al. 2008; Beston 2011). Whether increased conflicts are due to growing populations, or alternatively environmental-mediated behavioral changes, remains unknown; and without a thorough understanding of individual, environmental, and population characteristics that contribute to nuisance bears, effective management has proven difficult. As conflicts are predicted to continue to rise, multi-pronged approaches that quantify the influence of anthropogenic foods are needed, as well as those that can assess regional population trends. Stable isotope analysis has yielded significant contributions to wildlife ecology in the last several decades (Kelly 1999; Crawford et al. 2008); of particular interest to managers has been quantifying diet components of free-ranging vertebrates using carbon and nitrogen isotopes. Because corn and sugar utilize a distinct photosynthetic pathway from native plants in temperate North America, corn-dominated human food (waste and agriculture) exhibit distinct carbon (δ13C) values, which can be measured in consumer tissues (Jahren et al. 2006) (Figure 1). In addition, measuring nitrogen (δ15N) values can indicate trophic position and animal content in the diet; higher nitrogen values reflect higher trophic positions (Hobson and Welch 1992). Traditional diet reconstruction methods (such as scat or stomach content analyses) tend to underestimate highly digestible resources. Because diet analysis with stable isotopes uses the abundance of two elements (13C and 15N) it Figure 1. Illustration of carbon and nitrogen isotopic avoids this bias. Further, sampling tissues with different signatures of potential black bear diet sources. Bear tissues will exhibit signatures based upon their diet, metabolic rates allows for higher resolution of temporal which can be reconstructed using mixing models. patterns of resource use (Hilderbrand et al. 1996). Using isotopic mixing models, we can calculate the percent of diet obtained from native plants, heterotrophs and human-derived food items (Phillips et al. 2005). Recently, 13C and 15N have been employed attempting to discern bear reliance on human foods in Missoula, Montana and Yosemite, California. Although the study in Montana was unable to distinguish “wildland” from “urban” bears (Merkle et al. 2011), researchers in Yosemite were successful in using 222 �stable isotopes to differentiate management bears (conditioned to human food) from non-management bears (Hopkins et al. 2012). CPW (lead by Heather Johnson) is currently investigating bear behavior and habitat use as relates to nuisance bears. Our project will complement the work being conducted around Durango by assessing diet contributions across a broad spatial scale (the entire state), using stable isotope analysis and hunter-harvested animals. Aging and telomeres Quantifying the age structure of a population is central to understand its population growth rate and to forecast changes in population size. The age of bears, as well as other mammals, is typically determined by pulling a vestigial premolar and counting cementum annuli (Schroeder and Robb 2005). The estimated age from counts of cementum annuli is highly accurate, but requires the animal to be captured or harvested. With rising numbers of studies using noninvasive sampling for DNA analyses of hair, feather, and scat samples, an aging technique that could be applied to these samples would be desirable. Currently in Colorado a noninvasive hair-snare project is underway to estimate regional black bear densities. Consequently, a noninvasive aging technique would provide managers with the age structure of bears within Colorado and more power in modeling population trends and forecasting population growth. Recently developed in a few other species (e.g. Pauli et al. 2011), telomere length shows promise as such a molecular aging technique. Previous research has demonstrated age-related telomere attrition in a variety of species and has correlated telomere length with individual age (e.g. Hemann and Greider 2000, Haussmann et al. 2003, Pauli et al. 2011). Telomeres are repetitive DNA sequences that cap the ends of eukaryotic chromosomes, whose nucleotide sequence (T2AG3)n is highly conserved across vertebrate species (Meyne et al. 1989). During each cell cycle telomeric repeats are lost because DNA polymerase is unable to completely replicate the 3’ end of linear DNA (Watson 1972). Thus, telomeres progressively shorten with each cell division. Telomerase, a reverse transcriptase, counteracts this loss in the germline, but tends to be far less active in somatic cells; this activity seems to vary with body mass, with larger animals having less telomerase activity (Seluanov et al. 2007). Additionally, lifestyle-related activities, in particular oxidative stress, can affect telomere length negatively (von Zglinicki 2002). Using hair samples, Pauli et al. (2011) quantified telomere length via real-time quantitative polymerase chain reaction (Q-PCR) to age martens (Martes spp.). When accounting for a few covariates thought to influence telomere length (sex of the animal, size of the population, and geographic location), Pauli et al. (2011) found they could obtain accurate estimates of age class, and that age estimation via their model in fact exceeded those typically obtained from counts of cementum annuli. Thus, they concluded that quantification of telomere length could be a promising tool to age carnivores and estimate demographic structure for noninvasively collected hair samples (Pauli et al. 2011). Subsequently, Jon Pauli and Mat Alldredge explored telomere length as a possible age marker for black bears using bears of known-age in Colorado and Wyoming. They found a weak linear relationship with telomere length declining with increasing animal age (Pauli and Alldredge, personal communication). Although much variation existed, this relationship was deemed to be potentially useful for further exploration. Taking advantage of the availability of hunter-harvested and nuisance bear samples with known ages, both diet via stable isotopes and aging via telomere length can be explored, with the goal of assigning biologically meaningful age classes. Creating a reliable aging model would be aided by a deeper understanding of telomere dynamics and those biological covariates responsible for variation in rates of telomeric attrition. Telomere lengths and rates of attrition vary strongly between individuals and sexes of the same species, and inconsistently across vertebrate groups (Monaghan and Haussmann 2006). As they seem to reflect biological, rather than chronological age, understanding the factors that relate to telomere dynamics would enhance the 223 �development of an accurate model for aging and indicate which covariates are most influential. The vast majority of studies have focused on a single sampling in time (such as the hunter-harvested samples we are analyzing), and only a few studies have been conducted on free-ranging populations. Dunshea et al. (2011) recently called for more longitudinal studies to elucidate the factors that affect telomere dynamics. Thus, in order to rigorously investigate telomeres as an aging model for bears, further understanding of telomere attrition rates within individuals, not simply at a single time point, is required. Multiple factors could play a role in aging, and hence telomere shortening (Monaghan and Haussmann 2006). Some species exhibit sex differences in telomere attrition (though not consistently across species) (Barret and Richardson 2011), and body size is known to be correlated with telomerase activity (Seluanov et al. 2007). Additional lifestyle factors such as nutritional condition and diet have also been linked to aging in some species (e.g. Shi et al. 2007, Cassidy et al. 2010), which are frequently related to oxidative stress, a known agent of telomeric shortening (von Zglinicki 2002). Further, considerable effort has been spent to understand bear hibernation physiology (e.g. Hellgren 1998), which may also be an important factor in aging. During hibernation, bears experience a slower metabolic rate, which results in less cell turnover (Koizumi et al. 1992). However, oxidative stress also increases as part of this process of metabolic depression (Chauhan et al. 2002), and aging is known to be strongly negatively affected by oxidative stress (von Zglinicki 2002, Cattan et al. 2008). This presents a potentially interesting question regarding whether telomeric attrition rates would be accelerated or attenuated during hibernation. Given that studies have shown torpor and lowered body temperatures to be associated with increased longevity (Lyman et al. 1981; Turbill et al. 2011), one would expect hibernation to slow the rate of telomere shortening. Only one study to our knowledge has examined telomeric attrition rates within individuals utilizing a lowered metabolic rate, a laboratory experiment on Djungarian hamsters (Turbill et al. 2012). In this case, they manipulated the environmental conditions of the individuals, and found that telomeres in fact increased in length more in those hamsters that used torpor more frequently (due to telomerase activity), in particular at lower body temperatures (Turbill et al. 2012). However, bears have substantially different hibernation characteristics than smaller mammals, in that undergo less severe hypothermia, avoid bone loss, (McGee-Lawrence et al. 2008) and have minimal loss of muscle strength as well (Harlow et al. 2001). Understanding how hibernation and other life history tradeoffs affect telomere dynamics in black bears (Monaghan and Haussmann 2006) would augment their value as an age marker. To this end, we will work with collared wild and captive black bears on the Colorado Front Range, in addition to the hunter-harvested samples. We will investigate black bear diet and telomere length to assess characteristics of bears reliant on human foods, and investigate telomere dynamics with the intent to develop an aging model. Objectives 1. Quantify diet via stable isotopes in hunter-harvested and nuisance bears a. Examine relevant covariates (including age, sex, body condition, size, location, land use, distance to human development/agriculture, etc.) as related to stable isotope signatures of individuals b. Examine different tissue types to compare individual bear diet recently and averaged over a lifetime 2. Quantify telomere length in hunter-harvested bears a. Assess how biologically relevant covariates (as in Objective 1) are related to telomere length b. Model biologically relevant age classes as a function of telomere length and explore the potential of this model in aging noninvasively collected hair samples 3. Investigate individual telomere attrition rate longitudinally in wild and captive bears 224 �a. Determine telomeric attrition rates for individual free-ranging and captive bears in Colorado and examine longitudinal changes in telomere length in relation to attributes of hibernation and other relevant covariates including body condition, sex, and habitat use b. Use those most influential covariates to inform model building for Objective 2 Anticipated Benefits This project will yield increased understanding of factors involving black bear reliance on human food and complement CPW’s ongoing behavioral study of black bears around Durango. This study will also examine regional patterns of black bear diet on a broad spatial scale. Further, we will explore the potential of aging black bears via telomeres with the hope that it could be applied to noninvasively collected hair snares ongoing in the state. The ability to estimate age structure for the black bears within the state of Colorado would increase understanding of population trends. Finally, examining hibernation and other effects on telomeric attrition rates will be the first such study in a large mammal in the wild, and has potential applications to our understanding of aging generally, as well as informing an aging model. Approach Objectives 1 and 2: Conduct a broad spatial scale analysis of diet and telomere length in CO black bears Hunter-harvested and nuisance bears In 2011, we worked closely with District Managers to opportunistically collect samples from hunter-harvested and nuisance bears. When possible, District Managers collected four tissue samples from each bear: hair, whole blood, muscle tissue, and teeth. Hair, blood, and teeth are being analyzed with stable isotopes for diet; and hair and blood are also being utilized for DNA extraction for determination of telomere length. Muscle tissue will be preserved for future DNA extraction if necessary. Analyzing different tissue types with stable isotopes will allow us to ascertain diet in different snapshot windows of time. For black bears, blood represents recent diet (last 2-4 weeks), hair represents diet during the period of growth (May-Oct), and teeth (or bone) represent lifetime-accumulated diet (Hilderbrand et al. 1996). In August 2011, we presented our project design to District Managers and distributed one thousand collection kits to stations throughout the state with sampling instructions. Managers were asked to collect a few mls of whole blood (from body cavity, mouth, or vein), pull clumps of guard hair (with follicles intact), cut a small muscle sample (size of a dime), and pull a vestigial premolar (additional to the one pulled for aging). Samples were stored in the freezer until brought to Madison in December 2011. We received samples from about 400 individual bears with hair and teeth and muscle, and about half of those also had whole blood. Further, when available, nuisance bears that were tranquilized for Figure 2. Location of hunter-harvested samples collected in fall transport, or euthanized, were sampled in a similar 2012 manner. Nuisance bears will also be sampled in 2012 for comparison. Data collected included customer ID, sex, and zygomatic width (on a paper ruler). We will also have access to age and reproductive history (for females) obtained from the teeth sent by CPW to Matson’s laboratory, and GPS coordinates (about 300 of the harvests appear to have reasonable coordinates) (Figure 2). 225 �Diet samples and location-specific covariates We will collect potential diet samples (Table 1) from CO in summer/fall 2012. Table 1. Potential native Colorado bear diet items obtained from (Irwin and Hammond 1985; Raine and Kansas 1990; Baldwin and Bender 2009) Spring beauty (Claytonia Herbaceous lanceolata) Fireweed (Epilobium angustifolium) Glacier lily (Erythronium grandiflorum) Dandelions (Taraxacum spp.) Cow parsnip (Heracleum maximum) Grasses, sedges, rushes Hard mast Oak acorns (Quercus spp.) Berries Chokecherries (Prunus spp.) Blueberry (Vaccinium spp.) Currants (Ribes spp.) Buffaloberry (Sheperdia spp.) Mammals Elk (Cervus elaphus) Mule deer (Odecoileus hemionus) Small mammals (Rodentia, Lagomorpha) Ants (Camponotus spp., Formica Insects spp.) Yellowjackets/wasps (Vespidae spp.) We will obtain samples from four major regions (Northern Front Range, Southern Front Range, Southwest San Juan Mountains, and Piceance Basin in the Northwest). We will also opportunistically sample human food waste. In order to elucidate environmental covariates that might influence diet choices, we will obtain other relevant covariates from available CPW spatial layers and datasets, as well as National Landcover Datasets (NLCD) and other publically available datasets. Using location data provided by hunters, for those bears with GPS coordinates, we will extract covariates that measure human influence, such as land use, distance to human development and agriculture. Ultimately, we will examine patterns of isotopic signature and telomere length in relation to individuals and environmental covariates. Objective 3: Examine factors contributing to individual telomeric attrition rate Free-ranging bears Rates of telomere loss are often not constant with age (Hall et al. 2004), thus understanding the factors that contribute to these rates necessitates multiple samples from the same individuals. In order to examine individual telomeric attrition rate through time, we will work with bears on the Front Range that are being captured and tracked via GPS collars as a part of Mark Vieira’s population study in summer 2012. We will attempt to collar at least 8 adult black bears (preferentially focusing on females, but an even split between sexes is appropriate) on the Northern Front Range in Colorado. Gender and organ specific differences in telomeres have been found in other species (e.g. Cherif et al. 2003), and may exist in bears. Further, because of the potential cost of reproduction (Heidinger et al. 2012), and sex differences in hibernation and thus amount of oxidative damage (Beaulieu et al. 2011), females are of primary interest. Few telomere studies have followed individuals longitudinally, and none have been conducted on large mammals to our knowledge. As discussed earlier, telomere length can vary widely across individuals and species, and can be counteracted in high metabolic creatures (birds, bats) with high levels of telomerase (Munshi-South and Wilkinson 2010). In most mammals, telomerase activity decreases with age in somatic tissues, but animals that undergo physiological adaptations such as torpor, may counteract telomere shortening in other ways (Turbill et al. 2011). Thus, we will examine telomere length before, during, and after hibernation to estimate rate of change. We will obtain hair samples seasonally, 4 times a year for two years, in order to have replicate datasets and explore variation in weather covariates. Blood samples will be collected at first capture and subsequent den checks for stable isotope and body condition analyses (such as leptin, Spady et al. 2009), stable isotope, and telomeres. Capture procedures will principally follow the protocol approved for Heather Johnson’s Durango study (see Appendix A). 226 �To avoid disturbing bears within their dens multiple times, we will obtain pre- and posthibernation hair samples using a hair snag, requiring only a single visit to a den each winter. We will use an individual’s GPS data to place a hair snag and trail camera within its known range to obtain a hair sample prior to hibernation. If the identify of the individual is uncertain, we can confirm it by genotyping DNA extracted from the hair follicles (genotypes will already be known from Mark Vieira’s study). Hair snags will be repeated after emergence from the dens in the spring. Measuring hibernation physiology throughout the winter has proven difficult, and frequently is rather invasive, most methods requiring surgery. The majority of metabolic suppression in black bears appears to be independent of lowered core body temperature (Tøien et al. 2011). Also, core and surface body temperatures can differ greatly, possibly due to shivering thermogenesis for muscle maintenance (Harlow et al. 2004). Further, a recent study allowed heart rate monitoring through the year, and found individual differences (Laske et al. 2011). Heart rate then, rather than core body temperature may be a better proxy for metabolic rate. Since we do not currently have the capacity to measure these throughout the winter, the first winter we will use hibernation length as obtained from GPS collar data and ambient temperature as proxies for hibernation physiology. In subsequent winters, pending adequate funding, we will obtain collars with heart rate monitors (or retrofit the current collars) to use as an index of hibernation. Captive bears Most studies quantifying telomere attrition rates have been conducted in captivity. Here we will compare rates of telomere loss between captive and wild bears. If telomere dynamics prove to be similar, then captive studies may be representative of wild populations. However, it is well established that captive animals may undergo behavioral and physiological changes (e.g. Morato et al. 2001). We are fortunate to have access to a captive facility that houses black bears on the Front Range, The Wild Animal Sanctuary in Keenesburg, CO. We will work with 12 female bears, 2 each across a range of age classes if available. The facility houses about 70 black bears with relatively well-known histories, so selecting this subset should be possible. Using 2 bears each of similar age will allow for contrasts of telomere length differences within age class. Similar to wild caught bears, we will pull hair 4 times a year, and conduct a full workup while denning. Handling procedures will be the same as those for free-ranging black bears (see Appendix A), but we will not collar these bears, and likely trapping will be unnecessary as they are fairly tame. We will not have movement data on these bears, but being in captivity, their habitat and activity can be well estimated. For the captive bears, we will only include females in the study because males are sterilized, which may have unknown effects on aging. Analyses (all objectives) Stable isotope analysis Bear hair will have follicles clipped off and placed aside for DNA extraction. The remaining hair shaft will be rinsed three times with 2:1 chloroform: methanol solution to remove surface oils (Cryan et al. 2004), dried for 72 hours at 60°C, and homogenized with surgical scissors. Whole blood samples will be dried for 72 hours at 60°C, and homogenized with a spatula. Teeth will undergo collagen extraction by soaking in 32% HCl for 24 hours to remove biogenic carbonates, followed by drying at 60°C for one week, then freeze drying for three days, and homogenized in a ball mill (Mixer Mill MM200, Restch Inc. Newton, PA, USA) (Owen et al. 2011). Diet samples will also be dried for 72 hours at 60°C and homogenized in a ball mill. For 13C and 15N analysis, samples will be weighed, placed in tin capsules and submitted to the Stable Isotope Facility at the University of Wyoming to be analyzed with a Costech 4010 elemental analyzer attached to a Thermo Finnigan DeltaPLUS XP Continuous Flow Isotope Ratio Mass Spectrometer. Results will be provided as per mil (parts per thousand [‰]) ratios relative to the international standards of Peedee Belemnite (PDB; δ13C) and atmospheric nitrogen (AIR; δ15N) with calibrated internal laboratory standards. 227 �Telomere length analysis Blood and hair samples will be extracted with standard procedures using Qiagen Dneasy tissue extraction kit. We will quantify the relative length of telomeres using real-time quantitative polymerase chain reaction (Q-PCR) (Cawthon 2002). This approach has been found to be highly accurate (Cawthon 2002), in particular for within species comparison (Nakagawa et al. 2004). The method determines relative telomere length by comparing a DNA sample’s ratio of telomere repeat copy number (T) to single copy gene number (S) to that of an arbitrary reference DNA. Relative differences in telomere length between individuals then, is exhibited by contrasting the T/S ratio of one individual to that of another. Any single copy gene sequence can be employed for standardization, and we chose to use the single copy gene, 36B4, which was originally employed to develop this method for quantifying telomere length in humans (Cawthon 2002) and subsequently found to be highly suitable for a wide range of species, including black bears (Pauli et al. 2011). Data analysis By quantifying the isotopic signature in tissues of bear and that of diet sources, we can quantify the contribution of isotopically distinct items to the diet of the bear. To do this, we will employ isotope mixing models that use Bayesian statistics to quantify the proportional importance of each diet type to bears in the last month (blood), summer (May-Oct) (hair), and lifetime (tooth). Specifically, we will utilize the MixSIR models (Parnell et al. 2010; Layman et al. 2011), which incorporate prior information on variability in isotopic signatures and proportional contributions of sources, resulting in more precise estimates of consumption. We will also explore IsotopeR models (Hopkins and Ferguson 2012), recently developed and validated in Yosemite black bears, which incorporate additional sources of uncertainty and variation. For the hunter-harvested bears, we will compare differences in diet between black bear age-sex groups, and other human and land use covariates with ANOVA-type analyses, and explore dietary shifts within individuals with a GLM approach. For the wild and captive bears, we will also explore dietary changes throughout the year as related to habitat use. We will then compare differences in telomere length between age groups and individual hunterharvested and nuisance bears, and explore relationships to other covariates with simple correlations and ttests. If as expected, more complex modeling is necessary, we will use the Bayesian Network modeling shell Netica (Norsys Software Corp. Vancouver, Canada) to develop and test models with various covariates that all include telomere length (Marcot et al. 2006, Pauli et al. 2011). Telomere length of blood and hair samples will be compared within individuals as well to determine tissue type differences. Stable isotopic signature will be included as a covariate. For free-ranging and captive bears, rates of telomere shortening will be calculated and examined between individuals and seasons, compared with hibernation length and other covariates. Ultimately, this study is using multiple techniques at two scales: a broad scale single time point sample, and a smaller regional scale with multiple samples. Together, these approaches will illuminate the relative importance of factors influencing diet and aging in Colorado black bears. 228 �Schedule Activity Sample collection - harvested bears Sample collection - nuisance bears Trap and collar bears Hair snags for collared bears Diet sample collection Den visits Stable isotope analysis Telomere analysis Project completion Timeline Fall 2011 Fall 2011-2012 Summer 2012 (if necessary, 2013) Fall/Spring 2012-2014 Summer/Fall 2012-2013 Winter 2012-2014 Winter 2011-ongoing, completed by fall 2013 Winter 2011-ongoing, completed by Spring 2015 Summer 2015 Literature Cited Baldwin, R.A., and L.C. Bender. 2009. Foods and nutritional components of diets of black bear in Rocky Mountain National Park, Colorado. Canadian Journal of Zoology 87:1000–1008. Barrett, E.L.B. and D.S. Richardson. 2011. 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We will use cage traps in areas close to Fort Collins with high human activity, and where there is good road access. Snares will be used for more remote trapping locations, away from human activity and where vehicle access is limited. Once a bear has been captured using either method, field crews will use an identical protocol to process animals. Cage Traps We will capture bears with two different trap designs, as specified in Heather Johnson’s protocol, a cage trap designed and used extensively by Beck (1993), and a newly designed trap to specifically target female bears. The trap developed by Beck is 1.8 m long and 1.0 m in height and width. The frame is constructed of angle iron, all side and top panels are wire mesh of 1.9 x 1.9 in size, and the trap has a floor that is 16-gauge steel. A spring-powered, solid aluminum door is mounted on a full-length hinge at one end and a latching mechanism holds the door closed. The door is triggered via a treadle pedal on the floor, and a standard garage door coil spring provides closing power. A hinged panel along the back of the trap allows access for administering immobilizing drugs via jabpole. In total, the trap weighs approximately 236 kg. In the first study in which these traps were used, only 1 bear in 134 captures was injured, as the individual broke a canine on the wire mesh. We will also use a smaller, lighter trap designed by Mat Alldredge, in conjunction with Tom Davies, Lyel Willmarth, Heather Johnson, and others, which discourages the capture of large males and increases portability in the field. These traps were built to be slightly larger than those that have been successfully used for cougars (Alldredge et al. personal communication) and are 34in high, 60in long, and 25in wide. The frame is built with 1x1in heavy gauge steel, covered with 1x1in heavy gauge, high tinsel, steel mesh. The smaller dimensions of the mesh will reduce the possibility that animals will break their teeth on the cage. The sides of the trap have additional braces to increase overall strength and support. The door of the trap comprises one end of the structure and is designed drop and latch to the bottom of the frame. Bait is hung from a cable attached to an archery trigger, and the door falls shut when the trigger is released. Due to the smaller size of the trap, it only weighs approximately 60 kg. Cage traps will be positioned so they are in the shade, and exposure to sun and precipitation is minimized. All cage traps will be clearly marked with warning signs. Cages will be baited with rotting fish, fruit, or road kill. They will be set in the late afternoon or evening and checked the following morning to minimize the time an animal spends in a trap. If the bear is a cub or yearling (too small for a GPS collar), it will be released without being immobilized. If the bear is an adult, it will be immobilized following procedures described below. Bears will be immobilized with a jabpole, syringe pole, or syringe (hand injection), with the injection targeted into muscle tissue along the shoulder or thigh. Aldrich Foot Snares Aldrich foot snares were specifically developed to capture bears and have proven to be safe and effective (Jonkel 1993). The spring activated snare secures a ¼ inch steel cable around the foot of the bear, closing tight with the action of a small piece of angle iron fashioned into a sliding lock mechanism. The inside of the snare loop is wrapped with duct tape to minimize surface abrasion on the skin of the 233 �foot. We will modify snares with additional duct tape and/or surgical tubing over the cable to serve as a “cub stopper” such that small bears (cubs and yearlings) have a low probability of being captured (Jonkel 1993). An in-line swivel is placed in the cable to avoid torsion of the foot and a potential bone fracture. A short lead is attached to the snare to further minimize stress to the leg. The lead is then secured to an anchor tree at least 10 inches in diameter with a ¼ in steel cable clamped and stapled to the base of the tree so the bear cannot climb it. Branches of the tree are lopped off with a saw or axe about 8 ft up, so the bear cannot hang itself from a branch by the snare cable. An area of ≥5 meters is cleared around the snare site to eliminate potential that the bear is able to twist the snare loop around any obstacles (saplings, brush, etc). Large branches will be angled over the snare to force ungulates to step over or go around it, minimizing the possibility of catching non-target animals. Additional details of setting snares can be found in Jonkel (1993). A disadvantage of using foot snares is that all bears that are caught (even if they are a male bear or too small to collar) must be immobilized to be released. Other non-target animals that are caught (i.e. mountain lions, coyotes, etc) will be immobilized with Telazol and released. Snares will be set in the evening and checked in the morning, operated when ambient temperatures are between 32 and 90°F. Snared bears will be immobilized using a jabpole or CO2 dart gun with the injection targeted into muscle tissue along the shoulder or thigh. Animal Processing During summer months bears will be anesthetized with butorphanol, azaperone, and medetomidine (BAM), a drug combination that has been successful immobilizing black bears and is reversible with atipamezole (a medetomidine antagonist), allowing a faster and safer release of animals around urban environments (Wolfe et al. 2008). BAM will be administered at a volume of 0.4ml/23kg (50 lbs) with a dosage of 0.26mg/kg for butorphaneol, 0.22mg/kg for azaperone and 0.09mg/kg for medetomidine. We will initially give the recommended dose based on estimated animal weight and boost as necessary by ½ and ¼ of the original dose for the first and second boosters, respectively. To reverse immobilization we will intravenously administer atipamezole. We will dispense a volume of 1ml/1ml at a dosage of 5mg/1mg of medetomidine or 0.45mg/kg. One dose should be sufficient to reverse BAM. Bears immobilized with BAM should not be consumed for 45 days afterward, information which will be printed on collars and ear-tags (see below). Following the injection of BAM, field personnel will approach and gently prod the bear to ensure that the animal is fully anesthetized, administering additional doses as needed. Once anesthetized, the bear will be removed from the trap or snare and placed in a sternally recumbent position with front and rear legs extended. If the bear will not be collared it will be subcutaneously injected with a passive integrated transponder (PIT) tag and marked with a single black or brown ear-tag that is labeled with the appropriate consumption date information. Afterwards, the bear will be administered atipamezole and released. Adult female bears will be discriminated from subadults based on weight, and nipple size and coloration (Beck 1991). Adult bears will be fully processed. They will immediately be treated with eye ointment and blindfolded to reduce visual stimuli and protect the eyes from debris and bright light. Throughout the time a bear is anesthetized, its vital signs (heart rate, respiration and temperature) will be monitored. Normal ranges for vital rates of adult bears: heart rate = 60-90 beats/minute, respiration = 15-20 breaths/minute, and temperature = 99.6 - 101.0°F (Jonkel 1993). If a bear’s body temperature exceeds the normal range, field staff will cool the underside of the bear with water, particularly the armpits, groin and stomach. If heart rate and respiration values fall outside normal expectations we will reverse the anesthesia and release the bear. In processing bears, we will check each animal for any lacerations that occurred in the capture process and treat them with topical antibiotics. Additionally, bears will be given an injection of 234 �Oxytetracycline (9mg/lb) or Baytril (7.5 mg/kg) to reduce chances of infection from darting and tooth extraction (described below). Adult bears will be subcutaneously injected with a PIT tag. If the individual has been identified by CDOW Area staff as a “conflict” bear it will be marked in accordance with CDOW Administrative Directive W-2. Individuals will be weighed using a portable spring scale and pulley system and their breeding status will be recorded (lactating, cubs present, evidence of suckling, etc). We will take multiple body size measurements including total length, chest girth and neck girth. During winter months we will also use bioelectrical impedance analysis to measure bear body fat (Farley and Robbins 1994, Hilderbrand et al. 1998). Additionally we will draw blood and collect a hair sample. These samples will be used for telomere and stable isotope analysis. To age captured bears using tooth cementum annuli counts (Stoneberg and Jonkel 1966, Willey 1974), we will remove the first vestigial premolar (or if unavailable the lower first premolar) using a dental elevator. For tooth extraction, we will topically apply Lidocaine and subcutaneously administer Ketofen for analgesia (1cc/100lb). A piece of foam gel will then be placed on the removal site and left for adhesion and filling of the wound. We will attach a GPS collar (~700 g) with a ~2 year life expectancy. Collars will be programmed to collect ≥4 locations/day, and will be labeled with the appropriate consumption date based on immobilization. The GPS collar will include a VHF transmitter that allows tracking via standard telemetry equipment and the retrieval of collars (we will use both North Star and Vectronic collars). We will recapture each collared bear each winter to assess fecundity and body condition, and take samples for telomere analysis during hibernation. GPS collars will upload the location of each individual every day via a satellite system and the location will be available to researchers in real-time. When animal processing procedures are completed, the blindfold will be removed and the immobilization reversal will be administered. Field staff will observe the bear from a safe distance to ensure that the animal recovers to a standing position (Wolfe et al. 2008). Winter Den Checks To assess fecundity, body condition, and obtain winter hair and blood samples for telomere analysis, we will recapture collared bears each winter. Bears will be tracked to their dens using GPS collar locations, and researchers will dig through the snow as needed to access the den. Adult bears (and accompanying yearlings) will be anesthetized with Telazol using a jabpole or CO2 dart gun. Telazol will be administered intramuscularly with a dose of 1.5 – 2.5mg/lb at a lower concentration (5cc at 100mg/ml). Bears will be immobilized at a higher concentration (3cc at 166 mg/ml) if they are particularly agitated or large. We will initially give the recommended dose based on estimated animal weight and boost as necessary by ½ and ¼ of the original dose for the first and second boosters, respectively. Unlike BAM, there is no reversal drug for Telazol. That said, an immobilized bear can be returned to its den for recovery, reducing animal stress and increasing researcher safety. Once immobilized, bears will be removed from the den, placed on a blanket, and processed in a similar manner to that described above. Field staff will check the fit of the GPS collar and make any necessary modifications, and clean up any neck wounds with saline solution. Newborn cubs in the den will be tucked inside the jacket of a field crew member, next to their body, so that the cub says warm and quiet. After processing, bears will be returned to the den; adults and yearlings will be positioned on their side and newborn cubs will be placed on their mother’s back. The den entrance will be covered with sticks and boughs and a layer of snow to discourage the bear from leaving the den. We will retain a small opening in the snow to ensure that the bear has a fresh supply of air (Jonkel 1993). Injuries and Euthanasia If an animal is seriously injured (e.g. fractured or broken appendage, vertebrae, pelvis, or jaw, severe dislocation, laceration or any other injury that severely compromises its ability to survive and/or causes 235 �severe pain or distress) during capture, it will be quickly and humanely euthanized. Bears will be deeply anesthetized with BAM or Telazol and euthanized via an intravenous potassium chloride (KCl; 400-800 mEq) injection or gunshot to the head or neck. Carcasses that are euthanized will be disposed of in a landfill or left in an area appropriate for scavengers. Literature Cited Beck, T.D.I. 1991. Black bears of west-central Colorado. Technical Publication 39, Colorado Division of Wildlife, Fort Collins, Colorado. Beck, T.D.I. 1993. Development of black bear inventory techniques; job progress report. Colorado Division of Wildlife, Project Number W-153-R-6. Farley, S.D., and C.T. Robbins. 1994. Development of two methods to estimate body composition of bears. Canadian Journal of Zoology 72:220-226. Hilderbrand, G.V., S.D. Farley, and C.T. Robbins. 1998. Predicting body condition of bears via two field methods. Journal of Wildlife Management 62:406-409. Jonkel, J.J. 1993. A manual for handling bears for managers and researchers. Office of Grizzly Bear Recovery, US Fish and Wildlife Service, University of Montana, Missoula, Montana. Stoneberg, R.P., and C.J. Jonkel. 1966. Age determination of black bears by cementum layers. Journal of Wildlife Management 30:411-414. Willey, C.H. 1974. Aging black bears from first premolar tooth sections. Journal of Wildlife Management 38:97-100. Wolfe, L.L., C.T. Goshorn, and S. Baruch-Mordo. 2008. Immobilization of black bears (Ursus americanus) with a combination of butorphanol, azaperone, and medetomidine. Journal of Wildlife Diseases 44:748-752. 236 �APPENDIX II Front-range Cougar Research 2011-2012 & 2012-2013 Stable isotope analyses for reconstructing the diets of large predators in Colorado’s Front Range UW-Wisconsin & Colorado Parks and Wildlife Wynne Moss Jonathan Pauli Mat Alldredge Research Proposal 237 �Stable isotope analyses for reconstructing the diets of large predators in Colorado’s Front Range (Study Plan for submission to 2011-2012 Mammals Research Report) Wynne Moss, M.S. student, UW-Madison Introduction Understanding the diet composition of large carnivores is of fundamental importance in wildlife ecology and management, as apex predators can exert strong effects on prey populations and ecosystem processes. In multi-prey systems, quantifying prey selection and predation rates can be a major challenge, in part due to the difficulty of accurately reconstructing the diets of cryptic predators (Knopff et al. 2010). Because black bears (Ursus americanus) and cougars (Puma concolor) are two of the major predators of neonate elk and mule deer, management of Colorado’s native ungulate populations would benefit from a greater understanding of the diets of these predators. In addition, the diet composition of bears and cougars is likely to be affected by urbanization and changes in prey density, such as are currently being experienced along Colorado’s Front Range. Bears and cougars may shift foraging in response to increasing human density (Kertson et al. 2011, Merkle et al. 2011). As human-derived diet items become available, it is unknown how these sources will affect and be affected by large predators, and how reliance on alternate prey items will affect predator and native ungulate survival. As such, a rigorous examination of cougar and bear diets, especially in relation to human density, temporal and spatial scale, and age-sex classes is integral to minimizing human-wildlife interactions, managing Colorado’s carnivores, and predicting how predator-prey relationships may change in the future. Approaches to diet reconstruction Diet composition studies on large, wide-ranging predators have historically relied upon scat analyses and kill site investigations to identify the relative importance of different diet items. An important advantage of these approaches is the ability to study temporal resource use, which can vary highly by season. However, both fecal and kill site analyses can create significant biases in estimating diet composition. For instance, kill site investigations may fail to detect the presence of small prey items (Knopff et al. 2009), and are limited to meat, which only represents a small proportion of the total diet for omnivores like bears. More importantly, studies using kill site analyses often require the capture and handling of individuals to assign GPS collars, and therefore can be limited in the number of individuals monitored. Alternatively, though they can be collected non-invasively and in large sample sizes, scat samples cannot be traced back to an individual or even to age-sex classes without the use of molecular techniques. Therefore, studying resource use for the same individual over a temporal or spatial scale can only be accomplished if paired with genotyping. Finally, fecal analyses underestimate the importance of highly digestible food items, like meat, and overestimate indigestible items, like invertebrate chitin (Dickman and Huang 1988, Hewitt and Robbins 1996) and thus can create inaccurate estimates of dietary contributions. The analysis of naturally occurring stable isotopes has become an increasingly useful tool for ecologists and managers in understanding a myriad of animal behaviors, including dispersal, prey selection, and resource use (Kelly 2000). Dietary analysis using stable isotopes evaluates the ratios of heavy and light isotopes of carbon, nitrogen, and oxygen in tissue samples, and thus avoids the pitfalls of more traditional methods, which fail to detect highly digestible materials and provide only a snapshot of resource use. Additionally, stable isotopes can provide information on foraging at different time periods. For instance, blood reflects the isotopic signature of food consumed over the previous two months (Hilderbrand et al. 1996) and collagen extracted from bone can be used to estimate diet over an individual’s lifetime. Hair, which can be collected non-invasively, reflects items consumed during active phases of hair growth. Specifically, underfur represents autumn diet (Jones et al. 2006), while guard hair can be cut into smaller segments to provide a finer temporal scale within the molt (Pauli et al. 2009). By comparing the isotopic values of hair or other tissue to the isotopic signatures of potential diet items, it is 238 �possible to quantify the relative importance of each food source. We plan to develop techniques for stable isotope analysis of Colorado’s two largest predators: black bears and cougars. Such analyses will allow management agencies to non-invasively reconstruct the diets of these two species, and examine covariates that influence foraging behavior and predation along the urban-wildland interface. Black Bear (Ursus americanus) Black bears are the primary predators of neonate ungulates in many regions of the Rocky Mountains and may significantly impact ungulate population dynamics (Zager and Beecham 2006). Neonatal ungulates represent a pulsed, highly accessible resource to opportunistic carnivores like bears. So much so, that ungulate meat often becomes the primary dietary source of bears during the calving season (Hilderbrand et al. 1999). Although the spring and summer months correspond to a peak in ungulate consumption by black bears (Zager and Beecham 2006), the extent to which bears rely on ungulate meat can strongly vary both geographically and by age-sex group. This variation has not been particularly well characterized, and diet interpretation has been complicated by important methodological differences between studies. Figure 1.: Illustration of carbon and nitrogen Furthermore, few studies have rigorously measured isotopic signatures (‰) of potential diet items: resource use by individual black bears on a fine A) C3 plants and berries; B) C4 plants; C) spatiotemporal scale, although this information would insects (Hymenoptera); D) native ungulates greatly improve our ability to predict ungulate (mule deer and elk). Isotopic values of diet depredation rates by black bears. In fact, only one study items obtained from preliminary data (C;D) or literature (A: Hobson et al., 2000; B: (Baldwin and Bender 2009) has investigated the Merkle et al., 2011) seasonal diets of black bears in Colorado. This study used fecal analysis, and therefore may have underestimated the importance of meat, which is highly digestible, and overestimated the contribution of Table 1. Summary of results for previous studies used less digestible materials like plants and insects. to estimate black bear diet in the Intermountain West. Data is presented as average proportion of diet for each food group; ranges are shown parenthetically. The diets of black bears in the Western US have also been investigated with stable Method % meat % plant % insect isotopes; these studies generally detected higher Stable isotope 26* 58 -* rates of meat consumption than scat analysis analysis1 (5-54) (25-95) (Table 1). However, previous isotopic studies relied upon analysis of 15N and 13C in bulk hair Fecal analysis2 8 63 24 samples and, thus, integrated ungulate (0-12) (51-74) (5-37) consumption over an entire period of hair growth (May-October). In reality, black bear 1: Stable isotope analyses (n=4): Jacoby et al., 1999; Hobson et al., 2000; Fortin, 2011; Merkle et al., 2011 diet is strongly seasonal, with predation of 2: Fecal analyses (n=4): Irwin and Hammond, 1985; Raine and ungulates peaking the month after calving Kansas, 1990; Bull et al., 2001; Baldwin and Bender, 2009 (Barber-Meyer et al. 2008). Averaging bear diet *Meat cannot be differentiated from insects in stable isotope analyses; meat estimate may include contribution of insects across the entire period of hair growth obscures important seasonal patterns in their foraging ecology. Instead, by segmenting guard hair into biologically relevant sections, one could explore seasonal differences in diet for a large number of individual bears, and avoid the need to serially sample bears 239 �through an entire year. Such a methodological advancement would be especially relevant to management agencies that are increasingly employing non-invasive sampling programs. However, for this approach to be successful in free-ranging populations, species- and site-specific molt chronologies and rates need to be quantified for black bears in Colorado. Finally, stable isotope analyses depend upon differences between the isotopic signatures of diet sources; isotopic differences enable the construction of a “mixing space”, which is used to estimate the proportional importance of each diet source (Fig. 1). If diet sources do not differ isotopically, their relative importance cannot be distinguished with mixing models. The δ13C and δ15N values of insects and ungulates do not significantly differ; consequently, previous studies were unable to differentiate the importance of these items in bear diet (Hobson et al., 2000; Bull et al., 2001; Mattson, 2001; Baldwin and Bender, 2009). This limitation is particularly problematic because insects and ungulates represent the two most important summer diet sources for black bears in the Intermountain West. Though not previously used in black bear diet reconstruction, the analysis of a third isotope, 18 O, could distinguish between these two diet sources and allow us to more reliably calculate the seasonal importance of ungulates. Insect chitin and haemolymph are enriched in 18O over atmospheric water due to the loss of the lighter isotope,16O, during molting (Schimmelmann and DeNiro 1986, Ellwood et al. 2011). Conversely, other potential diet sources, including berries, herbaceous matter, and ungulate meat, do not show an enrichment in oxygen. In a preliminary analysis of ant and 18 ungulate samples collected across the state of Figure 2.: δ O values for ant (Formica spp. and Camponotus spp.; n = 6), ungulate (mule deer and Colorado, we found that ants are significantly enriched over ungulates in 18O (Fig. 2). Therefore, elk; n = 8) and black bear (n = 2) samples collected in Colorado. Values given in ‰ the analysis of oxygen in concert with carbon and VSMOW. nitrogen may allow the differentiation of diet sources that were heretofore isotopically indistinguishable, and enable a rigorous quantification of seasonal black bear diet in Colorado. Before applying this to free-ranging black bears, a controlled diet study is needed to quantify the processes affecting 18O assimilation. Cougar (Puma concolor) Cougars, though capable of preying upon a wide variety of species, generally select for ungulates (Anderson and Lindzey 2003, Knopff et al. 2010). Yet, cougars may also utilize alternate prey, such as smaller mammals and domesticated pets and livestock. Virtually all data on cougar diet have been derived from scat samples or kill sites and to date, there have been no estimations of diet using stable isotope analysis. As such, it is quite possible that our estimates of cougar prey use are biased towards larger, less digestible items. In regions of increasing human density, where cougars more often prey upon non-ungulates (Kertson et al. 2011), these biases may be more severe. Therefore, along the Front Range in particular, stable isotope analyses could reveal novel, cryptic diet items that have been missed by previous approaches. 240 �Our preliminary analysis of diet items collected from cougar kill sites indicates that prey species possess distinct isotopic signatures (Fig. 3). Consequently, we can quantify the proportional importance of these prey items. Finally, data from kill site investigations and GPS-collars currently being collected by CPW provide a unique opportunity to refine and verify our stable isotope analyses, as well as examine the effects of numerous covariates. By analyzing the stable isotope signature of GPS-collared cougars, we can relate cougar diet composition to individual age, sex, and habitat use. This may provide useful insights into cougar foraging in an urban landscape and may identify age and/or sex classes that are prone to depredation of pets and livestock. Figure. 3. Illustration of carbon and nitrogen isotopic signatures (‰) of potential diet times: A) rabbits; B) native ungulates (elk and mule deer); C) domesticated ungulates (llamas, alpacas, cows); D) native mesocarnivores (skunks, coyotes, raccoons); E) sheep and goats; F) domestic pets (dogs and cats). Isotopic values of diet items obtained from preliminary data conducted by Pauli (UW) and Alldredge (CPW). Objectives 1. Quantify the molt chronology and guard hair growth rate of captive black bears. Baseline information on black bear hair growth will enable us to reliably sub-section and analyze guard hairs of bears to evaluate seasonal shifts in their diet. 2. Using captive bears and feeding trials, evaluate the efficacy of carbon, nitrogen, and oxygen isotopes in diet reconstruction. We will also develop correction factors and mixing models that can be used by managers in isotope analyses of free-ranging bears. 3. Develop mixing models to reconstruct diets for collared cougars in CPW’s front-range cougar study. Prey composition from kill site investigations will be used to establish prior probabilities for mixing models. In addition, we will compare diet across habitats and age-sex classes to determine what factors influence reliance on domestics or smaller-bodied prey. Methods Black bear Black bears incorporate dietary C, N, and O into hair keratin during the period of molt from early May to October (Jacoby et al. 1999, Hobson et al. 2000); therefore hair isotopic signature reflects diet during this time. However, the stable isotope signature of hair differs from diet due to chemical equilibrium reactions (fractionation) as well as preferential allocation of certain molecules to different tissue types (routing). A controlled feeding study will allow us to quantify the effects of routing and fractionation in bears, since any difference in δ15N, δ13C, and δ18O values between hair and diet can be attributed to these two processes. By measuring the isotopic signature of hair in relation to a known diet, we can ascertain a correction constant (trophic discrimination factor) to be applied to samples from freeranging bears; this correction factor has not been previously calculated for black bears. Additionally, there is evidence that isotopic routing and fractionation are influenced by diet and composition of weight gain (Hilderbrand et al., 1999; Voigt et al., 2008; Caut et al., 2009; Newsome et al., 2010), therefore these rates might change temporally with bear nutritional status and diet. We will simulate temporal changes in 241 �diet by varying dietary meat concentration during the month when highest meat consumption is expected in the wild. The routing and fractionation rates obtained from this process will be more specific to black bears in late spring to fall and improve the accuracy of our isotopic analyses. Our controlled feeding program for black bears will run from April-October 2013 at The Wild Animal Sanctuary in Keenesburg, CO. From April to May, all individuals (n = 8; Fig. 4) will be fed a pelleted high protein omnivore diet. During this time, the isotopic signature of growing hair will equilibrate, ensuring that the isotopic signature of diet is the same for all bears and providing a baseline value to which changes in diet can be compared. In June, we will increase the meat component of the diet to mimic what we expect for the range of free-ranging black bears during ungulate calving. Bears will be divided into four treatment groups: high ungulate diet (n = 2; 90% ungulate meat, 10% omnivore diet), medium ungulate diet (n = 2; 25% ungulate meat, 75% omnivore diet) or no ungulate diet (n = 2; 100% omnivore diet). Ungulate meat will be obtained from road-killed mule deer or elk collected by CPW. The fourth treatment group (n = 2) will be fed 100% omnivore diet spiked with 99% atom 18O enriched glycine (Sigma Aldrich; Pauli et al. 2009). Using an 18O-enriched diet will simulate the seasonal pulse in insectivory (Fig. 2), and will allow us to measure isotopic discrimination of 18O from diet. Finally, for the remainder of the study, from July to October, all bears will be fed non-enriched 100% omnivore diet. Once per month, from April-October, we will collect hair and blood from each individual for stable isotope analysis. In addition, because drinking water may also be a major source of 18O, we will control access to water sources with a constant 18O signature and monitor δ18O values of water throughout the summer to control for fluctuations in water isotopic signature. During our controlled feeding study, we will also establish hair growth curves for black bears. Once per month, we will feed all individuals 22 mg/kg of the nontoxic dye rhodamine B. Rhodamine B has proven to be an effective and safe biomarker in a variety of wildlife species wildlife (Fisher 1999, Fry et al. 2010, Palphramand et al. 2011). The dye is incorporated into hair and other keratinous tissue growing at the time of ingestion, forming a distinct band visible under a UV light microscope (Fry et al. 2010). We will collect hair from all individuals and measure the distance between bands to calculate hair growth (mm/day) from April-October. In addition, by measuring from tip to root, we will establish a growth curve that can be applied to non-marked bears, allowing us to sub-sample hair to analyze a segment corresponding to a particular month. Hair growth rates will be modeled with a Gompertz function (Pauli et al. 2009). For free-ranging bears, the parameter estimates can be used to section hair samples into biologically Figure 4. Controlled feeding program for meaningful seasons (e.g., timing of ungulate calving). black bears. For all months except June, bears (n = 8) will be fed an omnivore diet. After the feeding trial is complete, hair in the In June we will divide bears into four anagen phase will be plucked from captive bears and treatment groups to represent varying segmented according to the growth model developed, with degrees of ungulate use; in addition, one group will be fed an 18O enriched omnivore each segment representing the diet during the month in 18 which it was grown. We will separately analyze hair from diet to determine the efficacy of O as a each month from May-October. After segmenting, all hair tracer in bear studies. samples will be rinsed three times with 2:1 chloroform: methanol solution to remove surface oils (Cryan et al. 2004), dried for 72 hours at 60°C, and 242 �homogenized with surgical scissors. For 13C and 15N analysis, samples will be weighed, placed in tin capsules and submitted to the Stable Isotope Facility at the University of Wyoming. Analysis of 13C and 15 N levels will be conducted with a Costech 4010 elemental analyzer attached to a Thermo Finnigan DeltaPLUS XP Continuous Flow Isotope Ratio Mass Spectrometer. For 18O analysis, samples will be submitted to the Stable Isotope Facility at the University of Wyoming and analyzed with a temperature conversion elemental analysis attached to a continuous flow Thermo Scientific Delta V mass spectrometer. Diet (omnivore pellets and ungulate meat) and water samples will also be analyzed. Results will be provided as per mil (parts per thousand [‰]) ratios relative to the international standards of Peedee Belemnite (PDB; δ13C), atmospheric nitrogen (AIR; δ15N) and Vienna Standard Mean Ocean Water (VSMOW; δ18O) with calibrated internal laboratory standards. We will compare the isotopic values (in δ13C, δ15N, and δ18O) of all treatment diets to those of sectioned bear hair for each month of our study to calculate the rates of discrimination and timing of nutrient incorporation in black bears. Using the same diet throughout hair growth will allow the quantification of intra- and inter-individual variation and the construction of accurate mixing models. Finally, enriching the diet in 18O will determine whether oxygen is a useful tracer to quantify the diet of black bears Cougar From 2011-2012 CPW has collected hair samples from cougars captured along the front-range of Colorado as part of the parent project: Cougar Demographics and Human Interactions Along the UrbanExurban Front-range of Colorado (Alldredge 2008). All required sampling will be done as part of this project and has been approved by CPW’s Animal Care and Use Committee. In total, hair samples from approximately 30 cougars are available in conjunction with hair samples from known prey items killed by these individual cougars. These samples will be the foundation of the proposed project. Fieldwork will concentrate on continuing hair collection of potential cougar diet items from kill sites in Colorado. Species targeted will include mule deer (Odocoileus hemionus), elk (Cervus elaphus), fox (Vulpes spp.), coyote (Canis latrans), raccoon (Procyon lotor), skunk (Mephitis mephitis), mountain cottontail (Sylvilagus nuttallii) wild turkey (Meleagris gallopavo) and a variety of domestic animals. Specifically, we will collect hair samples from carcasses found while investigating kill sites. We will also collect the following domestic species: alpaca (Vicugna pacos), goat (Capra aegagrus hircus), cow (Bos taurus), donkey (Eqqus africanus asinus), llama (Lama glama), sheep (Ovis aries), horse (Equus ferus caballus), cat (Felis catus), dog (Canis lupus familiaris), and chicken (Gallus gallus domesticus). Cougars exhibit less seasonal variability in diet than bears; therefore, hair will be analyzed in bulk rather than by sub-sections. In addition, potential prey items for cougars can be distinguished by carbon and nitrogen signatures alone (Fig. 3) and as such, we do not need to analyze oxygen signatures for either cougars or their prey. For these reasons, a captive study of cougars to examine hair growth rate and oxygen incorporation is not necessary. In the laboratory, all samples will be dried for 72 hr at 60°C and homogenized in a ball mill (Mixer Mill MM200, Retsch Inc., Newtown, PA, USA). Cougar and prey hair samples will be rinsed three times with 2:1 chloroform : methanol solution to remove surface oils (Cryan et al. 2004), dried for 72 hr at 60°C, and homogenized with surgical scissors. Samples will be weighed, placed in tin (13C and 15 N) capsules and submitted to the Stable Isotope Facility at the University of Wisconsin. Analysis of 13C and 15N levels will be conducted with a Costech 4010 elemental analyzer attached to a Thermo Finnigan DeltaPLUS XP Continuous Flow Isotope Ratio Mass Spectrometer. Results will be provided as per mil (parts per thousand [‰]) ratios relative to the international standards of Peedee Belemnite (PDB; δ13C) and atmospheric nitrogen (AIR; δ15N) with calibrated internal laboratory standards. By quantifying the isotopic signature of prey items (i.e., dietary sources), and consumers (i.e., cougars) one can quantify the contribution of each isotopically distinct diet item to the consumer. To that 243 �end, we will use a Bayesian-based approach to quantify the proportional importance of each prey type to individual cougars. Specifically, we will employ the MixSIR models (Parnell et al. 2010, Layman et al. 2011), which are based on a series of linear equations that utilize Bayesian statistics to identify proportional contribution of source pools to a diet. Most importantly, MixSIR models incorporate prior information on the variability in isotopic signatures and the proportional contributions of sources. As a consequence, such Bayesian-based models can substantially narrow the reported ranges of source pool contributions to consumers and result in more precise estimates of prey consumption. We will explore how cougar diet differs between age-sex groups and across habitat types. Specifically, we will examine differences in cougar diets associated with distance from urban areas and in relation to human density. Anticipated Benefits This project will be the first to assess the utility of oxygen isotopes in diet reconstruction of freeranging wildlife. We will use captive feeding trials to develop novel methods for analyzing the stable isotopes of carbon, nitrogen, and oxygen in black bears. Predation of ungulates is an increasing concern for sportsmen and stakeholders in Colorado, and is likely to become a focus of CPW studies. Through the use of stable isotopes and segmented guard hairs, this study could provide managers with a new method for quantifying the importance of ungulate prey items at a fine temporal scale for a large sample size. If successful, the use of oxygen isotopes in mammalian diet reconstruction could be applicable to other carnivores and management settings. This study will also be the first to use isotope analysis to reconstruct cougar diet. Such an approach can identify potentially important prey items that may have been previously overlooked in kill site and scat analyses. In addition, the use of GPS collar data will enable us to test assumptions about the importance of different prey items across an increasingly urbanized landscape. This increased understanding could have important implications for the mitigation of human-wildlife interactions and the conservation of cougars in North America. 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Ursus 17:95–108. 246 �APPENDIX III Front Range Cougar Research Winters, 2011–2012 & 2012–2013 PUMA FORAGING IN AN URBAN TO RURAL LANDSCAPE CSU & Colorado Parks and Wildlife Kevin Blecha Randy Boone Mat Alldredge Research Summary June 30, 2012 247 �PUMA FORAGING IN AN URBAN TO RURAL LANDSCAPE Kevin Blecha, M.S. student, CSU Introduction The Rocky Mountain Front Range of Colorado has experienced drastic increases in human population, and a surge of suburban and exurban landscapes are sprawling into areas occupied by cougar (Puma concolor). Some evidence suggests that cougar show avoidance of these areas of high human density. However, cougar use of human developed landscapes does occur at some level and thus conflicts arise between cougars and humans. This study examines cougar predation characteristics and prey selection in reference to landscape features such as prey availability, anthropogenic development, and hobby livestock. Long term objectives: 1) Examine cougar selection of feeding sites in relation to these main variables: a. Human density/activity b. Prey availability c. Hobby livestock availability 2) Examine cougar dietary compositions and kill rates in relation to: a. Individual cougar characteristics (i.e. sex/age) b. Landscape characteristics A current paradigm in cougar management revolves around the idea that cougar populations may not be sustained without ungulate prey (CMGWG 2005). Exurban and suburban landscapes of the Front Range are relatively free of human hunting pressure, which is possibly linked to elevated levels of cougar’s primary ungulate prey (mule deer [Odocoileus hemionus]). Cougars may be drawn to these areas because they are more likely to increase their encounter with deer, as landscape features used by a primary prey species may be the primary driver for selection of feeding locations of cougar (Pierce et al. 1999, Pierce et al. 2000, Atwood et al. 2007). However, contrary to the idea that increased cougar use of a landscape is a function of increasing prey availability, other recent studies have found that cougar exhibit avoidance to/select against areas of high human activity (Mattson 2007, Burdett et al. 2010, Kertson 2011). Therefore, it is unclear which primary factor may drive landscape use by cougar in the Colorado Front Range. Many studies on other vertebrate species point out that an animal forages optimally (MacArthur and Pianka 1966, Emlen 1966), in which it may sacrifice hunting in areas with high foraging availability for the security provided by areas further away from risks (Willems and Hill 2009). However, whether or not cougar forage optimally in reference to prey availability and human disturbance factors is untested. Testing whether the likelihood of cougar feeding events on the landscape changes in various combinations of low/high prey encounter probability and low/high human disturbance levels, may shed light on: 1.) Whether or not cougar are feeding in exurban areas based on high availability of prey. 2.) The degree of optimal foraging behavior in cougar. Cougar have the ability to prey on all species of livestock, but the highest losses in Colorado occur in commercial sheep ranching. In the Front Range region however, hobby livestock depredations represent a majority of the owner losses. Hobby livestock owners inhabiting the sprawling exurban and developing rural areas of the Front Range that live in or adjacent to highest suitable cougar habitat are at the highest risk of experiencing a hobby livestock depredation (Torres et al. 1996, Michalski et al. 2006). When a cougar is observed or found on property containing livestock, that cougar may be wrongly accused or suspected of hunting livestock as prey. Protection of livestock, including hobby livestock, is enough justification for wildlife managers/livestock owners to destroy the cougar. It is unknown whether or not cougar, while hunting, select for areas with hobby livestock or whether cougar hunt on ranched landscapes selectively or opportunistically. Detailed information on whether or not certain classes 248 �(sex/age) of cougar are more likely to seek prey near hobby livestock is important for predicting which type of cougar may be more likely to commit a depredation offense. Knowing whether cougar that have committed a livestock depredation in the past are more likely to hunt near properties containing hobby livestock will shed light on whether or not individual cougar may behave as specialist toward livestock prey items. Understanding what biological and environmental factors influence cougar predation is important to the management of cougar and the subsequent prey species. It has been hypothesized that stimuli from human disturbances may increase energetic costs (Frid and Dill 2002), thus a decrease in fitness may occur through decreased mating opportunities (Schoener 1971, Pyke et al. 1977) or through lowered survival of offspring. If human activities increase an animal’s search time for acquiring food, through direct disturbances or alterations in landscape configuration, the energetic demands are increased, and thus changes in foraging characteristics may reflect the disturbance/alteration (Gill and Sutherland 2000, Blumstein et al. 2005). Kertson (2010) did find a shift in prey composition in residential areas toward higher proportions of smaller and/or domestic prey. In addition, cougars are known to show individual differences in predation characteristics based on sex, age, and reproductive status (Ackerman et al. 1986, Murphy 1998, Laundre 2005, Laundre 2008, Cooley et al. 2008, Knopff et al. 2010). To assess how different landscapes, seasons, and individual cougar differences influence prey consumption, I will examine characteristics of cougar dietary composition/overlap and feeding rates. Segment Objectives: 1. Advance model-based methods for identifying feeding events/locations from GPS cluster data. a. Assess proportion of sites representing feeding events for various cluster types b. Assess prevalence of scavenging in feeding events c. Assess prey composition by various cluster types 2. Develop a fine scale dataset for depicting the distribution of primary cougar prey in relation to general habitat and human density/activity a. Deploy camera traps across gradients of: i. General habitat conditions ii. Human density iii. Distance to house 3. Develop a thematic map of hobby livestock presence/absence 4. Compare species composition (frequency of occurrence) of cougar diets and compare predation rates on mule-deer and alternative prey items a. Assess species composition of cougar diets b. Assess use of ungulate prey by prey sex/age c. Assess seasonal differences in prey usage Methods This study is an extension of a parent project: Cougar Demographics and Human Interactions Along the Urban-Exurban Front-range of Colorado (see elsewhere in this annual report) project initiated by the Colorado Division of Wildlife ( now Colorado Parks and Wildlife [CPW]), which is charged with managing Colorado’s cougar population. Conflicts between cougar and humans have increased dramatically in the past two decades, thus the FRCP was initiated to address questions regarding cougar natural history, population estimation, response to aversive conditioning, response to relocation, livestock depredation opportunity, and predator/prey relationships. The 2862 km2 extent of the study area, shown in Figure 1, encompasses the foothill/mountainous regions of Boulder County, north Jefferson County, and portions of Clear Creek, Gilpin and Larimer Counties. This area is characterized by a patchwork of private and publicly owned land held by federal, state, and 249 �municipal governing agencies. However, if a subject leaves the study area, standard GPS tracking and field data will be collected on the subject until it establishes what appears to be a maintained home range. All objectives listed below require using cougar fitted with GPS radio collars, and thus only subjects captured in the parent project (See elsewhere in this annual report) are utilized in this project. Objective 1(Advance model-based methods for extracting feeding events/locations from GPS cluster data) Many future analyses conducted in this project require determining the exact location and timing (±30 meters) of feeding/predation events from a sample of cougar subjects. Deploying GPS radio collars on the sample of cougars allows us to study predator-prey relationships. The collars collect GPS locations (a.k.a: fixes or points) 7 to 8 times/day, at 3 or 4 hour intervals. GPS locations are classified into clusters (groups of GPS locations), based on the spatial and temporal relationships of a GPS location to other GPS locations (Anderson and Lindzey 2003). These GPS clusters are then classified into selection sets based on the likelihood of the set of locations (clusters) representing a kill site (Alldredge et al. 2008), thus providing a sound sampling frame from which statistical inferences can be made about GPS clusters that are not physically investigated. To identify unique clusters of GPS locations, a rule-based clustering algorithm was written in Visual Basic and was designed to run within ArcGIS (Alldredge and Schuette, CDOW unpubl. Data 2006). The algorithm was designed to identify clusters in five selection sets (S1, S2, S3, S4, and S5), in order to stratify cluster investigation efforts over a range of different GPS location characteristics for each collared cougar and specified time period (1 month intervals). S1 clusters consists of >2 GPS locations within 200 meters and within a 4 day window. To help account for missing GPS fixes; S2 clusters consist of any two consecutively collected GPS points, separated by a range of 200-500 meters, but are missing the scheduled GPS fix in between the two points. To account for the potential that a cougar may feed quickly or to have a short handling time, S3, S4, and S5 clusters were created to sample locations collected along presumed travelling paths. S3 clusters are any two locations within a range of 200 – 500 meters, while S4 clusters are any two locations separated with a range of 500-1000 meters. S5 cluster types are any single GPS location separated >1000 meters from any other GPS location. In addition to the spatial and temporal criteria, >1 of the points comprising the cluster must have been collected during the night-time. The study period is divided into monthly sub-periods, and sampling is conducted throughout each month. This continuous monitoring was implemented so that a large temporal continuum of conditions (i.e. changes in season, weather, human activities) can be accounted for. For each monthly sub-period, and by each individual cougar subject, we ran the clustering algorithm script on the GPS locations retrieved from the collar. For each cluster of GPS points a random number was assigned so that a sampling frame could be created for each of the five cluster selection sets (S1, S2, S3, S4, S5). For each month and each cougar, the top two random S1 clusters, top S2 cluster, top S3 cluster, top S4 cluster, and top S5 cluster are visited by an investigator. In some months, S2, S3, or S4 cluster types are not created, and thus were not represented in every combination of month and cougar. S1 cluster types have spatial and temporal attributes very similar to the way GPS clusters were defined in previous published research on cougar predation. These studies identified clusters as >2 GPS points (fix frequency of 3-4 hour intervals) within a 1-2 day period (Anderson and Lindzey 2003) or >2 GPS points (3 hour intervals) within a 6 day period (Knopff et al. 2009) within 200 m. White et al. (2011) identified clusters as >2 GPS points within 100 m recorded within a 1-2 day period, and then (Kertson et al. 2011) identified clusters as >3 locations within 100 m during a 24 hour period. Unique to our study is the effort placed on non-S1 cluster types (S2, S3, S4, S5 types). 250 �Randomly sampled clusters are investigated by trained biologists to determine the probable action carried out by the cougar (feeding/resting) while at the site. If evidence of feeding activities is detected (presence of carcass remains), then we determine: 1. Species, sex, and age of prey remains 2. Whether the focal cougar actually killed the animal We used the following protocol to investigate cougar GPS clusters in the field: For S1 clusters, we investigate each cougar GPS location in the cluster by spiraling out a minimum of 20 m from the GPS waypoint while using the GPS unit as a guide, and visually inspecting overlapping field of view in the area for prey remains. Normally this is sufficient to detect prey remains and other cougar sign, (e.g., tracks, beds, latrines) associated with cougar. If prey remains are not detected within 20 m radius of cluster waypoints, then we expand our search to a minimum of 50 m radius around each waypoint. For S2, S3, S4 and S5 clusters, we visit each cougar GPS location and spiral out to a maximum of 50 m around each waypoint, while using the GPS unit as a guide. Depending on the number of locations, topography, vegetation type and density, we spend a minimum of 1 hour and up to 3 hours per cluster to judge whether the cluster was a feeding site. For future analysis, we will follow methods of Anderson and Lindzey (2003) and then improved upon by Knopff et al. (2009). First, clusters investigated in the field are classified by the presence (1) or absence (0) of feeding evidence. Predictive logistic regression models or mixed effects regression models will be created using the presence/absence data as dependent variables, while a suite of attributes will be used as independent variables (Table 1). If sufficient data is available, regression models will be created on an individual cougar basis in order for the model to be reapplied to the un-sampled clusters of that particular cougar. If little variation exists between subjects, then a single model or fewer models (potentially by cougar sex/age/gender) may be implemented. For this report, three preliminary analyses were conducted to explore characteristics of GPS cluster locations and their abilities to identify feeding events. For all analyses, a sample unit is defined as an individual cougar in order for the variance to represent inter-subject variability. Simple descriptive statistics (mean, standard deviation, confidence intervals) were then calculated across a sample of cougars with sufficient amount of data. These analyses were: 1. Assess the proportion of randomly sampled clusters sites that represent feeding sites, for each cluster type (S1 – S5). 2. Assess the proportion of feeding sites that are known scavenging events. These known scavenging events are identified from clusters visited by field investigators who determined that the prey cause of death was from a hunter, vehicle collision, deposition of carcass, bait site, or non-focal lion (feeding site was visited by another GPS collared lion prior to arrival of subject cougar). Because the cause of death is not always obtainable, this scavenging frequency is a minimum estimate. 3. Assess the composition of prey resulting from S1 cluster types versus Non-S1 cluster types (S2 – S5’s). It is anticipated that the non-S1 cluster types may be useful for identifying feeding events on smaller prey items. An assumption is that smaller prey items have shorter handling times, and thus a cougar can easily “dine and dash” within the time period between two consecutive GPS locations recorded by the collar. Prey species were grouped into three prey classes: Deer, Elk, and Non-Cervid. Objective 2 (Development of prey distribution in relation to general habitat and human density/activity) In order to answer questions related to cougar selection of prey, a measure of fine-scale prey availability must be derived. Detailed spatial and temporal prey availability data is not attainable for the 251 �large spatial and temporal extent of the study area/period, as obtaining abundance estimates for even conspicuous animals is difficult in the exurban areas of the Front Range [i.e., deer (CDOW 2006)]. Therefore, an array of 131 camera trap units (Reconyx HyperFire, Holmen, Wisconsin) were distributed throughout the study area to sample encounter rates of prey across the various landscape types. Estimated photographic rates will be interpreted as the probability of encountering a particular prey species, rather than a density or abundance metric. Royle and Nichols (2003) show that heterogeneity in the detection probability parameter of a typical occupancy modeling framework (MacKenzie et al. 2002) is usually most dependent on underlying localized abundance of a surveyed site, especially if all other variables influencing detectability are accounted for. Using camera traps to derive repeated presence-absence data is a novel approach at deriving detection probability estimates that are less influenced by variables other than the localized abundance of a targeted species at a site. Camera traps are less likely to be influenced by observers or sight-ability as the detection of a subject is automated (O’Brien 2010). Encounter rates derived from camera traps may be subject to heterogeneity across ambient temperatures, seasons, species, and body mass of a targeted animal (Rowcliff et al. 2011), but changes in encounter rates between camera traps/sites reflect relative changes in abundance if we assume that detection probabilities are constant among these camera traps/sites (O’Brien 2010). In addition, previous work has shown correlations between camera trapping rates and abundance measures in various ungulate studies (O’Brien et al. 2003, Rowcliffe et al. 2008, Rovero and Marshal 2009). Measures taken to limit inter-site heterogeneity in detection probability include blocking study periods into shorter discrete seasons, in order to account for differences in ambient temperatures, movement behaviors, and animal congregation behaviors (e.g.: seasonal grouping of deer) (Rowcliffe et al. 2011). This study will not attempt to make cross-species comparisons, as the ability to account for inter-species detection heterogeneity is more difficult as movement characteristics from species to species are unique (Efford and Dawson 2012). Camera-trap photograph encounter rates (number of independent photographs per unit time), for each particular prey species of interest, will be measured on a localized scale (25x25 m grid resolution). This high resolution scale was chosen as it fits the fine scale upon which cougar may make decisions regarding hunting and feeding locations, especially considering cougar are shown to select for edge habitats when killing deer (Laundre and Hernandez 2003). Sunquist & Sunquist (1989) suggest that most large stalking felid species must approach within 30 m of a prey item before attacking. Past work characterizing cougar hunting habits in relation to habitat edge, characterize “edge habitats” as a distance band 15-20 m from the interface of two habitat types (Altendorf et al. 2001, Holmes and Laundre 2006). This high resolution was also chosen based on the resolution of the readily available major land-cover data. A ground-truthed land-cover dataset from the Colorado Vegetation Classification BASINWIDE project (CDOW 2003) was chosen for representing major vegetation types. The temporal extent of this study is approximately 1 year (December 2011 – December 2012). The spatial extent of this study consists of Boulder County, Gilpin County, northern Jefferson County, and Clear Creek Counties of the Front Range region of Colorado (Figure 1). The study area extent was chosen to reflect a majority of the home ranges inhabited by cougars fitted with GPS collars. To gather sighting data used to calculate encounter rates, camera traps were placed on a stratified random sample of 25 m grid cell sites (n = 131). Sites are defined by single 25x25 m cells, delineated with the boundaries of the 25 m grid cells used in the BASINWIDE Colorado Vegetation Classification Project (CDOW 2003). Because there is potential to model a variety of species potentially preyed upon by cougar, each with differing movement and habitat selection patterns, sites chosen for surveys were randomly placed (Kays et al. 2010, Harmsen et al. 2010, O’Brien et al. 2010). This is particularly important in multi-species assessments, as placing cameras in habitats targeting certain species with low detection probabilities (as commonly done) may violate assumptions, thus causing biased results (Tobler et al. 2008). A stratified random design was utilized in which six major land-cover types, three housing density levels, and three levels characterizing the proximity to houses are represented (Table 2). Not all combinations of strata are present within the study area. Some of these categories may eventually be 252 �measured as continuous variables when included in final analysis, and thus these levels and strata are only used to guide the placement of cameras to ensure broad and even sampling across a range of possible habitat conditions. Placement of the camera unit within the 25 x 25 m site was chosen by randomly generating a point location and azimuth (0-359º). In forested habitats, or habitats providing a stable structure for mounting a trail camera, the unit was placed on the tree/structure closest to the randomly generated point. In sites not providing a suitable mounting location, cameras were placed on a stake (Figure 2). Some pruning of shrubbery/branches was permitted if maximum visibility was limited and if no more than 10% of the cameras detection zone was obstructed. If maximum visibility range of the camera sensor was limited, and pruning was not an option, the cameras direction was adjusted to a new randomly chosen azimuth. If no alternative azimuth was available because of complete 360 º obstruction, then the camera was moved to an alternative random location within the 25x25 m cell. Trail cameras were elevated ~50 cm from the ground to standardize the angle and viewing range of the infrared sensor and/or camera lens. However, camera heights were slightly modified to accommodate snow accumulations and growth of low lying vegetation. Cameras were positioned so that the unit is parallel with the contour of the ground while the planar detection zone is perpendicular to the ground. Camera units were programmed to record a burst of 5 pictures (1 picture/second) upon triggering, with a quiet period of 30 seconds between triggers. Care was taken to have cameras placed so that vegetation movements in the wind will not give false triggers, as false triggers will consume memory and battery life. A General Linearized Modeling technique will be used to model the encounter rates of each particular prey species across un-sampled sites of the study area, given a-priori selected landscape covariate data such as major land-cover (BASINWIDE vegetation data set), elevation, aspect, hydrology, NDVI, edge proximity, etc. A distribution map of predicted encounter rates for each of the prey species, for each month, will be used to infer spatial relative encounter rate estimates. Relative encounter rate estimates across species may not be readily compared using this technique unless efforts are made to assess the probability of detection among targeted species. Particular focus, sampling effort, and analysis time may be placed on the late winter period and late summer periods. The late winter period (i.e. March – May) is of special interest as this is a period of relative stability in ungulate behaviors, as well as the presumed lowest period of prey availability for cougar. The late summer period (August-Sep), which will initiate after the ungulate birthing pulse, will represent a period of relatively stable ungulate behavior and highest presumed prey availability. Significant covariates with high predictive capabilities will be used to interpolate encounter rates at other non-sampled 25 m cells across the study area, for each monthly time period of interest, for each of the six most common prey species [Mule deer, elk (Cervus elaphus), raccoon (Procyon lotor), housecat (Felis catus), red fox (Vulpes vulpes), coyote (Canis latrans)] of cougar on the front range. Study period lengths and encounter rate definitions (i.e.: change photographs/day to photographs/week) may be manipulated to simplify calculations and modeling. Ultimately, whichever statistical modeling technique is used, the metric shall be interpreted as the rate of encountering a prey item at that given cell on the landscape within the monthly time period of interest. Objective 3 (Cougar selection of hunting areas near hobby livestock) Formal knowledge on the distribution of hobby livestock of the Front Range does not exist. This will be countered by creating a thematic presence/absence map of all parcels of land containing hobby livestock items. Any parcel of land with the confirmed presence of hobby livestock items will be verified through roadside observations of all private land containing evidence of hobby livestock enclosures. Information regarding hobby livestock presence/absence in the individual parcels may be also gathered from: - Knowledge from CPW staff working in the study area. - Knowledge from collaborating agency staff in study area. - Communications with local residence and livestock owners. 253 �- Specific CPW wildlife/livestock conflict reports. - Kill-site investigators’ knowledge of vicinity of any visited cougar GPS location cluster. Road-side observations and personal landowner visitations may be conducted to verify any presence/absence data collected above. Larger pastures inhabited by commercial stock (cattle/sheep/horses) will be denoted separately, as the amount of area utilized by livestock at any one time may be relatively small compared to the overall aerial coverage of the pasture at hand. Objective 4 (Compare dietary composition and predation rates) This component of the study will utilize the larger long term data set of GPS cluster confirmed feeding events spanning November 2008 –November 2012. For each cougar, the number of feeding events for each particular prey species is divided by the total number of confirmed feeding events. A sample unit is defined as an individual cougar in order for the variance to represent inter-subject variability. Simple descriptive statistics (mean, standard deviation, confidence intervals) were then calculated across a sample of cougars with sufficient amount of data. For this exploratory analysis, frequencies of occurrence measures were calculated by: 1.) Ungulate sex 2.) Ungulate age (fawn, sub-adult, adult) 3.) Prey class (deer, elk, non-cervid) The dataset was divided into three seasons based on time periods relevant to behavior of mule-deer (cougar’s primary prey): Summer (Jun. 1 – Sep. 30): Fawn rearing, male social aggregations Fall (Oct. 1 – Dec. 31): Mating Winter/Spring (Jan. 1 – May 31): Winter social aggregations A preliminary estimate of feeding rates (i.e. feeding events/year) was calculated using estimated proportions of clusters representing kill types, total numbers of GPS clusters produced by the clustering algorithm, and frequency of occurrence by prey class. First a sample of subjects, each having at least one year of continuous data collected anytime between January 2011 through June 2012, were used to estimate the mean number of GPS location clusters produced by the algorithm for each of the five selection sets. For each selection set, the mean number of clusters was multiplied by the proportion of clusters representing feeding sites (see objective 1) to produce the annual number of feeding events. Next, the proportion representing each prey class was multiplied by this annual number of feeding events to estimate the number of deer, elk, and non-cervid prey feeding events per year. Preliminary Results and Discussion Objective 1 Investigations on the sampled GPS location clusters were conducted on a dataset spanning November 2008 – June 2012. Investigations were collected on 53 different GPS collared cougar subjects. Each analysis conducted in this annual report may utilize a slightly different subset of cougars, as subjects were only included if they produced a sufficient number of clusters/feeding events and relatively high quality GPS data for a period >x days, where x depends on the particular analysis. Cluster investigations were conducted on a total of 3723 clusters, with 2383 of these being from the first and second randomly selected clusters from each month for each subject. It is projected by the end date of the project (December 2012), ~4500 clusters will have been visited with approximately 2900 of these being from the randomly selected set. As mentioned prior, this study is unique in the effort placed on non-S1 cluster types (S2, S3, S4, S5 types), which made up 950 of the 2383 randomly selected clusters visited by investigators. 254 �Feeding events were present at a mean proportion of 0.43 ±0.03(1/2 95% confidence interval) of the S1 clusters, while a much smaller proportion was found at the S2, S3, S4, and S5 sites (range of 0.04 – 0.11) (Figure 3). Using a sample of 48 cougars with at least two feeding events, the minimum known scavenging proportion of total feeding events was a mean 0.11 (±0.05). Out of the 18 cougars with at least 15 feeding events being documented at their respective top randomly selected clusters, all but one had confirmed evidence of scavenging (Table 3). The prey composition for S1 cluster types was compared against all non-S1 cluster types pooled. Results are shown in Figure 4. Deer made up a majority of both S1 (0.70 ±0.07) and non-S1 cluster types (0.55 ±0.15). The Non-cervid class of the non-S1 clusters (0.34 ±0.15) made up a proportion nearly twice as high as the S1 cluster types (0.17± 0.07). Elk surprisingly made up approximately equal proportions (~0.11) between S1 and non-S1 clusters. It is likely that many of the feeding events on deer and elk found at non-S1 clusters are scavenging events, or potentially cases where the subject was displaced (i.e. by another cougar, human, other predator species) from the site soon (<3 hours) after submission of the prey. Future analysis will use logistic regression models, using a host of variables, to model predation events from GPS cluster data. Several factors influence the success of how a logistic regression model will perform. The first factor is the detection probability of an observer finding evidence of feeding remains likely declines as a function of the amount of time elapsed between the date the cougar was present at a site and the date that the observer visited the site. The second factor is that some subject’s collars had low GPS fix rate success. Lower fix rates logically translate to a negatively biased number of clusters created by the clustering algorithm, which in turn can bias kill rate estimates (see objective 4). A third factor is that GPS location clusters that form on natal dens of female cougar may have similar characteristics as clusters formed on feeding events. All three of these factors will be addressed in subsequent analysis. Objective 2 For the assessment of prey distribution, a single camera was deployed at each of the 131 sites between November 6, 2011 and March 1, 2012. Cameras will remain in the field until November 30, 2012. Cooperation with private landowners was required at 74 of the sites. Remaining sites are located on various tracts of public land owned by Jefferson County Open Space, USFS, Clear Creek County, Denver Mountain Parks, Colorado Parks and Wildlife, City of Boulder Open Space and Mountain Parks, and Boulder County Parks and Open Space. All camera sites were revisited at least once between March and July to assess battery life, memory card space, and over-all functionality. In some cases, new vegetation growth occurred directly in front of the camera that would either render pictures useless (blocked field of view) or trigger the camera when winds moved the vegetation, thus using up memory card space. Cursory inspections of the incoming data indicate that every site has been triggered at least once by a common cougar prey species. Simultaneously answering questions relating cougar use of the landscape relative to prey distribution and human disturbance will give valuable insights to how a large top tier carnivore fits predictions of optimal foraging theory. Specifically, insight to how a top tier predator perceives its landscape and whether or not tradeoffs are being made between maximizing food intake and reducing risks posed by humans is important to advancing knowledge of how animals use resources and perceive their environment. Applications of optimal foraging theory to large carnivorous species are rare, and thus would add knowledge to whether or not predictions drawn from model species are scalable to the highest trophic levels. In addition, results from this study are important to conservation and management of the landscapes occupied by cougar. A study that simultaneously examines the influences of human development and prey distributions on cougar is important to predicting how well foraging behaviors of 255 �cougar may adapt to future urban sprawl. Finally, this study will provide knowledge on hypotheses regarding whether or not elevated prey resource levels are a driver of cougar use of exurban and suburban landscapes. Currently, analysis in the camera trap portion of this study allows for the assessment of cougar use for a particular prey species on an individual species basis. Much focus will be placed on species most commonly preyed upon by cougar, such as deer, elk and raccoon. Incorporating a wider range of species, in addition to accounting for detectability differences between species, would potentially allow future analysis to assess the selection of one particular species over other available species. In addition, fine scale species distribution data are rare, and thus these data may be useful to other wildlife/land managers and researchers. Objective 3 Mapping of parcels of land containing hobby livestock was initiated in April 2012 through digitizing USGS color high resolution (0.6 m) ortho-imagery that was fortunately available for the extent of the study area. Specifically, point features were created on any tract of land that showed obvious evidence of hobby livestock husbandry practices (corrals/ barns/ fences/ bareground). Roadside visual mapping efforts will be conducted Fall 2012 after deciduous trees have shed leaves. Knowing if cougar seek hobby livestock in certain seasons is important to predicting cougar/human conflicts. It is suspected that the spring periods are when livestock depredations are most reported. Speculations exist that cougar are seeking alternative prey sources during the spring months when primary prey sources (ungulates) are at their lowest availability. Increasing harvest rates of species involved in human/wildlife conflicts are a common practice for managers of wildlife populations. However, increasing the harvest quota may not be a suitable management method to decrease human/cougar conflicts in a localized area for various reasons. First, increases in the quota for maximum harvest have not resulted in a substantial increase of harvested cougar (CDOW 2004). Second is that other research has found that small areas with high harvest may only exhibit increased immigration rates especially from younger age classes (Cooley et al. 2009), with no significant overall decrease in density. Thus, a population skewed toward a younger age structure may occur (Cooley et al. 2009). If speculations are true that younger cougar, relative to older cougar, are more likely to prey on hobby livestock, then hobby livestock owners may suffer an increased level of losses in the future. Objective 4 A sample of 25 cougars (7 male and 18 female cougar) was used to assess cougar usage of ungulate prey based on ungulate sex. At deer feeding sites, cougars and/or other scavengers often crush the skulls, which contain antler pedicels, the primary characteristic for assessing gender in the field if antlers are not yet present. Investigators were unable to determine sex on a high proportion (Summer: 82%, Fall: 64%, Winter: 62%) of the deer carcasses found. Sex was rarely determinable on fawn deer, as skulls of fawns appear to be more fragile and thus a large majority of the deer with undetermined gender seemed to be of the fawn age class. Thus it is assumed that proportions of males and female carcasses in the unidentifiable sex group are similar to the proportions found in identifiable carcasses, and thus proportions of male and females are corrected to reflect this. Using only cougars having ungulate kills with determinable sex, we used a sample of 13 cougars in the summer, 17 cougars in the fall, and 21 cougars in the winter to calculate the proportion of ungulate feeding events comprising each sex. In the summer season, the male to female prey ratio was 1:2.4 (Figure 5), but this ratio was nearly reversed in the fall season with a 1.8:1 ratio. During the winter 256 �season, the ratio was near unity at 1:1.02. Confidence intervals for all estimates are very wide, even for normal approximations. The proportion of deer carcasses identified as fawn (<1 YOA [years of age]), sub-adult (1-2 YOA), adult (>2 YOA), and unknown age, were calculated from a sample of 26 individual cougars (7 males and 19 female cougar), with sufficient data, that fed upon > 1 deer carcass in each of the three seasons. Age class of deer was identified by mandibular tooth eruption patterns, and thus age was assigned to be unknown if the lower mandibles could not be found by cluster investigators. Deer carcasses falling in the unknown age class made up a moderate amount of the carcasses found in each of the three seasons (summer: 0.13, fall: 0.40, winter: 0.25). A comparison of the proportions of each age class, for each season, is shown in Figure 6. Most notably was the difference in fawn and adult usage in the summer versus the winter season. During the summer, 0.68 ± 0.12 of the carcasses were found to be fawns (usually new born fawns), while only 0.25 ± .12 were adults. However in the winter season adults made up 0.65 ± 0.10 while fawns made up only 0.18 ± 0.08. Sub-adults appeared to be preyed on the least of the three age classes. For prey composition, we calculated the frequency of occurrence of food items, averaged over a sample of collared cougars with sufficient data (11 males and 22 females) where investigations on random sub-sample of clusters from each cougar yielded a total of 620 different prey items. Across all seasons, deer were preyed on most frequently (0.68 ±0.07), non-cervids second most frequently (0.20 ±0.07), and elk least frequently (0.12 ±0.04). While, the proportion of mule deer prey dominated over the alternative prey classes (elk and non-cervids) in all seasons, a slightly lower proportion of mule deer was observed in the winter season (0.61 +0.1) compared to the following summer season (0.73 ±0.08) (Figure 7). Testing for seasonal differences in prey-species composition indices and frequency of occurrence of individual species may have relevance to prey-switching abilities of cougar. Following these assumptions: - Winter season (January - May) represents the time period with lowest primary prey (deer) availability, while the summer season (June - September) represents the highest availability of primary prey. - Alternative prey follows similar trends in availability as primary prey. - Energetic demands are equal throughout the year. One may utilize the seasonal differences as a proxy to test whether or not cougar switch from using predominately deer or other natural prey items, to other prey species when faced with lower levels of primary prey availability. Additional background work will be conducted to assess the validity of these assumptions in the applicability to the study at hand. Also, future work will incorporate additional investigations, increase the sample size of subjects, and use more refined methods of variance estimation to assess whether the seasonal differences found in this analysis are significantly different. Showing differences in prey-species composition indices and frequency of occurrences of individual species between differing sex and age classes is important to management/conservation of the prey species. Management techniques that change the sex or age structure of the cougar population may impact populations of certain prey species. For instance, if younger cougar are more likely to feed on alternative prey species, then using techniques that shift the cougar population to a younger age structure may have a larger impact on populations of alternative prey. Preliminary estimates of feeding rates were calculated from a sample of 22 subjects (7 males, 15 females), with sufficient data. The mean numbers of GPS location clusters produced by the algorithm for each of the five cluster types are displayed in Figure 8. Using feeding proportions (Figure 3), a mean of 257 �93.3 (95% C.I.: 85-101) annual feeding events may be expected, with 70.6 of these occurring from S1 clusters and 22.7 occurring from non-S1 cluster types. If our study had only conducted field investigations on S1 cluster types (only visit clusters consisting of >2 GPS locations within 100 m), feeding/kill rates may be biased low by 25%. Multiplying this preliminary kill rate by the proportions of each prey class utilized by cluster type (Figure 4), while ignoring the additional variance induced by this measure, a preliminary mean estimate of 62.5 deer, 10.8 elk, and 20.12 non-cervid prey items are consumed per cougar annually. These feeding/kill rates are only preliminary, and additional work must be done to disentangle several factors that produce positive and negative biases in these estimates. Factors such as poor GPS fix success rate, and failure of field investigators to find prey remains at a clusters can negatively bias feeding/kill rates. Our clustering algorithm can assign more than one unique cluster identification record to a group of GPS points if the cougar spends more than 8 days at the cluster (i.e. in the case of elk predations), and thus this can place a positive bias on feeding kill/rates. While this was a simple deterministic model, future analysis will be conducted on a per-subject basis, where the results from logistic regression models (as developed in Objective 1 above) will be used to identify probability of any un-visited cluster, based on a suite of variables, to represent a feeding site. Cougars were once thought to rarely scavenge, but recent work has indicated that scavenging events are more common than once thought (Nowak et al. 2000, Bauer et al. 2005, Bacon and Boyce 2010, Knopff et al. 2010). Not separating predation events from scavenging events will positively bias the number of prey items killed per capita. Cursory examinations of the GPS cluster location data collected in vicinities inhabited by multiple collared cougars indicate that sharing of food items does exist to some degree. Sharing of food items is essentially a form of scavenging, and even the most prompt visits to cluster sites are sometimes unable to disentangle whether the focal cougar (GPS collared cougar) indeed killed the prey item. This is especially important in predation studies that do not have all cougars in an area collared. Additional work must be done to either 1) estimate which clusters represent scavenging events, or 2) conduct a post-hoc estimation of the proportion of feeding events that are actually scavenging events. To assess the degree of scavenging and the effect on predation rate calculations, known scavenging events on feeding sites derived from carcass dumps, road-kill, hunter-kill, and non-cougar usurped kills will be identified. Cougar shared/usurped kills will be identified by examining direct spatial and temporal overlap of GPS cluster data collected from pairs of GPS collared cougars. Not all cougars in an area are monitored with GPS collars, and thus a separate model will be created that predicts the amount of kill sharing as a function of pair-wise home range overlap. Assessing whether differences exist in cougar dietary composition and feeding rates of deer, between levels of high and low human density may be relevant toward discussions of whether or not suburban/exurban landscapes have an impact on cougar fitness, or on the contrary, how cougar may adapt to these potential human disturbances. 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The study area encompasses the approximate home ranges for a sample of GPS collared cougars. 262 �Figure 2: For randomly selected sites with no available trees, camera units are installed on a T-post with a bracket custom made for the unit. Figure 3: Proportion of clusters representing feeding events for each cluster type (selection set). Error bars represent 95% confidence intervals using a normal approximation. 263 �Figure 4: Comparison of S1 and Non-S1 cluster types in the proportion of feeding events represented by deer, elk, and non-cervid prey class. Error bars represent 95% confidence intervals using a normal approximation. Figure 5: Comparison of male and female ungulate proportion comprising feeding events in Summer, Fall, and Winter seasons. Error bars represent 95% confidence intervals using a normal approximation. Figure 6: Comparison of proportion of ungulate feeding events representing fawns, sub-adults, and adult age classes for the Summer, Fall, and Winter seasons. Error bars represent 95% confidence intervals using a normal approximation. 264 �Figure 7: Comparison of the proportion of feeding events for each prey class, by Summer, Fall, and Winter seasons. Error bars represent 95% confidence intervals using a normal approximation. Figure 8: Comparison of the number of clusters produced by clustering algorithm of each cluster type. Total number of non-S1 clusters (S2, S3, S4, and S5 types) outnumber S1 cluster types by almost 2:1. 265 �Explanatory Variable Major Type Variable Total duration of cluster (hours) Fidelity to cluster site GPS Based GPS fix success GPS location dispersion Proportion of nighttime locations Average X axis measure Description Cumulative number of hours spent at cluster site Proportion of points collected during the time window of the cluster that actually occur at the cluster Proportion of successful GPS locations recorded by the GPS collar during the time window of the cluster Standard deviation of GPS locations (UTM units) of all points at the cluster site Proportion of GPS locations at cluster occurring at night Higher X axis values collected ±30 minutes of GPS fix time potentially indicate more straightline movements (i.e. travelling) Higher mean Y axis values collected ±30 minutes of GPS fix time Average Y axis Accelerometer Based potentially indicate more head twisting movements (i.e. prey measure handling) Standard deviation X or High stdev in X axis values potentially indicate less consistent Y axis behavior (i.e. mix of travelling, feeding, resting) Observer/Cluster Investigator Based Terrain ruggedness Rugged terrain more difficult to search Visitation lag* Time between dates of cougar arrival and investigator visitation Observer experience* Number of cluster investigations previously participated in Season Season adjusted temperature Ambient temp from on-board GPS collar themometer, rescaled by seasonal high and low temp Snow cover* Environmental Based Landcover i.e. Grassland, Shrubland, Forested, Urban Human activity where the potential of feeding behavior to be interrupted by humans may be higher (i.e. distance to house, housing density) Canopy Cover* Cougar Subject Specific Age Independent Sub-adult or Adult Sex Male or Female Maternal Status Presence/absence of kittens, age and size of kittens, etc * Variable is unable to be derived for unvisited clusters Table 1: Variables to be used in logistic regression models for predicting feeding events from GPS location cluster data. Strata Factor Sub-Type Description DEC Deciduous trees present GRS Site dominated by grassland HEC Site dominated by coniferous forest >8000 ft elevation LEC Site dominated by coniferous forest <8000 feet in elevation Site dominated by scrub/shrub Major habitat SHR URB Stream1 Site located in urban/suburban housing density levels and within 100 meters of a perennial stream URB Stream2 Site located in urban/suburban housing density levels and 100-750 meters of a perennial stream URB Stream3 Site located in urban/suburban housing densities and >750 m from a perrenial stream MIX Site located in a mix of one of the major habitat classes Rural Housing density >16.18 ha/unit Housing Exurban Housing density 0.68-16.18 ha/unit Density Suburban/Urban Housing density <0.68 ha/unit House 1 Site located < 200 m of house Proximity to House 2 Site located within 200-700 m of house Dwelling House 3 Site located >700 m from house # of Sites 19 20 20 27 20 6 6 6 8 67 47 18 61 50 21 Table 2: Placement of cameras followed a stratified random sampling design across three major stratifications. These strata were chosen in order to spread out the cameras across a range of conditions, as well as to ensure adequate characterization of prey availability in relation to human activity. 266 �Cougar Subject ID AF61 AF01 AM13 AF19 AF69 AF54 AF15 AF62 AF40 AF79 AF34 AM14 AF59 AF77 AF73 AM44 AF52 AM76 AM74 Sub-sample size (total feeding events) 22 25 21 20 17 27 49 22 32 18 27 26 17 16 15 22 20 20 17 Proportion confirmed scavenging 0.000 0.040 0.048 0.050 0.059 0.074 0.082 0.091 0.094 0.111 0.111 0.115 0.118 0.125 0.133 0.136 0.200 0.200 0.235 Table 3: Proportion of feeding events determined to be known scavenging cases for individual cougar subjects with at least 15 feeding events documented at randomly selected cluster sites. 267 �APPENDIX IV Front Range Cougar Research Winters, 2011–2012 & 2012–2013 Predator-Prey Dynamics in Relation to Chronic Wasting Disease and Scavenging Interactions at Cougar Kill Sites Colorado Parks and Wildlife Joe Halseth Mat Alldredge Research Proposal February, 2012 268 �Predator-Prey Dynamics in Relation to Chronic Wasting Disease and Scavenging Interactions at Cougar Kill Sites Joe Halseth and Mat Alldredge, CPW Need The current Colorado Parks and Wildlife (CPW) cougar (Puma concolor) research on the Frontrange is utilizing advanced GPS radio collar technology. This technology allows researchers to track cougar movements on an almost real time basis, with the roughly 25 current active project collars uploading seven times per day. These dependable GPS uploads give researchers the ability to identify possible kill sites quickly, sometimes as soon as 6 to 12 hours after a kill is made. This provides the opportunity to explore previously un-researched facets of cougar behavior during the relatively short time interval from the point a cougar makes a kill, to the point at which it abandons the carcass. Feeding behavior, intraspecific kill site interaction, and scavenger competition can now be investigated. Similar data to that collected in Krumm et al.’s (2005) and Miller et al.’s (2008) cougar studies, which examined cougar selection of Chronic Wasting Disease (CWD) positive mule deer (Odocoileus hemionus), can now be collected with a greater degree of efficiency. The study areas of each of the two prior CWD cougar projects lie within the more broad boundaries of the current Front Range cougar project, and a larger number of known cougars will increase sample sizes of CWD tissues from cougar killed mule deer. Additionally, much of the field work from the two previous studies is nearly a decade old which justifies another project to compare to past results. The ability to collect a potentially larger sample size will yield more accurate findings, identify gaps in need of further study, and/or detect developing trends in regards to possible temporal patterns. The ongoing cougar project’s available technology and resources, and the relatively minor additional project costs, provide the opportunity to initiate a camera study to explore cougar feeding behavior and scavenger interaction in the period immediately following a cougar kill. Site visitation of fresh cougar kills also allows for the collection of adequate tissue samples to test for CWD, in order to further explore if cougars are selecting for CWD positive mule deer or other ungulates. Background Cougar behavior and scavenger interaction: Although there have been significant cougar research projects in the U.S. and Canada, only recent GIS advancements have allowed researchers the ability to monitor cougar movements and locations with dependable accuracy on a real-time basis. With GPS collar technology, researchers can collect data on kill sites, prey items, home ranges, den locations, preferred habitats, and a variety of other previously underexplored areas of cougar ecology and behavior. This new technology initiated many projects that examined cougar feeding behavior. These projects collected extraordinary data documenting duration of kill site occupation, prey analysis, biomass consumption, and feeding patterns (Anderson and Lindzey 2003, Bauer et al 2005, Knopff et al 2010, Blecha and Alldredge unpublished data). However, actual behavior, feeding activity, consumption rates, and scavenger interactions has yet to be thoroughly documented. Placing cameras on fresh kill sites will document feeding behavior, such as the length of actual feeding sessions, and will identify any patterns of behavior that exist during the progression of feeding on a prey item. Additionally, placing cameras will document interaction with competing scavengers and conspecifics. A goal of this proposed project is to document how often scavengers challenge cougars on fresh kills and how successful these competing scavenging species are at stealing the food item. Using the time stamped photos from cameras, we will be able to determine the average time it takes for competing scavengers to arrive on site after a kill and the 269 �rate in which the scavenger species successfully displaces the cougar. Seasonal variation in scavenging rates of fresh carcasses will be analyzed, especially with regard to bear activity and changes in diet competition. Basic cougar ecology suggests that with the exception of family groups and mating interaction, cougars are largely solitary animals (Seidensticker et al. 1973). On numerous occasions throughout the course of the ongoing lion project, researchers have documented two cougars on the same kill site. One can only speculate on their interaction. This proposed project also seeks to document behavior in such situations to observe if cougars are sharing kills or challenging one another for feeding opportunities. CWD component: Ongoing cougar research on the northern Front-range (Alldredge, unpublished data) as well as other significant cougar research (Logan and Sweanor 2001, Anderson and Lindzey 2003, Hornocker 1970) has shown that cougars prey on a wide diversity of prey species, but select for deer and elk in higher proportions. Additionally, the northern Front Range has been identified as the epicenter of the Chronic Wasting Disease (CWD) epidemic, possessing the highest infection rates in the state (Miller et al. 2000). CWD is a naturally occurring prion disease effecting deer, elk and moose. Early stages of infection are difficult to recognize but advanced signs of CWD infected deer are more readily identified by humans, with symptoms including poor body condition, reduced coordination, excessive salivation, and increased isolation from other deer (Williams and Young 1980). Basic predation theories suggest that predators prey upon young, sick, and older individuals in greater proportion than fit, mature individuals (Errington 1946, Slobodkin 1968). Optimal foraging theory predicts that predators ought to choose the most “profitable” prey (MacArthur and Pianka 1966, Schoener 1971, Pulliam 1974), which should be the largest prey available that can safely be killed. Thus, we might assume cougars can identify a deer in the later stages of CWD infection. Miller et al. (2008) speculated that cougars could have the ability to identify the most subtle changes in behavior or body condition in early stage CWD positive deer, causing them to be more vulnerable to predation. While it is known that cougars prey on deer or other ungulates as a primary food source, only two studies have explored whether cougars are selecting for CWD positive deer (Krumm et al. 2005, Miller et al. 2008.) Krumm et al. (2005) found the percentage of CWD infected mule deer killed by cougars was significantly higher than hunter harvested deer in the same area. Miller et al. (2008) found infected deer were much more likely to be killed by cougars than uninfected ones. There is little information on cougar selection of CWD infected elk but this proposed study will document any CWD occurrence in cougar killed elk. Over the past three years, the ongoing cougar project has established many positive relationships with a variety of stakeholders within the study area. Prominent land owners, land managers, various municipal organizations, and many members of the general public are aware and supportive of the project. Additionally, District Wildlife Managers, Boulder County, and Boulder City open space rangers often respond to reports of cougar kills on open space parks and protected areas and within the urban fringe areas. These established relationships increase the frequency of lion activity alerts, yielding more opportunities for researchers to capture cougars. These relationships will continue to provide increased future opportunities to place cameras on fresh cougar kills and collect CWD testable tissues. Advanced GPS technology, coupled with in-field awareness and participation, will allow researchers to capitalize on opportunities and bolster sample size. It is the responsibility of CPW to utilize the best science when managing Colorado’s wildlife resources. Exploring cougar kill site behavior will determine loss rates from scavenging/competition of fresh carcasses. This could provide insight on actual prey consumption and clarify an important variable in estimating the frequency of cougar deer and elk kills. Documenting feeding behavior has not previously 270 �been done in this proposed fashion and will provide invaluable information on basic cougar ecology and behavior. Collecting samples for CWD testing will provide a welcome opportunity to compare new data to the two previous studies and to existing (and evolving) CPW CWD data. Furthering our understanding of the relationships between predator/prey and disease dynamics will afford biologists better information in managing Front Range wildlife populations. Objectives 1. 2. 3. 4. Document sharing and/or abandonment rates of cougars occupying kill sites in response to presence of other cougars and/or scavengers Document time from kill until presence of competing scavengers Document feeding patterns and length of individual feeding sessions. Compare CWD infection rates from cougar killed deer and elk to existing CPW CWD infection rates to determine if cougars are selecting for CWD positive deer and elk. Methods Researchers will monitor cougar movements using GPS data on a GIS to detect possible kill sites as early as possible. This is already successfully being done by viewing collar locations to address the feasibility to initiate capture operations in order to re-collar specific cougars. After a location is deemed permissible and realistic to access, researchers will travel to the kill site area and navigate to the potential kill site location. Personnel will use a VHF signal to monitor cougar location during the approach to avoid contact. In the event the cougar is onsite, at the kill, researchers will reassess approach and come back at another time. In the event a kill is found, a maximum of two cameras will be placed to document feeding activity and scavenger interaction. Multiple cameras will be used in the event the cached prey item is slightly moved and to monitor activity within a larger area. Cameras will be affixed to adequate stationary objects and camouflaged with vegetation to minimize sight manipulation and detection. The reconyx cameras currently used in the parent cougar project are 4x6 inches and emit a low glow instead of a flash during nighttime photographs. Cameras will be left in place up to two weeks after the cougar has left the kill site. If the prey item is a mule deer or other ungulate, retropharyngeal lymph nodes and/or the medulla oblongata at the obex will be collected for CWD testing. Additionally a lower incisor will be obtained for accurate age analysis. Krumm et al. (2005) collected 54 testable samples from cougar killed mule deer in 42 months. Miller et al. (2008) observed 11 CWD positive collared deer succumbed to cougar predation at a rate nearly four times that of uninfected collared deer. With the large number of collared cougars in the current Front Range cougar project (n≈25), we predict the ability to collect a target sample size of 4-5 tissue samples per month. A large sample is necessary to determine if cougars are selecting for CWD positive deer, as the power to detect a 10% difference using binomial proportions is only 0.75 (n=200). While some disturbance to cougars may be unavoidable if the animal is alerted upon researcher approach, precautions will be taken to not force cougars off a kill. Past experiences, especially those associated with capture activities, on the Front Range cougar project have shown that a cougar is not likely to be affected if briefly disturbed at their kill. Ideally, the potential kill site will be approached between feeding sessions when the cougar is day bedded offsite. Initial kill site investigations are currently being conducted in the parent cougar project to establish the probability the kill site is detected by technicians at a later date. There have been no instances of abandonment. Additionally, many bait sites occupied by cougars are visited daily by technicians to switch memory cards in cameras, adjust location of placed bait carcasses, and/or refresh bait as needed to keep a cougar in the immediate area. Often times 271 �this is done for a series of days until researchers can attempt to conduct a capture. Even with these daily visits, patterns of bait site abandonment have not been observed. However, if these kill site visits and camera placements prove to disturb the cougar, and a pattern of kill site abandonment is observed, site visits and camera placement will cease. Literature Cited Anderson, C.R. and Lindzey, F. G.2003. Estimating cougar predation rates from GPS clusters. Journal of Wildlife Management 67, 307-316. Bauer, J.W., Logan, K.A., Sweanor, L.L and Boyce, W.M. 2005. Scavenging Behavior in Puma. The Southwestern Naturalist. 50(4): 466-471. Errington, P.L. 1946. Predation and vertebrate populations. Quarterly Review of Biology 21:145-245. Hornocker, M. G. 1970. An analysis of mountain lion predation upon mule deer and elk in the Idaho primitive area. Wildlife Monographs 16, 3-39. Knopff, K.H., Knopff A.A., Kortello, A., and Boyce M.S. 2010. Cougar kill rate and prey consumption in a multiprey system. Journal of Wildlife Management 74(7):1435-1447. Krumm, C.E., Conner, M.M., Hobbs T.N., Hunter D.O., and Miller M.W. 2005. Mountain lions prey selectively on prion-infected mule deer. Biology letters 6, 209-211. Logan, K.A and Sweanor, L.L. 2001. Desert Puma: Evolutionary ecology and conservation of an enduring carnivore. Washington D.C., USA: Island Press. MacArthur, R.H., and E.R. Pianka. 1966. On the optimal use of a patchy environment. American Naturalist 100:603-609. Miller M.W., Swanson H.M., Wolfe L.L., Quartarone F.G., Huwer S.L., et al. (2008) Lions and Prions and Deer Demise. PLoS ONE 3(12): e4019 Miller M.W., Williams E.S., McCarthy C.W., Sparaker T.R., Kreeger, T.J., Larson, C.T., and Thorne, E.T. 2000. Epizootiology of chronic wasting disease in free-ranging cervids in Colorado and Wyoming. Journal of Wildlife Diseases 36:4, 676-690. Pulliam, H.R. 1974. On the theory of optimal diets. American Naturalist 108:59-75. Schoener, T.W. 1971. Theory of feeding strategies. Ann. Rev. Ecol. Syst. 2:369-404. Seidensticker IV, J.C., Hornocker, M.G., Wiles, W.V. and Messick, J.P. 1973. Mountain lion social organization in the Idaho primitive area. Wildlife Monographs (35). Slobondkin, L. 1968. How to be a predator. American Zoologist 8:43-51. Sweanor, L.L., Logan, K.A. and Hornocker, M.G. Puma responses to close approaches by researchers. Wildlife Society Bulletin 33:3, 905-913. Williams, E.S and Young, S. 1980. Chronic wasting disease of captive mule deer: a spongiform encephalopathy. Journal of Wildlife Diseases 16:1, 89-98. 272 �APPENDIX V Continuous-Time Discrete-Space Models for Animal Movement Data Ephraim M. Hanks Department of Statistics, Colorado State University, Fort Collins, CO, U.S.A. Email: hanks@stat.colostate.edu Mevin B. Hooten U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, Fort Collins, CO U.S.A. Mat W. Alldredge Colorado Division of Parks and Wildlife Fort Collins, CO, U.S.A. October 22, 2012 273 �Abstract The processes influencing animal movement and resource selection are complex and varied. Past efforts to model changing behavior over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practicioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor ) in Colorado, USA. Keywords: Agent-Based Model; Animal Movement; Mountain Lion; Multiple Imputation; Varying-Coefficient Model. 274 �1. Introduction Animal telemetry data have been used extensively in recent years to study animal movement, space use, and resource selection (e.g., Johnson et al., 2011; Hanks et al., 2011; Fieberg et al., 2010). The ease with which telemetry data are being collected is increasing, leading to vast increases in the number of animals being monitored, as well as the temporal resolution at which telemetry locations are obtained (Cagnacci et al., 2010). This combination can result in huge amounts of telemetry data on a single animal population under study. Additionally, the processes driving animal movement are complex, varied, and changing over time. For example, animal behavior could be driven by the local environment (e.g., Hooten et al., 2010), by conspecifics or predator/prey interactions (e.g., Merrill et al., 2010), by internal states and needs (e.g., Nathan et al., 2008), or by memory (e.g., Van Moorter et al., 2009). The animal’s response to each of these drivers of movement is also likely to change drastically over time (e.g., Nathan et al., 2008; Hanks et al., 2011; McClintock et al., 2012). The large amount of telemetry data available, even for one animal, and the complex behavior displayed in animal movement results in a challenging situation for statistical modeling. There is no shortage of existing statistical models of animal movement; however, most of these models are computationally demanding, and most are inaccessible to the practicioner. For example, consider the agent-based model of animal movement of Hooten et al. (2010). The agent-based framework is highly flexible, allowing for location-based (static) and directional (dynamic) drivers of movement, but is computationally expensive. Analyzing the movement path of one animal using the approach of Hooten et al. (2010) can require computational time on the order of days using standard computing resources. The velocity-based framework for modeling animal movement of Hanks et al. (2011) allows for time-varying behavior through a changepoint model of response to drivers of movement, and is more computationally efficient than the approach of Hooten et al. (2010), requiring computational time on the order of hours. Similarly, the mechanistic state-switching approach of McClintock et al. (2012) allows for time-varying behavior through a state-switching approach. These three approaches use Bayesian statistical models, and both Hanks et al. (2011) and McClintock et al. (2012) allow for time-varying behavior by letting the model parameter space vary, either through a reversible-jump Markov chain Monte Carlo approach (Green, 1995) or the related birth-death Markov chain Monte Carlo approach (Stephens, 2000). These methods can be quite computationally demanding, require the user to tune the algorithm to ensure convergence, and can be inaccessible to many practitioners. The agent-based model of Hooten et al. (2010) assumes a representation of the animal’s movement path that is discrete in both space (grid cells) and time (fixed time intervals). The velocity-based movement model of Hanks et al. (2011) assumes a representation of the movement path that is continuous in space and discrete in time. The state-switching model of McClintock et al. (2012) assumes a representation of the movement path that is discrete in time and continuous in space. 275 �In this paper, we present a continuous-time, discrete-space (CTDS) model for animal movement which allows for flexible modeling of an animal’s response to drivers of movement in a computationally efficient framework. Instead of a Bayesian approach, we adopt a likelihood-based approach for inference, and instead of a state-switching or change-point model for changing behavior over time, we adopt a time-varying coefficient model. We also allow for variable selection using a lasso penalty. This CTDS approach is highly computationally efficient, requiring only minutes or seconds to analyze movement paths that would require hours using the approach of Hanks et al. (2011) or days using the approach of Hooten et al. (2010), allowing the analysis of longer movement paths and more complex behavior than has been previously possible. To make this CTDS approach for modeling animal movement and resource selection accessible to practitioners, code to implement this approach is available online (www.stat.colostate.edu/˜hanks) in the form of a package for the R statistical computing environment (R Development Core Team, 2012) with worked examples. In Section 2 Preliminaries, we describe the continuous-time continuous-space model of Johnson et al. (2008) which is used to make inference on the posterior predictive distribution of an animal’s continuous movement path, conditioned on observed telemetry locations. We then describe the method of multiple imputation (Rubin, 1987) which we use to integrate over the uncertainty in the animal’s continuous movement path. In Section 3 ContinuousTime Discrete-Space Movement Model, we describe the CTDS model for animal movement, and show how inference can be made on parameters in this model using standard software for generalized linear models (GLMs). In Section 4 Time-Varying Behavior and Variable Selection we use a varying-coefficient approach to model changing behavior over time, and use a lasso penalty for variable selection. In Section 5 Drivers of Animal Movement we discuss modeling potential covariates in the CTDS framework. In Section 6 Example: Mountain Lions in Colorado we illustrate our approach through an analysis of mountain lion (Puma concolor ) movement in Colorado, USA. Finally, in Section 7 Discussion we discuss possible extensions to the CTDS approach. 2. Preliminaries 2.1 Continuous-Time Continuous-Space Movement Model To model animal movement, we make use of the continuous time correlated random walk (CTCRW) model of Johnson et al. (2008) to characterize a distribution for the continuous path conditioned on observed telemetry data. Let S = {s(t), t = t0 , t1 , . . . , tT } be a collection of time-referenced telemetry locations for an animal. If the animal’s location and velocity at an arbitrary time t are s(t) and v(t), respectively, then the CTCRW model can be specified as follows, ignoring the multivariate notation for simplicity: � ψ2 e−ψ3 t ω e2ψ3 t , v(t) = ψ1 + √ 2ψ3 276 (1) �Z t v(u)du , s(t) = s(0) + 0 where ψ = [ψ1 , ψ2 , ψ3 ] control the movement and ω(t) is standard Brownian motion. This model can be discretized and formulated as a state-space model, which allows for efficient computation of discretized paths S̃ at arbitrarily fine time intervals via the Kalman filter (Johnson et al., 2008). If a Bayesian framework is used for inference on ψ, Johnson et al. (2008) shows how the posterior predictive distribution of the animal’s continuous path S̃ can be approximated using importance sampling. We will refer to the posterior predictive path distribution as [S̃|S], where the bracket notation ‘[·]’ denotes a probability distribution. 2.2 Multiple Imputation Our general strategy is to construct a model conditioned on the continuous path S̃, and then integrate over the uncertainty in the posterior predictive distribution [S̃|S] (e.g., Hooten et al., 2010; Hanks et al., 2011). If we treat the unobserved continuous path S̃ as missing data, then we can make inference on model parameters using multiple imputation (Rubin, 1987). We motivate multiple imputation as posterior predictive inference on the imputation distribution within a Bayesian framework. Our treatment is similar to that of Rubin (1987) and Rubin (1996). If we desire posterior predictive inference [θ|S] concerning environmentally relevant movement parameters θ, conditioned on the telemetry data S and the posterior predictive path distribution [S̃|S], then we can write: Z [θ|S] = [θ|S̃][S̃|S]dS̃. (2) S̃ In the multiple imputation literature, the posterior predictive path distribution [S̃|S] is called the imputation distribution and specifies a statistical model for the missing data S̃ conditioned on the observed data S. We will use the CTCRW model of Johnson et al. (2008) as the imputation distribution [S̃|S] in our CTDS approach to modeling animal movement. The CTCRW model is a mechanistic model of animal movment that has been successfully applied to studies of aquatic (Johnson et al., 2008) and terrestrial (Hooten et al., 2010) animals, and can represent a wide range of behavior. Hooten et al. (2010) and Hanks et al. (2011) use composition sampling to obtain samples from the posterior predictive distribution [θ|S] in (2) by sampling iteratively from [θ|S̃] and [S̃|S]. Alternately, under the multiple imputation framework the posterior distribution [θ|S] is assumed to be asymptotically Gaussian. The posterior can then be approximated using only the posterior predictive mean and variance, which can be obtained using conditional mean and variance formulae: 277 �Z Z E(θ|S) ≈ θ [θ|S̃][S̃|S]dS̃dθ � Z �Z S̃ = θ[θ|S̃]dθ [S̃|S]dS̃ S̃ Θ � � = ES̃|S E(θ|S̃) Θ and likewise: (3) � � � � Var(θ|S) ≈ ES̃|S Var(θ|S̃) + VarS̃|S E(θ|S̃) . (4) As the posterior distribution [θ|S̃] converges asymptotically to the sampling distribution of the maximum likelihood estimate (MLE) of θ, we can approximate [θ|S̃] by obtaining the asymptotic sampling distribution of the MLE. This allows us to use standard maximum likelihood approaches for inference, which can be much more computationally efficient than their Bayesian counterparts for this class of models. The multiple imputation estimate θ̂ M I is typically obtained by approximating the integrals in (3) and (4) using a finite sample from the imputation distribution. The procedure can be summarized as follows: 1. Draw K different realizations (imputations) S̃(k) ∼ [S̃|S] from the imputation distribution. (k) 2. For each realization, find the MLE θ̂ and asymptotic variance V ar(θ̂ estimate based on the the full data: (S̃). (k) ) of the 3. Combine results from different imputations using finite sample versions of the conditional expectation (3) and variance (4) results: K 1 X (k) θ̂ θ̂ M I = K k=1 (5) K K (k) 1 X 1 X � (k) ¯ �2 var(θ̂ ) + V ar(θ̂ M I ) = θ̂ − θ̂ . K k=1 K k=1 (6) Equations (5) and (6) are the commonly used combining rules (Rubin, 1987) for multiple imputation estimators in the scalar case. When θ is vector-valued, similar approaches can be used (Rubin, 1987). 278 �3. Continuous-Time Discrete-Space Movement Model Having described the multiple imputation framework, we now focus on specifying a model of animal response to drivers of movement [(S̃, S)|θ] that is flexible and computationally efficient. In doing so, we will assume a discrete (e.g., gridded) model for space (e.g., Hooten et al., 2010), and model animal movement as a continuous-time random walk through the discrete, gridded space. Let the the study area be defined as a graph (G, A) of M locations G = (G1 , G2 , . . . , GM ) connected by “edges” Λ = {λij : i ∼ j, i = 1, . . . , M } where i ∼ j means that the nodes Gi and Gj are directly connected. For example, in a gridded space each grid cell is a node and the edges connect each grid cell to its first-order neighbors (e.g., a rook’s neighborhood). In typical studies, the spatial resolution of the grid cells in G will be determined by the resolution at which environmental covariates that may drive animal movement and selection are available. A path realization S̃ from the CTCRW model is continuous in time and space (Figure 1). If we consider a discrete, gridded space G, then the continuous-time, continuous-space path S̃ is represented by a continuous-time, discrete-space path (g, τ ) consisting of a sequence of grid cells g = (Gi1 , Gi2 , . . . , GiT ) transversed by the animal’s continuous-space path and the residence times τ = (τ1 , τ2 , . . . , τT ) in each grid cell. In practice, this transformation from continuous space to discrete space results in a compression of the data to a temporal scale that is relavent to the resolution of the environmental covariates that may be driving movement and selection. For example, if an animal is moving slow relative to the time it takes to traverse a grid cell in G, then the quasi-continuous path S̃ may contain a long sequence of locations within one grid cell. The discrete-space representation of the path represents this long sequence of locations as one observation (a grid cell Git and residence time τt ). This data compression is especially relevant for telemetry data, in which observation windows can span years or even decades for some animals. 3.1 Random Walk Model The discrete-space representation (g, τ ) of the movement path allows us to use standard discrete-space random walk models to make inference about possible drivers of movement. While we will relax this assumption later to account for temporal autocorrelation in movement behavior, we initially assume that the the t-th observation (Git , τt ) in the sequence is independent of all other observations in the sequence. Under this assumption, the likelihood of the sequence of transitions {(Git → Git+1 , τt ), t = 1, 2, . . . , T } is just the product of the likelihoods of each individual observation. We will focus on modeling each transition (Git → Git+1 , τt ), and will drop the t subscript in this section to simplify notation. 279 �Figure 1: Continuous-time continuous-space and continuous-time discrete-space representations of an animal’s movement path. 280 �If an animal is in cell Gi at time t, then define the Poisson rate of transition from cell Gi to a neighboring cell Gj as (7) λij (β) = exp{x0ij β} where xij is a vector containing covariates related to drivers of movement specific to cells i and j, and β is a vector of parameters that define how each of the covariates in xij drive animal movement. The total transistion rate λi from cell i is the sum of the transition rates P to all neighboring cells: λi (β) = j∼i λij (β) and the time τ that the animal resides in cell Gi is exponentially-distributed with rate parameter equal to the total transition rate λi (β): [τ |β] = λi (β) exp {−τ λi (β)} . (8) When the animal transitions from cell Gi to one of its neighbors, the probability of transitioning to cell Gk , an event we denote as Gi → Gk , follows a multinomial distribution with probability proportional to the transition rate λik to cell Gk : [Gi → Gk |β] = P λik (β) λik (β) = . λi (β) j∼i λij (β) (9) The residence time and eventual destination are independent events, and so the likelihood of the observation (Gi → Gk , τ ) is the product of the likelihoods of its parts: λik (β) · λi (β) exp {−τ λi (β)} λi (β) = λik (β) exp {−τ λi (β)} . [Gi → Gk , τ |β] = (10) 3.2 Latent Variable Representation We now introduce a latent variable representation of the transition process that is equivalent to (10), but allows for inference within a standard generalized linear modeling framework. For each j such that i ∼ j, define zj as ( 1 , Gi → Gj zj = 0 , o.w. and let z [zj , τ |β] ∝ λijj exp {−τ λij (β)} (11) where ni is the number of neighbors of the i-th grid cell. Then the product of [zj , τ |β] over all j such that i ∼ j is equivalent to the likelihood (10) of the observed transition: 281 �Y [zj , τ |β] = j:i∼j Y z λijj exp {−τ λij (β)} j:i∼j = λik (β) exp {−τ λi (β)} , where Gi → Gk = [Gi → Gk , τ |β] The benefit of this latent variable representation is that the likelihood of zj , τ |β in (11) is equivalent to the kernel of the likelihood in a Poisson regression with the canonical log link, where zj are the observations and log(τ ) is an offset or exposure term. The likelihood of the entire continuous-time, discrete-space path (g, τ ) can be written (returning t to the notation) as: T Y Y � zjt � [g, τ |β] = [Z, τ |β] ∝ λit jt (β) exp{−τt λit jt (β)} (12) t=1 it ∼jt 0 where Z = (z1 , . . . , zT ) is a vector containing the latent variables zi = (zi1 , zi2 , . . . , ziK )0 for each grid cell in the discrete-space path. Inference can be made on β in (12) using standard Poisson GLM approaches (e.g., maximum likelihood). This provides a computationally efficient framework for the statistical analysis of potential drivers of movement within the multiple imputation framework of Section 2.2. Multiple path realizations (imputations) can be drawn from [S̃|S]. Each continuous path S̃ can then be transformed into a CTDS path (g, τ ), which can then be used to make inference on β using (12). The results from the multiple imputed paths can then be combined using (5) and (6), resulting in a multiple imputation estimate β̂ M I and estimated variance V ar(β̂ M I ). 4. Time-Varying Behavior and Variable Selection In this section we describe how covariate effects can be allowed to vary over time using a varying-coefficient model, and how variable selection can be accomplished through shrinkage estimation. 4.1 Changing Behavior Over Time Animal behavior and response to drivers of movement can change significantly over time. These changes can be driven by external factors such as changing seasons (e.g., Grovenburg et al., 2009) or predator/prey interactions (e.g., Lima, 2002), or by internal factors such as internal energy levels (e.g., Nathan et al., 2008). The most common approach to modeling time-varying behavior in animal movement is state-space modeling, typically within a Bayesian framework (e.g., Morales et al., 2004; Jonsen et al., 2005; Getz and Saltz, 2008; Nathan et al., 2008; Forester et al., 2009; Gurarie et al., 2009; Merrill et al., 2010). In the state-space framework, the animal is assumed to exhibit a number of behavioral states, 282 �each characterized by a distinct pattern of movement or response to drivers of movement. The number of states can be either known and specified in advance by the researcher (e.g., Morales et al., 2004; Jonsen et al., 2005) or allowed to be random (e.g., Hanks et al., 2011; McClintock et al., 2012). State-space models are an intuitive approach to modeling changing behavior over time, but there are limits to the complexity that can be modeled using this approach. Allowing the number of states to be unknown and random requires a Bayesian approach with a changing parameter space. This is typically implemented using reversible-jump MCMC methods (e.g., Green, 1995; McClintock et al., 2012; Hanks et al., 2011), which are computationally expensive and can be difficult to tune. Our approach is to use a computationally efficient GLM (12) to analyze parameters related to drivers of animal movement. Instead of using the common state-space approach, we employ varying-coefficient models (e.g., Hastie and Tibshirani, 1993) to model time-varying behavior in animal movement. The model for the Poisson transition rate (7) will typically contain an intercept term and multiple covariates {x}. For simplicity in notation, consider the case where there is only one covariate x in the model (7) and no intercept term. The varying-coefficient approach generalizes easily to the case where there are multiple covariates and an intercept term in (7). In a time-varying-coefficient model, we allow the parameter β(t) to vary over time in a functional (continuous) fashion. The transition rate (7) then becomes: λij (β(t)) = exp {xij β(t)} where t is the time of the observation and xij is the value of the covariate related to the Poisson rate of moving from cell i to cell j. The functional regressor β(t) is typically modeled as a linear combination of nspl spline basis functions {φk (t), k = 1, . . . , nspl } : β(t) = nspl X αk φk (t). k=1 B-spline basis functions are among the most-widely used choices for {φk (t)}, and are appropriate in most cases. Fourier basis functions are commonly used for {φk (t)} when the behavior is thought to be periodic (e.g., diurnal variation in behavior). Under this varying-coefficient specification, (7) can be rewritten as λij (β(t)) = exp {xij β(t)} ( nspl ) X = exp xij αk φk ((t)) = exp � k=1 0 φij α 283 (13) �where α = (α1 , . . . , αnspl )0 and φij = xij ·(φ1 (t), . . . , φnspl (t))0 . The result is that the varyingcoefficient model can be written as a GLM with a modified design matrix. This specification provides a flexible framework for allowing the effect of a driver of movement (x) to vary over time that is computationally efficient and simple to implement using standard GLM software. 4.2 Shrinkage Estimation The model we have specified in (12) is likely to be overparameterized, especially if we utilize a varying-coefficient model (13). Animal movement behavior is complex, and a typical study could envision a large number of potential drivers of movement, but an animal’s response to each of those drivers of movement is likely to change over time, with only a few drivers being relevant at any one time. Under these assumptions, many of the parameters αk in (13) are likely to be very small or zero. Multicollinearity is also a potential problem, as many potential drivers of movement could be correlated with each other. We propose a shrinkage estimator of α using a lasso penalty (Tibshirani, 1996). The typical maximum likelihood estimate of α is obtained by maximizing the likelihood [Z, τ |α] from (12), or equivalently by maximizing the log-likelihood log[Z, τ |α]. The lasso estimate is obtained by maximizing the penalized log-likelihood, where the penalty is the sum of the absolute values of the regression parameters {αk }: ) ( K X |αk | . (14) α̂lasso = max log[Z, τ |α] − γ α k=1 As the tuning parameter γ increases, the absolute values of the regression parameters {αk } are “shrunk” to zero, with the parameters that best describe the variation in the data being shrunk more slowly than parameters that do not. Cross-validation is typically used to set the tuning parameter γ at a level that optimizes the model’s predictive power. Shrinkage approaches such as the lasso are well-developed for GLMs, and computationallyefficient methods are available for fitting GLMs to data (e.g., Friedman et al., 2010). Recent work has also applied the lasso to multiple imputation estimators (e.g., Chen and Wang, 2011). The main challenge in applying the lasso to multiple imputation is that a parameter may be shrunk to zero in the analysis of one imputation but not in the analysis of another. The solution is to use a so-called group lasso (Yuan and Lin, 2006), in which a group of parameters is constrained to either all equal zero or all be non-zero together. The lasso can be seen as a constrained optimization problem, with αlasso minimizing the mean squared error subject to the constraint that ||αlasso ||1 ≤ ν, where || · || is the L-1 norm and the value of ν is determined by the tuning parameter γ. As the estimate αlasso typically falls on the boundary of the constrained space, conventional approaches for estimating the standard error of αlasso are unavailable. Bayesian versions of the lasso (Park and Casella, 284 �2008) and group lasso (Raman et al., 2009) provides alternatives that allow for estimating the uncertainty about the parameters αlasso through posterior analysis. The Bayesian approach entails significantly more computational complexity, and may not be as accessible to practitioners. We instead focus on the likelihood-based stacked lasso estimate of Chen and Wang (2011). In this estimate, instead of computing the lasso estimate αlasso for each imputation individually, and then combining the results using (5) and (6), the imputed data from all estimates are “stacked” together and a group lasso estimate is obtained for the combined data. We note that this likilihood-based stacked lasso approach does not allow for the estimation of the variance of αlasso . If uncertainty estimates are a priority, we recommend choosing a parsimonious selection of potential drivers of movement a priori that exhibit little multicollinearity and computing the traditional multiple imputation estimates α̂M I . 5. Drivers of Animal Movement We now provide some examples showing how a range of hypthesized drivers of movement could be modeled within the CTDS framework. Following Hooten et al. (2010), we consider two distinct categories for drivers of movement from cell Gi to cell Gj : static drivers ({pki , k = 1, 2, . . . , K}) which are determined only by the characteristics of cell Gi , and dynamic drivers ({qlij , l = 1, 2, . . . , L}) which vary with direction of movement. Under a time-varying coefficient model for each driver, the transition rate (7) from cell Gi to cell Gj is ( ) K L X X λij (β(t)) = exp β0 (t) + pki βk (t) + qlij βl (t) (15) k=1 l=1 where β0 (t) is a time-varying intercept term, {βk (t)} are time-varying effects related to static drivers of movement, and {βl (t)} are time-varying effects related to dynamic drivers of movement. We consider both static and dynamic drivers in what follows. 5.1 Static (Location-Based) Drivers of Movement Hooten et al. (2010) denote location-based, non-directional drivers of movement as static drivers of movement. Static drivers of movement can be used to examine differences in animal movement rates that can be explained by the environment an animal resides in. In the CTDS context, static drivers would be covariates dependent only on the characteristics of the cell where the animal is currently located. Large positive (negative) values of the corresponding βk (t) would indicate that the animal tends to transition quickly (slowly) from a cell containing the cover type in question. 285 �5.2 Dynamic (Directional) Drivers of Movement In contrast to static drivers, which describe the effect that the local environment in which the animal resides has on movement rates, dynamic drivers of movement (Brillinger et al., 2001; Hooten et al., 2010; Hanks et al., 2011) capture directional selection by the individual. A dynamic driver of movement is defined by a vector which points toward (or away) from something that is hypothesized to attract (or repel) the animal in question. Let vl be the vector corresponding to the l-th dynamic driver of movement. In the CTDS model for animal movement, the animal can only transition from cell Gi to one of its neighbors Gj : j ∼ i. Let wij be a unit vector pointing from the center of cell Gi in the direction of the center of cell Gj . Then the covariate qlij relating the l-th dynamic driver of movement to the transition rate from cell Gi to cell Gj is the dot (or inner) product of vl and wij : qlij = vl0 wij . Then plij will be positive when vl points nearly in the direction of cell Gj , negative when when vl points directly away from cell Gj , and zero if vl is perpendicular to the direction from cell Gi to cell Gj . 5.3 Examples We now provide multiple examples of drivers of movement to illustrate the range of effects that can be modeled using this framework. 5.3.1. Overall Movement Rate The intercept term β0 (t) in (15) can be seen as a static driver of movement in which p0i = 1 for every cell Gi ∈ G. This intercept term controls the animal’s overall rate of transition from any cell, and thus models the animal’s overall movement rate. Allowing the intercept parameter β0 (t) to vary over time could reveal changes in activity levels over time. For example, we might expect β0 (t) to be larger at night for nocturnal species and smaller during the day. 5.3.2. Movement Response to Land Cover Types Indicator variables could be used to examine how animal movement differs between different landscape cover types (e.g., forest vs. plains) by setting pki = 1 for each cell Gi that is classified as containing the k-th cover type. As in the case of the static intercept, 286 �allowing the parameter βk (t) related to the k-th cover type to vary over time can reveal variation in an animal’s movement pattern through the cover type. For example, an animal may move quickly through open terrain during the day, but may move more slowly through the same terrain at night. 5.3.3. Environmental Gradients Animals may use environmental gradients for navigation. For example, a mule deer might move predominantly in the direction of increasing elevation during a spring migration (e.g., Hooten et al., 2010), or a seal might follow gradients in sea surface temperature to navigate toward land (e.g., Hanks et al., 2011). Such effects can be modeled by including a dynamic driver of movement in (15) defined by a gradient vector vl which points from the center of cell Gi in the direction of steepest increase in the covariate xl . Positive values of βl indicate that the animal moves generally towards cells with higher values of xl , while negative values of βl indicate that the animal moves generally towards cells with lower values of xl . 5.3.4. Activity Centers Many animals exhibit movement patterns that are centered on a location in space. This central location may be temporary, such as a kill site for a predator (e.g., Knopff et al., 2009), or more permanent, such as a den for a central place forager (e.g., Hanks et al., 2011; McClintock et al., 2012). This concept is the basis for the relatively new class of spatial capture-recapture models (e.g., Royle and Young, 2008). Movement around an activity center can be modeled in the CTDS framework by including a dynamic driver of movement in (15) defined by a vector vl which points from the center of cell Gi to the location of the activity center. Then a positive value for βl would indicate that the animal is generally drawn toward this activity center. If the activity center is considered to be temporary (such as a kill site for a predator), than a time-varying-coefficient model should be used. The variable selection obtained through the lasso estimate can indicate the range of time in which the animal’s movement is centered around the activity center. If the activity center is considered to be permanent through the duration of the study, a varying-coefficient model may not be needed. Under the likelihood-based specification of the CTDS model for animal movement, it is necessary to specify the locations of all hypothesized activity centers beforehand. In Section 6, we show an example of the specification of hypothesized activity centers (potential kill sites for mountain lions) using the original telemetry data. If a Bayesian formulation of the CTDS model were used, then the location of hypothesized activity centers could be random, and inference could be made on their locations jointly with inference on the movement parameters, as in spatial capture-recapture models (e.g., Royle and Young, 2008). 287 �5.3.5. Conspecific Interaction An animal’s movement patterns can be greatly affected by interaction with conspecifics. For example, one animal could follow the trail left by another animal, two animals could avoid one another by changing course when they become close enough to sense the other animal, or a pair of animals could maintain proximity as they move together across the landscape. While there are many possible approaches to modeling such dependence in behavior, we choose to model each of these interactions through the inclusion of dynamic effects in the CTDS modeling framework. For example, a dynamic driver could be included in the movement model for one animal that is defined by a vector pointing to the current location of another animal to examine whether the animal being modeled is attracted to (βl > 0) or avoids (βl < 0) the conspecific. 5.3.6. Directional Persistence The CTCRW model of Johnson et al. (2008) is based on a correlated random walk model for velocity that allows for directional persistence in animal movement. So far, we have assumed that each discrete movement step in our CTDS model is independent, but this assumption is not met if the animal exhibits any directional persistence. To account for directional persistence in the CTDS approach, we use an autoregressive approach by including a dynamic driver of movement at each discrete movement step that is defined by a vector pointing in the direction of the previous move. If the animal moved west in the previous discrete movement step, then the autoregressive vector for the next step points west as well. Positive values of the β related to this dynamic driver of movement indicate that the animal is likely to maintain its direction of movement over time. 5.4 Spatial and Temporal Scale The choice of scale for a study can greatly influence results (e.g., Boyce, 2006). When speaking of the scale of a study, one could look at the grain, or resolution, at which the process is modeled, or the extent (coverage) over which the process is modeled. The spatial and temporal extent of a study of animal movement are determined by the telemetry data and the posterior predictive path distribution [S̃|S]. However, when implementing the CTDS approach, the researcher must make three choices pertaining to the grain or resolution: (1) the temporal scale at which the CTCRW movement path of the animal is sampled, (2) the spatial scale of the grid over which the discrete-space movement will be modeled, and (3) the temporal scale of the varying coefficient model, which is determined by the number and resolution of spline knots in the spline basis expansion. As the CTCRW model of Johnson et al. (2008) is a continuous-time model, we recommend sampling from the movement path at as fine an interval as is feasible. In practice, this will be limited by computational resources and the size of the study. The temporal 288 �resolution needs to be fine enough that realizations from the posterior predictive path distribution [S̃|S] are quasi-continuous and adequately capture the residence time τ in each grid cell in the CTDS representation of the movement path. The choice of spatial resolution of the raster grid on which the CTDS process occurs implicitly specifies a time scale at which the movement process is modeled. Coarser spatial resolution (larger grid cells) will correspond to longer residence times τ in the CTDS mode. The spatial resolution should be chosen so that the time scale at which an animal transitions from one grid cell to another is a time scale at which the animal in question can make meaningful choices about movement and resource selection. The time scale implicit in the choice of spatial resolution can be examined by plotting a histogram of the residence times in the CTDS representation of the movement path. If the lasso penalty is used, then it is common to choose a saturated spline basis expansion in the varying-coefficient model, where one spline knot is specified at each data point in time. We recommend specifying a spline basis expansion with knots at a similar temporal resolution to the temporal resolution of the telemetry data. The lasso penalization will shrink the overparameterized expansion to a more-parsimonious model that best fits the data. While a finer temporal resolution could be used, the posterior predictive path distribution is unlikely to show changes in behavior at time scales smaller than the time scale of the original data. Using a coarser temporal resolution will force β(t) to be smooth. This would imply that changes in animal behavior are gradual and occur at time scales larger than the time scale of the data. 6. Example: Mountain Lions in Colorado We illustrate our CTDS random walk approach to modeling animal movement through a study of mountain lions (Puma concolor ) in Colorado, USA. As part of a larger study, a female mountain lion, designated AF79, and her subadult cub, designated AM80, were fitted with global positioning system (GPS) collars set to transmit location data every 3 hours. We analyze the location data S from the first 18 days of location information for these two animals (Figure 2). We fit the CTCRW model of Johnson et al. (2008) to both animals’ location data using the ‘crawl’ package (Johnson, 2011) in the R statistical computing environment (R Development Core Team, 2012). Ten imputations from the posterior distribution of the quasi-continuous path distribution [S̃|S] were obtained at one-minute intervals. The result is a quasi-continuous path at extremely fine temporal resolution for each imputation. For covariate data, we used a landcover map of the state of Colorado created by the Colorado Vegetation Classification Project (http://ndis.nrel.colostate.edu/coveg/), which is a joint project of the Bureau of Land Management and the Colorado Division of Wildlife. The map contained gridded landcover information at 100m square resolution. Figure 3 289 �Figure 2: Telemetry data for a female mountain lion (AF79) and her male cub (AM80). A static covariate was defined by landcover that was not predominanty forested (a). Potential kill sites were identified, and a dynamic covariate defined by a vector pointing toward the closest kill site (b) was also used in the CTDS model. 290 �Figure 3: Residence times in each 100m-square grid cell in the continuous-time discretespace representation of the movement path of a male mountain lion (AM80). shows a histogram of the residence times τ in each grid cell in the CTDS representation of the movement path of AM80. The area traveled by the two animals in our study was predominantly forested. To assess how the animals’ movement differed when in terrain other than forest, we created an indicator covariate where all forested grid cells were assigned a value of zero, and all cells containing other cover types, including developed land, bare ground, grassland, and shrubby terrain, were assigned a value of one (Figure 2a). This covariate and an intercept covariate were used as static (locational) covariates in the CTDS model for both animals. For each animal, we created a set of potential kill sites (PKS) by examining the original GPS location data (Figure 2). A location was classified as a PKS if two or more GPS locations were found within 200m of the site within a six-day period (Knopff et al., 2009). We then created a covariate raster layer containing the distance to the nearest PKS for each grid cell (Figure 2). A dynamic (directional) covariate defined by a vector pointing towards the nearest PKS was included in the CTDS model for both animals. To examine how the movement path of the cub AM80 affected the movement path of 291 �the mother AF79, we included a directional covariate in the CTDS model for AF79 defined by a vector pointing from the mother’s location to the cub’s location at each time point. Similarly, we included a directional covariate in the CTDS model for AM80 defined by a vector pointing from the cub’s location to the mother’s location at each time point. For each animal, we also included a directional covariate pointing in the direction of the most recent movement at each time point. This covariate measures the strength of correlation between moves, and thus the strength of the directional persistence shown by the animal’s discrete-space movement path. As we are assuming an underlying correlated movement model (the CTCRW model of Johnson et al. (2008)), we expect the CTDS movement to be correlated in time as well. To allow for varying behavior over time, we used a varying-coefficient model for each covariate in the model. For all covariates except the directional covariate related to directional persistence, we used a B-spline basis expansion, with regularly spaced spline knots at hourly intervals. For the covariate related to directional persistence, we used a B-spline basis expansion with regularly spaced knots at 3-hour intervals. By choosing a coarser temporal resolution in our varying-coefficient model for directional persistence than for our other covariates we imply that the directional persistence should vary at larger time scales than the animal’s response to other covariates, which drive animal movement at finer time scales. We fit the CTDS model for each path using the ‘glmnet’ R package (Friedman et al., 2010), using a lasso penalty, with tuning parameter chosen to minimize the average squared error of the fit in a 10-fold cross-validation. 6.1 Results The time-varying results for the static and dynamic drivers of movement for AF79 are shown in Figure 4, with the corresponding results for AM80 shown in Figure 5. As we used a lasso penalty, we can only obtain point estimates (confidence intervals are unavailable) of the time-varying effects {β(t)}. A comparison of the differences between the results for AF79 and AM80 yields some insight into how the movement patterns of these two animals differ. The static intercept effect measures the animal’s general movement rate over time. Figure 4(a) and Figure 5(a) show the time-varying deviation from the grand mean for each animal. The static intercept for both lions tends to be higher during nighttime hours than during the day, indicating higher overall rates of movement during nocturnal hours. The static (location-based) response to non-forrested terrain (Figure 4b and Figure 5b) is zero for much of the study window for both AF79 and AM80. Forested terrain makes up over 90% of the study area, thus the mountain lions encounter different terrain infrequently. 292 �Figure 4: Time-varying results for the static and dynamic covariates in the continuous-time discrete-space model for a female mountain lion (AF79). 293 �Figure 5: Time-varying results for the static and dynamic covariates in the continuous-time discrete-space model for a male mountain lion (AM80). 294 �The male cub (AM80) moves through non-forested terrain at a relatively high rate of speed, while the female’s response is mixed. The male cub (AM80) has a very consistent positive response to the dynamic covariate pointing toward the nearest kill site (Figure 5c), indicating that much of the male’s movement resembles a random walk centered on an attractive central location (a PKS). In contrast, the female’s response to this covariate (Figure 4c) is less consistent, indicating that the female is less tied to the PKS than her cub. The results for the dynamic covariate pointing towards the female AF79 in the analysis of the cub AM80 (Figure 5d) show that the cub is drawn strongly towards the female during a number of brief periods during the observation window. The female’s response to her cub (Figure 4d) indicates more heterogeneity as the female alternately returns to her cub and moves away from him. The results for the autoregressive parameter (Figure 4e and Figure 5e) indicate that correlated movement is the norm for both animals. The magnitude of the autoregressive parameter is greater for the female (Figure 4e) than for the male (Figure 5e), indicating that the female may have a greater tendency for directed movements than the male. The CTDS movement paths are based on the CTCRW model of animal movement, which results in correlated movement paths. The inclusion of this autoregressive parameter is meant to account for the correlation in the CTDS path representation of the underlying correlated CTCRW movement path. 7. Discussion While we have couched our CTDS approach in terms of modeling animal movement, we can also view this approach in terms of resource selection (e.g., Manly, 2002). Johnson et al. (2008) describe a general framework for the analysis of resouce selection from telemetry data using a weighted distribution approach where an observed distribution of resource use is seen as a re-weighted version of a distribution of available resources, and the resource selection function (RSF) defines the preferential use of resources by the animal. Warton and Shepherd (2010) and Aarts et al. (2012) describe a point-process approach to resource selection that can be fit using a Poisson GLM, similar to the CTDS model we describe here. In the context of Warton and Shepherd (2010), the CTDS approach can be viewed as a resource-selection analysis with the available resources at any time defined as the neighboring grid cells. The transition rate (15) of the CTDS process to each neighboring cell contains information about the availability of each cell, as well as the RSF that defines preferential use of the resources in each cell. It is notable that the entire analysis in Section 6 takes less than five minutes from start to finish using a modest computer with 4 GB of memory and a 1.67 GHz quad-core processor. This increase in computational efficiency relative to the approaches of Johnson et al. (2008), 295 �Hooten et al. (2010), Hanks et al. (2011), and McClintock et al. (2012) allows for inference on complex behavior at finer temporal resolution than has been possible previously. To make our CTDS approach accessible to practitioners, we have created an R-package (‘ctds’) that contains R-code to fit the CTDS model using multiple imputation as described in Sections 2-4. A script file contained in the ‘ctds’ package allows for the re-analysis of the telemetry data of the two mountain lions analyzed in Section 6. This R-package can be downloaded from the first author’s website (http://www.stat.colostate.edu/˜hanks). The CTDS approach to modeling animal movement is flexible, and can be extended using standard approaches for GLMs. For example, if population-level inference is desired, the movement paths from multiple animals could be analyzed jointly, with population-level parameters in the GLM being shared by all animals. Similarly, interaction terms could be included in the model by including multiplied covariates in the design matrix. Fitting movement models in a GLM framework allows for many natural extensions with little additional effort. The use of dynamic (directional) drivers of movement has a long history. Brillinger et al. (2001) model animal movement as a continuous-time, continuous-space random walk where the drift term is the gradient of a “potential function” that defines an animal’s external drivers of movement. Tracey et al. (2005) use circular distributions to model how an animal moves in response to a vector pointing towards an object that may attract or repel the animal. Hanks et al. (2011) and McClintock et al. (2012) make extensive use of gradients to model directed movements, and movements about a central location. In our study of mountain lion movement data, we used directional drivers of movement to model conspecific interaction between a mother (AF79) and her cub (AM80). Interactions between predators and prey could also be modeled using dynamic covariates defined by vectors pointing between animals. Some movements based on memory could also be modeled using dynamic covariates. For example, a dynamic covariate defined by a vector pointing to the animal’s location one year prior could be used to model seasonal migratory behavior. The ability to model both static and dynamic drivers of movement make the CTDS framework a flexible and extensible framework for modeling complex behavior in animal movement. References Aarts, G., Fieberg, J., and Matthiopoulos, J. (2012). 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The Annals of Applied Statistics 4, 1383–1402. Yuan, M. and Lin, Y. (2006). Model selection and estimation in regression with grouped variables. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 68, 49–67. 298 �APPENDIX VI Front-Range Cougar Research Winters, 2011–2012 & 2012–2013 The Use of Lures, Hair Snares, and Snow Tracking as Non-Invasive Sampling Techniques to Detect and Identify Cougars CSU - Colorado Cooperative Fish and Wildlife Research Unit & Colorado Parks and Wildlife Kirstie Yeager Bill Kendall Mat Alldredge Research Proposal July 31, 2012 299 �The Use of Lures, Hair Snares, and Snow Tracking as Non-Invasive Sampling Techniques to Detect and Identify Cougars Kirstie Yeager, M.S. student, CSU Introduction To set harvest quotas, evaluate management practices, and understand the dynamics of predatorprey systems, it is desirable to have reliable estimates of population size. However, answering occupancy and abundance questions regarding carnivores has long been a challenging task (Ke̒ry et al. 2011). In general, carnivores are elusive and occupy large home ranges that often vary in size across the population (Anderson et al. 2004). As a result, it can be very difficult and expensive to obtain a representative sample that is large enough to produce a reliable estimate (Ruell et al. 2009). Despite the cost, it is essential that managers have accurate population estimates that can support management decisions (Dreher et al. 2007, Immell and Anthony 2008). Here, we focus on cougars (Puma Concolor). In the state of Colorado, cougars are a game species; and it is imperative that their population be responsibly managed. Wildlife personnel are also tasked with managing increasing cougar-human conflict in residential and recreational areas. Developers are pushing west into previously undisturbed habitat; pet loss complaints and depredation claims continue; and each year, municipalities acquire more land to be made available to the public. Abundance estimation is a primary objective of the sponsoring agency, Colorado Parks and Wildlife (CPW). A common way to estimate populations within an ecological context is to sample using capture-recapture, or mark-resight, methods (Pollock et al. 1990). Cougars have been sampled using a variety of strategies, some in need of further testing. Abundance estimates are then generated using models like the 2-occasion Lincoln-Peterson estimator (Williams et al. 2002) or the Huggins model (Huggins 1989). Generally, mark-resight models are bound by assumptions like closure and equal probability of capture/detection (Otis et al. 1978). However, in wildlife studies, detection is often less than certain (<1) and variable across the population (Link 2003). Before attempts can be made at estimating the population, the probability of detection must first be assessed and factors influencing detection should be explored. A thorough understanding of detection attributes within the population of interest will provide CPW with foundational information they need to estimate the population. Mark-resight analysis requires that animals first be detected and identified through sampling procedures requiring their capture or through noninvasive means where direct human contact is not needed (Pauli et al. 2010). Due to carnivore ecology and behavior, trapping and handling practices are generally costly and difficult making noninvasive genetic sampling methods (NGS) an attractive alternative (Long et al. 2008). In addition, NGS has other benefits in that it minimizes stress and disturbance to the study animals; and when successful, it allows a larger sample size at a lower cost (Pauli et al. 2010). Herein, we will consider noninvasive methods. Researchers have tested several noninvasive techniques, some quite creative, on a variety of carnivores to detect and count individuals. Track surveys have been used with success in occupancy studies but fall short in their ability to produce accurate abundance estimates (Diefenbach et al. 1994, Sargeant et al. 1998, Wilson and Delahay, 2001, Hayward et al. 2002, Choate et al. 2006, Gompper et al. 2006). However, when track surveys are combined with the collection of genetic material, species identification can be confirmed (McKelvey et al. 2006) and/or individuals identified, allowing for abundance estimates using mark-recapture analysis (Ulizio et al. 2006). Cameras, lures, and/or hair snares have also been used to survey cougars (Long et al. 2003, Choate et al. 2006, Sawaya et al. 2011), lynx (McDaniel et al. 2000, Schmidt and Kowalczyk 2006), bobcats (Harrison 2006), ocelots (Weaver et al. 2005), multiple felids (Harrison 1997, Downey et al. 2007), and carnivore communities (Sargeant et al. 1998, Long et al. 2007, Ruell and Crooks 2007, Castro-Arellano et al. 2008, Crooks et al. 2008). Though 300 �dozens of lures have been tested along with several novel hair-snaring devices, results have been erratic, suggesting no single method superior above all others. With regard to cougars, the potential of NGS has not been realized. Inconsistent results have left the techniques needing further testing and refinement. In past studies involving attractants, almost all have primarily used scents. Few surveys have incorporated auditory calls despite the fact that felids may exhibit a greater response to auditory and visual lures than to olfactory stimulus (Chamberlain et al. 1999). Further testing of this component is needed to assess whether calls will increase detection at the sites. Furthermore, McDaniel et al. (2000) described a hair-snaring device that consists of a board with a scent-lure-covered carpet pad and nails protruding through it nailed to a tree. Harrison (2006), McKelvey et al. (2006), Schmidt and Kowalczyk (2006), Long et al. (2007), and Sawaya et al. (2011) tested similar mechanisms on a variety of felids. These designs snagged hair part of the time though the quality of the hair and whether or not the hair was from the target species was inconsistent. Modifications in snare designs are needed to improve the reliability of the hair snagged, thus increasing the likelihood of obtaining a usable sample. Barbed wire is an alternative hair-snaring mechanism to traditional scratch-pad designs. Barbed wire has long been used to collect hair samples from grizzly and black bears (Woods et al. 1999, Mowat and Strobeck 2000, Poole et al. 2001, Boersen et al. 2003, Belant et al. 2005, Boulanger et al. 2006, Dreher et al. 2007, Kendall et al. 2008, Settlage et al. 2008, Proctor et al. 2010). Ebert and Schulz (2009) used barbed wire to snag hair from wild boar; and Belant et al. (2007) obtained hair from white-tailed deer. We could not find a study that used barbed wire in an attempt to snag hair from a felid species. However, we collected hair suspected to be cougar from a barbed-wire fence during a pilot snow-tracking survey. Snow tracking is another NGS method that has been implemented in a variety of cougar studies. Seidensticker et al. (1973) applied winter tracking to evaluate movement patterns relative to kill sites, reproductive status, and topography and vegetation. Hemker et al. (1984) used snow tracking to locate cougar sign needed in population estimation. Snow tracking can also be used to facilitate DNA sample collection where hair or scat found along a track can be genotyped to yield an individual identification (McKelvey et al. 2006, Ulizio et al. 2006). Sawaya et al. (2011) reported winter tracking cougars under favorable conditions returned hair samples 80% of the time after tracking on average 1.09 km. However, because success is largely dependent upon optimal snow conditions and timing after snow fall (Squires et al. 2004), this method may only be effective in specific geographic regions. Its utility has not been tested on the Front Range. Winter tracking may prove useful as a secondary method of detection in capture-recapture surveys. Utilizing multiple detection methods can reduce problems with bias due to the capture variation that arises when a single survey method is used (Noyce et al. 2001). For example, individuals that develop trap shyness to established sites can be detected alternatively via track surveys. Wildlife managers have used additional resources, such as animals collected during hunter harvest, as another ‘occasion’ in a detection history of a capture-recapture analysis (Garshelis and Visser 1997, Diefenbach et al. 2004, Nicolai et al. 2005, Dreher et al. 2007). Applying a secondary collection method, alternative to capture, can also reduce costs (Pauli et al. 2010) as the capture and handling of carnivores is often of great expense to federal and state agencies (Long et al. 2003, Immell and Anthony 2008). Eliminating or accounting for genotyping errors is essential in satisfying the assumption of known identity in mark-recapture models. Failure to do so can result in an over or under estimation of abundance depending upon the type of error (Lukacs and Burnham 2005). Hair and scat collected using NGS methods typically have a low quality and quantity of DNA (Broquet et al. 2007). Inherently small quantities of DNA are susceptible to sample contamination and degradation in the field and in the 301 �laboratory (Taberlet and Luikart 1999). The resulting poor DNA samples may fail to amplify or display genotyping errors by allelic dropout or false alleles exhibiting false homozygotes and heterozygotes respectively (Buchan et al. 2005). Ernest et al. (2000) report an 8% allelic dropout rate during fecal amplification compared to a < 1% error rate in blood and muscle assays. Strict data collection and laboratory protocols can minimize genotyping errors (Taberlet et al. 1999). When possible, errors can be observed by comparing NGS results to more reliable profiles generated through blood and tissue analyses (Ernest et al. 2000, Mills et al. 2000, Mondol et al. 2009). If errors are found, it may be necessary to run multiple tests on a single sample (Taberlet et al. 1999). DNA can be used to both confirm species and identify individuals (Woods et al. 1999, Ke̒ry et al. 2010). For our purposes, cameras should confirm species identification. Individuals are typically identified using nuclear DNA as it has a high level of variability needed to differentiate individuals (Menotti-Raymond and O’Brien 1995). Menotti-Raymond et al. (1999) developed a genetic linkage map for the domestic cat containing 253 microsatellite loci. These loci can be used in the analysis of other felids. How many and which microsatellites are used depend upon the degree of genetic diversity between individuals in the population sampled (Woods et al. 1999). Menotti-Raymond et al. (1995), Culver et al. (2000), Ernest et al. (2000), Anderson et al. (2004), and Mondol et al. (2009) reported between 7 and 12 loci with a high degree of variability was adequate to express enough heterozygosity to differentiate individuals in their respective studies. In summary, many attempts have been made to realize NGS methods capable of producing reliable responses. Up until now, results have been mixed. It is our goal to develop noninvasive field methods and apply laboratory techniques that will reliably detect and identify cougars (Chapter 1). If we succeed, we will apply this technique to a population of known individuals and estimate a detection probability (Chapter 2). We will also address closed mark-recapture model assumptions and investigate potential sources of capture variation (Chapter 3). Finally, we will evaluate whether snow tracking as a means to locate genetic material is a useful tool given the snow conditions on the Front Range (Chapter 4). Chapter 1. Evaluation of attractants and hair-snaring mechanisms Our objective is to further evaluate NGS methods to find a technique that is adequate for detecting a cougar and obtaining a genetic sample. We conducted pilot research last winter (February – April 2012) testing scent lures and predator calls in conjunction with two hair-snaring devices, a scratch pad similar to that of McDaniel et al. (2000) and a novel hair-snaring mechanism that used bait. Our preliminary results indicate that calls are successful attractants; but we were not able to obtain a genetic sample from either hair-snaring mechanism. This winter (November 2012 – April 2013), we will repeat our lure assessment in an attempt to solidify our findings regarding the utility of calls. We will also test an alternative hair-snaring technique that uses barbed wire. Methods - Pilot We first considered home range information for collared cougars monitored by Colorado Parks and Wildlife (CPW) and selected an area 1200 km² west of Boulder from the northern Boulder County boundary to I-70 and west of Highways 36 and 73. Several individuals with size-varying and overlapping home ranges resided in this area. Because the average female home range is 100 km² (Alldredge unpublished data), we subdivided the 1200 km² area into twelve 100 km² quadrats and selected 4 to survey due to these areas having the highest densities of collared individuals. We then partitioned each primary quadrat into twenty-five 4 km² parcels. After considering private property limitations, we randomly chose 20 parcels (4 or 6 in each primary quadrat). Finally, we selected exact site locations based on areas of low human activity, specific landscape features (ridgelines, drainages, game trails, canopy cover), and restrictions imposed by city and county officials. It should be noted that most of the area contained within 1 randomly selected quadrat was closed due to raptor nesting activity. Therefore, 302 �we placed our site to the south in the neighboring quadrat. At the conclusion of the season, it was discovered that miscalculations were made in the placement of 2 other sites. One site was placed in error 427 m to the east and the other 139 m to the north of the intended quadrats. We established 4 different types of sites. All sites consisted of a baited hair snare, a scratch pad with catnip, a visual lure (aluminum pie pan), and a camera. The sites varied by whether or not they included a scent lure, a call, neither, or both (Table 1). Components were assigned randomly except when permit restrictions prohibited us from putting calls at certain sites resulting in a slightly uneven distribution (6, 4, 5, and 5). Based on recommendations by lynx researchers (G. Merrill personal communication), we chose Pikauba® as our scent lure in our preliminary study design. However, Pikauba® was not successful in eliciting a rubbing response during the first observed cougar visits. Therefore, we added the scent, Canine Call®, to sites chosen to have scent lures. We secured calls (Wasatch Wildlife Product® FurFindR®) to a tree at approximately head height. The manufacturer programmed calls to transmit a 5 second distressed fawn or fox recording on 30 second intervals. These calls were also equipped with light sensors rendering them dormant during daylight hours. At each site, we placed an infrared motion-sensor camera (Reconyx® PC85 Rapidfire® or PC800 Hyperfire®) programmed to take 5 photos in rapid succession when triggered. To further evaluate the utility of the attractants, we positioned a second camera (Cuddeback® Capture®) within 18 – 102 m of 7 sites (2, 1, 2, and 2). The camera placed at a distance of 102 m was located across a drainage where the visual flasher was still visible. We chose locations in areas where animals were likely to pass (saddles, game trails, old roads, ridgelines) and at a distance where, in our opinion, the lure(s) should be effective attractant(s). All sites were checked for activity on average every 5 – 6 days. As necessary, baits and scents were replenished and new batteries were placed in cameras and calls. Visual flasher Scratch pad w/catnip Baited hair snare Scratch pad w/scent Animal distress call Camera 1 X X X X X 2 X X X 3 X X X X X X 4 X X X X X X Table 1. All site components for the 4 site types (scent, call, neither, and both) established in random locations. In conjunction with lures, we tested 2 hair-snare designs. We constructed a hair-snaring mechanism described as a metal mesh (1”) cube (25 cm edge) open on one end. We wired a 0.1 – 0.2 kg piece of deer meat in the back of the snare. To snag hair, we attached a 20 cm spring and a 13 cm barrel cleaning brush (Figure 1). To minimize access to the bait by non-target species, we secured the snares to trees at an initial height of 70 – 95 cm using cable and U clamps. After observing the first few cougar responses, we lowered the snares to 40 – 70 cm. After further observations, we lowered the snares all the way to the ground. The other snare was a scratch pad design. This mechanism consisted of a board (14 X 14 cm), cotton batting or a carpet swatch, and a piece of metal altered to snag hair (Figure 2). We placed one scratch pad with catnip oil and dried catnip at each site. We applied the scent lure, Pikauba® then Canine Call®, to another and placed it at selected sites. Scratch pads were nailed to a tree at an average height of 55 cm. To supplement the data collected at the 20 random sites, we targeted individual cougars by placing attractants and a camera in the vicinity of a collared animal. We established 4 sites with scent lures, a call, and a flasher. These sites were active for 3 – 6 days. Late in the season, we established 4 additional sites to test a modified site design. At these locations, we used calls and bait as the attractants. These sites were active for a longer period (5 – 16 days). 303 �Brus Sprin Figure 2. Catnip, Pikauba®, and Canine Call® were applied to scratch pads. Figure 1. Bait was wired in the back corner. In attempting to obtain the bait, the cougar would flex the spring catching hair and contact the barrel brush. Results – Pilot Our preliminary findings clearly indicate that calls are effective attractants. At the random sites, we observed 23 detections by at least 13 individuals. All but 2 occurred at sites with calls (Table 2). In addition, we observed 12 detections at the 8 selectively placed sites. It should be noted that 11 of the 12 visits occurred several hours or days after the site was established indicating that the cougars were not immediately drawn in. Furthermore, some sites were visited by a different cougar other than the one it was intended to attract. Photographic evidence also supports cougar interest in calls. Photos documented cougars looking towards calls and attempting to climb trees in pursuit of the devices. On 3 occasions, we observed the same cougar carrying off a call thought to be securely cabled to a tree. Contrary to calls, we have no data to suggest the scent lures we employed are successful in attracting cougars. We did not document a single rubbing response to any of the 20 scratch pads containing catnip nor the 11 scratch pads with Pikauba® or Canine Call®. In addition, we compared photos recorded on the 7 ancillary cameras with cougar activity observed at the sites. These cameras detected 3 cougars as they moved through the area. Two were not observed at the corresponding lure site (~18 m away) providing evidentiary support for the futility of the attractants (Canine Call®, catnip, and bait). Due to a small sample size of 7, results are far from conclusive but suggest, at the very least, placing a supplementary camera in a high traffic area near a site may be a useful tool in assessing the value of a lure. Finally, our hair-snaring mechanism containing the bait was ineffective. Cougars showed little interest in the meat wired in the back of the snare. In conclusion, we determined that calls were effective in attracting a cougar to a site but our attempts to entice a response necessary to obtain a sample failed. 304 �Detections 2nd Cameras 2nd Camera Detections 5.03 1 2 0 41 5.08 1 2 2 4 37 5.87 9 1 0 Bait, scent, & call 5 49 5.10 12 2 1 Totals and Averages 20 41 5.23 23 7 3 # Days Active Ave. Interval Checked Bait only 5 36 Bait & scent 6 Bait & call Table 2. This table summarizes the 20 randomly placed locations and includes the number of each site established, the average period each site was active, the average interval that each was checked, the number of detections per site type, the number of secondary cameras placed near each type, and the number of secondary camera detections. Methods – Winter 2012/2013 To further evaluate attractants, our site selection criterion remains unchanged. We will use the same four 100 km² quadrats subdivided into twenty-five 4 km² parcels. But, we chose to undergo a new random selection process and selected a fresh set of 4 parcels in each quadrat. We repeated this process 3 times as we will move the lure sites to a new location within the quadrat every 4 – 5 weeks. The criteria for choosing exact site locations will also stay the same (based on human use, landscape features, and imposed restrictions). Consistent with our pilot season, we will have 4 different types of sites (Table 3). However, we will focus on specific attractants by eliminating components we consider to be futile (visual lures and catnip). We will further modify the site configuration to accommodate the application of a new hairsnaring technique. All sites will have a natural, animal-scent component (bait) consisting of deer meat, blood, or hide. The sites will vary by whether or not they contain a scent lure (Pikauba®), a call (fawn distress), neither, or both. At sites designated to have scents, we will place Pikauba® near the base of a tree and 150 - 180 cm up in the same tree to aid in scent dispersal. Where applicable, we will cable the calls 30 – 60 cm up from the base of a tree. We will place the bait near the base next to the scent and/or call. We will then brush in the area surrounding the tree making most of the perimeter impenetrable. An obvious entry way will remain (Figure 3). Based on the terrain and configuration of the vegetation, we will stretch lines of barbed wire across the open entry camouflaging it with sticks, leaves, and other natural materials. The height of the wire will depend upon whether we desire a cougar to step over, under, or through 2 strands. Wire placement may be modified as the season progresses. In view of the entrance, we will secure an infrared motion-sensor camera (Reconyx® PC85 Rapidfire® or PC800 Hyperfire®) programmed to rapidly take 5 photos when triggered. In addition, we will further test the utility of a secondary camera (Cuddeback® Capture®) by deploying 8 additional cameras (2 at each of the 4 site types) in high traffic areas and within 20 – 50 m of lure sites. 305 �Bait Scent, Pikauba® Fawn Distress Call 1 X 2 X X 3 X X 4 X X X Table 3. All sites will have bait. In addition, one site will have Pikauba®, one site will have a call, and one site will have both. Figure 3. Last winter, we were able to test the modified site design, minus barbed wire. We placed a predator call and deer meat near the base of a tree and outlined the perimeter with thick brush leaving a single entry point. We positioned a camera towards the entry way. A cougar was observed entering and exiting as intended. The horizontal stick above its back represents a possible placement for a strand of barbed wire. To limit the possibility of sample contamination and degradation, sites will be checked every 5 – 7 days. We will consider all hair on a single barb as one sample (Poole et al. 2001, Dreher et al. 2007). Hair will be removed using sterile tweezers and placed in a small paper envelope. Paper envelopes will then be put in a plastic bag with a desiccant and stored at room temperature (Taberlet and Luikart 1999, Roon et al. 2003). Barbs will be re-sterilized by passing a flame under them to burn any remaining material (Kendall et al. 2008, Settlage et al. 2008). In addition, we will use photographic evidence to confirm individual identification and the presence of multiple animals. When sites are checked, we will also replenish the scent and bait and change the batteries in cameras and calls. At the conclusion of the survey, we will consider data from 4 sampling periods, each 4 – 5 weeks in length. The first occurred during the pilot season in 2012 (March 1 – 31). The other 3 will transpire this winter through the following time intervals: November 17 – December 20, December 21 – January 23, and January 24 - February 26. We will evaluate a total of 68 sites (approximately 17 of each type). The utility of the attractants will be judged by the quantity of detections and by comparing detection probabilities. If a cougar is documented by photo at the site, the attractant(s) will be counted once (per day per cougar). Detections will be totaled relative to each of the 4 site types. In addition, our analysis will state the total count at sites with Pikauba® and the total count at sites where calls were used. 306 �Detection probabilities (p) will also be used to confirm the value of an attractant. p can be estimated as a proportion of the number of detections (n) to the number of available animals (A) using the a simple binomial model; (Williams et al. 2002). We will apply the detection counts described above and determine an individual’s availability status by using secondary camera information and GPS location data. First, animals detected by the secondary camera will be counted as available. The remaining study animals found to be within a specified proximity to the site (500 – 1000 m) will also be counted. Using detection and availability counts, we will estimate the probability that a cougar is detected given that it is available and compare the resulting values. We will evaluate the results of the hair-snaring component by using site-specific photographic evidence as well as assessing the quantity and quality of the hair we collect. Photos will indicate if the animal moved through the site in the manner we intended. To assess quantity, we will conduct a visual evaluation at the time of sample collection. Samples will be scored 1 – 3 (1 indicating < 5 hairs collected on a single barb, 2 indicating 6 – 15 hairs collected, and 3 indicating > 15 hairs collected). Laboratory analysis will judge sample quality through amplification and genotyping error rates. We will process the hair samples at USGS Fort Collins Science Center, FORT Molecular Ecology Lab. When possible, we will extract DNA from 10 hairs (Goossens et al. 1998, Boersen et al. 2003) using Qiagen DNeasy® Tissue Kits (Qiagen Inc., Valencia, CA). We will then genotype each sample using 9 – 12 microsatellite primers shown to have high variability in cougars (Ernest et al. 2000, Sinclair et al. 2001, Anderson et al. 2004). The DNA will be amplified by polymerase chain reaction (PCR) using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). For known individuals, we will compare the resulting genotypes with blood and tissue samples collected by CPW during capture. DNA from blood and tissue is first extracted by personnel at the CPW Foothills Wildlife Research Facility. It is then genotyped using the same microsatellite loci at the USGS lab. We will address genotyping errors and if possible, rerun the samples. Chapter 2. Estimating the detection probability (p) using a noninvasive-sampling technique applied to a known population of cougars Our objective is to estimate a detection probability (p) needed for future population assessments. We will apply a noninvasive-survey technique to a population of cougars on the Front Range and estimate p using a simple binomial model, A is the total number of available animals; n is the number counted per occasion; and p̂ is the estimated probability of detecting an individual given that it is available (Williams et al. 2002). To estimate p, we will use cougars previously captured and collared by Colorado Parks and Wildlife (CPW). The collars applied to these animals are equipped with Global Positioning System (GPS) features. We will monitor cougar location data relative to study sites and consider their availability (A) to be detected. Those detected will be counted (n); and p will be estimated. The simple binomial model is bound by 2 assumptions (Williams et al. 2002). The first assumption is that the fate of all cougars is known. This assumption will be met since we are using a population of marked individuals whose location and mortality status will be known for the duration of the study. The second is that each detection is an independent event. We will place sites far enough apart so that one site should not influence detection at another. 307 �We are investigating detection for the purpose of gaining foundational knowledge that will be necessary in future population assessments. Concurrently, we hope to develop a mark-resight technique capable of producing reliable abundance estimates. Therefore, we also address closed mark-recapture model assumptions. Due to sample contamination and degradation, noninvasive-sampling techniques, similar to those that we will employ, may lead to the assumption violation of misidentification through genotyping errors (Taberlet and Luikart 1999, Lukacs and Burnham, 2005). Because our survey will use a population of known individuals, we can assess this source of error in the lab by comparing the samples we collect noninvasively with archived blood and tissue collected from the animal during the initial capture (Dreher et al. 2007). Another assumption, equal capture/detection, is especially pertinent to our work. It assumes that p is equal throughout all members of the population (White et al. 1982). This is often not the case in wild populations (Pollock et al. 1990). We will further investigate potential sources of capture variation in chapter 3. As suggested by Otis et al. (1978), we will attempt to minimize factors that may induce capture variation through study design. We anticipate trap response (a positive or negative behavioral response to the trapping event) to be one potential source of variation (Pollock et al. 1990). For example after the first few visits, it is possible that a cougar will lose interest in a site upon discovering that the distressed fawn call and deer scent is not a real animal. This ‘trap shy’ response can create positive bias in a population estimate (Williams et al. 2002). Mowat and Strobeck (2000) recommend reducing capture disparity by moving sites throughout the field season. It is our belief that choosing new locations will aid in keeping the sites novel as the efficacy of the lure site relies on provoking curiosity so that a cougar will alter its behavior and approach the site. The success of the hair snare is also dependent upon enticing interest. If in a fresh location, the cougar may once again be tempted to investigate the same fawn call and deer scent. In addition, selecting new locations is likely to accommodate the activity patterns of more animals. This will increase the likelihood that all individuals will come in contact with the sites thus reducing animal-specific heterogeneity (C. Anderson personal communication, Boulanger et al. 2006). February – April 2012, we conducted pilot research testing lures and hair-snaring mechanisms. After evaluating cougar responses, we concluded that applying predator calls to a site designed to use a barbed-wire hair snare could attract an individual and obtain a genetic sample. In short, we will establish lure sites within the range of known cougars to gain insight into the detection process. Methods – Winter 2012/2013 To estimate p, we refined the site selection process employed last year by expanding our sampling effort over a wider geographic range. Our study area remains an approximately 1200 km² area west of Boulder; but for the purpose of estimating p, we will sample the entire area (unlike our pilot season, where we chose four 100 km² areas to sample). The northern boundary is 4 km north of the town of Lyons and follows an arbitrary straight line due west. The southern boundary will follow Highway 6 then Interstate 70. Highway 36 and Highway 93 will define the approximate eastern boundary; and Highway 72 will delineate the west. Colorado Parks and Wildlife (CPW) monitors a higher density of collared animals in the eastern half of this area. Collared animals are an integral component in estimating p. Therefore, we divided the 1200 km² zone into 2 strata, east and west. In choosing individual site locations, we first created a map of the study area using ArcGIS® 10 and over-layed a 2 X 2 km grid. Partial cells around the perimeter were combined with neighboring cells. Next, we applied the Reversed Randomized Quadrant-Recursive Raster (RRQRR) algorithm to randomly select 15 cells in the eastern strata and 6 cells in the western strata for a total of 21 sites having an even spatial distribution (Theobald et al. 2007). Then, we considered access issues in each cell chosen. Cells we considered inaccessible or unusable, possibly due to private property restrictions or high human use, were discarded; and another cell was randomly chosen. To keep the sites novel, we repeated the selection process without replacement 3 more times as it is our intention to move the sites 4 times throughout the season. Finally, 308 �we will select exact site locations to correspond to areas known to be favorable cougar habitat: ridgelines, drainages, game trails, treeline edges, and saddles (K. Logan personal communication). All 84 sites will contain the same elements. Our primary attractant will be a predator call (Wasatch Wildlife Products® Custom FurFindR®) programmed to play a 5 second distressed fawn recording on 30 second intervals. These calls are also furnished with light sensors rendering them inactive during daylight hours. We will cable the calls 30 – 60 cm up from the base of a tree and further secure them using a 30 X 30 cm piece of chicken wire. To incorporate a natural prey scent, we will place bait (deer meat, hide, or blood) near the tree base. We will then build an impenetrable perimeter around the tree with thick brush leaving an obvious entry way to the call and bait. We will configure lines of barbed wire within the entrance. Terrain and vegetation features will determine the height of the wire and consequently whether we desire a cougar to step over, under, or through 2 strands. In addition, we will attempt to conceal the wire with sticks and other natural materials (Chapter 1, Figure 3). At each site, we will position an infrared motion sensor camera (Reconyx® PC85 Rapidfire® or PC800 Hyperfire®) set to rapidly take 5 photos when triggered. To minimize the possibility of sample contamination and degradation, we will conform to the same protocols for sample collection outlined in Chapter 1. We will check the sites for activity every 5 – 7 days collecting all samples, replenishing bait, and changing batteries. We will consider hair on a single barb as one sample and denote quantity with a score of 1 – 3 (1 equals < 5 hairs, 2 equals 6 – 15 hairs, and 3 equals > 15 hairs). We will remove hair using sterile tweezers and re-sterilize the barb by passing a flame under it (Kendall et al. 2008, Settlage et al. 2008). We will place the hair in a small paper envelope. Paper envelopes will then be put in a plastic bag with a desiccant and stored at room temperature (Taberlet and Luikart 1999). We will evaluate 21 sites during each of the four 4 – 5 week sampling periods: November 17 – December 20, December 21 – January 23, January 24 – February 26, and February 27 – April 1 for a total of 84 sites. We will tally detections as one per night per cougar based on photographic confirmation. Dependent kittens will not be counted. Though we expect all animals visiting the sites to be detected by camera, hair samples may also provide proof of cougar presence as well as identifying unmarked animals. Hair samples will be processed at the USGS Fort Collins Science Center, FORT Molecular Ecology Lab. Taberlet et al. (1996) suggested that to achieve a correct genotype at a 99% confidence level, 8 U template DNA is needed (1 U is equivalent to the DNA content of 1 diploid cell). Therefore when possible, we will extract DNA from 10 hairs (Goossens et al. 1998, Boersen et al. 2003) using Qiagen DNeasy® Tissue Kits (Qiagen Inc., Valencia, CA). Samples will be genotyped using 9 – 12 microsatellite primers shown to have high variability in cougars (Ernest et al. 2000, Sinclair et al. 2001, Anderson et al. 2004). We will amplify the DNA by polymerase chain reaction (PCR) using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). To assess error, the results from hair genotyping will be compared with archived blood and tissue samples collected by CPW during capture. If possible, we will re-process hair samples shown to contain error at one or more alleles. A total count of available animals (A) is needed to estimate p. An individual’s availability must first be appropriately defined for the estimate to be unbiased. We will base availability on GPS locations included within a circular buffer zone around a site. The radial distance will be determined by collar error due to fix rates and missed fixes. We are limited by the technology we will employ. Collars will be programmed to download a fix every hour from 7 pm to 7 am and every 4 hours during the day. It will not be possible to know an animal’s exact location at all times resulting in potential error in determining availability. Availability missed due to collar error will result in positively biased p estimates. For example, if an individual was not detected but passed within the buffered region without recording a fix, the availability value would be low resulting in a high p estimate. Positive bias would also result if the 309 �same individual was detected but never considered available. This can be troublesome as a positively biased estimate for p applied in population estimation will result in a negatively-biased abundance estimation. We will determine the distance the collar error becomes negligible by increasing the buffer zone until all animals detected can also be considered available. For animals not detected, we will connect successive locations with a straight line. If this line passes through any part of the buffer zone, we will count the animal as available. We will apply the count of available animals (A) and the number detected (n) to estimate the detection probability (p). First, we will use a simple binomial model to estimate p for each of the i sites: (Williams et al. 2002). Next, we will estimate the average p for all 84 sites, where x is the number of sites, (Thompson 2002). We will then estimate the sampling variance per site, (Williams et al. 2002). Next, we will estimate the process variation, or the actual variation, in the detection probability across sites (Link and Nichols 1994). Total variance [vâr (p̂)] is comprised of two components: process variation (var (pᵢ) = σ²) and sampling variation [var (p̂ᵢǀpᵢ)] (Burnham and White 2002). The site locations are chosen relative to the sampling method. Because the sites are inherently variable, no two sites will have the exact same vegetation composition, aspect, elevation, etc. To eliminate the variation associated with the sampling and estimation procedure and focus on the precision of the detection probability across all sites, we will consider the variance using a variance components approach. Our variance estimate will consider process variation only and be derived by subtracting the estimated average of the sampling variances across all sites from the total variance. (Gould and Nichols 1998), where (Link and Nichols 1994), and (Williams et al. 2002). 310 �Finally, we will construct confidence intervals around p̄̂ at an alpha level of 0.05 using a teststatistic obtained from the student’s t distribution with degrees of freedom 60>120 (1.99), (Ott and Longnecker 2010), where (Williams et al. 2002). Confidence intervals are typically computed using the standard error (SE) of the estimate. However, because we are subtracting the sampling variation to determine the actual variation (σ²), we will use the standard deviation (SD = ) to construct a confidence interval. In addition, we will explore the variance components between survey periods. We acknowledge that a sample size of 4 is most likely inadequate to make temporal inferences. Multiple years of data may be needed to assess the process variation in p over survey periods that are 4 – 5 weeks in length. Chapter 3. Investigating the assumptions of the Lincoln-Peterson Estimator and other closed mark-recapture models Mark-recapture methods are widely used in wildlife population monitoring. For the results to produce unbiased and precise estimates, model assumptions must be addressed (White et al. 1982). Closed mark-recapture models maintain 4 primary assumptions. These assumptions include: demographic and geographic closure; no tag loss; accurate individual identification; and equal probability of capture (Otis et al. 1978). The Lincoln-Peterson estimator is a simple, two-period, mark-recapture model, based on the relationship where m1 individuals are marked at occasion 1 and released; n2 individuals are counted on occasion 2 with m2 marked animals; and N is abundance and is often the parameter of interest (Link 2003). The Lincoln-Peterson estimator is bound by closed-model assumptions (Williams et al. 2002). This model does not accommodate unequal detection (Link 2003). If capture variation is found to exist in the target population, then the simple application of the Lincoln-Peterson estimator may prove inadequate requiring the use of more complex models (Otis et al. 1978). Therefore if during initial planning, it is suspected that study design or idiosyncrasies unique to the species or population of interest may violate one or more model assumption, then, an a priori model set considering covariate and group attributes should be constructed to investigate possible sources of these violations (Willson et al. 2011). Model selection criteria like Akaike’s Information Criterion (AIC, Stanley and Burnham 1998) can then be applied to compare model fit using program MARK (White and Burnham 1999). The assumption of geographic and demographic closure (no immigration, emigration, births or deaths) is of fundamental importance in the analysis of mark-recapture data under closed models (Stanley and Burnham 1998). This assumption is likely to be violated in most field applications (Kendall 1999). Consequently, complex models have been developed to test for closure violations (Stanley and Burnham 1998) and to estimate the parameters responsible (Kendall 1999). However, because we are estimating detection (p) with a population of cougars wearing Global Positioning System (GPS) collars, their location in or out of the study area will be known with certainty. We will also know their survival state. Newly captured animals will be added to the study; and individuals that die will be censored. 311 �Next, we will consider the assumptions of no tag loss and accurate individual identification within the context of our study. At the time of capture, Colorado Parks and Wildlife (CPW) marks all cougars with a unique set of tags (inscribed with a 3 – 4 character identification code) one in each ear. The direction of the tag is specific to sex (i.e. left facing forward and right facing back for females). CPW also applies a GPS collar around the neck that is clearly visible in photos. It is highly unlikely that a cougar would lose all 3 marks. In addition, GPS location information will confirm an individual was in the vicinity of a site. Tag loss is doubtful; but misidentification through genotyping error is possible, potentially biasing population estimates. False genotypes result in population over-estimation and multiple individuals assigned the same genotype produce under-estimates (Lukacs and Burnham, 2005). We will assess genotyping error rates by comparing samples obtained via our noninvasive method with blood and tissue samples collected during initial capture (Dreher et al. 2007). The final assumption of equal capture or detection is often violated in wildlife studies (Link 2003). Otis et al. (1978) presented, in detail, 3 models (and all combinations thereof) in which the assumption of equal capture can be relaxed. Model Mt considers variation between sampling occasions. The second primary model, Mb, accommodates a behavioral change due to trap response, ‘trap happy’ or ‘trap shy’. Failure to consider capture variation due to a behavioral response can lead to biased population estimates. A ‘trap happy’ response can negatively bias estimates; whereas, a ‘trap shy’ response will create positive bias (Williams et al. 2002). Finally, model Mh assumes individual heterogeneity amongst individuals. Unmodeled heterogeneity may overstate precision and include bias (Link 2003). Accounting for individual heterogeneity in abundance estimation has long plagued researchers (Link 2003). Burnham and Overton (1978) presented a jackknife estimator that can provide some robustness in population estimation where heterogeneity in capture probabilities is present. However, because the jackknife estimator is not a maximum likelihood estimator, the sources of variation cannot be evaluated by comparing models using likelihood ratio tests or through model selection criteria (Akaike’s Information Criterion, AIC) (Williams et al. 2002). Pledger (2000) fit finite mixture models in addressing capture heterogeneity by maximum likelihood, thus allowing for model comparisons. Finite mixture theory groups individuals into two or more mixtures and considers the probability that an individual is in one mixture (π) and the probability that an individual is in the other mixture (1-π), though it is not possible to discern to which group an individual belongs. Huggins (1989) presents another maximum likelihood approach that will accommodate individual capture covariates when deriving the abundance parameter. Sources of heterogeneity modeled as covariates can then be evaluated through likelihood ratio tests and model selection criteria. Huggins (1989) suggests that the asymptotic properties of his estimators are normal in large sample sizes. However, in the case of small sample sizes, which are common in most wildlife studies, his simulations showed a skewed distribution (Huggins 1989). In response, he describes a conditional bootstrap method that can be applied to overcome problems of nonnormality thus producing reasonable confidence interval estimations. The potential for model assumption violations is largely dependent upon survey design and nuances of the target population (Otis et al. 1978). Last winter, we evaluated attractants and a hairsnaring mechanism applied to a population of cougars. Based on the limited success described in past studies, we anticipated few, if any, detections. However, in our short survey, we observed dozens of responses including multiple detections of the same individuals. We have not found any other study with the promise of a reliable noninvasive-survey method to both attract a cougar and obtain a genetic sample. If a high detection rate persists throughout the ensuing season, we will be presented with an ideal opportunity to explore possible sources of capture variation. Much is already known about cougar behavior to suggest that capture variation is possible and likely (C. Anderson personal communication). Resident adult home-range sizes vary between season 312 �(Seidensticker et al. 1973), sex (Dickson and Beier 2002, Anderson et al. 2004), and female reproductive status (Hornocker 1969). Males generally occupy larger areas than females (Anderson et al. 2004); but female home-range sizes are more variable (Hornocker 1969). Movements differ among behaviors such as hunting, feeding, and mating (Beier et al. 1995). Scrapes suggest a pattern in how cougars travel (Hornocker 1969) indicating that cougars do not occupy all parts of their home ranges equally. In addition, females with small kittens will be less mobile and confined to a smaller area (Seidensticker et al. 1973). Activity also varies relative to time of day, peaking in the evening hours (Sweanor et al. 2008). Finally, transients create another dynamic in the population that must be considered (Lindzey et al. 1994). The population of cougars on the Front Range to which we will apply our sampling protocol is subject, but not limited, to all of the potential sources of variation described above. We expect to have a sample size of approximately 20 – 25 individuals based on past capture success. Due to a small sample size relative to the large quantity of factors that may contribute to capture variation, we propose the Huggins model, which considers relationships as covariate and applies a bootstrap procedure, may be an appropriate estimator for use in future population assessments. To fit this model, we will formulate an a priori list of potential categorical and continuous variables (Figure 4) and describe any additional field protocols needed to collect the data. At the time of capture, we will note age (adult or subadult), sex (male or female), and if possible, reproductive status (with kittens or without). Photographic evidence at the sites may also aid in determining the reproductive condition of females. Using photos, we will log the time of the detection (day, dusk, night, or dawn) and the presence of multiple adult cougars. We will also consider general site specific aspects (ridgeline, drainage, or saddle). Finally, we will assign a behavior to each animal found to be available (feeding, traveling, mating, or denning) via GPS location cluster data. 313 �Age Sex Behavior Subadult Male Adult Female Feeding Traveling Mating Denning Site w/ kittens Time w/o kittens Saddle Ridge Drainage Day Dusk Night Dawn Figure 4. Variables we will consider in the detection process. At this time, it is not our intention to estimate the population size. Our efforts are simply exploratory in nature. Therefore, we reserve the possibility of investigating additional variables post hoc. If possible, we will also apply information we gain from our exploratory investigations to testing models with simulated data. Chapter 4: The utility of snow tracking on the Front Range Our objective is to evaluate the utility of snow tracking as a means to obtain genetic material given the terrain and snow conditions on the Front Range and determine if it can be useful as a secondary source of detection in population estimation. Last February, we began our assessment by locating and following tracks from known cougars collecting hair and scat samples found en route. The samples that we collected will be processed and evaluated based on the successful genotyping of individuals. We found that many variables contributed to the condition of the track and to the quality and quantity of genetic material available forcing us to reconsider our initial objectives. This winter (November 2012 – April 2013), we will test a modified sampling plan that we feel will have a more practical application given the conditions on the Front Range. Methods - Pilot Our initial objective was to investigate the ability to find a genetic sample relative to the time after a snow fall event and the age of the track. On the first day after it snowed, we would randomly choose 5 cougars whose track would be surveyed on day 1, 2, 3, 4, or 5. On the second day, we would choose 4 more animals to be surveyed on day 2, 3, 4, or 5. We would continue this trend for 5 days (Table 4). For example, on day 3, we would survey 3 tracks: a one-day old track, a two-day old track, and a three-day old track. 314 �Days after snow Track age 1 2 3 4 5 1 2 3 4 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Table 4. Schematic of a 5-day sampling period following a snow-fall event considering tracks that are 1 – 5 days old. Our interest also lay in determining the distance we needed to travel to obtain an adequate sample. We would use GPS collared cougars to locate tracks and to evaluate genotyping success by comparing DNA from hair and scat samples with archived DNA from blood and tissue collected during capture. We would follow the track 1 – 2 km, collect all hair and scat found (differentiating between hair found on the surface of the snow, snagged on brush, or in day beds), assess which samples were genotyped successfully, and determine the average minimum distance we needed to survey before an individual could be identified. Results – Pilot We were able to locate multiple hair samples and 2 scats by following tracks on average 1.25 km but only within 1 – 2 days after a snow fall. Snow conditions were not conducive to tracking over the full 5 day survey period we had described. Many factors, such as temperature, wind conditions, aspect, snow depth, canopy cover, and vegetation type, contributed to our ability to find and follow a track and to the quality and quantity of genetic material we found. In addition, our initial study plan dictated we would follow a track for 1 – 2 km. However, we often lost the track on dry ground or encountered private property boundaries and could not continue. We also struggled with determining which cougars to survey and where to start. We used the GPS collared animals monitored by CPW to efficiently locate the tracks but needed to randomly choose a starting point and a direction of travel (forward or backward). Our study area is a mosaic of private parcels and public open space. Cougars available to be surveyed needed to have moved a considerable distance across public land shortly after it snowed. We found that, on any given day, only ~¼ of the collared cougars were traveling on public land. Consequently the morning after a snowfall, we were limited to 4 – 6 possible tracks to pursue. We encountered other logistical challenges while tracking. Snow conditions on sunny, exposed, south-facing slopes, deteriorated rapidly thus ending our progress by mid-morning the first day. Conversely, tracks remained in good condition for several days in north-facing, wooded areas. We had difficulty tracking where more than one cougar was present, especially females with multiple kittens. We also encountered males following in the tracks of the females we were surveying. Not knowing for certain which cougar left the sample was problematic to our initial objectives. In addition, other species like deer would travel over cougar tracks making tracking difficult and obscuring genetic material. We determined that we could find hair and scat by following tracks but only within a day after it snowed, preferably first thing in the morning. Snow conditions on the Front Range did not allow for a 5day sampling period. We have not yet processed the samples to determine if the hair and scat we collected contain enough DNA to genotype without error. 315 �Methods – Winter 2012/2013 We recognize that inconsistent snow conditions may deem winter tracking to be an inefficient field method when applied as the sole surveying procedure used in population estimation; but snow tracking does have some utility in that genetic samples are easily located along a fresh track. Our modified objectives will consider the function of snow tracking as a secondary means to detect cougars and be based on resources that we believe wildlife managers might have available to them. We will work within the 1200 km² area west of Boulder detailed in Chapter 2 (page 13). We divided the region into 3 equal sections (~400 km²), north to south. To maximize efficiency, we will use roads and established trails. We chose 10 stretches of road/trail 2 km in length per section. The 10 segments will be ordered so that they can be most efficiently checked. However, the starting point will be randomly selected per snow event. Based on observed weather patterns, we expect to have 1 – 2 snow fall events per week requiring enough resources to employ 3 persons at most twice a week. The morning after a snow fall, 1 person per section will begin checking each stretch, one after the other, until a track is found. When possible, tracks will be followed in the backward direction and mapped via a Garmin® handheld GPS unit until an adequate sample is found. We consider an adequate sample to be a tuft of >15 hairs collected from a branch or fence, hair collected from a daybed, or a scat. Hair will be collected using sterile tweezers and placed in a small, paper envelope. The envelope will then be put in a plastic bag with desiccant and stored at room temperature (Taberlet and Luikart 1999). We will re-sterilize tweezers with a bleach water rinse. Scats will be placed in a plastic bag and frozen (Ernest et al. 2000). If time allows, we will continue checking stretches for additional tracks. Hair and scat samples will be processed at the USGS Fort Collins Science Center. When possible, we will extract DNA from 10 hairs (Goossens et al. 1998, Boersen et al. 2003) using Qiagen DNeasy® Tissue Kits or from scat using Qiagen Stool DNA Kits (Qiagen Inc., Valencia, CA). Once the DNA has been extracted, samples will be genotyped using 9 – 12 microsatellite primers shown by Ernest et al. (2000), Sinclair et al. (2001), and Anderson et al. (2004) to have high variability in cougars. The DNA will be amplified by polymerase chain reaction (PCR) using a M13-tailed forward primer as described by Boutin-Ganache et al. (2001). When possible, we will compare the results from hair and scat genotyping with archived blood and tissue samples from the same individuals. At the end of the season, we will consider how many samples we were able to locate and genotype correctly relative to the effort we applied. We will determine if snow tracking could be useful as a complement to our lure site component. We will also consider winter tracking with regard to cougars previously captured and collared by CPW by quantifying the proportion of marked to unmarked animals detected during snow tracking. Timeline February – April 2012 November 17 – December 20, 2012 December 21 – January 23, 2013 January 24 - February 26, 2013 February 27 – April 1, 2013 November – April, 2013 Pilot Season 1st Sampling period 2nd Sampling period 3rd Sampling period 4th Sampling period Snow tracking efforts Lures will be tested (Chapter 1) during the pilot season and the 1st – 3rd sampling periods. The detection probability (Chapter 2) and capture variation (Chapter 3) will be considered during the 1st – 4th sampling periods. 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Wildlife Society Bulletin 27:616-627. 320 �321 �Colorado Parks and Wildlife July 2011 – June 2012 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Federal Aid Project No. Colorado 3430 7210 1 : : : : Parks and Wildlife Mammals Research Customer Services/Research Support Library Services N/A Period Covered: July 1, 2011 – June 30, 2012 Author: Kay Horton Knudsen Personnel: Kay Horton Knudsen, Chad Bishop, Mat Alldredge All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. ABSTRACT The Colorado Parks and Wildlife (formerly Colorado Division of Wildlife) Research Center Library has existed for several decades in the Ft. Collins office. A library housed in the Denver office was moved to Ft. Collins many years ago. Early librarians, Marian Hershcopf and Jackie Boss, can be credited with the physical organization of the Library including seven decades of Federal Aid reports, almost 50 years of Wildlife Commission reports and a unique book and journal collection. Jackie Boss retired in April 2007 and the Library was temporarily closed to all services. Kay Horton Knudsen was hired as the new Research Center Librarian and began employment on August 30, 2008. The goal, as stated by a former supervisor, was to reopen the Library and expand the electronic and digital capabilities of library services to the entire Agency. Chad Bishop became the Mammals Research Leader in July 2009. His duties include supervision of the Research Center Library. Mat Alldredge was Acting Mammals Leader from April to July 2012. A progress report and current status of the Library are detailed below. 322 �WILDLIFE RESEARCH REPORT COLORADO PARKS AND WILDLIFE RESEARCH LIBRARY SERVICES KAY HORTON KNUDSEN P.N. OBJECTIVE Provide an effective support program of library services at minimal cost through centralization and enhancement of accountability for Colorado Parks and Wildlife employees, cooperators and wildlife educators. SEGMENT OBJECTIVES 1. Continue to improve and modernize library services. 2. Continue to develop, improve, and implement the CPW Research Center Library web-site. SUMMARY OF LIBRARY SERVICES The Research Center Library celebrates its fourth full year of operation since reopening in 2008. Work continues on upgrading website features, filling literature research requests and taking a more longterm view on improving Library services. Following the merger with State Parks, the librarian reached out to the Parks biology staff to assist with their information retrieval needs. During the first year of operation, in additional to cleaning and physical organization, a priority task was choosing and implementing a web-based Integrated Library System (ILS) and purchasing statewide access for CPW staff to online research databases. The second year emphasis was on meeting Agency staff and promoting the Library in a series of training demonstrations. Moving into the third and now fourth year of operation, major projects were purchase of a new federated search feature for the Library website, digitization of CPW publications and continued contact with staff statewide to meet their bibliographic research needs. Since the Library serves as a historic archive for CPW publications, each meeting with staff also includes a request to be included in the dissemination of white papers, journal articles and internal reports. Day-to-day duties continue to be responding to research and document retrieval requests, cataloging newly acquired material and digitizing internal CPW reports. EOS International is the vendor for the ILS. It was decided to initially purchase the basic modules (a hosted system with library catalog, circulation, cataloging and serials control). The Library website was released to CPW staff in March 2009. The next module purchased from EOS was Indexer – this feature allows for full-text searching of PDFs linked to bibliographic records and was implemented in December 2009. The latest modules are Knowledge Builder and Classification Management. They are used to archive and index historic research documents. In addition to the catalog of books and reports housed in the Ft. Collins Library, the Library website also gives CPW staff access to research databases. Current subscriptions include BioOne, four of EBSCO’s specialty databases (Environment Complete, Fish and Fisheries Worldwide, Wildlife and Ecology Studies Worldwide and Criminal Justice with Full Text), SORA (Avian journals) and the JSTOR Life Sciences collection. The decision was made in late 2011 to discontinue the print subscriptions to many of the major journals. Online access to the journals was retained and continues as the primary usage point for staff. This online subscription often includes the publisher’s full-text online archives; backfiles of major wildlife and aquatic journals were purchased when necessary to expand the full-text 323 �capability. CPW staff statewide are authenticated through WildNet and WildPoint (intranet) eliminating the need for individual usernames and passwords. A federated, or integrated, search feature for the Library website was on the wish-list from day one. Federated searching combines access to the Research Library catalog, all of the third-party databases listed above, as well as most of the online journals into one all-in-one search. EBSCOHost’s Integrated Search (EHIS) was chosen in the fall of 2010 and the link was made available on the Library website in the spring of 2011. Library handouts were updated and a new handout created to explain the features and offer tips on the use of the all-in-one search. The entire federated search industry is evolving and the librarian will continue to work with EBSCO staff to resolve problems and maintain links to all resources. The next major project envisioned at the reopening of the Library was the digitization of CPW publications. Research on various digitization options took place in 2009/2010. An HP printer/scanner with optical character recognition software was purchased, installed and tested by summer 2010. The first document series to be digitized was Outdoor Facts. The second series digitized was the much larger Special Reports collection. The resulting PDFs are attached to bibliographic records for each title within the series and are available via the Library catalog for download by CPW staff throughout the state. In late 2011, Federal Aid staff in Denver donated a large collection of Terrestrial Federal Aid reports to the Library. It was decided to use these for the next digitization project. With the help of a work-study student from Colorado State University, several decades of early reports have been scanned and uploaded to the Library catalog. Other projects in the Library this year included: 1) processing journal subscription renewals and updates to include full-text online access, 2) finishing a project to catalog the backlog of theses/dissertations, 3) continuing to add links to PDF formats into the catalog’s bibliographic file, 4) printing and cataloging the Data Analysis Unit (DAU) reports, 5) gathering the transition and merger documents as produced by the Division of Wildlife and State Parks Transition teams to maintain a historic record in the Library collection, 6) sorting and organizing the Government Documents collection, and 7) distribution and cataloging of the Mammals, Avian and Aquatics Research annual reports. The librarian attended the following conferences and workshops: 1) Colorado Association of Libraries annual conference in Loveland, October 2011, 2) Google User’s one day workshop at CSU, January 2012, 3) InterLibrary Loan conference, CSU, April 2012, and 4) “Bridging the data divide”, 2day data curation workshop sponsored by NCAR/UCAR/NOAA in Boulder, April 2012. There was also the opportunity throughout the year to participate in several online “webinars” sponsored by various vendors and library agencies to expand knowledge on trends in the library field. With expanded library services, the number of requests for documents or research assistance has grown. Most questions received in the Library are from CPW staff or from outside researchers (generally consultants and out-of-state natural resources employees). The Library is not open on a walk-in basis to the general public but the librarian does assist the Help Desk at the Denver office with questions they receive. CPW employees generally request journal articles or items from the Library collection; outside researchers most often want a copy of a CPW publication. The chart below shows the number of reference questions and document requests handled by the librarian during the past 4 years. Please note that one request from a CPW staff member may be for multiple journal or book titles. It is also interesting that the current record for number of requests per month was set in January 2012. 324 �2008/09 July August September October November December January February March April May June TOTAL 15 21 33 14 28 33 30 35 24 13 20 266 2009/10 20 25 30 38 28 32 62 43 36 23 17 26 380 2010/11 45 34 37 41 46 34 48 43 46 30 51 27 482 2011/12 28 52 53 42 52 52 64* 43 36 42 53 36 553 STATISTICS: As of June 30, 2012, the Research Center Library holds 18,512 titles and 24,371 items (these are the multiple copies of a title) and has 142 registered patrons (CPW staff). Usage statistics for the research databases are given in the chart below. For BioOne and EBSCO the numbers are for the total searches run; for JSTOR the statistics are for the number of successful full-text article requests. July 2011 August 2011 September 2011 October 2011 November 2011 December 2011 January 2012 February 2012 March 2012 April 2012 May 2012 June 2012 TOTAL BioOne 217 194 188 222 192 190 144 131 191 117 122 88 1996 EBSCO searches 1370 3356 1662 2047 1226 1193 1167 2097 2729 1221 1125 1210 20,403 Prepared by ___________________________ Kay Horton Knudsen 325 JSTOR 348 306 262 238 209 289 259 214 411 198 189 134 3057 � https://cpw.cvlcollections.org/files/original/e43c3c5a908d16f25ff25c5a42ff1180.pdf 397c4ca0fcc7f55334c0d8940c67f3f6 https://cpw.cvlcollections.org/files/original/13ce4ff069a2bc6aee2f8e81b627ab73.pdf 6d087aedba1ca8eccad205093ef07497 PDF Text Text MAMMALS - JULY 2014 �ii �WILDLIFE RESEARCH REPORTS JULY 2013 – JUNE 2014 MAMMALS PROGRAM COLORADO PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). iii �Executive Summary This Wildlife Research Report represents summaries (<5 pages each) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) from July 2013 through June 2014. These research efforts represent long term projects (2 – 10 years) in various stages of completion addressing applied questions to benefit the management of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammals.aspx or from the project principal investigators listed at the beginning of each summary. Current mammals research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to various habitat alterations, humanwildlife interations, and investigating improving approaches to wildlife management. The Mammals Conservation Section addresses mammal and breeding bird responses to the recent bark beetle outbreak influencing about 3.7 million acres of spruce and pine forests in Colorado. The Ungulate Conservation section includes 3 projects addressing mitigation approaches to benefit mule deer exposed to energy development activities, an assessment of potential factors influencing mule deer declines the past 40 years, and an evaluation of moose demographic parameters that will inform future management of this recently established ungulate species in Colorado. The Predatory Mammals Conservation section addresses improved understanding and management approaches to address black bear and mountain lionhuman interactions, evaluation of sport harvest for mountain lion management, and assessment of noninvasive sampling methods to estimate abundance, diet composition, and age class distribution of carnivore populations. The Support Services section describes the CPW library services to provide internal access of CPW publications and online support for wildlife and fisheries related publications. We are greatful for the numerous collaborations that support these projects and the opportunity to work with and train gradute students that will serve wildlife management in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, Idaho State University, University of Wisconsin-Madison, the Buerau of Land Management, City of Boulder, Boulder and Jeffereson County open space, City of Durango, Big Horn Sheep and Moose Auction/Raffle Grants, Species Conservation Trust Fund, Safari Club International, Boone and Crocket Club, Colorado Mule Deer Association, The Mule Deer Foundation, Wildlife Conservation Society, SummerLee Foundation, EnCana Corp., ExxonMobil/XTO Energy, Marathon Oil, Shell Exploration and Production, WPX Energy, and private land owners who have provided access for research projects. iv �STATE OF COLORADO John Hickenlooper, Governor DEPARTMENT OF NATURAL RESOURCES Mike King, Executive Director PARKS AND WILDLIFE COMMISSION William Kane, Chair……………………………………………………………………………….....Basalt Gaspar Perricone, Vice Chair ……………………………………………………………………….Denver Chris Castilian, Secretary …………………………………….………….….………………............Denver Robert Bray………………………………………………………………………………………....Redvale Jeanne Horne………………………………………………………………………….….………….Meeker Dale Pizel………………………………………….………..………………….…….........................Creede James Pribyl………………………………………………………………………………………...Boulder James Vigil………………………………………………………………………………………....Trinidad Dean Wingfield………………………………………………………………………..…………….Vernon Michelle Zimmerman…………………………………………………………………………Breckenridge Alex Zipp…………………………………………………………………………….………………Pueblo Mike King, Executive Director, Ex-officio………….…………………...………………….……......Parker John Salazar, Dept. of Agriculture, Ex-officio….………………………………..…….………... Lakewood DIRECTOR’S LEADERSHIP TEAM Bob Broscheid, Director Chad Bishop, Ken Brink, Steve Cassin, Heather Dugan, Gary Thorson, Jeff Ver Steeg, Pat Dorsey Dan Prenzlow, Ron Velarde, Steve Yamashita MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Wildlife Researcher Eric Bergman, Wildlife Researcher Jake Ivan, Wildlife Researcher Heather Johnson, Wildlife Researcher Ken Logan, Wildlife Researcher Kay Knudsen, Librarian Margie Michaels, Program Assistant v �vi �Colorado Division of Parks and Wildlife July 2013 − June 2014 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH SUMMARIES MAMMAL CONSERVATION MAMMAL AND BREEDING BIRD RESPONSE TO BARK BEETLE OUTBREAKS IN COLORADO by J. Ivan and A. Seglund………………...………...1 UNGULATE CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson……………………………………………………..5 QUALIFYING LOSS AND DEGRADATION OF MULE DEER HABITAT ACROSS WESTERN COLORADO by H. Johnson………………………………......9 EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS, AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO by E. Bergman….…….……………….11 PREDATORY MAMMALS CONSERVATION BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS by H. Johnson………………………………………………………………15 SHIFTING PERCEPTIONS OF RISK AND REWARD: TEMPORAL AND SPATIAL VARIATION IN SELECTION FOR HUMAN DEVELOPMENT BY BLACK BEARS AROUND THREE URBAN SYSTEMS by H. Johnson……….....19 MOUNTAIN LION POPULATION RESPONSES TO SPORT-HUNTING ON THE UNCOMPAHGRE PLATEAU, COLORADO by K. Logan……………………23 COUGAR AND BLACK BEAR DEMOGRAPHICS AND COUGAR-HUMAN INTERACTIONS IN COLORADO by M. Alldredge………………………………...27 SUPPORT SERVICES LIBRARY SERVICES by K. Knudsen……..……………………………...………….49 vii �viii �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mammal and breeding bird response to bark beetle outbreaks in Colorado Period Covered: July 1, 2013 − June 30, 2014 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Amy Seglund, Amy.Seglund@state.co.us ; All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) infestations have reached epidemic levels in Colorado, impacting approximately 3.7 million acres since the initial outbreak in 1996 (Figure 1). Though bark beetles are native to Colorado and periodic infestations are considered a natural ecological process, the geographic scale of their impact and simultaneous infestation within multiple forest systems has never been observed. This historic outbreak is having significant impacts on composition and structure of forest stands that will propagate for decades into the future. The widespread mortality of forested systems in Colorado is likely to have a dramatic, but poorly understood effect on wildlife species that depend on these habitats. The project described here uses occupancy estimation to determine which wildlife species (both species of conservation concern and game species) decrease their use of an area as bark beetles pass through, which increase their use, and which exhibit use similar to levels prior to infestation. Statewide sampling was conducted during the summers of 2013 and 2014 (Figure 2). We sampled 150 Engelmann spruce (Picea engelmanni)/subalpine fir (Abies lasiocarpa) sites and 150 sites consisting mostly of lodgepole pine (Pinus contorta) or lodgepole pine mixed with other conifers. For both strata, sampling covered conditions ranging from sites that have yet to be impacted by bark beetles to those that were impacted by beetles more than a decade ago. At each 1-km2 site, we sampled the breeding bird community using the Rocky Mountain Bird Observatory’s protocol for “Integrated Monitoring in Bird Conservation Regions” (Hanni et al. 2014). We sampled the mammal community by deploying a remote camera near the center of each sample unit. Fieldwork for this phase of the project is now complete. However, data entry for 2014 is ongoing. For the purposes of this interim document, we report preliminary results for 3 mammalian species of conservation concern based on 2013 data only: snowshoe hares (Lepus americanus) and red squirrels (Tamiasciurus hudsonicus), which together comprise nearly 100% of the diet of the federally listed Canada lynx (Lynx canadensis), and American marten (Martes americana), which is a USFS Region 2 sensitive species. We collected 197,092 photos of 25 species during summer 2013. Occupancy analyses of these data indicate that snowshoe hares are more likely to use spruce/fir stands than lodgepole stands, but in both cases, use of these stands declines as bark beetle infestations pass by. We expected use to increase dramatically at some point as the understory responds to increased light, but that response will apparently take longer than the decade or so that has passed since the earliest infestations. Unlike hares, red squirrel use is similar for spruce/fir and lodgepole stands, but similar to hares, use of these stands declined after bark beetle infestations. This may be related to significant mortality of cone-bearing trees that occurs with beetle infestations. Use of the 2 stand types by marten was similar, but in contrast to the previous 2 species, use is expected to increase following bark beetle infestations. We expect to complete a full analysis and report for this project by Fall 2015. 1 �Figure 1. Current (2013) extent of mountain pine beetle (red) and spruce beetle (purple) infestations in spruce/fir (blue-green) and lodgepole pine (bright green) forests in Colorado. Bark beetle data were collected via USFS aerial surveys. Figure 2. Sites sampled via point counts and remote cameras to assess impacts of bark beetle infestations on breeding bird and mammal species in spruce/fir (blue-green, N = 150) and lodgepole pine (bright green, N = 150) stands in Colorado, 2013−2014. 2 �Figure 3. Snowshoe hare occupancy (i.e., use) of stands in relation to the number of years since initial infestation by bark beetles. Note that “0” years since infestation represents stands that have not yet been impacted. Use of spruce/fir stands is generally higher than use of lodgepole stands, but in both strata, use is expected to decline through time as bark beetles pass over an area. Figure 4. Red squirrel occupancy (i.e., use) of stands in relation to the number of years since initial infestation by bark beetles. Note that “0” years since infestation represents stands that have not yet been impacted. Use of spruce/fir and lodgepole stands is generally similar (only a single line here compared to 2 lines for snowshoe hares above) and is predicted to decline through time as bark beetles pass over an area. 3 �Figure 3. American marten occupancy (i.e., use) of stands in relation to the number of years since initial infestation by bark beetles. Note that “0” years since infestation represents stands that have not yet been impacted. Use of spruce/fir and lodgepole stands is generally similar (only a single line here compared to 2 lines for snowshoe hares above) and is predicted to increase through time as bark beetles pass over an area. 4 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation Period Covered: July 1, 2013 − June 30, 2014 Principal Investigator: Charles R. Anderson, Jr., Chuck.Anderson@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent the first 5 pretreatment years and 1 year post treatment of a long-term study addressing habitat improvements and evaluation of energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. We monitored 4 winter range study areas representing varying levels of development to serve as treatment (North Magnolia, South Magnolia) and control (North Ridge, Ryan Gulch) sites (Fig. 1) and recorded habitat use and movement patterns using GPS collars (≥5 location attempts/day), estimated overwinter fawn and annual adult female survival, estimated early and late winter body condition of adult females using ultrasonography, and estimated abundance using helicopter mark-resight surveys. During this research segment, we targeted 240 fawns (60/study area) and 170 does (30–70/study area) in early December 2013 for VHF and GPS radiocollar attachment, respectively, and 120 does in March 2013 (30/study area) for late winter body condition assessment. Winter range habitat improvements completed spring 2013 resulted in 604 acres of mechanically treated pinion-juniper/mountain shrub habitats in each of the 2 treatment areas (Fig. 2) with minor and extensive energy development, respectively. Posttreatment monitoring will continue for 4 years to provide sufficient time to measure how vegetation and deer respond to these changes. Based on data collected during the 5-year pretreatment phase and 1 year post-treatment: (1) annual adult survival was consistent among areas averaging 80-84% annually, but overwinter fawn survival was more variable ranging from 48% to 95% within study areas, with annual and study area differences primarily due to annual weather conditions on seasonal ranges and in some cases density dependent influences; (2) migratory mule deer (Fig. 3) selected increased cover and increased their rate of travel through developed areas, but did not avoid development structures and avoided negative influences through behavioral shifts in timing and rate of migration; (3) mule deer body condition early and late winter was generally consistent within areas, with higher variability among study areas early winter, which likely relate to seasonal moisture within areas and relative forage capacity among areas; (4) mule deer densities have increased in 3 of 4 areas, with fluctuating and recently increasing deer densities evident in the 4th area (Fig. 4); (5) post treatment vegetation responses have been promising with evidence of improved forage conditions, but longer term monitoring will be required to address the full potential of habitat mitigation efforts. Detailed habitat use analyses are still pending for the pretreatment period. We will continue to collect population and habitat use data across all study sites to evaluate the effectiveness of habitat improvements on winter range. This approach will allow us to determine whether 5 �it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation efforts toward less or non-impacted areas. In collaboration with Colorado State University, we are also evaluating deer behavioral responses to varying levels of development activity in the Ryan Gulch study area and neonate survival in relation to energy development from all study areas. This will allow us to assess the effectiveness of certain Best Management Practices (BMPs) for reducing disturbance to deer and include neonatal data to other demographic parameters for evaluation of mule deer/energy development interactions. The study is slated to run through 2018 to allow sufficient time for measuring mule deer population responses to landscape level manipulations. A more detailed version of this project summary (Anderson 2014, Federal Aid Report W-185-R) and information about recent publications from this effort can be accessed at http://cpw.state.co.us/learn/Pages/ResearchMammalDeer.aspx Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, winter 2013/14 (Accessed http://cogcc.state.co.us/ Dec. 31, 2013). 6 �Figure 2. Habitat treatment site delineations in 2 mule deer study areas (604 acres each) of the Piceance Basin, northwest Colorado (Top; cyan polygons completed Jan. 2011 using hydro-axe; yellow polygons completed Jan. 2012 using hydro-axe, roller-chop, and chaining; and remaining polygons completed April 2013 using hydro-axe). January 2011 hydro-axe treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 7 �Figure 3. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012). Piceance Basin late winter mule deer density 30.00 Deer/km2 25.00 20.00 North Ridge 15.00 Ryan Gulch 10.00 North Magnolia South Magnolia 5.00 0.00 2009 2010 2011 2012 2013 2014 Year Figure 4. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2014. 8 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Quantifying loss and degradation of mule deer habitat across western Colorado Period Covered: July 1, 2013 − June 30, 2014 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: Sarah E. Reed, Jessica R. Sushinsky, Andy Holland, Trevor Balzer, Jim Garner All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. In recent decades, mule deer populations have declined across the western U.S., causing wildlife management agencies to seek factors limiting deer performance and strategies to increase their population sizes. The trend of declining mule deer populations has been primarily attributed to loss and degradation of deer habitat, through mechanisms such as urban/exurban development, resource extraction, agriculture, roads and vehicular traffic, fire suppression, and changing patterns in weather and plant productivity. While wildlife managers are well aware that these different factors can negatively affect deer populations, there is no information on their relative or cumulative impacts. In a report to the Colorado state legislature in 2001 titled, “Declining mule deer populations in Colorado: reasons and responses” Gill (2001) concluded that habitat factors had likely taken the greatest toll on deer populations but that there was no information quantifying the extent of habitat loss or deterioration across the state; critical information that is still lacking today. To address this issue, our objective is to conduct the first spatial and temporal analysis of landscape changes that have occurred to mule deer habitat across western Colorado (west of Interstate 25; Fig. 1). Specifically we are 1) mapping and quantifying changes to deer habitat that have occurred over the last ~40 years (in 5-10 year increments) related to residential development, energy development, fire, climate, and plant productivity, 2) calculating the amount of habitat that has been degraded and lost (directly and indirectly) due to these factors on an individual and cumulative basis for each deer data analysis unit (DAU) and within winter and summer ranges of each DAU, and 3) examining whether spatial and temporal changes to habitat conditions may be associated with observed trends in deer recruitment rates. During fiscal year 2013-2014 we completed the first two objectives of this project, and quantified the total area and proportion of deer habitat that was impacted by each land use land cover (LULC) factor, summarized by DAU. While we wanted to conduct these calculations across all LULC types for the past ~40 years, we were limited by the available data. We calculated metrics for climate and wildfire on an annual basis and in 5-year increments. Habitat loss due to residential development was summarized by decade because that is the finest temporal resolution available for the selected data source. Changes to deer habitat were determined on 5-year increments for energy development and annually for vegetation productivity, because collaborators agreed these were the most useful temporal resolutions for these LULC types. A brief summary of the data used to quantify each type of LULC change is described below: • Climate data were acquired from Parameter-elevation Regressions on Independent Slopes Models (PRISM) to quantify changes to precipitation and temperature. This dataset is considered to be one of the highest-quality historical climate datasets currently available, and was summarized at a 800 m spatial scale. From this dataset we calculated annual precipitation, June precipitation, summer precipitation, winter precipitation, and June minimum temperatures. 9 �• • • • Data on energy development were acquired from the Colorado Oil and Gas Conservation Commission. We obtained a spatial dataset representing the point locations of all oil and gas wells statewide and a tabular dataset representing years of well activity. We merged these datasets to produce a database which attributes all wells with the year the wells were drilled or first became active. At 5-year increments, we calculated the cumulative area affected by energy development at three distances: 200 m, 700 m, and 2,700 m. Changes to residential development were mapped and quantified using the Spatially Explicit Regional Growth Model (SERGoM) dataset. This nationwide dataset models housing density by decade at a spatial resolution of 100 m. Changes to deer habitat by DAU were calculated for urban, suburban, exurban, rural and undeveloped housing categories. We quantified plant productivity or “greenness” from the Normalized-Difference Vegetation Index (NDVI), which has been widely used to assess forage quality for deer and other large herbivores. We used NDVI metrics derived from 1 km Advanced Very High Resolution Radiometer (AVHRR) satellite imagery. For each DAU, on an annual basis, we determined the length of the growing season, time peak plant productivity, the rate of “green-up” across the season, and the cumulative area under the curve for the growing season. Data on fire history were obtained from the Monitoring Trends in Burn Severity (MTBS) project of the US Geological Survey and USDA Forest Service. This nationwide dataset maps the boundaries of wildfires as polygons on an annual basis between 1985 and 2010, on a 100 m spatial resolution. Information on changes to deer habitat due to climate, energy development, residential development, plant productivity and wildlife will be 1) distributed to biologists and relevant CPW staff in western Colorado to aid in future DAU planning, and 2) used to assess whether spatial and temporal changes to mule deer habitat are related to deer recruitment, a key measure of deer population performance. Results of this work will benefit wildlife professionals at statewide, regional, and local scales that will be able to use project results to help prioritize habitat enhancement efforts, connect deer population objectives to landscape conditions, identify key areas for habitat protection, provide comments on land-use proposals, develop policies related to land-use in critical deer ranges, and quantify general habitat impacts that are relevant to deer across western Colorado. Figure 1. The area of interest including all deer analysis units west of Interstate 25 in Colorado. Colorado state boundary 10unit (DAU) Deer analysis Interstate highway 25 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation and incorporation of life history traits, nutritional status, and browse characteristics in Shira’s moose management in Colorado Period Covered: July 1, 2013 − June 30, 2014 Principal Investigator: Eric J. Bergman, eric.bergman@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. We initiated a large scale moose research project in November of 2013. Preliminary field efforts were centered on ground and helicopter darting of moose. The majority of captures occurred during January of 2014. Capture efforts were focused in 3 study areas in Colorado — the Laramie River and Red Feather Lakes areas (NE Colorado), the Rabbit Ears range that separates North Park from Middle Park (NW Colorado), and along the Upper Lake Fork, Rio Grande Reservoir, and near Slumgullion Pass (SW Colorado). All captured moose were fitted with either GPS or VHF collars. Body condition and pregnancy status of each captured animal was also evaluated at time of capture. Survival status of collared animals was monitored through June 2013. Additionally, preliminary calf twinning rates and observations were documented in the northeast region. Survival rates tended to be high and little variation was observed among study areas but pregnancy rates were highly variable among study areas. A total of 58 moose were captured and collared during the 2013–2014 field season. Twenty moose were captured in each of the NW and NE study areas. Eighteen moose were captured in the SW study area. Of these 58 animals, 2 animals in the NE study area were captured via ground darting. The remaining moose were captured via helicopter darting. The majority of captures (n=55) occurred in late January. For purposes of body condition evaluation, it is expected that the greatest amount of variation will be observed during early winter, such that the majority of variation can be explained by individual reproductive and habitat use characteristics. Thus, captures during the late January time frame were not ideal and future efforts will concentrate on early time periods. Survival of radio collared animals was high in all study areas. Survival rates ranged between 0.94–1.00 from the time of capture through the end of June. Pregnancy rates by study area at the time of capture were highly variable (range: 0.60–0.95). Anecdotal calf:cow ratio data were also collected at the time of capture. While these ratios are vulnerable to observer bias (i.e., false negatives can be expected to occur at a greater frequency), the observed rates shadowed pregnancy rates and ranged between 0.27– 0.72. Mean measured rump fat at the time of capture ranged between 2.6–4.2 mm among study areas. Mean measured loin depth at the time of capture ranged between 40.9–49.6 mm among study areas. Pregnancy status was best predicted by measured loin depth. Moose data collected during this period largely met expectations. In particular, survival rates were high in all study areas. However, it was also assumed that not all of Colorado’s moose herds are equally productive. This assumption was largely validated by variation in pregnancy rates. However, additional years of data collection are needed to confirm this result. Within this, the age of captured animals remains unknown and could partially explain the variation in pregnancy data. Addition of annual browse utilization data will occur during spring 2015, and will hopefully provide insight into body condition and pregnancy status of animals. This study is scheduled to continue through 2021. 11 �Figure 1. Moose research study areas, located in 3 regions in Colorado. A total of 58 moose were captured during the winter of 2013–2014. Twenty moose were caught in the Northeast and Northwest regions, 18 moose were caught in the Southwest region. Survival of moose was high in all study areas. Figure 2. At the time of capture, moose were fitted with either a GPS or VHF collar. Data on body condition and pregnancy status were also collected at this time. 12 �Figure 3. Moose body condition was highly variable within study areas, although variation among areas was not as pronounced. 13 �14 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2013 − June 30, 2014 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: S.A. Lischka, S. Breck, J. Beckmann, J. Broderick, J. Apker, K. Wilson, and P. Dorsey All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or just bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a unique collaboration that builds on the resources and abilities of personnel from 4 entities: Colorado Parks and Wildlife (CPW), the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have designed and implemented a study on black bears that 1) determines the influence of urban environments on bear behavior and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. This project was initiated in FY2010-11; during this past fiscal year we have primarily focused on collecting field data in the vicinity of Durango, Colorado. Our efforts focused largely on field data needed to meet research objectives 1-3, information which will eventually be used to address objective 4. Specifically, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, collected GPS collar location data on bears along the urban-wildland interface, monitored bear demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, collected data on the availability of late summer/fall mast, tracked human-related bear mortalities and removals from the study area, performed non-invasive genetic mark-recapture surveys, deployed an additional ~150 bear-resistant containers for an experiment on the effectiveness of urban-bear-proofing for reducing bear-human conflicts, obtained data on garbage-related bear-human conflicts, monitored resident use of project-supplied bear-resistant garbage containers, and conducted a survey assessing resident attitudes about bears and bear-human interactions. • • Major research accomplishments from fiscal year 2013-14: Between June 2013 and April 2014 (the 2013-2014 capture year), an additional 75 unique bears were marked during 206 bear captures. To date on the project there have been 280 different individuals marked during 601 captures. Nine new adult females were collared during summer 2013 to collect demographic and habitat-use data. Bear capture and marking efforts are allowing us to track bear population parameters and habitat-use patterns along the urban-wildland interface. During January - March 2014, we visited the winter dens of 35 collared females (Photo 1). Of those females, 13 did not have any cubs or yearlings, 9 had yearlings (13 total yearlings in total), and 13 15 �• • • • had newborn cubs (26 cubs). We found that reproductive success, measured as the number of live cubs/adult female was 0.74 (SE = 0.18) for winter 2014, compared to 0.95 (SE = 0.24) in 2012 and 0.52 (SE = 0.16) in 2013. Cub survival for 2014 (survival from newborn to 1 year) was 50% (based on 12 cubs), compared to 40% in 2013. To date, we have obtained >300,000 locations from GPS collars on 67 different adult female bears along the urban-wildland interface; 42 different bears provided location data during the active bear year of 2013 (May – October; Fig. 1). While most locations were in close proximity to Durango, a Photo 1. Sow and cub in a den. few animals ventured outside the primary study area, including a sow that moved to New Mexico (Fig. 1). Location data are being used to assess drivers of bear resource-use of human development. In summer 2013, we collected 1,365 hair samples for a non-invasive genetic mark-recapture study designed to estimate bear densities and population sizes around the vicinity of Durango and an adjacent “wildland” site. Over a 6 week sampling period, a total of 680 hair samples were collected from the Durango grid and 685 samples from the wildland grid. From those samples, 693 valid genotypes were obtained; 334 from the Durango grid and 359 from the wildland grid. Around Durango, 86 different individuals were detected during 160 “captures” (multiple hair samples from a single bear during 1 week were considered 1 “capture”). For the wildland site, 110 different individuals were detected during 183 “captures.” Detailed mark-recapture analyses of these data will be conducted in the future to estimate annual density and abundance at each site. During summer 2013 (July through September) we collected our first year of post-treatment data on an experiment designed to assess the effectiveness of wide-scale urban bear-proofing for reducing bear-human conflicts (pre-treatment data were collected during 2011 and 2012). Within treatment and control areas we observed 330 instances of bears accessing residential garbage during morning patrols; observations peaked in early September. Of those garbage containers accessed by bears, 84% were regular and 16% were bear-resistant; 131 garbage conflicts were observed in treatment areas (across 1,231 total residences) and 156 occurred in control areas (across 1,259 total residences). In spring 2014 an additional 150 containers were deployed to “clean up” treatment areas and ensure that all residences had a bear-resistant garbage container (Fig. 2). We will continue to collect posttreatment data through 2015. Between January and April 2014, a second mail survey of resident attitudes about bears was administered. Surveys were sent to all residents within Durango city limits and a random sample of 1,500 residents outside city limits but within the study area. A total of 5,853 residents were surveyed, yielding an adjusted response rate of 45%. Detailed analysis of tolerance for black bears, compliance behaviors and perceived risk of bear-human conflicts will be conducted in future years. In addressing our research objectives we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between bear-human conflicts and bear behavior and demography, understand the effect of bear-human interactions on human attitudes and actions, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. See Johnson et al. (2014, Federal Aid Report W-204-R1) for a more detailed version of this project summary. 16 �Figure 1. GPS collar locations from 42 adult female black bears collected during 1 January–31 December 2013 in the vicinity of Durango, Colorado (different colored clusters of points represent different individual bears): A) an overview of all locations and B) locations around the town of Durango. A B 17 �Figure 2. Change in garbage containers (regular to bear-resistant) at residences in experimental areas pretreatment (2012) and post-treatment (2014), Durango, Colorado. 18 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Shifting perceptions of risk and reward: temporal and spatial variation in selection for human development by black bears around three urban systems Period Covered: July 1, 2013 − June 30, 2014 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: Stewart W. Breck, Sharon Baruch-Mordo, David L. Lewis, Carl W. Lackey, Kenneth R. Wilson, John Broderick, Julie S. Mao, and Jon P. Beckmann All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. As landscapes across the globe rapidly change due to increased human development, there is uncertainty about the behavioral responses of wildlife to these changes given associated shifts in resource availability and risk. Human development typically reduces native foods for animals, but introduces novel anthropogenic foods (crops, livestock, garbage, watered landscaping, etc) along with risks associated with foraging in human-dominated landscapes. The initial response of animals to human development is typically a change in behavior, as animals have been observed to alter patterns of habitat selection, vigilance, daily activities and foraging, often in highly diverse ways. These behavioral responses reflect perceived trade-offs between the benefits of acquiring key resources and the risks associated with human activity. While these trade-offs should be dynamic in space and time as a function of habitat quality, natural food conditions and the physiological states of individuals, little is known about how animals in human-altered landscapes behaviorally adapt to such variation, particularly under varying ecological conditions. Elucidating the behavioral responses of wildlife to human development is particularly important for large carnivores as their home ranges frequently overlap with human infrastructure and activities, and their interactions with people are often a major source of conflict. In many cases, large carnivores avoid people indicating they associate humans with risk. Some carnivores, however, forage within human development on their natural foods or on anthropogenic foods, exploiting resources associated with human infrastructure. Such behavior has been associated with increased human-carnivore conflicts, generating concern over human safety and property, and stymieing conservation efforts for some carnivore species. If wildlife managers are going to be successful at reducing human-carnivore conflicts and promoting public tolerance for these species, they need to understand how these animals are behaviorally responding to increased development, and the conditions that modify their behavior. These concerns are particularly relevant for black bears (Ursus americanus). Bears can readily exploit the wealth of reliable, high-calorie food resources available around residential development (i.e., garbage, fruit trees, livestock), but are also susceptible to increased mortality from vehicle collisions, conflict-related euthanasia, and other human-related factors. Although studies have found that bears perceive risk associated with human activity, human-bear conflicts have generally increased over time, albeit highly variable. As a long-lived species with relatively stable population dynamics, variation in conflict activity is likely a consequence of shifting foraging behavior, not shifting population sizes, as bears reassess trade-offs of using human foods. Factors such as natural food conditions, a bear’s gender, age, physiological state (e.g., reproductive status), or degree of exposure to human activity, may influence 19 �the benefits and risks of foraging in human-dominated landscapes, driving observed variation in conflict activity. To understand how a large carnivore weighs the benefits and risks of using human development, we examined patterns of black bear resource selection in three developed areas in the western US (Aspen [CO], Durango [CO], and Lake Tahoe [NV]). Using data from 109 bears, our objectives were to 1) examine temporal patterns of selection for development within and across years, 2) compare spatial patterns of selection for development across study systems, and 3) identify individual attributes (e.g., age, maternal status) associated with increased selection for development. Using mixed effects resource selection models we found that use of development by bears was similar across study sites, modifying their selection within and across seasons based on changing environmental and physiological conditions (Fig. 1). Results were based on 331851 locations collected May - October; 87,530 locations for Aspen females (14 different bears), 82,272 for Aspen males (29 bears), 152,365 for Durango females (50 bears), and 9,684 for Tahoe females (16 bears). Selection for human development was tied to nutritional demands, as bears increased their use of anthropogenic foods throughout the summer-fall and in years with poor natural food availability (Figs. 1 and 2). Selection also appeared to be related to bear experience, increasing with animal age. While there were general trends in how bears selected for human development across sites, there were also idiosyncratic differences between them. For example, Aspen males, Aspen females, and Tahoe females tended to select for intermediate development densities, while Durango females displayed a bimodal pattern of either selecting for very high or very low development densities (Fig. 1). In Aspen, males selected for intermediate densities of development in both good and poor natural food years (amplifying their selection for development in poor food years), while females avoided areas with high development densities in good natural food years and strongly selected for high development in poor years, particularly during hyperphagia (Fig. 1). Our findings illustrate that for three areas in the western US black bears selected positively for human development, increasing their use of development in years with poor natural food conditions, throughout the summer-fall, and as bears increased in age. These patterns were generally consistent across study systems and over numerous years of data collection, despite variation in individual bear behavior. Such patterns suggest that bears are similarly interpreting the shifting benefits and risks associated with foraging in human-dominated landscapes, as factors such as natural food conditions, physiological state (i.e., hyperphagia), and experience with anthropogenic foods, simultaneously shape their habitat selection decisions. Variation in bear use of development appeared to be primarily tied to nutritional demands, as the benefits of obtaining anthropogenic foods likely outweighed the risks of foraging around human activity when bears needed additional food resources. Results from this study have key implications for bear management. Wildlife agencies often assume that bears exposed to human food will consistently exhibit nuisance behavior, but our results suggest that bear behavior can be highly variable within and across years, and that bears may often use anthropogenic resources as a source of subsidy rather than relying on those resources outright. Because bear populations are notoriously difficult to monitor, wildlife agencies also often assume that increases in human-bear conflicts reflect increases in bear populations. Our work, however, suggests that bear selection for development may be increasing over time, particularly as individuals get older and gain experience with anthropogenic foods. This behavior may then be the source of additional conflicts without an associated increase in population size, a pattern that has been observed for polar bears. As human development continues to permeate bear habitat, and as changes in climate reduce natural foods for bears in some areas, we expect that bear exposure to development and anthropogenic foods will increase as will their selection for these resources. 20 �Figure 1. Black bear probabilities of selection for density of human development from May through October in Aspen (CO), Durango (CO), and Tahoe (NV), USA. Warm colors depict selection during poor natural food years and cooler colors depict selection in good natural food years. Data for bears in Tahoe were not available for years with different natural food conditions. Note: Durango experienced a maximum of 375 human structures/km2, while Aspen and Tahoe had maximum densities of 540 and 660 structures/km2, respectively. Figure 2. Spatial predictions of resource selection from female black bears in Durango, Colorado, for a good (A) and poor (B) natural food year during fall (Oct 1st). 21 �22 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mountain lion population responses to sport-hunting on the Uncompahgre Plateau, Colorado Period Covered: July 31, 2013 ─ June 30, 2014 Principal Investigator: Kenneth A. Logan, Ken.Logan@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. The Colorado Parks and Wildlife (CPW) initiated a 10-year study in 2004 on effects of sporthunting on a mountain lion population on the Uncompahgre Plateau. This study was designed to provide information that can be applied to lion management. The study quantifies lion population characteristics in the absence of hunting (termed the reference period, years 1-5) and the application of hunting (termed the treatment period, years 6-10). The purpose of the study is to evaluate the current biological assumptions used by CPW to manage lions with hunting and to learn how lion hunter behavior may influence harvest. Testing the management assumptions is important because managers normally have no information on lion abundance, population sex and age structure, or effects of hunting on lions for any region of Colorado. Therefore, managers are highly dependent on assumptions. Lion hunter behavior is important to understand because it may influence the sex and age structure of lions killed by hunters, and those harvest data are used by CPW managers in an effort to make biological judgments about lion populations and effects of hunting. The reference period began December 2004 and ended July 2009, during which we captured, sampled, and marked 109 individual lions for research purposes. During this period without sport-hunting as a mortality factor the population of independent lions comprised of adults and subadults increased from a low of 33 lions counted in reference year 4 to a high of 55 lions counted in the treatment year 1 (Fig. 1). This was an indication that lion management on the Uncompahgre Plateau previous to this study may have suppressed the lion population. Along with the population increase during the reference period, adult lion survival was high and the age structure of independent lions increased; expected characteristics of an increasing population. The main cause of death in adults was aggression by other lions. Only one death of a radio-collared independent lion was due to human causes; an adult female killed for depredation control purposes. Infanticide by male lions was the main cause of death for cubs. The treatment period, in which managed sport-hunting of lions was applied on the study area, began August 2009. Since then 115 additional lions were captured and marked for research purposes. As indicated previously, treatment year 1 was the first year that hunting influenced the lion population after 5 years of no hunting and it was marked with the highest estimate of independent lions (55) on the study area. During treatment years 1 through 3, the lion harvest rate was set with a quota of 8 lions to test a prediction that a 15% harvest of independent lions would result in a stable-to-increasing lion population. This is an important management assumption to test because it represents a maximum mortality rate on independent lions that was assumed to achieve a stable-to-increasing population trend; one of two CPW lion population management objectives that are applied to certain regions (Data Analysis Units, DAUs, each comprised of multiple Game Management Units, GMUs). This objective provides a capacity for a lion population to be resilient to all causes of mortality, including hunting and assists CPW to achieve a goal for a healthy, self-sustaining lion population state-wide while providing hunting opportunity. However, the expectation that a 15% harvest results in a stable-to-increasing population was not supported as the population of independent lions declined from 55 in treatment year 1 to 42 by treatment year 4 (Fig. 1). The other CPW lion management objective is to manage certain regions to substantially 23 �reduce or suppress lion abundance with hunting. Results from treatment years 1 through 4 indicated that reducing a lion population with hunting is achievable with as low as 15% harvest of independent lions. The lion population was expected to continue to decline if the quota remained at 8 lions because 8 lions represented a 19% harvest by treatment year 4, a larger percentage than the 15% harvest that had already contributed to population decline. Therefore, in an effort to find a harvest rate useful to managers that would result in a stable-to-increasing population for the remainder of the study, the quota was reduced to 5 lions. This quota represented about 11-12% harvest rate of independent lions for treatment years 4 and 5. The count of independent lions in treatment years 4 and 5 were 42 and 44 lions, respectively, suggesting that the lower harvest rate of 11-12% resulted in a cessation of the decline and a stabilization, if not marginal increase, in the number of independent lions. During the treatment, the main cause of death to independent lions was hunting. Survival rates of adult lions declined as did the age structure of independent lions, as expected in a declining population. Infanticide by male lions was the main cause of death for cubs, just as it was in the reference period. During the treatment period, additional independent radio-collared lions were killed by hunters outside of the study area during the Colorado lion hunting season spanning November through March each winter. Those lions were counted as part of the harvest quotas in other GMUs. This occurred even though the study area was a large GMU in Colorado. Home ranges of most lions, particularly of males, were large enough to span at least two GMUs so lion movements put some individuals at risk to hunting mortality even after the study area quota was filled and closed to hunting for the remainder of the season. The total hunting mortality plus other human causes of mortality, such as road kill and depredation control, and natural mortality that occurred throughout the year contributed to the lion population decline and low phase (Fig. 1). This indicated a need for managers to consider how all mortality might impact a lion population. The phenomenon of lion movements spanning GMU boundaries also revealed that hunting can affect lion populations at considerably larger spatial scales than the current GMU structure. Data from voluntary surveys of lion hunters on the study area revealed that a large majority of lion hunters used dogs. A large majority of lion hunters considered themselves to be selective hunters, meaning they specifically hunted for a specific type of legal lion such as a male, large male or large female, and therefore attempted to distinguish between male and female tracks, and large and small males or females. Moreover, data on the actual hunting experience of hunters that answered the survey supported the hunters’ claims and indicated that they generally detected female lions in the field more frequently than male lions, yet they strongly selected to kill male lions, and they sometimes captured and released female and small male lions. The lion harvest composition was strongly influenced by hunter predilections. Hunters did not merely sample the lion population at random or kill the most detectable lions. Even though lion hunters generally selected to kill males, the lion population declined with a 15% harvest of independent lions (Fig. 1). Besides the study on effects of sport-hunting on lions, other projects associated with lion ecology were developed in collaboration with colleagues in CPW, Colorado State University, Colorado Cooperative Fish and Wildlife Research Unit, Oklahoma State University, and University of Arizona. We collaborated with Ph.D. student Jesse Lewis and Dr. Kevin Crooks (C.S.U., Dep. of Fish, Wildlife, and Conservation Biology) from August to December 2009 in a study of relationships of bobcats to mountain lions and considerations in using a camera grid with marked lions to estimate lion detection, abundance, and density. Jesse is currently involved with data analysis and writing on that project, projected completion December 2014. We collaborated with Master’s student Kirstie Yeager (Colorado Cooperative Fish and Wildlife Research Unit) and Dr. Mat Alldredge (Mammals Researcher, CPW) from December 2012 to March 2013 to test non-invasive methods for tissue-sampling lions for efforts to estimate abundance. This effort also allowed us to assess the proportion of lions marked in the population in winter on the Uncompahgre Plateau study. A sampling grid with 2 by 2 kilometer cells covering 540 square kilometers was established on the study area. A total of 54 random cells were sampled with digital wildlife cameras and electronic predator calls. Eighteen photographs of lions were recorded by cameras, and all 18 photos depicted radio-collared lions that could be identified to the individual. Of the 11 collared lions known to use the grid, seven of them were photographed one to four times each. The 24 �probability of detecting collared lions during the entire survey time was 0.64. Projected completion of Kirstie’s study is May 2015. We are involved in ongoing studies of diseases in mountain lions with Dr. Sue VandeWoude (C.S.U., Dep. Of Microbiology, Immunology, and Pathology), Dr. Kevin Crooks and their colleagues and graduate students. Diseases and pathogens to which lions sampled from the Uncomphagre Plateau study area were exposed, included: plague (caused by the bacteria Yersinia pestis), Feline immunodeficiency virus (a lentivirus), Bartonnela sp. (a vector-borne bacteria), and Toxoplasma gondii (a protozoan). In addition, Dr. Mason Reichard (Dep. of Veterinary Pathology, Oklahoma State University) found that up to 45% of independent lions sampled may be infected with Trichinella sp. (a nematode). Finally, we are collaborating with Dr. Melanie Culver (Arizona Cooperative Fish and Wildlife Research Unit, Univ. of Arizona) and Ph.D. student Alex Erwin (Univ. of Arizona, Conservation Genetics Lab) to examine lion genetic relatedness, reproductive success, and population structure. Field operations for this study will be completed by end of December 2014. Starting January 2015 the principal investigator along with collaborators will begin a formal phase of data analysis and write-up to prepare the information for application in lion management in Colorado. Mountain Lion Population Trend, Uncompahgre Plateau, Colorado No. of Independent Lions 60 55 52 48 50 45 40 47 43 33 42 44 40 41 30 44 39 37 38 33 33 TY3 TY4 20 10 0 RY4 RY5 Minimum Count TY1 TY2 Harvest reduction TY5 All mortalities reduction Figure 1. Trends in the population of independent mountain lions associated with no sport-hunting in the reference period years 4 and 5 (RY4, RY5) and with sport-hunting in the treatment period years 1 through 5 (TY1 to TY5), Uncompahgre Plateau, Colorado. The minimum count data were gathered from November through April each winter in efforts to canvass the study area thoroughly to count the number of independent lions in addition to non-marked lions killed by hunters. These data represent the number of independent lions expected to be on the study area during November through March each winter and coincided with the Colorado lion hunting season. 25 �26 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Cougar and black bear demographics and cougar-human interactions in Colorado Period Covered: July 1, 2013 − June 30, 2014 Principal Investigator: Mathew W. Alldredge, mat.alldredge@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. PROJECT NARRITIVE OBJECTIVE 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban Front Range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus), assessing diet composition and estimating population densities of cougars for the state of Colorado. SEGMENT OBJECTIVES Section A: Telomeres and Stable Isotopes 1. Evaluate the potential to develop a model for estimating age of bears and cougars based on telomere length. 2. Determine diet composition of bears and cougars using stable isotopes. Section B: Front Range cougars 3. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. 4. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets (Completed). 5. Continue to assess relocation of cougars as a practical management tool. 6a. Assess cougar predation rates and diet composition based on GPS cluster data (Completed). 6b. Assess kill site dynamics and prey selection of cougar kills. 7. Model movement data of cougars to understand how cougars are responding to environmental variables. 8. Develop non-invasive mark-recapture techniques to estimate cougar population size. 2013-2014 Project Overview Field efforts during 2013-2014 were primarily focused on the development of noninvasive population estimation techniques for cougars and bobcats (see summary for Noninvasive genetic sampling to estimate cougar and bobcat abundance, age structure, and diet composition). The field efforts for the remaining segment objectives listed above have been completed and are in various stages of data analysis and publication. 27 �Section A: Telomeres and Stable Isotopes 1. Evaluate the potential to develop a model for estimating age of bears and cougars based on telomere length. Field work completed—data analysis and publication in progress (see summaries Spatiotemporal patterns of diet and telomere length in Colorado black bears and Effect of human activity on cougar diet and age structure: non-invasive approaches) 2. Determine diet composition of bears and cougars using stable isotopes. Field work completed—data analysis and publication in progress (see summaries Spatiotemporal patterns of diet and telomere length in Colorado black bears and Effect of human activity on cougar diet and age structure: non-invasive approaches) Section B: Front Range cougars 3. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. Field work nearly completed—see Federal Aid report for preliminary summaries 4. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets. Field work completed—see Federal Aid report for preliminary results and summaries 5. Continue to assess relocation of cougars as a practical management tool. In progress—see Federal Aid report for preliminary data 6a. Assess cougar predation rates and diet composition based on GPS cluster data. Field work completed—data analysis and publication in progress (see summary Puma foraging in an urban to rural landscape) 6b. Assess kill site dynamics and prey selection of cougar kills. Field work completed—data analysis and publication in progress (see Predator-prey dynamics in relation to chronic wasting disease and scavenging interactions at cougar kill sites) 7. Model movement data of cougars to understand how cougars are responding to environmental variables. Field work completed—contact Mat Alldredge for current publications. 8. Develop non-invasive mark-recapture techniques to estimate cougar population size. Field work completed—data analysis and publication in progress (see summary The Use of Lures, Hair Snares, and Snow Tracking as Non-Invasive Sampling Techniques to Detect and Identify Cougars) 28 �Noninvasive genetic sampling to estimate cougar and bobcat abundance, age structure, and diet composition Cougar and bobcat populations are actively hunted throughout the state of Colorado and management is applied using the best available information. Unfortunately, reliable information on cougar and bobcat populations is nascent. The best information available comes from long-term studies on relatively small populations where animals have been repeatedly captured. However, to better manage these populations, broad-scale information for these species is necessary. We have begun developing noninvasive genetic sampling (NGS) techniques to provide better, less expensive data for cougars and bobcats that can be implemented at broad geographic scales with state-wide application. The methods being developed should provide information on population size/trend, sex structure, age structure, and diet composition. This information is valuable to the future management of these species and for the justification of harvest levels imposed on them. Over the next few years we intend to further refine these NGS techniques for cougars and bobcats so that they can be reliably implemented to inform management decisions. We also intend to perform at least one full survey over multiple years so that we can assess the reliability and repeatability of this approach. Following these efforts our hope is that we will have a fully developed NGS approach for cougars and bobcats that can be implemented at a state-wide level for future monitoring of these species. Objectives: 1. Continue to evaluate the use of auditory calls for NGS sampling of cougars. 2. Implement a NGS survey for cougars over multiple years to evaluate the consistency of the approach. 3. Use collared cougars to evaluate trap response of cougars and assess potential biases in the NGS approach. 4. Evaluate the potential to sample bobcats using the same NGS approach. 5. Test alternative hair snaring devices for felids. 6. Assess a simultaneous sampling approach for bobcats and cougars relative to differences in home-range size. 7. Implement an NGS survey over multiple years for bobcats and cougars to determine the logistics, cost and feasibility of sampling to obtain estimates of density, sex structure, age structure and diet composition. Following on the success of the development of noninvasive techniques for sampling cougars (reference attached summary) we initiated a three year study to continue to develop noninvasive methods for sampling cougars and bobcats. Sites were built in November and December, 2013, and were monitored for 12 weeks during January – April, 2014 (Reference FA report – website link?). A total of 105 sites were set starting on January 6, 2014 and concluding on April 9, 2014. Individual sites were active for an average of 82 days (range 26-82) for a total of 5,178 site days. A minimum of 61 cougar detections were documented during the sampling at 37 different sites. A total of 78 hair samples were collected from cougars, but these did not always have photographic evidence of the detection. Although it was not emphasized 16 cougar tracks were recorded at sites. There were also many occasions where cougars were detected but did not leave hair samples on the snags. A minimum of 18 bobcat detections were documented on camera during the sampling at 16 different sites. Only 1 hair sample was obtained from these bobcats. Likely this is because hair snags were set at heights more appropriate for snagging cougar hair. The potential for setting vertical snags instead of horizontal snags needs to be investigated as they may be less sensitive to animal size. Bobcat tracks were seen at 3 different sites. This study is scheduled to continue through spring of 2016. 29 �Figure 1: Study area boundary and grid layout for NGS cougar and bobcat sites. Larger squares represent the 5 km2 grid overlaid with a 1 km2 grid. White 1 km2 cells represent the randomly selected cells where actual lure sites will be placed. 30 �Spatio-temporal patterns of diet and telomere length in Colorado black bears Becky Kirby (UW-Madison), Jonathan Pauli (UW-Madison), Mat Alldredge (Colorado Parks & Wildlife) The effect of human-derived food on free-ranging wildlife populations is a growing problem across North America, and is particularly evident among carnivore populations. In Colorado, American black bear (Ursus americanus) conflicts have been increasing, and research is focused on elucidating factors that drive such conflicts. Understanding the influences of food availability and population trends is necessary to mitigate risks posed by these conflicts. To this end, this project aims to assess broad-scale patterns of diet and age in black bears across Colorado in hunter-harvested bears. We are quantifying diet and telomere length of black bears, in relation to geographic and habitat variables. Specifically, we are examining the amount of human food consumption, compared to native foods. Because human food is often underestimated using traditional diet reconstruction analyses due to issues such as digestibility, we are using stable isotope analyses that reflect assimilated diet. Further, we are examining a non-invasive technique related to aging in black bears, using genetic analyses of telomere length measured by qPCR. Telomere length is related to chronological age, but also can be a valuable indicator of fitness and senescence. In fall 2011, we collected hair and blood samples from ~400 hunter-harvested and nuisance bears, and have analyzed the isotopic signature in δ13C and δ15N. Enriched (higher) signatures likely indicate greater consumption of human-derived foods and animal matter, respectively. Adults and eastern bears are significantly enriched in both δ13C and δ15N in hair samples. Females are also enriched in δ13C, as well as nuisance/roadkill bears (Table 1). Using stable isotopic mixing models parameterized with diet samples, preliminary results indicate that as a whole population, Colorado bears are primarily consuming vegetation (80-90%), followed human-derived foods (~10%), and very little animal matter (Figure 1). These preliminary analyses suggest individual and seasonal differences in diet, and refined analyses are forthcoming. We also quantified relative telomere length from these hair follicles in 248 individuals, ranging in age from 1-21 (estimated by cementum annuli). Samples exhibit wide variation among telomere length (T/S) across ages, showing no significant trend (Figure 2). Further, we found no relationship with either sex or head size of individuals and telomere length. Because these individual characteristics seem to play little role in telomere attrition in this population, we sought to examine other factors that may be driving telomere length in Colorado bears. So far, the strongest patterns of telomere length emerge along latitude and elevation; telomere length is negatively correlated with both (Figure 3). Because we are starting to see interesting patterns in telomere length, ongoing longitudinal studies are necessary to elucidate rates of change rather than single time-point samples and increase resolution of covariates. This study will yield insight into bear foraging ecology and aging, especially how human food and land use impacts both. Further development of these isotopic and molecular techniques will be aid in future bear management and biological studies. 31 �Table 1. Stable isotope signatures of Colorado bear hair (represents summer diet) and blood (represents fall diet) grouped by region, age class, mortality type, and sex. Eastern bears are generally enriched in δ13C and δ15N in hair samples, as are adult bears. Blood samples of each, however, are less differentiated, suggesting a more uniform fall diet. Conflict bears are enriched in δ13C and δ15N. Females are enriched in δ13C in hair compared to males, but there is no difference between sexes in blood samples. Group Comparisons NE NW SE SW n 45 126 86 97 p-value 156 61 106 Adults SubAdults Juveniles p-value Hunter-harvested 325 Nuisance/Roadkill 29 p-value Male Female 218 135 p-value Stable Isotope Signature Hair Blood 13 15 13 δ C δ N n δ C δ15N -20.93a -22.20b -20.90a -22.01b <0.001 -21.46a -21.58ab -22.09b <0.001 -21.77 -20.55 <0.001 -21.80 -21.47 0.01 4.95 5.05 5.81 5.05 <0.00 1 5.51 5.38 4.78 <0.00 1 5.15 6.02 0.001 5.32 5.06 0.05 19 49 41 43 -22.18a -23.85b -22.34a -23.78b 5.93 5.52 5.92 5.17 67 27 41 <0.001 -23.31a -22.89a -23.37a 0.03 5.61 5.87 5.33 0.37 127 -23.37 25 -22.43 0.22 5.45 6.24 0.01 -23.19 -23.24 0.82 0.007 5.69 5.39 0.16 95 56 32 �Figure 1. Results from SIAR for Colorado bear hair (n=354) analyzed as a single population, characterized by diet mixing space indicating proportional contributions of each diet group. Figure 2. Age and telomere length (T/S) (n=220). No significant relationship. 33 �b) a) Figure 3. a) Telomere length (T/S) regressed on UTMy coordinates (latitude) showing a significant trend toward shorter telomeres farther north. P<0.001, Adj. R-squared = 0.09. b) Telomere length (T/S) regressed on elevation showing a significant trend toward shorter telomeres at higher elevations; P<0.007, Adj. R-squared = 0.03. 34 �Effect of human activity on cougar diet and age structure: non-invasive approaches Wynne Moss (UW-Madison), Jonathan Pauli (UW-Madison), Mat Alldredge (Colorado Parks & Wildlife) The cougar (Puma concolor) is an ecologically important top predator, and one that is increasingly found in urban areas. In the Front Range of Colorado, cougars frequently utilize rapidly expanding urban and exurban habitats, leading to a high incidence of cougar-human conflict. Understanding how and why cougar use these habitats would help mitigate risk to both humans and cougars. In particular, examining the foraging behavior of cougars is a high priority, as it can drive habitat use and propensity for conflict, and is important for predicting their influence on native prey species. We are quantifying the habitat use and diet composition of cougars in both wildland and nearurban environments of Colorado to understand how urbanization may alter foraging ecology. Specifically, we are comparing the diets of cougars on the Uncompahgre Plateau (a wildland area) to those in the Front Range (a near-urban area). To better understand the factors influencing cougar prey use, we are also examining how diet composition in the Front Range is related to cougar age-sex class, body condition, and habitat use. Because cougars are cryptic in behavior, we are utilizing stable isotope analysis, which has the potential to be applied non-invasively, to study diet. In addition to developing a non-invasive approach for studying diet, we are also exploring ways to non-invasively monitor cougar age structure through genetic analysis of telomere length. Beginning in 2012, we have collected hair samples from both cougar and potential prey species, and have analyzed the isotopic signature in δ13C and δ15N (Table 1). Using stable isotope mixing models, we estimated the relative importance of different classes of prey to cougar diets. We found that cougars in the Front Range obtained 67-76% of their diet from native herbivores, mostly elk and deer, whereas in the Uncompagre Plateau, nearly all of the diet (98-100%) came from native herbivores (Figure 1). Individuals in the Front Range population were much more heterogeneous in diet, and these differences appeared to be driven mostly by habitat use. Individuals who foraged in areas of higher housing density relied more heavily on smaller-bodied prey, like synanthropic wildlife and domestic species (Figure 2). Males were also more likely to use non-ungulate prey than females. Finally, we have obtained blood and hair samples from known-age cougars on the Front Range and have begun extracting DNA to measure relative telomere length. In numerous mammals, telomeres shorten as an individual ages, and thus shorter telomeres indicate an older individual. This relationship has not been characterized in cougars; therefore it is not known whether such a correlation exists. In the upcoming year, we will utilize quantitative PCR to estimate telomere length, and examine whether this technique could be used to age non-invasively obtained hair samples. This study will yield novel insights into cougar foraging ecology, primarily how diet is affected by human activity. In addition, we are developing important tools to non-invasively monitor cougars that could help implement more cost-effective and wider-scale studies of their behavior and population biology. 35 �Table 1. Stable isotope values for cougars and their potential prey in the Front Range (FR) and Uncompahgre Plateau (UP) study areas, 2007-2013. Isotope values are given in ‰, relative to international standards and are not corrected for trophic discrimination. When prey signatures were not different between study sites, they were grouped. The Front Range population has higher variability in isotopic signature, and therefore diet. δ13C (‰) Mean ± SD δ15N (‰) Mean ± SD Sample n Cougar 41 FR -21.3±0.7 8.1±0.8 63 8.5±0.5 UP -21.6±0.5 Prey Small domestics1 29 -16.7±2.4 6.2±1.3 2 Synanthropic wildlife 38 -20.6±1.3 7.4±1.4 Large domestics3 26 -22.5±1.4 6.9±1.6 4 Native herbivores (FR) 48 -24.4±1.0 3.8±1.5 Native herbivores (UP) 15 -24.1±0.4 5.0±1.1 1 Small domestics: cat (Felis catus), dog (Canis familiaris), chicken (Gallus domesticus) 2 Synanthropic wildlife: raccoon (Procyon lotor), skunk (Mephitis mephitis), fox (Vulpes vulpes), coyote (Canis latrans), squirrel (Sciurus spp.) 3 Large domestics: llama (Llama glama), sheep (Ovis aries), goat (Capra aegagrus), alpaca (Vicugna pacos) 4 Native herbivores: mule deer (Odocoileus hemionus), elk (Cervus elaphus), rabbit (Sylvilagus nuttallii) 36 �Figure 1. Relative contributions of diet items to the cougar populations in the Front Range (left) and Uncompahgre Plateau (right). Output from isotope mixing models are shown as density plots from simulations, or the relative likelihood of a diet item occurring in a given proportions. Native herbivores (NH) contribute the most to both populations’ diet, followed by large domestics (LD), synanthropic wildlife (SW), and small domestics (SD). Cougars in the Uncompahgre Plateau rely much more heavily upon native herbivores, primarily elk and mule deer. 37 �Figure 2. Effect of housing density and sex on proportional contribution of native herbivores to cougar diet. Housing density at foraging locations and sex were the two most important covariates in predicting isotopic signature. The percent of diet from native herbivores was estimated using mixing models and mean and 95% credibility intervals are plotted for each individual. As individuals foraged in more urban areas, where housing density is greater, their use of primary prey decreased. Overall, males utilized less primary prey than females, across all levels of housing density. 38 �Puma foraging in an urban to rural landscape Kevin Blecha (Colo. State Univ.), Mat Alldredge (CPW), and Randy Boone (Colo. State Univ.) Improvements on GPS location cluster analysis for the prediction of large carnivore feeding activities: Model based sampling, detection probability, and inclusion of activity sensor measures Animal space-use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use of animals. GPS location cluster analysis is one such technique increasingly applied to large carnivores to identify the timing and location of feeding events. Integral to identifying feeding events, is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Despite the high cost of conducting ground-truthing visits, model-based methods for making predictions to non-visited clusters are often overlooked. Published feeding prediction models seemed to have explored a small range of covariates; usually limited to spatio-temporal characteristics of the GPS data. We include activity sensor data as an additional covariate to increase prediction performance using a simple logistic regression GLM. Additionally we include covariates influencing the probability of ground-truthing observers to detect prey remains given a search delay of 260 days. Using a separate double observer study, we assess how much prey may be missed by an observer 2-60 days post cougar presence. We conclude that very few larger prey items are missed in our system and that the false-absences are from missing the prey remains of smaller species. Failing to account for sources of ground-truthing error can bias feeding rate predictions. The methods demonstrated will help future studies improve ground-truthing efficiency and model prediction accuracy while decreasing biases. We urge future studies to use shorter GPS fix intervals when possible along with a design based groundtruth sampling strategy, especially when predation on small prey is of concern. Testing optimal foraging theory, energy maximization, and fear driven human avoidance of a large carnivore’s foraging strategy Understanding predator foraging ecology in regions of increasing anthropogenic development is important when devising management strategies to reducing cougar-human conflicts. A pure energy maximization strategy predicts that patch use of a foraging cougar is driven by the selection of landscape factors that maximize encounters with primary prey species. However, previous research on fine scale patch-use rarely shows linear relationships with direct measures of prey availability. A pure fear-driven strategy predicts that patch use is driven by landscape factors associated with higher risk of mortality. While it is logical that a cougar would avoid areas linked to higher rates of mortality, testing this has been met with only limited success. Optimal foraging theory would attempt to explain patch usage as a behavioral balancing act between energy maximization and fear-driven human aversion. A novel camera trapping survey technique using 41,000 trap nights was used to model fine scale background encounter rates across the landscape of various prey species of cougars, with particular emphasis on a range of housing densities. Predicted feeding site locations were derived for 49 cougars by a model using a training set of 4,400 clusters of ground-truthed GPS locations. Using a step-selection function analysis, characteristics (human housing, prey availability, and natural habitat) of hunting and feeding locations were compared to matched available locations. Then, landscape characteristics of feeding sites were compared to characteristics of GPS locations within the prior travelling sequence to test which factors led to a successful kill. Preliminary results indicate direct and indirect relationships in reference to humans and background encounter rates of primary prey (deer). Interestingly, successful hunting locations were more likely to occur with an increase in human housing intensity. However, some difficulties arise when teasing out the influence of alternative prey species (i.e., raccoon, domestic cat), whose background encounter rates may have increased the likelihood of this relationship. 39 �Figure 1. Proportion of cougar feeding sites composed of small (raccoon, house cat) and large-sized prey (adult wild ungulates) in the Colorado Front Range categorized by the housing density level the feeding site was located in. – not referenced in the above abstracts. 40 �Predator-Prey dynamics in relation to chronic wasting disease and scavenging interactions at cougar kill sites Joe Halseth, Matt Strauser, and Mat Alldredge (CPW) The current Colorado Parks and Wildlife (CPW) cougar (Puma concolor) research on the Frontrange is utilizing GPS radio collar technology allowing researchers to track cougar movements on a real time basis. With up to seven uploads a day, the roughly 20 current active project collars give researchers the ability to identify possible kill sites quickly, sometimes as soon as 6 to 12 hours after a kill is made. This provides the opportunity to explore previously un-researched facets of cougar behavior during the relatively short time interval from the point a cougar makes a kill, to the point at which it abandons the carcass. Feeding behavior, intraspecific kill site interaction, and scavenger competition can now be investigated. Similar data to that collected in Krumm et al.’s (2005) and Miller et al.’s (2008) cougar studies, which examined cougar selection of Chronic Wasting Disease (CWD) positive mule deer (Odocoileus hemionus), can now be collected with a greater degree of efficiency. The study areas of each of the two prior CWD cougar projects lie within the more broad boundaries of the current Front-range cougar project, and a larger number of known cougars will increase sample sizes of CWD tissues from cougarkilled mule deer. Additionally, much of the field work from the two previous studies is nearly a decade old which justifies another project to compare to past results. The ability to collect a potentially larger sample size will yield more accurate findings, identify gaps in need of further study, and/or detect developing trends in regards to possible temporal patterns. The ongoing cougar project’s available technology and resources, and the relatively minor additional project costs, provide the opportunity to initiate a camera study to explore cougar feeding behavior and scavenger interaction in the period immediately following a cougar kill. Site visitation of fresh cougar kills also allows for the collection of adequate tissue samples to test for CWD, in order to further explore if cougars are selecting for CWD positive mule deer or other ungulates. Objectives: 1. Document sharing and/or abandonment rates of cougars occupying kill sites in response to presence of other cougars and/or scavengers 2. Document time from kill until presence of competing scavengers 3. Document feeding patterns and length of individual feeding sessions. 4. Compare CWD infection rates from cougar-killed deer and elk to existing CPW CWD infection rates to determine if cougars are selecting for CWD positive deer and elk. Scavenging and Kill Site Interactions Placing cameras at kill sites was completed in January 2014 wrapping up 25 months of data collection. Over the course of the study we placed cameras on 225 kill sites recording over 400,000 photos. Pictures have been identified once and are currently in the process of a second round of identification. Timely approaches to kill sites continued to be successful in 2013 and early 2014, usually occurring within 24 hours of a cougars first GPS location at a kill site. This allowed technicians to evaluate the prey item to ensure the estimated time of death matched the carcass condition in order to rule out other possible causes of death (road kill, hunting loss, etc). Cougars were often present at the kill site upon approach but usually retreated as the researcher neared the site. There were several situations where a cougar had been unwilling to move from a kill. In these situations technicians left the area, and if time allowed, returned at a later time. We documented 6 instances throughout the study where carcasses were abandoned following camera placement. Four of these abandonments were due to the cougar occupying a second kill site and never returning to the first, and not likely a result of human visitation and camera placement on the first 41 �carcass. Cameras continued to document bear visitation in both scavenging and direct competition situations and photo sequences continue to be analyzed to determine frequency of these scenarios. Red fox (Vulpes vulpes) were commonly observed scavenging at cougar kill sites. Other scavengers documented include striped skunk (Mephitis mephitis), spotted skunk (Spilogale gracilis), raccoon (Procyon lotor), ringtail cat (Bassariscus astutus), grey fox (Urocyon cinereoargenteus), coyote (Canis latrans), domestic dog (Canis lupus familiaris), bobcat (Lynx rufus), golden eagle (Aquila chrysaetos), red-tailed hawk (Buteo jamaicensis), great-horned owl (Bubo virginianus) and a variety of Corvidae bird species. Over the course of the study there have been at least 12 camera sites where we have identified multiple cougars simultaneously occupying a kill site. These observations include two ‘sharing’ situations involving two cougar family groups and multiple sharing situations involving an adult male and female. Other interactions include two instances of female cougars stealing food items from another female, three unrelated adult females, and one instance of an adult male feeding on a prey item occupied by a female and three young kittens. There have also been several instances where non-focal cougars scavenge on the remains of prey items already consumed and abandoned by the focal cougar. CWD sample collections from cougar-killed ungulates were completed in April 2014 wrapping up 30 months of data collection. In 2013 and 2014, there were no problems with obtaining tissue samples to test for CWD except in rare situations where tissues have been consumed by the cougar. Samples collected in the field were issued a head tag and transferred to the CPW Wildlife Health Lab in Fort Collins for testing. Throughout the course of the study, we collected 192 samples from cougar-killed ungulates of which 190 were testable. Of these, 163 were adult mule deer (65M, 98F), 11 were adult elk and the rest comprised fawn mule deer (n=14), an elk calf (n=1), and an adult white-tailed deer (n=1). Table 1 shows the breakdown of species, age and test results within each deer DAU from adult mule deer sampled within the broad boundary of the front-range cougar project. Tables 2 and 3 show mule deer sampling by sex and figure 1 shows the sampling breakdown by month throughout the entire study. 42 �Table 1. Total CWD results Total Total % DAU GMU Sampled Positive Positive D-10 20 28 4 14.29% D-27 29 78 17 21.79% D-27 38 45 13 28.89% D-17 39 2 0 0.00% D-17 391 10 3 30.00% Total 163 37 22.70% Table 2. Male mule deer CWD results DAU D-10 D-27 D-27 D-17 GMU 20 29 38 39 D-17 391 Total Males Males % Sampled Positive Positive 8 1 12.50% 32 10 31.25% 18 8 44.44% 2 0 0.00% 5 1 20.00% 65 20 30.77% Table 3. Female mule deer CWD results DAU D-10 D-27 D-27 D-17 D-17 GMU 20 29 38 39 391 Total Females Females % Sampled Positive Positive 20 3 15.00% 46 7 15.22% 27 5 18.52% 0 0 0.00% 5 2 40.00% 98 17 17.35% 43 �Nov-11 Dec Jan-12 Feb Mar Apr May June July Aug Sept Oct Nov Dec Jan-13 Feb Mar Apr May June July Aug Sept Oct Nov Dec Jan-14 Feb Mar Apr 16 14 12 10 8 CWD Negative 6 CWD Positive 4 2 0 Figure 1. Mule deer CWD results by month. 44 �The use of lures, hair snares, and snow tracking as non-invasive sampling techniques to detect and identify cougars Kirstie Yeager, (Colo. State Univ.) Mat Alldredge (CPW), and Bill Kendall (Colo. State Univ.) Development of a non-invasive method to sample cougars(Puma concolor) A noninvasive method that will sample all individuals in a population over multiple occasions is a useful tool in assessing population demographics with little disturbance to the target animals. However, finding such a method for large carnivores, such as cougars, is a challenging task due to their elusive nature and large home-range sizes. Current methods to sample cougars usually involve a capture component, but obtaining reliable estimates can be difficult and cost prohibitive when using capture as the sole sampling method. Because cougars leave sign, and exhibit behaviors like territoriality and curiosity, a noninvasive-genetic-sampling (NGS) method can be a plausible alternative. Hair contains DNA which can be genetically analyzed to yield the individual identification necessary for population assessments and can be obtained without handling the animal. We tested NGS techniques to obtain genetic samples from cougars. We evaluated attractants and hair-snaring techniques at lure sites in Boulder and Jefferson Counties on the Front Range, Colorado during February – April, 2012 and November – April, 2013. We tested auditory predator calls and scent lures in conjunction with hair-snaring techniques. We established 16–20 sites over four ≈ 30-day sampling periods. At 18 (out of 33) sites with auditory calls, we observed 40 site visits by ≥ 13 individual cougars (Table 1). In addition, we obtained 14 hair samples. We conclude that auditory calls and hair snares are an effective way to assess the various population demographics that are needed to inform management decisions. Table 1. Sixty-eight sites were established on the Front Range, Colorado, over two winter field seasons to sample cougars. Attractants were placed at each site. Four different types of sites, varying by the attractant present, were established (16 – 18 of each type). The average time a site was active ranged from 29.0 – 33.3 days. The total sampling effort for each site type was 464 – 600 days. Motion-censor cameras placed at each site documented cougar detections. Some cougars were uniquely marked with ear tags indicating the number of individual marked cougars detected (n = 13). Some were detected at multiple site types. In addition, we estimated the proportion of sites (±SE) where > 1 cougar was detected. Attractant(s) Bait only Bait & scent Bait & call Bait, scent, & call No. of sites 17 18 16 17 Avg. days active 31.6 33.3 29.0 32.2 Total days active 538 600 464 547 Total no. of detections 5 12† 15 25 † Seven detections were at the same site and probably by two individuals. ‡ Several individual cougars were detected at multiple site types. 45 No. of different marked cougars detected ‡ 2 3 7 9 Proportion of sites w/detections 0.24 ± 0.11 0.28 ± 0.11 0.50 ± 0.13 0.59 ± 0.12 �Assessing the probability of individually identifying cougars using auditory predator calls and hair snares Detecting all individuals in a population equally and with certainty will yield unbiased population estimates; however, many current sampling techniques have inherent variation, such as a trap response or individual heterogeneity. From November – April, 2013, we applied a noninvasive method to sample cougars and assessed variation in detection in two study areas in Colorado; one on the Front Range (FR; 1,270 km²) in Boulder, Jefferson, and Gilpin Counties and one on the Uncompahgre Plateau (UP; 540 km²) in Montrose and Ouray Counties. In total, we established 148 lure sites with auditory predator calls and hair snares over three (UP) and four (FR) sampling periods. Each site was active an average of 28.5 days (4,214 sampling nights). On the FR, we observed 98 detections by 13 independent marked cougars, two sibling groups, and ≥ 16 unmarked animals (Table 1). On the UP, we documented 18 detections by seven independent marked cougars and no unmarked animals. Collectively, 14 of the 20 detected cougars were observed multiple times. We used the GPS location data of 27 previously radiocollared cougars to determine availability and estimated detection probabilities. The probability of detecting an independent marked cougar at least once during the study adjusted for partial availability was 0.83 ± 0.10 (FR) and 1.00 (UP). We collected 59 hair samples. Thirty-two were genotyped at ≥ 8 loci identifying 26 unique cougars. Given our results, we concluded that a noninvasive-sampling technique using auditory calls and hair snares can be a useful tool in assessing population demographics of cougar populations. 46 �Table 1. From November to April, 2013, 21 – 25 lure sites for each of four sampling periods were placed across the Front Range, Colorado, to sample cougars. We observed 98 detections. We estimated the probability of detecting a marked cougar (via photograph) given that it was in the study area at least one night during the sampling period (± 1 SE). In addition, we estimated the probability that a cougar entered the site given that it was observed and the probability of obtaining a hair sample given that the cougar entered the site. Period 1 Period 2 Period 3 Period 4 No. of detections 27 30 25 16 Detected/ available 0.38 ± 0.15 0.39 ± 0.13 0.35 ± 0.13 0.35 ± 0.13 Entered/ detected 0.74 ± 0.09 0.77 ± 0.08 0.80 ± 0.08 0.69 ± 0.12 47 No. of samples 8 19 16 9 Samples/ entered 0.40 ± 0.10 0.83 ± 0.07 0.80 ± 0.08 0.82 ± 0.10 �48 �Colorado Parks and Wildlife WILDLIFE RESEARCH REPORT SUMMARY Research library, annual report Period Covered: July 1, 2013– June 30, 2014 Author: Kay Horton Knudsen, kay.knudsen@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. The Colorado Parks and Wildlife Research Center Library has existed for several decades in the Ft. Collins office. Early librarians can be credited with the physical organization of the Library including seven decades of Federal Aid reports, over 50 years of Wildlife Commission reports and a unique book and journal collection. The goal of the Library is to provide an effective program of library services for Colorado Parks and Wildlife employees, cooperators and wildlife educators. The Library also serves as a historic archive for CPW publications. The mission of outreach and support is fulfilled using technology to provide a library website with the online catalog, wildlife databases and digitized documents available to CPW staff statewide. As of June 30, 2014, the Research Library held 18,948 titles and 31,559 items (these are the multiple copies of a title) and had 169 registered patrons (CPW staff). As part of the project to digitize CPW documents, the equivalent of 6GB of data has been scanned and uploaded to the catalog vendor. Current wildlife databases include BioOne, four of EBSCO’s specialty databases (Environment Complete, Fish and Fisheries Worldwide, Wildlife and Ecology Studies Worldwide and CAB Abstracts), Birds of North America, ProQuest Dissertations and Theses and the JSTOR Life Sciences collection. Print subscriptions to the major wildlife journals were cancelled several years ago, however online access to the journals was retained and continues as a primary usage point for staff. CPW staff statewide are authenticated through WildPoint (intranet) eliminating the need for individual usernames and passwords. A major project has been the digitization of CPW publications. In the last 3 years, Terrestrial Federal Aid reports (1948 to present) along with the report collections Outdoor Fact, Special Reports, Technical Publications and Division Reports have all been scanned. The resulting PDFs are attached to bibliographic records for each title within the series and are available via the Library catalog for download. At CPW staff request, digital scans of Big Game Hunting brochures from 1950-1995 were made at a local commercial vendor in the spring of 2014. These and other hunting brochures will eventually be made available to staff and the public. With expanded library services, the number of requests for documents or research assistance has grown. The Library website provides more full-text resources than ever before, however there are also more abstract-only indexes. The Library is not open on a walk-in basis to the general public but the librarian does assist the Denver Help Desk and area staff with questions they receive from citizens. The chart below shows the number of reference questions and document requests handled by the librarian each month during the past 6 years (Table 1); the highest number of monthly requests occurred October 2013. Please note that one request from a CPW staff member may be for multiple journal or book titles. 49 �Table 1. Monthly CPW Research Library reference requests August 2008–June 2014. 2008-09 July 2009-10 2010-11 2011-12 2012-13 2013-14 20 45 28 37 60 Aug 15 25 34 52 44 45 Sept 21 30 37 53 48 46 Oct 33 38 41 42 39 74 Nov 14 28 46 52 51 48 Dec 28 32 34 52 49 46 Jan 33 62 48 64 46 53 Feb 30 43 43 43 54 62 Mar 35 36 46 36 53 48 Apr 24 23 30 42 70 57 May 13 17 51 53 65 39 June 20 26 27 36 35 34 TOTAL 266 380 482 553 591 612 50 � https://cpw.cvlcollections.org/files/original/ba3ef896ed509380cf3aef5eca021299.pdf 8b7041be72c47e74abde1744f4953b6a PDF Text Text MAMMALS - JULY 2015 �ii �WILDLIFE RESEARCH REPORTS JULY 2014 – JUNE 2015 MAMMALS RESEARCH PROGRAM COLORADO PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). iii �Executive Summary This Wildlife Research Report represents summaries (<5 pages each or including short subsections) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) from July 2014 through June 2015. These research efforts represent long term projects (4 – 10 years) in various stages of completion addressing applied questions to benefit the management of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx or from the project principal investigators listed at the beginning of each summary. Current mammal research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to various habitat alterations, humanwildlife interations, and investigating improving approaches to wildlife management. The Mammal Conservation Section addresses mammal and breeding bird responses to the recent bark beetle outbreak influencing about 3.7 million acres of spruce and pine forests in Colorado and preliminary results of lynx monitoring in the San Juan Mountain Range of southwest Colorado. The Ungulate Conservation section includes 3 projects addressing mitigation approaches to benefit mule deer exposed to energy development activities, an assessment of potential factors influencing mule deer recruitment the past 40 years, and an evaluation of moose demographic parameters that will inform future management of this recently established ungulate species in Colorado. The Predatory Mammal Conservation section addresses improved understanding and management approaches to address black bear and mountain lion-human interactions, evaluation of sport harvest for mountain lion management, and assessment of non-invasive sampling methods to estimate abundance, diet composition, and age class distribution of carnivore populations. The Support Services section describes the CPW library services to provide internal access of CPW publications and online support for wildlife and fisheries related publications. We have benefited from the numerous collaborations that support these projects and the opportunity to work with and train wildlife technicians and gradute students that will enhance wildlife management and ecology in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, Idaho State University, University of Wisconsin-Madison, the Buerau of Land Management, City of Boulder, Boulder and Jeffereson County open space, City of Durango, Big Horn Sheep and Moose Auction/Raffle Grants, Species Conservation Trust Fund, GOCO YIP Internship program, Safari Club International, Boone and Crocket Club, Colorado Mule Deer Association, The Mule Deer Foundation, Wildlife Conservation Society, SummerLee Foundation, EnCana Corp., ExxonMobil/XTO Energy, Marathon Oil, Shell Exploration and Production, WPX Energy, and private land owners who have provided access for research projects. iv �STATE OF COLORADO John Hickenlooper, Governor DEPARTMENT OF NATURAL RESOURCES Mike King, Executive Director PARKS AND WILDLIFE COMMISSION Robert Bray, Chair…………………………………………………………………………………..Redvale Chris Castilian, Vice Chair.………………………………….………….….……………….............Denver Jeanne Horne, Secretary…………………..………………………………………….….…………..Meeker John Howard………………………………………………………………………………….……..Boulder William Kane, ………….……………………………………………………………………………..Basalt Dale Pizel……………………………………………………………………………………………..Creede James Pribyl…………………………………………………………………………………………Boulder James Vigil………………………………………………………………………………………….Trinidad Dean Wingfield………………………………………………………………………..……………..Vernon Michelle Zimmerman………………………………………………………………………….Breckenridge Alexander Zipp……………………………………………………………………………………….Pueblo Mike King, Executive Director, Ex-officio………….…………………...………………….……......Parker Don Brown, Dept. of Agriculture, Ex-officio….………………………………..…………….Yuma County DIRECTOR’S LEADERSHIP TEAM Bob Broscheid, Director Margaret Taylor, Steve Cassin, Chad Bishop, Heather Dugan, Gary Thorson, Jeff Ver Steeg, Pat Dorsey, Dan Prenzlow, Ron Velarde, Steve Yamashita, MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Wildlife Researcher Eric Bergman, Wildlife Researcher Jake Ivan, Wildlife Researcher Heather Johnson, Wildlife Researcher Ken Logan, Wildlife Researcher Kay Knudsen, Librarian Margie Michaels, Program Assistant v �vi �Colorado Division of Parks and Wildlife July 2014 − June 2015 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH SUMMARIES MAMMAL CONSERVATION MAMMAL AND BREEDING BIRD RESPONSE TO BARK BEETLE OUTBREAKS IN COLORADO by J. Ivan & A. Seglund………………...…………………….1 CANADA LYNX MONITORING IN COLORADO by J. Ivan, E. Odell, & S. Wait…………..6 UNGULATE CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson……………………………………………………………....11 QUALIFYING LOSS AND DEGRADATION OF MULE DEER HABITAT ACROSS WESTERN COLORADO by H. Johnson, S. Reed, J. Sushinsky, A. Holland, T. Balzer, & J. Garner……………………………………………………………...16 EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO by E. Bergman….…….……………………….. 21 PREDATORY MAMMAL CONSERVATION BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS by H. Johnson………………………………………………………………………. 25 MOUNTAIN LION POPULATION RESPONSES TO SPORT-HUNTING ON THE UNCOMPAHGRE PLATEAU, COLORADO by K. Logan……………………………...30 COUGAR AND BLACK BEAR DEMOGRAPHICS AND COUGAR-HUMAN INTERACTIONS IN COLORADO by M. Alldredge………………………………................33 SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT by K. Knudsen……..………………………….44 vii �MAMMAL CONSERVATION MAMMAL AND BREEDING BIRD RESPONSE TO BARK BEETLE OUTBREAKS IN COLORADO CANADA LYNX MONITORING IN COLORADO viii �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mammal and breeding bird response to bark beetle outbreaks in Colorado Period Covered: July 1, 2014 − June 30, 2015 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Amy Seglund, Amy.Seglund@state.co.us ; All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) infestations have reached epidemic levels in Colorado, impacting approximately 4 million acres since the initial outbreak in 1996 (Figure 1). Though bark beetles are native to Colorado and periodic infestations are considered a natural ecological process, the geographic scale of their impact and simultaneous infestation within multiple forest systems has never been observed. This historic outbreak is having significant impacts on composition and structure of forest stands that will propagate for decades into the future. The widespread mortality of forested systems in Colorado may have a dramatic, but poorly understood effect on wildlife species that depend on these habitats. The project described here uses occupancy estimation to determine which wildlife species (both species of conservation concern and game species) decrease their use of an area as bark beetles pass through, which increase their use, and which exhibit use similar to levels prior to infestation. Statewide sampling was conducted during the summers of 2013 and 2014 (Figure 2). We sampled 150 Engelmann spruce (Picea engelmanni)-subalpine fir (Abies lasiocarpa) sites and 150 sites consisting mostly of lodgepole pine (Pinus contorta) or lodgepole pine mixed with other conifers. For both strata, sampling covered conditions ranging from sites that have yet to be impacted by bark beetles to those that were impacted by beetles more than a decade ago. At each 1-km2 site, we sampled the breeding bird community using the Rocky Mountain Bird Observatory’s protocol for “Integrated Monitoring in Bird Conservation Regions” (Hanni et al. 2014). We sampled the mammal community by deploying a remote camera near the center of each sample unit. Avian data have not yet been analyzed. We collected 388,951 photos of 56 species (26 mammalian species). For the purposes of this interim document, we report preliminary results for 3 mammalian species of conservation concern: snowshoe hares (Lepus americanus) and red squirrels (Tamiasciurus hudsonicus), which together comprise nearly 100% of the diet of the federally listed Canada lynx, and American marten (Martes americana), which is a USFS Region 2 sensitive species. Using Program MARK (White and Burnham 1999), we fit standard occupancy models (MacKenzie et al. 2006) to data for each species in the following manner. First, we fit a base model with parameters for the spruce-fir or lodgepole stratum, percentage of aspen present at the site, canopy cover, shrub cover, amount of down wood, amount of bare ground, and three physiographic variables that collectively account for elevation, moisture accumulation, and solar radiation at each site. The purpose of this model was to account for basic occupancy patterns of each species in the state irrespective of bark beetles. Next, we fit additional parameters to the base model which allowed occupancy to change in a variety of patterns (e.g., linearly, quadratic, spline, change-point, etc.) in relation to time elapsed since a stand was initially impacted by beetles. We also explored whether there was any interaction between response to beetles and stratum and/or response to beetles and the severity of the impact (percent of trees that were killed). We used Akaike’s Information Criterion (Burnham and Anderson 2002) to assess fit of these various beetle response models, and model-averaged occupancy across the model set to provide a best estimate of response of each species to beetles. 1 �Results indicate that snowshoe hares are more likely to use spruce-fir stands than lodgepole stands (Figure 3). There may be a slight increase in use around the time needles drop, followed by a steady fall back to ‘green’ forest levels, but in general hare use remained relatively constant for the initial decade after bark beetle infestation. Red squirrel use was similar between the two stand types (Figure 4). However, best fitting models included an interaction between severity of the beetle outbreak and response of red squirrels. In areas of low severity, response was minimal (Figure 4a). However, in areas of high severity, red squirrel use was 25−35% lower (Figure 4b). Use of the two stand types by marten was similar and relatively invariant to beetle impact (Figure 5). Literature Cited Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Figure 1. Current (2014) extent of mountain pine beetle (red) and spruce beetle (purple) infestations in spruce/fir (blue-green) and lodgepole pine (bright green) forests in Colorado. Bark beetle data were collected via USFS aerial surveys. 2 �Figure 2. Sites sampled via point counts and remotes cameras to assess impacts of bark beetle infestations on breeding bird and mammal species in spruce/fir (blue-green, N = 150) and lodgepole pine (bright green, N = 150) stands in Colorado, 2013−2014. Figure 3. Snowshoe hare occupancy (i.e., use) of stands in relation to stage of infestation by bark beetles. ‘Green’ forests are those that have not yet been impacted. ‘Red’ forests are recently impacted; dead needles remain on trees. ‘Silver’ forests were impacted more distantly in the past and needles have fallen. Numbers in parentheses approximately correspond to the number of years that have passed since trees initially turned red. 3 �a) b) Figure 4. Red squirrel occupancy (i.e., use) of stands in relation to the number of years since initial infestation by bark beetles. Use of spruce-fir and lodgepole stands is generally similar and remains stable for stands that are lightly impacted by beetles (a; 25% dead). However, red squirrel occupancy is reduced by 25-35% in stands that are heavily impacted (b; 75% dead). 4 �Figure 5. American marten occupancy (i.e., use) of stands in relation to stage of infestation by bark beetles. Use does not vary appreciably by stand type, and remains stable through time as bark beetles pass over an area. 5 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Canada Lynx Monitoring in Colorado Period Covered: July 1, 2014 − June 30, 2015 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Eric Odell, Eric.Odell@state.co.us; Scott Wait, Scott.Wait@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that the population of Canada lynx in the state was apparently viable and self-sustaining. In order to track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is required. During 2014-2015 we implemented a portion of the statewide monitoring scheme described in Ivan (2013). Specifically, we sampled 50 75-km2 units selected at random from a population of 179 units that collectively encompassed potential lynx habitat in the San Juan Mountain Range of southwest Colorado (Fig. 1). Of the 50 sample units, 19 were sampled via snow tracking surveys conducted between January 1 and March 31. On each of 3 independent occasions, survey crews searched roadways (paved roads and logging roads) and trails for lynx tracks. Crews searched the maximum linear distance of roads possible within each survey unit given safety and logistical constraints. Each survey covered a minimum of 10 linear kilometers distributed across at least 2 quadrants of the unit. The remaining 31 units could not be surveyed via snow tracking because they occurred in wilderness or were otherwise inaccessible. Survey crews deployed 4 passive infrared motion cameras in each of these units during fall 2014. Cameras were baited with visual attractants and scent lure to enhance detection of lynx living in the area. Cameras were retrieved during summer 2015 and all photos were archived and viewed by at least 2 observers to determine species present in each. Camera data were then binned such that each of 5 30-day periods from December 1 through April 30 was considered an ‘occasion,’ and any photo of a lynx obtained during a 30-day period was considered a detection during that occasion. Crews covered a total of 884 km during snow tracking surveys − 697 km by snow machine, 140 km by vehicle, and 47 km by snowshoe. Mean distance surveyed per occasion was 20 km. Lynx were detected at seven snow tracking units (Figure 1). Scat or hair samples were collected from seven of the 12 lynx tracks discovered (tracks were discovered at some units on >1 occasion) and are pending genetic analysis to confirm that tracks were from lynx. Camera sets yielded 134,695 photos of which 302 were lynx. Lynx were detected at 27 cameras in seven camera units (Figure 1). Of note, resident lynx were documented for the first time in the LaGarita Mountains north of Creede. Similarly, resident lynx were documented about 15 km from the New Mexico border in the South San Juans, an area rarely used by resident animals in the past. In both cases, lynx were detected at camera sets. Also, adult females with kittens were detected at cameras in units near Silverton and Platoro Reservoir, thus documenting that at least some reproduction occurred in the study area. Using Program MARK (White and Burnham 1999), we standard occupancy models (MacKenzie et al. 2006) to our survey data to estimate the probability of a unit being occupied (or used) by lynx over 6 �the course of the winter. ‘Survey method’ was treated as a group so that we could, based on previous work, 1) allow detection probability to vary by survey method and 2) include a breeding season effect for detection at cameras (lynx tend to move more in late winter when they begin to breed, and thus should encounter cameras more often). We also considered a suite of covariates that could potentially explain variation in occupancy including proportion of the unit that was covered by spruce/fir forest, proportion covered by modeled lynx habitat (Ivan et al. 2011), average years since bark beetle infestation, variability (standard deviation) in years since bark beetle infestation, proportion of the unit that was burned during Summer 2013, occupancy status of neighboring units, and the number of photos of other species that could potentially impact presence of lynx (e.g., snowshoe hares as a food source, coyotes as potential competitors). For the purposes of model-fitting, we included data from both the pilot study (2010-2011) and first year of implementation (2014-2015) to maximize the information estimates were based on. ‘Year’ was treated as a group variable in this case to obtain a separate occupancy estimate for each effort. We limited our model set by considering only combinations of two of these covariates on ψ (occupancy probability), in addition to the two covariates on detection. The best-fitting model characterized occupancy as a function of 2 covariates: the proportion of the sample unit covered by spruce-fir forest and the number of photos of hares recorded at camera stations (Table 1). In both cases, the association was positive, indicating that the probability of lynx use increased with more spruce-fir and more hares. Other covariates appear in top models with spruce-fir, but addition of these covariates did not improve AICc scores beyond the model with spruce-fir only (Table 1). This phenomenon indicates that these other variables were not as informative. Of these less informative variables, lynx occupancy was negatively associated with bobcat use and proportion of the unit burned but positively associated with the proportion of mapped lynx habitat in the unit; there was no discernible association with any other species and no relationship between lynx occupancy and impact by bark beetles. Detection probability was relatively high for snow tracking surveys (p = 0.56, 95% confidence interval: 0.41−0.69), and low for monthly camera surveys (p = 0.24, 95% confidence interval: 0.12−0.41) during December−February, although detection increased to 0.41 (95% confidence interval: 0.21−0.65 during breeding season (March and April) as expected. For winter 2014-2015 we estimated that 29% of the sample units in the San Juans were occupied by lynx (95% confidence interval: 0.15 − 0.48). Occupancy estimates from the 2014-2015 monitoring effort were similar to those obtained during pilot research work in 2010-2011 but the sampling frames were different between the 2 years so results are not directly comparable (Figure 2). Literature Cited Ivan, J. S. 2013. Statewide Monitoring of Canada lynx in Colorado: Evaluation of Options. Pages 15-27 in Wildlife Research Report - Mammals. Colorado Parks and Wildlife., Fort Collins, CO, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx Ivan, J. S., M. Rice, P. M. Lukacs, T. M. Shenk, D. M. Theobald, and E. Odell. 2011. Predicted lynx habitat in Colorado. Pages 21-35 in Wildlife Research Report - Mammals. Colorado Parks and Wildlife, Fort Collins, CO, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. 7 �Figure 1. Lynx monitoring results for 2014-2015, San Juan Mountains, southwest Colorado. Colored units (n = 50) indicate those selected at random from the population of units (n = 179) encompassing lynx habitat in the San Juan Mountains. Blue units were surveyed via snow tracking; orange units were surveyed via deployment of four cameras per unit during winter months. Lynx were detected in 14 of the sampled units. 8 �1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 2009 2010 2011 2012 2013 2014 2015 Figure 2. Model-averaged occupancy estimates for lynx in the San Juan Mountains, southwest Colorado. ‘Year’ indicates when the efforts were initiated (2010-11, 2014-15). Table 1. Model selection results for lynx monitoring data collected in the San Juan Mountains, Colorado, 2014-2015. Rankings are based on Akaike’s Information Criterion adjusted for small sample size (AICc). Fourteen variables were considered as covariates to inform estimation of occupancy (ψ). The complete model set (n = 64) included all combinations of two, in addition to modeling detection (p) as a function of survey method and breeding season. Only the best 10 models are shown. Model AICc ΔAICc AICc Wts No. Par. ψ(Year + SpruceFir +Hare)p(Method + Breeding) 281.4 0.0 0.35 7 ψ(Year + SpruceFir)p(Method + Breeding) 283.8 2.4 0.10 6 ψ(Year + SpruceFir + Bobcat)p(Method + Breeding) 284.2 2.8 0.09 7 ψ(Year + SpruceFir + Coyote)p(Method + Breeding) 284.6 3.2 0.07 7 ψ(Year + PropLynxHabitat + Hare)p(Method + Breeding) 285.5 4.1 0.04 7 ψ(Year + SpruceFir + PropBurn)p(Method + Breeding) 285.6 4.2 0.04 7 ψ(Year + SpruceFir + Fox)p(Method + Breeding) 285.6 4.2 0.04 7 ψ(Year + SpruceFir + Cougar)p(Method + Breeding) 285.7 4.3 0.04 7 ψ(Year + SpruceFir + AvgBeetleKill)p(Method + Breeding) 286.0 4.6 0.03 7 ψ(Year + SpruceFir + SDBeetleKill)p(Method + Breeding) 286.1 4.7 0.03 7 9 �UNGULATE CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION QUALIFYING LOSS AND DEGRADATION OF MULE DEER HABITAT ACROSS WESTERN COLORADO EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO 10 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation Period Covered: July 1, 2014 − June 30, 2015 Principal Investigator: Charles R. Anderson, Jr., Chuck.Anderson@state.co.us Collaborators: Colorado Parks and Wildlife, BLM-White River Field Office, Idaho State University, Colorado State University, Federal Aid in Wildlife Restoration, EnCana Corp., ExxonMobil Prod. Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, WPX Energy, Colorado Mule Deer Assn., Colorado Mule Deer Found., Colorado State Severance Tax Fund, Boone & Crocket Club, and Safari Club Int. All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent the first 5 pretreatment years and 3 years post treatment of a long-term study addressing habitat improvements and evaluation of energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. We monitored 4 winter range study areas representing varying levels of development to serve as treatment (North Magnolia, South Magnolia) and control (North Ridge, Ryan Gulch) sites (Fig. 1) and recorded habitat use and movement patterns using GPS collars (≥5 location attempts/day), estimated neonatal and overwinter fawn and annual adult female survival, estimated early and late winter body condition of adult females using ultrasonography, and estimated abundance using helicopter mark-resight surveys. During this research segment, we targeted 240 fawns (60/study area) and 120 does (30/study area) in early December 2014 for VHF and GPS radiocollar attachment, respectively, and attempted recapture of 120 does in March 2015 (all captures = 26-32/study area) for late winter body condition assessment. Winter range habitat improvements completed spring 2013 resulted in 604 acres of mechanically treated pinion-juniper/mountain shrub habitats in each of the 2 treatment areas (Fig. 2) with minor and extensive energy development, respectively. Post-treatment monitoring will continue for 3 years to provide sufficient time to measure how vegetation and deer respond to these changes. Based on data collected during the 5-year pretreatment phase and 3 years post-treatment: (1) annual adult survival was consistent among areas averaging 79-87% annually, but overwinter fawn survival was variable, ranging from 48% to 95% within study areas, with annual and study area differences primarily related to annual weather conditions; (2) migratory mule deer selected for areas with increased cover and increased their rate of travel through developed areas, and avoided negative influences through behavioral shifts in timing and rate of migration, but did not avoid development structures (Fig. 3); (3) mule deer body condition early and late winter was consistent within areas, with higher variability among study areas early winter, which was likely related to seasonal moisture within areas and relative forage capacity among areas; (4) mule deer exhibited behavioral plasticity in relation to 11 �energy development, where disturbance distance varied relative to diurnal extent and intensity of development activity (Fig. 4), which may provide for several options in future development planning; (5) mule deer densities appear to be increasing in 3 of 4 areas, with a stable population in North Ridge (Fig. 5); and (6) post treatment vegetation responses have been promising with evidence of improved forage conditions, but longer term monitoring will be required to address the full potential of habitat mitigation efforts. We will continue to collect population and habitat use data across all study sites to evaluate the effectiveness of habitat improvements on winter range. This approach will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation efforts toward less or non-impacted areas. In collaboration with Colorado State University, we are also monitoring neonate survival in relation to energy development from all study areas. This will allow us to include neonatal data to other demographic parameters for improved evaluation of mule deer/energy development interactions. Results from the neonate survival component of the project should be available in next year’s annual report. The study is slated to run through 2018 to allow sufficient time for measuring mule deer population responses to landscape level manipulations. A more detailed version of this project summary and information about recent publications from this effort can be accessed at: http://cpw.state.co.us/Documents/Research/Mammals/Publications/AndersonPiceanceDeer_W185R14_ProgressReport_2014-15.pdf Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, winter 2013/14 (Accessed http://cogcc.state.co.us/ Dec. 31, 2013). 12 �Figure 2. Habitat treatment site delineations in 2 mule deer study areas (604 acres each) of the Piceance Basin, northwest Colorado (Top; cyan polygons completed Jan. 2011 using hydro-axe; yellow polygons completed Jan. 2012 using hydro-axe, roller-chop, and chaining; and remaining polygons completed April 2013 using hydro-axe). January 2011 hydro-axe treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 13 �Figure 3. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012; http://dx.doi.org/10.1890/ES12-00165.1). 14 �Figure 4. Posterior distributions of population-level coefficients related to natural gas development for RSF models during the day (top) and night (bottom) for 53 adult female mule deer in the Piceance Basin, Northwest Colorado. Dashed line indicates 0 selection or avoidance (below the line) of the habitat features. ‘Drill’ and ‘Prod’ represent drilling and producing well pads, respectively. The numbers following ‘Drill’ or ‘Prod’ represent the distance from respective well pads evaluated (e.g., ‘Drill 600’ is the number of well pads with active drilling between 400–600 m from the deer location; from Northrup et al. 2015; http://onlinelibrary.wiley.com/doi/10.1111/gcb.13037/abstract). Road disturbance was relatively minor (~60 – 120 m, not illustrated above). Piceance Basin late winter mule deer density 30.00 25.00 North Ridge 20.00 Ryan Gulch North Magnolia South Magnolia 5.00 2009 2010 2011 2013 2012 2014 2015 Year Figure 5. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2015. 15 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Quantifying loss and degradation of mule deer habitat across western Colorado Period Covered: July 1, 2014 − June 30, 2015 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: Sarah E. Reed, Jessica R. Sushinsky, Andy Holland, Trevor Balzer, Jim Garner, Eric Bergman All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Background In recent decades, mule deer populations have declined across the western U.S., causing wildlife management agencies to seek factors limiting deer performance and strategies to increase their population sizes. The trend of declining mule deer populations has been primarily attributed to loss and degradation of deer habitat, through mechanisms such as urban/exurban development, resource extraction, roads and vehicular traffic, and changing patterns in weather and plant productivity. Other factors have also been implicated in contributing to deer declines, such as predation, interspecific competition with elk, and disease, but these factors have not been associated with much empirical support. While wildlife managers are well aware that different habitat factors can negatively affect deer populations, there is no information on their relative or cumulative impacts. In a report to the Colorado state legislature in 2001 titled, “Declining mule deer populations in Colorado: reasons and responses” Gill (2001) concluded that habitat factors had likely taken the greatest toll on deer populations but that there was no information quantifying the extent of habitat loss or deterioration across the state; critical information that is still lacking today. To address this issue, we conducted the first spatial and temporal analysis of landscape changes that have occurred to mule deer habitat across western Colorado (west of Interstate 25). Specifically, our objectives were to 1) quantify the annual changes that had occurred across the DAU and within winter and summer ranges relative to residential development, energy development, wildfire, plant productivity and weather conditions, and 2) test for associations between those changes in habitat conditions and deer recruitment. During FY2013-2014 we quantified changes that had occurred within mule deer ranges for each habitat factor (see Johnson et al. 2014), and in FY2014-15 we tested for associations between those factors and patterns in deer recruitment. In this summary we report findings with respect to residential development, energy development and climate conditions using data collected between 1980 and 2010. These habitat factors had consistent data available across this time period, years when major changes in both landscape conditions and deer populations occurred. Methods To quantify changes in residential development, energy development and climate conditions across western Colorado we were limited to coarse data types with high temporal and spatial extents. We tracked changes in residential development using the Spatially Explicit Regional Growth Model dataset (Bierwagen et al. 2010), which estimates changes in areas of rural, exurban, suburban and urban housing units over time (100m resolution). We obtained information on energy development from the Colorado Oil and Gas Conservation Commission, and used the date of first activity to monitor increases in the number of wells over the course of the study. Because the exact impact area for each well was unknown, we calculated areas within deer ranges that were within 2700m of oil and gas wells (100m resolution), 16 �based on Sawyer et al. (2006) that demonstrated mule deer avoidance within that distance. To assess climatic patterns that may influence deer recruitment, we used historic data from the Parameter-elevation Regressions on Independent Slopes Model (www.prism.oregonstate.edu). The model depicts precipitation and temperature on a monthly basis (800m resolution), which we used to calculate several metrics hypothesized to affect recruitment: average June minimum temperature, June precipitation, summer precipitation (May-Sep), average summer maximum temperature (Jun-Aug), winter precipitation (DecMar) and average winter minimum temperature (Dec-Mar). For more detailed information about the data types used in the analysis refer to Sushinsky et al. (2014). To examine the influence of development and climate factors on mule deer, we used recruitment as our response variable. We chose this demographic parameter because it exhibits high temporal and spatial variation, is sensitive to environmental conditions, is minimally influenced by harvest regulations, and is typically the most influential vital rate driving population growth. Our measure of fawn recruitment was fawn ratios collected annually by CPW personnel. Fawn ratios were observed with post-hunt helicopter surveys in each deer DAU in most years. Surveys occurred between 1 December and 15 January; survey data collected in January were considered data from the previous calendar year (the biological birth year of the fawns). During surveys, non-random paths were flown across the winter ranges with the purpose of encountering as many deer as possible. All observed deer were counted and classified as adult females, fawns or males based on body size and antler morphology. Annual ratios of the number of fawns/100 adult females (n = 904 ratios) and the number of males/100 adult females (n = 901 ratios) for each DAU were calculated from classification data. In conducting the analyses, we first estimated changes in habitat conditions across each DAU, winter and summer ranges by fitting linear mixed models with “year” as the explanatory variable and treating DAU as a random intercept to account for repeated measurements over time. We then tested univariate relationships between each habitat variable and recruitment rates (while also testing for lag effects), retaining those variables that had 80% confidence intervals non-overlapping zero. From the remaining variables, we then checked for multicollinearity. If two variables were highly correlated (r >|0.6|) we retained the variable with the higher univariate relationship with recruitment rates (based on tvalues). Our final variable set included total development across the DAU, exurban development on winter range, energy development on winter range, winter precipitation, June minimum temperature, June precipitation, summer precipitation, the male/female ratio, an interaction between June temperature and precipitation, and an interaction between energy development and precipitation on winter range. We used linear mixed models (DAU was the random intercept) to test all subsets of these habitat variables in predicting fawn recruitment. We used model selection to identify the top models and model averaging to estimate standardized and unstandardized coefficients. Results Increases in residential housing were significant for all development classes (rural, exurban, suburban and urban), particularly on mule deer winter ranges (Fig. 1). Between 1980 and 2010, across all DAUs, the proportion of winter range that was associated with residential development (all types) increased by an average 0.25%/year (SE=0.01, range = 0 – 0.85%/year), while on summer range it increased by an average of 0.18% (SE=0.01, range = 0.02 – 0.65%/year). Both winter and summer ranges experienced major increases in rural development, and winter ranges also experienced major increases in exurban development. On average, 23.8% of deer winter ranges overlapped with some form of residential development in 1980 and 31.2% overlapped with development in 2010; on average, 14.0% of deer summer ranges overlapped with development in 1980 and 19.5% in 2010. Changes in development were greatest in the Southwest and Southeast regions, driven by increases in the number of rural housing units. By 2010 between 0.7% (DAU 1) and 66.0% (DAU 29) of DAU winter ranges overlapped with residential development, while between 0.8% (DAU 41) and 46.0% (DAU 34) of summer ranges overlapped with development. On both winter and summer ranges, energy development significantly increased over time, although winter ranges experienced the greatest increase. Between 1980 and 2010, on average, the 17 �proportion of winter range associated with a well within 2700 m increased by an average of 0.24%/year (SE=0.01; range = 0.0 – 1.4%/year), while on summer range it increased by 0.18%/year (SE=0.01, range = 0.0 – 1.9%/year). Across all DAUs the average proportion of winter range within 2700 m of a well was 16.7% in 1980 and 23.8% in 2010. The average proportion of summer range within 2700 m of a well was 9.6% in 1980 and 15.6% in 2010. Rates of energy development differed among regions with the Northwest and Southeast experiencing the highest rates of increase. By 2010, the proportion of deer winter ranges within 2700 m of a well varied among DAUs between 0% (DAUs 14, 18, 25, and 53) and 79% (DAUs 11 and 12), while summer range varied between 0% (DAUs 18 and 25) and 68% (DAU 11). Seasonal temperature metrics significantly increased over time, while seasonal precipitation metrics significantly decreased, with the exception of winter precipitation which displayed no temporal trend. Between 1980 and 2010, models estimated that on average, June mean minimum temperatures increased from 3.91°C to 5.23°C, summer mean maximum temperatures increased from 21.98°C to 22.58°C, winter mean minimum temperatures increased from -10.72°C to -9.84°C, June precipitation decreased from 3.42 cm to 3.00 cm, and summer precipitation decreased from 26.29 cm to 21.42 cm. The only metric that showed a significant difference by region was the change in minimum temperatures in June, which were much higher in Southwest Colorado than any other region of the state (Table 1). The mean fawn ratio across all DAUs over the course of the study was 56.0 fawns/100 adult females (SE=13.6), with mean ratios in different DAUs ranging between 42.9 (SE=7.6; DAU 23) and 76.6 (SE=12.7, DAU 27). Across years, the mean ratio in the Southwest was 50.2 (SE=11.3), in the Southeast was 58.5 (SE=16.9), in the Northwest was 60.3 (SE=12.4) and in the Northeast was 64.6 (SE=14.6; Fig. 2A). Across all DAUs, in 1980 the modeled mean ratio was 65.4 (SE = 1.4) and in 2010 it was 50.4 (SE = 1.3). Over the course of the study, recruitment decreased by an average of 0.5 fawns/100 adult females/year, with the greatest rates of decline in Southwest (-0.66) and Northwest (-0.46) Colorado. Rates of change were highly variable among DAUs. Forty DAUs exhibited declining trends over time while 4 DAUs exhibited slightly increasing trends, with the rates of change varying between 8.50 to 0.15 fawns/100 adult females/year (Fig. 2B). In contrast to fawn ratios, the ratio of adult male/adult female mule deer significantly increased over the course of the study. In 1980 the mean was 13.5 adult males/100 adult females (SE = 1.1) and by 2010 the mean was 34.0 adult males/100 adult females (SE = 1.0). This increase was influenced by conservative buck harvest strategies implemented during the late 1990s. On average the number of adult males/100 adult females increased by 0.68 males/100 adult females/year (SE=0.03). There was no significant difference in the rate of change in male ratios among regions. Fawn ratios generally decreased in association with increasing residential development, energy development, June temperatures, winter precipitation, and male ratios. Fawn ratios increased in association with higher June precipitation, summer precipitation and winter precipitation in the previous year (lag effect). The interaction of June temperature and precipitation indicated that cold, dry weather had the greatest positive correlation with fawn recruitment, while warm, dry weather had the greatest negative correlation with recruitment. The interaction of energy development and precipitation on winter range suggested that winter severity had the strongest association with fawn recruitment when development was minimal. When a greater proportion of the winter range was impacted by energy development, the negative association with winter precipitation dampened. Fawn recruitment was predicted to be highest when both winter precipitation and energy development were low. Standardized coefficients of the main effects suggested that residential development had the strongest association with fawn recruitment (>2 times the magnitude of any other main effect), and fawn ratios were predicted to vary by 16 fawns/100 adult females across the observed range of development values. Energy development had the second strongest association with recruitment, followed closely by the climate variables. Conclusions Our results indicate that declining trends in mule deer recruitment are correlated with increasing residential and energy development on deer ranges, particularly within winter ranges. Recruitment is the 18 �primary demographic parameter responsible for ungulate population growth, and thus, factors that reduce deer productivity have long-term consequences for overall population performance. Comparing the relative magnitude of correlations of human development factors with climate factors, which are wellknown to be important drivers of juvenile survival, we found that residential housing had >2 times the magnitude of association of any other factor, and that the association with energy development was similar to key climate variables. We detected significant relationships between deer recruitment and habitat conditions, but it is important to acknowledge drawbacks of our analysis that limit our inference. For example, the correlations we detected between recruitment and habitat conditions do not demonstrate causation, as we could not experimentally manipulate levels of human development or climate metrics. Additionally, the data sources used in this analysis were coarse, limited to those that were available over extensive spatial and temporal scales. While development factors were associated with declining recruitment, the specific mechanisms responsible for these correlations are largely unknown and will require additional investigation. Finally, it is important to remember that this analysis only examined a few factors affecting deer habitat, but numerous factors have been associated with demographic trends in deer (i.e., predation, disease, competition with native and domestic ungulates, etc). Our findings have key implications for the conservation of mule deer across Colorado. Adequate, high quality winter range has been speculated to be the primary factor limiting mule deer in the state, and our findings generally corroborate this hypothesis. Indeed, development impacts on winter ranges were more strongly correlated with declining recruitment than impacts on summer ranges, and increases in both development types were greater on winter ranges. Our results suggest that expanding residential and energy development on mule deer ranges may not be compatible with the goal of maintaining highly productive deer populations, and that additional development may further reduce recruitment rates, and potentially, population sizes. Additionally, historic mule deer population objectives may be unrealistic given the increased development activity associated with declining fawn recruitment. While additional research is needed on the mechanisms driving the correlation between anthropogenic developments and declining deer recruitment, wildlife professionals should carefully consider changes to the human footprint when specifying long-term population objectives. If healthy mule deer populations are going to be maintained across the state, conservation practitioners, policy-makers, and land-use planners will need to collectively work to ensure that seasonal habitats, particularly winter ranges, are well preserved. Literature Cited Bierwagen, B.G., D.M. Theobald, C.R. Pykec, A. Choated, P. Crothd, J.V. Thomase, and P. Morefield. 2010. National housing and impervious surface scenarios for integrated climate impact assessments. Proceedings of the National Academy of Sciences of the United States of America 107:20887-20892. Johnson, H.E., S.E. Reed, J.R. Sushinsky, A. Holland, T. Balzer, J. Garner, and E. Bergman. 2014. Quantifying loss and degradation of mule deer habitat across western Colorado. Wildlife Research Project Summary. Colorado Parks and Wildlife, Fort Collins, Colorado. Sawyer, H., R.M. Nielson, F. Lindzey, and L.L. McDonald. 2006. Winter habitat selection of mule deer before and during development of a natural gas field. Journal of Wildlife Management 70:396- 403. Sushinsky, J.R., H.E. Johnson, A. Holland, T. Balzer, J. Garner, and S.E. Reed. 2014. Quantifying landuse and land-cover change in mule deer habitat across Western Colorado. Technical report to Colorado Parks and Wildlife. Wildlife Conservation Society, North America Program, Bozeman, Montana. 19 �Figure 1. Map of Colorado deer data analysis units (DAUs) and regions (heavy black lines) designated by Colorado Parks and Wildlife. DAU colors represent the average annual rate of increase in residential development between 1980 and 2010. A B 100 90 80 Fawn Ratio 70 60 50 40 30 20 10 0 1980 1990 2000 2010 Year Figure 2. Mean temporal trends between 1980 and 2010 in mule deer recruitment in Colorado by a) region and b) deer data analysis unit. 20 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation and incorporation of life history traits, nutritional status, and browse characteristics in Shira’s moose management in Colorado Period Covered: July 1, 2014 − June 30, 2015 Principal Investigator: Eric J. Bergman, eric.bergman@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. During November of 2013 we initiated a large scale moose research project in 3 of Colorado Parks and Wildlife’s 4 geographical regions. This project was continued into the 2014–2015 fiscal year. During the first year of this project, field efforts were primarily focused on the capture and collaring of moose. These capture efforts were continued into the 2nd year of the study. Field efforts were also expanded to include estimation of parturition rates. During the second year of the study, all captures occurred during late December (2014). During both years, capture efforts were focused in 3 study areas in Colorado — the Laramie River and Red Feather Lakes areas (NE Colorado), the Rabbit Ears range that separates North Park from Middle Park (NW Colorado), and along the Upper Lake Fork, Rio Grande Reservoir, and near Slumgullion Pass (SW Colorado; Fig. 1). Fifty-eight and 50 cow moose were captured and radio-collared during the first and second years of the study, respectively. Of the 50 cows that were captured during December 2014, 11 were recaptures of animals that were first caught during the 2013–2014 field season. Twenty moose were captured in the NW study area (including 3 recaptures of cows originally captured during the 2013–2014 field season), 14 moose were captured in the NE study area (0 recaptures), and 16 were captured in the SW study area (including 8 recaptures of cows originally captured during the 2013–2014 field season). Body condition and pregnancy status was determined for each animal at the time of capture. Annual survival rates for each study area were calculated for the 12-month period ending in mid-May. During May and June of 2015 parturition and twinning rates were estimated for the northeast and northwest study area. Mean measured rump fat during December 2014 ranged between 6.21–7.25 mm among study areas. Mean measured loin depth at the time of capture ranged between 41.7–43.3 mm among study areas. When data from 2013–2014 and 2014–2015 were pooled, pregnancy status was best predicted by maximum rump fat (Fig. 3). As was the case during the first year of the study, survival of radio collared animals was high in all study areas. Survival rates ranged between 85%–94% during 2013–2014 and from 88%–96% during 2014–2015. Pregnancy rates during 2013–2014 ranged between 68%–95%, and increased slightly during 2014–2015, ranging between 78%–95% (Fig. 2). Parturition rates were consistent between the northeast and northwest study areas (80%). Twinning rates at the time of capture ranged between 5.3%–12.5%. Thus far, data collected during this project have met expectations. In particular, survival rates have been consistently high in all study areas. Lower productivity was consistently observed in the northeast herd during both years. During future years, we will investigate opportunities to evaluate moose browse selection behavior. Likewise, we will begin investigations for determining herd level pregnancy status in cost effective ways. 21 �Probability of Being Pregnant Figure 1. Moose research study areas, located in 3 regions in Colorado. A total of 58 moose were captured during the winter of 2013–2014 and 50 moose were captured during the winter of 2014–2015. Survival of moose was high in all study areas and during both years. 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 2 4 6 8 10 12 14 16 Measured Rump Fat (mm) 18 20 22 24 Figure 2. Probability of moose pregnancy was best predicted by maximum measured rump fat. This strong relationship between body condition and pregnancy status reflects how nutritional condition can influence pregnancy, with animals in the poorest condition having lower probabilities of breeding. 22 �1 0.9 Pregnancy Rate 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Northeast Northwest Southwest Figure 3. Pregnancy rates for all moose at the time of capture from 2013–2014 (white bars) and 2014– 2015 (black bars). Lower pregnancy rates were observed in the northeast study area during both years. 23 �PREDATORY MAMMAL CONSERVATION BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS MOUNTAIN LION POPULATION RESPONSES TO SPORT-HUNTING ON THE UNCOMPAHGRE PLATEAU, COLORADO COUGAR AND BLACK BEAR DEMOGRAPHICS AND COUGAR-HUMAN INTERACTIONS IN COLORADO 24 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2014 − June 30, 2015 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: S.A. Lischka, S. Breck, J. Beckmann, J. Broderick, J. Apker, K. Wilson, and P. Dorsey All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a collaborative study involving Colorado Parks and Wildlife (CPW; lead agency), the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have designed and implemented a study on black bears that 1) determines the influence of urban environments on bear behavior and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. This project was initiated in FY2010-11; during this past fiscal year we have primarily focused on collecting field data in the vicinity of Durango, Colorado. Our efforts focused largely on field data needed to meet research objectives 1-3, information which will eventually be used to address objective 4. Specifically, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, monitored bear demographic rates (adult female survival, adult female fecundity and cub survival) through telemetry and winter den visits, tracked human-related bear mortalities and removals from the study area, performed non-invasive genetic mark-recapture surveys to estimate bear density, collected GPS collar location data on bears along the urban-wildland interface, monitored the availability of late summer/fall mast, obtained data on garbage-related bear-human conflicts, and assessed resident use of project-supplied bear-resistant garbage containers. Major research accomplishments from fiscal year 2014-15: • Between July 2014 and March 2015 (the 2014-2015 capture year), an additional 63 unique bears were marked during 147 bear captures. To date on the project there have been 327 different individuals marked during 717 captures. Five new adult females were collared during summer 2014 to collect demographic and habitat-use data (70 adult females have been collared to date). Bear capture and marking efforts are allowing us to track bear population parameters and habitat-use patterns along the urban-wildland interface. 25 �• During January - March 2015, we visited the winter dens of 37 collared females (Photo 1). Of those females, 11 did not have any cubs or yearlings, 8 had yearlings (12 total yearlings in total), and 19 had newborn cubs (41 cubs). We found that reproductive success, measured as the number of cubs/adult female, was 1.15 (SE = 0.20). This was the highest observed fecundity rate to date, as previous rates ranged between 0.52 (SE=0.16) and 0.95 (SE=0.24). Cub survival for 2015 (survival from newborn to 1 year) was 58% (based on 24 cubs), compared to 50% in 2014 and 40% in 2013. Photo 1. Cubs at a black bear den. Fecundity rates in 2015 were the highest that have been observed during the study (Photo Credit: Bill Masure). • To date, we have obtained >500,000 locations from GPS collars on 70 different adult female bears along the urban-wildland interface; 42 different bears provided location data during the active bear year of 2014 (May – October; Fig. 1). While most locations were in close proximity to Durango, a couple of bears were found outside the primary study area (Fig. 1). For example, B67 had moved to New Mexico in 2013, but moved back to Durango in fall of 2014 (with 2 cubs in tow). Another sow, B57, left her home range in lower Junction Creek (just north of Durango) to travel north to Hamilton Mesa (just south of Norwood), before returning to her original range. • In summer 2014, we collected 1,209 hair samples for a non-invasive genetic mark-recapture study designed to estimate bear densities and population sizes around the vicinity of Durango and an adjacent “wildland” site. Over a 6 week sampling period, a total of 551 hair samples were collected from the Durango grid and 658 samples from the wildland grid. The number of samples/snare ranged from 0 to 66 in the Durango grid and from 2 to 50 in the wildland grid. Genotype results should be returned from Wildlife Genetics International during fall 2015. Detailed mark-recapture analyses of these data to estimate density and abundance will be conducted in FY15-16. • Based on 15 1-km transects in the study area, the availability of natural mast foods was generally very good in late summer and fall 2014. Mast surveys demonstrated that the peak time for maturation of wild crabapple was late July, serviceberry was the first half of August, chokecherry was mid-August, hawthorne was late August, gambel oak was early September, and pinyon pines had cones developing in mid-September. On transects that had those species, mast was present on approximately 40% of wild crabapple shrubs, 70% of hawthorne shrubs and trees, and 50% of chokecherry, serviceberry oak and pinyon pine shrubs and trees. • During summer 2014 (July through September) we collected our second year of post-treatment data on an experiment designed to assess the effectiveness of wide-scale urban bear-proofing for reducing bear-human conflicts (pre-treatment data were collected during 2011 and 2012, post-treatment data were collected in 2013 and 2014). Within treatment and control areas we observed 202 instances of bears accessing residential garbage during morning patrols; observations generally peaked in midAugust. Of those garbage containers accessed by bears, 79% were regular and 21% were bearresistant; 40 garbage conflicts were observed in treatment areas (across ~1230 total residences) and 162 occurred in control areas (across ~1260 total residences; Fig. 2). We will continue to collect posttreatment data through 2015. 26 �• During summer 2014 we found that the average compliance of residents to wildlife ordinances was 55% in the north treatment area and 45% in the south treatment area. “Compliance” was defined as having a container that was properly locked (both latches clipped) or secured in a garage or shed before 6:00 am. Across all sampling periods, compliance was generally higher in the northern experimental area than in the southern area. In the northern area, compliance increased from ~45% in 2013 to ~55% in 2014. In the southern area compliance remained ~45% in both years. • Two journal articles were published this past year that used data from the study. In one article, black bear GPS collar locations were used to examine bear selection for human development (Johnson et al. 2015) and the other article evaluated a new immobilization drug combination for bears (Wolfe et al. 2014). In addressing our research objectives we hope to better understand the influence of human development on bear populations, elucidate the relationship between bear-human conflicts and bear behavior and demography, understand the effect of bear-human interactions on human attitudes and actions, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. For a more detailed version of this project summary see Johnson et al. (2015, Federal Aid Report W-204-R1): http://cpw.state.co.us/Documents/Research/Mammals/Publications/AlldredgeFrontRangeCougar_W204R4_ProgressReport_2014-15.pdf Literature Published in FY2014-15 Johnson, H.E., S.W. Breck, S. Baruch-Mordo, D.L. Lewis, C.W. Lackey, K.R. Wilson, J. Broderick, J.S. Mao, and J.P. Beckmann. 2015. Shifting perceptions of risk and reward: dynamic selection for human development by black bears in the western United States. Biological Conservation 187:164-172. Wolfe, L.L., H.E. Johnson, M.C. Fisher, M.A. Sirochman, B. Kraft, and M.W. Miller. 2014. Use of Acepromazine and Medetomidine in combination for sedation and handling of Rocky Mountain elk (Cervus elaphus nelsoni) and black bears (Ursus americanus). Journal of Wildlife Diseases 50:979-981. 27 �A B Figure 1. GPS collar locations from 42 adult female black bears collected during 1 January – 31 December 2014 in the vicinity of Durango, Colorado (different colored clusters of points represent different individual bears): A) an overview of all locations and B) locations around the town of Durango. 28 �Figure 2. Garbage-related black bear-human conflicts observed during July through September 2014. Red lines indicate treatment areas and black lines indicate control areas. Green circles represent conflicts with regular residential garbage containers and yellow circles represent conflicts with wildlife-resistant containers. 29 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mountain lion population responses to sport-hunting on the Uncompahgre Plateau, Colorado Period Covered: July 31, 2014 ─ June 30, 2015 Principal Investigator: Kenneth A. Logan, Ken.Logan@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. The Colorado Parks and Wildlife (CPW) initiated a 10-year study in 2004 on the effects of sporthunting on a mountain lion population on the Uncompahgre Plateau. This study was designed to provide information that can be applied to future lion management. The study quantifies lion population characteristics in the absence of hunting (termed the reference period, years 1-5) and the application of hunting (termed the treatment period, years 6-10). The purpose of the study is to evaluate the current biological assumptions used by CPW to manage lions with hunting and to learn how lion hunter behavior may influence harvest. Testing the management assumptions is important, because managers normally have no information on lion abundance, population sex and age structure, or effects of hunting on lions for any region of Colorado; therefore, unreliable assumptions might lead to management errors that could affect regional lion populations. Lion hunter behavior is important to understand because it may influence the sex and age structure of lions killed by hunters, and those harvest data are used by CPW managers in an effort to make biological judgments about lion populations and effects of hunting. Field operations for this study were completed in December 2014. Starting January 2015 the principal investigator along with collaborators began a formal phase of data analysis, partially included in this report. Analyses are ongoing and are expected to provide reliable information for application in lion management in Colorado. The reference period began December 2004 and ended October 2009, during which we captured, sampled, and marked 109 individual lions for research purposes. During this period without sport-hunting as a mortality factor the population of independent lions comprised of adults and subadults increased from a low of 33 lions counted in reference year 4 to a high of 56 lions counted in the treatment year 1 (Fig. 1). This was an indication that lion management on the Uncompahgre Plateau previous to this study likely suppressed the lion population. Along with the population increase during the reference period, adult lion survival was high and the age structure of independent lions increased; expected characteristics of an increasing population. The main cause of death in adults was aggression by other lions (57%, n = 4). Two deaths of radio-collared adult lions were due to human causes; 1 adult female killed for depredation control and 1 adult female killed by vehicle strike. Only 1 subadult lion died of human causes; 1 female killed by vehicle strike. Infanticide by male lions was the main cause of death for cubs (81%, n = 13). The treatment period, in which managed sport-hunting of lions resumed on the study area, began in November 2009 and ended December 2014. An additional 115 lions were captured and marked in the treatment period. As indicated previously, treatment year 1 was the first year that hunting influenced the lion population after 5 years of no hunting, and it was marked with the highest estimate of independent lions (56) on the study area. During treatment years 1 through 3, the lion harvest rate was set with a design quota of 8 lions to test a prediction that a 15% harvest of independent lions would result in a stable-to-increasing population. This is an important management assumption to test, because it represented a maximum mortality rate on independent lions that was assumed to achieve a stable-toincreasing population trend, one of two CPW lion population management objectives that are applied to certain regions (Data Analysis Units, DAUs, each comprised of multiple Game Management Units, 30 �GMUs). However, the expectation that a 15% harvest results in a stable-to-increasing population was not supported as the population of independent lions declined from 56 in treatment year 1 to 42 by treatment year 4 (Fig. 1). The other CPW lion management objective was to manage certain regions to substantially reduce or suppress lion abundance with hunting. Results from treatment years 1 through 4 indicated that reducing a lion population with hunting is achievable at a 15% harvest rate. Hunting-caused mortality was the single most important cause of mortality in adult and subadult lions, comprising 57% (n = 21) and 55% (n = 11) respectively. Starvation and infanticide by male lions were the main causes of death for cubs, 33% (n = 9) and 30% (n = 8) respectively. The lion population was expected to continue to decline if the quota remained at 8 lions, because 8 lions represented a 19% harvest by treatment year 4, a larger percentage than the 15% harvest that had already contributed to population decline. Therefore, in an effort to find a harvest rate useful to managers that would result in a stable-to-increasing population for the remainder of the study, the quota was reduced to 5 lions. This quota represented about 11-12% harvest rate of independent lions for treatment years 4 and 5. The count of independent lions in treatment years 4 and 5 were 42 and 44 lions, respectively, suggesting that the lower harvest rate of 11-12% resulted in a cessation of the decline in the number of independent lions. The minimum of 42 independent lions counted in treatment year 4, represented a 25% decline since treatment year 1. We used an information-theoretic approach and Akaike’s Information Criterion to rank survival models with and without the treatment effect. The hunting treatment was indicated as an important factor explaining variation in lion survival rates. Survival rates of adult male lions declined from 0.96 in the reference period to 0.40 in the treatment period, and adult female survival declined from 0.86 to 0.74 in those respective periods. Subadult survival rates declined from 0.84 in the reference period to 0.52 in the treatment period. Cub survival rates declined from 0.50 in the reference period to 0.34 in the treatment period. The age structure of independent lions also declined in the treatment period. Moreover, there was a substantial biological effect in the fecundity rate, which declined from 0.63 in the reference period to 0.48 in the treatment period. During the treatment period, additional independent radio-collared lions were killed by hunters outside of the study area during the Colorado lion hunting season spanning November through March each winter. Those lions were counted as part of the harvest quota in other GMUs. This occurred even though the study area was one of the largest GMUs in Colorado. Home ranges of most lions, particularly of males, were large enough to span at least two GMUs so lion movements put some individuals at risk of hunting mortality even after the study area quota was filled. Therefore, hunting-caused mortality affected the study lion population over a larger area and for a longer period of time than was expected under the current lion management structure. The total hunting mortality plus other human causes of mortality, such as road kill and depredation control, and natural mortality contributed to the lion population decline and low phase. This indicated a need for managers to consider how all mortality might impact a lion population, as well as, modifications to the current management structure. Besides the study on effects of sport-hunting on lions, other projects associated with lion biology were developed in collaboration with colleagues in CPW, Colorado State University, Colorado Cooperative Fish and Wildlife Research Unit, Oklahoma State University, University of Wisconsin, and Arizona State University. From August to December 2009 we collaborated with Ph.D. student Jesse Lewis and Dr. Kevin Crooks (C.S.U., Dep. of Fish, Wildlife, and Conservation Biology) in a study of relationships of bobcats to mountain lions and considerations in using a camera grid with marked lions to estimate lion detection, abundance, and density. Jesse completed his Ph.D. dissertation and manuscripts submitted to journals by December 2014. From December 2012 to March 2013 we collaborated with Master’s student Kirstie Yeager (Colorado Cooperative Fish and Wildlife Research Unit) and Dr. Mat Alldredge (Mammals Researcher, CPW) to test non-invasive methods for detecting lions for efforts to estimate abundance. Her work also allowed us to assess the proportion of lions marked in the population on the Uncompahgre Plateau study. Kirstie defended her thesis in May 2015, is making final edits to her thesis, and is in the process of submitting papers for publication in journals. We are also involved in an ongoing study of diseases in mountain lions and bobcats with Dr. Sue VandeWoude (C.S.U., Dep. Of 31 �Microbiology, Immunology, and Pathology), Dr. Kevin Crooks and their colleagues and graduate students. Diseases and pathogens to which lions and bobcats sampled from the Uncomphagre Plateau study area were exposed, included: plague (caused by the bacteria Yersinia pestis), Feline immunodeficiency virus, Bartonnela sp., and Toxoplasma gondii. Several manuscripts have been published on those efforts. In addition, Dr. Mason Reichard (Dep. of Veterinary Pathology, Oklahoma State University) found that up to 45% of independent lions sampled may be infected with 3 species of Trichinella sp. A manuscript on that work is in review for journal publication. We collaborated with Master’s student Wynne Moss (Dep. of Forestry and Wildlife Ecology, Univ. of Wisconsin) to conduct isotopic analysis of lion diet in wildland and developed habitats to examine shifts in lion diet and niche breadth. A manuscript by Wynne is in press. Finally, we are collaborating with Dr. Melody Roelke (Arizona Cooperative Fish and Wildlife Research Unit, Univ. of Arizona) and Ph.D. student Alex Erwin to examine lion genetic relatedness, reproductive success, and population structure. The projected time for completion for that work is spring 2017. Figure 1. Trends in the population of independent mountain lions associated with no sport-hunting in the reference period years 4 and 5 (RY4, RY5) and with sport-hunting in the treatment period years 1 through 5 (TY1 to TY5), Uncompahgre Plateau, Colorado. The count data were gathered from November through April each winter in efforts to canvass the study area thoroughly to count the number of independent lions in addition to the lion harvest. These data represent the number of independent lions expected to have been at risk to hunting during the Colorado lion hunting season November through March each year. 32 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Cougar and bear demographics and human interactions in Colorado Period Covered: July 1, 2014 − June 30, 2015 Principal Investigator: Mathew W. Alldredge, mat.alldredge@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. PROJECT NARRITIVE OBJECTIVES 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban Front Range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus), assessing diet composition and estimating population densities of cougars for the state of Colorado. SEGMENT OBJECTIVES Section A: Telomeres and Stable Isotopes 1. Evaluate the potential to develop a model for estimating age of bears and cougars based on telomere length. 2. Determine diet composition of bears and cougars using stable isotopes. Section B: Front Range cougars 3. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. 4. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets (Completed). 5. Continue to assess relocation of cougars as a practical management tool. 6a. Assess cougar predation rates and diet composition based on GPS cluster data (Completed). 6b. Assess kill site dynamics and prey selection of cougar kills. 7. Model movement data of cougars to understand how cougars are responding to environmental variables. 8. Develop non-invasive mark-recapture techniques to estimate cougar population size. 2014-2015 Project Overview Field efforts during the 2014-2015 year were primarily focused on the development of noninvasive population estimation techniques for cougars and bobcats (see summary for Noninvasive genetic sampling to estimate cougar and bobcat abundance, age structure, and diet composition). The field efforts for the remaining segment objectives listed above have been completed and are in various stages of data analysis and publication. 33 �Section A: Telomeres and Stable Isotopes 1. Evaluate the potential to develop a model for estimating age of bears and cougars based on telomere length. Field work completed—data analysis and publication (see summary Spatio-temporal patterns of diet and telomere length in Colorado black bears) 2. Determine diet composition of bears and cougars using stable isotopes. Field work completed—data analysis and publication (see summaries Spatio-temporal patterns of diet and telomere length in Colorado black bears and thesis abstracts Novel habitats present novel challenges for an apex carnivore (Puma concolor) and Niche sprawl in an opportunistic apex predator (Puma concolor)) Section B: Front Range cougars 3. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. Field work completed—see Federal Aid Report for preliminary summaries 4. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets. Field work completed—see Federal Aid Report for preliminary results and summaries 5. Continue to assess relocation of cougars as a practical management tool. In progress—see Federal Aid Report for preliminary data 6a. Assess cougar predation rates and diet composition based on GPS cluster data. Field work completed—data analysis and publication (see thesis abstract Risk-reward tradeoffs in the foraging strategy of cougar (Puma concolor): Prey distribution, anthropogenic development, and patch-selection) 6b. Assess kill site dynamics and prey selection of cougar kills. Field work completed—data analysis and publication in progress 7. Model movement data of cougars to understand how cougars are responding to environmental variables. Field work completed—contact Mat Alldredge for current publications. 8. Develop non-invasive mark-recapture techniques to estimate cougar population size. Field work completed—data analysis and publication (see thesis abstracts The Use of Lures, Hair Snares, and Snow Tracking as Non-Invasive Sampling Techniques to Detect and Identify Cougars) Noninvasive genetic sampling to estimate cougar and bobcat abundance, age structure, and diet composition Cougar and bobcat populations are actively hunted throughout the state of Colorado and management is applied using the best available information. Unfortunately, reliable information on cougar and bobcat populations is nascent. The best information available comes from long-term studies on relatively small populations where animals have been repeatedly captured. However, to better manage these populations, broad-scale information for these species is necessary. We have begun developing noninvasive genetic sampling (NGS) techniques to provide better, less expensive data for cougars and bobcats that can be implemented at broad geographic scales with state-wide application. The methods being developed should provide information on population size, sex structure, age structure, and diet composition. This information is valuable to the future management of these species and for the justification of harvest levels imposed on them. Over the next few years we intend to further refine these NGS techniques for cougars and bobcats so that they can be reliably implemented to inform management decisions. We also intend to perform at least one full survey over multiple years so that we can assess the reliability and repeatability of this approach. Following these efforts our hope is that we will have a fully developed NGS approach for cougars and bobcats that can be implemented at a state-wide level for future monitoring of these species. 34 �Objectives: 1. Continue to evaluate the use of auditory calls for NGS sampling of cougars. 2. Implement a NGS survey for cougars over multiple years to evaluate the consistency of the approach. 3. Use collared cougars to evaluate trap response of cougars and assess potential biases in the NGS approach. 4. Evaluate the potential to sample bobcats using the same NGS approach. 5. Test alternative hair snaring devices for felids. 6. Assess a simultaneous sampling approach for bobcats and cougars relative to differences in home-range size. 7. Implement an NGS survey over multiple years for bobcats and cougars to determine the logistics, cost and feasibility of sampling to obtain estimates of density, sex structure, age structure and diet composition. Following on the success of the development of noninvasive techniques for sampling cougars we initiated a three-year study to continue to develop noninvasive methods for sampling cougars and bobcats. Sites were built in November and December, 2013, and were monitored for 12 weeks during January – April, 2014 (see study plan for details, Appendix VI). This year sites (Figure 1) were built during November and monitored for three months starting the 1st of December and continuing through the first week of March. Sites were modified this year to use vertical hair snags instead of horizontal snags in an attempt to get more animals to enter the cubbies and to create a snag that could obtain samples from both bobcats and cougars. The number of unique observations of cougars decreased from 86 in 2014 to 42 in 2015, while observations of bobcats increased from 31 to 68 across years (Table 1). Hair samples for cougars decreased accordingly from 55 in 2014 to 32 the following year. Hair samples from bobcats increased from 5 the first year to 12 the second year. Genotypes from bobcat hair have not been successful, but is somewhat successful for cougars. Table 1: Noninvasive hair snag capture results for bobcats and cougars. Number of animals seen, number of hair samples collected and number of successful genotypes. Species Year Pictures Hair Samples Genotypes Bobcat Bobcat Cougar Cougar 2014 2015 2014 2015 31 68 86 42 5 12 55 32 0 1 20 11 35 �Figure 1: Study area boundary and grid layout for NGS cougar and bobcat sites. Larger squares represent the 5 km2 grid overlaid with a 1 km2 grid. White 1 km2 cells represent the randomly selected cells where actual lure sites will be placed. Spatio-temporal patterns of diet and telomere length in Colorado black bears Becky Kirby (UW-Madison), Jonathan Pauli (UW-Madison), Mat Alldredge (Colorado Parks & Wildlife) The effect of human-derived food on free-ranging wildlife populations is a growing problem across North America, and is particularly evident among carnivore populations. In Colorado, American black bear (Ursus americanus) conflicts have been increasing, and research is focused on elucidating factors that drive such conflicts. Understanding the influences of food availability and population trends is necessary to mitigate risks posed by these conflicts. To this end, this project aims to assess broad-scale patterns of diet and age in black bears across Colorado in hunter-harvested bears. We are quantifying diet and telomere length of black bears, in relation to geographic and habitat variables. Specifically, we are examining the amount of human food consumption, compared to native foods. Because human food is often underestimated using traditional diet reconstruction analyses due to issues such as digestibility, we are using stable isotope analyses that reflect assimilated diet. Further, we are examining a non-invasive technique related to aging in black bears, using genetic analyses of telomere length measured by qPCR. Telomere length is related to chronological age, but also can be a valuable indicator of fitness and senescence. 36 �We analyzed isotopic signature (δ13C and δ15N) for ~ 300 hunter-harvested bears. Enriched (higher) signatures likely indicate greater consumption of human-derived foods and animal matter, respectively. Adults and eastern bears are significantly enriched in both δ13C and δ15N. Proportional diet estimates from SIAR suggest that northeastern bears consume the greatest amount of human-derived foods compared to other regional bear populations (Table 1). This appears to be driven primarily by availability, as human activity (indexed by road density) is the strongest predictor of human-derived food consumption at a landscape scale (Figure 1). Further, the odds of being a nuisance bear increased by 60% for each per mil increase in δ13C. We also quantified relative telomere length from these hair follicles in 245 individuals, ranging in age from 1-21 (estimated by cementum annuli). Samples exhibit wide variation among telomere length (T/S) across ages, showing no significant trends. Telomere length declined with increasing latitude and increasing elevation, suggesting a geographical relationship with telomere length (Figure 2). However, telomere length increased with measures of habitat quality, suggesting a positive effect of habitat quality on telomere length. We suspect these patterns reflect differences in important environmental conditions, particularly those driving physiological stress and characteristics of hibernation, that are overwhelming potential relationships to typical predictors of telomere length. Thus, ongoing longitudinal studies are necessary to elucidate rates of change rather than single timepoint samples and increase resolution of covariates. This study will yield insight into bear foraging ecology and aging, especially how human food and land use impacts both. Further development of these isotopic and molecular techniques will be aid in future bear management and biological studies. Table 1. Assimilated dietary estimates for black bears in the summer and fall seasons, obtained from the isotopic signatures of hair and blood, respectively. Eastern bears consumed more human-derived foods than western bears, regardless of season, but bears consumed less human-derived foods during the fall than the summer. Estimates provided by region of Colorado. Mean Proportion (95% CI) Diet Groups NE CO SE CO NW CO SW CO Hair (n) 29 71 104 92 Vegetation 0.69 (0.65-0.74) 0.72 (0.69-0.76) 0.83 (0.80-0.85) 0.85 (0.82-0.88) Animal matter 0.04 (0.02-0.07) 0.06 (0.05-0.08) 0.11 (0.09-0.12) 0.11 (0.10-0.13) Human-derived foods 0.26 (0.21-0.32) 0.22 (0.18-0.26) 0.07 (0.03-0.10) 0.04 (0.00-0.07) Blood (n) 9 29 37 38 Vegetation 0.64 (0.53-0.76) 0.77 (0.70-0.84) 0.83 (0.80-0.86) 0.86 (0.83-0.88) Animal matter 0.07 (0.00-0.13) 0.07 (0.05-0.11) 0.15 (0.12-0.17) 0.13 (0.11-0.15) Human-derived foods 0.29 (0.14-0.45) 0.15 (0.06-0.24) 0.02 (0.00-0.05) 0.01 (0.00-0.04) 37 �Figure 1. Linear regression of δ13C on road density (natural-log transformed), showing a positive relationship between increased road density and δ13C enrichment, with points representing age-sex classes: adult male (filled black circles), adult female (filled gray circles), subadult male (open black circles), subadult female (open gray circles). 38 �Figure 2. Relationship of relative telomere length (T/S) with individual covariates that we predicted could influence telomere lengths in Colorado black bears. Regression lines shown for significant relationships. 39 �Novel habitats present novel challenges for an apex carnivore (Puma concolor) Wynne E. Moss (UW-Madison), Mathew W. Alldredge (CPW), Jonathan N. Pauli (UW-Madison) Abstract: Human-modified landscapes are now the most common global cover type. Species persistence in these landscapes hinges upon adaptability, including the capacity to exploit novel food resources and habitats. Yet, for large carnivores, there may be significant costs of such a strategy. Cougars (Puma concolor), though generally considered specialists of large ungulates, are capable of preying upon a variety species, which could be advantageous in novel ecosystems like developed landscapes. However, these areas also represent a landscape of heightened risk of conflict with humans. We examined the tradeoff between dietary flexibility and survival in a population of cougars inhabiting Colorado’s urban-wildland interface. We monitored space use of GPS-collared cougars and related this to estimates of diet from stable isotope analysis. Our population-wide estimate of diet revealed that native herbivores constituted the bulk of assimilated biomass (64-79%), though there was considerable variation among individuals. Cougars using the most highly developed areas obtained 20% more of their diet from alternative prey (synanthropic wildlife and domestic animals) than those in the least developed areas. Adult males and subadults consumed more alternative prey compared to adult female cougars. Use of developed areas significantly increased risk of mortality for both males and females. Thus, though cougars displayed a highly plastic foraging strategy in developed areas, they were less likely to survive. Our findings reveal that, despite their dietary flexibility, the heightened risk from human conflict is likely to inhibit cougar population recoveries in densely populated areas. Niche sprawl in an opportunistic apex predator (Puma concolor) Wynne E. Moss (UW-Madison), Mathew W. Alldredge (CPW), Kenneth A. Logan (CPW), and Jonathan N. Pauli (UW-Madison) Abstract: Urban areas are dramatic examples of landscape change and increasingly identified as systems in which to promote ecological complexity and conservation. Yet, little is known about the processes that regulate highly developed ecosystems, or the behaviours employed by species adapting to them. We evaluated the isotopic niche of an ecologically important apex carnivore, the cougar (Puma concolor), over broad spatiotemporal scales and in a region characterized by rapid human growth. We detected a niche expansion, from specialization on native herbivores in wildlands to enhanced reliance on exotic and invasive species by cougars in contemporary urban interfaces. We show that 25 years ago, cougars inhabiting these same urban interfaces possessed diets that more closely resembled their wildland counterparts, suggesting foraging adaptations are recent. Thus, urban sprawl has been accompanied by a niche sprawl over both time and space, indicating that an important top predator is interacting in novel ways. Thus, adaptations to urbanization could alter the ecological role of apex carnivores, and while human-dominated landscapes may maintain these species, their functional relationships are unlikely to remain the same. 40 �Risk-reward tradeoffs in the foraging strategy of cougar (Puma concolor): prey distribution, anthropogenic development, and patch-selection – MS Thesis Abstract Kevin Blecha (Colo. State Univ.), Mat Alldredge (CPW), and Randy Boone (Colo. State Univ.) Empirical efforts for understanding whether the space utilization patterns of large elusive carnivores foraging on highly mobile prey are sparse. Having an understanding of the patch choices made by a large carnivore while engaged in foraging behaviors is of particular importance to understanding their conflicts with humans. The over-arching goal of this thesis is to test whether the foraging strategies carried out by a large carnivore inhabiting an area marked by human housing development can be explained by classic optimal foraging theory (OFT). My research takes place in a portion of the Colorado Front Range, which is a foothill-montane system characterized by the urban-wildland interface of the greater Denver metropolitan area and surrounding cities (Boulder, Golden, Evergreen). A matrix of varying levels of rural, exurban, and suburban development are expected to drive the patch-choices made by cougar, a large obligate carnivore that can conflict with human interests when it conducts foraging behaviors. Before answering questions involving patch choice foraging behaviors, several pieces of information must be acquired. Specifically, Chapter 1 and Chapter 2 take an Eulerian approach to understanding the space utilization patterns of wild prey commonly sought by cougar in this area. Predicted utilization by these prey species is mapped for the study area on a fine (30 m) scale, with the premise that cougar may be attracted to localities where the opportunity of encountering a potential prey item is greater. Appendix 2 provides details on methods used to determine the distribution of housing development, a patch characteristic that cougars may have fear toward. This appendix also provides some discussion on the anthropogenic development experienced in the study area. Appendix 4 provides details on the construction of various “natural” landscape variables from readily available data sources. Chapter 1 shows that simple encounter measures collected from camera traps can provide a measure of landscape utilization for an animal population at extremely fine scale patch size. I demonstrate that the amount of utilization at a patch, whether by one or many animals, is a function of the abundance of animals within some area around the camera and the micro-habitat utilization patterns of the individuals in that population. However, I show that biases will exist in many situations if certain protocols are not adhered to. Chapter 2 applies the principle from Chapter 1 to produce a landscape utilization map of common cougar prey species at a fine scale. This was done using a count measure of the amount of time spent by animals within the field-of-view of a sample of 131 camera trap sites monitored over a one year period. While doing so, I accounted for the probability of detection within the camera’s field-of-view in the count response. Probability of detection was found to be influenced by several environmental and animal specific variables. A secondary focus was to understand the associations between animal utilization and housing development. The associations found were generally supportive of those found in previous studies using habitat selection, occupancy, and abundance as response variables. Finally in Chapter 3, using cougar as a model species, I test whether a large carnivore’s foraging strategy can be explained by optimal foraging theory, which says that an animal makes decisions while foraging that balances the process of acquiring energy with the process of avoiding risks. In seminal optimal foraging works, authors proposed that an animal will be less cautious in avoiding risks when energetically stressed. I demonstrate that cougars make a tradeoff between choosing locations that would yield a higher encounter rate of prey with choosing safer patches. Cougars were found to show avoidance of higher housing densities, but also shown to be attracted to higher primary prey (mule deer) availability. Support for this tradeoff was shown by demonstrating that hunting success increased as cougars hunted in higher housing densities. Furthermore, the strength of the housing avoidance behavior declined as cougar hunger levels increased. A similar behavior was observed during temporal periods associated with assumingly decreased availability of primary prey; cougars became less cautious when imposed with energetic constraints. 41 �The Use of Lures, Hair Snares, and Snow Tracking as Non-Invasive Sampling Techniques to Detect and Identify Cougars – MS Thesis Abstracts Kirstie Yeager, (Colo. State Univ.), Mat Alldredge (CPW), and Bill Kendall (Colo. State Univ.) Development of a Noninvasive Method to Sample Cougars (Puma concolor) A noninvasive method that will sample all individuals in a population over multiple occasions is a useful tool in assessing population demographics with little disturbance to the target animals; however, finding such a method for large carnivores, such as cougars, is challenging due to their elusive nature and large home-range sizes. Current methods to sample cougars usually involve a physical capture component, but obtaining reliable estimates can be difficult and cost prohibitive when using capture as the sole sampling method. Because cougars leave sign, and exhibit behaviors like territoriality and curiosity, a noninvasive-genetic-sampling (NGS) method may be a plausible alternative. Hair contains DNA, which can be genetically analyzed to yield the individual identification necessary for population assessments and can be obtained without handling the animal. I tested NGS techniques using attractants, specifically scent lures and auditory calls, and hair snares to sample cougars at lure sites on the Front Range, Colorado during February – April, 2012 and November, 2012 – April, 2013. I established 16 – 20 sites over four ≈ 30-day sampling periods. In general, my results suggest calls are more effective attractants than scents. At sites with auditory calls, photographs documented 40 visits by ≥ 13 individual cougars, and I obtained 14 hair samples. Only 2 hair samples were collected using scented scratch pads and no samples were acquired via a novel hair snare. I conclude that given the ability to successfully genotype the hair samples collected, auditory calls and hair snares may be an effective way to assess the various population demographics that are needed to inform management decisions. Assessing the Probability of Identifying Cougars by Noninvasive-Genetic Sampling with Auditory Predator Calls and Hair Snares Detecting all individuals in a population equally and with certainty will yield unbiased population estimates; however, many current sampling techniques for cougars have inherent variation, such as a trap response or individual heterogeneity in detection probability. From November, 2012 – April, 2013, I applied a noninvasive method to sample cougars and assessed variation in detection in 2 study areas in Colorado, one on the Front Range (FR; 1,270 km²) and one on the Uncompahgre Plateau (UP; 540 km²). In total, I established 148 lure sites with auditory predator calls and hair snares over 3 (UP) and 4 (FR) sampling periods. Each site was active an average of 28.5 days (4,214 sampling nights). On the FR, I observed 98 detections by 13 independent marked cougars, 2 sibling groups, and ≥ 16 unique unmarked animals. On the UP, I documented 18 detections by 7 independent marked cougars and no unmarked animals. Collectively, 14 of the 20 marked cougars detected were observed multiple times. I used the GPS location data of 27 previously marked cougars to determine availability and estimated detection probabilities. The probability of detecting an independent marked cougar at least once during the study adjusted for partial availability was 0.83 ± 0.10 (FR) and 1.00 (UP). I collected 59 hair samples. Thirtytwo were genotyped at ≥ 8 loci identifying 26 unique cougars. I concluded that a noninvasive-sampling technique using auditory calls and hair snares can be a useful tool in assessing population demographics of cougar populations. 42 �SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT 43 �Colorado Parks and Wildlife WILDLIFE RESEARCH REPORT SUMMARY Research library, annual report Period Covered: July 1, 2014 – June 30, 2015 Author: Kay Horton Knudsen, kay.knudsen@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. The Colorado Parks and Wildlife Research Center Library has existed for several decades in the Ft. Collins office. Early librarians can be credited with the physical organization of the Library including 77 years of Federal Aid reports, 7 decades of Wildlife Commission reports and a unique book and journal collection. The goal of the Library is to provide an effective program of library services for Colorado Parks and Wildlife employees, cooperators and wildlife educators. The Library also serves as an archive for CPW publications. The mission of outreach and support is fulfilled using technology to provide a library website with the online catalog, wildlife databases and digitized documents available to CPW staff statewide. As of June 30, 2015, the Research Library held 19,464 titles and 32,170 items (these are the multiple copies of a title) and had 172 registered patrons (CPW staff). As part of the project to digitize CPW documents, the equivalent of 8GB of data has been scanned and uploaded to the catalog vendor. Current wildlife databases include BioOne, four of EBSCO’s specialty databases (Environment Complete, Fish and Fisheries Worldwide, Wildlife and Ecology Studies Worldwide and CAB Abstracts), Birds of North America, ProQuest Dissertations and Theses and the JSTOR Life Sciences collection. Print subscriptions to the major wildlife journals were cancelled several years ago, however online access to the journals was retained and continues as a primary usage point for staff. CPW staff statewide are authenticated through WildPoint (intranet) eliminating the need for individual usernames and passwords. An on-going project has been the digitization of Colorado Parks and Wildlife publications. This year the Aquatic Federal Aid reports were scanned and the resulting PDFs made available via the Library catalog. At CPW staff request, digital scans of Big Game Hunting brochures from 1949-1996 were made at a local commercial vendor. Due to the large file size, extensive work was required to make the PDFs both word-searchable and transferable. CPW staff can now access these historic files on WildPoint. In the Fall of 2014, an astute new employee in the Denver office of CPW found several boxes of diaries and logbooks. The boxes made their way to the Library in Ft. Collins where they were discovered to be the extensive hand-written daily logs (1929-1984) of John D. Hart. Hart was a long-time employee who started as a game warden and then served as Assistant Director of Colorado Division of Wildlife. As a collection, the logbooks constitute valuable primary-source material. They were donated to the Western Heritage Collection of Denver Public Library where they will be properly preserved and used by researchers of Colorado’s natural resources history. The Library website provides more full-text resources than ever before, however there are also more abstract-only indexes. A major role of the librarian is to assist CPW staff with document delivery and research assistance. The Library is not open on a walk-in basis to the general public, but the librarian does assist the Denver Help Desk and area staff with questions they receive from citizens. The librarian has Affiliate Faculty status with the Colorado State University Library, which provides access to the large natural resources and science collection at that facility. The chart below shows the number of reference questions and document requests handled by the librarian each month during the past 7 years. Please note that one request from a CPW staff member may be for multiple journal or book titles. Even though the 44 �total number of requests dropped slightly this year, it is interesting that the current record for number of requests per month was set in January 2015 and then immediately increased in February 2015. Table 1. Monthly CPW Research Library reference requests August 2008 – July 2015. 2008-09 July 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 20 45 28 37 60 44 Aug 15 25 34 52 44 45 25 Sept 21 30 37 53 48 46 42 Oct 33 38 41 42 39 74 37 Nov 14 28 46 52 51 48 47 Dec 28 32 34 52 49 46 35 Jan 33 62 48 64 46 53 75 Feb 30 43 43 43 54 62 77 Mar 35 36 46 36 53 48 70 Apr 24 23 30 42 57 58 May 13 17 51 53 70 65 39 58 June 20 26 27 36 35 34 34 TOTAL 266 380 482 553 591 612 602 45 � https://cpw.cvlcollections.org/files/original/dbd8b593a45e95989198c9b8f168cd04.pdf 452bed7a682eb64f04639eb9c067c6f9 PDF Text Text MAMMALS - JULY 2016 �ii �WILDLIFE RESEARCH REPORTS JULY 2015 – JUNE 2016 MAMMALS RESEARCH PROGRAM COLORADO PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). iii �Executive Summary This Wildlife Research Report represents summaries (5 pages each) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) and habitat restoration projects from the CPW Avian Research Section from July 2015 through June 2016. These research efforts represent long term projects (4 – 10 years) in various stages of completion addressing applied questions to benefit the management of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx or from the project principal investigators listed at the beginning of each summary. Current research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to various habitat alterations, human-wildlife interations, and investigating improving approaches to wildlife and habitat management. The Mammal Conservation Section addresses mammal and breeding bird responses to the recent bark beetle outbreak influencing about 3.7 million acres of spruce and pine forests in Colorado and ongoing results of lynx monitoring in the San Juan Mountain Range of southwest Colorado. The Ungulate Conservation section includes 4 projects addressing development planning and mitigation approaches to benefit mule deer exposed to energy development activities, an assessment of mechanical habitat treatment methods to improve mule deer habitat, mitigation techniques to restore native vegetation following energy development disturbances, and an evaluation of moose demographic parameters that will inform future management of this recently established ungulate species in Colorado. The Predatory Mammal Conservation section addresses black bear use of urban environments and approaches for managing black bear-human interactions, evaluation of sport harvest for mountain lion management, and assessment of cougar and black bear demographics and human interactions in Colorado. The Support Services section describes the CPW library services to provide internal access of CPW publications and online support for wildlife and fisheries related publications. We have benefited from the numerous collaborations that support these projects and the opportunity to work with and train wildlife technicians and gradute students that will enhance wildlife management and ecology in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, Idaho State University, University of Wisconsin-Madison, the Buerau of Land Management, City of Boulder, Boulder and Jefferson County open space, City of Durango, Big Horn Sheep, Moose and Mule Deer Auction/Raffle Grants, Species Conservation Trust Fund, GOCO YIP Internship program, CPW Habitat Partnership Program, Safari Club International, Boone and Crocket Club, Colorado Mule Deer Association, The Mule Deer Foundation, Muley Fanatic Foundation, Wildlife Conservation Society, SummerLee Foundation, EnCana Corp., ExxonMobil/XTO Energy, Marathon Oil, Shell Exploration and Production, WPX Energy, and private land owners who have provided access for research projects. iv �STATE OF COLORADO John Hickenlooper, Governor DEPARTMENT OF NATURAL RESOURCES Mike King, Executive Director PARKS AND WILDLIFE COMMISSION Chris Castilian, Chair ......................................................................................................................... Denver Jeanne Horne, Vice Chair ................................................................................................................... Meeker James Pribyl, Secretary ...................................................................................................................... Boulder Robert Bray ........................................................................................................................................ Redvale John Howard ...................................................................................................................................... Boulder William Kane ........................................................................................................................................ Basalt Dale Pizel ............................................................................................................................................. Creede James Vigil........................................................................................................................................ Trinidad Dean Wingfield ................................................................................................................................... Vernon Michelle Zimmerman................................................................................................................. Breckenridge Alexander Zipp .................................................................................................................................... Pueblo Mike King, Executive Director, Ex-officio ........................................................................................... Parker Don Brown, Dept. of Agriculture, Ex-officio............................................................................ Yuma County DIRECTOR’S LEADERSHIP TEAM Bob Broscheid, Director Margaret Taylor, Justin Rutter, Reid DeWalt, Heather Dugan, Gary Thorson, Jeff Ver Steeg, Pat Dorsey, Dan Prenzlow, Ron Velarde, Mark Leslie MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Wildlife Researcher Eric Bergman, Wildlife Researcher Jake Ivan, Wildlife Researcher Heather Johnson, Wildlife Researcher Ken Logan, Wildlife Researcher Kay Knudsen, Librarian Margie Michaels, Program Assistant v �vi �Colorado Division of Parks and Wildlife July 2015  June 2016 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH SUMMARIES MAMMAL CONSERVATION MAMMAL AND BREEDING BIRD RESPONSE TO BARK BEETLE OUTBREAKS IN COLORADO by J. Ivan & A. Seglund………………………………………………………..1 CANADA LYNX MONITORING IN COLORADO by J. Ivan, E. Odell, & S. Wait.………….6 UNGULATE AND HABITAT CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson……….12 EXAMINING THE EFFECTIVENESS OF MECHANICAL TREATMENTS AS A RESTORATION TECHNIQUE FOR MULE DEER HABITAT by D. Johnston……………...17 RESTORING ENERGY FIELDS FOR WILDLIFE by D. Johnston…………………………...22 EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO by E. Bergman….…….………………………………………………………..27 PREDATORY MAMMAL CONSERVATION BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS by H. Johnson..............................................................................................................31 MOUNTAIN LION POPULATION RESPONSES TO SPORT-HUNTING ON THE UNCOMPAHGRE PLATEAU, COLORADO by K. Logan……………………………............36 COUGAR AND BEAR DEMOGRAPHICS AND HUMAN INTERACTIONS IN COLORADO by M. Alldredge……………………………….....................................................40 SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT by K. Knudsen………………………………….44 vii �MAMMAL CONSERVATION MAMMAL AND BREEDING BIRD RESPONSE TO BARK BEETLE OUTBREAKS IN COLORADO CANADA LYNX MONITORING IN COLORADO viii �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mammal and breeding bird response to bark beetle outbreaks in Colorado Period Covered: July 1, 2015  June 30, 2016 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Amy Seglund, Amy.Seglund@state.co.us ; All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. ABSTRACT Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) infestations have reached epidemic levels in Colorado, impacting approximately 4 million acres since the initial outbreak in 1996 (Figure 1). Though bark beetles are native to Colorado and periodic infestations are considered a natural ecological process, the geographic scale of their impact and simultaneous infestation within multiple forest systems has never been observed. This historic outbreak is having significant impacts on composition and structure of forest stands that will propagate for decades into the future, which in turn may have dramatic, but poorly understood effects on wildlife species that depend on these habitats. This project used occupancy estimation to determine statewide wildlife response to bark beetle outbreaks, as mediated by changes in forest structure. Surveys were conducted during the summers of 2013 and 2014. We randomly sampled 150 Engelmann spruce (Picea engelmanni)-subalpine fir (Abies lasiocarpa) sites and 150 sites consisting mostly of lodgepole pine (Pinus contorta) or lodgepole pine mixed with other conifers. For both strata, sampling covered conditions ranging from sites that were not impacted by bark beetles to those that were impacted by beetles more than a decade ago. At each 1-km2 site, we sampled the breeding bird community using the Rocky Mountain Bird Observatory’s protocol for “Integrated Monitoring in Bird Conservation Regions” (Hanni et al. 2014). We sampled the mammal community by deploying a remote camera near the center of each sample unit. Avian data have not yet been analyzed. We collected 388,951 photos of 56 species (26 mammalian species). Using Program MARK (White and Burnham 1999), we fit standard occupancy models (MacKenzie et al. 2006) to data for each species in the following manner. First, we fit a base model with parameters for the spruce-fir or lodgepole stratum, percentage of aspen present at the site, canopy cover, shrub cover, amount of down wood, amount of bare ground, and three physiographic variables that collectively account for elevation, moisture accumulation, and solar radiation at each site. The purpose of this model was to account for basic occupancy patterns of each species in the state irrespective of bark beetles. Next, we fit additional parameters to the base model which allowed occupancy to change in a variety of patterns (e.g., linear, quadratic, 3rd order polynomial, or change points when needles drop following an outbreak) in relation to time elapsed since a stand was initially impacted by beetles. We also explored whether there was any interaction between response to beetles and stratum or the severity of the outbreak (percent of trees that were killed). We used Akaike’s Information Criterion (Burnham and Anderson 2002) to assess fit of these various beetle response models, and model-averaged occupancy across the model set (i.e., ‘year since beetle outbreak’ was treated as a group such that parameters for each group could be averaged across all models in the set) to provide a best estimate of response of each species to beetles. Note that because we sampled mobile animals in a continuous landscape, ‘occupancy’ in this case refers to the probability that a species uses the forest stand which the camera was placed. 1 �Mean responses indicate that use of subalpine forest by elk (Figure 2) and mule deer (Figure 3) increased after stands were impacted by bark beetles (either through time or with increasing severity). Use by red squirrels (Figure 4) and coyotes (Figure 5) declined. Use by red fox (Figure 6) and black bears (Figure 7) was mixed as it increased through time after an outbreak, but may have declined with increasing severity. Snowshoe hares (Figure 9), and American martens (Figure 10) were largely unaffected by bark beetles in terms of their use of a stand as a function of beetle outbreaks. Both red squirrels and snowshoe hares used spruce-fir stands more heavily than lodgepole stands. Data from other species was too sparse to support fitting of the suite of models presented here. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Figure 1. Extent of mountain pine beetle (red) and spruce beetle (purple) infestations in spruce/fir (bluegreen) and lodgepole pine (bright green) forests in Colorado, 2014. Data were summarized from USFS Aerial Surveys. 2 �Figure 2. Elk occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas Dotted lines indicate 95% confidence intervals. Color bar indicates approximately when forest canopy changes from green to red (dead needles) to gray (no needles) following a bark beetle outbreak. Figure 3. Mule Deer occupancy occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. Figure 4. Red squirrel occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 3 �Figure 5. Coyote occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. Figure 6. Red Fox occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. Figure 7. Black bear occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 4 �Figure 8. Snowshoe Hare occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. Figure 9. American marten occupancy (use) of subalpine forest stands in relation to the number of years since initial infestation by bark beetles for lightly (left) and severely (right) impacted areas. 5 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Canada Lynx Monitoring in Colorado Period Covered: July 1, 2015  June 30, 2016 Principal Investigators: Eric Odell, Eric.Odell@state.co.us; Jake Ivan, Jake.Ivan@state.co.us; Scott Wait, Scott.Wait@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 19992006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that the population of Canada lynx in the state was apparently viable and self-sustaining. In order to track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is required. During 2014−2015 CPW initiated a portion of the statewide monitoring scheme described in Ivan (2013) by completing surveys in a random sample of monitoring units (n = 50) from the San Juan Mountains in southwest Colorado (n = 179 total units; Figure 1). During 2015−2016 personnel from CPW and USFS completed the second year of monitoring work on this same sample of 75-km2 units (approximate size of female home range). Specifically, 17 were sampled via snow tracking surveys conducted between December 1 and March 31. On each of 3 independent occasions, survey crews searched roadways (paved roads and logging roads) and trails for lynx tracks. Crews searched the maximum linear distance of roads possible within each survey unit given safety and logistical constraints. Each survey covered a minimum of 10 linear kilometers distributed across at least 2 quadrants of the unit. Two additional units were scheduled for snow track surveys but surveys were not completed due to poor conditions. The remaining 31 units could not be surveyed via snow tracking because they occurred in wilderness or were otherwise inaccessible. Survey crews deployed 4 passive infrared motion cameras in each of these units during fall 2015. Cameras were baited with visual attractants and scent lure to enhance detection of lynx living in the area. Cameras were retrieved during summer 2016 and all photos were archived and viewed by at least 2 observers to determine species present in each. Camera data were then binned such that each of 10 15-day periods from December 1 through April 30 was considered an ‘occasion,’ and any photo of a lynx obtained during a 15-day period was considered a detection during that occasion. Surveyors covered a total of 898 km during snow tracking surveys and detected lynx at 8 units (Table 1). They also collected 455 photos of lynx from 10 cameras in 7 camera units (Table 2). Resident lynx were documented in the La Garita Mountains north of Creede (Figure 1) for the second consecutive year, which is notable given that resident lynx were never observed in the La Garitas during the reintroduction work. Lynx were again detected in 2 units northeast of Wolf Creek Pass, an area that was used during the reintroduction but lacked lynx detections after the West Fork Fire of 2013. Similarly lynx were also detected in a unit southwest of Lizard Head Pass where they occurred during the reintroduction but had not been detected during the monitoring effort. Lynx were not documented near the New Mexico border where they had been detected for the first time during the 2014 effort. Also, an adult female with kittens was detected at cameras in a unit near Platoro Reservoir, thus documenting that at least some reproduction occurred in the study area. 6 �Using Program MARK (White and Burnham 1999), we fit standard occupancy models (MacKenzie et al. 2006) to our survey data to estimate the probability of a unit being occupied (or used) by lynx over the course of the winter. ‘Survey method’ was treated as a group so that we could, based on previous work, 1) allow detection probability (p) to vary by survey method and 2) include a breeding season effect for detection at cameras (lynx tend to move more in late winter when they begin to breed, and thus should encounter cameras more often). We also considered a suite of covariates that could potentially explain variation in occupancy () including proportion of the unit that was covered by spruce/fir forest, proportion covered by modeled lynx habitat (Ivan et al. 2011), average years since bark beetle infestation, variability (standard deviation) in years since bark beetle infestation, proportion of the unit impacted by bark beetles, proportion of the unit that was burned during Summer 2013, and the number of photos of other species that could potentially impact presence of lynx (e.g., snowshoe hares as a food source, coyotes as potential competitors). For the purposes of model-fitting, we included data from the pilot study (2010−2011) and the first (2014−2015) and second (2015−2016) years of implementation to maximize sharing of information across surveys. ‘Year’ was treated as a group variable in this case to obtain a separate occupancy estimate for each effort. We limited our model set by considering only combinations of two of these covariates on , in addition to the two covariates on detection. The best-fitting model characterized occupancy as a function of 2 covariates: the proportion of the sample unit covered by spruce-fir forest and the number of photos of hares recorded at camera stations (Appendix 1). In both cases, the association was positive, indicating that the probability of lynx use increased with more spruce-fir and more hares. Other covariates appear in top models with spruce-fir, but addition of these covariates did not improve AICc scores beyond the model with spruce-fir only (Appendix 1). This phenomenon indicates that these other variables were not as informative. Of these less informative variables, lynx occupancy was positively associated with the proportion of mapped lynx habitat in the unit, the proportion of the unit that had been impacted by spruce beetles, and the years since beetle impact, although coefficients for each of these effects partially overlapped zero, indicating that the strength of these associations was somewhat weak. There was no discernible association between lynx occupancy and number of photos of other species outside of hares. Detection probability was relatively high for snow tracking surveys (p = 0.56, 95% confidence interval: 0.440.67), and low for monthly camera surveys (p = 0.20, 95% confidence interval: 0.140.28) during DecemberFebruary and April, although detection increased to 0.41 (95% confidence interval: 0.270.57) during breeding season (March) as expected. For winter 2015−2016 we estimated that 29% of the sample units in the San Juans were occupied by lynx (95% confidence interval: 0.160.46). Occupancy estimates from the 2015−2016 monitoring effort were similar to those obtained during the first year of implementation and to those obtained during pilot research work in 2010−2011, although the sampling frame was different for the pilot work so results are not directly comparable (Figure 2). Note that during preliminary analyses of these data, we fit 2 new types of occupancy models that incorporate unexplained heterogeneity in detection probability among units, (i.e., mixture models and random effects as per Pledger 2000, McClintock and White 2009, Gimenez and Choquet 2010). That is, they acknowledge that the detection probability in each unit likely varies, and does so in ways that cannot be completely explained by covariates such as effort, conditions, breeding season, etc. According to AICc, the fit of these models was a strong improvement over the standard occupancy formulation, however occupancy estimates from these new models were ~0.55 and ~0.85, respectively, and some model parameters could not be estimated. These estimates seem unreasonably high, and the fact that some model parameters could not be estimated is troubling. Thus, we elected to continue reporting results from the standard approach. However, the fit of the new models does suggest unexplained heterogeneity in detection among the units in our survey, and because of this, estimates from the standard approach are likely biased low to some degree. 7 �LITERATURE CITED Gimenez, O., and R. Choquet. 2010. Individual heterogeneity in studies on marked animals using numerical integration: capture-recapture mixed models. Ecology 91:951–957. Ivan, J. S. 2013. Statewide Monitoring of Canada lynx in Colorado: Evaluation of Options. Pages 15–27 in Wildlife Research Report - Mammals. Colorado Parks and Wildlife., Fort Collins, CO, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx Ivan, J. S., M. Rice, P. M. Lukacs, T. M. Shenk, D. M. Theobald, and E. Odell. 2011. Predicted lynx habitat in Colorado. Pages 21–35 in Wildlife Research Report - Mammals. Colorado Parks and Wildlife, Fort Collins, CO, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. McClintock, B. T., and G. C. White. 2009. A less field-intensive robust design for estimating demographic parameters with mark-resight data. Ecology 90:313−320. Pledger, S. 2000. Unified maximum likelihood estimates for closed capture-recapture models using mixtures. Biometrics 56:434–442. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120–138. Table 1. Summary statistics from snow tracking effort. Season #Units Surveyed #Units with Lynx #Lynx Tracks #Genetic Samplesa Km Surveyed (Total) Mean Km Surveyed per Visit #CPW Personnel #USFS Personnel 2014−2015 18 7 12 8b 884 20.1 30 13 2015−2016 17 8 14 9c 898 21.4 23 6 a Number of genetic samples (scat or hair) collected via backtracking putative lynx tracks DNA analysis confirms that all samples collected from putative lynx tracks were lynx c DNA confirmation pending b Table 2. Summary statistics from camera effort. Season #Units Surveyed #Units with Lynx #Photos (Total) #Photos (Lynx) #Cameras with Lynx #CPW Personnel #USFS Personnel 2014−2015 32 8 134,694 301 14 46 12 2015−2016 31 7 101,534 455 10 33 9 8 �a) b) Figure 1. Lynx monitoring results for a) 2015−2016 and b) 2014−2015, San Juan Mountains, southwest Colorado. Colored units (n = 50) indicate those selected at random from the population of units (n = 179) encompassing lynx habitat in the San Juan Mountains. Blue units were surveyed via snow tracking; orange units were surveyed via deployment of four cameras per unit during winter months. Lynx were detected in 14 and 15 of the sampled units in 2014−2015 and 2015−2016, respectively. 9 �1.0 0.9 0.8 Occupancy 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 2009 2010 2011 2012 2013 2014 2015 2016 Figure 2. Model-averaged occupancy estimates and 95% Confidence Intervals for Canada lynx in the San Juan Mountains, southwest Colorado. ‘Year’ indicates when the efforts were initiated (2010−11 [pilot year], 2014−15, 2015−16). Appendix 1. Model selection results for lynx monitoring data collected in the San Juan Mountains, Colorado, 2015−2016. Rankings are based on Akaike’s Information Criterion adjusted for small sample size (AICc). Thirteen variables were considered as covariates to inform estimation of occupancy (). The complete model set (n = 77) included all combinations of two, in addition to modeling detection (p) as a function of survey method and breeding season. Only the best 10 models are shown. Model AICc ΔAICc AICcWts No. Par.  (Year + SpruceFir + SnowshoeHare)p(Method + Breeding) 527.2 0.0 0.54 8  (Year + SpruceFir)p(Method + Breeding) 531.1 3.9 0.08 7  (Year + SpruceFir + Coyote)p(Method + Breeding) 532.0 4.7 0.05 8  (Year + SpruceFir + Cougar)p(Method + Breeding) 532.6 5.3 0.04 8  (Year + SnowshoeHare + PropBeetleKill)p(Method + Breeding) 533.1 5.9 0.03 8  (Year + SpruceFir + Fox)p(Method + Breeding) 533.3 6.0 0.03 8  (Year + SpruceFir + Bobcat)p(Method + Breeding) 533.3 6.1 0.03 8  (Year + SpruceFir + PropBurn)p(Method + Breeding) 533.4 6.1 0.03 8  (Year + SpruceFir + YrSinceBeetle)p(Method + Breeding) 533.4 6.1 0.03 8  (Year + SpruceFir + PropBeetleKill)p(Method + Breeding) 533.4 6.1 0.03 8 10 �UNGULATE CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION EXAMINING THE EFFECTIVENESS OF MECHANICAL TREATMENTS AS A RESTORATION TECHNIQUE FOR MULE DEER HABITAT RESTORING ENERGY FIELDS FOR WILDLIFE EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO 11 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation Period Covered: July 1, 2015  June 30, 2016 Principal Investigator: Charles R. Anderson, Jr., Chuck.Anderson@state.co.us Collaborators: Colorado Parks and Wildlife, BLM-White River Field Office, Idaho State University, Colorado State University, Federal Aid in Wildlife Restoration, EnCana Corp., ExxonMobil Prod. Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, WPX Energy, Colorado Mule Deer Assn., Muley Fanatic Found., Colorado Mule Deer Found., Colorado State Severance Tax Fund, Boone & Crocket Club, and Safari Club Int. All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent the first 5 pretreatment years and 4 years post treatment of a long-term study addressing habitat improvements and evaluation of energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. We monitored 4 winter range study areas representing varying levels of development to serve as treatment (North Magnolia, South Magnolia) and control (North Ridge, Ryan Gulch) sites (Fig. 1) and recorded habitat use and movement patterns using GPS collars (≥5 location attempts/day), estimated neonatal and overwinter fawn and annual adult female survival, estimated early and late winter body condition of adult females using ultrasonography, and estimated abundance using helicopter mark-resight surveys. During this research segment, we targeted 240 fawns (60/study area) and 120 does (30/study area) in early December 2014 for VHF and GPS radiocollar attachment, respectively, and attempted recapture of 120 does and 40 fawns in March 2015 for late winter body condition assessment. Winter range habitat improvements completed spring 2013 resulted in 604 acres of mechanically treated pinionjuniper/mountain shrub habitats in each of the 2 treatment areas (Fig. 2) with minor and extensive energy development, respectively. Post-treatment monitoring will continue for 2 years to provide sufficient time to measure how vegetation and mule deer respond to these changes. Based on data collected prior to habitat improvements (i.e., pretreatment phase): (1) annual adult survival was consistent among areas averaging 79-87% annually, but overwinter fawn survival was variable, ranging from 48% to 95% within study areas, with annual and study area differences primarily due to early winter fawn condition and annual weather conditions; (2) migratory mule deer (Fig. 3) selected for areas with increased cover and increased their rate of travel through developed areas, and avoided negative influences through behavioral shifts in timing and rate of migration, but did not avoid development structures; (3) mule deer body condition was generally consistent within areas, with higher variability among study areas early winter, primarily due to December lactation rates, and late winter condition appeared related to seasonal moisture and winter severity; (4) mule deer exhibited behavioral 12 �plasticity in relation to energy development, where disturbance distance varied relative to diurnal extent and magnitude of development activity (Fig. 4), which may provide for several options in future development planning; (5) late winter mule deer densities have increased in all study areas (Fig. 5), averaging 76% in the low development areas and 80% in the high development areas since 2008; and (6) post treatment vegetation responses have provided evidence of improved forage conditions with improved winter fawn condition, but longer term monitoring will be required to address the full potential of habitat mitigation efforts. We will continue to collect population and habitat use data across all study sites to evaluate the effectiveness of habitat improvements on winter range. This approach will allow us to determine whether it is possible to effectively mitigate development impacts in highly developed areas, or whether it is better to allocate mitigation efforts toward less or non-impacted areas. In collaboration with Colorado State University, we are also monitoring neonate survival in relation to energy development from all study areas. This will allow us to include neonatal data to other demographic parameters for improved evaluation of mule deer/energy development interactions. Results from the neonate survival component of the project are currently being peer-reviewed and will be reported in next year’s annual report. The study is slated to run through 2018 to allow sufficient time for measuring mule deer population responses to landscape level manipulations. A more detailed version of this project summary and information about recent publications from this effort can be accessed at: http://cpw.state.co.us/Documents/Research/Mammals/Publications/AndersonPiceanceDeer_W185R14_ProgressReport_2014-15.pdf Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, winter 2013/14 (Accessed http://cogcc.state.co.us/ Dec. 31, 2013; energy development activity been minor since 2012). 13 �Figure 2. Habitat treatment site delineations in 2 mule deer study areas (604 acres each) of the Piceance Basin, northwest Colorado (Top; cyan polygons completed Jan. 2011 using hydro-axe; yellow polygons completed Jan. 2012 using hydro-axe, roller-chop, and chaining; and remaining polygons completed April 2013 using hydro-axe). January 2011 hydro-axe treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 14 �Figure 3. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012; http://dx.doi.org/10.1890/ES12-00165.1). 15 �Figure 4. Posterior distributions of population-level coefficients related to natural gas development for RSF models during the day (top) and night (bottom) for 53 adult female mule deer in the Piceance Basin, Northwest Colorado. Dashed line indicates 0 selection or avoidance (below the line) of the habitat features. ‘Drill’ and ‘Prod’ represent drilling and producing well pads, respectively. The numbers following ‘Drill’ or ‘Prod’ represent the distance from respective well pads evaluated (e.g., ‘Drill 600’ is the number of well pads with active drilling between 400–600 m from the deer location; from Northrup et al. 2015; http://onlinelibrary.wiley.com/doi/10.1111/gcb.13037/abstract). Road disturbance was relatively minor (~60 – 120 m, not illustrated above). Piceance Basin late winter mule deer density 35.00 30.00 Deer/km2 25.00 20.00 North Ridge 15.00 Ryan Gulch North Magnolia 10.00 South Magnolia 5.00 0.00 2009 2010 2011 2012 2013 2014 2015 2016 Year Figure 5. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2016. 16 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Examining the effectiveness of mechanical treatments as a restoration technique for mule deer habitat Period Covered: July 1, 2015 – July 30, 2016 Principal investigator: Danielle B. Johnston, Danielle.Bilyeu@state.co.us Collaborators: Colorado Parks and Wildlife, BLM-White River Field Office, Colorado State University, M. Paschke, ExxonMobil Prod. Co./XTO Energy All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. The pinyon-juniper (PJ) habitat type has been expanding in the western United States, and understory forage for big game may become reduced in areas where PJ has outcompeted more palatable species. Because prescribed fire is often difficult to implement, managers often rely on mechanical tree removal methods such as ship anchor chaining, roller chopping, and mastication. These methods differ in cost, type of woody debris produced, and soil disturbance (Johnston 2014). We made head-to-head comparisons of understory vegetation changes due to chaining, rollerchopping, and mastication (Figure 1), and also examined how each treatment impacted the success of seeding desirable understory forage species. Half of each treated plot was seeded with a shrub-heavy seed mix including chokecherry (Prunus virginiana), Saskatoon serviceberry (Amelanchier alnifolia), Utah serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), and winterfat (Kraschenninnikovia lanata). The study was conducted at two sites in the Magnolia region of the Piceance Basin, Rio Blanco County, Colorado. The North Magnolia site (n = 4) had higher control plot tree density, lower tree basal area, and higher shrub cover than the South Magnolia site (n = 3). Treatments were implemented in fall 2011, and understory vegetation data (cover, biomass, and shrub density) was collected in 2012 and 2013 through collaboration with Colorado State University. Site visits in 2014 and 2015 indicated significant changes from this initial assessment period, particularly in the cover of cheatgrass (Bromus tectorum), an invasive annual grass that reduces wildlife habitat quality. Understory vegetation cover was assessed in July 2016 using about 300 point-intercept hits (arrayed over 13 transects) in each plot. Five years post-treatment, differences in understory vegetation due to type of mechanical treatment were minimal, but all treated plots differed greatly from controls. Treated plots had 3-5 times higher perennial grass cover than control plots, with bottlebrush squirreltail (Elymus elymoides), Indian ricegrass (Achnatherum hymenoides), and western wheatgrass (Pascopyrum smithii) dominating (Figure 2). In addition, treatment plots had about 10 times higher cheatgrass cover than control plots (Figure 3). Cheatgrass had been present at only 1-3% cover in the 2013 data (Stephens et al. 2016), and was practically undetectable at the South Magnolia site. By 2016, cheatgrass cover in treated plots was about 27% at North Magnolia and about 7% at South Magnolia. Differences in shrub cover were apparent at North Magnolia only (Figure 4), with chaining and mastication producing higher shrub cover than the control. Much of this increase was due to snowberry (Symphoricarpos rotundifolius; Figure 4), which is not a preferred forage species in the study area. A companion study in nearby locations quantified both cover and forage biomass in response to mastication for preferred species including serviceberry, bitterbrush, and mountain mahogany. Although cover 217 �years post-treatment did not differ, forage biomass increased nearly 2-fold in masticated plots. It is reasonable to conclude that forage biomass of preferred species was also higher in treated versus control plots in this study. Even so, a shift in dominance towards snowberry with mechanical treatment is a possible negative consequence which should be noted. Seeding had effects only on forb cover and cheatgrass cover five years post-treatment. In the absence of seeding, forb cover was similar between treated and control plots, but within treated plots, seeding increased forb cover from 2.4% to 5.4% at South Magnolia and from 3.5% to 7.9% at North Magnolia (p < 0.006). Utah sweetvetch (Hedysarum boreale) accounted for most of the difference, followed by Lewis flax (Linum lewisii). Again, results were similar among each of the three mechanical treatment types. Seeding had no effect on cheatgrass at North Magnolia, but at South Magnolia, cheatgrass cover was 2-3 times higher in seeded subplots within chained (p < 0.01) and rollerchopped (p < 0.008) plots. We suspect cheatgrass contamination in the seed that was used. This was not apparent in our earlier analysis. Apparently, seed contamination may cause problems which take several years to manifest. We urge practitioners to be cautious when applying seed, especially in areas previously free of cheatgrass. Seeding did not affect grass or total shrub cover 5 years post-treatment. In the earlier analysis, we found an effect of seeding on density of seeded shrubs at South Magnolia, due largely to bitterbrush. In the 2016 data, we looked at bitterbrush cover specifically, and found that seeding had an effect across sites, increasing it from 2.9% to 3.8% (p = 0.04). Again, there was no difference among mechanical treatment types. The seed mix used was very expensive, about $714/ac. If we had seeded only the species which actually responded (bitterbrush, Utah sweetvetch, and Lewis flax), the price would have been $173/ac. Obviously, it is important to choose species judiciously and to limit seeding only to those sites lacking in a desirable plant type. Utah sweetvetch is a species which has performed well at many research sites in northwest Colorado (Johnston 2016). In the treatments which used bulldozers, chaining and rollerchopping, we planted large-seeded species with a Hansen dribbler (Johnston 2014). This tool dribbles the seed onto the track and facilitates deep planting. Bitterbrush and Utah sweetvetch were both planted this way, and it is interesting to note that bitterbrush established as well in the rollerchop and chaining treatments as it did in the mastication treatment. In the mastication treatment, all species were broadcast-seeding prior to treatment, which required more effort. The dribbler seems to be a useful tool to plant large-seeded species efficiently. We found little difference in understory cover in 2016 with mechanical treatment type in our study area. This differed somewhat from analysis of 2012-2013 data, which found that undesirable nonnatives were somewhat worse with rollerchopping, and native annuals established best with mastication (Stephens et al. 2016). While more years of sampling would be desirable, it seems that the differences in vegetation response are sufficiently small that the choice of mechanical treatment type should be dictated by other factors in this study area. Among these factors are per-acre cost, mobilization cost, and the ability to create the desired spatial arrangement of treatment patches. More detailed mosaics are possible with mastication than with rollerchopping, and chaining is the least flexible. We used a shorter-than-typical 50-foot smooth chain in our study, which could be a viable and cost-effective option for creating small treatment patches. However, it is not possible to leave isolated trees with chaining. Chaining costs are one-third to one-sixth that of mastication, with rollerchopping having intermediate costs. More detailed cost information is available in a prior report (Johnston 2014). The increase in cheatgrass with all three treatment types, at both study sites, is somewhat alarming. Recent research has shown that cheatgrass is adapting to higher elevation sites (Merrill et al. 2012), therefore problems with cheatgrass can be expected to worsen. Nevertheless, the substantial amount of perennial grass cover at these sites should prevent cheatgrass from dominating. Wildlife benefits are still possible with PJ removal if enough understory vegetation is present to respond (Miller et al. 2005), but practitioners should consider potential risks as well as benefits when selecting projects (Figure 5). 18 �plotcover SUM 50 40 M 50 30 40 20 30 10 20 10 Figure 1. Looking west from Rio Blanco CR 76 to treatment plots in North Magnolia in fall of 2012. The three rectangular patches in the left, along with a control plot, comprise one of 4 experimental blocks at this site. 0Each treatment plot received either chaining, mastication, or rollerchopping, and half of each CHAIN CONTROL HYDRO ROLLER CHAIN HYDRO MECHANICAL treated plot was seeded with a shrub-heavy seed CONTROL mix. Plot sizeROLLER is about 2 acres. TREATMENT NORTH MAGNOLIA plotcover SUM SOUTH MAGNOLIA SITE 50 CommonName Basin wild rye Bearded bluebunch wheatgrass a Blue Gramma Bluebunch wheatgrass a Bottlebrush squirreltail Indian ricegrass Kentucky Bluegrass Needle and Thread CHAIN CONTROL HYDRO ROLLER CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT Prairie Junegrass Sandburg Bluegrass Slender wheatgrass Western wheatgrass NORTH MAGNOLIA SOUTH MAGNOLIA SITE 40 foxtail barley muttongrass Basin wild rye Bearded bluebunch wheatgrass CommonName Blue Gramma Bluebunch wheatgrass Bottlebrush squirreltail Indian ricegrass Kentucky Bluegrass Needle and Thread Prairie Junegrass Sandburg Bluegrass 30 Slender wheatgrass Western wheatgrass foxtail barley muttongrass Cover (%) 0 a a a a 20 b 10 b 0 CHAIN CONTROL HYDRO ROLLER NORTH MAGNOLIA CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT SOUTH MAGNOLIA SITE Basin wild rye Bearded bluebunch wheatgrass CommonName Figure 2. Cover of perennial grasses in response toGramma chaining (CHAIN), mastication (HYDRO), Blue Bluebunch wheatgrassand Bottlebrush squirreltail Indian ricegrass rollerchopping (ROLLER) at two sites, North Magnolia and South Magnolia. Letters indicate Bluegrass Needle and Thread significantly different means among treatmentsKentucky at α Junegrass = 0.05 (Sites considered separately). Seeding had no Prairie Sandburg Bluegrass Slender wheatgrass Western wheatgrass effect on perennial grasses. foxtail barley 19 muttongrass �0 CHAIN CONTROL HYDRO ROLLER CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT plotcover SUM NORTH MAGNOLIA 40 SOUTH MAGNOLIA Cheatgrass CommonName a SITE Japanese Brome a Cover (%) 30 a 20 plotcover SUM 50 50 40 b a plotcover SUM 50 b ab 10 plotcover SUM 40 c 30 0 CHAIN CONTROL HYDRO ROLLER 40 30NORTH MAGNOLIA CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT SOUTH MAGNOLIA 20 Cheatgrass CommonName SITE Japanese Brome Figure 3. Cover of annual grasses in response to chaining (CHAIN), mastication (HYDRO), and rollerchopping30(ROLLER) at two sites, North Magnolia 10and South Magnolia. Letters indicate 20 significantly different means among treatments at α = 0.05 (Sites considered separately). 20 10 0 plotcover SUM CHAIN CONTROL HYDRO ROLLER 50 NORTH MAGNOLIA 10 0 CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT SOUTH MAGNOLIA SITE Big Sagebrush Bitterbrush Greasewood Green Rabbitbrush CHAIN CONTROL HYDRO ROLLER CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT Rubber Rabbitbrush Rubber rabbitbrush Snowberry NORTH MAGNOLIA SOUTH MAGNOLIA SITE Spineless Horsebrush 40 longflower rabbitbrush white sagebrush 0 Big Sagebrush Bitterbrush Broom snakeweed CommonName Greasewood Green Rabbitbrush Oregon grape CHAIN CONTROL HYDRO ROLLER CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT Rubber Rabbitbrush Rubber rabbitbrush Serviceberry Snowberry Spineless Horsebrush alderleaf mountain mahogany NORTH MAGNOLIA SOUTH MAGNOLIA SITE longflower rabbitbrush white sagebrush Big Sagebrush Bitterbrush Broom snakeweed CommonName 30 Greasewood Green Rabbitbrush Oregon grape Rubber Rabbitbrush Rubber rabbitbrush Serviceberry Snowberry Spineless Horsebrush alderleaf mountain mahogany longflower rabbitbrush white sagebrush CommonName a Broom snakeweed Oregon grape Serviceberry alderleaf mountain mahogany ac Cover (%) bc b 20 10 0 CHAIN CONTROL HYDRO ROLLER NORTH MAGNOLIA CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT SOUTH MAGNOLIA SITE Big to Sagebrush Bitterbrush snakeweed Cover ofCommonName shrubs in response chaining (CHAIN), mastication (HYDRO), andBroom rollerchopping Figure 4. Greasewood Green Rabbitbrush Oregon grape (ROLLER) at two sites, North Magnolia South Magnolia. Rubber Letters indicate significantly different Rubberand Rabbitbrush rabbitbrush Serviceberry Spineless Horsebrush mountain mahogany means among treatments at α = 0.05 Snowberry (Sites considered separately). Seeding had no effectalderleaf on total shrub longflower rabbitbrush white sagebrush cover. 20 �Figure 5. A photo collage of sites where PJ was removed at the North Magnolia site shows good perennial grass and shrub cover, but also reveals some undesirable cheatgrass patches. LITERATURE CITED Johnston, D. B. 2014. Examining the effectiveness of mechanical treatments as a restoration technique for mule deer habitat: Colorado Division of Parks and Wildlife Avian Research Program annual progress report, Colorado Parks and Wildlife, Fort Collins, CO. Johnston, D. B. 2016. Restoring Energy Fields for Wildlife: Colorado Division of Parks and Wildlife Avian Research Program annual progress report. Colorado Parks and Wildlife, Fort Collins, CO. Merrill, K. R., S. E. Meyer, and C. E. Coleman. 2012. Population genetic analysis of Bromus tectorum (Poaceae) indicates recent range expansion may be facilitated by specialist genotypes. American Journal of Botany 99:529-537. Miller, R. F., J. D. Bates, T. J. Svejcar, F. B. Pierson, and L. E. Eddleman. 2005. Biology, ecology, and management of western juniper (Juniperus occidentalis). Oregon State University Agricultural Experiment Station. Stephens, G. J., D. B. Johnston, J. L. Jonas, and M. W. Paschke. 2016. Understory responses to mechanical treatment of pinyon-juniper in northwestern Colorado. Rangeland Ecology & Management 69:351-359. 21 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Restoring energy fields for wildlife Period Covered: January 16, 2013 – June 30, 2016 Principal Investigator: Danielle B. Johnston, Danielle.Bilyeu@state.co.us Collaborators: Colorado Parks and Wildlife, BLM-White River Field Office, BLM- Colorado River Valley Field Office, Colorado State University, Phillip L. Chapman, EnCana Corp., ExxonMobil Prod. Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, WPX Energy All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Healthy sagebrush-steppe areas of western Colorado are characterized by a diverse mixture of shrubs, forbs, and grasses. Restoring such habitats following oil and gas disturbances is often difficult because of the variety of impacted precipitation zones and the threat of weed invasion. An area of particular concern is the Piceance Basin gas field because of its value to mule deer (Odocoileus hemionus), greater sage-grouse (Centrocercus urophasianus), and other wildlife. In 2008, 2009, and 2012, a series of six experiments was implemented on simulated well pads and pipelines covering the wide range of precipitation and ecological conditions represented in the Piceance Basin gas field. The experiments conducted at lower elevations emphasize weed control, particularly that of cheatgrass (Bromus tectorum), which presents a serious obstacle to effective reclamation (Knapp 1996, Chambers et al. 2007, Reisner et al. 2013). The four lower elevation experiments are the Pipeline experiment (implemented at six sites ranging from 1561 to 2216 m in elevation), the Competition and Competition 2 Experiments (implemented at two sites of elevations 2004 and 2216 m), and the Gulley experiment (implemented at four sites ranging from 1561 to 2084 m in elevation). The remaining two experiments, conducted at high or middle elevations, emphasized maximizing plant diversity. The Mountain Top experiment was implemented at the four highest elevation sites, ranging from 2342 to 2676 m. The Strategy Choice experiment was implemented at four moderate elevation sites ranging from 1662 to 2216 m. Sites were prepared in 2008 by simulating pipeline disturbances and well pad disturbances. These two disturbance types differ in the length of time topsoil is stored, an important variable for restoration. The Pipeline Experiment was implemented in 2008, three weeks after the disturbances. All other experiments were implemented on well pad disturbances. These experiments were implemented in 2009 immediately after the well pads were reclaimed, except for the Competition 2 Experiment, which was implemented in 2012. Results and analysis for at least 3 post-treatment years for all experiments is now available, either within this report or via the included links to publications. Although the complexity of elevation, soil type, and prior land use history make finding general recommendations for improving restoration for wildlife challenging, a general theme did emerge over the seven years these six experiments have been studied. This general theme is the importance of controlling weed seed propagule pressure. Propagule pressure is the number of weed seeds per area per unit of time. Even the experiments that were not explicitly designed to address propagule pressure ultimately provided lessons about its importance, and what we can do about controlling it. This corroborates research in other ecosystems which has demonstrated that controlling propagule pressure is more important than other factors managers might try to influence, such species diversity, herbivory, or abiotic conditions (Von Holle and Simberloff 2005, Eschtruth and Battles 2009). 22 �In the Pipeline Experiment, we learned that in limited circumstances, pipeline disturbances can reduce cheatgrass density compared to unimpacted areas (Johnston 2015). When combined with Plateau ® (ammonium salt of imazapic) herbicide, enough cheatgrass control can be achieved to allow establishment of big sagebrush (Artemisia tridentata). While Plateau is a useful herbicide, using it alone is sometimes ineffective because applying it at high enough rates to get sufficient cheatgrass control results in unacceptable injury to desirable plants (Owen et al. 2011). By causing cheatgrass seeds to be buried too deeply to germinate, ground disturbances can work additively with herbicides to reduce cheatgrass propagule pressure. The timing of the disturbance is important. We quantified the seasonality of cheatgrass propagule pressure using seed traps (Appendix 1). Most cheatgrass seeds arrive between May and June, but seeds continued to arrive until September. The disturbances in the Pipeline Experiment occurred in September, which maximized burial of seeds from the prior growing season. A disturbance earlier in the growing season may not be as helpful for limiting cheatgrass. May June July August Sept. Figure 1. Propagule pressure of cheatgrass seeds between May and September in undisturbed locations near 6 sites: GVM, RYG, SKH, WRR, YC1, and YC2, which varied in elevation from 1561- 2216 m (5120-7268 ft.) and cheatgrass cover from 0% to 70%. Data are averages over 3 years, 2009-11 In the Competition and Competition 2 Experiments, cheatgrass propagule pressure was intentionally controlled in order to look for other factors that may limit cheatgrass during restoration. These experiments had mixed results. We focused on abiotic manipulations which might exploit cheatgrass’s weaknesses: lower competitive ability under higher, more stable soil moisture (Chambers et al. 2007, Bradley 2009), and inability to germinate through compacted soils (Thill et al. 1979, Beckstead and Augspurger 2004). In the Competition Experiment, the treatments were super-absorbent polymer (SAP) application (to increase water retention), a soil binding agent designed to increase water infiltration (DirtGlue ®), and compaction with a heavy roller. Rolling was not helpful. SAP increased initial perennial grass density and reduced subsequent cheatgrass cover at one of two sites, and the binding agent increased perennial grass density and reduced cheatgrass cover at one of two sites. Because the binding agent application was more expensive, the Competition 2 Experiment focused on SAP. In Competition 2, SAP had beneficial effects at one site (increasing perennial grass cover and reducing cheatgrass), but detrimental effects at the other site, causing a five-fold increase in cheatgrass. The limitations on cheatgrass germination and the nature of competitive interactions between cheatgrass and desirable perennial plants appears to be a complex interaction of site conditions, treatment timing, and treatment choice. Right now, clear management recommendations on how to use SAP or binding agent are not available, although this may be improved through further study. 23 �The Gulley Experiment focused on identifying which sources of propagule pressure are important to control: the seed bank, new seeds entering from the surrounding landscape, or both. The treatments were application of Plateau herbicide at 140 g ai/ha (8 oz/ac) just prior to seeding, fallowing for one year with the broad-spectrum pre-emergent herbicide Pendulum™ (pendamethilin, BASF Corporation), and surrounding plots with seed dispersal barriers of aluminum window screen. The barriers had slight effects which were entirely positive: lower annual forb cover at some sites where Russian thistle (Salsola tragus) was dominant, and higher perennial grass and forb cover. The herbicide treatments were a lesson in the dangers of over application. The pendamethilin treatment was especially detrimental. Both herbicides in combination so suppressed perennial vegetation that by four years post-treatment, there was a trend for higher cheatgrass cover where both had been applied, in spite of both herbicides effectively controlling cheatgrass in the initial years of the experiment. The barriers did not reduce cheatgrass cover, possibly because cheatgrass seeds passed under the barriers or blew over them. The Mountain Top and Strategy Choice Experiments examined a treatment that had more success at reducing cheatgrass cover. The Mountain Top Experiment was initially designed to address how to maximize plant diversity in restoration. This is critical because restored areas are often dominated by grasses, even after decades of recovery. Unexpectedly, this experiment also demonstrated that high elevation sites in Piceance are vulnerable to cheatgrass invasion, and revealed a useful technique for combating that invasion. The treatments were: seeding (17.8 kg/ha PLS native species including 60% grass or no seed), soil surface (roughened with 50 cm-deep holes or flat), and brush mulch replacement (0.024 m3/m2 or no brush). Unseeded plots were initially dominated by annual forbs, while seeded plots were dominated by perennial grasses. After five years, unseeded plot annual forb cover had declined to 10%, perennial grass cover had increased to 24% (about two-thirds of that of seeded plots), and perennial forb cover was 6.8% (about one-third that of seeded plots). Cover of shrubs (mostly big sagebrush, Artemisia tridentata) in unseeded plots was 26% (almost double that of seeded plots), highlighting the degree to which competition by seeded species can slow the recovery of sagebrush. Brush mulch benefitted shrubs, perennial grasses, and perennial forbs, and also slightly reduced annual forbs. Contrary to expectations, the rough soil surface did not have any large effects on cover of perennial grasses, forbs, or shrubs, but it did have an effect on cheatgrass. By five years post-treatment, cheatgrass had become established in unseeded plots at two sites, especially Scandard. At Scandard, the rough surface reduced unseeded plot cheatgrass cover from 13% to 3% (Figure MountainTop 5). We hypothesize that cheatgrass seeds become entrapped in the bottom of holes, limiting their spatial distribution, and forcing them to compete under wetter conditions under which they are less competitive. Cover (%) 20 * 15 Flat 10 Rough * * 5 0 2011 2012 2013 2014 Figure 2. Percent cover of annual grass (Bromus tectorum) in response to a rough versus flat soil surface in unseeded plots at Scandard Ridge 2-5 years post-disturbance. Error bars are SE. Stars denote significant differences at α = 0.05. 24 �The Strategy Choice Experiment also included a rough vs. flat soil surface treatment, although in this experiment the rough surface was always applied with brush (and broadcast seeded), while the flat surface was always applied with straw mulch (and primarily drill-seeded). The Strategy Choice Experiment was conducted at middle elevations where the threat of weed invasion was moderate or ambiguous, in order to find optimal strategies in uncertain circumstances. The other treatments included Plateau (8 oz/ac vs. none) and a seed mix treatment. There were two seed mixes compared: one that had about equal numbers of forb, shrub, and grass seeds, and one that was about 75% forbs, 17% shrubs, and only 8% grass. Cheatgrass established at two of the four sites, one each with high (GVM) and low (MTN) cheatgrass propagule pressure. The Plateau treatment successfully controlled cheatgrass, but caused an increase in annual forbs, and had either neutral or negative effects on perennials. At GVM, the rough surface augmented the effect of Plateau, reducing cheatgrass biomass six-fold. At MTN, the rough surface reduced cheatgrass biomass 10-fold in the absence of Plateau and reduced weedy annual forbs 100-fold in the presence of Plateau. Across sites, there was no difference in cheatgrass due to seed mix, and forb and shrub biomass were higher with the high-forb mix. Looking across the Mountain Top and Strategy Choice experiments, the rough surface helped control cheatgrass at three of four sites where cheatgrass became established. The one site where it had no effect, the Sprague site in Mountain Top, had only sparse and patchy cheatgrass. As an extension of this project, we implemented a rough surface treatment along with a light (4 oz/ac) Plateau application to 7 acres at Horsethief SWA, and successfully turned a cheatgrass near-monoculture into a diverse stand of grasses, forbs, and shrubs (Johnston 2014). Weedy species, almost by definition, produce large numbers of rapidly dispersing seeds to quickly exploit any open or disturbed areas. From prior research we know that holes entrap many kinds of seeds (Chambers 2000), and that cheatgrass seeds disperse 10 to 50-fold farther over bare soils than in intact ecosystems (Kelrick 1991, Johnston 2011, Monty et al. 2013). Our research supports the conclusion that landscapes which permit rapid seed dispersal foster weeds; landscapes which slow seed dispersal favor less weedy species. Altered seed dispersal is one reason why cheatgrass responds so well to fire. Even though a fire may kill 97% of cheatgrass seeds (Humphrey and Schupp 2001), fire also removes vegetation, which allows cheatgrass seeds to travel farther (Monty et al. 2013). The few surviving seeds grow in the absence of competition, which enables them to produce 40 times more seed than they might have within a dense stand (Hulbert 1955). These seeds disperse readily over the burned surface, producing a second generation of plants which are also relatively free from competition. By two years after the fire, cheatgrass is fully recovered from the 97% reduction (Humphrey and Schupp 2001). A rough soil surface can entrap seeds near the parent plant, preventing the growth of isolated, highly productive cheatgrass plants. This may slow the cheatgrass recovery cycle enough for perennial plants to establish. A rough soil surface is a practical tool managers can use to limit cheatgrass and other weedy invasives after disturbances including fire and development. The two experiments which addressed seeding practices demonstrate the costs of including too much grass seed in seed mixes: forb and shrub growth is delayed. Including at least a little grass in seed mixes is probably wise, as research has shown that the best competitors for invasive species are native species of the same functional group (i.e. grasses compete best with grass, and forbs with forbs; Fargione et al. 2003). Even so, the high-forb seed mix performed well at the GVM site, which had high cheatgrass propagule pressure. The recent investments made by CPW through the Uncompagre Project to make additional forb species available at low cost are critical, and additional resources should be devoted to this task. Results of Plateau application in this series of experiments are mixed, generating beneficial results in one experiment (Pipeline), mixed results in another experiment (Gulley), and largely detrimental results a third experiment (Strategy Choice). Successful use of this herbicide requires accurately applying a light rate, focusing on areas with cheatgrass cover prior to disturbance, and combining Plateau with other measures to reduce cheatgrass propagule pressure, such as a rough soil surface or a well-timed ground disturbance. 25 �Restoring oil and gas disturbances to fully functional, diverse wildlife habitat in northwestern Colorado is possible. Making use of a higher proportion of forbs and shrubs in seed mixes, considering the timing of weed seed dispersal, combining herbicides with other factors to reduce weed propagule pressure, and seeding over a rough soil surface are strategies which can be used over a wide range of elevations and ecological conditions to the benefit of wildlife. LITERATURE CITED Beckstead, J., and C. K. Augspurger. 2004. An experimental test of resistance to cheatgrass invasion: limiting resources at different life stages. Biological Invasions 6:417-432. Chambers, J. C. 2000. Seed movements and seedling fates in disturbed sagebrush steppe ecosystems: implications for restoration. Ecological Applications 10:1400-1413. Chambers, J. C., B. A. Roundy, R. R. Blank, S. E. Meyer, and A. Whittaker. 2007. What makes Great Basin sagebrush ecosystems invasible by Bromus tectorum? Ecological Monographs 77:117-145. Eschtruth, A. K., and J. J. Battles. 2009. Assessing the relative importance of disturbance, herbivory, diversity, and propagule pressure in exotic plant invasion. Ecological Monographs 79:265-280. Fargione, J., C. S. Brown, and D. Tilman. 2003. Community assembly and invasion: An experimental test of neutral versus niche processes. Proceedings of the National Academy of Sciences of the United States of America 100:8916-8920. Hulbert, L. C. 1955. Ecological studies of Bromus tectorum and other annual bromegrasses. Ecological Monographs 25:181-213. Humphrey, L. D., and E. W. Schupp. 2001. Seed banks of Bromus tectorum-dominated communities in the Great Basin. Western North American Naturalist 61:85-92. Johnston, D. B. 2011. Movement of weed seeds in reclamation areas. Restoration Ecology 19:446-449. Johnston, D. B. 2014. Rangeland restoration with super-absorbent polymer and potholed surface at Horsetheif State Wildlife Area: Colorado Division of Parks and Wildlife Avian Research Program annual progress report http://cpw.state.co.us/Documents/Research/Habitat/2014-Annual-Reoprt-RangelandRestoration.pdf. Johnston, D. B. 2015. Downy brome (Bromus tectorum) control for pipeline restoration. Invasive Plant Science and Management 8:181-192. Johnston, D. B., and P. L. Chapman. 2014. Rough surface and high-forb seed mix promote ecological restoration of simulated well pads. Invasive Plant Science and Management 7:408-424. Kelrick, M. 1991. Factors affecting seeds in a sagebrush-steppe ecosystem and implications for the dispersion of an annual plant species, cheatgrass (Bromus tectorum L.). Utah State University, Logan, UT. Monty, A., C. S. Brown, and D. B. Johnston. 2013. Fire promotes downy brome (B. tectorum) seed dispersal. Biological Invasions 15:1113-1123. Owen, S. M., C. H. Sieg, and C. A. Gehring. 2011. Rehabilitating Downy Brome (Bromus tectorum)Invaded Shrublands Using Imazapic and Seeding with Native Shrubs. Invasive Plant Science and Management 4:223-233. Reisner, M. D., J. B. Grace, D. A. Pyke, and P. S. Doescher. 2013. Conditions favouring Bromus tectorum dominance of endangered sagebrush steppe ecosystems. Journal of Applied Ecology 50:1039-1049. Thill, D. C., R. D. Schirman, and A. P. Appleby. 1979. Influence of soil-moisture, temperature, and compaction on the germination and emergence of downy brome (Bromus tectorum). Weed Science 27:625-630. Von Holle, B., and D. Simberloff. 2005. Ecological resistance to biological invasion overwhelmed by propagule pressure. Ecology 86:3212-3218. 26 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation and incorporation of life history traits, nutritional status, and browse characteristics in Shira’s moose management in Colorado Period Covered: July 1, 2015  June 30, 2016 Principal Investigator: Eric J. Bergman, eric.bergman@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. During November of 2013 we initiated a large scale moose research project in 3 of Colorado Parks and Wildlife’s 4 geographical regions. This project was continued into the 2015–2016 fiscal year. A primary objective during all years of this project has been the capture of adult female moose for the purposes of deploying VHF and GPS collars, collecting pregnancy data via blood serum, evaluating body condition via ultrasonography, evaluating body condition via blood thyroid hormone concentrations, and collecting early winter calf-at-heel ratios. During the FY 2014-2015 and FY 2015-2016, field efforts were expanded to include estimation of parturition rates. During the third year of the study, all captures occurred during late December (2015) and were focused in 3 study areas in—along the Laramie River (NE Colorado), southern North Park and the Williams Fork drainage (NW Colorado), and near the community of Creede and near the Rio Grande Reservoir (SW Colorado). During the third year of the study 42 cow moose were captured and collared. Of these 42 animals, 25 were recaptures of animals that had been captured during previous winters of the study. Eleven of these recaptures occurred along the Laramie River (NE Colorado), and 14 recaptures occurred in North Park and along the Williams Fork River (NW Colorado). No recaptures occurred in southwest Colorado during FY 2015-2016, although capture efforts in this region were concentrated in areas where no collars had previously been deployed. Individual animals were recaptured to meet 2 objectives. First, many animals wore GPS collars that stored location data within the collar. Those data could not be retrieved without retrieving the collar. These animals were subsequently re-collared with satellite collars that are now capable of transmitting location data. The second objective was to establish a longitudinal data set that will allow us to determine long-term productivity of individual animals. In particular, repeated measurements of individuals will allow us to evaluate if different reproductive strategies occur within moose, and if those strategies can be linked to annual variation within individual condition. Annual adult female moose survival rates for each study area were calculated for the 12-month period ending in mid-May. During May, June, and July of 2016, parturition and twinning rates were also estimated for all 3 study areas. Measured rump fat at the time of capture (December 2015) ranged between 0–31 mm among study areas. Measured loin depth at the time of capture ranged between 29–58 mm among study areas. Measured loin fat, at the time of capture, ranged between 0–36mm. When data from 2013–2016 were pooled, pregnancy status was best predicted by the additive model of maximum rump fat plus the number of calves-at-heel. However, no regional or annual effects in pregnancy rates were detected. As has been the case during all years of the study, survival of radio collared animals was high in all study areas (85%– 96%). During 2015–2016 pregnancy rates ranged between 70%–95%. In comparison to previous years, lower pregnancy rates were observed during 2015–2016 in southwest Colorado, although these lower rates are believed to be associated with a younger age class of animals being captured (multiple yearling females in sample). Compared to previous winters, higher pregnancy rates were observed in northeast 27 �Colorado during 2015–2016. During 2015–2016, observed twinning rates at the time of parturition were low in northeast and northwest Colorado (0%), but high in southwest Colorado (33%). Thus far, data collected during this project have met expectations. In particular, survival rates have been consistently high in all study areas. Lower reproductive rates previously observed in the northeast herd were more similar to other herds during 2015–2016. During future years, we will investigate opportunities to evaluate moose browse selection behavior. Likewise, we will begin investigations for determining herd level pregnancy status in cost effective ways. Figure 1. Moose research study areas, located in 3 regions in Colorado. A total of 43 moose were captured during the winter of 2015–2016. Survival of moose was high in all study areas and during both years. 28 �1 0.8 0.6 0.4 0.2 0 2013-2014 2014-2015 2015-2016 Figure 2. Pregnancy data were collected for all moose at the time of capture. Data from northeast Colorado are depicted by black bars, data from northwest Colorado are depicted by gray bars, and data from southwest Colorado are depicted by white bars. 1 Probability of Being Pregnant 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1 3 5 7 9 11 13 15 17 19 21 Measured Rump Fat (mm) 23 25 27 29 31 Figure 3. Probability of moose pregnancy was best predicted by maximum measured rump fat. This strong relationship between body condition and pregnancy status reflects how nutritional condition can influence pregnancy, with animals in the poorest condition having lower probabilities of breeding. 29 �PREDATORY MAMMAL CONSERVATION BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS MOUNTAIN LION POPULATION RESPONSES TO SPORT-HUNTING ON THE UNCOMPAHGRE PLATEAU, COLORADO COUGAR AND BEAR DEMOGRAPHICS AND HUMAN INTERACTIONS IN COLORADO 30 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2015  June 30, 2016 Principal Investigator: Heather E. Johnson, Heather.Johnson@state.co.us Project Collaborators: S.A. Lischka, S. Breck, J. Beckmann, J. Apker, K. Wilson, and P. Dorsey All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a collaborative study involving Colorado Parks and Wildlife (CPW; lead agency), the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have designed and implemented a study on black bears that 1) determines the influence of urban environments on bear behavior and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. This project was initiated in FY2010-11; during this past fiscal year we focused on collecting field data in the vicinity of Durango and modeling demographic parameters from known-fate and markrecapture data. With respect to data collection, we worked with collaborators and stakeholders on research logistics, trapped and marked black bears, monitored bear demographic rates through telemetry and winter den visits, tracked human-related bear mortalities and removals from the study area, collected GPS collar location data from bears along the urban-wildland interface, monitored the availability of summer/fall mast, obtained data on garbage-related bear-human conflicts, assessed resident use of project-supplied bear-resistant containers, and surveyed residents about their attitudes and behaviors with respect to bears. Information from this study will provide solutions for sustainably managing black bears outside urban environments, while reducing bear-human conflicts within urban environments; knowledge that is critical for wildlife managers in Colorado and across the country. Major research accomplishments from fiscal year 2015-16:  Between 5 July 2015 and 23 March 2016 (the 2015-2016 capture year), an additional 54 unique bears were marked during 136 bear captures. To date on the project there have been 380 different individuals marked during 891 captures. Five new adult females were collared during summer 2015 (83 adult females have been collared to date). Annual survival of all collared bears during the year (1 April – 30 March) was 0.88 (SE = 0.05), which was close to the 5 year study average (range: 0.82 – 0.94). Bear capture and marking efforts are allowing us to track bear population parameters and habitat-use patterns along the urban-wildland interface.  Between January and March 2016, we visited the winter dens of 34 collared female bears. Of those females, 7 did not have any cubs or yearlings, 15 had yearlings (24 total yearlings in total), and 12 31 �      had newborn cubs (25 cubs). We found that reproductive success, measured as the number of cubs/adult female, was 0.74 (SE = 0.15); previous rates have ranged between 0.58 and 1.28. Annual cub survival (survival from newborn to 1 year) was 66% (based on 33 cubs), which was the highest rate observed during the study (range: 0.42 – 0.54; Photo 1). To date, we have obtained >705,000 locations from GPS collars on 83 different adult female bears along the urban-wildland interface; 46 different bears provided location data during the active bear year of 2015 (May – October; Fig. 1). There were no extraordinary movements recorded this past year, as collared bears generally stayed within the vicinity of Durango. The furthest a bear traveled to the north was up Hermosa Creek, to the east was Vallecito Reservoir, to the south was the ColoradoNew Mexico border, and to the west was the La Plata River. Based on 15 1-km transects in the study area, the availability of natural mast foods was generally moderate in late summer and fall of 2015. Surveys demonstrated that the peak time for mast maturation of native crabapple was early August, serviceberry was between mid-August and midSeptember, chokecherry was early September, gambel oak was mid-September, and pinyon pines was in mid- to late-September. Generally, the maturation of soft and hard mast occurred later in 2015 than in previous years. On transects that had key mast species, mast was present on about 25% of chokecherry, 15% of native crabapple, and 10% of oak and serviceberry shrubs, while approximately 30% of pinyon pines produced moderate to abundant cones. While mast from important species like oak and chokecherry were relatively low in 2015, mast from native crabapple and pinyon pines were quite high; pinyon pines had >3 times the mast that had been observed during any previous year of the study. This past year we used genotype data to estimate female bear abundance and density around Durango. We used an integrated modeling approach that simultaneously combined spatially-explicit capturemark-recapture data from non-invasive hair snags and location data from GPS-collared females. Based on a study area size of 840 km2, integrated spatially-explicit capture-mark-recapture models estimated that female bear abundance in the vicinity of Durango was 156.6 (SE = 22.2) in 2011, 182.7 (SE = 35.7) in 2012, 83.7 (SE = 9.8) in 2013, and 76.2 (SE = 11) in 2014. Density estimates ranged from 0.09 (SE = 0.01) to 0.22 (SE = 0.04; Fig. 2). Abundance and density estimates were dramatically lower in 2013 and 2014, which followed a severe natural food failure in late summer/fall of 2012. During summer 2015 (July through September) we collected our third year of post-treatment data on an experiment designed to assess the effectiveness of wide-scale urban bear-proofing for reducing bear-human conflicts (pre-treatment data were collected 2011 - 2012, post-treatment data were collected 2013 – 2015). Within treatment and control areas we observed 473 instances of bears accessing residential garbage during morning patrols; observations generally peaked in late-August. Of those garbage containers accessed by bears, 76% were regular and 24% were bear-resistant; 115 garbage conflicts were observed in treatment areas (across ~1230 total residences) and 358 occurred in control areas (across ~1260 total residences). We used kernel density functions to spatially estimate the probability of trash-related bear conflicts before and after the distribution of bear resistant containers. We found that since the implementation of the bear-proofing experiment in 2013, trash conflicts have been significantly reduced in the northern experimental unit, and have shifted to the control area in the south experimental unit (Fig. 3). During summer 2015 we found that the average compliance of residents to wildlife ordinances was 59% in the north treatment area and 35% in the south treatment area. “Compliance” was defined as having a container that was properly locked (both latches clipped) or secured in a garage or shed before 6:00 am. In the northern area, compliance increased from 45% in 2013 to 52% in 2014, to 59% in 2015. In the southern area compliance increased from 29% in 2013, to 34% in 2014, to 35% in 2015. A journal article was published this past year from the study, evaluating a new immobilization drug combination for black bears: Wolfe, L.L., H.E. Johnson, M.C. Fisher, W.R. Lance, D.K. Smith, and 32 �M.W. Miller. Chemical immobilization in American black bears using a combination of nalbuphine, medetomindine, and azaperone. Ursus 27:1-4. Data collection for this project will persist through winter 2017, and we will continue to analyze data and prepare research publications. In the coming year, we will be finalizing demographic estimates from the non-invasive genetic mark-recapture data, and developing integrated population models which can be used to better track trends in bear population dynamics. In addition, we will be identifying factors affecting driving tolerance for black bears, compliance behaviors related to bear-proofing, and the effects of bear-proofing efforts on risk of conflict with bears. Once data collection is complete, we will then be able to conduct the remainder of the analyses needed to meet project goals. By addressing our research objectives we hope to better understand the influence of urban environments on bear populations, elucidate the relationship between human-bear conflicts and bear behavior and demography, understand the effect of human-bear interactions on human attitudes and actions, develop tools to promote the sustainable management of bears in Colorado, and ultimately, identify solutions for reducing bear-human conflicts in urban environments. See Johnson et al. (2016, Federal Aid Report W-204-R1) for a more detailed version of this project summary. Photo 1. Two immobilized yearling black bears laying on top of their mother while completing data collection at a winter den in 2016. 33 �Figure 1. GPS collar locations from 46 adult female black bears collected during 1 January – 31 December 2015 in the vicinity of Durango, Colorado (different colors represent different bears). Figure 2. Model averaged density estimates based on integrated spatially-explicit capture-mark-recapture models (solid lines; using both hair-snare and GPS collar data) and standard spatially-explicit capturemark-recapture models (dashed lines; using hair-snare data only) for female black bears near Durango, Colorado, USA from 2011 to 2014. 34 �Figure 3. ‘Hot spots’ of black-bear human trash conflicts pre- and post-distribution of bear-resistant trash containers in Durango, Colorado. All residents in treatment areas (outlined in red) were given bearresistant trash containers in 2013; residents in the control areas (outlined in black) did not receive bearresistant containers. Pre-treatment data were collected 2011-2012, and post-treatment data were collected 2013-2015. Hot spots were identified as those areas with the highest probabilites of conflict from kernal density functions of all observed trash conflicts. Pre-Treatment Post-Treatment Treatment Control Treatment Control 35 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mountain lion population responses to sport-hunting on the Uncompahgre Plateau, Colorado Period Covered: July 31, 2015−June 30, 2016 Principal Investigator: Kenneth A. Logan, Ken.Logan@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. Colorado Parks and Wildlife (CPW) conducted a 10-year (2004−2014) study on effects of sporthunting on a mountain lion population on the Uncompahgre Plateau. The purpose was to examine effects of hunting on a lion population, to evaluate assumptions used by CPW in lion management, and learn how lion hunter behavior may influence harvest. This report summarizes the latest analysis of the effects of hunting and other causes of mortality on a lion population. Analyses are ongoing and are expected to provide reliable information for application in lion management in Colorado. The study was designed with a reference period (years 1−5, RY1−RY5) without mountain lion hunting, and a treatment period (years 6−10, TY1−TY5) with lion hunting. The reference period began December 2004 and ended October 2009. The treatment period began November 2009 and all data collection ended in December 2014. The study area was on the Uncompahgre Plateau in Mesa, Montrose, Ouray, and San Miguel Counties. The 2,996 km2 (1,157 mi.2) study area included the southern halves of Game Management Units (GMUs) 61 and 62, and the northern edge of GMU 70. The Uncompahgre Plateau Study Area GMU (UPSA from here on) was in the largest 8% of the 185 GMUs used to manage lions in Colorado (average = 1,457 km2, range = 71−4,460 km2). Because this study was designed to represent a lion population segment on a Colorado GMU scale, the study area was managed as its own GMU so that inferences from the study could be interpreted at the GMU scale. From December 2, 2004 to October 30, 2014 we captured about 256 individual lions a total of 440 times on the UPSA. We individually marked 226 lions: 109 in the reference period and 115 in the treatment period. Marked lions provided known-fate data on 75 adults, 75 subadults, and 118 cubs. In addition to the lions captured by our research team during the treatment period, lion hunters captured and killed a total of 35 lions, including 8 adult females, 16 adult males, 3 subadult females, and 8 subadult males. Lion hunters also reported having captured and released 30 independent lions, with their reported gender identification of 19 females and 11 males. During the reference period without sport-hunting as a mortality factor the population of independent lions comprised of adults and subadults increased from a low of 33 lions counted in RY4 to a high of 56 lions counted in TY1 (Fig. 1). This indicated that lion management on the study area before this study probably suppressed the lion population. Along with the population increase during the reference period, adult lion survival was high and the age structure of independent lions increased. In the reference period, of the 32 (21 females, 11 males) adult radio-collared lions we monitored 7 adult lions died but none from hunting. Causes of death were attributed to: 5 natural causes (4 intraspecific strife, 1 unknown), 1 vehicle strike, and 1 depredation control. Of the 22 subadults (8 females, 14 males) providing known-fate data, 3 died. One male that had dispersed from the study area was killed by a hunter that did not see the tags (tagged lions that ranged north of the study area were protected from hunting during the reference period). Other causes of death in subadults were 1 natural cause (trampled by elk) and 1 vehicle strike. Of 55 radio-collared cubs (28 females, 27 males) monitored in the reference period, 16 died. Causes included: 13 infanticide, 1 predation, 1 unknown natural, and 1 vehicle strike. In 36 �the reference period natural causes dominated deaths of adults and cubs (71.3% and 93.8%, respectively), but 2 of 3 subadult deaths were from human causes. The treatment period was managed with mountain lion sport-hunting. TY1 was the first year that hunting influenced the lion population after 5 years of no hunting, and it was marked with the highest count of independent lions (56) on the study area. TY1−TY3, the lion harvest rate was set with a design quota of 8 lions to test if a 15% harvest of independent lions with 35−45% independent females in the harvest would result in a stable-to-increasing population. However, the expectation that a 15% harvest results in a stable-to-increasing population was not supported as the population of independent lions declined steadily from 56 in TY1 to 42 by TY4 (Fig. 1). Results from TY1−TY4 indicated that reducing a lion population with hunting is achievable at a 15% harvest rate with other human-caused and natural mortality operating on the population. The lion population in the treatment period was expected to continue to decline if the quota remained at 8 lions. Therefore, in an effort to find a harvest rate useful to managers that might result in a stable-to-increasing population for the remainder of the study, the quota was reduced to 5 lions. This quota represented about 11−12% harvest rate of independent lions for TY4 and TY5. Sport-hunting was the most important cause of death for independent lions during the treatment period. Of the 61 adults (39 females, 22 males) we radio-monitored during the period, 37 died. Hunting caused 56.8% of adult deaths (n = 21: 14 males, 7 females), followed by natural causes (27%; n = 10: 7 unknown with 6 probably disease-related and 1 due to starvation with senescence, 3 intra-specific strife), and other human causes (16.2%; n = 6: 3 vehicle strike, 2 depredation control, and 1 illegal kill). Of the 53 subadults (19 females, 34 males) providing known-fate data, 20 died. Hunting caused 55% of the subadult deaths (n = 11: 9 males, 2 females). Natural mortality followed in importance with 25% (n = 5: 3 intra-specific strife, 2 other natural), then closely by 20% other human causes of death (n = 4: 3 depredation control, 1 vehicle strike). Combining adult and subadult lion deaths in the treatment period, human causes were 73.7 % (i.e., 42/57*100), of which hunting caused 76.2% (i.e., 32/42*100) and other human causes comprised 23.8% (10/42*100). Of the 63 radio-collared cubs (27 females, 36 males) monitored, 27 died. Mortality causes in the cubs included: 9 infanticide, 4 other natural, 2 vehicle strike, 3 depredation control, and 9 starvation. The 9 cubs starved after the deaths of 5 mothers due to: hunting (2 mothers involving 3 cubs), depredation control (1 mother with 3 cubs), and natural causes (2 mothers involving 3 cubs). Natural mortality comprised the majority of cubs’ deaths (15/27*100 = 55.6%). But, human-caused cub deaths in the treatment period increased to 44.4% (12/27*100 = 44.4%) from 6.2% in the reference period. In the treatment period, the population of independent lions declined from a total count of 56 in TY1 to a low of 42 in TY4, a 25% decline after three hunting seasons (Fig. 1). The abundance of adult females declined 23.3% by TY5. Adult males declined 55% by TY3 and TY4, and 50% by TY5. The percentage of females in the harvest TY1−TY5 was 31.6%; comprised of 23% adult females and 8.6% subadult females. The remainder of the harvest was comprised of adult males (45.7%) and subadult males (22.9%). After we reduced the quota to 5 for TY4 and TY5, the abundance of independent pumas seemed to stay in a low phase and may have slightly increased (Fig. 1). Hunting in surrounding GMUs also contributed to the decline in the abundance of independent lions on UPSA. Ten radio-collared independent lions (2 adult females, 7 adult males, 1 subadult female) included in treatment year winter counts were killed by hunters in adjoining GMUs 61 North, 62 North, 65, and 70 because those lions had home ranges that extended beyond the boundaries of UPSA. Those lions were counted in the hunting quota in the adjoining GMUs, not UPSA. Including these deaths off the study area, the percent of hunting kill from TY1−TY5 ranged from 11.4%−25% (average = 18.2%) of independent lions in winter counts on the UPSA. The actual hunter-kill of the number of independent lions during TY1−TY3 ranged from 17.3−25% (average = 21.8%), and was associated with the population decline phase. During TY4−TY5 the actual hunter-kill was 11.4−19.0% (average = 15.2%), and was associated with the low population phase. We used an information-theoretic approach and Akaike’s Information Criterion to rank survival models with and without the treatment effect for adults, subadults, and cubs. The hunting treatment was 37 �indicated as an important factor explaining variation in adult and subadult male lion survival rates. Average annual survival rates of adult male lions declined significantly from 0.96 in the reference period to 0.40 in the treatment period. Likewise, subadult male lion survival rates declined significantly from 0.92 in the reference period to 0.43 in the treatment period. Although average annual adult female lion survival in the reference period, 0.86, was not statistically different than in the treatment period, 0.74, the decline in the abundance of adult females by 23.3% from TY1−TY5 suggested that the lower survival rate during the treatment period was biologically significant. Subadult female survival in the reference period, 0.63, was not statistically different from survival in the treatment period, 0.70. For cubs, models indicated that whether the dam lived or died was the single most important factor affecting cub survival. For the entire study period, the rate of cub survival to the subadult stage was 0.45. Female cub survival, 0.42, was not statistically different than male cub survival, 0.48. Age structure of independent lions declined from TY1−TY5. After 5 years of no hunting, the younger and up to middle aged (i.e., 1−5 years old) lions comprised the majority of the population and with both adult females and males being represented up to the oldest ages (i.e., >5−10+ years old). After 5 years of hunting, adult males >5 years old were eliminated from the age structure. Average litter size in the reference period, 2.76, was not statistically different from the treatment period, 2.38. Likewise, parturition rate for adult females in the reference period, 0.63, was not statistically different from the treatment period, 0.48. Sex ratio of cubs born in the reference or treatment periods, and in the study overall was not statistically different from parity. Management Implications 1) In the GMU-based mountain lion management structure in Colorado, a design harvest of ≥15% of independent lions with an average of ≥20% adult (i.e., 2+ years old) females in the harvest, and with other human and natural causes of mortality operating on a relatively high density lion population, can cause population decline in as few as 3 years. Managers should consider accounting for all detectable (i.e., recorded) human-caused mortality in quotas when setting removal rates in respect to lion population management objectives. Other human causes of death comprised about 24% of the total human-caused mortality with the remaining 76% of deaths due to hunting in the treatment period on the UPSA GMU when the lion population declined and reached a low phase. 2) It can take up to 5 years for a lion population previously reduced to a low density to recover to a relatively high density after hunting has been eliminated. 3) Design harvests of up to 11−12% of independent lions with an average of <20% adult females in the harvest is expected to result in a stable, possibly increasing population, considering that other human- and natural-causes of mortality operate on the population. 4) Lion population segment management objectives and attendant harvest rates can affect lion abundance in the particular GMUs of interest and adjacent GMUs where lions have home ranges overlapping GMU boundaries because GMUs in connected lion habitat are not closed lion populations. 5) Lion harvest management structure which includes provisions for reducing lion population segments to achieve specified management objectives (e.g., reduce predation on livestock or mule deer populations) should also provide for lion population segments managed with conservative harvest rates to allow for stable or increasing lion population segments (i.e., source-sink management) to ensure overall lion population resiliency because of all the unknowns and uncertainties associated with lion population management, including lion abundance and effects of harvest and other human and natural causes of lion mortality in GMUs. 6) Management experiments and research involving lion population segments should consider potential effects of historical lion hunting on and around the study areas. When experimental designs require reference conditions, human-caused mortality to lions should be limited or eliminated if possible. 38 �Final publications from this work are in preparation and will be submitted to the USFWS Wildlife & Sport Fish Restoration Program upon completion. Figure 1. Trends in the population of independent mountain lions associated with no sport-hunting in the reference period years 4 and 5 (RY4, RY5) and with sport-hunting in the treatment period years 1 through 5 (TY1−TY5), Uncompahgre Plateau, Colorado. The count data were gathered from November through April each winter in efforts to canvass the study area thoroughly to count the number of independent lions in addition to the lion harvest. These data represent the number of independent lions expected to have been at risk to hunting during the Colorado lion hunting season November through March each year. 39 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Cougar and bear demographics and human interactions in Colorado Period Covered: July 1, 2015  June 30, 2016 Principal Investigator: Mathew W. Alldredge, mat.alldredge@state.co.us Collaborators: Jefferson County Open Space, Boulder County Open Space, Boulder Open Space and Mountain Parks, U.S. Forest Service, USGS Fort Collins Science Center All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. ABSTRACT Our principal research objective was to assess cougar population ecology, prey use, movements, and interactions with humans along the urban-exurban Front Range of Colorado. This year capture efforts focused on removing collars from previously collared cougars. Only 4 cougars remain with collars as batteries died before they could be captured and collars removed. Only one mortality was documented this year, an adult male injured while preying on an elk. Home-range patterns remained consistent to previous years. Mule deer are the predominant prey in cougar diets, although cougars will also utilize elk regularly. The focus of this year’s efforts was on further development of noninvasive sampling of cougars and bobcats. This project has been completed with the exception of final publications. Project Narrative Objectives 1. To assess cougar (Puma concolor) population demographic rates, movements, habitat use, prey selectivity and human interactions along the urban-exurban Front Range of Colorado. 2. Develop methods for delineating population structure of cougars and black bears (Ursus americanus), assessing diet composition and estimating population densities of cougars for the state of Colorado. Segment Objectives Front Range cougars 1. Capture and mark independent age cougars and cubs to collect data to examine demographic rates for the urban cougar population. Remove collars in final year (Completed). 2. Continued assessment of aversive conditioning techniques on cougars within urban/exurban areas, including use of hounds and shotgun-fired bean bags or rubber bullets (Completed). 3. Continue to assess relocation of cougars as a practical management tool (Completed). 4. Assess cougar predation rates and diet composition based on GPS cluster data (Completed). 5. Model movement data of cougars to understand how cougars are responding to environmental variables (Field work completed, publication pending). 6. Develop non-invasive mark-recapture techniques to estimate cougar population size (Field work completed, publication pending). 40 �2015-2016 Project Overview Field efforts during the 2015-2016 year were primarily focused on the development of noninvasive population estimation techniques for cougars and bobcats (see summary for Noninvasive genetic sampling to estimate cougar and bobcat abundance, age structure, and diet composition). The field efforts for the remaining segment objectives listed above have been completed and are in various stages of data analysis and publication. Capture efforts focused on catching and removing collars from all previously collared cougars. We are continuing to collaborate with CSU to examine cougar movement models to better understand how cougars are responding to their environment. 1. Model movement data of cougars to understand how cougars are responding to environmental variables. Field work completed - (see abstract Mountain Lion Movement Dynamics in the Wildland- Urban Interface) 2. Develop non-invasive mark-recapture techniques to estimate cougar population size. Field work completed - data analysis and publication in progress Mountain Lion Movement Dynamics in the Wildland-Urban Interface Assessing preferential use of the landscape is important for managing wildlife and can be particularly useful in transitional habitats, such as at the wildland-urban interface. We characterized preferential habitat selection by a population of mountain lions (Puma concolor) inhabiting the Front Range of Colorado, an area exhibiting rapid population growth. Preferential use is often evaluated using resource selection functions (RSFs), but they do not account for the habitat available to an individual at a given time and may mask conflict or avoidance behavior. Contemporary approaches to account for availability based on movement include spatio-temporal point process models, step-selection functions, and continuous-time discrete-space (CTDS) models. We used a continuous-time discrete-space (CTDS) framework to model transition rates among grid-cells as a function of landscape covariates. The CTDS framework is based on an underlying movement model and allows for inference on the same spatial scale as the covariates. We exploited the flexibility of the CTDS framework to accommodate location- and gradient-based drivers of movement, individual variation, and time-varying responses to variables such as prey availability, development, topography, and canopy cover. We failed to detect a significant population-level response to any of the covariates except for distance to kill site, which had a positive effect on both transition rates (as individuals were further from a kill site, they were more likely to transition out of a grid cell) and directionality (individuals were more likely to transition towards a kill site). Noninvasive genetic sampling to estimate cougar and bobcat abundance, age structure, and diet composition Cougar and bobcat populations are actively hunted throughout the state of Colorado and management is applied using the best available information. Unfortunately, reliable information on cougar and bobcat populations is nascent. The best information available comes from long-term studies on relatively small populations where animals have been repeatedly captured. However, to better manage these populations, broad-scale information for these species is necessary. We have continued developing noninvasive genetic sampling (NGS) techniques to provide better, less expensive data for cougars and bobcats that can be implemented at broad geographic scales with state-wide application. The methods being developed should provide information on population size, sex structure, age structure, and diet composition. This information is valuable to the future management of these species and for the justification of harvest levels imposed on them. Over the last few years we have further refine these NGS techniques for cougars and bobcats so that they could be reliably implemented to inform management decisions. We have also performed a full survey over multiple years to assess the reliability and repeatability of this approach. Following these 41 �efforts we hoped to have a fully developed NGS approach for cougars and bobcats that could be implemented at a state-wide level for future monitoring of these species. Objectives 1. Continue to evaluate the use of auditory calls for NGS sampling of cougars. 2. Implement a NGS survey for cougars over multiple years to evaluate the consistency of the approach. 3. Use collared cougars to evaluate trap response of cougars and assess potential biases in the NGS approach. 4. Evaluate the potential to sample bobcats using the same NGS approach. 5. Test alternative hair snaring devices for felids. 6. Assess a simultaneous sampling approach for bobcats and cougars relative to differences in home-range size. 7. Implement an NGS survey over multiple years for bobcats and cougars to determine the logistics, cost and feasibility of sampling to obtain estimates of density, sex structure, age structure and diet composition. Following on the success of the development of noninvasive techniques for sampling cougars, we initiated a three-year study to continue to develop noninvasive methods for sampling cougars and bobcats. Sites were built in November and December, 2013, and were monitored for 12 weeks during January – April, 2014. In 2014/15 and 2015/16 sites were built during November and monitored for three months starting the 1st of December and continuing through the first week of March. Sites were modified in 2014/15 to use vertical hair snags instead of horizontal snags in an attempt to get more animals to enter the cubbies and to create a snag that could obtain samples from both bobcats and cougars. The number of unique observations of cougars increased this year compared to the previous and was comparable to the first year (Table 3). Hair samples from cougars increased accordingly and was comparable to the first year of the study. Hair samples from bobcats increased from 5 the first year to 12 the second year and 31 this year. This is likely a result of narrowing the spacing between the barbed wire to approximately 6 inches. Genotypes from bobcat hair has had limited success but is more successful for cougars. Field efforts for this portion of the study have concluded. Table 3: Noninvasive hair snag capture results for bobcats and cougars. Number of animals seen, number of hair samples collected and number of successful genotypes. Species Bobcat Bobcat Bobcat Cougar Cougar Cougar Year 2014 2015 2016 2014 2015 2016 Pictures 31 68 86 42 42 Hair Samples 5 12 31 55 32 51 Genotypes 0 1 4 20 11 15 �SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT 43 �Colorado Parks and Wildlife WILDLIFE RESEARCH REPORT SUMMARY Research library, annual report Period Covered: July 1, 2015 – June 30, 2016 Author: Kay Horton Knudsen, kay.knudsen@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. The Colorado Parks and Wildlife Research Center Library has existed for several decades in the Ft. Collins office. Early librarians can be credited with the physical organization of the Library including Federal Aid reports, Wildlife Commission reports and a unique book and journal collection. The goal of the Library is to provide an effective program of library services for Colorado Parks and Wildlife employees, cooperators and wildlife educators. The Library also serves as an archive for CPW publications. The mission of outreach and support is fulfilled using technology to provide a library website with the online catalog, wildlife databases and digitized documents available to CPW staff statewide. As of June 30, 2016, the Research Library held 19,714 titles and 29,175 items (these are the multiple copies of a title) and had 177 registered patrons (CPW staff). As part of the project to digitize CPW documents, the equivalent of 8GB of data has been scanned and uploaded to the catalog vendor. Current wildlife databases include BioOne, four of EBSCO’s specialty databases (Environment Complete, Fish and Fisheries Worldwide, Wildlife and Ecology Studies Worldwide and CAB Abstracts), Birds of North America, ProQuest Dissertations and Theses and the JSTOR Life Sciences collection. Print subscriptions to the major wildlife journals were cancelled several years ago however online access to the journals was retained and continues as a primary usage point for staff. CPW staff statewide are authenticated through CPWNet (intranet) eliminating the need for individual usernames and passwords. Major special projects this year focused on maintenance of the physical Library collection. When the Library catalog was automated in 1994, the records for some books were not converted from the old card catalog to the online version. These books were inaccessible online but were taking up shelf space desperately needed for new material. As the collection was inventoried, retention decisions were made with the help of Research managers and staff. All theses and dissertations were retained and cataloged if necessary. In addition, there was a huge backlog of items that had never been cataloged. The Collection Development Policy states that the Library is to be an archive for CDOW/CPW material. Therefore, the priority was to catalog and retain reports authored by Division of Wildlife or CPW staff or those reports with a strong Colorado connection. The non-Colorado material was sent to a Library-material recycler. As a form of outreach to staff and stakeholders, the Research branch has made an effort to restart the Technical Publication series. The Librarian was involved in editing and proofreading as well as coordinating publications on the Rio Grande turkey, the Georgetown bighorn sheep herd, Cyprinid fish larvae (written by staff at CSU’s Larval Fish Lab) and others currently in process. The Library website provides more full-text resources than ever before, however there are also more abstract-only indexes. A major role of the librarian is to assist CPW staff with document delivery and research assistance. The Library is not open on a walk-in basis to the general public but the librarian does assist the Denver Help Desk and area staff with questions they receive from citizens. The librarian has Affiliate Faculty status with the Colorado State University Library which provides access to the large natural resources and science collection at that facility. The chart below shows the number of reference questions and document requests handled by the librarian each month during the past 8 years. Please note 44 �that one request from a CPW staff member may be for multiple journal or book titles. A new record for the most requests in a month was set in March 2016*. 45 � https://cpw.cvlcollections.org/files/original/d16ff855d3bfa623b68cde24e4c1d77c.pdf 5aa6dcfbfc7ea93c2903a7020d484b46 PDF Text Text MAMMALS - JULY 2017 �ii �WILDLIFE RESEARCH REPORTS JULY 2016 – JUNE 2017 MAMMALS RESEARCH PROGRAM COLORADO PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). iii �Executive Summary This Wildlife Research Report represents summaries (≤5 pages each) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) and mechanical habitat treatment method comparisons from the CPW Habitat Reseacher of the Avian Research Section from July 2016 through June 2017. These research efforts represent long term projects (4 – 10 years) in various stages of completion addressing applied questions to benefit the management of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx or from the project principal investigators listed at the beginning of each summary. Current research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to habitat alterations, human-wildlife interactions, and investigating improved approaches for wildlife and habitat management. The Nongame Mammal Conservation Section addresses preliminary results of mammal responses to the recent spruce beetle outbreak causing large scale changes in subalpine forest habitats in Colorado and lynx population monitoring results from the San Juan Mountain Range in southwest Colorado since 2014. The Ungulate Conservation Section includes 4 projects addressing effectiveness of mechanical treatment methods in restoring mule deer habitats, development planning and mitigation approaches to benefit mule deer exposed to energy development activity, evaluation of moose demographic parameters that will inform future moose management in Colorado, and a pilot study addressing factors influencing elk calf recruitment. The Predatory Mammal Conservation Section addresses black bear use of urban/exurban environments and approaches for managing black bear-human interactions and evaluation of harvest management for mountain lions in western Colorado. The Support Services Section describes the CPW library services to provide internal access of CPW publications and online support for wildlife and fisheries management related publications. We have benefitted from numerous collaborations that support these projects and the opportunity to work with and train wildlife technicians and graduate students that will enhance understanding of wildlife management and ecology in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, Idaho State University, University of Wisconsin-Madison, U.S. Bureau of Land Management, U.S. Forest Service, City of Boulder and Jefferson County Open Space, City of Durango, CPW big game auctionraffle grants, Species Conservation Trust Fund, GOCO YIP internship program, CPW Habitat Partnership Program, Safari Club International, Boone and Crocket Club, Colorado Mule Deer Association, The Mule Deer Foundation, Muley Fanatic Foundation, Wildlife Conservation Society, SummerLee Foundation, EnCana Corp., ExxonMobil/XTO Energy, Marathon Oil, Shell Exploration and Production, WPX Energy, and private land owners providing access to support field research projects. iv �STATE OF COLORADO John Hickenlooper, Governor DEPARTMENT OF NATURAL RESOURCES Bob Randall, Executive Director PARKS AND WILDLIFE COMMISSION John V. Howard, Chair.……………………………………………………………………….......... Boulder Michelle Zimmerman, Vice Chair.……………………………………………………………. Breckenridge James Vigil, Secretary…………………………………………………………..………………......Trinidad Robert Bray…………………………………………………………………………………………. Redvale Marie Haskett ……………………………………………….………….….………………............... Meeker Carrie Besnette Hauser….……………………………………………………………….. Glenwood Springs Marvin McDaniel……………………………………………………………………………….…….Sedalia Dale E. Pizel…………………………………………………………………………………………....Creed Jim Spehar…………………………………………………………………………………... Grand Junction Robert “Dean” Wingfield…………………………………………………………………………….Vernon Alexander Zipp………………………………………………………………………………………. Pueblo Don Brown, Dept. of Agriculture, Ex-officio….………………………………..…….………............. Yuma Bob Randall, Executive Director, Ex-officio……….…………………...………………….……....... Denver DIRECTOR’S LEADERSHIP TEAM Bob Broscheid, Director Ried DeWalt, Heather Dugan, Justin Rutter Margret Taylor, Gary Thorson, Jeff Ver Steeg, Pat Dorsey, Mark Leslie, Dan Prenzlow, JT Romatzke MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Wildlife Researcher Eric Bergman, Wildlife Researcher Jake Ivan, Wildlife Researcher Heather Johnson, Wildlife Researcher Ken Logan, Wildlife Researcher Kay Knudsen, Research Librarian Michelle Gallagher, Program Assistant v �Colorado Parks and Wildlife July 2016  June 2017 TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS NONGAME MAMMAL CONSERVATION MAMMAL AND BREEDING BIRD RESPONSE TO BARK BEETLE OUTBREAKS IN COLORADO by J. Ivan and A. Seglund………………...……………………. 1 CANADA LYNX MONITORING IN COLORADO……………………………………………...7 UNGULATE AND HABITAT CONSERVATION EXAMINING THE EFFECTIVENESS OF MECHANICAL TREATMENTS AS A RESTORATION TECHNIQUE FOR MULE DEER HABITAT by D. Johnston……………….12 POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson………………………………………………………………..16 EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO by E. Bergman …………………………………...21 ELK RECRUITMENT AND HABITAT USE IN COLORADO by M. Alldredge, B. Banulis, and A. Vitt…………………………………………………………………………… 24 PREDATORY MAMMAL CONSERVATION BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS by H. Johnson………………………………………………………………………… 28 EFFECTS OF HUNTING ON A MOUNTAIN LION POPULATION ON THE UNCOMPAHGRE PLATEAU, COLORADO by K. Logan……………………………………. 31 SUPPORT SERVICES LIBRARY SERVICES by K. Knudsen……..……………………………...……………………. 37 vi �NONGAME MAMMAL CONSERVATION MAMMAL AND BREEDING BIRD RESPONSE TO BARK BEETLE OUTBREAKS IN COLORADO CANADA LYNX MONITORING IN COLORADO 1 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mammal and breeding bird response to bark beetle outbreaks in Colorado Period Covered: July 1, 2016  June 30, 2017 Principal Investigators: Jacob S. Ivan, Jake.Ivan@state.co.us; Amy Seglund, Amy.Seglund@state.co.us ; All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. ABSTRACT: Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) infestations have reached epidemic levels in Colorado, impacting over 4 million acres since the initial outbreak in 1996. Though bark beetles are native to Colorado and periodic infestations are considered a natural ecological process, the geographic scale of their impact and simultaneous infestation within multiple forest systems has never been observed. This historic outbreak is having significant impacts on composition and structure of forest stands that will propagate for decades into the future. Here we used occupancy estimation to determine statewide wildlife response to bark beetle outbreaks, as mediated by changes in forest structure. Surveys were conducted during the summers of 2013 and 2014. We randomly sampled 150 Engelmann spruce (Picea engelmanni)-subalpine fir (Abies lasiocarpa) sites and 150 sites consisting mostly of lodgepole pine (Pinus contorta) or lodgepole pine mixed with other conifers. For both strata, sampling covered conditions ranging from sites that were not impacted by bark beetles to those that were impacted by beetles more than a decade ago. At each 1-km2 (0.4 mi2) site, we sampled the breeding bird community using the Rocky Mountain Bird Observatory’s protocol for “Integrated Monitoring in Bird Conservation Regions” (Hanni et al. 2014). We sampled the mammal community by deploying a remote camera near the center of each sample unit. Avian data have not yet been analyzed. We collected 388,951 photos of 56 species (25 mammalian species). Using Program MARK (White and Burnham 1999), we fit standard occupancy models (MacKenzie et al. 2006) to data for each species in the following manner. First, we identified the best-fitting ‘base’ model from among all combinations of 0-4 of the following variables: spruce-fir or lodgepole stratum, percentage of aspen present at the site, canopy cover, shrub cover due to deciduous species, shrub cover due to conifer species, shrub height, amount of down wood, amount of bare ground, and four physiographic variables that collectively account for elevation, topographic position (e.g., valley bottom, ridge top), moisture accumulation, and solar radiation at each site. The purpose of this model was to account for basic occupancy patterns of each species in the state irrespective of bark beetles. Next, we fit additional parameters to the base model which allowed occupancy to change in a variety of patterns (e.g., linear, quadratic, 3rd order polynomial, or change points when needles drop following an outbreak) in relation to time elapsed since a stand was initially impacted by beetles. We also explored whether there was any interaction between response to beetles and stratum or the severity of the outbreak (percent of trees that were killed). We used Akaike’s Information Criterion (Burnham and Anderson 2002) to assess fit of these various beetle response models, and model-averaged occupancy across the model set (i.e., ‘year since beetle outbreak’ was treated as a group such that parameters for each group could be averaged across all models in the set) to provide a best estimate of response of each species to beetles. As per our hypotheses, results suggest that ungulate species are positively associated with bark beetle outbreaks, although the shape and nature of their responses was variable (Fig. 1). Also not 2 �surprisingly, granivore species comprised the majority of species that were negatively associated with bark beetle outbreaks, although again the magnitude and shape of responses was variable (Fig. 2). We did not detect any response to bark beetles by American marten or black bears (Fig. 3). Snowshoe hares did not follow expectation either, as their use did not markedly increase through time with increasing development of a dense understory (Fig. 3). Both red squirrels and snowshoe hares used spruce-fir stands more heavily than lodgepole stands. Figure 1. Species that exhibited a positive association between use of forested stands and beetle activity (either years since the outbreak occurred, severity, or both). From left to right, panels indicate predicted model-averaged responses for cases where 10%, 50%, and 90% of the overstory in a stand is killed by beetle activity. From top to bottom, panels show response for elk, mule deer, and moose. Probably of use was estimated to vary little between the spruce-fir and lodgepole pine stands, so responses are pooled among strata for these species. Shaded areas represent model-averaged 95% confidence intervals. 3 �Figure 2. Species that exhibited a negative association between use of forested stands and beetle activity (either years since the outbreak occurred, severity, or both). From left to right, panels indicate predicted model-averaged responses for cases where 10%, 50%, and 90% of the overstory in a stand is killed by beetle activity. From top to bottom, panels show response for red squirrel, golden-mantled ground squirrel, chipmunk spp., and coyote. For red squirrels, use was estimated to vary between the spruce-fir (blue) and lodgepole pine stands (gray); for other species, habitat strata was less important and responses are pooled across habitat types. Shaded areas represent model-averaged 95% confidence intervals. 4 �Figure 3. Species that exhibited a little association between use of forested stands and beetle activity (either years since the outbreak occurred, severity, or both). From left to right, panels indicate predicted model-averaged responses for cases where 10%, 50%, and 90% of the overstory in a stand is killed by beetle activity. From top to bottom, panels show response for American marten, black bear, snowshoe hare, and porcupine. For snowshoe hares, and porcupine, use was estimated to vary between the sprucefir (blue) and lodgepole pine stands (gray); for other species, habitat strata was less important and responses are pooled across habitat types. Shaded areas represent model-averaged 95% confidence intervals. 5 �Figure 4. Species that exhibited mixed associations between use of forested stands and beetle activity (positive association with YSO but negative with severity, or vice-versa). From left to right, panels indicate predicted model-averaged responses for cases where 10%, 50%, and 90% of the overstory in a stand is killed by beetle activity. From top to bottom, panels show responses for red fox and yellow-bellied marmot. Use was estimated to vary little between the spruce-fir and lodgepole pine stands, so responses are pooled among strata for these species. Shaded areas represent model-averaged 95% confidence intervals. LITERATURE CITED Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populationsof marked animals. Bird Study 46 Supplement:120-138. 6 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Canada Lynx Monitoring in Colorado Period Covered: July 1, 2016  June 30, 2017 Principal Investigators: Eric Odell, Eric.Odell@state.co.us; Jake Ivan, Jake.Ivan@state.co.us; Scott Wait, Scott.Wait@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 19992006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that the population of Canada lynx in the state was apparently viable and self-sustaining. In order to track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is required. During 2014−2017 CPW initiated a portion of the statewide monitoring scheme described in Ivan (2013) by completing surveys in a random sample of monitoring units (n = 50) from the San Juan Mountains in southwest Colorado (n = 179 total units; Figure 1). During 2016−2017 personnel from CPW and USFS completed the third year of monitoring work on this same sample of monitoring units. Specifically, 16 units were sampled via snow tracking surveys conducted between December 1 and March 31. On each of 3 independent occasions, survey crews searched roadways (paved roads and logging roads) and trails for lynx tracks. Crews searched the maximum linear distance of roads possible within each survey unit given safety and logistical constraints. Each survey covered a minimum of 10 linear kilometers (6.2 miles) distributed across at least 2 quadrants of the unit. An additional unit was scheduled for snow track surveys but surveys were not completed. The remaining 33 units could not be surveyed via snow tracking because they occurred in wilderness or were otherwise inaccessible or prone to poor tracking conditions. Survey crews deployed 4 passive infrared motion cameras in each of these units during fall 2016. Cameras were baited with visual attractants and scent lure to enhance detection of lynx living in the area. Cameras were retrieved during summer 2017 and all photos were archived and viewed by at least 2 observers to determine species present in each. Camera data were then binned such that each of 10 15-day periods from December 1 through April 30 was considered an ‘occasion,’ and any photo of a lynx obtained during a 15-day period was considered a detection during that occasion. Crews covered a total of 703 km (437 mi) during snow tracking surveys: 511 km (318 mi) by snow machine, 171 km (106 mi) by truck, and 20 km (12 mi) by snowshoe. Mean distance surveyed per occasion was 18 km (11 mi). Lynx were detected at eight snow tracking units (Figure 1). Scat or hair samples were collected from seven of the 13 lynx tracks discovered (tracks were discovered at some units on >1 occasion). Genetic analyses confirmed that 5 of the 7 samples were lynx (one sample was coyote, another was snowshoe hare). Camera sets yielded 168,705 photos of which 251 were lynx. Lynx were detected at 10 cameras in 6 camera units, although detections in 2 units occurred outside of the official survey period (Figure 1). Resident lynx were documented in the La Garita Mountains north of Creede (Figure 1) for the second consecutive year, which is notable given that resident lynx were never observed in the La Garitas during the reintroduction work. Lynx were again detected in a unit northeast of Wolf Creek Pass, an area 7 �that was used during the reintroduction but lacked lynx detections after the West Fork Fire of 2013. Similarly lynx were also detected in a unit southwest of Lizard Head Pass where they occurred during the reintroduction but had not been detected during the monitoring effort. Lynx were not documented near the New Mexico border where they had been detected for the first time during the 2014 effort. Also, an adult female with kittens was detected at cameras in a unit near Platoro Reservoir, thus documenting that at least some reproduction occurred in the study area. Using Program MARK (White and Burnham 1999), we fit standard occupancy models (MacKenzie et al. 2006) to our survey data to estimate the probability of a unit being occupied (or used) by lynx over the course of the winter. ‘Survey method’ was treated as a group so that we could, based on previous work, 1) allow detection probability (p) to vary by survey method and 2) include a breeding season effect for detection at cameras (lynx tend to move more in late winter when they begin to breed, and thus should encounter cameras more often). We also considered a suite of covariates that could potentially explain variation in occupancy () including proportion of the unit that was covered by spruce/fir forest, proportion covered by modeled lynx habitat (Ivan et al. 2011), average years since bark beetle infestation, variability (standard deviation) in years since bark beetle infestation, proportion of the unit impacted by bark beetles, proportion of the unit that was burned during Summer 2013, and the number of photos of other species that could potentially impact presence of lynx (e.g., snowshoe hares as a food source, coyotes as potential competitors). We limited our model set by considering only combinations of two of these covariates on , in addition to the two covariates on detection. For the purposes of model-fitting, we included data from the pilot study (2010−2011) as well as the first three years of monitoring (2014−2017) to maximize sharing of information across surveys. ‘Year’ was treated as a group variable in this case to obtain a separate occupancy estimate for each effort. . The best-fitting model characterized occupancy as a function of 2 covariates: the proportion of the sample unit covered by spruce-fir forest and the number of photos of hares recorded at camera stations (Table 1). In both cases, the association was positive, indicating that the probability of lynx use increased with more spruce-fir and more hares. Other covariates appeared in top models with spruce-fir, but addition of these covariates did not improve AICc scores beyond the model with spruce-fir only (Table 1). This phenomenon indicates that these other variables were not as informative. There was no discernible association between lynx occupancy and number of photos of other species outside of hares. Detection probability was relatively high for snow tracking surveys (p = 0.63, 95% confidence interval: 0.520.72), and low for monthly camera surveys (p = 0.21, 95% confidence interval: 0.160.28) during DecemberFebruary and April, although detection increased to 0.42 (95% confidence interval: 0.290.57) during breeding season (March) as expected. For winter 2016−2017 we estimated that 23% of the sample units in the San Juan’s were occupied by lynx (95% confidence interval: 0.130.38). Occupancy estimates from the 2016−2017 monitoring effort were slightly smaller to those obtained during the first year of implementation and to those obtained during pilot research work in 2010−2011, although confidence intervals overlapped substantially among years (Figure 2). Note that lynx were detected at the same number of units in 2016−2017 as in previous years, but detections at 2 units occurred outside of the official survey period. Thus, the spatial distribution of lynx in the San Juans is largely unchanged; estimates may have been smaller simply due to when lynx were detected. LITERATURE CITED Ivan, J. S. 2013. Statewide Monitoring of Canada lynx in Colorado: Evaluation of Options. Pages 15-27 in Wildlife Research Report - Mammals. Colorado Parks and Wildlife., Fort Collins, CO, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx Ivan, J. S., M. Rice, P. M. Lukacs, T. M. Shenk, D. M. Theobald, and E. Odell. 2011. Predicted lynx habitat in Colorado. Pages 21-35 in Wildlife Research Report - Mammals. Colorado 8 �Parks and Wildlife, Fort Collins, CO, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Table 1. Model selection results for lynx monitoring data collected in the San Juan Mountains, Colorado, 2010−2017. Rankings are based on Akaike’s Information Criterion adjusted for small sample size (AICc). Twelve variables were considered as covariates to inform estimation of occupancy (). The complete model set (n = 77) included all combinations of two, in addition to modeling detection (p) as a function of survey method and breeding season. Only the best 10 models are shown. Model y(Year + SpruceFir + SnowshoeHare)p(Method + Breeding) y(Year + SpruceFir)p(Method + Breeding) y(Year + SpruceFir + Cougar)p(Method + Breeding) y(Year + SpruceFir + Bobcat)p(Method + Breeding) y(Year + SpruceFir + Fox)p(Method + Breeding) y(Year + SpruceFir + Coyote)p(Method + Breeding) y(Year + SpruceFir + PropBeetleKill)p(Method + Breeding) y(Year + SpruceFir + SDBeetleKill)p(Method + Breeding) y(Year + SpruceFir + PropBurn)p(Method + Breeding) y(Year + SpruceFir + YrSinceBeetle)p(Method + Breeding) 9 AICc 648.1 651.7 652.3 653.4 653.5 653.5 653.6 653.7 653.9 653.9 ΔAICc 0.0 3.7 4.2 5.3 5.4 5.4 5.5 5.7 5.8 5.8 AICcWts 0.54 0.09 0.07 0.04 0.04 0.04 0.03 0.03 0.03 0.03 No. Par. 9 8 9 9 9 9 9 9 9 9 �a) b) Figure 1. Lynx monitoring results for a) the current sampling season (2016−2017) and b) the cumulative monitoring effort (2014−2017), San Juan Mountains, southwest Colorado. Colored units (n = 50) indicate those selected at random from the population of units (n = 179) encompassing lynx habitat in the San Juan Mountains. Lynx were detected in 14 units in 2016−2017 (but detections at 2 units occurred outside of the official survey period) and 18 units cumulatively since monitoring began in 2014−2015. 10 �UNGULATE AND HABITAT CONSERVATION EXAMINING THE EFFECTS OF MECHANICAL TREATMENTS AS A RESTORATION TECHNIQUE FOR MULE DEER HABITAT POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACRIVITY AND HABITAT DEGRADATION EVALUATION AND INCORPORATION OF LIGE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO ELK RECRUITMENT AND HABITAT USE IN COLORADO 11 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Examining the effectiveness of mechanical treatments as a restoration technique for mule deer habitat Period Covered: July 1, 2016 – September 30, 2017 Principal investigator: Danielle B. Johnston, Danielle.Bilyeu@state.co.us Collaborators: Colorado Parks and Wildlife, BLM-White River Field Office, Colorado State University, M. Paschke, J. Jonas, ExxonMobil Prod. Co./XTO Energy All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. The pinyon-juniper (PJ) habitat type has been expanding in the western United States, and understory forage for big game may become reduced in areas where PJ has outcompeted more palatable species. Because prescribed fire is often difficult to implement, managers often rely on mechanical tree removal methods such as ship anchor chaining, roller chopping, and mastication. These methods differ in cost, type of woody debris produced, and soil disturbance (Johnston 2014). We made head-to-head comparisons of understory vegetation changes due to chaining, rollerchopping, and mastication (Figure 1), and also examined how each treatment impacted the success of seeding desirable understory forage species. Each plot was divided into 2 subplots, one of which was seeded with a shrub-heavy seed mix including big sagebrush (Artemisia tridentata), chokecherry (Prunus virginiana), Saskatoon serviceberry (Amelanchier alnifolia), Utah serviceberry (Amelanchier utahensis), mountain mahogany (Cercocarpus montanus), bitterbrush (Purshia tridentata), and winterfat (Kraschenninnikovia lanata). The study was conducted at two sites in the Magnolia region of the Piceance Basin, Rio Blanco County, Colorado. The North Magnolia site (n = 4) had higher control plot tree density, lower tree basal area, and higher shrub cover than the South Magnolia site (n = 3). Treatments were implemented in fall 2011, and understory vegetation data (cover, biomass, and shrub density) was collected in 2012 and 2013 through collaboration with Colorado State University. Site visits in 2014 and 2015 indicated significant changes from this initial assessment period, particularly in the cover of cheatgrass (Bromus tectorum), an invasive annual grass that reduces wildlife habitat quality. In addition, the earlier study did not assess palatable shrub biomass, a key response for big game in this winter range area. In 2016 and 2017, we assessed understory vegetation cover in July using about 300 point-intercept hits arrayed over 13 transects in each subplot. In September 2017, we assessed density, summer utilization, and winter-available forage (hereafter winter forage) for the most prevalent palatable shrubs: big sagebrush, serviceberry (both species lumped), bitterbrush, and mountain mahogany. This report summarizes the 2017 shrub density, utilization and winter forage data; 2017 cover data is still being processed. We measured shrubs within 4 belt transects totaling ~ 240 m2 (0.6 acres) per subplot. Summer utilization was assessed by trained ocular estimation of average twig length removal per shrub. We estimated winter forage by canopy measurements of shrubs. For serviceberry, bitterbrush, and mountain mahogany, regressions predicting winter forage from canopy measurements had been developed 20132016 within the study area (average R2 = 0.73). A regression for big sagebrush was available in the literature (Cleary et al. 2008). We considered winter forage to be current-year shoots without leaves, excluding portions removed by summer browsing. We included non-ephemeral leaves for big sagebrush. 12 �We conducted separate analyses to test for effects of mechanical treatment vs. seeding (Stephens et al. 2016). We saw no significant effects of mechanical treatment on total shrub density. Summer utilization differed by mechanical treatment, with masticated plots having greater utilization than chained or roller chopped plots, which were in turn greater than control plots (Fig. 2). There was a trend for lower total winter forage in masticated plots than in chained or control plots (p = 0.07; Figure 3). Mountain mahogany winter forage followed the same pattern (p = 0.05). Other species had no significant effects for winter forage. Seeding increased total shrub density only within roller chopped plots (treatment*seeding interaction p = 0.01), where shrub density increased from 0.23 ± 0.05 plants/m2 to 0.46 ± 0.10 plants/m2 (1 m2 = 10.8 ft2). Bitterbrush and mountain mahogany density followed the same pattern, with effects of seeding evident within roller chopped plots only. There was no effect of seeding on serviceberry or sagebrush density. Summer utilization was higher in seeded plots at North Magnolia only (p = 0.04), where it increased from 12.0 ± 1.4% to 14.5 ± 1.4%. Seeding effects on winter forage differed by site (site*treatment*seeding interaction, p = 0.01). At North Magnolia, there were no significant effects, although there was a trend for lower winter forage with seeding in chained plots (p = 0.08). At South Magnolia, there was lower winter forage with seeding in chained plots (p = 0.01), and trends for higher winter forage with seeding in masticated and roller chopped plots (p < 0.07). The most obvious explanation for lower winter forage in masticated plots is the greater summer utilization in those plots. Unlike in chained and roller chopped plots, shrubs within masticated plots were specifically targeted for biomass removal. The increased utilization of these plants is probably because of this rejuvenation, which increased palatability. The trend for lessened winter forage with mastication differs from a 2014 analysis of nearby mastication treatments which were a part of a more extensive study on mitigation treatments for mule deer impacted by oil and gas development. In that study, masticated plots had about double the winter forage of control areas. The discrepancy between these studies may be due to the age of the treatments; in this study shrub productivity has likely already peaked. In a 10-year study of effects of biomass removal on productivity of mountain mahogany, serviceberry, and bitterbrush, Shepard (1971) found that heavy clipping causes these species to have an initial spike in productivity. However, continued heavy removal in subsequent years causes drought sensitivity and lower productivity (Shepard 1971). The masticated shrubs in this study experienced initial heavy biomass removal followed by increased utilization, conditions somewhat similar to the plants in Shepard’s study. Although the level of removal does not appear to be enough to jeopardize plant survival, it looks likely that it is impacting productivity. Repeated rejuvenation of these shrubs is not advised. Seeding of shrubs was successful only in roller chopped plots. Roller chopping produced the largest amount of bare ground out of the 3 treatments tested, and also produced more undesirable nonnatives in the early years of this study (Stephens et al. 2016). The disturbance induced by roller chopping apparently has benefits as well as drawbacks. Lessened winter forage with seeding in chained plots is a perplexing result. In 2016, greater cheatgrass (Bromus tectorum L.) cover was evident in seeded subplots at South Magnolia, possibly the result of seed contamination. Forb cover, particularly Utah sweetvetch (Hedysarum boreale), was also higher in seeded subplots. There may be competitive dynamics in chained plots which differ from those in other treatments. An explanation may be more apparent once the 2017 cover data is analyzed. The second phase of monitoring of this study is now complete. Data from 2016 and 2017 will be synthesized for a final report and publication. 13 �Figure 1. Looking west from Rio Blanco CR 76 to treatment plots in North Magnolia in fall of 2012. The three rectangular patches in the left, along with a control plot, comprise one of 4 experimental blocks at this site. Each treatment plot received either chaining, mastication, or rollerchopping, and half of each treated plot was seeded with a shrub-heavy seed mix. Plot size is about 2 acres. all species uti Summer utilization (% of current growth) 30 c 20 b b 10 a 0 CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT Figure 2. Average 2017 summer utilization of serviceberry, bitterbrush, mountain mahogany, and sagebrush plants within mechanical pinyon/juniper removal treatments of different types (Chain = trees removed by ship anchor chaining, Hydro = trees removed by mastication with mastication of shrubs as well, Roller = trees removed by a heavy rotating drum). Letters indicate significantly different means at α = 0.05. 14 �all species winBiomassPerM2 MEAN a 10 9 8 a Winter forage (g/m2) 7 6 ab 5 b 4 3 2 1 0 CHAIN CONTROL HYDRO ROLLER MECHANICAL TREATMENT species2 BigSagebrush Bitterbrush Mtn.Mahogany Serviceberry Figure 3. 2017 winter-available forage of serviceberry, bitterbrush, mountain mahogany, and sagebrush plants within mechanical pinyon/juniper removal treatments of different types (Chain = trees removed by ship anchor chaining, Hydro = trees removed by mastication with mastication of shrubs as well, Roller = trees removed by a heavy rotating drum). Letters indicate significantly different means at α = 0.05. Literature Cited Cleary, M. B., E. Pendall, and B. E. Ewers. 2008. Testing sagebrush allometric relationships across three fire chronosequences in Wyoming, USA. Journal of Arid Environments 72:285-301. Johnston, D. B. 2014. Examining the effectiveness of mechanical treatments as a restoration technique for mule deer habitat: Colorado Division of Parks and Wildlife Avian Research Program annual progress report, Colorado Parks and Wildlife, Fort Collins, CO. Shepard, H. 1971. Effects of clipping on key browse species in Southwestern Colorado, Technical Publication Number 28. Colorado Division of Game, Fish, and Parks, Denver, Co. Stephens, G. J., D. B. Johnston, J. L. Jonas, and M. W. Paschke. 2016. Understory responses to mechanical treatment of pinyon-juniper in northwestern Colorado. Rangeland Ecology & Management 69:351-359. 15 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation Period Covered: July 1, 2016  June 30, 2017 Principal Investigator: Charles R. Anderson, Jr., Chuck.Anderson@state.co.us Collaborators: Colorado Parks and Wildlife, BLM-White River Field Office, Idaho State University, Colorado State University, Federal Aid in Wildlife Restoration, EnCana Corp., ExxonMobil Prod. Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, WPX Energy, Colorado Mule Deer Assn., Muley Fanatic Found., Colorado Mule Deer Found., Colorado State Severance Tax Fund, Boone & Crocket Club, and Safari Club Int. All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent the first 5 pretreatment years and 4 years post treatment of a long-term study addressing habitat improvements and evaluation of energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. We monitored 4 winter range study areas representing varying levels of development to serve as treatment (North Magnolia, South Magnolia) and control (North Ridge, Ryan Gulch) sites (Fig. 1) and recorded habitat use and movement patterns using GPS collars (≥5 location attempts/day), estimated neonatal and overwinter fawn and annual adult female survival, estimated early and late winter body condition of adult females using ultrasonography, and estimated abundance using helicopter mark-resight surveys. During this research segment, we targeted 240 fawns (60/study area) and 120 does (30/study area) in early December 2016 for VHF and GPS radiocollar attachment, respectively, and attempted recapture of 120 does and 40 fawns in March 2017 for late winter body condition assessment. Winter range habitat improvements completed spring 2013 resulted in 604 acres of mechanically treated pinionjuniper/mountain shrub habitats in each of the 2 treatment areas (Fig. 2) with minor and extensive energy development, respectively. Post-treatment monitoring will continue for another year to provide sufficient time to measure how vegetation and mule deer respond to these changes. Based on data collected through year 9 of this 10-year project: (1) annual adult female survival was consistent among areas averaging 79-87% annually, but overwinter fawn survival was variable, ranging from 31% to 95% within study areas, with annual and study area differences primarily due to early winter fawn condition, annual weather conditions, and winter conditions potentially enhancing predation success; (2) migratory mule deer selected for areas with increased cover and increased their rate of travel through developed areas, and avoided negative influences through behavioral shifts in timing and rate of migration, but did not avoid development structures (Fig. 3); (3) mule deer body condition early and late winter was generally consistent within areas, with higher variability among study areas early winter, primarily due to December lactation rates, and late winter condition related to seasonal 16 �moisture and winter severity; (4) mule deer exhibited behavioral plasticity in relation to energy development, where disturbance distance varied relative to diurnal extent and magnitude of development activity (Fig. 4), which may provide for several options in future development planning; (5) late winter mule deer densities have consistently increased in 3 of 4 study areas, averaging about +6% annually, with the North Ridge study area exhibiting erratic population changes that may be an artifact of periodic migration behavior prior to survey timing (Fig. 5); and (6) post treatment vegetation responses have provided evidence of improved forage conditions, but longer term monitoring will be required to address the full potential of habitat mitigation efforts. Detailed habitat use analyses in relation to habitat treatments are still pending for the pre and post-treatment periods. We will continue to collect demographic and habitat use data across all study sites to evaluate the effectiveness of habitat improvements on winter range. This approach will allow us to determine whether it is possible to effectively mitigate development disturbances in highly developed areas, or whether it is better to allocate mitigation efforts toward less or non-impacted areas. In collaboration with Colorado State University, we are also monitoring neonate survival in relation to energy development from all study areas. This will allow us to include neonatal data to other demographic parameters for improved evaluation of mule deer/energy development interactions. Results from the neonate survival component of the project are currently in peer-review and should be published by the next reporting period. The study is slated to run through 2018 to allow sufficient time for measuring mule deer population responses to landscape level manipulations. A more detailed version of this project summary and information about recent publications from this effort can be accessed at: http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, winter 2013/14 (Accessed http://cogcc.state.co.us/ Dec. 31, 2013; energy development activity been minor since 2012). 17 �Figure 2. Habitat treatment site delineations in 2 mule deer study areas (604 acres each) of the Piceance Basin, northwest Colorado (Top; cyan polygons completed Jan. 2011 using hydro-axe; yellow polygons completed Jan. 2012 using hydro-axe, roller-chop, and chaining; and remaining polygons completed April 2013 using hydro-axe). January 2011 hydro-axe treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 18 �Figure 3. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012; http://dx.doi.org/10.1890/ES12-00165.1). 19 �Figure 4. Posterior distributions of population-level coefficients related to natural gas development for RSF models during the day (top) and night (bottom) for 53 adult female mule deer in the Piceance Basin, northwest Colorado. Dashed line indicates 0 selection or avoidance (below the line) of the habitat features. ‘Drill’ and ‘Prod’ represent drilling and producing well pads, respectively. The numbers following ‘Drill’ or ‘Prod’ represent the distance from respective well pads evaluated (e.g., ‘Drill 600’ is the number of well pads with active drilling between 400–600 m from the deer location; from Northrup et al. 2015; http://onlinelibrary.wiley.com/doi/10.1111/gcb.13037/abstract). Road disturbance was relatively minor (~60–120 m, not illustrated above). Piceance Basin late winter mule deer density 35.00 30.00 Deer/km2 25.00 20.00 North Ridge 15.00 Ryan Gulch North Magnolia 10.00 South Magnolia 5.00 0.00 2009 2010 2011 2012 2013 2014 2015 2016 2017 Year Figure 5. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2017. 20 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation and incorporation of life history traits, nutritional status, and browse characteristics in Shira’s moose management in Colorado Period Covered: July 1, 2016  June 30, 2017 Principal Investigator: Eric J. Bergman, eric.bergman@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. During November of 2013 we initiated a large scale moose research project in 3 of Colorado Parks and Wildlife’s 4 geographical regions. This project was continued into the 2016–2017 fiscal year. A primary objective during all years of this project has been the capture of adult female moose for the purposes of deploying VHF and GPS collars, collecting pregnancy data via blood serum, evaluating body condition via ultrasonography, evaluating body condition via blood thyroid hormone concentrations, and collecting early winter calf-at-heel ratios. During fiscal years 2014–2015, 2015–2016, and 2016–2017 field efforts included estimation of parturition rates. During the fourth year of the study, all captures occurred during late December (2016) and early January (2017). Captures during the 2016–2017 winter were concentrated in 2 study areas: the Laramie River (NE Colorado), and southern North Park (NW Colorado). During the fourth year of the study 30 cow moose were captured and radio-collared. Of these 30 animals, 11 were recaptures of animals that had been captured during previous winters of the study. Five of these recaptures occurred along the Laramie River (NE Colorado), and 6 recaptures occurred in North Park (NW Colorado). Individual animals were recaptured to meet 2 objectives. First, many animals wore GPS collars that stored location data within the collar. Those data could not be retrieved without retrieving the collar. These animals were subsequently re-collared with satellite collars that are now capable of transmitting location data. The second objective was to establish a longitudinal data set that will allow us to determine long-term productivity of individual animals. In particular, repeated measurements of individuals will allow us to evaluate if different reproductive strategies occur within moose, and if those strategies can be linked to annual variation within individual condition. Annual adult female moose survival rates for each study area were calculated for the 12-month period ending in midMay. During May, June, and July of 2017, parturition and twinning rates were also estimated for all 3 study areas. During the 2016–2017 winter, measured rump fat at the time of capture ranged between 0–17 mm among study areas. Measured loin depth at the time of capture ranged between 32–55 mm among study areas. Measured loin fat, at the time of capture, ranged between 0–5 mm. When data from 2013–2017 were pooled, pregnancy probability was best predicted by the additive model of maximum rump fat plus a subjective Body Condition Score (BCS) as well as the number of calves-at-heel. Due to the unbalanced sampling design, regional and annual effects in pregnancy rates were not evaluated. As has been the case during all years of the study, survival of radio collared animals was high in all study areas (85%–96%). During 2015–2016 pregnancy rates ranged between 70%–95%, but during 2017 low pregnancy rates in NW Colorado were detected (47%). No clear cause of this anomaly was observed. During the 4 winters of data collection, an upward trend in pregnancy rates has been observed in northeast Colorado. During 2016–2017, observed twinning rates at the time of parturition were low (9%), which is consistent with past years of data collection (observed range has been 5%–12%). 21 �During the summer of 2017 an initial round of vegetation sampling occurred in NW and NE Colorado. These efforts are directed at: 1) identifying willow community diversity at known moose locations, 2) determining if moose demonstrate preference among willow species while browsing, and 3) to determine the nutritional quality of willows throughout the summer period. Ultimately, these data will be used to develop a linkage between moose body condition, moose pregnancy, and moose habitat conditions. Thus far, data collected during this project have met expectations. In particular, survival rates have been consistently high in all study areas. However, the singularly low pregnancy rate observed in NW Colorado during 2016–2017 is noteworthy. Future sampling efforts will demonstrate if this data point was a single stochastic event or indicative of a pattern. During future years, we will develop methodology for determining herd level pregnancy status in cost effective ways. Figure 1. Moose research study areas, located in 3 regions in Colorado. A total of 181 moose were captured during winters between 2013–2014 and 2016–2017. During the winter of 2016–2017, a total of 30 moose were captured in the Northeast and Northwest study areas. Survival of moose was high in all study areas and during all years of the study. 22 �1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 2013-2014 2014-2015 2015-2016 2016-2017 Probability of Being Pregnant Figure 2. Pregnancy data were collected for all moose at the time of capture. Data from northwest Colorado are depicted by black bars, data from northeast Colorado are depicted by gray bars, and data from southwest Colorado are depicted by white bars. Data from southwest were sparse during 2015–2016 (n = 7 animals) and not collected during 2016–2017. The cause and consequences of the low pregnancy rate observed in northwest Colorado during 2016–2017 are yet to be determined. 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 Maximum Measured Rump Fat (mm) Figure 3. Probability of moose pregnancy was best predicted by maximum measured rump fat, body condition score, and the number-of-calves as heel. The strong relationship between body condition and pregnancy status, reflected by the solid black line and data collected during the first 3 years of the study, was diminished by the low pregnancy rate observed in northwest Colorado during 2016–2017 (dashed black line). Data collected during 2017–2018 will help inform if the 2016–2017 data were a singular stochastic event or indicative of an emerging pattern or trend of concern. 23 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY PILOT STUDY—Elk recruitment and habitat use in Colorado Period Covered: July 1, 2016  June 30, 2017 Principal Investigators: Mathew W. Alldredge, mat.alldredge@state.co.us; Brad Banulis, brad.banulis@state.co.us; Allen Vitt, allen.vitt@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. ABSTRACT Our principal research objective is to address elk (Cervus canadensis) recruitment across southern Colorado in response to declining December calf:cow ratios. These ratios have been declining for more than a decade in the majority of the data analysis units (DAUs) across the southern half of Colorado. We have specifically focused on Data Analysis Units E-20 and E-33 as these two analysis units have some of the lowest reported ratios in the state, nearing 20 calves per 100 cows in December. To address this we have initiated a pilot study to examine potential drivers of low recruitment. This includes examining body condition and pregnancy rates of cow elk and cause specific mortality of calves. Body condition and pregnancy rates of cows did not indicate that low recruitment was being driven by these factors. Preliminary results suggest that mortality of calves in E-33 is a contributing factor to low recruitment rates but retention of calf collars in both areas has limited our assessment of calf mortality. Collar failure issues evident this past year will be addressed during the next field season. PROJECT NARRITIVE OBJECTIVE 1. To assess adult cow elk body condition and pregnancy rates in two different elk populations, DAUs E20 and E-33, in southern Colorado. 2. Assess cause specific calf mortality and recruitment into the yearling age class for two different elk populations, E-20 and E-33, in southern Colorado. 3. Assess cow and calf habitat use in relation to body condition and survival. SEGMENT OBJECTIVES Elk Recruitment 1. Measure body condition, pregnancy and fetal rates for cow elk within each study area. 2. Measure calf elk weight at parturition and relate this to the dam’s body condition and whether she had a calf the previous year. 3. Determine cause specific mortality for elk calves from birth to age one. 4. Examine cow elk habitat use, including use of habitat treatments in the study area. 2016-2017 Project Overview Rocky Mountain Elk is an iconic species throughout western North America and especially in Colorado, with a high recreational value to hunters, photographers, artists and wildlife enthusiasts in general. Elk populations are known to fluctuate greatly following habitat alteration, especially following historic wildfires. Human exploitation, habitat loss, predation and disease are all factors that can lead to 24 �population declines. In order to maintain healthy populations, managers must understand these factors and use their best knowledge to set herd objectives, harvest strategies and monitoring programs. Concerns about elk calf ratios have been expressed for about a decade, but factors influencing local populations remain largely unknown. During the 1990’s and early 2000’s, elk herds were above objective and efforts were made to reduce elk populations. Calf ratios started declining in the early 2000’s while herds were generally still above objective. Many studies have been conducted to investigate environmental influences on elk, many of which center around juvenile recruitment (Alldredge and Phillips 2000, White et al. 2010, Sargeant et al. 2011, Cook et al. 2013, Proffitt et al. 2014). Colorado is no exception, in many parts of the state recruitment rates are low and declining, which will have long term ramifications on elk populations across the state. Low recruitment rates for elk across the state and potential long term population level ramifications are of great concern to CPW wildlife managers and biologists. If the trend of low recruitment rates continues, resulting declining elk populations will significantly impact both recreational opportunity and economics in Colorado and for CPW. Furthermore, CPW has a statutory responsibility to manage elk. However, very little is known as to the factors driving declining recruitment rates. Research on this topic is vital. A recent study on mule deer (Odocoileus hemionus) has demonstrated a paradigm shift in causes of low recruitment for this species from the historical research demonstrating low over-winter survival (Bartmann et al. 1992) to recent developments suggesting low neonatal survival (Anderson 2015). It is imperative that CPW conduct similar investigations on elk to gain information on factors affecting low recruitment across the state and develop management strategies to mitigate these factors. Because little is known about the factors affecting elk recruitment in the state, we proposed a pilot study designed to identify primary factors. Given that this low recruitment is occurring across a broad spatial scale we also proposed that this work be conducted in multiple study areas exhibiting low recruitment and one study area with higher recruitment as a reference area. The intent of this 2 year pilot study is to determine pregnancy rates, fetal counts, and cause specific mortality of calf elk from birth to age 1. Additional data on cow body condition, birth weights and consecutive year reproduction will allow determination of potential causes of low elk recruitment. Measuring individual body condition of cow elk in the study and then ascertaining the fate of each cow’s calf will provide valuable insights regarding nutritional influences on both calf survival and future pregnancy rates. Examinations of cow elk habitat use will also be conducted, including use of habitat treatments that exist on the landscape, to determine differences in habitat use and the impact that has on pregnancy rates and calf survival. Cow elk capture was initiated in late February, 2017 in E-20 and E-33. Weather was hot and dry so baiting elk had limited success as natural forage was starting to develop. A total of 8 elk were caught in E-20 and 5 in E-33 using clover traps. The remaining elk were caught in early March using helicopter net gunning. Body condition was estimated for 32 and 29 elk in E-20 and E-33 respectively and 23 were GPS collared in each area. Body condition of elk, based on loin thickness, rump fat and a body condition score was reasonably good in both study areas (Table 1). Vaginal implant transmitters (VITs) were placed in pregnant elk. Pregnancy rates were 78.1% and 90.0% in E-20 and E-33 respectively (Table 1). Calf capture began in the middle of May. Only 2 of 40 VITs functioned properly so capture was primarily opportunistic. A total of 40 and 57 calves were caught in E-20 and E-33, respectively (Table 2). Average age at capture was estimated at just over 2 days old, although some older calves were caught at a week old. Average capture weight was 17.3 kg for both areas. In E-33, initial calf mortality was significant (19 total mortalities). However, collar retention has been an issue in both areas as numerous collars have dropped off as the belting is not holding up as expected, so it will be difficult to address cause specific mortality of calves in E-33 and early collar drops prohibited mortality assessment in E-20. As this is the first year of the study and data is just starting to be collected, no factors have been identified as potentially contributing to low recruitment rates for these elk herds. In the southwest corner of E-20, pregnancy rates were very low. Of the 8 cows captured there, only 4 were pregnant. However, pregnancy rates in the rest of this unit were high. This may be of interest for further investigation to 25 �determine if there are localized low pregnancy rates in this area. Beyond this, the project is on schedule and proceeding as planned. Table 1: Cow capture statistics for E-20 and E-33. Loin thickness (mm), rump fat thickness (mm), body condition score (BCS) and percent pregnant by year and location. Year n Loin Rump BCS % Pregnant 2017 32 48.7 7.1 3.4 78.1 2017 29 52.0 5.7 3.4 90.0 E-20 E-33 Table 2: Calf capture summary for E-20 and E-33. Sex ratio (female:male), estimated capture age (days) and capture weight (kg). Year n F:M Age Weight 2017 40 20:20 2.3 17.3 2017 57 29:26 2.6 17.3 E-20 E-33 26 �PREDATORY MAMMAL CONSERVATION BLACK BEAR EXPLOITATION OF URBAN ENVIRONMENTS: FINDING MANAGEMENT SOLUTIONS AND ASSESSING REGIONAL POPULATION EFFECTS EFFECTS OF HUNTING ON A MOUNTAIN LION POPULATION ON THE UNCOMPAHGRE PLATEAU, COLORADO 27 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Black bear exploitation of urban environments: finding management solutions and assessing regional population effects Period Covered: July 1, 2016  June 30, 2017 Principal Investigator: Heather E. Johnson, heatherjohnson@usgs.gov Project Collaborators: S.A. Lischka, S. Breck, J. Beckmann, J. Apker, K. Wilson, and P. Dorsey All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the principal investigator. Manipulation of these data beyond that contained in this summary is discouraged. Across the country conflicts among people and black bears are increasing in frequency and severity, and have become a high priority wildlife management issue. Whether increases in conflicts reflect recent changes in bear population trends or bear behavioral shifts to anthropogenic food resources, is largely unknown, with key implications for bear management. This issue has generated a pressing need for bear research in Colorado and has resulted in a collaborative study involving Colorado Parks and Wildlife (CPW; lead agency), the USDA National Wildlife Research Center, Wildlife Conservation Society and Colorado State University. Collectively, we have designed and implemented a study on black bears that 1) determines the influence of urban environments on bear behavior and demography, 2) tests a management strategy for reducing bear-human conflicts, 3) examines public attitudes and behaviors related to bear-human interactions, and 4) develops population and habitat models to support the sustainable monitoring and management of bears in Colorado. Field data collection for this project was initiated spring 2011 and completed spring 2016. Several publications from this work are in various stages of analyses, peer-review and publication. Publications in progress and published abstracts are listed below: Publications in Progress: Laufenberg, J., H.E. Johnson, S. Breck, and P. Doherty. Using integrated population models to understand spatio-temporal dynamics in Colorado black bear populations. In Preparation for Ecological Applications. Kirby, R., H.E. Johnson, M.W. Alldredge, and J.N. Pauli. The tension between foraging and hibernation shapes biological aging in bears. In Preparation for Journal of Animal Ecology. Lischka, S., T. Teel, H. E. Johnson, S. Breck, and K. Crooks. Factors associated with public compliance of wildlife ordinances. In Preparation for Journal of Wildlife Management. Johnson, H.E., S.W. Breck, and D.L. Lewis. The effects of human development on black bear survival and fecundity. In Preparation for Journal of Animal Ecology. Lischka, S. T. Teel, H.E. Johnson, S. Breck, and K. Crooks. What drives real and perceived risk of human-wildlife conflict? In Preparation for Human Dimensions of Wildlife. 28 �Johnson, H.E., D.L. Lewis, S. Lischka, and S.W. Breck. Bear-resistant containers reduce human-black bear conflicts and improve public perceptions. Journal of Wildlife Management, In Press. Wibur, R.C., S.A. Lischka, J.R. Young and H.E. Johnson. 2017. Experience, attitudes and demographic factors influence the probability of reporting human–black bear interactions. Wildlife Society Bulletin, In Press. Published Abstracts: Shifting perceptions of risk and reward: Dynamic selection for human development by black bears in the western United States H.E. Johnson1, S.W. Breck2, S. Baruch-Mordo3, D.L. Lewis4, C.W. Lackey5, K.R. Wilson4, J. Broderick6, J.S. Mao7, J.P. Beckmann8 1 Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81303, USA USDA-Wildlife Services, National Wildlife Research Center, 4101 La Porte Ave, Fort Collins, CO 80521, USA 3 The Nature Conservancy, 117 E Mountain Ave, Suite 201, Fort Collins, CO 80524, USA 4 Colorado State University, 1474 Campus Delivery, Fort Collins, CO 80523, USA 5 Nevada Department of Wildlife, 2788 Esaw Street, Minden, NV 89423, USA 6 Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, CO 80526, USA 7 Colorado Parks and Wildlife, 0088 Wildlife Way, Glenwood Springs, CO 81601, USA 8 Wildlife Conservation Society, 301 North Willson Ave, Bozeman, MT 59715, USA 2 Citation: Johnson, H. E., Breck, S. W., Baruch-Mordo, S., Lewis, D. L., Lackey, C. W., Wilson, K. R., Broderick, J., Mao, J. S., & Beckmann, J. P. 2015. Shifting perceptions of risk and reward: Dynamic selection for human development by black bears in the western United States. Biological Conservation 178:164–172. Abstract As landscapes across the globe experience increasing human development, it is critical to identify the behavioral responses of wildlife to this change given associated shifts in resource availability and risk from human activity. This is particularly important for large carnivores as their interactions with people are often a source of conflict, which can impede conservation efforts and require extensive management. To examine the adaptations of a large carnivore to benefits and risks associated with human development we investigated black bear behavior in three systems in the western United States. Our objectives were to (1) identify temporal patterns of selection for development within a year and across years based on natural food conditions, (2) compare spatial patterns of selection for development across systems, and (3) examine individual characteristics associated with increased selection for development. Using mixed effects resource selection models we found that bear selection for development was highly dynamic, varying as a function of changing environmental and physiological conditions. Bears increased their use of development in years when natural foods were scarce, throughout the summer-fall, as they aged, and as a function of gender, with males exhibiting greater use of development. While patterns were similar across systems, bears at sites with poorer quality habitat selected development more consistently than bears at sites with higher quality habitat. Black bears appear to use development largely for food subsidy, suggesting that conflicts with bears, and potentially other large carnivores, will increase when the physiological demand for resources outweighs risks associated with human activity. 29 �Human development and climate affect hibernation in a large carnivore with implications for human–carnivore conflicts Heather E. Johnson1, David L. Lewis1, Tana L. Verzuh1, Cody F. Wallace1, Rebecca M. Much1, Lyle K. Willmarth1, Stewart W. Breck2 1 Colorado Parks and Wildlife, Durango CO, USA USDA National Wildlife Research Center, Fort Collins, CO, USA 2 Citation: Johnson, H. E., D. L. Lewis, T. L. Verzuh, C. F. Wallace, R. M. Much, L. K. Willmarth and S. W. Breck. 2017. Human development and climate affect hibernation in a large carnivore with implications for human-carnivore conflicts. Journal of Applied Ecology, DOI:10.1111/1365-2664.13021 Abstract 1. Expanding human development and climate change are dramatically altering habitat conditions for wildlife. While the initial response of wildlife to changing environmental conditions is typically a shift in behaviour, little is known about the effects of these stressors on hibernation behaviour, an important lifehistory trait that can subsequently affect animal physiology, demography, interspecific interactions and human-wildlife interactions. Given future trajectories of land use and climate change, it is important that wildlife professionals understand how animals that hibernate are adapting to altered landscape conditions so that management activities can be appropriately tailored. 2. We investigated the influence of human development and weather on hibernation in black bears (Ursus americanus), a species of high management concern, whose behaviour is strongly tied to natural food availability, anthropogenic foods around development and variation in annual weather conditions. Using GPS collar data from 131 den events of adult female bears (n = 51), we employed fine-scale, animalspecific habitat information to evaluate the relative and cumulative influence of natural food availability, anthropogenic food and weather on the start, duration and end of hibernation. 3. We found that weather and food availability (both natural and human) additively shaped black bear hibernation behaviour. Of the habitat variables we examined, warmer temperatures were most strongly associated with denning chronology, reducing the duration of hibernation and expediting emergence in the spring. Bears appeared to respond to natural and anthropogenic foods similarly, as more natural foods, and greater use of human foods around development, both postponed hibernation in the fall and decreased its duration. 4. Synthesis and applications. Warmer temperatures and use of anthropogenic food subsides additively reduced black bear hibernation, suggesting that future changes in climate and land use may further alter bear behaviour and increase the length of their active season. We speculate that longer active periods for bears will result in subsequent increases in human–bear conflicts and human-caused bear mortalities. These metrics are commonly used by wildlife agencies to index trends in bear populations, but have the potential to be misleading when bear behaviour dynamically adapts to changing environmental conditions, and should be substituted with reliable demographic methods. 30 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Effects of hunting on a mountain lion population on the Uncompahgre Plateau, Colorado Period Covered: July 31, 2016−June 30, 2017 Principal Investigator: Kenneth A. Logan, Ken.Logan@state.co.us All information in this project summary is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulations of these data beyond that contained in this report is discouraged. We conducted a 10-year (2004−2014) study on effects of hunting on a mountain lion population on the Uncompahgre Plateau. The purpose was to examine lion demographics without and with hunting, and learn how lion hunter behavior may influence harvest and the lion population. This report summarizes the latest analysis of the effects of hunting and other causes of mortality on a lion population in preparation of this information for publication. Final analyses and writing are in final stages and are expected to provide reliable information for application of lion management in Colorado. The study was designed with a five-year reference period (years RY1−RY5) when mountain lion hunting was prohibited and a five-year treatment period (years TY1−TY5) with regulated hunting of lions. The reference period began December 2004 and ended October 2009. The treatment period began November 2009 and ended in December 2014. During the treatment period we surveyed lion hunters to learn about their participation in the hunting treatment and hunting preferences. The study area was on the Uncompahgre Plateau in Mesa, Montrose, Ouray, and San Miguel Counties. The 1,157 square mile study area included the southern halves of Game Management Units (GMUs) 61 and 62, and the northern edge of GMU 70. The Uncompahgre Plateau Study Area GMU (UPSA for short) was the 8th largest lion GMU in Colorado. The UPSA contained about 657 square miles of big game winter range where we focused our efforts to study lion demographics. We examined effects of hunting on mountain lions starting at the GMU scale because GMUs were used in Colorado to spatially distribute and regulate lion harvest to achieve specified population objectives at the much larger Data Analysis Unit (DAU) scale. Each GMU was assigned a lion hunting quota (i.e., harvest limit) as a portion of a target DAU lion harvest. Hunting in the GMU was closed when the lion quota was reached or the end of the hunting season, whichever came first. Prior to this research there was no information in Colorado indicating how lion harvest at the GMU scale related to lion management objectives at the larger DAU scale. From December 2, 2004 to October 30, 2014 we captured 256 individual mountain lions a total of 440 times. We individually marked 226 lions: 109 in the reference period and 115 in the treatment period. Marked lions provided known-fate data on 75 adults (2+ yr. old), 75 subadults (1−2 yr. old), and 118 cubs. In addition to the lions captured by our research team during the treatment period, lion hunters captured and killed a total of 35 lions, including 8 adult females, 16 adult males, 3 subadult females, and 8 subadult males. Lion hunters also reported capturing and releasing 30 lions, including 19 females and 11 males. We assessed effects of hunting on mountain lions based on changes in four variables: 1) abundance of independent lions (i.e., adults and subadults; legal game in Colorado), 2) survival of adult, subadult, and cub lions, 3) reproduction, including litter sizes, birth intervals, and birth rates, and 4) gender and age structure of the independent (>1 year old) lions. We estimated abundance of independent lions by using the ratio of marked lions in the population each winter that were re-detected in the population and applied that to the total number of lions caught each winter. The estimates included lions that were not observed, but expected to be present. We estimated survival for the marked samples of 31 �adults, subadults, and cubs and identified factors that best explained animal survival. We estimated reproduction rates by intensively monitoring adult females the year-round. We compared the gender and age structure of the lion population after five years of no hunting (start of TY1) and after four years of hunting (start of TY5). Mountain lion mortality and hunting In the reference period, mortality from natural causes, vehicle strikes and depredation control affected individual lions. However, the totality of the mortality did not inhibit population increase. The hunting treatment was intended to remove a 15% target harvest of independent lions on the UPSA during TY1−TY3 and 11−12% target harvest during TY4− TY5. These percentages were based on modeled lion abundance projections for TY1 and TY4. The observed (actual) harvest rates of independent lions on the UPSA based on the abundance estimates for TY1 and TY2 and associated with the decline in abundance of independent lions by TY3 ranged from 0.14−0.16. During TY3−TY5 the observed harvest rate on the UPSA ranged from 0.12−0.18. However, hunters killed 11 additional radio-collared independent lions (2 adult females, 8 adult males, 1 subadult female) in adjacent GMUs because those lions had home ranges beyond the UPSA boundaries. The number of marked lions killed by hunters outside of UPSA ranged from 0 to 5 and averaged 2 each year from TY1−TY5. These additional hunting deaths contributed to the demographic response of lions on the UPSA. Other causes of mortality, including natural causes, vehicle strikes and depredation control also affected independent lions in the treatment period. Considering all known deaths (i.e., from hunting, other human and natural causes) to independent lions in the treatment period hunting seasons on UPSA, total observed mortality during TY1−TY2 ranged from 0.16−0.18, and 0.14−0.23 during TY3−TY5. However, four adult females that died of natural causes on the UPSA were not detected by wildlife officials, but by our radiotelemetry monitoring. Just counting the deaths on UPSA that would have been detected by wildlife officials (i.e., harvest, depredation control) the total observed mortality during TY1−TY2 ranged from 0.16−0.18. Likewise, during TY3−TY5 the total observed mortality rates were 0.12−0.18. Mountain lion hunters overwhelmingly indicated they were selective hunters. They exhibited selectivity directly by harvesting mostly adult male lions and capturing and releasing mostly female lions. Furthermore, they exhibited selection even though they encountered fresh female tracks more frequently than male tracks. Mountain lion abundance Abundance of independent lions increased in the reference period (without hunting) from 33 in RY4 to 57 in TY1 at annual rates of 24% and 39% between RY4−RY5 and RY5−TY1, respectively (Fig. 1). In the treatment period (with hunting) estimates of independent lions were 57 and 56 in TY1 and TY2, respectively, and declined to a low of 37 by TY5. There was no apparent decline in abundance of independent lions until after TY2. Abundance declined by 21% between TY2 and TY3, and thereafter remained in a low phase to TY5. Survival of mountain lions Gender and period (i.e., reference and treatment) were important factors explaining adult and subadult male lion survival. Adult male survival was 0.96 (95% CI = 0.75−0.99) in the reference period and 0.40 (95% CI = 0.22−0.57) in the treatment period. Adult female survival was 0.86 (95% CI = 0.72−0.94) in the reference period and 0.74 (95% CI = 0.63−0.82) the treatment period. Subadult male survival was 0.92 (95% CI = 0.57−0.99) in the reference period and 0.43 (95% CI = 0.25−0.60) in the treatment period. However, subadult female survival was similar in the reference (0.63, 95% CI = 0.17−0.89) and treatment periods (0.70, 95% CI = 0.39−0.88). The most important factor explaining cub survival was survival of the dam during the time the cubs were dependent on her. The cub survival rate was 0.45 (95% CI = 0.303−0.587) for the reference and treatment periods combined. 32 �Mountain lion reproduction Reproduction rates, including litter sizes, birth intervals, and birth rates were not statistically different in the reference and treatment periods. Average litter size was 2.8 (95% CI = 2.4−3.1) for the reference period and 2.4 (95% CI = 2.0−2.8) for the treatment period. Average birth interval length in the reference period was 18.3 months (95% CI = 15.5−21.1), and for the treatment period was 19.4 months (95% CI = 16.2−22.6). Average birth rate (proportion of adult females giving birth each year) was 0.63 (95% CI = 0.49−0.75) for the reference period and 0.48 (95% CI 0.37−0.59) for the treatment period. Mountain lion gender and age structure After 5 years of no hunting, lions 1−5 years old comprised 66% of the independent lions; the other 34% were adult females and males 6−10+ years old. Adult males declined 62% between TY1 and TY5. In TY1 adult males over 5 years old comprised 43% of the adult males; but after 4 years of hunting 13% were over 5 years old (Fig. 2). Adult female abundance fluctuated from TY1−TY5 but with a declining trend. At the beginning of TY1 independent males averaged 4.2 years old (95% CI = 3.1−5.2), similar to the average of 4.4 years for adult females (95% CI = 3.4−5.3). By the start of TY5 the average age of independent males had declined to 2.9 years old (95% CI = 2.1−3.7); independent females averaged 4.5 years old (95% CI = 3.3−5.7), similar to TY1. Other important mountain lion demographics We estimated a minimum frequency of emigration of offspring (i.e., animals leaving the UPSA) by using the known fate data on the radio-collared cubs we used in the survival analysis. Of 37 cubs surviving to the subadult stage in the reference period at least 10 (9 males, 1 female) or 27% were known to have emigrated from the UPSA. Similarly, of 36 cubs surviving to subadult stage in the treatment period at least 9 (8 males, 1 female) or 25% were known to have emigrated from the UPSA. Most emigrating lions moved into other parts of western Colorado and eastern Utah, but extreme dispersals of lions were to southern Wyoming and northern New Mexico. Management Implications 1) Regulated hunting can affect mountain lion abundance. Harvest rates of 0.14−0.16 and observed human-caused mortality rates of 0.16−0.18 in two hunting seasons on the UPSA was associated with a decline in abundance of independent lions. 2) Additional hunting mortality of independent lions from the UPSA that ranged onto adjacent GMUs contributed to the decline of lions on the UPSA. Therefore, the expected hunting mortality rate from a harvest limit set at the GMU may be biased low. 3) Considering that the harvest of lions inside and outside the UPSA boundaries and emigration and apparent immigration all affected lion population response, lion management is better considered at scales larger than GMUs, such as DAUs or larger regions. Although GMUs could be used to address local lion management concerns, such as predation on wild ungulates or livestock, or to limit adult female lion harvest. 4) Dam survival was important to cub survival, supporting current regulation in Colorado protecting dams that are detected by hunters. In addition, regulations that limit adult female harvest could be used in areas with management objectives for lion conservation and hunting opportunity. 5) Lion hunters using dogs to catch lions can practice selection, affect the harvest and the lion population, and facilitate lion population management. 33 �Nc Estimated No. Independent Mountain Lions 65 60 55 50 45 40 35 30 25 20 15 10 RY4 RY5 No Hunting TY1 TY2 Study Winters TY3 TY4 TY5 Hunting Figure 1. Change in abundance (black dots) of independent mountain lions (i.e., adults and subadults) during reference year 4 (RY4) through treatment year 5 (TY5), Uncompahgre Plateau, Colorado. Bars represent 95% confidence intervals. We were sufficiently familiar with the study area to thoroughly search it for lion estimates by RY4; so lion abundance estimates span from RY4 to TY5. 34 �A 9 No. of Mountain Lions 8 7 6 5 4 3 2 Female 1 Male 0 1 to 2 >2 to >3 to >4 to >5 to >6 to >7 to >8 to >9 to 10+ 3 4 5 6 7 8 9 10 Age (years) B No. of Mountain Lions 6 5 4 3 Female 2 Male 1 0 1 to 2 >2 to >3 to >4 to >5 to >6 to >7 to >8 to >9 to 10+ 3 4 5 6 7 8 9 10 Age (years) Figure 3. Age structures of independent mountain lions in November, Uncompahgre Plateau, Colorado. Graph A shows the age structure after 5 years of no hunting and just before the first treatment hunting season (TY1). Graph B shows the change in age structure at the start of TY5 after 4 years of hunting lions (TY1─TY4). 35 �SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT 36 �Colorado Parks and Wildlife WILDLIFE RESEARCH REPORT SUMMARY Research library, annual report Period Covered: July 1, 2016– June 30, 2017 Author: Kay Horton Knudsen, kay.knudsen@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. The Colorado Parks and Wildlife Research Center Library has existed for several decades in the Ft. Collins office. However, the mission of the Library has expanded in recent years to serve all CPW staff regardless of location. The Library is now vital to the science-driven wildlife management work of the agency. The Librarian has become a valued partner in assisting with research and supplying full-text reference resources for the work done by biologists, researchers and wildlife managers across the state. Early librarians can be credited with the physical organization of the Library which continues to serve as the center for effective research services for employees, cooperators and wildlife educators. The goal of outreach and support is today fulfilled using technology to provide a Library website with the online catalog, wildlife databases and digitized documents. The website, available on CPWNet, is a 24/7 resource with 70 years of Colorado Federal Aid reports, online access to numerous wildlife journals and databases, as well as an index to the unique book collection. The Federal Aid reports are required by the Pittman-Robertson (Terrestrial) and Dingell-Johnson (Aquatic) Acts; federal funding awarded to the State of Colorado for wildlife and sport fish restoration. CPW may be the only wildlife agency to have digital access in the form of full-text, word-searchable PDFs, for this important collection. The Library is also an archive for historic CPW publications including 80 years of Wildlife Commission minutes and Director’s reports beginning in 1877. The special collection of original Colorado hunting and fishing brochures, some digitized, serve as a history of our rules and regulations and are often accessed by staff. As of October 2017, the Research Library held 19,966 cataloged titles and 29,395 items (these are the multiple copies of a title) and had 183 registered patrons (CPW staff). As part of the project to digitize CPW documents, the equivalent of 9GB of data has been scanned and uploaded to the catalog vendor. Current wildlife databases include BioOne, four of EBSCO’s specialty databases (Environment Complete, Fish and Fisheries Worldwide, Wildlife and Ecology Studies Worldwide and CAB Abstracts), Birds of North America, ProQuest Dissertations and Theses and the JSTOR Life Sciences collection. Online subscriptions to the major wildlife journals continue to be a primary usage entry point. CPW staff statewide are authenticated through CPWNet (intranet) eliminating the need for individual usernames and passwords. As a form of outreach to staff and stakeholders, the Research branch has made an effort to restart the Technical Publication series. The Librarian was involved in editing and proofreading as well as coordinating publications on Cyprinid fish larvae (written by staff at CSU’s Larval Fish Lab), Field investigations of mortality in mule deer, the Upper Arkansas River habitat restoration project and others currently in process. The Library website provides more full-text resources than ever before, however there are also more abstract-only indexes. A major role of the Librarian is to assist CPW staff with document delivery and research assistance. The Library is not open on a walk-in basis to the general public but the Librarian does assist the Denver Help Desk and area staff with questions they receive from citizens. The Librarian has Affiliate Faculty status with the Colorado State University Library which provides access to the large 37 �natural resources and science collection at that facility. The chart below shows the number of reference questions and document requests handled by the Librarian each month during the past 9 years. Please note that one request from a CPW staff member may be for multiple journal or book titles. A new record for the most requests in a month was set in January 2017*. Table 1. 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Center, 317 West Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NO BE PUBLISHED OR QUOTED without permission of the Author(s). By providing these summaries, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain confidentiality of ongoing research projects. CRS § 24-72-204. COLORADO PARKS AND WILDLIFE RESEARCH POLICY AND PLANNING BRANCH ii �EXECUTIVE SUMMARY This Wildlife Research Report represents summaries (≤6 pages each with tables and figures) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) from July 2018 through June 2019. These research efforts represent long-term projects (4–10 years) in various stages of completion addressing applied questions to benefit the management and conservation of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx or from the project principal investigators listed at the beginning of each summary. Current research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to habitat alterations, human-wildlife interactions, and investigating improved approaches for wildlife and habitat management. The Nongame Mammal Conservation Section addresses preliminary results of a recent project addressing influence of forest management practices on snowshoe hare density in Colorado. The Ungulate and Habitat Conservation Section includes 4 projects addressing mule deer/energy development interactions to inform future development planning, vegetation and animal responses to habitat treatments applied to mitigate energy development activity, evaluation of moose demographic parameters that will inform future moose management in Colorado, and a recent study to identify factors influencing elk calf recruitment. The Support Services Section describes the CPW library services to provide internal access of CPW publications and online support for wildlife and fisheries management related publications. In addition to the ongoing project summaries described above, Appendix A includes 18 publication abstracts (<1 page summaries) completed by CPW mammals research staff since July 2018. These scientific publications provide results from recently completed CPW research projects and other outside collaborations with universities and wildlife management agencies. Topics addressed include mammal responses to beetle-killed forests in Colorado, lynx response to winter recreation, carnivore ecology and management (factors limiting mountain lion populations, lion movements and human interactions along the urban-wildland interface; evaluation of Colorado’s 2-strike black bear management directive; assessment of garbage storage and social dynamics associated with black bear management along the urban-wildland interface), ungulate ecology and management (evaluating elk-livestock brucellosis transmission risk, applying acoustic technology to address mule deer foraging behavior, using GPS data to identify mule deer birth sites), remote camera sampling (application to estimate a low density bobcat population, and development of machine learning technology to enhance photo processing time), and genetics and disease research (interpretation of black bear telomere length, virus detection from fecal DNA, and mountain lion gene flow and genetic diversity). We have benefitted from numerous collaborations that support these projects and the opportunity to work with and train wildlife technicians and graduate students that will likely continue their careers in wildlife management and ecology in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, Idaho State University, University of Wisconsin-Madison, Montana State University, U.S. Bureau of Land Management, U.S. Forest Service, City of Boulder and Jefferson County Open Space, City of Durango, CPW big game auction-raffle grants, Species Conservation Trust Fund, GOCO YIP internship program, CPW Habitat Partnership Program, Safari Club International, Boone and Crocket Club, Colorado Mule Deer Association, The Mule Deer Foundation, Muley Fanatic Foundation, Wildlife Conservation Society, Summerlee Foundation, EnCana Corp., ExxonMobil/XTO Energy, Marathon Oil, Shell Exploration and Production, WPX Energy, and private land owners providing access to support field research projects. iii �STATE OF COLORADO Jered Polis, Governor DEPARTMENT OF NATURAL RESOURCES Dan Gibbs, Executive Director PARKS AND WILDLIFE COMMISSION Michelle Zimmerman, Chair.…………………………………………………………………. Breckenridge Marvin McDaniel, Vice-Chair.…………………………………………………………………….... Sedalia James Vigil, Secretary…………………………………………………………..………………......Trinidad Taishya Adams……………………………………………………………………………………… Boulder Betsy Blecha……………………………………………………………………………………………Wray Robert Bray…………………………………………………………………………………………. Redvale Charles Garcia……………………………………………………………………………………….. Denver Marie Haskett ……………………………………………….………….….………………............... Meeker Carrie Besnette Hauser….……………………………………………………………….. Glenwood Springs Luke B. Shafer………………………………………………………………………………………… Craig Eden Vardy…………………………………………………………………………………………… Aspen Kate Greenberg, Dept. of Agriculture, Ex-officio….………………………………..…….……….. Durango Dan Gibbs, Executive Director, Ex-officio……….…………………...………………….……..........Denver DIRECTOR’S LEADERSHIP TEAM Dan Prenzlow, Director Reid DeWalt, Heather Dugan, Justin Rutter Margret Taylor, Gary Thorson, Jeff Ver Steeg, Cory Chick, Brett Ackerman, JT Romatzke, Mark Leslie MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Wildlife Researcher Alexandria Austermann, Research Librarian Eric Bergman, Wildlife Researcher Michelle Gallagher, Program Assistant Jake Ivan, Wildlife Researcher Ken Logan, Wildlife Researcher Nathaniel Rayl, Wildlife Researcher iv �TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS NONGAME MAMMAL CONSERVATION INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO by J. Ivan and E. Newkirk …...2 UNGULATE AND HABITAT CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson .………………………………………………………………..6 VEGETATION AND CAMERA DATA TO ACCOMPANY THE STUDY ‘Population performance of Piceance Basin mule deer in response to natural gas resource selection and mitigation efforts to address human activity and habitat degradation’ by D. Johnston and C. Anderson…………………………………………………………………………………………. 11 EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO by E. Bergman ..………………………………….17 EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO by N. Rayl, M. Alldredge, and C. Anderson….………………………………………………………... 21 SUPPORT SERVICES LIBRARY SERVICES by A. Austermann.…….……………………………...………………… 26 APPENDIX A. MAMMALS RESEARCH PUBLICATION ABSTRACTS MAMMAL RESPONSES TO BEETLE-KILLED FORESTS IN COLORADO……………….. 28 LYNX RESPONSE TO WINTER RECREATION (2 publications)……………………………. 29 CARNIVORE ECOLOGY AND MANAGEMENT (3 mt. lion publications addressing factors limiting populations, lion-human interactions, and movement behavior along the urban interface; 4 black bear publications addressing Colorado’s 2-strike management directive, and evaluation of garbage storage and the social dynamics of black bear management along the urban interface.... 31 UNGULATE ECOLOGY AND MANAGEMENT (3 publications evaluating elk-livestock brucellosis transmission risk, auditory technology to investigate mule deer foraging behavior, and application of GPS data to identify mule deer birth site)…............................................................35 REMOTE CAMERA SAMPLING (2 publications addressing estimation of a low-density bobcat population, and development of machine learning to enhance photo processing time)…………. 37 GENETICS AND DISEASE RESEARCH (3 publications from university collaborations evaluating black bear telomeres, viruses from fecal DNA, and mt. lion genetics)……………….39 v �NONGAME MAMMAL CONSERVATION INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO 1 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Influence of forest management on snowshoe hare density in lodgepole and spruce-fir systems in Colorado Period Covered: July 1, 2018  June 30, 2019 Principal Investigators: Jake Ivan, Jake.Ivan@state.co.us; Eric Newkirk, Eric.Newkirk@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. Understanding and monitoring snowshoe hare (Lepus americanus) density in Colorado is important because hares comprise 70% of the diet of the state-endangered, federally threatened Canada lynx (Lynx canadensis; U.S. Fish and Wildlife Service 2000, Ivan and Shenk 2016). Forest management is an important driver of snowshoe hare density, and all National Forests in Colorado are required to include management direction aimed at conservation of Canada lynx and snowshoe hare as per the Southern Rockies Lynx Amendment (SRLA; https://www.fs.usda.gov/detail/r2/landmanagement/ planning/?cid= stelprdb5356865). At the same time, Forests in the Region are compelled to meet timber production and management response obligations. Such activities may depress snowshoe hare density, improve it, or have mixed effects dependent on the specific activity and the time elapsed since that activity was initiated. Here we describe a sampling scheme to assess impacts of common forest management techniques on snowshoe hare density in both lodgepole pine and spruce-fir systems in Colorado. To select forest stands for sampling, we first used U. S. Forest Service (USFS) spatial data to delineate all spruce-fir and lodgepole pine stands (stratum 1) on USFS land in Colorado, and identified all of the management activities that have occurred in each stand over time. With consultation from the USFS Region 2 Lynx-Silviculture Team, we then grouped relevant forest management activities (stratum 2) into 4 broad categories: even-aged management, uneven-aged management, thinning, and unmanaged controls. We wanted to assess both the immediate and long-term impacts of management on hare densities. Therefore, when selecting stands for sampling, we took the additional step of binning the date of the most recent management activity into 2-decade intervals (i.e., 0-20, 20-40, and 40-60 years before 2018). We then selected a spatially balanced random sample of 5 stands within each combination of forest type × management activity × time interval. This design ensured that we sampled the complete gradient of time since implementation for each management activity of interest in each forest type of interest. There is no notion of “completion date” for unmanaged controls, so we simply sampled 10 randomly selected stands from this combination. Also, uneven-aged lodgepole pine treatments are rare, so we did not sample that combination, leaving a total of n = 105 stands sampled (Figure 1). During summer 2018, we established n = 50 1-m2 permanent circular plots within each of the n = 105 stands selected for sampling. Plot locations within each stand were selected in a spatially balanced, random fashion. Technicians cleared and counted snowshoe hare pellets in each plot as they were established. These same plots were re-visited and re-counted during summer 2019. In addition to sampling the previously cleared plots from 2018, technicians were able to install plots at 2 more replicate sites for each combination of forest type × management activity × time interval, meaning that inference 2 �from future years will be based on 7 stands within each combination, or n = 128 total stands (note that this total also reflects a handful of stands that were re-classified based field observations, along with new stands that were brought into the sample in 2019 to replace those that were reclassed). Pellet information from cleared plots is more accurate than that from uncleared plots because uncleared plots usually include pellet accumulation across several years (Hodges and Mills 2008). The degree to which previous years are represented can depend on local weather conditions, site conditions at the plot, and variability in actual snowshoe hare density over previous winters. Data from cleared plots necessarily reflects hare activity from the previous 12 months, and tracks true density more closely. Therefore, we focused the current analysis on the 2019 data from previously cleared plots. For each forest type × management activity combination, we plotted mean pellet counts against “year since activity,” then fit a curve (e.g., quadratic function) through the data (Figure 2). Results from this preliminary analysis suggest that on average the highest snowshoe hare densities typically occur in unmanaged spruce-fir forests, and that unmanaged spruce-fir forests are estimated to have twice the relative hare density of unmanaged lodgepole pine forests. For both forest types, the fitted line suggests that even-aged management (e.g., clearcutting), immediately depresses relative hare density to near zero, but density rebounds and peaks 20-40 years after management before declining again 40-60 years after. Estimated peak hare densities after even-aged management in lodgepole systems tend to be higher than the control condition, but in spruce-fir systems estimated peak densities approach, but never match, the control condition. In both forest types, thinning (which often occurs 20-40 years after stands undergo even-aged management, especially in lodgepole), immediately depresses hare densities, but densities are estimated to slowly recover through time in nearly linear fashion, reaching their maximum 45-55 years after the treatment. As with the even-aged treatment, maximum hare density after thinning in lodgpole systems is estimated to be higher than the control condition, whereas in spruce-fir systems, the maximum hare density matches that of the control sites. Uneven-aged management of spruce-fir forests results in a similar snowshoe hare trajectory as that observed in thinned spruce-fir forests. Note the two outliers on the right side of the even-aged lodgepole panel. These “high density” sites are represent even-aged lodgepole stands that happen to be surrounded by high quality spruce-fir forest on at least two sides. Thus, the high relative hare density observed at these sites may be due to the quality habitat in adjacent stands rather than by the quality of the sampled stands themselves. While we left them on the figure for transparency, we excluded them when fitting the curve as they appear to be true outliers. Also note that in some cases, 95% CIs are relatively large and overlap the control reference line in some panels. Thus, even though the fitted lines indicate the relationships discussed above, evidence for some of these patterns is moderate or weak. In future years, each panel will include cleared plot data from 6 additional sites, and each site will have data from multiple years (i.e., repeated measures). Both phenomena will greatly improve sample sizes, diminish the role of a few outlying data points, and tighten up our estimate, and corresponding inference, regarding the response of snowshoe hare density to forest management through time. Literature Cited: Hodges, K. E., and L. S. Mills. 2008. Designing fecal pellet surveys for snowshoe hares. Forest Ecology and Management 256:1918-1926. Ivan, J. S., and T. M. Shenk. 2016. Winter diet and hunting success of Canada lynx in Colorado. The Journal of Wildlife Management 80:1049-1058. U.S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: determination of threatened status for the contiguous U. S. distinct population segment of the Canada lynx and related rule, final rule. Federal Register 65:16052–16086. 3 �Figure 1. Location of all stands (n = 105) resampled for snowshoe hare pellets, June-September 2019. Unmanaged Q) 0 0.. .._. Cl) Uneven-aged Thinned 12 12 12 12 ·a. 10 10 10 10 C .._. Even-aged Q) 0 8 c.. 6 Cl -0 0 ....J 4 Q) Q) 0 0 , 60 0 0 Q) 10 20 30 40 50 60 0 0 10 20 30 40 50 60 0 10 20 30 40 50 60 0 10 20 30 40 50 60 0.. C ro Q) ~ .... ch (.) ::::J .... c.. ~ C/) 12 12 12 12 10 10 10 10 8 6 6 4 4 0 0 >60 0 0 10 20 30 40 50 60 0 10 20 30 40 50 60 Years Since Treatment Figure 2. Fitted quadratic function (white line) and 95% CI (shaded polygon) relating pellet counts (i.e., relative snowshoe hare density) to time elapsed since treatment for each forest type × management activity combination. Dotted lines indicate the mean pellets/plot for the unmanaged controls for each forest type. 4 �UNGULATE AND HABITAT CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACRIVITY AND HABITAT DEGRADATION VEGETATION AND CAMERA DATA TO ACCOMPANY THE STUDY ‘Population performance of Piceance Basin mule deer in response to natural gas resource selection and mitigation efforts to address human activity and habitat degradation’ EVALUATION AND INCORPORATION OF LIGE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO 5 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation Period Covered: July 1, 2018–June 30, 2019 Principal Investigator: Charles R. Anderson, Jr., Chuck.Anderson@state.co.us Collaborators: Colorado Parks and Wildlife, BLM-White River Field Office, Idaho State University, Colorado State University, Federal Aid in Wildlife Restoration, EnCana Corp., ExxonMobil Prod. Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, WPX Energy, Colorado Mule Deer Assn., Muley Fanatic Found., Colorado Mule Deer Found., Colorado State Severance Tax Fund, Boone & Crocket Club, and Safari Club Int. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent preliminary and final results of a 10-year research project addressing habitat improvements and evaluation of energy development practices intended to improve mule deer fitness in areas exposed to extensive energy development. We monitored deer on 4 winter range study areas representing relatively high (Ryan Gulch, South Magnolia) and low (North Magnolia, North Ridge) levels of development activity (Fig. 1) to address factors influencing deer behavior and demographics and to evaluate success of habitat treatments as a mitigation option. We recorded habitat use and movement patterns, estimated annual neonatal, overwinter fawn and annual adult female survival, estimated annual early and late winter body condition of adult females, and estimated annual abundance among study areas. Winter range habitat improvements completed spring 2013 resulted in 604 acres of mechanically treated pinion-juniper/mountain shrub habitats in each of 2 treatment areas (Fig. 2) with minor (North Magnolia) and extensive (South Magnolia) energy development, respectively. During this research segment, we removed store-on-board GPS collars from adult female mule deer, addressed mule deer winter concentration areas during a post-drilling production phase, measured vegetation response of habitat treatment sites and established camera grids to address summer/fall use of habitat treatments (see next research summary). Based on final (migration, mule deer behavioral responses, reproductive success and neonate survival) and preliminary data analyses for this 10-year project: (1) annual adult female survival was consistent among areas averaging 79-87% annually, but overwinter fawn survival was variable, ranging from 31% to 95% within study areas, with annual and study area differences primarily due to early winter fawn condition, annual weather conditions, and factors associated with predation on winter range; (2) mule deer body condition early and late winter was generally consistent within 6 �areas, with higher variability among study areas early winter, primarily due to December lactation rates, and late winter condition related to seasonal moisture and winter severity; (3) late winter mule deer densities increased through 2016 in all study areas, ranging from 50% in North Ridge to 103% in North Magnolia, but have stabilized recently in 3 of the 4 study areas with recent decline evident in North Ridge (Fig. 3); (4) migratory mule deer selected for areas with increased cover and increased their rate of travel through developed areas, and avoided negative influences through behavioral shifts in timing and rate of migration, but did not avoid development structures (Fig. 4); (5) mule deer exhibited behavioral plasticity in relation to energy development, where disturbance distance varied relative to diurnal extent and magnitude of development activity, which may provide for several options in future development planning (Fig 5); and (6) energy development activity under existing conditions did not influence pregnancy rates, fetal rates or early fawn survival (0-6 months), but may have reduced neonatal survival (March until birth) when drought conditions persisted during the third trimester of doe parturition (Fig. 6). Final results are pending to address vegetation and mule deer responses to assess habitat treatment mitigation options for energy development planning, and final results addressing the interaction of mule deer behavioral and demographic factors associated with energy development activity have recently been submitted for scientific peer-review and publication. Final data collection addressing GPS collar recovery and summer/fall use of habitat treatment sites will be completed by December 2019. Completion of this project, including data analyses and interpretation of results, is anticipated by fall/winter 2020-21. r study areas Well Pads & Facilities rth Magnolia ! In development l Producing well E Development facilities uth Magnolia rth Ridge 10 Miles Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, winter 2013/14 (Accessed http://cogcc.state.co.us/ December 31, 2013; energy development activity has been minor since 2013). 7 �North Magnolia treatement si tes (587 acres) CJ 8earSet_15_35b_andG CJ BearSet_1_8andA_E D BearSet_36_54andJ n GreasewoodSet_g16_g29 GreasewoodSet_g1 _g 15 CJ GreasewoodSet_g30_g42 LeeOversights_ a_fand16_ 17 Mechanical tre atment comparison (54 acres) - - North Hatch PilotTreatments (116 acres) Figure 2. Habitat treatment site delineations in 2 mule deer study areas (604 acres each) of the Piceance Basin, northwest Colorado (Top; cyan polygons completed Jan 2011 using hydro-axe; yellow polygons completed Jan 2012 using hydro-axe, roller-chop, and chaining; and remaining polygons completed Apr 2013 using hydro-axe). January 2011 hydro-axe treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 8 �Piceance Basin late winter mule deer density 35.00 30.00 Deer/km2 25.00 20.00 North Ridge 15.00 Ryan Gulch 10.00 North Magnolia 5.00 South Magnolia 0.00 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Year Figure 3. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2018. Figure 4. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012; http://dx.doi.org/10.1890/ES12-00165.1). 9 �"'I Prod 400 Prod 600 Prod 800 Prod 1000 Drill 400 Drill 600 Drill 800 Drill 1000 Drill 600 Drill 800 Drill 1000 Covariates 0 ' N I "'I Prod 400 Prod 600 Prod 800 Prod 1000 Drill 400 Figure 5. Posterior distributions of population-level coefficients related to natural gas development for RSF models during the day (top) and night (bottom) for 53 adult female mule deer in the Piceance Basin, northwest Colorado. Dashed line indicates 0 selection or avoidance (below the line) of the habitat features. ‘Drill’ and ‘Prod’ represent drilling and producing well pads, respectively. The numbers following ‘Drill’ or ‘Prod’ represent the distance from respective well pads evaluated (e.g., ‘Drill 600’ is the number of well pads with active drilling between 400–600 m from the deer location; from Northrup et al. 2015; http://onlinelibrary.wiley.com/doi/10.1111/gcb.13037/abstract). Road disturbance was relatively minor (~60–120 m, not illustrated above). 1.00 ~ ' 0.80 - - -- + (1) ro L.. co > 0.60 -~ ::::l (/) ro 0.40 a, LL 0.20 0.00 2012 2013 2014 Year □ High development □ Low development I Figure 6. Model averaged estimates of mule deer fetal survival from early March until birth (late May– June) in high and low energy development study areas of the Piceance Basin, northwest Colorado, 2012– 2014 (from Peterson et al. 2017; http://www.bioone.org/doi/pdf/10.2981/wlb.00341). 10 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Vegetation and camera data to accompany the study ‘Population performance of Piceance Basin mule deer in response to natural gas resource selection and mitigation efforts to address human activity and habitat degradation’ Period Covered: July 1, 2012–June 30, 2019 Principal Investigators: Danielle Johnston (Danielle.bilyeu@state.co.us), Chuck Anderson (Chuck.Anderson@state.co.us) Collaborators: Colorado Parks and Wildlife, BLM-White River Field Office, Idaho State University, Colorado State University, Federal Aid in Wildlife Restoration, EnCana Corp., ExxonMobil Prod. Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, WPX Energy, Colorado Mule Deer Assn., Muley Fanatic Found., Colorado Mule Deer Found., Colorado State Severance Tax Fund, Boone & Crocket Club, and Safari Club Int. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In 2011 and 2013, about 1,200 acres of pinyon and juniper (PJ) mastication treatments were completed in the Magnolia region of the Piceance Basin. Treated parcels averaged 7 acres in size, and were intended to increase winter range quality for deer. The treatments were part of a study to evaluate the effectiveness of PJ removal as mitigation for impacts of natural gas development on deer, with outcomes assessed in terms of deer population and demographic parameters. This summary addresses some side questions relevant to the main study, with outcomes assessed in terms of vegetation response and animal use of vegetation treatments. We were interested in quantifying the understory forage produced by the mastication treatments. We used paired masticated/control point-intercept transects on a subset of parcels (Graham 2013) to quantify cover of plant groups relevant to deer nutrition. We used belt transects and trained ocular estimation, with benchmarks (Johnston 2018), to estimate summer utilization on individual shrubs, then scaled these to the plot level (Bilyeu, Cooper et al. 2007). We used belt transects of shrub canopy measurements, coupled with biomass equations developed for the study area (Johnston 2018) to quantify winter forage production of key browse species. Winter forage production was defined as current-year stems, not including leaves, not including biomass removed by summer browsing, and not including very small stems which would likely be shed prior to winter (Johnston 2018). We were interested in how summer use of treatments, and use of treatments by non-target animals, impacted winter forage availability. Ten cattle exclosures, distributed broadly throughout the study area (Figure 1), were built within mastication treatments in 2011 and 2013. We assessed plant cover and summer shrub utilization within these using techniques described above. On paired masticated/control transects, we deployed Reconyx Hyperfire cameras July-November 2018-2019. These were programmed to facilitate creating an index of use: 5 pictures per motion trigger, 3 second interval between pictures, a 5 minute wait time between triggers, and a sensitivity setting of High (Rhodes, Larsen et al. 2018). An animal observed with their head down or other indication of foraging in one or more of 11 �the photos in a 5 photo set was counted as one foraging event, and non-foraging occurrences were counted similarly. Sampling efforts by year are given in Table 1. Because the plant cover data contained many zeros, we modeled presence/absence of each plant group separately from its cover where present (Fletcher, Mackenzie et al. 2005), using the lme4 package in R (Bates 2005). For both analyses, treatment, year, and their interaction were considered fixed effects, year was included as a categorical variable, and pair ID and plot ID were included as random effects. We used a similar approach for camera data for cattle and elk, which also contained many zeros. In general, grasses responded positively to treatment (Figure 2a). Wheatgrass presence, wheatgrass cover, and needlegrass presence were higher in treated than untreated plots. Poa grass presence was higher in treated plots by 2018, although poa grass presence and cover initially had a negative response to treatment. Cheatgrass presence also responded positively to treatment (Figure 2a). Wheatgrasses, poa species, and cheatgrass all had significant year*treatment interactions for either presence or cover. Interannual variation in cover was greater in masticated plots than in control plots for these species groups (Figure 2a). Forbs responded positively to treatment. Annual forb and perennial forb presence were higher in treated than untreated plots (Figure 2b). Some shrubs responded positively to treatment, while others did not. Snowberry cover was lower in treated plots in 2013, but in 2016 and 2018, cover was higher in treated plots (Figure 2c). Variation in snowberry cover was greater in masticated than in control plots (Figure 2c). Bitterbrush did not display any significant effects until 2018, when cover was higher in treated plots (Figure 2c). Serviceberry cover was lower in treated plots over all years (Figure 2d). Sagebrush cover was initially lower in treated plots, but by 2018 this difference was no longer significant (Figure 2d). Summer utilization of serviceberry and mountain mahogany in 2018 was significantly higher in masticated than in control plots, but no differences were detected in bitterbrush or sagebrush. Winter forage production, which was summed over serviceberry, mountain mahogany, and bitterbrush, was significantly higher in masticated plots than in unmasticated plots in all years except 2016, when the pattern was reversed (Figure 3). There was no significant effect of exclosures on any plant cover group or on summer utilization in 2018. Deer, horse, elk, and cattle all foraged more often in masticated plots than in controls in 2018 (Figure 4). Cattle were only observed foraging at 6 of 20 locations, horse were observed at 9, deer at 19, and elk at 6. Mastication treatments had many positive effects on forage availability, including higher cover of desirable grass groups such as poa grasses and wheatgrasses, higher cover of perennial forbs, and usually higher productivity of winter-available shrub forage. There were some negative effects and some differences in effects among years, however. Cheatgrass was higher in masticated plots than in controls, and snowberry cover was higher in masticated plots in 2016 and 2018. 2016 was an unusual year compared to other years of this study, with very high productivity of grasses (including cheatgrass, especially in masticated plots), and unusually high productivity of winter-available forage of desirable shrubs in control but not masticated plots. Summer shrub utilization in 2018 was higher in masticated plots than in controls. We lack any data on utilization from 2016, which might have helped explain if the lower production of winteravailable forage in masticated plots was due to higher summer utilization in those plots that year. Another explanation for the 2016 results is that good conditions for grass, cheatgrass, and/or snowberry productivity in masticated plots led to increased competition which lessened productivity of desirable forage shrubs. All four of the large herbivores of interest foraged more frequently in summer and fall in masticated plots than in control plots in 2018. The impact of cattle was concentrated in only a few plots, but they did forage frequently in plots where they occurred. Cattle use ended in September, prior to the period of heavy use by deer in October. The data from the cattle exclosures does not indicate that cattle are having any measurable negative effect on forage resources. In summary the impact of cattle on the 12 �forage resources available to deer in mastication treatments seems minimal. However, the effect of the sum of cattle, horse, and elk foraging may have some impact. In 2019, we collected vegetation data and camera data. 2019 is the last year of data collection for this study, and final analyses will be incorporated into publications in 2020-21. Literature Cited: Bates, D. (2005). "Fitting linear mixed models in R." R news 5(1). Bilyeu, D. M., D. J. Cooper and N. T. Hobbs (2007). "Assessing impacts of large herbivores on shrubs: tests of scaling factors for utilization rates from shoot-level measurements." Journal of Applied Ecology 44(1): 168-175. Fletcher, D., D. D. Mackenzie and E. Villouta (2005). "Modelling skewed data with many zeros: a simple approach combining ordinary and logistic regression." Environmental and ecological statistics 12: 45-54. Graham, T. (2013). Magnolia habitat manipulation project vegetative monitoring: June 2013 notes on data collection and methods used, Ranch Advisory Partners, LLC: 7. Johnston, D. B. (2018). Wildlife Research Report: Examining the effectiveness of mechanical treatments as a restoration technique for mule deer habitat. Fort Collins, CO, Colorado Parks and Wildlife. Rhodes, A. C., R. T. Larsen and S. B. S. Clair (2018). "Differential effects of cattle, mule deer, and elk herbivory on aspen forest regeneration and recruitment." Forest Ecology and Management 422: 273-280. Table 1. Number of transects sampled for a given data type each year. Variables quantified 2011 2012 2013 2014 2015 2016 2018 Percent cover of plant functional groups 90* 2019 69 107† 40 (camera sites) 63 75† 75† Summer utilization of bitterbrush, serviceberry, mountain mahogany, and sagebrush 75† 75† Index of deer, elk, horse, and cattle use in summer and fall, as determined by trail camera (EventsPerDay) 40 40 (2 cameras each) (2 cameras each) 90* 159 145 70† Winter-available forage of bitterbrush, serviceberry, mountain mahogany (ShrubMassPerArea) 27† * Pretreatment data collected 2011-2012 will be added to a later report. †Includes 24-30 locations taken at exclosure sites. 13 �Legend Cameras CamerasAsDeployedJuly2018 Cover data MagnoliaHydroAxSitesToSample Exclosure sites ExclosureSites Figure 1. Sampling locations within the Magnolia region of the Piceance Basin. 14 �a ....Q) b 10.0 - cheq~rass +, P , , , '' 15 - > 0 7.5 - 0 u c 5.o wh~.iir;ss +, PC , , ' c a> Q) ~ ~ ..,, , Q) 0.. ' , ~ 10 - ._ Q) > perennial forb +, P 5- " \ ~ ~ ~ Q) ' 0.. ~' o- 2.5 - 0.0 I I I I I I I I 2013 2014 2016 2018 2013 2014 2016 2018 year year C d 8- ....Q) 9 - cu 6 - s > 0 u > 0 u a> ~ 4 _ sa c 6~ ~ Q) Q) 0.. 0.. 3- 2- I I I I I I I I 2013 2014 2016 2018 2013 2014 2016 2018 year year Figure 2. Cover of some plant functional groups and species important for evaluating habitat quality. Dashed lines indicate masticated plots and solid lines are controls. A “+” or “-“ sign indicates significant positive or negative main effect of mastication across years (α = 0.05). “P” indicates that the significant effect was observed in the presence/absence analysis, and “C” indicates a significant effect in the cover-where-present analysis. 15 �Winter-available forage per unit shrub area (g/m2) 20 - Treatment control - • - masticated 90- * * 60- * * 30- 2013 2014 2015 2016 2018 year Figure 3. Mass of winter-available forage (current-year stem mass measured in September, not including leaves or mass removed by summer browsing) per unit shrub area. Data are summed over serviceberry, mountain mahogany, and bitterbrush. N=8 for 2013 and 2015 and 25-31 for other years. No transects inside fences were included. Error bars = SE. Stars indicate significant differences at alpha = 0.05 Foraging, near camera Not foraging , near camera * a b 75 - >- 75- ro 0 ,_ Q) a.. ro I Treatment 50 - <ii 50 - a.. ■ ■ 1/) 'E Q) > w Ol -~ 250> † ~ * control masticated 25 - * 0 u_ o- o' cattle ' elk ' horse mule' deer ' cattle Herbivore ' elk ' horse mule' deer Herbivore Figure 4. a) Average number of foraging events per hectare per day between mid-July and midNovember, 2018 in control versus masticated plots. Stars indicate significant differences at α = 0.05. † indicates a significant difference in presence of foraging events. b) Average number of non-foraging observations per hectare per day. 16 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation and incorporation of life history traits, nutritional status, and browse characteristics in Shira’s moose management in Colorado Period Covered: July 1, 2018  June 30, 2019 Principal Investigator: Eric J. Bergman, eric.bergman@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. During November of 2013 we initiated a large scale moose research project in 3 of Colorado Parks and Wildlife’s 4 geographical regions (NE, NW, and SW). After 3 field seasons this research was scaled back and became focused on moose herds in the NW (North Park) and NE (Laramie River) Regions. During FY 20-21 this research project will be completed. A primary objective during all years of this project was the capture of adult female moose for the purposes of deploying VHF and GPS collars, collecting pregnancy data via blood serum, evaluating body condition via ultrasonography, and collecting early winter calf-at-heel ratios. Beginning in 2014–2015 and continuing through the summer of 2019, summer field efforts focused on estimation of parturition rates. Between November 2013 and January 2019, 255 moose were captured. These 255 capture events were comprised of 178 unique individuals and 78 recaptures. During winter of 2018–2019, 36 cow moose were captured. Of these 36 animals, 21 were captured in NW Colorado (8 recaptures and 13 new individuals) and 15 were captured in NE Colorado (7 recapture and 15 new individual). Individual animals were recaptured to meet 2 objectives. First, most animals were fitted with GPS collars that have limited battery life. Recapture of individuals allowed replacement of older collars with newer collars that had longer battery life. The second objective was to establish a longitudinal data set that will allow us to determine long-term productivity of individual animals. In particular, repeated measurements of individuals will allow us to evaluate if different reproductive strategies occur within moose, and if those strategies can be linked to annual variation within individual condition. During the 2018–2019 winter, measured rump fat at the time of capture ranged between 0–11 mm among study areas. Measured loin depth at the time of capture ranged between 27–63 mm among study areas. Measured loin fat, at the time of capture, ranged between 0–5 mm. In comparison to the winter of 2017–2018, the values observed during 2018–2019 were consistently lower, but still within the range of expected values. Over the course of this study, we have observed that the probability of moose being pregnant was best predicted by considering maximum loin depth. Regional and annual effects in pregnancy rates were not evaluated. As has been the case during all years of the study, survival of radio collared animals was high in all study areas (85%–96%). During 2018–2019 pregnancy rates were similar between areas (70% in NW Colorado, 60% in NE Colorado), but strong inference was limited by samples size. However, in comparison to the preceding 5 winters of data collection, observed pregnancy rates between 60%–70% during 2018–2019 were consistent long-term rates. Over the course of this study, calf-at-heel estimates at the time of capture have average 0.55. During 2018–2019, the observed calf-at-heel rates in both NW Colorado (0.24) and NE Colorado (0.43) were lower than average. Beginning summer 2017 and continuing through summer of 2019, vegetation sampling occurred in NW and NE Colorado. These efforts were directed at: 1) identifying willow community diversity at 17 �known moose locations, 2) determining if moose demonstrate preference among willow species while browsing, and 3) to determine the nutritional quality of willows throughout the summer period. Ultimately, these data will be used to develop a linkage between moose body condition, moose pregnancy, and moose habitat conditions. Thus far, data collected during this project have met expectations. In particular, survival rates have been consistently high in all study areas. However, a large degree of variation within pregnancy rates have been observed, which is intriguing. Despite variant and lower than expected pregnancy rates during the course of this study, observed winter calf-at-heel rates suggest that moose calf survival during the first 6 months of life is high. During the remainder of FY 19-20 and during FY 20-21, data collected during this study will be analyzed to evaluate the relationship between moose pregnancy and browse availability and browse nutritional character will be discerned to help biologists project moose population trajectory and to refine moose herd management objectives. Similarly, various metrics (such as pregnancy rates and observed calf-at-heel ratios) will be evaluated in the context of their utility for long term management of moose in Colorado. Northwest Study Area Southw1 Study Ar~ / Figure 1. Moose research study areas, located in 3 regions in Colorado. A total of 255 moose were captured during winters between 2013–2014 and 2018–2019. During the winter of 2018–2019, a total of 36 moose were captured in the Northeast and Northwest study areas. Survival of moose was high in all study areas and during all years of the study. 18 �100% I 90% I 80% 70% 60% 50% 40% 30% 20% 10% 0% I~ • I I I n I I ~ I • ■ I • .... - . - -I I '-- I I ~ 2013-2014 2014-2015 2015-2016 2016-2017 2017-2018 2018-2019 Probability of Being Pregnant Figure 2. Pregnancy data were collected for all moose at the time of capture. Data from northwest Colorado are depicted by black bars, data from northeast Colorado are depicted by gray bars, and data from southwest Colorado are depicted by white bars. Data from southwest were sparse during 2015–2016 (n = 7 animals) and not collected between 2016–2019. The cause and consequences of the low pregnancy rate observed in northwest Colorado during 2016–2017 were never determined and that was considered to be an outlier event. 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 ,, ,,,, ,,------------------ ----------~ ,,,' ,' I ,' ,' ,' ,,,, ,, ,, ,,,, ,, _____ , ,, I ,,,' ,, ___ , ,,,, -----------------1 6 11 16 21 26 31 36 41 46 Moose Loin Depth (mm) 51 56 Figure 3. During the course of this study, probability of moose pregnancy has been best predicted by measured loin depth. The relationship between body condition and pregnancy status is reflected by the solid black line and from data collected during the all 5 years of the study (dotted lines represent 95% confidence intervals for moose pregnancy probability). No regional effects were found in our data, and the lack of significance of annual effects in our best performing models is likely driven by small sample sizes. 19 �Proportion of Cows with Calves at Heel (capture) 1.00 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0.00 2013-2014 2014-2015 2015-2016 2016-2017 2017-2018 Figure 4. Moose calf-at-heel data were collected for all cow moose at the time of capture. Data from northwest Colorado are depicted by black bars, data from northeast Colorado are depicted by gray bars, and data from southwest Colorado are depicted by white bars. Data from southwest were sparse during 2015–2016 (n = 7 animals) and not collected during 2016–2017 or 2017–2018. Overall, recruitment of moose calves into the winter time period has consistently exceeded 50%. Anecdotal evidence suggests that overwinter survival of moose calves in Colorado is high, thereby lending evidence moose herds are likely stable or increasing despite documented highly variable pregnancy rates. 20 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluating factors influencing elk recruitment in Colorado Period Covered: July 1, 2018-June 30, 2019 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Mat Alldredge, mat.alldredge@state.co.us; Chuck Anderson chuck.anderson@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. Over the last two decades, wildlife managers in Colorado have become increasingly concerned about declining winter elk calf recruitment (estimated using juvenile:adult female ratios) in the southern portion of the state. Although juvenile:adult female ratios are often highly correlated with juvenile elk survival, they are an imperfect estimate of recruitment because they are affected by harvest, pregnancy rates, juvenile survival, and adult female survival. Thus, there is a need for elk research in Colorado based upon monitoring of marked individuals to evaluate factors affecting each stage of production and survival. In 2016, Colorado Parks and Wildlife (CPW) began a 2-year pilot study to investigate factors influencing elk recruitment in 2 elk Data Analysis Units (DAUs; E-20, E-33) with low juvenile:adult female ratios in the state (Fig. 1). In FY2018-19, CPW expanded this pilot study work into a 3rd DAU (E2), with high juvenile:adult female ratios, which will serve as a reference area. We plan to conduct this study for 6 additional years to better determine how various factors (habitat, weather condition, predation, human disturbance) may be impacting elk recruitment in Colorado. During FY2018-19 we successfully worked with private landowners and personnel from CPW to coordinate field research logistics and initiate the first year of this study. We collected data on body condition and reproduction by capturing adult female elk, and we outfitted 62 pregnant females with GPS collars and vaginal implant transmitters (VITs; used to detect calf birth sites). We did not reach our target sample size of 30 collared pregnant females from the Bear’s Ears herd because we halted capture operations due to acute mortalities that occurred during helicopter net-gunning. As a result, we had to adjust our sampling strategy for elk calves in this area to capture a greater number of opportunistically encountered calves due to the low number of calves available to capture from collared adult female elk. We successfully captured and collared >45 newborn elk from each study area, meeting our sample size objectives. Calf survival monitoring is ongoing with year one results pending the first year of data collection. In 2019, we estimated that pregnancy rates of adult female elk were 100% in the Bear’s Ears herd (95% CI = 44-100%; n = 3), 91% in the Trinchera herd (95% CI = 76-97%; n = 33), and 97% in the Uncompahgre Plateau herd (95% CI = 84-100%; n = 31; Fig. 2). Elk populations experiencing good to excellent summer-autumn nutrition typically have pregnancy rates ≥90% (Cook et al. 2013). We estimated the mean IFBF of adult female elk to be 5.8% from the Bear’s Ears herd, 6.4% from the Trinchera herd, and 7.1% from the Uncompahgre Plateau herd (Fig. 3). When late-winter IFBF values are <8-9% for adult female elk that have lactated through the previous growing season, this suggests that there may be nutritional limitations, but it does not identify whether limitations are a result of summer-autumn or winter nutrition (R. Cook, personal communication). During May and June 2019, we captured and collared 146 elk calves, 51 from the Bear’s Ears herd, 46 from the Trinchera herd, and 49 from the Uncompahgre Plateau herd. From the Bear’s Ears herd, 21 �we successfully captured and collared 100% (2/2) of the calves of collared adult female elk outfitted with VITs. From the Trinchera herd, we successfully captured and collared 90% (27/30) of the calves of collared adult female elk outfitted with VITs. From the Uncompahgre Plateau herd, we successfully captured and collared 83% (25/30) of the calves of collared adult female elk outfitted with VITs. The estimated mean date of calving was June 11 in the Bear’s Ears herd, June 1 in the Trinchera herd, and June 3 in the Uncompahgre Plateau herd (Fig. 4). Data collection will continue through 2024 to address factors influencing elk calf recruitment in Colorado. CPW Animal Care and Use Committee protocols have been modified to insure sample size requirements will be achieved throughout the remainder of the study. E-4 Calves :100 adult females (2013-2017) Insufficient data 0 25-300 30-350 35-400 40-450 45-500 50-55 55-60 E-51 E-99 j 0 30 60 Miles Figure 1. Number of elk calves per 100 adult females observed during December-February aerial surveys (5-year average from 2013-2017) within elk Data Analysis Units (DAUs; labeled with black text) in Colorado, USA. 22 �1.0 3 33 31 0.9 0.8 +-' C cu 0.7 C 0) ~ 0.6 a. C o 0.5 t: 0 g-0.4 ~ o.. 0.3 0.2 0.1 0.0 Bear's Ears Trinchera Uncompahgre Plateau Herd Figure 2. Estimated average pregnancy rates of adult female elk from the Bear’s Ears, Trinchera, and Uncompahgre Plateau herds sampled during late winter 2019 in Colorado, USA. The sample size is given at the top of the 95% binomial confidence intervals (black lines). 23 �12.5 - ~ 10.0 - ...-~ ~ >, "'O 0 .o 7.5Q) Q) ~ ... I ro Cl) Q) C) C 5.0 - 2 .5 - Bear's Ears Trinchera Uncompahgre Plateau Herd Figure 3. The estimated ingesta-free body fat (%) of adult female elk from the Bear’s Ears (n = 3), Trinchera (n = 33), and Uncompahgre Plateau (n = 31) herds during late-winter 2019 in Colorado, USA. 24 �Jun 17 - Jun 10 Q) ..... ro "'O cn Jun 03 c "> ro () May 27 - May 20 Bear's Ears Trinchera Uncompahgre Plateau Herd Figure 4. The distribution of calving dates of adult female elk estimated from vaginal implant transmitters (VITs) from the Bear’s Ears (n = 2), Trinchera (n = 30), and Uncompahgre Plateau (n = 30) herds during 2019 in Colorado, USA. 25 �SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT CPW Research Library .Annual Report July 1, 2018 -June 30, 2019 Aut hor Alex andria Ausi e.rmann, alex andria auS1ermann@st at e.co us Library cat alog. h~:p.l/c1.011oeos-iml ne"/C10110/publ1cllndexaspx Articles Retrieved by Month ,. ,.. ., ... ,. ,. 2 purposes. 1 . The library supports wildlife research and management by providing needed informat ion including Titles: ~ • Copies: 16,728 ~ 29,911 books and full-text articles. Notable Special Collections: 2 . The library serves as an instit ut ional reposit ory for documents w ritten by division staff and makes t hose freel y available t o t he public. Federal Aid Reports: 4, 265 Visits to the Library Catalog by IP Address Divis.ion Reports: 4, 070 .. "'' .."" Phy;ical Journal Issues: 8,194 It ems n t he collect ion include The Research Library has been in service ofCO tP, • Vlffls from th~ CPW IP ""' Wilclife-related Books: 7,593 so+j Vi1ih from other St.it~ , Artides by Division staff: 1, 292 ■ VIS/ts from Other IPs ..., ,., books, reports and physical jouma s. It does not include e· • Vl"liU from unique! IP.. cont ent. Tit les are unique it ems in t he collection. A t it le may have mult iple copies. The numb-er of copies is t he t ot al number of it ems in t he collection Special Collect ions are sub·set s of t he overall collect ion. All info·mation in this report is prelimiury and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED with-out permission of the author. ...., 1 0,20,C, VnifOfffl Manipulation ofthesedata beyond that contained in this report isdiscouraged. m ..... History of the Division 0,1°" Journal Subscriptions 8 1.8g7 Colorado Game, Fish and f o·estry Department established @ Offke Supplies 1899 Name cha nged to Colorado Department of Game and Fish A,1963 Game & Fish Department ard 0-epartm-ent of Parks & W Recreation merge to form Game, Fish & Parks Department 1971 Division of Game, Fish & Parks is separated into t h-e Division of VYildlife and t he Divisi,, nof Parks & Outdoor Recreation A Colorado State Parks merges w ith t he Colorado Div ision of The library also subscribes. t o sev en I dat abases. t hat prov ide acces.s t o W W ildlife to form Colorado Parksa,d Wildlife t housands more journals. - 2 011 26 �APPENDIX A. CPW mammal research abstracts published July 2018 – November 2019. 27 �MAMMAL RESPONSES TO BEETLE-KILLED FORESTS IN COLORADO Mammalian responses to changed forest conditions resulting from bark beetle outbreaks in the southern Rocky Mountains Jacob S. Ivan,a Amy E. Seglund,b Richard L. Truex,c and Eric S. Newkirka a Mammals Research Section, Colorado Parks and Wildlife, 317 West Prospect Road, Fort Collins, CO 80526 USA b Species Conservation Section, Colorado Parks and Wildlife, 2300 South Townsend Avenue, Montrose, CO 81401 USA c U.S. Department of Agriculture Forest Service, Rocky Mountain Region, 1617 Cole Boulevard, Building 17, Lakewood, CO 80401 USA Citation: Ivan, J. S., A. E. Seglund, R. L. Truex, and E. S. Newkirk. 2018. Mammalian responses to changed forest conditions resulting from bark beetle outbreaks in the southern Rocky Mountains. Ecosphere 9(8); doi.org/10.1002/ecs2.2369 ABSTRACT Spruce beetle (Dendroctonus rufipennis) and mountain pine beetle (Dendroctonus ponderosae) outbreaks have impacted millions of acres of conifer forest from Alaska to northern Mexico. These species are native to North America, and periodic outbreaks have shaped the structure and composition of conifer forests for millennia. However, the extent and severity of current outbreaks, fueled by favorable climatic conditions and increased susceptibility of forests, are unmatched in recorded history. To characterize the response of a suite of mammalian species to beetle-induced changes in vegetation in the southern Rocky Mountains, we deployed cameras at 300 randomly selected sites during summer 2013–2014. Selected sites spanned gradients of years elapsed since bark beetle outbreaks (YSO) and severity. We fit single-season occupancy models to detection/non-detection data collected for each species to examine a variety of plausible relationships between use of a given stand and YSO, severity, or both. Ungulates exhibited a positive association with bark beetle activity, although the nature of these associations varied by species. Elk (Cervus canadensis) were positively associated with severity, but not YSO; mule deer (Odocoileus hemionus) exhibited the opposite relationship. Moose (Alces alces) responded in a quadratic fashion; use of forest stands adjacent to preferred willow habitat peaked 3–7 yr after an outbreak commenced, but only at high severity. Similarly, yellow-bellied marmot use of impacted stands adjacent to rock outcroppings followed a quadratic trend, but only at high severity. Red squirrel (Tamiasciurus hudsonicus) use declined in severely impacted stands, likely as a response to diminished cone crops. Golden-mantled ground squirrels (Callospermophilus lateralis) and chipmunks (Neotamias spp.) exhibited a shallow negative relationship with YSO, as did coyotes (Canis latrans). Contrary to our hypotheses, black bears (Ursus americanus), American marten (Martes americana), snowshoe hares (Lepus americanus), and porcupines (Erethizon dorsatum) did not appear to be substantially influenced by beetle activity. Red fox (Vulpes vulpes) use was positively associated with YSO, but overall use declined as severity increased. Note that changes in probability of use described here could reflect changes in abundance, home range size, habitat use, or some combination, and in several cases, there was considerable uncertainty across competing models. Published August 2018 28 �LYNX RESPONSE TO WINTER RECREATION Sharing the same slope: Behavioral responses of a threatened mesocarnivore to motorized and nonmotorized winter recreation Lucretia E. Olson,a John R. Squires,a Elizabeth K. Roberts,b Jacob S. Ivan,c and Mark Hebblewhited a Rocky Mountain Research Station, U.S. Forest Service, 800 Beckwith Avenue, Missoula, MT 59801, USA b White River National Forest, 900 Grand Avenue, Glenwood Springs, CO 80601, USA c Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA d Wildlife Biology Program, Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA Citation: Olson, L. E., J. R. Squires, E. K. Roberts, J. S. Ivan, and M. Hebblewhite. 2018. Sharing the same slope: Behavioral responses of a threatened mesocarnivore to motorized and nonmotorized winter recreation. Ecology and Evolution 8:8555–8572; doi.org/10.1002/ece3.4382 ABSTRACT Winter recreation is a widely popular activity and is expected to increase due to changes in recreation technology and human population growth. Wildlife are frequently negatively impacted by winter recreation, however, through displacement from habitat, alteration of activity patterns, or changes in movement behavior. We studied impacts of dispersed and developed winter recreation on Canada lynx (Lynx canadensis) at their southwestern range periphery in Colorado, USA. We used GPS collars to track movements of 18 adult lynx over 4 years, coupled with GPS devices that logged 2,839 unique recreation tracks to provide a detailed spatial estimate of recreation intensity. We assessed changes in lynx spatial and temporal patterns in response to motorized and nonmotorized recreation, as well as differences in movement rate and path tortuosity. We found that lynx decreased their movement rate in areas with high‐intensity back‐country skiing and snowmobiling, and adjusted their temporal patterns so that they were more active at night in areas with high‐intensity recreation. We did not find consistent evidence of spatial avoidance of recreation: lynx exhibited some avoidance of areas with motorized recreation, but selected areas in close proximity to nonmotorized recreation trails. Lynx appeared to avoid high‐intensity developed ski resorts, however, especially when recreation was most intense. We conclude that lynx in our study areas did not exhibit strong negative responses to dispersed recreation, but instead altered their behavior and temporal patterns in a nuanced response to recreation, perhaps to decrease direct interactions with recreationists. However, based on observed avoidance of developed recreation, there may be a threshold of human disturbance above which lynx cannot coexist with winter recreation. Published July 2018 Winter recreation and Canada lynx: reducing conflict through niche partitioning John R. Squires,a Lucretia E. Olson,a Elizabeth K. Roberts,b Jacob S. Ivan,c and Mark Hebblewhited a Rocky Mountain Research Station, U.S. Forest Service, 800 Beckwith Avenue, Missoula, MT 59801, USA b White River National Forest, 900 Grand Avenue, Glenwood Springs, CO 80601, USA c Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA d Wildlife Biology Program, Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA Citation: Squires, J. R., L. E. Olson, E. K. Roberts, J. S. Ivan, and M. Hebblewhite. 2019. Winter recreation and Canada lynx: reducing conflict through niche partitioning. Ecosphere 10(10); doi.org/10.1002/ecs2.2876 ABSTRACT Outdoor recreationists are important advocates for wildlife on public lands. However, balancing potential impacts associated with increased human disturbance with the conservation of sensitive species is a central issue facing ecologists and land managers alike, especially for dispersed winter recreation due to its disproportionate impact to wildlife. We studied how dispersed winter recreation (outside developed ski areas) impacted a reintroduced meso‐carnivore, Canada lynx (Lynx canadensis), at the southern periphery of the species’ range in the southern Rocky Mountains. On a voluntary basis, we distributed global positioning system (GPS) units to winter recreationists and documented 2143 spatial movement tracks of recreationists engaged in motorized and nonmotorized winter sports for a total cumulative distance of 56,000 km from 2010 to 2013. We also deployed GPS radio collars on adult Canada lynx that were resident in the mountainous topography that attracted high levels of dispersed winter recreation. We documented that resource‐selection models (RSFs) for Canada lynx were significantly improved when selection patterns of winter recreationists were included in best‐performing models. Canada lynx and winter recreationists partitioned environmental gradients in ways that reduced the potential for recreation‐related disturbance. Although the inclusion of recreation improved the RSF model for Canada lynx, environmental covariates explained most variation in resource use. The environmental gradients that most separated areas selected by Canada lynx from those used by recreationists were forest canopy closure, road density, and slope. 29 �Canada lynx also exhibited a functional response of increased avoidance of areas selected by motorized winter recreationists (snowmobiling off‐trail, hybrid snowmobile) compared with either no functional response (hybrid ski) or selection for (backcountry skiing) areas suitable for nonmotorized winter recreation. We conclude with a discussion of implications associated with providing winter recreation balanced with the conservation of Canada lynx. Published October 2019 30 �CARNIVORE ECOLOGY AND MANAGEMENT Puma population limitation and regulation: what matters in puma management? Kenneth A. Logan Mammals Research Section, Colorado Parks and Wildlife, 2300 S. Townsend Avenue, Montrose, CO 81401, USA Citation: Logan, K. A. 2019. Puma population limitation and regulation: what matters in puma management? Journal of Wildlife Management 83:1652–1666; doi.org/10.1002/jwmg.21753 ABSTRACT Wildlife managers require reliable information on factors that influence animal populations to develop successful management programs, including the puma (Puma concolor), in western North America. As puma populations have recovered in recent decades because of restrictions on human‐caused mortality, managers need a clear understanding of the factors that limit or regulate puma populations and how those factors might be manipulated to achieve management objectives, including sustaining puma and other wildlife populations, providing hunting opportunity, and reducing puma interactions with people. I synthesized technical literature on puma populations, behavior, and relationships with prey that have contributed to hypotheses on puma population limitation and regulation. Current hypotheses on puma population limitation include the social limitation hypothesis and the food limitation hypothesis. Associated with each of those are 2 hypotheses on puma population regulation: the social regulation hypothesis and the competition regulation hypothesis. I organize the biological and ecological attributes of pumas reported in the literature under these hypotheses. I discuss the validity of these hypotheses based on the limits of the research associated with the hypotheses and the evolutionary processes theoretically underlying them. I review the management predictions as framed by these hypotheses as they pertain to puma hunting, puma‐ prey relationships, and human‐puma interactions. The food limitation and competition regulation hypotheses explain more phenomena associated with puma and likely would guide more successful management outcomes. © 2019 The Wildlife Society. Featured article November 2019 issue of Journal of Wildlife Management Human–Cougar interactions in the wildland–urban interface of Colorado’s Front Range Mathew W. Alldredge,a Frances E. Buderman,b and Kevin A. Blechac a Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO, USA b Colorado State University, Fort Collins, CO, USA c Terrestrial Section, Colorado Parks and Wildlife, Gunnison, CO, USA Citation: Alldredge, M. W., F. E. Buderman, and K. A. Blecha. 2019. Human-Cougar interactions in the wildland-urban interface of Colorado’s Front Range. Ecology and Evolution 9:10415–10431; doi.org/10.1002/ece3.5559 ABSTRACT As human populations continue to expand across the world, the need to understand and manage wildlife populations within the wildland–urban interface is becoming commonplace. This is especially true for large carnivores as these species are not always tolerated by the public and can pose a risk to human safety. Unfortunately, information on wildlife species within the wildland–urban interface is sparse, and knowledge from wildland ecosystems does not always translate well to human‐dominated systems. Across western North America, cougars (Puma concolor) are routinely utilizing wildland–urban habitats while human use of these areas for homes and recreation is increasing. From 2007 to 2015, we studied cougar resource selection, human–cougar interaction, and cougar conflict management within the wildland–urban landscape of the northern Front Range in Colorado, USA. Resource selection of cougars within this landscape was typical of cougars in more remote settings but cougar interactions with humans tended to occur in locations cougars typically selected against, especially those in proximity to human structures. Within higher housing density areas, 83% of cougar use occurred at night, suggesting cougars generally avoided human activity by partitioning time. Only 24% of monitored cougars were reported for some type of conflict behavior but 39% of cougars sampled during feeding site investigations of GPS collar data were found to consume domestic prey items. Aversive conditioning was difficult to implement and generally ineffective for altering cougar behaviors but was thought to potentially have long‐term benefits of reinforcing fear of humans in cougars within human‐dominated areas experiencing little cougar hunting pressure. Cougars are able to exploit wildland–urban landscapes effectively, and conflict is relatively uncommon compared with the proportion of cougar use. Individual characteristics and behaviors of cougars within these areas are highly varied; therefore, conflict management is unique to each situation and should target individual behaviors. The ability of individual cougars to learn to exploit these environments with minimal human–cougar interactions suggests that maintaining 31 �older age structures, especially females, and providing a matrix of habitats, including large connected open‐space areas, would be beneficial to cougars and effectively reduce the potential for conflict. Published August 2019 Time-varying predatory behavior is primary predictor of fine-scale movement of wildland-urban cougars Frances E. Buderman,a Mevin B. Hooten,b Mathew W. Alldredge,c Ephraim M. Hanks,d and Jacob S. Ivanc a Colorado State University, Department of Fish, Wildlife, and Conservation Biology, 1484 Campus Delivery, Fort Collins, CO 80523, USA b U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Department of Fish, Wildlife, and Conservation Biology, 1484 Campus Delivery, Fort Collins, CO 80523, USA c Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA d Pennsylvania State University, W-250 Millennium Science Complex, University Park, State College, PA 16802, USA Citation: Buderman, F. E., M. B. Hooten, M. W. Alldredge, E. M. Hanks, and J. S. Ivan. 2018. Time-varying predatory behavior is primary predictor of fine-scale movement of wildland-urban cougars. Movement Ecology 6(22); doi.org/10.1186/s40462-108-0140-6 Abstract Background: While many species have suffered from the detrimental impacts of increasing human population growth, some species, such as cougars (Puma concolor), have been observed using human-modified landscapes. However, human-modified habitat can be a source of both increased risk and increased food availability, particularly for large carnivores. Assessing preferential use of the landscape is important for managing wildlife and can be particularly useful in transitional habitats, such as at the wildland-urban interface. Preferential use is often evaluated using resource selection functions (RSFs), which are focused on quantifying habitat preference using either a temporally static framework or researcher-defined temporal delineations. Many applications of RSFs do not incorporate time-varying landscape availability or temporally-varying behavior, which may mask conflict and avoidance behavior. Methods: Contemporary approaches to incorporate landscape availability into the assessment of habitat selection include spatio-temporal point process models, step selection functions, and continuous-time Markov chain (CTMC) models; in contrast with the other methods, the CTMC model allows for explicit inference on animal movement in continuous-time. We used a hierarchical version of the CTMC framework to model speed and directionality of finescale movement by a population of cougars inhabiting the Front Range of Colorado, U.S.A., an area exhibiting rapid population growth and increased recreational use, as a function of individual variation and time-varying responses to landscape covariates. Results: We found evidence for individual- and daily temporal-variability in cougar response to landscape characteristics. Distance to nearest kill site emerged as the most important driver of movement at a population-level. We also detected seasonal differences in average response to elevation, heat loading, and distance to roads. Motility was also a function of amount of development, with cougars moving faster in developed areas than in undeveloped areas. Conclusions: The time-varying framework allowed us to detect temporal variability that would be masked in a generalized linear model, and improved the within-sample predictive ability of the model. The high degree of individual variation suggests that, if agencies want to minimize human-wildlife conflict management options should be varied and flexible. However, due to the effect of recursive behavior on cougar movement, likely related to the location and timing of potential kill-sites, kill-site identification tools may be useful for identifying areas of potential conflict. Published November 2018 Summarizing Colorado’s black bear two-strike directive 30 years after inception Jonathan H. Lewis,a Mathew W. Alldredge,a Brian P. Dreher,b Janet L. George,c Scott Wait,d Brad Petch,e and Jon P. Rungef a Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA b Terrestrial Section, Colorado Parks and Wildlife, 4255 Sinton Road, Colorado Springs, CO 80907, USA c Terrestrial Section, Colorado Parks and Wildlife, 1313 Sherman Street, Denver, CO 80203, USA d Terrestrial Section, Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81303, USA e Terrestrial Section, Colorado Parks and Wildlife, 711 Independent Avenue, Grand Junction, CO 81505, USA f Terrestrial Programs, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA Citation: Lewis, J. H., M. W. Alldredge, B. P. Dreher, J. L. George, S. Wait, B. Petch, and J. P. Runge. 2019. Summarizing Colorado’s black bear two–strike directive 30 years after inception. Wildlife Society Bulletin; doi.org/10.1002/wsb.1032 ABSTRACT Colorado Parks and Wildlife implemented a new statewide management policy in 1985 for nuisance black bears (Ursus americanus), known today as the 2‐strike directive. It allowed wildlife managers to assess the repeatability of nuisance bear behavior after translocating them to quality bear habitat away from human food 32 �sources. We evaluated this directive using 30 years (1987–2016) of nuisance black bear capture records. Statewide, 53% of 1,093 bears caught, marked, and moved (1st strike) were never reported again, while 25% were killed for a 2nd strike, and hunters harvested 17%. Subadult males committed 2nd strikes more quickly than adult males and females. Although time between strikes was greatest for adult females (496 days), they had the largest probability of committing a 2nd strike among all cohorts. We found that the number of 1st strike captures, from late summer through fall was greatest during years of poor mast production. We suggest that the 2‐strike policy has been an effective management tool for nuisance black bears in Colorado, USA, because of low rates of nuisance behavior following 1st‐strike translocation. If a state or local management objective is to increase black bear populations, wildlife managers may increase tolerance of adult bears that have received their 1st strike in years when fall mast crops largely fail because they are less likely to commit a 2nd strike. Lower tolerance of subadult males may be warranted in bad food years, especially in areas where reductions in bear populations are desired, because they tend to repeat nuisance behaviors more quickly than other bears. © 2019 The Wildlife Society. Published Nov. 2019 Assessing ecological and social outcomes of a bear-proofing experiment Heather E. Johnson,a David L. Lewis,a Stacy A. Lischka,b and Stewart W. Breckc a Mammals Research Section, Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81303, USA b Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 317 W. Prospect Avenue, Fort Collins, CO 80526, USA c U.S. Department of Agriculture National Wildlife Research Center, 4101 LaPorte Avenue, Fort Collins, CO 80521, USA Citation: Johnson, H. E., D. L. Lewis, S. A. Lischka, and S. W. Breck. 2018. Assessing ecological and social outcomes of a bear–proofing experiment. Journal of Wildlife Management 82:1102–1114; DOI: 10.1002/jwmg.21427 ABSTRACT Human-black bear conflicts within urban environments have been increasing throughout North America, becoming a high priority management issue. The main factor influencing these conflicts is black bears foraging on anthropogenic foods within areas of human development, primarily on residential garbage. Wildlife professionals have advocated for increased bear-proofing measures to decrease the accessibility of garbage to bears, but little research has been conducted to empirically test the effectiveness of this approach for reducing conflicts. Between 2011 and 2016, we conducted a before-after-control-impact experiment in Durango, Colorado where we distributed 1,110 bear-resistant trash containers, enhanced education, and increased enforcement to residents in 2 treatment areas, and monitored 2 paired control areas. We examined the ecological and social outcomes of this experiment, assessing whether bear-resistant containers were effective at reducing conflicts; the level of public compliance (i.e., properly locking away garbage) needed to reduce conflicts; whether the effectiveness of bearresistant containers increased over time; and if the distribution of bear-resistant containers changed residents’ attitudes about bear management, support for ordinances that require bear-proofing, or perceptions of their future risk of garbage-related conflicts. After the bear-resistant containers were deployed, trash-related conflicts (i.e., observations of strewn trash) were 60% lower in treatment areas than control areas, resident compliance with local wildlife ordinances (properly locking away trash) was 39% higher in treatment areas than control areas, and the effectiveness of the new containers was immediate. Conflicts declined as resident compliance with wildlife ordinances increased to approximately 60% (by using a bear-resistant container or locking trash in a secure location), with minor additional declines in conflicts at higher levels of compliance. In addition to these ecological benefits, public mail surveys demonstrated that the deployment of bear-resistant containers was associated with increases in the perceived quality of bear management and support for ordinances that require bear-proofing, and declines in the perceived risk of future trash-related conflicts. Our results validate efforts by wildlife professionals and municipalities to reduce black bear access to human foods, and should encourage other entities of the merits of bear-proofing efforts for reducing human-bear conflicts and improving public attitudes about bears and their management. © 2018 The Wildlife Society. Featured article August 2018 issue of Journal of Wildlife Management A conceptual model for the integration of social and ecological information to understand human-wildlife interactions Stacy A. Lischka,a,b Tara L. Teel,c Heather E. Johnson,d Sarah E. Reed,b,e Stewart Breck,f Andrew Don Carlos,c Kevin R. Crooksb a Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 317 W. Prospect Ave., Fort Collins, CO 80526, USA b Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA c Department of Human Dimensions of Natural Resources, Colorado State University, Fort Collins, CO 80523, USA d Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 415 Turner Dr., Durango, CO 81301, USA e Americas Program, Wildlife Conservation Society, 2300 Southern Blvd., Bronx, NY 10460, USA f National Wildlife Research Center, USDA Wildlife Services, 4101 Laporte Ave., Fort Collins, CO 80521, USA 33 �Citation: Lischka, S. A., T. L. Teel, H. E. Johnson, S. E. Reed, S. Breck, A. Don Carlos, and K. R. Crooks. 2018. A conceptual model for the integration of social and ecological information to understand human-wildlife interactions. Biological Conservation 225:80–87; doi.org/10.1016/j.biocon.2018.06.020 ABSTRACT There is growing recognition that interdisciplinary approaches that account for both ecological and social processes are necessary to successfully address human-wildlife interactions. However, such approaches are hindered by challenges in aligning data types, communicating across disciplines, and applying social science information to conservation actions. To meet these challenges, we propose a conceptual model that adopts a socialecological systems approach and integrates social and ecological theory to identify the multiple, nested levels of influence on both human and animal behavior. By accounting for a diverse array of influences and feedback mechanisms between social and ecological systems, this model fulfills a need for approaches that treat social and ecological processes with equal depth and facilitates a comprehensive understanding of the drivers of human and animal behaviors that perpetuate human-wildlife interactions. We apply this conceptual model to our work on human-black bear conflicts in Colorado, USA to demonstrate its utility. Using this example, we identify key lessons and offer guidance to researchers and conservation practitioners for applying integrated approaches to other humanwildlife systems. Published September 2018 Understanding and managing human tolerance for a large carnivore in a residential system Stacy A. Lischka,a, b Tara L. Teel,c H. E. Johnson,d and K. R. Crooksb a Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA b Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA c Department of Human Dimentions of Natural Resources, Colorado State University, Fort Collins, CO 80523, USA d Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81301, USA Citation: Lischka, S. A., T. L. Teel, H. E. Johnson, and K. R. Crooks. 2019. Understanding and managing human toleralce for a large carnivore in a residential system. Biological Conservation 238:1081–1089; doi.org/10.1016/j.biocon.2019.07.034 ABSTRACT Human tolerance for interactions with large carnivores is an important determinant of their persistence on the landscape, yet the relative importance of factors affecting tolerance is not fully understood. Further, the impact of management efforts to alter tolerance has not been adequately assessed. We developed a model containing a comprehensive set of predictors drawn from prior studies and tested it through a longitudinal survey measuring tolerance for black bears (Ursus americanus) in the vicinity of Durango, Colorado, USA. Predictors included human-bear conflicts, outcomes of interactions with bears, perceptions of benefits and risks from bears, trust in managers, perceived similarity with the goals of managers, personal control over risks, value orientations toward wildlife, and demographic factors. In addition, we monitored changes in tolerance resulting from a bear-proofing experiment designed to reduce garbage-related conflicts in the community. Residents who perceived greater benefits associated with bears and more positive impacts from bear-related interactions had higher tolerance. Residents who perceived greater risks and more negative impacts and who had greater trust in managers, domination wildlife value orientations, and older age were less tolerant. Conflicts with bears were not an important predictor, supported by our finding that changes in conflicts resulting from our bear-proofing experiment did not affect tolerance. In contrast to conservation approaches that focus primarily on decreasing human-wildlife conflicts, our findings suggest that communication approaches aimed at increasing public tolerance for carnivores could be improved by emphasizing the benefits and positive impacts of living with these species. Published October 2019 34 �UNGULATE ECOLOGY AND MANAGEMENT Modeling elk‐to‐livestock transmission risk to predict hotspots of brucellosis spillover Nathaniel D. Rayl,a Kelly M. Proffitt,b Emily S. Almberg,b Jennifer D. Jones,b Jerod A. Merkle,c Justin A. Gude,d and Paul C. Crosse a Current Affiliation: Mammals Research Section, Colorado Parks and Wildlife, Grand Junction, CO 81505, USA b Montana Fish, Wildlife and Parks, Bozeman, MT 59718, USA c Wyoming Cooperative Fish and Wildlife Research Unit, Dept. of Zoology and Physiology, University of Wyoming, Laramie, WY 82071, USA d Montana Fish, Wildlife and Parks, Helena, MT 59718, USA e U.S. Geological Survey, Northern Rocky Mountain Science Center, Bozeman, MT 59715, USA Citation: Rayl, N. D., K. M. Proffit, E. S. Almberg, J. D. Jones, J. A. Merkle, J. A. Gude, and P. C. Cross. 2019. Modeling elk‐to‐livestock transmission risk to predict hotspots of brucellosis spillover. Journal of Wildlife Management 83:817–829; doi.org/10.1002/jwmg.21645 ABSTRACT Wildlife reservoirs of infectious disease are a major source of human‐wildlife conflict because of the risk of potential spillover associated with commingling of wildlife and livestock. In the Greater Yellowstone Ecosystem, the presence of brucellosis (Brucella abortus) in free‐ranging elk (Cervus canadensis) populations is of significant management concern because of the risk of disease transmission from elk to livestock. We identified how spillover risk changes through space and time by developing resource selection functions using telemetry data from 223 female elk to predict the relative probability of female elk occurrence daily during the transmission risk period. We combined these spatiotemporal predictions with elk seroprevalence, demography, and transmission timing data to identify when and where abortions (the primary transmission route of brucellosis) were most likely to occur. Additionally, we integrated our predictions of transmission risk with spatiotemporal data on areas of potential livestock use to estimate the daily risk to livestock. We predicted that approximately half of the transmission risk occurred on areas where livestock may be present (i.e., private property or grazing allotments). Of the transmission risk that occurred in livestock areas, 98% of it was on private ranchlands as opposed to state or federal grazing allotments. Disease prevalence, transmission timing, host abundance, and host distribution were all important factors in determining the potential for spillover risk. Our fine‐resolution (250‐m spatial, 1‐day temporal), large‐scale (17,732 km2) predictions of potential elk‐to‐livestock transmission risk provide wildlife and livestock managers with a useful tool to identify higher risk areas in space and time and proactively focus actions in these areas to separate elk and livestock to reduce spillover risk. © 2019 The Wildlife Society. Published March 2019 On-animal acoustic monitoring provides insight to ungulate foraging behavior Joseph M. Northrup,a Alexandra Arvin,a Charles R. Anderson Jr.,b Emma Brown,c and George Whittemyera a Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA b Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO 80526, USA c National Parks Service Natural Sounds and Skies Division, Fort Collins, CO 80525, USA Citation: Northrup, J. M., A. Arvin, C. R. Anderson Jr., E. Brown, and G. Whittemyer. 2019. On-animal acustic monitoring provides insight to ungulate foraging behavior. Journal of Mammology 100:1479–1489; doi.org/10.1093/jmammal/gyz124 ABSTRACT Foraging behavior underpins many ecological processes; however, robust assessments of this behavior for freeranging animals are rare due to limitations to direct observations. We leveraged acoustic monitoring and GPS tracking to assess the factors influencing foraging behavior of mule deer (Odocoileus hemionus). We deployed custom-built acoustic collars with GPS radiocollars on mule deer to measure location-specific foraging. We quantified individual bites and steps taken by deer, and quantified two metrics of foraging behavior: the number of bites taken per step and the number of bites taken per unit time, which relate to foraging intensity and efficiency. We fit statistical models to these metrics to examine the individual, environmental, and anthropogenic factors influencing foraging. Deer in poorer body condition took more bites per step and per minute and foraged for longer irrespective of landscape properties. Other patterns varied seasonally with major changes in deer condition. In December, when deer were in better condition, they took fewer bites per step and more bites per minute. Deer also foraged more intensely and efficiently in areas of greater forage availability and greater movement costs. During March, when deer were in poorer condition, foraging was not influenced by landscape features. Anthropogenic factors weakly structured foraging behavior in December with no relationship in March. Most research on animal foraging is interpreted under the framework of optimal foraging theory. Departures from predictions developed under this framework provide insight to unrecognized factors influencing the evolution of foraging. Our results only conformed to our predictions when deer were in better condition and ecological conditions were declining, 35 �suggesting foraging strategies were state-dependent. These results advance our understanding of foraging patterns in wild animals and highlight novel observational approaches for studying animal behavior. Published August 2019 Using maternal mule deer movements to estimate timing of parturition and assist fawn captures Mark E. Peterson,a Charles R. Anderson Jr.,b M. W. Alldredge,b and P. F. Doherty Jr.a a Department of Fish, Wildlife, and Conservation Biology, Colorado State University, 1474 Campus Delivery, Fort Collins, CO 80523, USA b Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA Citation: Peterson, M. E., C. R. Anderson Jr., M. W. Alldredge, and P. F. Doherty Jr. 2018. Using maternal mule deer movements to estimate timing of parturition and assist fawn captures. Wildlife Society Bulletin 42:616–621; doi.org/10.1002/wsb.935 ABSTRACT Movement patterns of maternal ungulates have been used to determine parturition dates and aid in locating fawns, which may be important for understanding reproductive rates (e.g., pregnancy and fetal), but such methods have not been validated for mule deer (Odocoileus hemionus). We first determined timing of parturition using vaginal implant transmitters (VITs) and then predicted timing of parturition using VITs in conjunction with Global Positioning System collar data in the Piceance Basin of northwestern Colorado, USA, during 2012–2014. We examined daily movement rate to determine differences in movement rate among days (7 days pre- and postpartum) and for movement patterns indicative of parturition. Mean daily movement rate (m/day) of 102 maternal deer decreased by 46% from 1 day preparturition (mean = 1,253, SD = 1,091) to parturition date (mean = 682, SD = 574), and remained at this low rate 1–7 days postpartum. We applied an independent data set to validate predicted parturition dates based on daily movement rate. We estimated day of parturition correctly (i.e., day 0), within 1–3 days postparturition, and ≥4 days postparturition of field-reported dates for 10 (29%), 21 (60%), and 4 (11%) maternal females, respectively. For novel data sets, we predict that a mule deer female whose daily movement rate decreases by ≥46% and remains low ≥3 days postparturition particularly when preceded by a sudden increase in movement—has given birth. However, we caution that disturbance of deer by field crews should be minimized, and if birth sites are not found, neonatal mortality will be underestimated. Our results can help determine timing and general location of parturition as an aid in capturing fawns when the use of VITs is not feasible, with the ultimate objective of estimating pregnancy, fetal, and fawn survival rates if birth sites are found. © 2018 The Wildlife Society. Published December 2018 36 �REMOTE CAMERA SAMPLING Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture– recapture data from camera traps Christopher N. Jaques,a Robert W. Klaver,b Tim C. Swearingen,a Edward D. Davis,a Charles R. Anderson,c Jonathan A. Jenks,d Christopher S. Deperno,e and Robert D. Bluettf a Department of Biological Sciences, Western Illinois University, Macomb, IL 61455, USA b Department of Natural Resource Ecology and Management, U.S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University, Ames, IA 50011, USA c Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA d Department of Natural Resource Management, South Dakota State University, Brookings, SD 57007, USA e Depertment of Forestry and Environmental Resources, Fisheries, Wildlife, and Conservation Biology Program, North Carolina State Univeristy, Raleigh, NC 27695, USA f Illinois Department of Natural Resources, 1 Natural Resources Way, Springfield, IL 62702, USA Citation: Jaques, C. N., R. W. Klaver, T. C. Swearingen, E. D. Davis, C. R. Anderson, J. A. Jenks, C. S. Deperno, and R. D. Bluett. 2019. Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture–recapture data from camera traps. Wildlife Society Bulletin 43:256–264; doi.org/10.1002/wsb.968 ABSTRACT Camera‐trapping data analyzed with spatially explicit capture–recapture (SCR) models can provide a rigorous method for estimating density of small populations of elusive carnivore species. We sought to develop and evaluate the efficacy of SCR models for estimating density of a presumed low‐density bobcat (Lynx rufus) population in fragmented landscapes of west‐central Illinois, USA. We analyzed camera‐trapping data from 49 camera stations in a 1,458‐km2 area deployed over a 77‐day period from 1 February to 18 April 2017. Mean operational time of cameras was 52 days (range = 32–67 days). We captured 23 uniquely identifiable bobcats 113 times and recaptured these same individuals 90 times; 15 of 23 (65.2%) individuals were recaptured at ≥2 camera traps. Total number of bobcat capture events was 139, of which 26 (18.7%) were discarded from analyses because of poor image quality or capture of only a part of an animal in photographs. Of 113 capture events used in analyses, 106 (93.8%) and 7 (6.2%) were classified as positive and tentative identifications, respectively; agreement on tentative identifications of bobcats was high (71.4%) among 3 observers. We photographed bobcats at 36 of 49 (73.5%) camera stations, of which 34 stations were used in analyses. We estimated bobcat density at 1.40 individuals (range = 1.00–2.02/100 km2). Our modeled bobcat density estimates are considerably below previously reported densities (30.5 individuals/100 km2) within the state, and among the lowest yet recorded for the species. Nevertheless, use of remote cameras and SCR models was a viable technique for reliably estimating bobcat density across west‐central Illinois. Our research establishes ecological benchmarks for understanding potential effects of colonization, habitat fragmentation, and exploitation on future assessments of bobcat density using standardized methodologies that can be compared directly over time. Further application of SCR models that quantify specific costs of animal movements (i.e., least‐cost path models) while accounting for landscape connectivity has great utility and relevance for conservation and management of bobcat populations across fragmented Midwestern landscapes. © 2019 The Wildlife Society. Published June 2019 Machine learning to classify animal species in camera trap images: Applications in ecology Michael A. Tabak, Mohammad S. Norouzzadeh, David W. Wolfson, Steven J. Sweeney, Kurt C. Vercauteren, Nathan P. Snow, Joseph M. Halseth, Paul A. Di Salvo, Jesse S. Lewis, Michael D. White, Ben Teton, James C. Beasley, Peter E. Schlichting, Raoul K. Boughton, Bethany Wight, Eric S. Newkirk, Jacob S. Ivan, Eric A. Odell, Ryan K. Brook, Paul M. Lukacs, Anna K. Moeller, Elizabeth G. Mandeville, Jeff Clune, Ryan S. Miller (reference publication for author affiliations) Citation: Tabak, M.A., M.S. Norouzzadeh, …, E.S. Newkirk, J.S. Ivan, E.A. Odell, et al. 2018. Machine learning to classify animal species in camera trap images: Applications in ecology. Methods in Ecology and Evolution 10:585–590; doi.org/10.1111/2041-210X.13120 Abstract 1. Motion‐activated cameras (“camera traps”) are increasingly used in ecological and management studies for remotely observing wildlife and are amongst the most powerful tools for wildlife research. However, studies involving camera traps result in millions of images that need to be analysed, typically by visually observing each image, in order to extract data that can be used in ecological analyses. 37 �2. We trained machine learning models using convolutional neural networks with the ResNet‐18 architecture and 3,367,383 images to automatically classify wildlife species from camera trap images obtained from five states across the United States. We tested our model on an independent subset of images not seen during training from the United States and on an out‐of‐sample (or “out‐of‐ distribution” in the machine learning literature) dataset of ungulate images from Canada. We also tested the ability of our model to distinguish empty images from those with animals in another out‐of‐ sample dataset from Tanzania, containing a faunal community that was novel to the model. 3. The trained model classified approximately 2,000 images per minute on a laptop computer with 16 gigabytes of RAM. The trained model achieved 98% accuracy at identifying species in the United States, the highest accuracy of such a model to date. Out‐of‐sample validation from Canada achieved 82% accuracy and correctly identified 94% of images containing an animal in the dataset from Tanzania. We provide an R package (Machine Learning for Wildlife Image Classification) that allows the users to (a) use the trained model presented here and (b) train their own model using classified images of wildlife from their studies. 4. The use of machine learning to rapidly and accurately classify wildlife in camera trap images can facilitate non‐invasive sampling designs in ecological studies by reducing the burden of manually analysing images. Our R package makes these methods accessible to ecologists. Published Nov. 2018 38 �GENETICS AND DISEASE RESEARCH The cascading effects of human food on hibernation and cellular aging in free-ranging black bears Rebecca Kirby,a Heather E. Johnson,b Mathew W. Alldredge,b and Johathan N. Paulia a Department of Forestry and Wildlife Ecology, University of Wisconsin–Madison, USA b Mammals Research Section, Colorado Parks and Wildlife, Durango and Fort Collins, USA Citation: Kirby, R., H. E. Johnson, M. W. Alldredge, and J. N. Pauli. 2019. The cascading effects of human food on hibernation and cellular aging in free-ranging black bears. Scientific Reports; doi.org/10.1038/s41598-019-38937-5 ABSTRACT Human foods have become a pervasive subsidy in many landscapes, and can dramatically alter wildlife behavior, physiology, and demography. While such subsidies can enhance wildlife condition, they can also result in unintended negative consequences on individuals and populations. Seasonal hibernators possess a remarkable suite of adaptations that increase survival and longevity in the face of resource and energetic limitations. Recent work has suggested hibernation may also slow the process of senescence, or cellular aging. We investigated how use of human foods influences hibernation, and subsequently cellular aging, in a large-bodied hibernator, black bears (Ursus americanus). We quantified relative telomere length, a molecular marker for cellular age, and compared lengths in adult female bears longitudinally sampled over multiple seasons. We found that bears that foraged more on human foods hibernated for shorter periods of time. Furthermore, bears that hibernated for shorter periods of time experienced accelerated telomere attrition. Together these results suggest that although hibernation may ameliorate cellular aging, foraging on human food subsidies could counteract this process by shortening hibernation. Our findings highlight how human food subsidies can indirectly influence changes in aging at the molecular level. Published February 2019 Identification of circular single-stranded DNA viruses in faecal samples of Canada lynx (Lynx canadensis), moose (Alces alces) and snowshoe hare (Lepus americanus) inhabiting the Colorado San Juan Mountains Simona Kraberger,a Kara Waits,b Jake Ivan,c Eric Newkirk,c Sue VandeWoude,a and Arvind Varsanib a Department of Microbiology, Immunology & Pathology, Colorado State University, Fort Colling, CO 80523, USA b The Biodesign Center for Fundamental and Applied Microbiomics, Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ 85287, USA c Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA Citation: Kraberger, S., K. Waits, J. Ivan, E. Newkirk, S. VandeWoude, and A. Varsani. 2018. Identification of circular single-stranded DNA viruses in faecal samples of Canada lynx (Lynx canadensis), moose (Alces alces) and snowshoe hare (Lepus americanus) inhabiting the Colorado San Juan Mountains. Infection, Genetics and Evolution 64:1–8; doi.org/10.1016/j.meegid.2018.06.001 ABSTRACT The San Juan Mountains of southern Colorado provide subalpine habitat for a suite of mammalian species including Canada lynx (Lynx canadensis), moose (Alces alces) and snowshoe hare (Lepus americanus). In the winter field season of 2016 five faecal samples from lynx, and one each from moose and snowshoe hare were collected to identify small single-stranded DNA viruses associated with these three prominent species. Thirty-two novel viruses were identified and classified as members of two well established ssDNA families Genomoviridae (n = 22) and Microviridae (n = 10) and one recently proposed new family, Smacoviridae (n = 1). In addition one highly novel circular ssDNA virus was identified which at present does not group with any known family. A high level of genomovirus diversity was identified from faeces collected between and across the three mammal species, with full genome-wide pairwise comparisons showing 57%–97% identity. Twenty genomoviruses can be assigned to the genus Gemycircularvirus and represent 11 species, and two into a distinct species in the genus Gemykolovirus. The single smacovirus identified from moose also represents a distinct smacovirus species. Ten microviruses, seven from moose, one from snowshoe hare and two from lynx, all are part of the Gokushovirinae subfamily. The two from lynx are highly similar to a microvirus previously detected in domestic cat (sharing 88%–90% genome-wide identity), indicating this may be a common felid gut microbiome associated virus. Our findings highlight the broad range of diverse ssDNA viruses present in three mammals inhabiting the San Juan Mountains. Published Oct. 2018 Urbanization impacts apex predator gene flow but not genetic diversity across an urban‐rural divide Daryl R. Trumbo,a Patricia E. Salerno,a Kenneth A. Logan,b Mathew W. Alldredge,b Roderick B. Gagne,c Christopher P. Kozakiewicz,d Simona, Kraberger,c Nicholas, M. Fountain-Jones,e Meggan E. Craft,e Scott Carver,d Holly B. Ernest,f Kevin R. Crooks,g Sue VandeWoude,c and W. Chris Funka aDepartment of Biology, Colorado State University, Fort Collins, CO, USA 39 �bMammals Research Section, Colorado Parks and Wildlife, Montrose and Fort Collins, CO, USA cDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, USA dDepartment of Biological Sciences, University of Rasmania, Hobart, TAS., Australia eDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, USA fDepartment of Veterinary Sciences, University of Wyoming, Laramie, WY, USA gDepartment of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA Citation: Trumbo, D.R., P.E. Salerno, K.A. Logan, M.W. Alldredge, R.B. Gagne, C.P. Kozakiewicz, S. Kraberger, N.M. Fountain-Jones, M.E. Craft, S. Carver, H.B. Ernest, K.R. Crooks, S. VandeWoude, and W.C. Funk. 2019. Molecular Ecology 28:4926–4940; doi.org/10.1111/mec.15261 ABSTRACT Apex predators are important indicators of intact natural ecosystems. They are also sensitive to urbanization because they require broad home ranges and extensive contiguous habitat to support their prey base. Pumas (Puma concolor) can persist near human developed areas, but urbanization may be detrimental to their movement ecology, population structure, and genetic diversity. To investigate potential effects of urbanization in population connectivity of pumas, we performed a landscape genomics study of 130 pumas on the rural Western Slope and more urbanized Front Range of Colorado, USA. Over 12,000 single nucleotide polymorphisms (SNPs) were genotyped using double‐digest, restriction site‐associated DNA sequencing (ddRADseq). We investigated patterns of gene flow and genetic diversity, and tested for correlations between key landscape variables and genetic distance to assess the effects of urbanization and other landscape factors on gene flow. Levels of genetic diversity were similar for the Western Slope and Front Range, but effective population sizes were smaller, genetic distances were higher, and there was more admixture in the more urbanized Front Range. Forest cover was strongly positively associated with puma gene flow on the Western Slope, while impervious surfaces restricted gene flow and more open, natural habitats enhanced gene flow on the Front Range. Landscape genomic analyses revealed differences in puma movement and gene flow patterns in rural versus urban settings. Our results highlight the utility of dense, genome‐scale markers to document subtle impacts of urbanization on a wide‐ranging carnivore living near a large urban center. Published October 2019 40 ��Wildlife Research Reports MAMMALS – JULY 2019 � https://cpw.cvlcollections.org/files/original/12d69d28e7fcb209d053eaba03cde061.pdf 558883f099a5d5d67dc068d3dbbb4206 PDF Text Text C O L O R A D O P A R K S & W I L D L I F E Wildlife Research Reports MAMMALS – JULY 2020 cpw.state.co.us �__________________________________________ Copies of this publication may be obtained from Colorado Parks and Wildlife Research Library 317 West Prospect, Fort Collins, CO 80526 �WILDLIFE RESEARCH REPORTS JULY 2019–JUNE 2020 MAMMALS RESEARCH PROGRAM COLORADO PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). By providing these summaries, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. ii �EXECUTIVE SUMMARY 7KLV�:LOGOLIH�5HVHDUFK�5HSRUW�UHSUHVHQWV�VXPPDULHV� ”5 pages each with tables and figures) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) from July 2019 through June 2020. These research efforts represent long-term projects (4–10 years) in various stages of completion addressing applied questions to benefit the management and conservation of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx or from the project principal investigators listed at the beginning of each summary. Current research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to habitat alterations, human-wildlife interactions, and investigating improved approaches for wildlife management. The Nongame Mammal Conservation Section addresses ongoing monitoring of lynx in the San Juan mountain range and preliminary results addressing influence of forest management practices on snowshoe hare density in Colorado. The Ungulate Conservation Section includes 4 projects addressing mule deer/energy development interactions to inform future development planning, evaluation of moose demographic parameters that will inform future moose management in Colorado, an evaluation of factors influencing elk calf recruitment, and a recent study initiated to address elk response to human recreation. The Support Services Section describes the CPW library services to provide internal access of CPW publications and online support for wildlife and fisheries management related publications. In addition to the ongoing project summaries described above, Appendix A includes 15 publication abstracts (<2 page summaries) completed by CPW mammals research staff since July 2019. These scientific publications provide results from recently completed CPW research projects and other outside collaborations with universities and wildlife management agencies. Topics addressed include nongame species ecology and conservation (lynx associations with beetle killed forests, assessment of wolverine monitoring, distribution and habitat associations across 4 western states, snowshoe hare morphology, and lynx response to winter recreation), carnivore ecology and management (mountain lion population response to hunter harvest, factors limiting mountain lion populations, evaluation of Colorado’s 2-strike black bear management directive, mountain lion/human interactions along Colorado’s Front Range, and assessment of the social dynamics associated with black bear management along the urban-wildland interface), ungulate ecology and management (mule deer response to energy development activity, 2 publications addressing moose calf detection and estimating parturition dates, and application of acoustic technology to address mule deer foraging behavior), and wildlife genetics research (investigating mountain lion gene flow and genetic diversity). We have benefitted from numerous collaborations that support these projects and the opportunity to work with and train wildlife technicians and graduate students that will likely continue their careers in wildlife management and ecology in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, Montana State University, University of Wyoming, U.S. Bureau of Land Management, U.S. Forest Service, City of Boulder and Jefferson County Open Space, City of Durango, CPW big game auctionraffle grants, Species Conservation Trust Fund, Great Outdoors Colorado, CPW Habitat Partnership Program, Safari Club International, Boone and Crocket Club, Colorado Mule Deer Association, The Mule Deer Foundation, Muley Fanatic Foundation, Wildlife Conservation Society, Summerlee Foundation, EnCana Corp., ExxonMobil/XTO Energy, Marathon Oil, Shell Exploration and Production, WPX Energy, and private land owners providing access to support field research projects. iii �STATE OF COLORADO Jered Polis, Governor DEPARTMENT OF NATURAL RESOURCES Dan Gibbs, Executive Director PARKS AND WILDLIFE COMMISSION Marvin McDaniel, Chair.…………………………………………………………………….............Sedalia Carrie Besnette Hauser, Vice Chair………………………………………………………Glenwood Springs Marie Haskett, Secretary……………………………….………….….………………...................... Meeker Taishya Adams………………………………………………………………………………………Boulder Betsy Blecha……………………………………………………………………………………………Wray Charles Garcia……………………………………………………………………………………….. Denver Dallas May…………………………………………………………………………………………….. Wray Duke Phillips IV…………………………………………………………………………...Colorado Springs Luke B. Schafer………………………………………………………………………………………...Craig James Jay Tutchton…………………………………………………………………………………….Hasty Eden Vardy…………………………………………………………………………………………… Aspen Kate Greenberg, Dept. of Agriculture, Ex-officio….………………………………..…….………..Durango Dan Gibbs, Executive Director, Ex-officio……….…………………...………………….……..........Denver DIRECTOR’S LEADERSHIP TEAM Dan Prenzlow, Director Reid DeWalt, Heather Dugan, Justin Rutter Lauren Truitt, Jeff Ver Steeg, Cory Chick, Brett Ackerman, JT Romatzke, Mark Leslie MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Wildlife Researcher Alexandria Austermann, Research Librarian Eric Bergman, Wildlife Researcher Michelle Gallagher, Program Assistant Jake Ivan, Wildlife Researcher Ken Logan, Wildlife Researcher Nathaniel Rayl, Wildlife Researcher iv �TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS NONGAME MAMMAL CONSERVATION CANADA LYNX MONITORING IN COLORADO by E. Odell, J. Ivan, and S. Wait…………. 2 INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO by J. Ivan and E. Newkirk …...7 UNGULATE MANAGEMENT AND CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson .………………………………………………………………11 EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO by E. Bergman ..………………………………….16 EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO by N. Rayl, M. Alldredge, and C. Anderson….………………………………………………………... 20 SPATIOTEMPORAL EFFECTS OF HUMAN RECREATION ON ELK BEHAVIOR: AN ASSESSMENT WITHIN CRITICAL TIME STAGES by N. Rayl, E. Bergman, and J. Holbrook…………………………………………………………………………………………. 25 SUPPORT SERVICES LIBRARY SERVICES by A. Austermann.…….……………………………...…………………28 APPENDIX A. MAMMALS RESEARCH PUBLICATION ABSTRACTS NONGAME MAMMAL ECOLOGY AND CONSERVATION (publications addressing lynx associations with beetle killed forests and assessment of wolverine monitoring, distribution and habitat associations across 4 western states, 2 publications addressing snowshoe hare morphology, and 1 publication addressing lynx response to winter recreation).………………... 34 CARNIVORE ECOLOGY AND MANAGEMENT (3 mountain lion publications addressing harvest management, factors limiting lion populations, and lion-human interactions; 2 black bear publications addressing Colorado’s 2-strike management directive and the social dynamics of black bear management along the urban interface)….................................................................... 38 UNGULATE ECOLOGY AND MANAGEMENT (2 publications evaluating mule deer response to energy development and auditory technology to investigate mule deer foraging behavior, and 2 publications addressing moose calf detection and estimating parturition dates)............................ 42 WILDLIFE GENETICS RESEARCH (1 publication evaluating mountain lion genetics and gene flow)…….…...…………………………………………................................................................45 v �NONGAME MAMMAL CONSERVATION CANADA LYNX MONITORING IN COLORADO INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO 1 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Canada Lynx Monitoring in Colorado Period Covered: July 1, 2018 � June 30, 2019 Principal Investigators: Eric Odell, Eric.Odell@state.co.us; Jake Ivan, Jake.Ivan@state.co.us; Scott Wait, Scott.Wait@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999�2006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that the population of Canada lynx in the state was apparently viable and self-sustaining. In order to track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is requirHG���'XULQJ�����í�����&3:�LQLWLDWHG�D�SRUWLRQ�RI�WKH�VWDWHZLGH�PRQLWRULQJ�VFKHPH� described in Ivan (2013) by completing surveys in a random sample of monitoring units (n = 50) from the San Juan Mountains in southwest Colorado (n = 179 total units; Figure 1). 'XULQJ�����í�����SHUVRQQHO�IURP�&3:�DQG�86)6�FRPSOHWHG�WKH�ILIWK�\HDU�RI�PRQLWRULQJ�ZRUN� on this same sample. Specifically, 14 units were sampled via snow tracking surveys conducted between December 1 and March 31. On each of 1–3 independent occasions, survey crews searched roadways (paved roads and logging roads) and trails for lynx tracks. Crews searched the maximum linear distance of roads possible within each survey unit given safety and logistical constraints. Each survey covered a minimum of 10 linear kilometers (6.2 miles) distributed across at least 2 quadrants of the unit. The remaining 36 units could not be surveyed via snow tracking. Instead, survey crews deployed 4 passive infrared motion cameras in each of these units during fall 2018. Cameras were baited with visual attractants and scent lure to enhance detection of lynx living in the area. Cameras were retrieved during summer or fall 2019 and all photos were archived and viewed by at least 2 observers to determine species present in each. Camera data were then binned such that each of 10 15-day periods from December 1 through April 30 was considered an ‘occasion,’ and any photo of a lynx obtained during a 15-day period was considered a ‘detection’ during that occasion. Surveyors covered 510 km (317 mi) during snow tracking surveys and detected lynx at 6 units (Table 1). This represents a 5-year low in snow tracking effort and is due mostly to the record-setting snows experienced during the 2018–2019 winter. However, the mean distance surveyed per visit as well as the number of units with lynx remained similar to previous years. Surveyors collected more photos during 2018–2019 than in any other year. This was due in part to replacing snow tracking units with camera units in recent years, but mostly because many cameras were not retrieved until late summer or fall 2019 due to access issues related to the heavy snow pack. For the second year in a row we collected <50% of the number of lynx photos collected during the initial years of the monitoring effort, although the number of units with lynx returned to ‘normal’ after last year’s low (Table 2). Perhaps the abnormal snow patterns during the past few years (lack of snow in 2017–18, record snow in 2018–19) impacted our detection probability. Alternatively, lack of detections could have been due to the new lure (Caven’s 2 �Violator 7; Minnesota Trapline Products, https://www.minntrapprod.com/Bobcat-andLynx/products/829/) we used in 2017–2018 and 2018–19 after the lure we used previously (Pikauba; Luerres Forget’s Lures, http://www.leurresforget.com/product.php?id_product=15) became unavailable. Unfortunately, the changes in snow and lure are confounded, thus making it difficult to determine which factor resulted in fewer detections. We will use the same new lure in 2019–2020, which if accompanied by a normal snowfall, may allow us to retrospectively assess the lack of detections. Compared to previous years, we obtained new lynx detections at a camera unit near Table Mountain northwest of Creede and one north of Lemon Reservior. Also, we detected lynx again for only the second season at a unit west of Trujillo Meadows, near the New Mexico border. However, we failed to detect lynx in two units near Silverton that have had detections each winter since the inception of monitoring (Figure 1). Potential tracks were observed in each of these, but conditions were such that they could not be confirmed. An adult female with kittens was detected at cameras in a unit near Platoro Reservoir, thus documenting that at least some reproduction occurred in the study area. We used the R (R Development Core Team 2018) package ‘RMark’ (Laake 2018) to fit standard occupancy models (MacKenzie et al. 2006) to our survey data using program MARK (White and Burnham 1999). Thus, we estimated the probability of a unit being occupied (i.e., used) by lynx over the course of the winter (\), along with the probability of detecting a lynx (p) given that the unit was occupied. ‘Survey method’ and ‘year’ were treated as group variables so that we could, based on previous work, 1) allow detection probability to vary by survey method, 2) allow for detection probability for 2017–18 and/or 2018–19 to differ from other years due to abnormal snow or new lure, and 3) include a breeding season effect for detection at cameras (lynx tend to move more in late winter when they begin to breed, and thus should encounter cameras more often). We also considered a suite of covariates that could potentially explain variation in occupancy including proportion of the unit that was covered by spruce/fir forest, average years since bark beetle infestation, variability (standard deviation) in years since bark beetle infestation, proportion of the unit impacted by bark beetles, proportion of the unit that was burned during Summer 2013, and the number of photos of other species that could potentially impact presence of lynx (e.g., snowshoe hares as a food source, coyotes as potential competitors). We limited our model set by first setting a general structure for \ while assessing fit of various combinations of variables expected to affect p. We then fixed the best-fitting structure for p, and assessed combinations of the covariates expected to influence \, allowing up to 2 of these covariates at a time, in addition to the covariates on detection. We included data from the pilot study (2010–11) as well as the first five years of PRQLWRULQJ� ����í���� �WR�PD[LPL]H�VKDULQJ�RI�LQIRUPDWLRQ�DFURVV�VXUYH\V��� Since the inception of our monitoring program, the best-fitting model characterized occupancy as a function of 2 covariates: the proportion of the sample unit covered by spruce-fir forest and the number of photos of hares recorded at camera stations (Appendix 1). However, for the 2018–19 sampling year, the best fitting model characterized occupancy as a function of proportion of the sample unit covered by spruce-fir and by the number of cougar photos recorded at camera sites. The association with spruce-fir was positive, indicating that the probability of lynx use increased with more spruce-fir; the association with cougars was negative, indicating that probability of lynx use decreased with more photos of cougars. The second best model included bobcat photos in addition to spruce-fir; again lynx use was negatively associated with increased bobcat photos. Other covariates appeared in top models with spruce-fir, but addition of these covariates did not improve AICc scores beyond the model with spruce-fir only (Appendix 1). This phenomenon indicates that these other variables were not informative. Detection probability was relatively high for snow tracking surveys (p = 0.59, SE=0.05), and relatively low for camera surveys (p = 0.22, SE = 0.03) during December�February and April, although detection at cameras increased to 0.39 (SE = 0.07) during breeding season (March) as expected. We found a significant, negative effect on p during winters when Violator 7 was used as lure (p = 0.03, SE = 0.01 for December�February and April; p = 0.06, SE = 0.03 for breeding season), although it is unclear whether this drop in detection probability was due to abnormal snowpack or the alternate scent lure. We estimated that 31% of the sample units in the San Juan’s were occupied by lynx (95% confidence interval: 12–60%) 3 �during 2018–19. Confidence intervals were quite large for the second year in a row, owing to the extra parameter needed to model the “Violator 7 effect and to the low, poorly estimated detection probability that resulted (Figure 2). The spatial distribution of lynx in the San Juans remained largely unchanged (Figure 1). LITERATURE CITED Ivan, J. S. 2013. Statewide Monitoring of Canada lynx in Colorado: Evaluation of Options. Pages 15-27 in Wildlife Research Report - Mammals. Colorado Parks and Wildlife., Fort Collins, CO, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx Laake, J. L. 2018. Package 'RMark': R Code for Mark Analysis. Version 2.2.5. https://cran.rproject.org/web/packages/RMark/RMark.pdf. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. R Development Core Team. 2018. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120-138. Table 1. Summary statistics from snow tracking effort. Season #Units Surveyed #Units with Lynx #Lynx Tracks #Genetic Samplesa Km Surveyed (Total) Mean Km Surveyed per Visit #CPW Personnel #USFS Personnel 2014–2015 24 8 13 10b 1,088 20.1 30 13 2015–2016 17 7 14 9c 987 21.9 23 6 d 703 18.0 20 8 2016–2017 16 8 13 7 2017–2018 14 7 9 3e 578 19.3 14 5 7 e 510 19.6 16 5 2018–2019 14 6 2 a Number of genetic samples (scat or hair) collected via backtracking putative lynx tracks b DNA analysis confirms that all samples collected from putative lynx tracks were lynx c DNA analysis confirms that 6 of 9 samples were lynx (1 coyote, 1 either mule deer or human, 1undetermined) d DNA analyses confirmed that 5 of 7 samples were lynx (1 coyote, 1 snowshoe hare) e DNA confirmation pending Table 2. Summary statistics from camera effort. Season 2014–2015 #Units Surveyed 32 2015–2016 31 #Units With Lynx #Photos (Total) #Photos (Lynx) #Cameras With Lynx #CPW Personnel 46 #USFS Personnel 12 134,694 301 14 33 9 101,534 455 10 2016–2017 33 29 9 168,705 251 10 6 (5) 2017–2018 35 35 8 173,279 90 8 5 (4) 2018–2019 36 31 7 204,243 60 10 7 (5) a Number in parenthesis indicates units with lynx during the official survey period (Dec 1–Apr 30) 8 (7) 7 (6) 4 �a) b) Figure 1. Lynx monitoring results for a) the current sampling season (2018–2019) and b) the cumulative monitoring effort (2014–2019), San Juan Mountains, southwest Colorado. Colored units (n = 50) indicate those selected at random from the population of units (n = 179) encompassing lynx habitat in the San -XDQ�0RXQWDLQV���/\Q[�ZHUH�GHWHFWHG�LQ����XQLWV�LQ�����í�����DQG����XQLWV�FXPXODWLYHO\�VLQFH� monitoring began in ����í����� 5 �1.0 0.9 0.8 0.7 >, u C: C'tl a. ::::i u u 0 0.6 0.5 0.4 0.3 0.2 0.1 I I I I 0.0 2010 201 1 2012 2013 2014 2015 2016 2017 2018 Year Figure 2. Model-averaged occupancy estimates and 95% confidence intervals for occupancy of Canada lynx in the San Juan Mountains, southwest Colorado. ‘Year’ indicates when the efforts were initiated H�J�������í��������í�� �� Appendix 1. Model selection results for lynx monitoring data collected in the San Juan Mountains, Colorado, 2010–2019. Rankings are based on Akaike’s Information Criterion adjusted for small sample size (AICc). Ten variables were considered as covariates to inform estimation of occupancy (\). The complete model set (n = 56) included all combinations of two, in addition to modeling detection (p) as a function of survey method, breeding season, and alternate lure used during the 2017–18 and 2018–19 seasons. Only the best 10 models are shown. Model AICc 'AICc AICc Wts No. Par. a p(Best ) \ (Cougar + Prop Spruce/Fir) 817.89 0 0.64 12 p(Best) \ (Bobcat + Prop Spruce/Fir) 820.87 2.98 0.15 12 p(Best) \ (Prop Spruce/Fir) 822.92 5.03 0.05 11 p(Best) \ (Prop Burned + Prop Spruce/Fir) 824.14 6.26 0.03 12 p(Best) \ (Coyote + Prop Spruce/Fir) 824.26 6.38 0.03 12 p(Best) \ (Years Since Beetles + Prop Spruce/Fir) 824.46 6.57 0.02 12 p(Best) \ (Fox + Proportion Spruce/Fir) 824.61 6.72 0.02 12 p(Best) \ (Hare + Proportion Spruce/Fir) 825.03 7.14 0.02 12 p(Best) \ (Prop Beetle + Prop Spruce/Fir) 825.06 7.17 0.02 12 p(Best) \ (Variability Beetles + Prop Spruce/Fir) 825.08 7.19 0.02 12 a Best-fitting structure for detection probability included effects for survey method, breeding season, and an effect for the 2017–18 and 2018–19 survey seasons when Violator 7 was used for lure rather than Pikauba. 6 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Influence of forest management on snowshoe hare density in lodgepole and spruce-fir systems in Colorado Period Covered: July 1, 2019 � June 30, 2020 Principal Investigators: Jake Ivan, Jake.Ivan@state.co.us; Eric Newkirk, Eric.Newkirk@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. Understanding and monitoring snowshoe hare (Lepus americanus) density in Colorado is important because hares comprise 70% of the diet of the state-endangered, federally threatened Canada lynx (Lynx canadensis; U.S. Fish and Wildlife Service 2000, Ivan and Shenk 2016). Forest management is an important driver of snowshoe hare density, and all National Forests in Colorado are required to include management direction aimed at conservation of Canada lynx and snowshoe hare as per the Southern Rockies Lynx Amendment (SRLA; https://www.fs.usda.gov/detail/r2/landmanagement/ planning/?cid= stelprdb5356865). At the same time, Forests in the Region are compelled to meet timber production obligations. Such activities may depress snowshoe hare density, improve it, or have mixed effects dependent on the specific activity and the time elapsed since that activity was initiated. Here we describe a sampling scheme to assess impacts of common forest management techniques on snowshoe hare density in both lodgepole pine (Pinus contorta) and spruce-fir (Picea engelmannii – Abies lasiocarpa) systems in Colorado. To select forest stands for sampling, we first used U. S. Forest Service (USFS) spatial data to delineate all spruce-fir and lodgepole pine stands (stratum 1) on USFS land in Colorado, and identified all of the management activities that have occurred in each stand over time. With consultation from the USFS Region 2 Lynx-Silviculture Team, we then grouped relevant forest management activities (stratum 2) into 4 broad catetories: even-aged management, uneven-aged management, thinning, and unmanaged controls. We wanted to assess both the immediate and long-term impacts of management on hare densities. Therefore, when selecting stands for sampling, we took the additional step of binning the date of the most recent management activity into 2-decade intervals (i.e., 0-20, 20-40, and 40-60 years before 2018). We then selected a spatially balanced random sample of 5 stands within each combination of forest type × management activity × time interval. This design ensured that we sampled the complete gradient of time since implementation for each management activity of interest in each forest type of interest. There is no notion of “completion date” for unmanaged controls, so we simply sampled 10 randomly selected stands from this combination. Also, uneven-aged lodgepole pine treatments are rare, so we did not sample that combination (Figure 1). During summer 2018, we established n = 50 1-m2 permanent circular plots within each of the stands selected for sampling. Plot locations within each stand were selected in a spatially balanced, random fashion. Technicians cleared and counted snowshoe hare pellets in each plot as they established them. These same plots were re-visited and re-counted during summers 2019 and 2020. In addition to sampling the previously cleared plots from 2018, technicians were able to install plots at 2 more replicate sites for each combination of forest type × management activity × time interval during 2019. Additionally, a handful of stands visited in 2019 and 2020 were re-classified or tossed based on field 7 �observations and new stands were sampled in their place by pulling the next one from the spatially balanced list. Currently, then inference is based on n = 130 total stands. Pellet information from cleared plots is more accurate than that from uncleared plots because uncleared plots usually include pellet accumulation across several years (Hodges and Mills 2008). The degree to which previous years are represented can depend on local weather conditions, site conditions at the plot, and variability in actual snowshoe hare density over previous winters. Data from cleared plots necessarily reflects hare activity from the previous 12 months, and tracks true density more closely. Therefore, we focused the current analysis on the 2019 and 2020 data from previously cleared plots. For each forest type × management activity combination, we plotted mean pellet counts against “year since activity”, then fit a curve (e.g., quadratic function) through the data (Figure 2). Results from this preliminary analysis suggest that on average the highest snowshoe hare densities typically occur in unmanaged spruce-fir forests, and that unmanaged spruce-fir forests are estimated to have twice the relative hare density of unmanaged lodgepole pine forests (Figure 2). For both forest types, the fitted line suggests that even-aged management (e.g., clearcutting), immediately depresses relative hare density to near zero, but density rebounds and peaks 20-40 years after management before declining again 40-60 years after. Estimated peak hare densities after even-aged management in lodgepole systems tend to be higher than the control condition. However, in spruce-fir systems the estimated fitted line is flatter and peak densities fell well short of the control condition. In both forest types, thinning (which often occurs 20-40 years after stands undergo even-aged management, especially in lodgepole), immediately depresses hare densities. In spruce-fir stands, densities were estimated to slowly recover through time in nearly linear fashion. However, they follow a peaked response in lodgepole pine, similar to the response to even-aged management. Uneven-aged management of spruce-fir forests results in immediate depression of relative hare density, which then recovers back to pre-treatment levels approximately 30 years after the treatment. Note the outlier on the right side of the even-aged lodgepole panel. This “high density” site is an even-aged lodgepole stand that happens to be surrounded by high quality spruce-fir forest on at least two sides. Thus, the high relative hare density observed at this site may be due to the quality habitat in adjacent stands rather than by the quality of the sampled stand itself. While we left the point on the figure for transparency, we excluded it when fitting the curve as it appears to be a true outlier (including it “flattens” the curve somewhat such that it crosses the control line at about 55 years). Literature Cited: Hodges, K. E., and L. S. Mills. 2008. Designing fecal pellet surveys for snowshoe hares. Forest Ecology and Management 256:1918-1926. Ivan, J. S., and T. M. Shenk. 2016. Winter diet and hunting success of Canada lynx in Colorado. The Journal of Wildlife Management 80:1049-1058. U.S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: determination of threatened status for the contiguous U. S. distinct population segment of the Canada lynx and related rule, final rule. Federal Register 65:16052–16086. 8 �Figure 1. Location of all stands (n = 130) resampled for snowshoe hare pellets, June-September 2020. Even-aged Unmanaged Uneven-aged Thinned <I) C 'ci. <I) 4 0 0 a. a.. Cl "O 2 +-' Cl) +-' <I) 0 _J 0 Q) Q) 0 >60 0 10 20 30 40 50 60 0 10 20 30 40 50 60 >60 0 10 20 30 40 50 60 0 10 20 30 40 50 60 0 10 20 30 40 50 60 0 10 20 30 40 50 60 a.. C '- ro .;::: ~ :::J Q) I <I) (.) 4 '- a. CJ) 0 Years Since Treatment Figure 2. Fitted quadratic function (white line) and 95% CI (shaded polygon) relating pellet counts (i.e., relative snowshoe hare density) to time elapsed since treatment for each forest type × management activity combination. Dotted lines indicate the mean pellets/plot for the unmanaged controls for each forest type. 9 �UNGULATE MANAGEMENT AND CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACRIVITY AND HABITAT DEGRADATION EVALUATION AND INCORPORATION OF LIGE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO SPATIOTEMPORAL EFFECTS OF HUMAN RECREATION ON ELK BEHAVIOR: AN ASSESSMENT WITHIN CRITICAL TIME STAGES 10 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation Period Covered: July 1, 2019 ��June 30, 2020 Author: C. R. Anderson, Jr. Personnel: D. Bilyeu-Johnston, D. Collins, B. deVergie, D. Finley, L. Gepfert, T. Knowles, B. Petch, J. Rivale, Z. Swennes, M. Way, CPW; L. Belmonte, BLM; J. Northrup, B. Gerber, G. Wittemyer, Colorado State University; L. Coulter, Coulter Aviation. Project support received from Federal Aid in Wildlife Restoration, Colorado Mule Deer Association, Colorado Mule Deer Foundation, Muley Fanatic Foundation, Colorado State Severance Tax Fund, Caerus Oil and Gas LLC, EnCana Corp., ExxonMobil Production Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, and WPX Energy. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent preliminary and final results of a 10-year research project addressing habitat improvements as mitigation and evaluation of deer responses to energy development activities to inform future development planning options on important seasonal ranges. From 2008 – 2019, we monitored deer on 4 winter range study areas representing relatively high (Ryan Gulch, South Magnolia) and low (North Magnolia, North Ridge) levels of development activity (Fig. 1) to address factors influencing deer behavior and demographics and to evaluate success of habitat treatments as a mitigation option. We recorded adult female habitat use and movement patterns; estimated neonatal, overwinter fawn and annual adult female survival; estimated annual early and late winter body condition, pregnancy and fetal rates of adult females; and estimated annual mule deer abundance among study areas. Winter range habitat improvements completed spring 2013 resulted in 604 acres of mechanically treated pinion-juniper/mountain shrub habitats in each of 2 treatment areas (Fig. 2) with minor (North Magnolia) and extensive (South Magnolia) energy development, respectively. During this research segment, we recovered the remaining store-on-board GPS collars from adult female mule deer during spring/summer 2019, completed the final year of measuring vegetation responses of habitat treatments completed spring 2013 and collected camera grid detections of summer/fall herbivore use of habitat treatment and control sites (preliminary results reported in Anderson 2020, Appendix B). Based on final (migration, mule deer behavioral responses, reproductive success and neonate survival; see Anderson 2020, Appendix A for publication abstracts) and preliminary data analyses (vegetation and herbivore response to habitat treatments, Anderson 2020, Appendix B) for this 10-year project: (1) annual adult female survival was consistent among areas averaging 79-87% annually, but overwinter fawn survival was variable, ranging from 31% to 95% within study areas, with annual and 11 �study area differences primarily due to early winter fawn condition, annual weather conditions, and factors associated with predation on winter range; (2) mule deer body condition early and late winter was generally consistent within areas, with higher variability among study areas early winter, primarily due to December lactation rates, and late winter condition related to seasonal moisture and winter severity; (3) late winter mule deer densities increased through 2016 in all study areas, ranging from 50% in North Ridge to 103% in North Magnolia, but have stabilized recently in 3 of the 4 study areas with recent decline evident in North Ridge (Fig. 3); (4) migratory mule deer selected for areas with increased cover and increased their rate of travel through developed areas, and avoided negative influences through behavioral shifts in timing and rate of migration, but did not avoid development structures (Fig. 4); (5) mule deer exhibited behavioral plasticity in relation to energy development, without evidence of demographic effects, where disturbance distance varied relative to diurnal extent and magnitude of development activity (Fig 5), which provide for useful mitigation options in future development planning; and (6) energy development activity under existing conditions did not influence pregnancy rates, fetal rates or early fawn survival (0-6 months), but may have reduced neonatal survival (March until birth) during 2012 when drought conditions persisted during the third trimester of doe parturition (Fig. 6). Final results are pending to address vegetation and mule deer responses to assess habitat treatment mitigation options for energy development planning. Final data collection efforts for this project were completed by spring 2020. Collaborative research with agency biologists, graduate students, and university professors has produced 22 scientific publications (see Anderson 2020, Appencix A) addressing improved monitoring techniques for neonate mule deer captures; development and evaluation of a remote mule deer collaring device; mule deer migration relative to energy development; improved approaches to address animal habitat use patterns; mule deer response to helicopter capture and handling; potential effects of male-biased harvest on mule deer productivity; mule deer genetics in relation to body condition and migration; acoustic monitoring to investigate spatial and temporal factors influencing mule deer vigilance and foraging behavior; the relationship of plant phenology with mule deer body condition; approaches to identify cause-specific mortality in mule deer from field necropsies; the influence of individual and temporal factors affecting late winter body condition estimates of adult female mule deer; and mule deer behavioral and demographic responses to energy development activities to inform future development planning. Publications describing these results are summarized in Anderson 2020, Appendix A, and preliminary results describing vegetation and herbivore responses to habitat treatments are reported in Anderson 2020, Appendix B. We anticipate the opportunity to work cooperatively toward developing solutions for allowing the nation’s energy reserves to be developed in a manner that benefits wildlife and the people who value both the wildlife and energy resources of Colorado and elsewhere. Literature Cited: Anderson, C. R., Jr. 2020. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Federal Aid in Wildlife Restoration Annual Report W-243-R4, Ft. Collins, CO USA. 12 �study areas Magnolia Well Pad• & Facllitiea : In CJCvelOpmenl l Producing wdl Oe'tet>pmenl rat es "..... Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, winter 2013/14 (Accessed http://cogcc.state.co.us/ December 31, 2013; energy development activity has been minor since 2013). tJCl1t'I MM!r'tlh !rHl!n'M!'II ~~C5B7 a~f) n BNrS~. 15. :l'iob. ll'ld<!I - Bul'Scl_l_8;r,tlA_E D St.lirseue_Shnd,J O.-i!'~&t_g18_929 Grt:n4'o\QClclSeU11...!I~ □ ~1~&t_g1D.Q41 M@'i,'rlr'rrC:M b!.!1'11!'1111 wrn:raliMM'r (~ atr HI ND1lhl1&1ct1fll1utl'red:.int"1"~,11e.t..re!i.J Figure 2. Habitat treatment site delineations in 2 mule deer study areas (604 acres each) of the Piceance Basin, northwest Colorado (Top; cyan polygons completed Jan 2011 using hydro-axe; yellow polygons completed Jan 2012 using hydro-axe, roller-chop, and chaining; and remaining polygons completed Apr 2013 using hydro-axe). January 2011 hydro-axe treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 13 �Piceance Basin late winter mule deer density 35.00 30.00 Deer/km2 25.00 20.00 North Ridge 15.00 Ryan Gulch 10.00 North Magnolia 5.00 South Magnolia 0.00 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Year Figure 3. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2018. Figure 4. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012; http://dx.doi.org/10.1890/ES12-00165.1). 14 �---- +----------- --- - .., I Prod 400 Prod 600 Prod 800 Prod 1000 Drill 400 Covariates Drill 600 Drill 800 Drill 100( 7 '--r--~----.----...----1---.-----..----r-' Prod 400 Prod 600 Prod 800 Prod 1000 Drill 400 Oriti 600 Drill 800 Drill 1OOC Figure 5. Posterior distributions of population-level coefficients related to natural gas development for RSF models during the day (top) and night (bottom) for 53 adult female mule deer in the Piceance Basin, northwest Colorado. Dashed line indicates 0 selection or avoidance (below the line) of the habitat features. ‘Drill’ and ‘Prod’ represent drilling and producing well pads, respectively. The numbers following ‘Drill’ or ‘Prod’ represent the distance from respective well pads evaluated (e.g., ‘Drill 600’ is the number of well pads with active drilling between 400–600 m from the deer location; from Northrup et al. 2015; http://onlinelibrary.wiley.com/doi/10.1111/gcb.13037/abstract). Road disturbance was relatively minor (~60–120 m, not illustrated above). 1.00 0.80 Q) ro,.._ - - - -+ co > 0.60 -~ ::, (/) ro 0.40 +-' Q) LL 0.20 0.00 2012 2013 2014 Year □ High development □ Low development I Figure 6. Model averaged estimates of mule deer fetal survival from early March until birth (late May– June) in high and low energy development study areas of the Piceance Basin, northwest Colorado, 2012– 2014 (from Peterson et al. 2017; http://www.bioone.org/doi/pdf/10.2981/wlb.00341). 15 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation and incorporation of life history traits, nutritional status, and browse characteristics in Shira’s moose management in Colorado Period Covered: July 1, 2019 � June 30, 2020 Principal Investigator: Eric J. Bergman, eric.bergman@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. During November of 2013 we initiated a large scale moose research project in 3 of Colorado Parks and Wildlife’s 4 geographical regions (NE, NW, and SW). After 3 field seasons this research was scaled back and became focused on moose herds in the NW (North Park) and NE (Laramie River) Regions. During FY 20-21 this research project will be completed. A primary objective during all years of this project was the capture of adult female moose for the purposes of deploying VHF and GPS collars, collecting pregnancy data via blood serum, evaluating body condition via ultrasonography, and collecting early winter calf-at-heel ratios. Beginning in 2014–2015 and continuing through the summer of 2019, summer field efforts focused on estimation of parturition rates. Between November 2013 and January 2019, 255 moose were captured. These 255 capture events were comprised of 178 unique individuals and 78 recaptures. Individual animals were recaptured to meet 2 objectives. First, most animals were fitted with GPS collars that have limited battery life. Recapture of individuals allowed replacement of older collars with newer collars that had longer battery life. The second objective was to establish a longitudinal data set that will allow us to determine long-term productivity of individual animals. In particular, repeated measurements of individuals will allow us to evaluate if different reproductive strategies occur within moose, and if those strategies can be linked to annual variation within individual condition. Over the course of this study, we observed that the probability of moose being pregnant was best predicted by considering maximum loin depth. Regional and annual effects in pregnancy rates are yet to be evaluated. Survival of radio collared animals was high in all study areas (85%–96%). Pregnancy rates were similar between areas (70% in NW Colorado, 60% in NE Colorado), but a high degree of annual variability was observed and strong inference was limited by samples size. Over the course of this study, calf-at-heel estimates at the time of capture have average 0.55. Beginning during the summer of 2017 and continuing through the summer of 2019, vegetation sampling occurred in NW and NE Colorado. These efforts were directed at: 1) identifying willow community diversity at known moose locations, 2) determining if moose demonstrate preference among willow species while browsing, and 3) to determine the nutritional quality of willows throughout the summer period. Ultimately, these data showed a direct correlation between the probability that a cow moose was observed with a calf and the total amount of willow in the cow’s home range. A similar correlation was not observed for any specific species of willow, nor was there a strong correlation with the dry-matter digestibility of willows. Completed analyses of data from this project initially focused on quantification of detection probabilities. More specifically, ground observations used to estimate productivity and calf-at-heel rates are prone to observer bias and misclassification. When a cow moose was observed without a calf, there 16 �was some possibility that a calf was present but obscured from the observer’s view. Relying on repeated observations of moose, this detection probability was estimated to be 0.80 (i.e., when a calf was present, it was actually observed 80% of the time). Estimation of this probability was necessary to facilitate an unbiased approximation of parturition timing, but also to minimize bias in future analyses that will focus on moose herd productivity from this study period. Thus, data collected during this project met expectations. In particular, survival rates were consistently high in all study areas. However, a large degree variation within pregnancy rates was observed, which is intriguing. Despite variant and lower than expected pregnancy rates during the course of this study, observed winter calf-at-heel rates suggest that moose calf survival during the first 6 months of life is high. During FY 20-21, data collected during this study will be analyzed to reconstruct moose population dynamics and to formulate population and harvest management recommendations. Ch.n·,1111t ~ Northeast Study Area Northwest Study A · . , , • ' ·~ ·-· ,.&.tool~ Al s'outhw Study,f;'efJ· Ji' Figure 1. Moose research study areas, located in 3 regions in Colorado. A total of 255 moose were captured during winters between 2013–2014 and 2018–2019. 17 �100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% I I I I I n I 1µ " - I ~ -I " -. " I I I " ■ I I ,-- -r-- 2013-2014 2014-2015 2015-2016 2016-2017 2017-2018 2018-2019 Probability of Being Pregnant Figure 2. Pregnancy data were collected for all moose at the time of capture. Data from northwest Colorado are depicted by black bars, data from northeast Colorado are depicted by gray bars, and data from southwest Colorado are depicted by white bars. Data from southwest were sparse during 2015–2016 (n = 7 animals) and not collected between 2016–2019. The cause and consequences of the low pregnancy rate observed in northwest Colorado during 2016–2017 were never determined and that was considered to be an outlier event. 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 ,,,--------------------■---- ,, ,, ,/ ,,,/ ,,,,, / / / / _________________ ,,,,' ___ , ,,,, 1 6 11 16 ,,,, ,, ,, ,,,, ,, ,, ,, 21 26 31 36 41 46 Moose Loin Depth (mm) 51 56 Figure 3. During the course of this study, probability of moose pregnancy has been best predicted by measured loin depth. The relationship between body condition and pregnancy status is reflected by the solid black line and from data collected during the all 5 years of the study (dotted lines represent 95% confidence intervals for moose pregnancy probability). No regional effects were found in our data, and the lack of significance of annual effects in our best performing models is likely driven by small sample sizes. 18 �Proportion of Cows with Calves at Heel (capture) 1.00 0.90 0.80 0.70 0.60 0.50 0.40 0.30 0.20 0.10 0.00 2013-2014 2014-2015 2015-2016 2016-2017 2017-2018 Figure 4. Moose calf-at-heel data were collected for all cow moose at the time of capture. Data from northwest Colorado are depicted by black bars, data from northeast Colorado are depicted by gray bars, and data from southwest Colorado are depicted by white bars. Data from southwest were sparse during 2015–2016 (n = 7 animals) and not collected during 2016–2017 or 2017–2018. Overall, recruitment of moose calves into the winter time period has consistently exceeded 50%. Anecdotal evidence suggests that overwinter survival of moose calves in Colorado is high, thereby lending evidence moose herds are likely stable or increasing despite documented highly variable pregnancy rates. 19 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluating factors influencing elk recruitment in Colorado Period Covered: July 1, 2019-June 30, 2020 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Mat Alldredge, mat.alldredge@state.co.us; Chuck Anderson chuck.anderson@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In Colorado, elk (Cervus canadensis) are an important natural resource that are valued for ecological, consumptive, aesthetic, and economic reasons. In 1910, less than 1,000 elk remained in Colorado, but today the state population is estimated to be the largest in the country, with more than 290,000 elk. Over the last two decades, however, wildlife managers in Colorado have become increasingly concerned about declining winter elk calf recruitment (estimated using juvenile:adult female ratios) in the southern portion of the state. Although juvenile:adult female ratios are often highly correlated with juvenile elk survival, they are an imperfect estimate of recruitment because they are affected by harvest, pregnancy rates, juvenile survival, and adult female survival. Thus, there is a need for elk research in Colorado based upon monitoring of marked individuals to evaluate factors affecting each stage of production and survival. In 2016, Colorado Parks and Wildlife (CPW) began a 2-year pilot study to investigate factors influencing elk recruitment in 2 elk Data Analysis Units (DAUs; E-20, E-33) with low juvenile:adult female ratios (Fig. 1). In 2019, CPW expanded this pilot study work into a 3rd DAU with high juvenile:adult female ratios (E-2), to better determine how predators, habitat, and weather conditions are impacting elk recruitment in Colorado. During the past year we focused on capturing and collaring elk and working with stakeholders and collaborators on research logistics. Field efforts were centered on 2 objectives: 1) capturing adult female elk, and collaring and outfitting pregnant females with vaginal implant transmitters (VITs) to collect data on elk demography, body condition, reproduction, and behavior, and 2) capturing and collaring newborn and 6-month old elk to collect data on calf survival and cause-specific mortality. In December 2019, we collared 50 6-month old elk calves, 25 each from the Bear’s Ears (DAU E-2) and Uncompahgre Plateau (DAU E-20) elk herds. The mean weight of calves from the Bear’s Ears herd was 101.8 kg (224.4 lb) (95% CI = 96.5-107.2 kg [212.7-236.3 lb]) and 113.9 kg (251.1 lb) (95% CI = 108.4-119.4 kg [239.0-263.2 lb]) from the Uncompahgre Plateau elk herd. During March 2020, we captured 113 adult female elk by helicopter net-gunning, 43 from the Bear’s Ears herd, 27 from the Trinchera herd (DAU E-33), and 43 from the Uncompahgre Plateau herd. We radio-collared 98 pregnant elk and outfitted them with VITs, 40 each from the Bear’s Ears and Uncompahgre Plateau herds, and 18 from the Trinchera herd. Additionally, we collared 1 non-pregnant elk from the Trinchera herd. 20 �In 2020, we estimated that pregnancy rates of adult female elk were 93% in the Bear’s Ears and Uncompahgre Plateau herds (both 95% CI = 81-98%; n = 43), and 78% in the Trinchera herd (95% CI = 59-89%; n = 27; Fig. 2). Elk populations experiencing good to excellent summer-autumn nutrition typically have pregnancy raWHV�•���� We estimated the mean IFBF of adult female elk to be 6.51% from the Bear’s Ears herd, 7.51% from the Trinchera herd, and 7.03% from the Uncompahgre Plateau herd (Fig. 3). When late-winter IFBF values are <8-9% for adult female elk that have lactated through the previous growing season, this suggests that there may be nutritional limitations, but it does not identify whether limitations are a result of summer-autumn or winter nutrition (R. Cook, personal communication). During May-July 2020, we captured and collared 127 elk calves, 54 from the Bear’s Ears herd, 21 from the Trinchera herd, and 52 from the Uncompahgre Plateau herd. From the Bear’s Ears and Uncompahgre Plateau herds, we successfully captured and collared 90% (35/39) of the calves of adult female elk outfitted with VITs. From the Trinchera herd, we successfully captured and collared 100% (15/15) of the calves of adult female elk outfitted with VITs. The estimated mean date of calving was May 31 in the Bear’s Ears and Uncompahgre Plateau herds, and June 3 in the Trinchera herd (Fig. 4). E-4 Calves:100 adult females (2013-2017) Insufficient data 0 25-30 30-350 35-400 40-450 45-500 50-55 55-60 E-51 E-99 0 30 60 Miles Figure 1. Number of elk calves per 100 adult females observed during December-February aerial surveys (5-year average from 2013-2017) within elk Data Analysis Units (DAUs; labeled with black text) in Colorado, USA. 21 �■ Bears Ear's ■ Trinchera ■ Uncompahgre Plateau 1.0 0.9 31 27 43 31 43 31 .....C 0.8 ~ 0.7 0) Cl) a. 0.6 C o 0 .5 t: g_o.4 e a.. 0.3 0.2 0.1 o.o~- 2017 2018 2019 2020 Year Figure 2. Estimated average pregnancy rates of adult female elk from the Bear’s Ears, Trinchera, and Uncompahgre Plateau herds sampled during late winter 2017-2020 in Colorado, USA. The sample size is given at the top of the 95% binomial confidence intervals (black lines). 22 �11 · • 1o- •• -- 9· --..... ~ 0 ~ >- 8· "'O 0 ..0 Q) Q) '-- 7· .,._ I ro 6..... en Q) O> C 5· 4· • 3· ' Bear's Ears ' Trinchera ' Uncompahgre Plateau Herd Figure 3. The estimated ingesta-free body fat (%) of adult female elk from the Bear’s Ears (n = 43), Trinchera (n = 25), and Uncompahgre Plateau (n = 42) herds during late-winter 2020 in Colorado, USA. 23 �Jul 01- • •• ...u Jun 1S- Q) m C> C > 8 Jun 01 I May 15- • ' Bear's Ears ' ' Trinchera Uncompahgre Plateau Herd Figure 4. The distribution of calving dates of adult female elk estimated from vaginal implant transmitters (VITs) from the Bear’s Ears (n = 39), Trinchera (n = 15), and Uncompahgre Plateau (n = 39) herds during 2020 in Colorado, USA. 24 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Spatiotemporal effects of human recreation on elk behavior: an assessment within critical time stages Period Covered: July 1, 2019-June 30, 2020 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Eric Bergman, eric.bergman@state.co.us; Joe Holbrook, Joe.Holbrook@uwyo.edu All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. The influence of recreational disturbance on ungulate populations is of particular interest to wildlife managers in Colorado, as there is growing concern about its potential impacts within the state. Currently, the western United States is experiencing some of the highest rates of human population growth in the country, with growth in rural and exurban areas frequently outpacing growth in urban areas. Additionally, participation in outdoor recreation is also increasing. In Colorado, the number of individuals participating in recreational activities, and the associated demand for recreational opportunities, appear to be increasing. Understanding potential impacts of recreational activity on elk spatial ecology in Colorado is critical for guiding management actions, as altered movements may result in reduced foraging time and higher energetic costs, which may decrease fitness. We are studying elk from the resident portion of the Bear’s Ears elk herd (DAU E-2) in Colorado to determine potential impacts of recreational activities on this population (Fig. 1). This research project is a collaboration between Colorado Parks and Wildlife (CPW) and the Haub School of Environment and Natural Resources at the University of Wyoming, and will form the basis of an M.S. thesis for a graduate student enrolled at the Haub School. In January 2020, we collared 30 adult female elk from the resident portion of the Bear's Ears elk herd on U.S. Forest Service (USFS) land near Steamboat Springs. The estimated pregnancy rate was 93% (95% CI: 79-98%). This spring, summer, and fall we will be deploying trail counters and cameras at trailheads in the study area, and handing out GPS units to recreationists to quantify human recreation on the landscape and evaluate how elk respond to recreationists. 25 �DENVER • Colorado 5 10 Figure 1. Routt National Forest study area located in northwest Colorado, USA. 26 �SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT 27 �a 7 !..5!,�2%0/24 &2/25$'2�3$5.6� �:,/'/,)( 5(6($5&+�/,%5$5< �*5,9���������*5.%��������� -Ѵ;Š-m7ub-ĺ-†v|;ul-mmŠv|-|;ĺ1oĺ†v _||rvĹņņ1r‰ĺ1-|-Ѵo]ĺ-vr;m1-|ĺbm=oņ �ѴѴ�bm=oul-|bom�bm�|_bv�u;rou|�bv�ru;Ѵblbm-u‹�-m7�v†0f;1|�|o =†u|_;u�;ˆ-Ѵ†-|bomĺ��m=oul-|bom���+���$�� ��&���"� �!� &�$ �‰b|_o†|�r;ulbvvbom�o=�|_;�-†|_ouĺ��-mbr†Ѵ-|bom o=�|_;v;�7-|-�0;‹om7�|_-|�1om|-bm;7�bm�|_bv�u;rou|�bv 7bv1o†u-];7ĺ .%7�,)"2!29�#!4!,/' ,Q�$SULO��WKH�/LEUDU\�VZLWFKHG�WR�WKH�QHZ�OLEUDU\ FDWDORJ��$VSHQ&DW��$VSHQ&DW�LV�D�XQLRQ�FDWDORJ� PHDQLQJ�LW�LV�FRPSRVHG�RI�D�JURXS�RI�OLEUDULHV�WKDW DJUHH�WR�VKDUH�UHVRXUFHV�ZLWK�HDFK�RWKHU��$VSHQ&DW�LV VLJQLILFDQWO\�FKHDSHU�WKDQ�WKH�ROG�OLEUDU\�FDWDORJ�DQG RIIHUV�PRUH�EHQHILW�WR�SDWURQV��LQFOXGLQJ�WKH�DELOLW\�WR FKHFN�RXW�H�ERRNV�DQG�H�DXGLRERRNV��IURP�WKH SDUWLFLSDWLQJ�SXEOLF�OLEUDULHV�b Catalog prke Patrons added 25 dropped by 84% 20 ----- 15 10 New patron regiistrati ons increased by 5 0 1000% ■ FY2016 ■ FY2017 ■ FY2018 ■ FY2019 ■ FY2020 �()34/29 7KH�/LEUDU\�ZDV�FUHDWHG�LQ�WKH�ODWH�����V��DW�WKH�)RUW�&ROOLQV�RIILFH��WR SURYLGH�VXSSRUW�SULPDULO\�WR�WKH�ZLOGOLIH�UHVHDUFK�VHFWLRQV��:LWK�WKH FKDQJLQJ�QHHGV�RI�&3:��WKH�PLVVLRQ�RI�WKH�/LEUDU\�KDV�H[SDQGHG�WR�VHUYH�DOO &3:�VWDII�UHJDUGOHVV�RI�ORFDWLRQ��7KH�/LEUDU\�LV�QRZ�YLWDO�WR�WKH�VFLHQFH� GULYHQ�ZLOGOLIH�PDQDJHPHQW�ZRUN�RI�WKH�DJHQF\��7KH�/LEUDULDQ�KDV�EHFRPH�D YDOXHG�SDUWQHU�LQ�DVVLVWLQJ�ZLWK�UHVHDUFK�DQG�VXSSO\LQJ�IXOO�WH[W�UHIHUHQFH UHVRXUFHV�IRU�WKH�ZRUN�GRQH�E\�ELRORJLVWV��UHVHDUFKHUV�DQG�ZLOGOLIH PDQDJHUV�DFURVV�WKH�VWDWH� -)33)/.�34!4%-%.4 $_;�!;v;-u1_��b0u-u‹�v;uˆ;v�Ƒ�r†urov;vĺ� Ɛĺ�$_;�Ѵb0u-u‹�v†rrou|v�‰bѴ7Ѵb=;�u;v;-u1_�-m7�l-m-];l;m|�0‹�ruoˆb7bm]�m;;7;7 bm=oul-|bom�bm1Ѵ†7bm]�0oohv�-m7�=†ѴѴŊ|;Š|�-u|b1Ѵ;vĺ� Ƒĺ�$_;�Ѵb0u-u‹�v;uˆ;v�-v�-m�bmv|b|†|bom-Ѵ�u;rovb|ou‹�=ou�7o1†l;m|v�‰ub||;m�0‹�7bˆbvbom v|-==�-m7�l-h;v�|_ov;�=u;;Ѵ‹�-ˆ-bѴ-0Ѵ;�|o�|_;�r†0Ѵb1ĺ �Chart Tit le !24)#,%3 5HTXHVWV�IRU�DUWLFOHV�KDYH�UHPDLQHG FRQVLVWHQW�ZLWK�\HDUV�SDVW��GHVSLWH�PDQ\ SHRSOH�ZRUNLQJ�IURP�KRPH�VLQFH�0DUFK� 7KHUH�ZDV�D�VSLNH�LQ�-XQH��EXW�QR�REYLRXV FDXVH� 0 Jul Aug Sep - II I I Oct Dec Nov FY2.020 - Jan Feb Mar Aver c€e FY2010-FY2019 "5$'%4 -RXUQDO�DQG�GDWDEDVH�VXEVFULSWLRQV�UHPDLQ�WKH�EXON�RI�WKH�OLEUDU\�EXGJHW��7KH OLEUDU\�FDWDORJ�IHOO�IURP�����RI�WKH�EXGJHW�LQ�)<�����WR����LQ�)<����� ~ Other (Includes, Books, Office Supplies, Recycl ing, Sh ipping and Travel) 4% Technology \ 11% \ \ LIBRARY BUDGET Joumal/Database Subscriptions 81% Apr May Jun �LULLI !::!:: Q L.Ur =::::, ___J- ___Jo https://cpw.catalog.aspencat.info/ CPW Research Library LUI.I.I !:::!:::C .....1- L.U;!? >::, .....10 • . TOGETHER ,. . https://cpw.catalog.aspencat.info/ �APPENDIX A. CPW mammal research abstracts published July 2019 – November 2020. 33 �NONGAME MAMMAL ECOLOGY AND CONSERVATION A specialized forest carnivore navigates landscape-level disturbance: Canada lynx in spruce-beetle impacted forests John R. Squires,a Joseph D. Holbrook,b Lucretia E. Olson,a Jacob S. Ivan,c Randal W. Ghormley,d Rick L. Lawrencee a USDA Forest Service, Rocky Mountain Research Station, Missoula, MT, USA b Haub School of Environment and Natural Resources, Department of Zoology and Physiology, University of Wyoming, Laramie, WY, USA c Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO, USA d Rio Grande National Forest (retired), Monte Vista, CO, USA e Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT, USA Citation: Squires, J. R., J. D. Holbrook, L. E. Olson, J. S. Ivan, R. W. Ghormley, and R. L. Lawrence. 2020. A specialized forest carnivore navigates landscape-level disturbance: Canada lynx in spruce-beetle impacted forests. Forest Ecology and Management 475:118400. ABSTRACT Canada lynx (Lynx canadensis) occupy cold wet forests (boreal and subalpine forest) that were structured by natural disturbance processes for millennia. In the Southern Rocky Mountains, at the species’ southern range periphery, Canada lynx habitat has been recently impacted by large-scale disturbance from spruce beetles (Dendroctonus rufipennis). This disturbance poses a challenge for forest managers who must administer this novel landscape in ways that also facilitate timber salvage. To aid managers with this problem, we instrumented Canada lynx with GPS collars to document their selection of beetle impacted forests at spatial scales that spanned from landscapes to movement paths. We used a use-availability design based on remotely-sensed covariates to evaluate landscape- and path-level selection. We evaluated selection at the home-range scale in beetle-kill areas based on vegetation plots sampled in the field to quantify forest structure and composition. We found that across all scales of selection, Canada lynx selected forests with a higher proportion of beetle-kill trees that were generally larger in diameter than randomly available. Within home ranges, Canada lynx selected forests with greater live components of subalpine fir and live canopy of Engelmann spruce. During winter, Canada lynx exhibited functional responses, or disproportionate use relative to availability, for forest horizontal cover, diameter of beetle killed trees, live canopy of Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa), and additive use (and consistent selection) for relative density of snowshoe hares and density of subcanopy subalpine fir 3–4.9 in. (7.6–12.4 cm) in diameter. We discuss our results in the context of balancing resource needs of Canada lynx with the desire to salvage timber in beetle-impacted forests. Published July 2020 Wolverine Occupancy, Spatial Distribution, and Monitoring Design P. M. Lukacs,a D. E. Mack,b R. Inman,c J. A. Gude,c J. S. Ivan,d R. P. Lanka,e J. C. Lewis,f R. A. Long,g R. Sallabanks,h Z. Walker,i S. Courville,j S. Jackson,k R. Kahn,l M. K. Schwartz,m S. C. Torbit,n J. S. Waller,o K. Carrollp aWildlife Biology Program, Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, 59812 USA b Idaho Department of Fish and Game, McCall Subregion, 555 Deinhard Lane, McCall, ID, 83638 USA c Montana Fish, Wildlife and Parks, 1420 East 6th Ave., P.O. Box 200701, Helena, MT, 59620 USA d Mammals Research Section, Colorado Parks and Widlife, 317 W. Prospect Rd., Fort Collins, CO, USA e Wyoming Game and Fish Department (Retired), 5400 Bishop Blvd., Cheyenne, WY, 82006 USA f Washington Department of Fish and Wildlife, 1111 Washington Street SE, Olympia, WA, 98501 USA g Woodland Park Zoo, 5500 Phinney Ave. N, Seattle, WA, 98103 USA h Idaho Department of Fish and Game, 600 S. Walnut St., Boise, ID, 83707 USA i Wyoming Game and Fish Department, 260 Buena Vista, Lander, WY, 82520 USA j Confederated Salish and Kootenai Tribe, P.O. Box 278, Pablo, MT, 59855 USA k USDA Forest Service, 26 Fort Missoula Road, Missoula, MT, 59804 USA l National Park Service (Retired), NRSS Biological Resource Management Division, 1201 Oakridge Drive, Suite 200, Fort Collins, CO, 80525 USA m National Genomics Center for Wildlife and Fish Conservation, USDA Forest Service, Rocky Mountain Research Station, 800 E. Beckwith Ave., Missoula, MT, 59801 USA n U.S. Fish and Wildlife Service (Retired), Mountain Prairie Region, Lakewood, CO, 80228 USA o Glacier National Park, P.O. Box 128, West Glacier, MT, 59936 USA p 'HSDUWPHQW�RI�(FRORJ\�0RQWDQD�6WDWH�8QLYHUVLW\��3�2��%R[���������%R]HPDQ��07�������ဨ3460 USA Citation: Lukacs, P. M., D. Evans Mack, R. Inman, J. A. Gude, J. S. Ivan, R. P. Lanka, J. C. Lewis, R. A. Long, R. Sallabanks, Z. Walker, S. Courville, S. Jackson, R. Kahn, M. K. Schwartz, S. C. Torbit, J. S. Waller, and K. Carroll. 2020. Wolverine Occupancy, Spatial Distribution, and Monitoring Design. Journal of Wildlife Management 84:841–851. ABSTRACT In the western United States, wolverines (Gulo gulo �W\SLFDOO\�RFFXS\�KLJKဨHOHYDWLRQ�KDELWDWV�� Because wolverine populations occur in vast, remote areas across multiple states, biologists have an imperfect 34 �understanding of this species' current distribution and population status. The historical extirpation of the wolverine, a subsequent period of recovery, and the lack of a coordinated monitoring program in the western United States to determine their current distribution further complicate understanding of their population status. We sought to define the limits to the current distribution, identify potential gaps in distribution, and provide a baseline dataset for future monitoring and analysis of factors contributing to changes in distribution of wolverines across 4 western states. We XVHG�UHPRWHO\�WULJJHUHG�FDPHUD�VWDWLRQV�DQG�KDLU�VQDUHV�WR�GHWHFW�ZROYHULQHV�DFURVV�UDQGRPO\�VHOHFWHG���ဨNPௗîௗ��ဨ km cells in Idaho, Montana, Washington, and Wyoming, USA, during winters 2016 and 2017. We used spatial occupancy models to examine patterns in wolverine distribution. We also examined the influence of proportion of the cell containing predicted wolverine hDELWDW��KXPDQဨPRGLILHG�ODQG��DQG�JUHHQ�YHJHWDWLRQ��DQG�DUHD�RI�WKH�FOXVWHU� of contiguous sampling cells. We sampled 183 (28.9%) of 633 cells that comprised a suspected wolverine range in these 4 states and we detected wolverines in 59 (32.2%) of these 183 sampled cells. We estimated that 268 cells �����������&,ௗ ௗ���–347) of the 633 cells were used by wolverines. Proportion of the cell containing modeled wolverine habitat was weakly positively correlated with wolverine occupancy, but no other covariates examined ZHUH�FRUUHODWHG�ZLWK�ZROYHULQH�RFFXSDQF\��2FFXSDQF\�UDWHV� ȥ �ZHUH�KLJKHVW�LQ�WKH�1RUWKHUQ�&RQWLQHQWDO�'LYLGH� (FRV\VWHP� ȥ�UDQJHௗ ௗ���–� ��LQWHUPHGLDWH�LQ�WKH�&DVFDGHV�DQG�&HQWUDO�0RXQWDLQV�RI�,GDKR� ȥ�UDQJHௗ ௗ���–0.6), and lower in the Greater YellRZVWRQH�(FRV\VWHP� ȥ�UDQJHௗ ௗ���–0.3). We provide baseline data for future surveys of wolverine along with a design and protocol to conduct those surveys. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society. Published March 2020 Latitudinal variation in snowshoe hare (Lepus americanus) body mass: a test of Bergmann’s rule Gigliotti, L. C.,a N. D. Berg,b R. Boonstra,c S. M. Cleveland,d D. R. Diefenbach,e E. M. Gese,f J. S. Ivan,g K. Kielland,h C. J. Krebs,i A. V. Kumar,j L. S. Mills,j J. N. Pauli,k H. B. Underwood,l E. C. Wilson,k and M. J. Sheriffm a Department of Forestry and Environmental Conservation, Clemson University, 261 Lehotsky Hall, Clemson, SC 29634, USA b U.S. Fish and Wildlife Service, National Wildlife Refuge System, Anchorage, AK 99503, USA c Department of Biological Sciences, University of Toronto Scarborough, Toronto, ON M1C 1A4, Canada d Department of Environmental and Forest Biology, State University of New York College of Environmental Science and Forestry, Syracuse, NY 13210, USA e U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, Pennsylvania State University, University Park, PA 16802, USA f U.S. Department of Agriculture, Wildlife Services, National Wildlife Research Center, Department of Wildland Resources, Utah State University, Logan, UT 84322, USA g Mammals Research Section, Colorado Parks and Widlife, 317 W. Prospect Rd., Fort Collins, CO, USA h Department of Biology and Wildlife, Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK 99775, USA i Department of Zoology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada j Wildlife Biology Program, University of Montana, Missoula, MT 59812, USA. k Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI 53706, USA l U.S. Geological Survey, Patuxent Wildlife Research Center, Tunison Laboratory of Aquatic Science, Cortland, NY 13043, USA m Biology Department, University of Massachusetts Dartmouth, Dartmouth, MA 02747, USA Citation: Gigliotti, L. C., N. D. Berg, R. Boonstra, S. M. Cleveland, D. R. Diefenbach, E. M. Gese, J. S. Ivan, K. Kielland, C. J. Krebs, A. V. Kumar, L. S. Mills, J. N. Pauli, H. B. Underwood, E. C. Wilson, and M. J. Sheriff. 2020. Latitudinal variation in snowshoe hare (Lepus americanus) body mass: A test of Bergmann’s rule. Canadian Journal of Zoology 4:1–35. Abstract: The relationship between body size and latitude has been the focus of dozens of studies across many species. However, results of testing Bergmann’s rule — that organisms in colder climates or at higher latitudes possess larger body sizes — have been inconsistent across studies. We investigated whether snowshoe hares (Lepus americanus Erxleben, 1777) follow Bergmann’s rule by investigating differences in body mass using data from six published studies and from data of 755 individual hares captured from 10 populations across North America covering 26° of north latitude. We also explored alternative hypotheses related to variation in hare body mass, including winter severity, length of growing season, elevation, and snow depth. We found body mass of hares varied throughout their range, but the drivers of body mass differed based on geographic location. In northern populations, females followed Bergmann’s rule, whereas males did not. In northern populations, male mass was related to mean snow depth. In contrast, in southern populations, body mass of both sexes was related to length of the growing season. These differences likely represent variation in the drivers of selection. Specifically, in the north, a large body size is beneficial to conserve heat because of low winter temperatures, whereas in the south, it is likely due to increased food supply associated with longer growing seasons. Published September 2019 35 �Local climate determines vulnerability to camouflage mismatch in snowshoe hares Zimova, M.,a A. P. K. Sirén,b J. J. Nowak,a A. M. Bryan,b J. S. Ivan,c T. Lyn,b S. L. Suhrer,a J. Whittington,d and L. S. Millsa Wildlife Biology Program, University of Montana, Missoula, MT 59812, USA b U.S.G.S, Northeast Climate Adaptation Science Center, Amherst, MA, USA c Mammals Research Section, Colorado Parks and Widlife, 317 W. Prospect Rd., Fort Collins, CO, USA d Parks Canada, Banff National Park Resource Conservation, Banff, Alberta, Canada a Citation: Zimova, M., A. P. K. Sirén, J. J. Nowak, A. M. Bryan, J. S. Ivan, T. Lyn, S. L. Suhrer, J. Whittington, and L. S. Mills. 2020. Local climate determines vulnerability to camouflage mismatch in snowshoe hares. Global Ecology and Biogeography 29:503–515. ABSTRACT Aim 3KHQRORJLFDO�PLVPDWFKHV��ZKHQ�OLIHဨHYHQWV�EHFRPH�PLVWLPHG�ZLWK�RSWLPDO�HQYLURQPHQWDO�FRQGLWLRQV��KDYH� become increasingly common XQGHU�FOLPDWH�FKDQJH��3RSXODWLRQဨOHYHO�VXVFHSWLELOLW\�WR�PLVPDWFKHV�GHSHQGV�RQ�KRZ� phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal. Location North America. Time period 2010–2017. Major taxa studied Snowshoe hare (Lepus americanus). Results Spatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on GDUN��VQRZOHVV�EDFNJURXQG�RFFXUUHG�SULPDULO\�GXULQJ�ORZဨVQRZ�\HDUV�LQ�UHJLRQV FKDUDFWHUL]HG�E\�VKDOORZ��VKRUWဨ lasting snowpack. Major conclusions /RQJဨWHUP�FOLPDWH�DQG�DQQXDO�YDULDWLRQ�LQ�VQRZ�DQG�WHPSHUDWXUH�GHWHUPLQH�FRDW�FRORXU�PRXOW� phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of FDPRXIODJH�PLVPDWFK�YDULHV�DFURVV�WKH�VSHFLHV¶�UDQJH��2XU�UHVXOWV�XQGHUVFRUH�WKH�SRSXODWLRQဨVSHFLILF�VXVFHSWLELOLW\� WR�FOLPDWH�FKDQJHဨLQGXFHG�VWUHVVRUV�DQG�WKH�QHFHVVLW\�WR�XQGHUVWDQG�WKLV�YDULDWLRQ�WR�SULRULWL]H�WKH�SRSXODWLRQV�PRVW� vulnerable under global environmental change. Published December 2019 Winter recreation and Canada lynx: reducing conflict through niche partitioning John R. Squires,a Lucretia E. Olson,a Elizabeth K. Roberts,b Jacob S. Ivan,c and Mark Hebblewhited a Rocky Mountain Research Station, U.S. Forest Service, 800 Beckwith Avenue, Missoula, MT 59801, USA b White River National Forest, 900 Grand Avenue, Glenwood Springs, CO 80601, USA c Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA d Wildlife Biology Program, Department of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation, University of Montana, 32 Campus Drive, Missoula, MT 59812, USA Citation: Squires, J. R., L. E. Olson, E. K. Roberts, J. S. Ivan, and M. Hebblewhite. 2019. Winter recreation and Canada lynx: reducing conflict through niche partitioning. Ecosphere 10(10); doi.org/10.1002/ecs2.2876 ABSTRACT Outdoor recreationists are important advocates for wildlife on public lands. However, balancing potential impacts associated with increased human disturbance with the conservation of sensitive species is a central issue facing ecologists and land managers alike, especially for dispersed winter recreation due to its disproportionate impact to wildlife. We studied how dispersed winter recreation (outside developed ski areas) impacted a UHLQWURGXFHG�PHVRဨFDUQLYRUH��&DQDGD�O\Q[� Lynx canadensis), at the southern periphery of the species’ range in the southern Rocky Mountains. On a voluntary basis, we distributed global positioning system (GPS) units to winter recreationists and documented 2143 spatial movement tracks of recreationists engaged in motorized and nonmotorized winter sports for a total cumulative distance of 56,000 km from 2010 to 2013. We also deployed GPS radio collars on adult Canada lynx that were resident in the mountainous topography that attracted high levels of GLVSHUVHG�ZLQWHU�UHFUHDWLRQ��:H�GRFXPHQWHG�WKDW�UHVRXUFHဨVHOHFWLRQ�PRGHOV� 56)V �IRU�&DQDGD�O\Q[�ZHUH VLJQLILFDQWO\�LPSURYHG�ZKHQ�VHOHFWLRQ�SDWWHUQV�RI�ZLQWHU�UHFUHDWLRQLVWV�ZHUH�LQFOXGHG�LQ�EHVWဨSHUIRUPLQJ�PRGHOV�� Canada lynx and winter recreationists partitioned environmental gradients in ways that reduced the potential for UHFUHDWLRQဨUHODWHG�GLVWXUEDQFH. Although the inclusion of recreation improved the RSF model for Canada lynx, environmental covariates explained most variation in resource use. The environmental gradients that most separated areas selected by Canada lynx from those used by recreationists were forest canopy closure, road density, and slope. 36 �Canada lynx also exhibited a functional response of increased avoidance of areas selected by motorized winter UHFUHDWLRQLVWV� VQRZPRELOLQJ�RIIဨWUDLO��K\EULG�VQRZPRELOH �FRPSDUHG�ZLWK�HLWKHU�QR�IXQFWLRQal response (hybrid ski) or selection for (backcountry skiing) areas suitable for nonmotorized winter recreation. We conclude with a discussion of implications associated with providing winter recreation balanced with the conservation of Canada lynx. Published October 2019 37 �CARNIVORE ECOLOGY AND MANAGEMENT Effects of Hunting on a Puma Population in Colorado Kenneth A. Logana and Jonathan P. Rungeb a Mammals Research Section, Colorado Parks and Wildlife, 2300 S. Townsend Avenue, Montrose, CO 81401, USA b Terrestrial Programs, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA Citation: Logan, K. A. and J. P. Runge. 2020. Effects of hunting on a pums population in Colorado. Colorado Parks and Wildlife Technical Publication No. 54, Fort Collins, CO, USA. CPW-R-T-54-20 ISSN 0084-8883. EXECUTIVE SUMMARY We investigated effects of regulated hunting on a puma (Puma concolor) population on the UncompahgrePlateau (UPSA; 2,996 km2) in southwestern Colorado. We examined the hypothesis that an annual harvest rate averaging 15% of the estimated number of independent pumas using the study area would result in a stable or increasing abundance of independent pumas. We predicted hunting mortality would be compensated by: 1) a reduction in other causes of mortality, thus overall survival would stay the same or increase; 2) increased reproduction rates; or 3) increased recruitment of young pumas. Our alternate hypothesis was that an annual harvest rate averaging 15% of the estimated number of independent pumas would result in a declining abundance of independent pumas. Under this hypothesis, we predicted that hunting mortality would be additive, with: 1) no reduction in other causes of mortality, thus overall survival would decline; and neither 2) enhanced reproduction, or 3) enhanced recruitment would fullyccompensate for hunting mortality. 7KH�VWXG\�RFFXUUHG�RYHU����\HDUV� ����í���� ��DQG�ZDV�GHVLJQHG�ZLWK�D�UHIHUHQFH�SHULRG� \HDUV��í���L�H�� R<�í5<� �ZLWKRXW�SXPD�KXQWLQJ�DQG�D�WUHDWPHQW�SHULRG� \HDUV��í����L�H���7<�í7<� �ZLWK�SXPD hunting. We captured and marked pumas on the UPSA and monitored them year-round to examine puma demographics. We estimated abundance of independent pumas using the UPSA each winter during the Colorado puma hunting season from reference year 2 (RY2) to treatment year 5 (TY5) by using the Lincoln-Petersen method. In addition, we surveyed puma hunters to investigate how hunter behavior influenced harvest and the puma population. We captured and marked 110 and 116 unique pumas in the reference and treatment periods, respectively, during 440 total capture events. Those pumas produced known-fate data for 75 adults, 75 subadults, and 118 cubs, which we used to estimate sex- and life stage-specific survival rates using program MARK. In the reference period, independent pumas using the UPSA more than doubled in abundance and exhibited high survival. Natural mortality was the major cause of death to independent pumas, followed by other human causes (e.g., vehicle strikes, depredation control). In the treatment period, hunters killed 35 independent pumas and captured and released 30 pumas on the UPSA. Abundance of independent pumas using the UPSA declined 35% after 4 years of hunting. Harvest rates of marked independent pumas with home ranges exclusively on the UPSA, overlapping the UPSA, and on adjacent management units representing the population-scale harvest averaged 22% annually in the same 4 years leading to the population decline. Adult females comprised 21% of the total harvest. Harvest rates from just the UPSA study area during the same period averaged 15%; but, as we note in the manuscript, the UPSA harvest estimate is biased and scale-dependent. The top-ranked adult survival model indicated a period effect interacting with sex best explained variation in survival. Annual adult male survival was higher in the UHIHUHQFH�SHULRG�>Dž� � 0.96, 95% Confidence Interval (CI) = ����í����@�than in the treatment period (Dž = 0.40, 95% CI = ����í���� �� Annual adult female survival was 0.8�� ����&,� �����í���� �LQ�WKH�UHIHUHQFH SHULRG�DQG������ ����&,� �����í���� � in the treatment period. The top subadult survival model showed that female subadult survival was constant across the reference and treatment periods (Dž = 0.68, 95% CI = ����í���4), while subadult male survival exhibited the same trend as adult male survival: higher in the reference period (Dž = 0.92, 95% CI = ����í���� �and lower in the treatment period (Dž = 0.43, 95% CI = ����í���� ��Cub survival was best explained by fates of mothers when cubs were dependent (Džmother alive = 0.51, 95% CI = ����í������Džmother died = 0.14, 95% CI = ����í���� ��The age distribution for independent pumas skewed younger in the treatment period. Adult males were most affected by harvest, with a 59% decline in their abundance after 3 hunting seasons, and no males >6 years old detected after 2 hunting VHDVRQV��6XFFHVVIXO�SXPD�KXQWHUV�XVHG�GRJV��VHOHFWHG�SULPDULO\�PDOHV��DQG�KDUYHVWHG�SXPDV�LQ��í� median number of days. Pumas born on the UPSA that survived to subadult stage exhibited traits of both philopatry and dispersal. Local recruitment and immigration contributed to positive population growth in the reference period. But recruitment did not compensate for the losses of adult males and partially compensated for losses of adult females in the treatment period. Average birth intervals were similar in the reference and treatment periods (reference period = �����PR�������&,� �����í������WUHDWPHQW�SHULRG� ������PR�������&,� ����í���� ��ZKLOH�OLWWHU�VL]Hs (reference 38 �SHULRG� ����������&,� ����í�����WUHDWPHQW�SHULRG� ����������&,� ���í��� �DQG�SDUWXULWLRQ�UDWHV� UHIHUHQFH�SHULRG� � ����������&,� �����í������WUHDWPHQW�SHULRG� ������ ����&,� �����í���� �GHFOLQHG�VOLJKWO\�LQ�WKH�WUHDWPHQW�SHULRG� We found that a harvest rate at the population scale averaging 22% of the independent pumas over 4 years and with >20% adult females in the total harvest greatly reduced puma abundance. At this scale total human-caused mortality rate averaged 27% annually. Mortality rates of independent pumas from hunting averaged 6.3 times greater than from all other human causes and 4.6 times greater than from all natural causes during the population decline. Hunting deaths largely added to other causes of mortality, and reproduction and recruitment did not compensate for hunting mortality. Puma hunters exhibited selection for male pumas, reduced male survival, and affected the sex and age structure of the population. We discuss our results in relation to a synthesis of published information on pumas in North America. We recommend how regulated hunting in a source-sink structure can be used to conserve puma populations, provide sustainable puma hunting opportunity, and address puma-human conflicts. Published June 2020 Puma population limitation and regulation: what matters in puma management? Kenneth A. Logan Mammals Research Section, Colorado Parks and Wildlife, 2300 S. Townsend Avenue, Montrose, CO 81401, USA Citation: Logan, K. A. 2019. Puma population limitation and regulation: what matters in puma management? Journal of Wildlife Management 83:1652–1666; doi.org/10.1002/jwmg.21753 ABSTRACT Wildlife managers require reliable information on factors that influence animal populations to develop successful management programs, including the puma (Puma concolor), in western North America. As puma SRSXODWLRQV�KDYH�UHFRYHUHG�LQ�UHFHQW�GHFDGHV�EHFDXVH�RI�UHVWULFWLRQV�RQ�KXPDQဨFDXVHG�PRUWDOLW\��PDQDJHUV�QHHG�D clear understanding of the factors that limit or regulate puma populations and how those factors might be manipulated to achieve management objectives, including sustaining puma and other wildlife populations, providing hunting opportunity, and reducing puma interactions with people. I synthesized technical literature on puma populations, behavior, and relationships with prey that have contributed to hypotheses on puma population limitation and regulation. Current hypotheses on puma population limitation include the social limitation hypothesis and the food limitation hypothesis. Associated with each of those are 2 hypotheses on puma population regulation: the social regulation hypothesis and the competition regulation hypothesis. I organize the biological and ecological attributes of pumas reported in the literature under these hypotheses. I discuss the validity of these hypotheses based on the limits of the research associated with the hypotheses and the evolutionary processes theoretically underlying them. I review the management predictions as framed by these hypotheses as they pertaLQ�WR�SXPD�KXQWLQJ��SXPDဨ SUH\�UHODWLRQVKLSV��DQG�KXPDQဨSXPD�LQWHUDFWLRQV��7KH�IRRG�OLPLWDWLRQ�DQG�FRPSHWLWLRQ�UHJXODWLRQ�K\SRWKHVHV�H[SODLQ� more phenomena associated with puma and likely would guide more successful management outcomes. © 2019 The Wildlife Society. Featured article November 2019 issue of Journal of Wildlife Management Summarizing Colorado’s black bear two-strike directive 30 years after inception Jonathan H. Lewis,a Mathew W. Alldredge,a Brian P. Dreher,b Janet L. George,c Scott Wait,d Brad Petch,e and Jon P. Rungef a Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA b Terrestrial Section, Colorado Parks and Wildlife, 4255 Sinton Road, Colorado Springs, CO 80907, USA c Terrestrial Section, Colorado Parks and Wildlife, 1313 Sherman Street, Denver, CO 80203, USA d Terrestrial Section, Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81303, USA e Terrestrial Section, Colorado Parks and Wildlife, 711 Independent Avenue, Grand Junction, CO 81505, USA f Terrestrial Programs, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA Citation: Lewis, J. H., M. W. Alldredge, B. P. Dreher, J. L. George, S. Wait, B. Petch, and J. P. Runge. 2019. Summarizing Colorado’s black bear two–strike directive 30 years after inception. Wildlife Society Bulletin; doi.org/10.1002/wsb.1032 ABSTRACT Colorado Parks and Wildlife implemented a new statewide management policy in 1985 for nuisance black bears (Ursus americanus ��NQRZQ�WRGD\�DV�WKH��ဨVWULNH�GLUHFWLYH��,W�DOORZHG�ZLOGOLIH�PDQDJHUV�WR�DVVHVV�WKH� repeatability of nuisance bear behavior after translocating them to quality bear habitat away from human food sources. We evaluated this directive using 30 years (1987–2016) of nuisance black bear capture records. Statewide, 53% of 1,093 bears caught, marked, and moved (1st strike) were never reported again, while 25% were killed for a 2nd strike, and hunters harvested 17%. Subadult males committed 2nd strikes more quickly than adult males and females. Although time between strikes was greatest for adult females (496 days), they had the largest probability of committing a 2nd strike among all cohorts. We found that the number of 1st strike captures, from late summer 39 �through IDOO�ZDV�JUHDWHVW�GXULQJ�\HDUV�RI�SRRU�PDVW�SURGXFWLRQ��:H�VXJJHVW�WKDW�WKH��ဨVWULNH�SROLF\�KDV�EHHQ�DQ� effective management tool for nuisance black bears in Colorado, USA, because of low rates of nuisance behavior IROORZLQJ��VWဨVWULNH�WUDQVORFDWLRQ��,I�D�state or local management objective is to increase black bear populations, wildlife managers may increase tolerance of adult bears that have received their 1st strike in years when fall mast crops largely fail because they are less likely to commit a 2nd strike. Lower tolerance of subadult males may be warranted in bad food years, especially in areas where reductions in bear populations are desired, because they tend to repeat nuisance behaviors more quickly than other bears. © 2019 The Wildlife Society. Published Nov. 2019 Understanding and managing human tolerance for a large carnivore in a residential system Stacy A. Lischka,a, b Tara L. Teel,c Heather E. Johnson,d and Kevin R. Crooksb a Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA b Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA c Department of Human Dimentions of Natural Resources, Colorado State University, Fort Collins, CO 80523, USA d Research, Policy, and Planning Branch, Colorado Parks and Wildlife, 415 Turner Drive, Durango, CO 81301, USA Citation: Lischka, S. A., T. L. Teel, H. E. Johnson, and K. R. Crooks. 2019. Understanding and managing human toleralce for a large carnivore in a residential system. Biological Conservation 238:1081–1089; doi.org/10.1016/j.biocon.2019.07.034 ABSTRACT Human tolerance for interactions with large carnivores is an important determinant of their persistence on the landscape, yet the relative importance of factors affecting tolerance is not fully understood. Further, the impact of management efforts to alter tolerance has not been adequately assessed. We developed a model containing a comprehensive set of predictors drawn from prior studies and tested it through a longitudinal survey measuring tolerance for black bears (Ursus americanus) in the vicinity of Durango, Colorado, USA. Predictors included human-bear conflicts, outcomes of interactions with bears, perceptions of benefits and risks from bears, trust in managers, perceived similarity with the goals of managers, personal control over risks, value orientations toward wildlife, and demographic factors. In addition, we monitored changes in tolerance resulting from a bear-proofing experiment designed to reduce garbage-related conflicts in the community. Residents who perceived greater benefits associated with bears and more positive impacts from bear-related interactions had higher tolerance. Residents who perceived greater risks and more negative impacts and who had greater trust in managers, domination wildlife value orientations, and older age were less tolerant. Conflicts with bears were not an important predictor, supported by our finding that changes in conflicts resulting from our bear-proofing experiment did not affect tolerance. In contrast to conservation approaches that focus primarily on decreasing human-wildlife conflicts, our findings suggest that communication approaches aimed at increasing public tolerance for carnivores could be improved by emphasizing the benefits and positive impacts of living with these species. Published October 2019 Human–Cougar interactions in the wildland–urban interface of Colorado’s Front Range Mathew W. Alldredge,a Frances E. Buderman,b and Kevin A. Blechac a Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO, USA b Colorado State University, Fort Collins, CO, USA c Terrestrial Section, Colorado Parks and Wildlife, Gunnison, CO, USA Citation: Alldredge, M. W., F. E. Buderman, and K. A. Blecha. 2019. Human-Cougar interactions in the wildland-urban interface of Colorado’s Front Range. Ecology and Evolution 9:10415–10431; doi.org/10.1002/ece3.5559 ABSTRACT As human populations continue to expand across the world, the need to understand and manage wildlife populations within the wildland–urban interface is becoming commonplace. This is especially true for large carnivores as these species are not always tolerated by the public and can pose a risk to human safety. Unfortunately, information on wildlife species within the wildland–urban interface is sparse, and knowledge from wildland HFRV\VWHPV�GRHV�QRW�DOZD\V�WUDQVODWH�ZHOO�WR�KXPDQဨGRPLQDWHG�V\VWHPV��$FURVV�ZHVWHUQ�1RUWK�$PHULFD��FRXJDUV� (Puma concolor) are routinely utilizing wildland–urban habitats while human use of these areas for homes and recreation is increasing. From 2007 to 2015, we studied cougar resource selection, human–cougar interaction, and cougar conflict management within the wildland–urban landscape of the northern Front Range in Colorado, USA. Resource selection of cougars within this landscape was typical of cougars in more remote settings but cougar interactions with humans tended to occur in locations cougars typically selected against, especially those in proximity to human structures. Within higher housing density areas, 83% of cougar use occurred at night, suggesting cougars generally avoided human activity by partitioning time. Only 24% of monitored cougars were reported for some type of conflict behavior but 39% of cougars sampled during feeding site investigations of GPS collar data 40 �were found to consume domestic prey items. Aversive conditioning was difficult to implement and generally ineffective for altering cougar behaviors but was thought to pRWHQWLDOO\�KDYH�ORQJဨWHUP�EHQHILWV�RI�UHLQIRUFLQJ�IHDU�RI� KXPDQV�LQ�FRXJDUV�ZLWKLQ�KXPDQဨGRPLQDWHG�DUHDV�H[SHULHQFLQJ�OLWWOH�FRXJDU�KXQWLQJ�SUHVVXUH��&RXJDUV�DUH�DEOH�WR� exploit wildland–urban landscapes effectively, and conflict is relatively uncommon compared with the proportion of cougar use. Individual characteristics and behaviors of cougars within these areas are highly varied; therefore, conflict management is unique to each situation and should target individual behaviors. The ability of individual cougars to learn to exploit these environments with minimal human–cougar interactions suggests that maintaining ROGHU�DJH�VWUXFWXUHV��HVSHFLDOO\�IHPDOHV��DQG�SURYLGLQJ�D�PDWUL[�RI�KDELWDWV��LQFOXGLQJ�ODUJH�FRQQHFWHG�RSHQဨVSDFH� areas, would be beneficial to cougars and effectively reduce the potential for conflict. Published August 2019 41 �UNGULATE ECOLOGY AND MANAGEMENT Behavioral and Demographic Responses of Mule Deer to Energy Development on Winter Range Joseph M. Northrup,a Charles R. Anderson Jr.,b Brian D. Gerber,c George Wittemyera a Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA b Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO 80526, USA c Department of Natural Resources Science, University of Rhode Island, 1 Greenhouse Road, Kingston, RI 02881ဨ2018, USA Citation: Northrup, J. M., C. R, Anderson Jr., B. D. Gerber, and G. Wittemyer. 2021. Behavioral and demographic responses of mule deer to energy development on winter range. Wildlife Monographs, In Press. ABSTRACT Anthropogenic habitat modification is a major driver of global biodiversity loss. In North America, one of the primary sources of habitat modification over the last 2 decades has been exploration for and production of oil and natural gas (hydrocarbon development), which has led to demographic and behavioral impacts to numerous wildlife species. Developing effective measures to mitigate these impacts has become a critical task for wildlife managers and conservation practitioners. However, this task has been hindered by the difficulties involved in identifying and isolating factors driving population responses. Current research on responses of wildlife to development predominantly quantifies behavior, but it is not always clear how these responses scale to demography DQG�SRSXODWLRQ�G\QDPLFV��&RQFRPLWDQW�DVVHVVPHQWV�RI�EHKDYLRU�DQG�SRSXODWLRQဨOHYHO�SURFHVVHV�DUH�QHHGHG to gain the mechanistic understanding required to develop effective mitigation approaches. We simultaneously assessed the demographic and behavioral responses of a mule deer (Odocoileus hemionus) population to natural gas development on winter range in the Piceance Basin of Colorado, USA, from 2008 to 2015. Notably, this was the period when development declined from high levels of active drilling to only production phase activity (i.e., no drilling). We focused our data collection on 2 contiguous mule deer winter range study areas that experienced starkly different levels of hydrocarbon development within the Piceance Basin. We assessed mule deer behavioral responses to a range of development features with varying levels of associatedhuman activity by examining habitat selection patterns of nearly 400 individual adult female mule deer. Concurrently, we assess ed the demographic and physiological effects of natural gas development by comparing annual DGXOW�IHPDOH�DQG�RYHUZLQWHU�IDZQ� �ဨPRQWKဨROG�DQLPDOV �VXUYLYDO��'HFHPEHU�IDZQ�PDVV��DGXOW�IHPDOH�ODWH� and early winter body fat, age, pregnancy rates, fetal counts, and lactation rates in December between the 2 study DUHDV��6WURQJ�GLIIHUHQFHV�LQ�KDELWDW�VHOHFWLRQ�EHWZHHQ�WKH���VWXG\�DUHDV�ZHUH�DSSDUHQW��'HHU�LQ�WKH�OHVVဨGHYHORSHG study area avoided development during the day and night, and selected habitat presumed to be used for foraging. Deer in the heavily developed study area selected habitat presumed to be used for thermal and security cover to a greater degree. Deer faced with higher densities of development avoided areas with more well pads during the day and responded neutrally or selected for these areas at night. Deer in both study areas showed a strong reduction in use of areas around well pads that were being drilled, which is the phase of energy development associated with the greatest amount of human presence, vehicle traffic, noise, and artificial light. Despite divergent habitat selection patterns, we found no effects of development on individual condition or reproduction and found no differences in any of the physiological or vital rate parameters measured at the population level. However, deer density and annual LQFUHDVHV�LQ�GHQVLW\�ZHUH�KLJKHU�LQ�WKH�ORZဨGHYHORSPHQW�DUHD��7KXV��WKH�UHFRUGHG�EHKDYLRUDO alterations did not appear to be associated with demographic or physiological costs measured at the individual level, possibly because populations are below winter range carrying capacity. Differences in population density between the 2 areas may be a result of a population decline prior to our study (when development was initiated) or DUHDဨVSHFLILF�GLIIHUHQFHV�LQ� habitat quality, juvenile dispersal, or neonatal or juvenile survival; however, we lack the required data to contrast evidence for these mechanisms. Given our results, it appears that deer can adjust to relatively high densities of well pads in the production phase (the period with markedly lower human activity on the landscape), provided there is sufficient vegetative and topographic cover afforded to them and populations are below carrying capacity. The strong reaction to wells in the drilling phase of development suggests mitigation efforts should focus on this activity and stage of development. 0DQ\�RI�WKH�ZHOOV�LQ�WKLV�DUHD�ZHUH�GLUHFWLRQDOO\�GULOOHG�IURP�PXOWLSOHဨZHOO�SDGV��OHDGLQJ�WR�D�UHGXFHG footprint of disturbance, but were still related to strong behavioral responses. Our results also indicate the likely value of mitigation efforts focusing on reducing human activity (i.e., vehicle traffic, light, and noise). In combination, these findings indicate that attention should be paid to the spatial configuration of the final development footprint to HQVXUH�DGHTXDWH�FRYHU��,Q�RXU�VWXG\�V\VWHP��PLQLPL]LQJ�WKH�URDG�QHWZRUN�WKURXJK�ODQGVFDSHဨOHYHO development planning would be valuable (i.e., exploring a maximum road density criteria). Lastly, our study highlights the 42 �importance of concomitant assessments of behavior and demography to provide a comprehensive understanding of how wildlife respond to habitat modification. © 2020 The Wildlife Society. Estimation of moose parturition dates in Colorado: incorporating imperfect detections Eric J. Bergman,a Forest P. Hayes,b and Kevin Aagaarda a Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO, USA b Wildlife Biology Program, University of Montana, Forestry 108, 32 Campus Drive, Missoula, MT 59812, USA Citation: Bergman, E. J., F. P. Hayes, and K Aagaard. 2020. Estimation of moose parturition dates in Colorado: incorporating imperfect detections. Alces 56:127–135. ABSTRACT Researchers and managers use productivity surveys to evaluate moose populations for harvest and population management purposes, yet such surveys are prone to bias. We incorporated detection probability estimates (p) into spring and summer ground surveys to reduce the influence of observer bias on the estimation of moose parturition dates in Colorado. In our study, the cumulative parturition probability for moose was 0.50 by May 19, and the probability of parturition exceeded 0.9 by May 27. Timing of moose calf parturition in Colorado appears synchronous with parturition in more northern latitudes. Our results can be used to plan ground surveys in a manner that will reduce bias stemming from unobservable and yet-born calves. Published August 2020 Moose calf detection probabilities: quantification and evaluation of a ground-based survey technique Eric J. Bergman,a Forest P. Hayes,b Paul M. Lukacs,b and Chad J. Bishopb a Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO, USA b Wildlife Biology Program, Dept of Ecosystem and Conservation Sciences, W.A. Franke College of Forestry and Conservation, Univ. of Montana, Missoula, MT, USA Citation: Bergman, E. J., F. P. Hayes, P. M. Lukacs, and C. J. Bishop. 2020. Moose calf detection probabilities: quantification and evaluation of a ground-based survey technique. Wildlife Biology 2020: doi: 10.2981/wlb.00599 ABSTRACT Survey data improve population management, yet those data often have associated bias. We quantified one source of bias in moose survey data (observer detection probability, p), by using repeated groundobservations of calves-at-heel of radio-collared moose in Colorado, USA. Detection probabilities, which varied both spatially and temporally, were estimated using an occupancy-modelling framework. We provide an efficient offset for modelled calf-at-KHHO�RFFXSDQF\� ȥ �HVWLPDWHV�WKDW�DFFRPPRGDWHV�VXPPHU�FDOI�PRUWDOLW\���'HWHFWLRQ� probabilities were most efficiently modelled with seasonal variation, with the lowest probability of detecting calvesat-heel occurring during parturition (i.e., May) and later autumn periods (after August). Our most efficiently PRGHOOHG�GHWHFWLRQ�SUREDELOLW\�HVWLPDWH�IRU�VXPPHU�ZDV������ 6(� ����� ���'XULQJ�WKH�IRXU�\HDUV�RI�WKLV�VWXG\��ȥ estimates ranged from 0.54–0.84 (SE = 0.08–���� ���$FFRXQWLQJ�IRU�������PRQWKO\�FDOI�VXUYLYDO�FRUUHFWHGȥ� HVWLPDWHV�GRZQZDUG� ȥ� �����–0.65). Our results suggest that repeated ground-based observations of individual cow moose, during summer months, can be can a cost-effective strategy for estimating a productivity parameter for moose. Ground survey results can be further improved by accounting for calf mortality. Published April 2020 On-animal acoustic monitoring provides insight to ungulate foraging behavior Joseph M. Northrup,a Alexandra Arvin,a Charles R. Anderson Jr.,b Emma Brown,c and George Whittemyera a Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA b Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO 80526, USA c National Parks Service Natural Sounds and Skies Division, Fort Collins, CO 80525, USA Citation: Northrup, J. M., A. Arvin, C. R. Anderson Jr., E. Brown, and G. Whittemyer. 2019. On-animal acustic monitoring provides insight to ungulate foraging behavior. Journal of Mammology 100:1479–1489; doi.org/10.1093/jmammal/gyz124 ABSTRACT Foraging behavior underpins many ecological processes; however, robust assessments of this behavior for freeranging animals are rare due to limitations to direct observations. We leveraged acoustic monitoring and GPS tracking to assess the factors influencing foraging behavior of mule deer (Odocoileus hemionus). We deployed custom-built acoustic collars with GPS radiocollars on mule deer to measure location-specific foraging. We quantified individual bites and steps taken by deer, and quantified two metrics of foraging behavior: the number of bites taken per step and the number of bites taken per unit time, which relate to foraging intensity and efficiency. We fit statistical models to these metrics to examine the individual, environmental, and anthropogenic factors 43 �influencing foraging. Deer in poorer body condition took more bites per step and per minute and foraged for longer irrespective of landscape properties. Other patterns varied seasonally with major changes in deer condition. In December, when deer were in better condition, they took fewer bites per step and more bites per minute. Deer also foraged more intensely and efficiently in areas of greater forage availability and greater movement costs. During March, when deer were in poorer condition, foraging was not influenced by landscape features. Anthropogenic factors weakly structured foraging behavior in December with no relationship in March. Most research on animal foraging is interpreted under the framework of optimal foraging theory. Departures from predictions developed under this framework provide insight to unrecognized factors influencing the evolution of foraging. Our results only conformed to our predictions when deer were in better condition and ecological conditions were declining, suggesting foraging strategies were state-dependent. These results advance our understanding of foraging patterns in wild animals and highlight novel observational approaches for studying animal behavior. Published August 2019 44 �WILDLIFE GENETICS RESEARCH 8UEDQL]DWLRQ�LPSDFWV�DSH[�SUHGDWRU�JHQH�IORZ�EXW�QRW�JHQHWLF�GLYHUVLW\�DFURVV�DQ�XUEDQဨUXUDO�GLYLGH Daryl R. Trumbo,a Patricia E. Salerno,a Kenneth A. Logan,b Mathew W. Alldredge,b Roderick B. Gagne,c Christopher P. Kozakiewicz,d Simona, Kraberger,c Nicholas, M. Fountain-Jones,e Meggan E. Craft,e Scott Carver,d Holly B. Ernest,f Kevin R. Crooks,g Sue VandeWoude,c and W. Chris Funka aDepartment of Biology, Colorado State University, Fort Collins, CO, USA bMammals Research Section, Colorado Parks and Wildlife, Montrose and Fort Collins, CO, USA cDepartment of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, USA dDepartment of Biological Sciences, University of Rasmania, Hobart, TAS., Australia eDepartment of Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, USA fDepartment of Veterinary Sciences, University of Wyoming, Laramie, WY, USA gDepartment of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, USA Citation: Trumbo, D.R., P.E. Salerno, K.A. Logan, M.W. Alldredge, R.B. Gagne, C.P. Kozakiewicz, S. Kraberger, N.M. Fountain-Jones, M.E. Craft, S. Carver, H.B. Ernest, K.R. Crooks, S. VandeWoude, and W.C. Funk. 2019. Molecular Ecology 28:4926–4940; doi.org/10.1111/mec.15261 ABSTRACT Apex predators are important indicators of intact natural ecosystems. They are also sensitive to urbanization because they require broad home ranges and extensive contiguous habitat to support their prey base. Pumas (Puma concolor) can persist near human developed areas, but urbanization may be detrimental to their movement ecology, population structure, and genetic diversity. To investigate potential effects of urbanization in population connectivity of pumas, we performed a landscape genomics study of 130 pumas on the rural Western Slope and more urbanized Front Range of Colorado, USA. Over 12,000 single nucleotide polymorphisms (SNPs) were JHQRW\SHG�XVLQJ�GRXEOHဨGLJHVW��UHVWULFWLRQ�VLWHဨDVVRFLDWHG�'1$�VHTXHQFLQJ� GG5$'VHT ��:H�LQYHVWLJDWHG� patterns of gene flow and genetic diversity, and tested for correlations between key landscape variables and genetic distance to assess the effects of urbanization and other landscape factors on gene flow. Levels of genetic diversity were similar for the Western Slope and Front Range, but effective population sizes were smaller, genetic distances were higher, and there was more admixture in the more urbanized Front Range. Forest cover was strongly positively associated with puma gene flow on the Western Slope, while impervious surfaces restricted gene flow and more open, natural habitats enhanced gene flow on the Front Range. Landscape genomic analyses revealed differences in puma movement and gene flow patterns in rural versus urban settings. Our results highlight the utility of dense, JHQRPHဨVFDOH�PDUNHUV�WR�GRFXPHQW�VXEWOH�LPSDFWV�RI�XUEDQL]DWLRQ�RQ�D�ZLGHဨUDQJLQJ�FDUQLYRUH�OLYLQJ�QHDU�D�ODUJH� urban center. Published October 2019 45 ��Notes: …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… �Notes: …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… …………………………………………………………………………………………… ��Wildlife Research Reports MAMMALS – JULY 2019 � https://cpw.cvlcollections.org/files/original/0e28a23786fead4e59b85b5751fa4e3f.pdf 01bc8ddc66545ed1baabc6b6f756fd8e PDF Text Text C O L O R A D O P A R K S & W I L D L I F E Wildlife Research Reports MAMMALS – JULY 2021 cpw.state.co.us �Copies of this publication may be obtained from Colorado Parks and Wildlife Research Library 317 West Prospect, Fort Collins, CO 80526 �WILDLIFE RESEARCH REPORTS JULY 2020–JUNE 2021 MAMMALS RESEARCH PROGRAM COLORADO PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). By providing these summaries, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. ii �EXECUTIVE SUMMARY This Wildlife Research Report represents summaries (≤5 pages each with tables and figures) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) during 2020 and 2021. These research efforts represent long-term projects (4–10 years) in various stages of completion addressing applied questions to benefit the management and conservation of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx or from the project principal investigators listed at the beginning of each summary. Current research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to habitat alterations, human-wildlife interactions, and investigating improved approaches for wildlife management. The Nongame Mammal Conservation Section addresses ongoing monitoring of lynx in the San Juan mountain range and preliminary results addressing influences of forest management practices on snowshoe hare density in Colorado. The Ungulate Conservation Section includes 6 projects addressing mule deer/energy development interactions to inform future development planning, related research addressing vegetation and mule deer responses to 3 mechanical treatment methods, evaluation of moose demographic parameters that will inform future moose management in Colorado, an evaluation of factors influencing elk calf recruitment, and 2 recent studies addressing elk response to human recreation. The Support Services Section describes the CPW library services to provide internal access of CPW publications and online support for wildlife and fisheries management related publications. In addition to the ongoing project summaries described above, Appendix A includes 12 publication abstracts (<2 page summaries) under 5 subject headings completed by CPW research staff since July 2020. These scientific publications provide results from recently completed CPW research projects and other collaborations with universities and wildlife management agencies. Topics addressed include nongame species ecology and conservation (lynx associations with beetle killed forests, and a collaborative modelling effort to address lynx distribution in the southern extent of their range), carnivore ecology and management (mountain lion population response to hunter harvest), ungulate ecology and management (mule deer response to energy development activity, applying memory covariates to enhance assessment of mule deer habitat use patterns, developing an approach to estimate timing of moose calf births, addressing the influence of willow nutrition and morphology on moose calving rates, and investigation of potential disease spread from migratory elk to livestock), university collaborations addressing wildlife genetics and disease research (evaluation of how human altered landscapes influence viral transmission in cougars, characteristics of anelloviruses in domestic and various wild cat species, and reconstructing statewide viral phylogenies from commonly collected mountain lion tooth samples), and a Journal of Wildlife Management editorial representing an evaluation of the journal from senior and mid-career scientists to provide suggestions for future improvement. We have benefitted from numerous collaborations that support these projects and the opportunity to work with and train wildlife technicians and graduate students that will likely continue their careers in wildlife management and ecology in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, Montana State University, University of Wyoming, U.S. Bureau of Land Management, U.S. Forest Service, CPW big game auction-raffle grants, Species Conservation Trust Fund, Great Outdoors Colorado, CPW Habitat Partnership Program, Safari Club International, Boone and Crocket Club, Colorado Mule Deer Association, The Mule Deer Foundation, Muley Fanatic Foundation, EnCana Corp., ExxonMobil/XTO Energy, Marathon Oil, Shell Exploration and Production, WPX Energy, and numerous private land owners providing access to support field research projects. iii �STATE OF COLORADO Jared Polis, Governor DEPARTMENT OF NATURAL RESOURCES Dan Gibbs, Executive Director PARKS AND WILDLIFE COMMISSION Carrie Besnette Hauser, Chair............................................................................................Glenwood Springs Charles Garcia, Vice Chair .................................................................................................................. Denver Luke B. Schafer, Secretary..................................................................................................................... Craig Marie Haskett ...................................................................................................................................... Meeker Taishya Adams ................................................................................................................................... Boulder Betsy Blecha........................................................................................................................................... Wray Dallas May ............................................................................................................................................ Lamar Duke Phillips IV.................................................................................................................. Colorado Springs James Jay Tutchton… ............................................................................................................................ Hasty Eden Vardy............................................................................................................................................ Aspen Karen Michelle Bailey ....................................................................................................................... Boulder Kate Greenberg, Dept. of Agriculture, Ex-officio.............................................................................. Durango Dan Gibbs, Executive Director, Ex-officio .......................................................................................... Denver DIRECTOR’S LEADERSHIP TEAM Dan Prenzlow, Director Reid DeWalt, Heather Dugan, Justin Rutter Lauren Truitt, Jeff Ver Steeg, Cory Chick, Brett Ackerman, Travis Black, Mark Leslie MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Wildlife Researcher Alexandria Austermann, Research Librarian Eric Bergman, Wildlife Researcher Michelle Gallagher, Program Assistant Jake Ivan, Wildlife Researcher Ken Logan, Wildlife Researcher Nathaniel Rayl, Wildlife Researcher iv �TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS NONGAME MAMMAL CONSERVATION CANADA LYNX MONITORING IN COLORADO by E. Odell, J. Ivan, S. Wait, and M. Hertel. 2 INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO by J. Ivan and E. Newkirk ....... 8 UNGULATE MANAGEMENT AND CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson ................................. 12 PLANT AND MULE DEER RESPONSES TO PINYON-JUNIPER REMOVAL BY THREE MECHANICAL METHODS by D. Johnston and C. Anderson...................................................... 17 EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO by E. Bergman. ......................................................................................................... 22 EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO by N. Rayl, M. Alldredge, and C. Anderson ............................................................................................. 25 RESPONSE OF ELK TO HUMAN RECREATION AT MULTIPLE SCALES: DEMOGRAPHIC SHIFTS AND BEHAVIORALLY MEDIATED FLUCTUATIONS IN ABUNDANCE by E. Bergman and N. Rayl ................................................................................... 30 SPATIOTEMPORAL EFFECTS OF HUMAN RECREATION ON ELK BEHAVIOR: AN ASSESSMENT WITHIN CRITICAL TIME STAGES by N. Rayl, E. Bergman, and J. Holbrook ......................................................................................................................................... 32 SUPPORT SERVICES LIBRARY SERVICES by A. Austermann ..................................................................................... 35 APPENDIX A. MAMMALS RESEARCH PUBLICATION ABSTRACTS NONGAME MAMMAL ECOLOGY AND CONSERVATION… ................................................ 42 CARNIVORE ECOLOGY AND MANAGEMENT ....................................................................... 44 UNGULATE ECOLOGY AND MANAGEMENT ........................................................................ 46 WILDLIFE GENETICSAND DISEASE RESEARCH .................................................................. 50 JOURNAL OF WILDLIFE MANAGEMENT EDITORIAL…...................................................... 52 v �NONGAME MAMMAL CONSERVATION CANADA LYNX MONITORING IN COLORADO INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO 1 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Canada lynx monitoring in Colorado Period Covered: July 1, 2019 − June 30, 2020 Principal Investigators: Eric Odell, Eric.Odell@state.co.us; Jake Ivan, Jake.Ivan@state.co.us; Scott Wait, Scott.Wait@state.co.us; Morgan Hertel, Morgan.Hertel@state.co.us Personnel: Brad Weinmeister, Evan Phillips, Nate Seward, Brent Frankland All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success, and that the population of Canada lynx in the state was apparently viable and self-sustaining. To track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is required. During 2014−2020 CPW initiated a portion of the statewide monitoring scheme described in Ivan (2013) by completing surveys in a random sample of monitoring units (n = 50) from the San Juan Mountains in southwest Colorado (n = 179 total units; Figure 1). During 2019−2020 personnel from CPW and USFS completed the sixth year of monitoring work on this same sample. Specifically, 14 units were sampled via snow tracking surveys conducted between December 1 and March 31. On each of 1–3 independent occasions, survey crews searched roadways (paved roads and logging roads) and trails for lynx tracks. Crews searched the maximum linear distance of roads possible within each survey unit given safety and logistical constraints. Each survey covered a minimum of 10 linear kilometers (6.2 miles) distributed across at least 2 quadrants of the unit. The remaining 36 units could not be surveyed via snow tracking. Instead, survey crews deployed 4 passive infrared motion cameras in each of these units during fall 2019. Cameras were baited with visual attractants and scent lure to enhance detection of lynx living in the area. Cameras were retrieved during summer or fall 2020 and all photos were archived and viewed by at least 2 observers to determine species present in each. Camera data were then binned such that each of 10 15-day periods from December 1 through April 30 was considered an ‘occasion,’ and any photo of a lynx obtained during a 15-day period was considered a ‘detection’ during that occasion. Surveyors covered 650 km during snow tracking surveys and detected lynx at 6 units (Table 1). These results are among the lowest recorded for the project, but mirror those recorded during the past 3 years (Table 1). Surveyors collected more than 3 times the photos during 2019–2020 than have been collected in any other year. This can be mostly attributed to the use of new, more sensitive cameras along with new, high capacity memory cards. However, for the third year in a row we collected <50% of the number of lynx photos taken during the initial years of the monitoring effort (Table 2). In fact, the 36 lynx photos collected during the 2019−20 season was the fewest recorded since the inception of the project. We initially considered at least 3 possible explanations for the lack of photos collected in recent years. First, we hypothesized that abnormal snow patterns (lack of snow in 2017–18, record snow in 2 �2018–19) could have impacted detection probability. Second, lack of detections could have been due to the new lure (Caven’s Violator 7; Minnesota Trapline Products, https://www.minntrapprod.com/Bobcatand-Lynx/products/829/) we used in 2017–18, 2018–19, and 2019−20 after the lure we used previously (Pikauba; Luerres Forget’s Lures, http://www.leurresforget.com/product.php?id_product=15) became unavailable. Finally, it could be that lynx have disappeared from a number of camera units. Unfortunately, the changes in snow and lure were confounded for a few years, thus making it difficult to determine which factor resulted in fewer detections. However, 2019−20 was a normal snow year, yet the number of lynx photos was still low. This indicates that abnormal snow was not the cause of the pattern we observed. Also, the number of snow tracking units with lynx has remained fairly steady throughout the project; we can think of no reason why snow track units would remain occupied while lynx blinked out of camera units, unless just by chance. Thus, we suggest that the new lure is less effective than the original. Fortunately the original formulation is again available and will be deployed for the 2020−21 survey. We plan to utilize this lure for the remainder of the survey efforts, provided it remains available. We obtained lynx detections for only the second time at a camera unit near Wolf Creek Pass. Lynx were again detected at Lizard Head Pass after no detections last year, and in all four snow tracking units along the Hwy 550 corridor after two of the four went without detections in 2018−19. However, we failed to detect lynx in at the Table Mountain Unit northwest of Creede, at Lemon Reservoir, at Little Squaw Creek west of Creede, and at Trujillo Meadows near the New Mexico border, where they had been detected the previous two seasons (Figure 1). We used the R (R Development Core Team 2018) package ‘RMark’ (Laake 2018) to fit multipleseason (i.e., “dynamic”) occupancy models (MacKenzie et al. 2006) to our survey data using program MARK (White and Burnham 1999). Thus, we estimated the derived probability of a unit being occupied (i.e., used) by lynx over the course of the winter (ψ), along with the probability of detecting a lynx (p) given that the unit was occupied, the probability a unit that was unused in one year was used the next (i.e., “local colonization”, γ), and the probability a used unit became unused from one year to the next (i.e., “local extinction”, ε). Based on previous work, we treated ‘survey method’ as a group variable so that we could allow p to vary by method. Additionally, we allowed p for 2017–18, 2018–19, and 2019–20 to differ from other years due to the new lure, and we included a breeding season effect for detection at cameras (lynx tend to move more in late winter when they begin to breed, and thus should encounter cameras more often). Also based on previous work, we specified initial ψ in the time series to be a function of the proportion of the unit that was covered by spruce/fir forest. We then allowed annual estimates of ε to be constant or a function of average years since bark beetle infestation, proportion of the unit impacted by bark beetles, proportion of the unit that was burned during Summer 2013, and the number of photos of other species that could potentially impact presence of lynx (e.g., snowshoe hares as a food source; coyotes, bobcats, foxes, and cougars as potential competitors). We allowed annual estimates of γ to be constant or a function of snowshoe hares. We limited our model set by first setting a general structure for ψ while assessing fit of various combinations of variables expected to affect p. We then fixed the best-fitting structure for p, and assessed combinations of the covariates expected to influence ε or γ, allowing up to 2 of these covariates at a time, in addition to the covariates on detection. We made inference from the best-fitting model as selected via Akaikie’s Information Criterion (AIC), adjusted for small sample size (Burnham and Anderson 2002). As has been the case since the inception of our monitoring program, the proportion of the sample unit covered by spruce-fir forest was positively associated with the initial occupancy estimate in the time series. Local colonization probability was estimated to be low (γ = 0.03, SE = 0.01 ) and constant; local extinction was also low, but in some years twice that of colonization (ε = 0.03 to 0.06, SE = 0.03 to 0.05). Furthermore, in all of the top models, ε was negatively (but weakly) associated with the number of coyote photos collected on the year indicating that the probability of extinction of a unit in any given year goes up as the index of coyote abundance goes down (Appendix 1). Local extinction was also significantly, positively associated with the number of fox photos in the top model, suggesting that extinction is more likely in units in which we detected fox more often. Other models for ε that performed better than a 3 �constant structure included a negative relationship with number of snowshoe hare photos (less likely to go extinct as hare index increases), a positive relationship with the number of bobcat photos (more likely to go extinct as bobcat index increases), and a positive association with proportion of a unit impacted by beetles. However, the hare, bobcat, and beetle models were not as well supported as those including coyotes and foxes. The five occupancy growth rates (λ) estimated between surveys were all near 1.0, indicating a stable distribution with little to no growth (Figure 2). Similar to previous years, detection probability was relatively high for snow tracking surveys (p = 0.59, SE=0.05), and relatively low for camera surveys (p = 0.23, SE = 0.04) during December−February and April, although detection at cameras increased to 0.34 (SE = 0.07) during breeding season (March) as expected. We found a significant, negative effect on p during winters when Violator 7 was used as lure (p = 0.08, SE = 0.02 for December−February and April; p = 0.13, SE = 0.05 for breeding season). We estimated that 29% of the sample units in the San Juan’s were occupied by lynx (95% confidence interval: 15–43%) during 2019– 20 (Figure 2). The spatial distribution of lynx in the San Juans remained largely unchanged (Figure 1). Table 1. Summary statistics from snow tracking effort. Season 2014-2015 #Units Surveyed 24 #Units with Lynx 8 #Lynx Tracks 13 2015-2016 17 7 14 #Genetic Samplesa 10b 9c 13 7d 2016-2017 16 8 Km Surveyed (Total) 1,088 Mean Km Surveyed per Visit 20.1 #CPW Personnel 30 #USFS Personnel 13 987 21.9 23 6 703 18.0 20 8 2017-2018 14 7 9 3e 578 19.3 14 5 2018-2019 14 6 7 2e 510 19.6 16 5 10 2b 650 19.7 15 3 2019-2020 15 6 Number of genetic samples (scat or hair) collected via backtracking putative lynx tracks b DNA analysis confirms that all samples collected from putative lynx tracks were lynx c DNA analysis confirms that 6 of 9 samples were lynx (1 coyote, 1 either mule deer or human, 1undetermined) d DNA analyses confirmed that 5 of 7 samples were lynx (1 coyote, 1 snowshoe hare) e DNA analysis confirms 1 sample was lynx; remaining samples were not analyzed a Table 2. Summary statistics from camera effort. Season 2014-2015 #Units Surveyed 32 2015-2016 2016-2017 31 33 2017-2018 35 2018-2019 36 2019-2020 36 #Units With Lynx #Photos (Total) #Photos (Lynx) #Cameras With Lynx 8 7 6 5 6 4 134,694 101,534 168,705 173,279 204,243 701,724 301 455 251 90 59 36 14 10 10 8 9 4 4 #CPW Personnel 46 #USFS Personnel 12 33 29 9 9 35 8 31 7 29 6 �a) b) Figure 1. Lynx monitoring results for a) the current sampling season (2019–2020) and b) the cumulative monitoring effort (2014–2020), San Juan Mountains, southwest Colorado. Colored units (n = 50) depicted here are those selected at random from the population of units (n = 179) encompassing lynx habitat in the San Juan Mountains. Lynx were detected in 11 units in 2019−2020 and 23 units cumulatively since monitoring began in 2014−2015. 5 �Figure 2. Occupancy estimates (Ψ, filled circles, left axis) and annual growth rate (λ) in occupancy between surveys (open circles, right axis) for Canada lynx in the San Juan Mountains, southwest Colorado. ‘Year’ indicates when the efforts were initiated (e.g., winter 2014−15, winter 2019−20). Growth rates less than 1.0 indicate a decline in occupancy; those >1.0 indicate an increase. Literature Cited Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York, New York, USA. Ivan, J. S. 2013. Statewide monitoring of Canada lynx in Colorado: evaluation of options. Pages 15–27 in Wildlife research report: Mammals. Colorado Parks and Wildlife., Fort Collins, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx. Laake, J. L. 2018. Package “RMark”: R Code for Mark Analysis. Version 2.2.5. https://cran.rproject.org/web/packages/RMark/RMark.pdf. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. R Development Core Team. 2018. No Title. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplem:120–138. 6 �Appendix 1. Model selection results for lynx monitoring data collected in the San Juan Mountains, Colorado, 2014–2020. Rankings are based on Akaike’s Information Criterion adjusted for small sample size (AICc). Eight variables were considered as covariates to inform estimation of local extinction (ε); one was considered for local colonization (γ). The complete model set (n = 46) included all combinations of two of these covariates, in addition to modeling detection (p) as a function of survey method, breeding season, and alternate lure used during the 2017–18, 2018–19, and 2019–2020 seasons. Only the best 10 models are shown. Model ψ (Prop Spruce/Fir) ε (Coyote + Fox) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (Coyote) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (Coyote + PropBeetle) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (Coyote + Hare) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (Bobcat + Coyote) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (.) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (Coyote + PropBurn) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (BKAvg + Coyote) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (Cougar + Coyote) γ (.) p (Best) ψ (Prop Spruce/Fir) ε (Bobcat) γ (.) p (Best) AICc 574.54 576.43 576.50 576.61 577.17 578.01 578.12 578.21 578.30 578.50 ∆AICc 0.00 1.89 1.96 2.07 2.63 3.47 3.58 3.67 3.76 3.96 AICc Wts 0.19 0.08 0.07 0.07 0.05 0.03 0.03 0.03 0.03 0.03 No. Par. 10 9 10 10 10 8 10 10 10 9 Best-fitting structure for detection probability included effects for survey method, breeding season, and an effect for the 2017–18, 2018–19, and 2019–20 survey seasons when Violator 7 was used for lure rather than Pikauba. a 7 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Influence of forest management on snowshoe hare density in lodgepole and spruce-fir systems in Colorado Period Covered: July 1, 2019 − June 30, 2020 Principal Investigators: Jake Ivan, Jake.Ivan@state.co.us; Eric Newkirk, Eric.Newkirk@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. Understanding and monitoring snowshoe hare (Lepus americanus) density in Colorado is important because hares comprise 70% of the diet of the state-endangered, federally threatened Canada lynx (Lynx canadensis; U.S. Fish and Wildlife Service 2000, Ivan and Shenk 2016). Forest management is an important driver of snowshoe hare density, and all National Forests in Colorado are required to include management direction aimed at conservation of Canada lynx and snowshoe hare as per the Southern Rockies Lynx Amendment (SRLA; https://www.fs.usda.gov/detail/r2/landmanagement/ planning/?cid= stelprdb5356865). At the same time, Forests in the Region are compelled to meet timber production obligations. Such activities may depress snowshoe hare density, improve it, or have mixed effects dependent on the specific activity and the time elapsed since that activity was initiated. Here we describe a sampling scheme to assess impacts of common forest management techniques on snowshoe hare density in both lodgepole pine (Pinus contorta) and spruce-fir (Picea engelmannii – Abies lasiocarpa) systems in Colorado. To select forest stands for sampling, we first used U. S. Forest Service (USFS) spatial data to delineate all spruce-fir and lodgepole pine stands (stratum 1) on USFS land in Colorado, and identified all of the management activities that have occurred in each stand over time. With consultation from the USFS Region 2 Lynx-Silviculture Team, we then grouped relevant forest management activities (stratum 2) into 4 broad categories: even-aged management, uneven-aged management, thinning, and unmanaged controls. We wanted to assess both the immediate and long-term impacts of management on hare densities. Therefore, when selecting stands for sampling, we took the additional step of binning the date of the most recent management activity into 2-decade intervals (i.e., 0-20, 20-40, and 40-60 years before 2018). We then selected a spatially balanced random sample of 5 stands within each combination of forest type × management activity × time interval. This design ensured that we sampled the complete gradient of time since implementation for each management activity of interest in each forest type of interest. There is no notion of “completion date” for unmanaged controls, so we simply sampled 10 randomly selected stands from this combination. Also, uneven-aged lodgepole pine treatments are rare, so we did not sample that combination (Figure 1). During summer 2018, we established n = 50 1-m2 permanent circular plots within each of the stands selected for sampling. Plot locations within each stand were selected in a spatially balanced, random fashion. Technicians cleared and counted snowshoe hare pellets in each plot as they established them. These same plots were re-visited and re-counted during summers 2019 and 2020. In addition to sampling the previously cleared plots from 2018, technicians were able to install plots at 2 more replicate sites for each combination of forest type × management activity × time interval during 2019. Also, a handful of stands visited in 2019 and 2020 were re-classified or tossed because ground-truthing revealed 8 �they did not actually fit in the stratum for which they were selected. New stands were sampled in their place by pulling the next one from the spatially balanced list. Similarly, a handful more stands were replaced during the 2021 field season, and 12 new stands were selected to replace those that burned during the 2020 fire season. Currently, inference is based on n = 130 total stands. Finally, in 2021, we sampled vegetation metrics in each stand that will hopefully account for the considerable noise we have observed (highly variable results for some strata) and allow us to better assess the effects of the treatments themselves. This vegetation sampling will be completed during the 2022 field season. Pellet information from cleared plots is more accurate than that from uncleared plots because uncleared plots usually include pellet accumulation across several years (Hodges and Mills 2008). The degree to which previous years are represented can depend on local weather conditions, site conditions at the plot, and variability in actual snowshoe hare density over previous winters. Data from cleared plots necessarily reflects hare activity from the previous 12 months, and tracks true density more closely. Therefore, we focused the current analysis on the 2019-21 data from previously cleared plots. For each forest type × management activity combination, we plotted mean pellet counts against “year since activity”, then fit a curve (e.g., quadratic function) through the data (Figure 2). Results from this preliminary analysis suggest that on average the highest snowshoe hare densities typically occur in unmanaged spruce-fir forests, and that unmanaged spruce-fir forests are estimated to have twice the relative hare density of unmanaged lodgepole pine forests (Figure 2). For both forest types, the fitted line suggests that even-aged management (e.g., clearcutting), immediately depresses relative hare density to near zero, but density rebounds and peaks 20-40 years after management before declining again 40-60 years after. Estimated peak hare densities after even-aged management in lodgepole systems tend to be higher than the control condition. However, in spruce-fir systems the estimated fitted line is flatter and peak densities fell well short of the control condition. In both forest types, thinning (which often occurs 20-40 years after stands undergo even-aged management, especially in lodgepole), immediately depresses hare densities. In spruce-fir stands, densities were estimated to slowly recover through time in nearly linear fashion. However, they follow a peaked response in lodgepole pine, similar to the response to even-aged management. Uneven-aged management of spruce-fir forests results in immediate depression of relative hare density, which then recovers back to pre-treatment levels approximately 30 years after the treatment. Note the outlier on the right side of the even-aged lodgepole panel (Figure 2). This “high density” site is an even-aged lodgepole stand that happens to be surrounded by high quality spruce-fir forest on at least two sides. Thus, the high relative hare density observed at this site may be due to the quality habitat in adjacent stands rather than by the quality of the sampled stand itself. While we left the point on the figure for transparency, we excluded it when fitting the curve as it appears to be a true outlier (including it “flattens” the curve somewhat such that it crosses the control line at about 55 years). Literature Cited: Hodges, K. E., and L. S. Mills. 2008. Designing fecal pellet surveys for snowshoe hares. Forest Ecology and Management 256:1918-1926. Ivan, J. S., and T. M. Shenk. 2016. Winter diet and hunting success of Canada lynx in Colorado. The Journal of Wildlife Management 80:1049-1058. U.S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: determination of threatened status for the contiguous U. S. distinct population segment of the Canada lynx and related rule, final rule. Federal Register 65:16052–16086. 9 �Figure 1. Location of all stands (n = 130) resampled for snowshoe hare pellets, June-September 2020. Figure 2. Fitted quadratic function (white line) and 95% CI (shaded polygon) relating pellet counts (i.e., relative snowshoe hare density) to time elapsed since treatment for each forest type × management activity combination. Dotted lines indicate the mean pellets/plot for the unmanaged controls for each forest type. 10 �UNGULATE MANAGEMENT AND CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACRIVITY AND HABITAT DEGRADATION PLANT AND MULE DEER RESPONSES TO PINYON-JUNIPER REMOVAL BY THREE MECHANICAL METHODS EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO RESPONSE OF ELK TO HUMAN RECREATION AT MULTIPLE SCALES: DEMOGRAPHIC SHIFTS AND BEHAVIORALLY MEDIATED FLUCTUATIONS IN ABUNDANCE SPATIOTEMPORAL EFFECTS OF HUMAN RECREATION ON ELK BEHAVIOR: AN ASSESSMENT WITHIN CRITICAL TIME STAGES 11 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation Period Covered: July 1, 2020 − June 30, 2021 Principal Investigator: C. R. Anderson, Jr. Personnel: D. Bilyeu-Johnston, K. Aagaard, CPW; J. Northrup, Ontario Ministry of Natural Resources and Forestry; B. Gerber, University of Rhode Island; G. Wittemyer, Colorado State University. Project support received from Federal Aid in Wildlife Restoration, Colorado Mule Deer Association, Colorado Mule Deer Foundation, Muley Fanatic Foundation, Colorado State Severance Tax Fund, Caerus Oil and Gas LLC, EnCana Corp., ExxonMobil Production Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, Williams and WPX Energy. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent preliminary and final results of a 10-year research project addressing habitat improvements as mitigation and evaluation of deer responses to energy development activities to inform future development planning options on important seasonal ranges. From 2008–2019, we monitored deer on 4 winter range study areas representing relatively high (Ryan Gulch, South Magnolia) and low (North Magnolia, North Ridge) levels of development activity (Figure 1) to address factors influencing deer behavior and demographics and to evaluate success of habitat treatments as a mitigation option. We recorded adult female habitat use and movement patterns; estimated neonatal, overwinter fawn and annual adult female survival; estimated annual early and late winter body condition, pregnancy and fetal rates of adult females; and estimated annual mule deer abundance among study areas. Winter range habitat improvements completed spring 2013 resulted in 604 acres of mechanically treated pinion-juniper/mountain shrub habitats in each of 2 treatment areas (Figure 2) with minor (North Magnolia) and extensive (South Magnolia) energy development, respectively. During this research segment, we finalized publication of mule deer behavioral and demographic responses to energy development activity (Northrup et al. 2021; Appendix A) and submitted results addressing vegetation and mule deer responses to 3 mechanical treatment methods (Johnston and Anderson, in review; see next research summary) for publication (Wildlife Society Bulletin). Based on final (migration, mule deer behavioral and demographic responses, reproductive success and neonate survival; see Anderson 2019 for detailed methods and results and Appendix A for publication abstracts) and preliminary data analyses (vegetation and herbivore response to habitat treatments, next research summary) for this 10-year project: (1) annual adult female survival was consistent among areas averaging 79-87% annually, but overwinter fawn survival was variable, ranging from 31% to 95% within study areas, 12 �with annual and study area differences primarily due to early winter fawn condition, annual weather conditions, and factors associated with predation on winter range; (2) mule deer body condition early and late winter was generally consistent within areas, with higher variability among study areas early winter, primarily due to December lactation rates, and late winter condition related to seasonal moisture and winter severity; (3) late winter mule deer densities increased through 2016 in all study areas, ranging from 50% in North Ridge to 103% in North Magnolia, but have stabilized recently in 3 of the 4 study areas with recent decline evident in North Ridge (Figure 3); (4) migratory mule deer selected for areas with increased cover and increased their rate of travel through developed areas, and avoided negative influences through behavioral shifts in timing and rate of migration, but did not avoid development structures (Figure 4); (5) mule deer exhibited behavioral plasticity in relation to energy development, without evidence of demographic effects, where disturbance distance varied relative to diurnal extent and magnitude of development activity (Figure 5), which provide for useful mitigation options in future development planning; and (6) energy development activity under existing conditions did not influence pregnancy rates, fetal rates or early fawn survival (0-6 months), but may have reduced fetal survival (March until birth) during 2012 when drought conditions persisted during the third trimester of doe parturition (Figure 6). Final results are pending to address vegetation and mule deer responses to assess habitat treatment mitigation options for energy development planning, and to develop a spatial planning tool to guide future energy development. Final data collection efforts for this project were completed by spring 2020. Collaborative research with agency biologists, graduate students, and university professors has produced 22 scientific publications (see Anderson 2021, Appendix A) addressing improved monitoring techniques for neonate mule deer captures; development and evaluation of a remote mule deer collaring device; mule deer migration relative to energy development; improved approaches to address animal habitat use patterns; mule deer response to helicopter capture and handling; potential effects of male-biased harvest on mule deer productivity; mule deer genetics in relation to body condition and migration; acoustic monitoring to investigate spatial and temporal factors influencing mule deer vigilance and foraging behavior; the relationship of plant phenology with mule deer body condition; approaches to identify causespecific mortality in mule deer from field necropsies; the influence of individual and temporal factors affecting late winter body condition estimates of adult female mule deer; and mule deer behavioral and demographic responses to energy development activities to inform future development planning. Publications describing these results are summarized in Anderson 2021, Appendix A, and preliminary results describing vegetation and herbivore responses to habitat treatments are reported in the next research summary. We anticipate the opportunity to work cooperatively toward developing solutions for allowing the nation’s energy reserves to be developed in a manner that benefits wildlife and the people who value both the wildlife and energy resources of Colorado and elsewhere. Literature Cited: Anderson, C. R., Jr. 2019. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Federal Aid in Wildlife Restoration Annual Report W-243-R3, Ft. Collins, CO USA. Anderson, C. R., Jr. 2021. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Federal Aid in Wildlife Restoration Annual Report W-243-R4, Ft. Collins, CO USA. Northrup, J. M., C. R. Anderson Jr., B. D. Gerber, and G. Wittemyer. 2021. Behavioral and demographic responses of mule deer to energy development on winter range. Wildlife Monographs 208:1–37; DOI: 10.1002/wmon.1060. 13 �Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, winter 2013/14 (Accessed http://cogcc.state.co.us/ December 31, 2013; energy development activity has been minor since 2013). Figure 2. Habitat treatment site delineations in 2 mule deer study areas (604 acres each) of the Piceance Basin, northwest Colorado (Top; cyan polygons completed Jan 2011 using hydro-axe; yellow polygons completed Jan 2012 using hydro-axe, roller-chop, and chaining; and remaining polygons completed Apr 2013 using hydro-axe). January 2011 hydro-axe treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 14 �Piceance Basin late winter mule deer density 35.00 30.00 Deer/km2 25.00 20.00 15.00 10.00 5.00 0.00 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Year Figure 3. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2018. Figure 4. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012; http://dx.doi.org/10.1890/ES12-00165.1). 15 �Figure 5. Posterior distributions of population-level coefficients related to natural gas development for RSF models during the day (top) and night (bottom) for 53 adult female mule deer in the Piceance Basin, northwest Colorado. Dashed line indicates 0 selection or avoidance (below the line) of the habitat features. ‘Drill’ and ‘Prod’ represent drilling and producing well pads, respectively. The numbers following ‘Drill’ or ‘Prod’ represent the distance from respective well pads evaluated (e.g., ‘Drill 600’ is the number of well pads with active drilling between 400–600 m from the deer location; from Northrup et al. 2015; http://onlinelibrary.wiley.com/doi/10.1111/gcb.13037/abstract). Road disturbance was relatively minor (~60–120 m, not illustrated above). Figure 6. Model averaged estimates of mule deer fetal survival from early March until birth (late May– June) in high and low energy development study areas of the Piceance Basin, northwest Colorado, 2012– 2014 (from Peterson et al. 2017; http://www.bioone.org/doi/pdf/10.2981/wlb.00341). 16 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Plant and mule deer responses to pinyon-juniper removal by three mechanical methods (follow-up to: Examining the effectiveness of mechanical treatments as a restoration technique for mule deer habitat) Period Covered: July 1, 2020 – June 30, 2021 Principal Investigators: Danielle Johnston (Danielle.bilyeu@state.co.us), Chuck Anderson (chuck.anderson@state.co.us) Personnel: C. Bishop, D. Collins, K. Kain, S. VanNortwick, B. deVergie, D. Finley, L. Gepfert, T. Knowles, B. Petch, J. Rivale, Z. Swennes, M. Way, CPW; L. Belmonte, E. Hollowed, BLM; M. Paschke, G. Stephens, B. Wolk, J. Northrup, B. Gerber, G. Wittemyer, Colorado State University; L. Coulter, Coulter Aviation. Project support received from Federal Aid in Wildlife Restoration, Colorado Mule Deer Association, Colorado Mule Deer Foundation, Muley Fanatic Foundation, Colorado State Severance Tax Fund, Caerus Oil and Gas LLC, EnCana Corp., ExxonMobil Production Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, and WPX Energy. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. Land managers in western North America often reverse succession by removing pinyon (Pinus spp.) and juniper (Juniperus spp.) trees to reduce fire risk and/or increase forage for wildlife or livestock (Monaco and Gunnell 2020). Because prescribed fire is risky, mechanical methods such as chaining, rollerchopping, and mastication are often used (Figure 1). Mechanical methods differ in cost and in the size of woody debris produced, and may also differ in plant and animal responses. We implemented a randomized, complete-block, split-plot experiment in December 2011 in the Piceance Basin, northwestern Colorado, USA, to compare chaining, rollerchopping, mastication and control (whole plots, n = 7) and to explore seeding (subplot) interactions (Figure 2). We assessed plants 1, 2, 5, and 6 years post-treatment, and mule deer (Odocoileus hemionus) response via GPS locations 3-8 years post-treatment. Early results were published previously (Stephens et al. 2016); this effort combines follow-up vegetation data with mule deer responses. By 2016, treated plots had 3-5 times higher perennial grass cover and ~10 times higher cheatgrass (Bromus tectorum) cover than controls (Figure 3). Rollerchopped plots had both the highest annual species cover, and when seeded, also the highest density of bitterbrush (Purshia tridentata), a nutritious shrub for mule deer (Figure 4). Winter deer GPS point detections in chained and rollerchopped plots were almost twice as high as control (P < 0.001), while detections in masticated plots were about 20% higher than control (P ≤ 0.042; Figure 5). Deer detections appear related to a combination of relative hiding cover, resulting from residual woody debris, and winter forage availability. Masticated plots received higher bitterbrush use during summer/fall than chained or rollerchopped plots (P < 0.05; Figure 6). This may have made masticated plots less attractive the following winter, as ungulates tend to browse the most palatable plants and plant parts first (Armstrong and Macdonald 1992). Rollerchopped and chained plots appeared to provide the best combination of mule deer cover and winter forage, but mastication, applied leaving dispersed security cover, may be a viable option where invasive species concerns exist. 17 �Literature Cited: Armstrong, H. M., and A. J. Macdonald. 1992. Tests of different methods for measuring and estimating utilization rate of heather (Calluna-Vulgaris) by vertebrate herbivores. Journal of Applied Ecology 29:285-294. Monaco, T. A., and K. L. Gunnell. 2020. Understory vegetation change following woodland reduction varies by plant community type and seeding status: a region-wide assessment of ecological benefits and risks. Plants 9:1113. Stephens, G. J., D. B. Johnston, J. L. Jonas, and M. W. Paschke. 2016. Understory responses to mechanical treatment of pinyon-juniper in northwestern Colorado. Rangeland Ecology & Management 69:351-359. Figure 1. Equipment, residual structure, and vegetation response 9 years post-treatment for a) chaining, b) rollerchopping, and c) mastication. 18 �Figure 2. Location of tree removal and control plots within north and south Magnolia winter range study areas in the Piceance Basin, Rio Blanco County, Colorado, USA. 19 �Figure 3. Percent cover of A) snowberry, B) perennial grasses, C) exotic annual forbs, and D) cheatgrass 1-6 years following implementation of 3 pinyon and juniper removal methods, unseeded subplots only. Points not sharing letters are significantly different at α = 0.05 for within-year contrasts between treatments. Error bars = 95% CIs. 20 �Figure 4. 2017 bitterbrush density within seeded (solid outline) and unseeded (dashed outline) subplots 6 years after implementation of 3 pinyon and juniper removal methods: CON (control), MAST (masticated), CHAIN (chained, and ROLLER (rollerchopped). Star indicates a significant contrast between seeded and unseeded subplots at α = 0.05. Error bars = 95% CIs. Figure 5. Mule deer GPS locations (points/ha) in winter over a 5-year period in control plots and plots treated to remove pinyon and juniper trees by 3 different methods: CON (control), MAST (masticated), CHAIN (chained), and ROLLER (rollerchopped). Bars not sharing letters are significantly different at α = 0.056. Error bars = 95% CIs. A B Figure 6. Percent of current year growth removed by herbivory during the growing season for A) bitterbrush and B) serviceberry 6 years following implementation of 3 pinyon and juniper removal methods: CON (control), MAST (masticated), CHAIN (chained), and ROLLER (rollerchopped), unseeded subplots only. Bars not sharing letters are significantly different at α = 0.05. Error bars = 95% CIs. 21 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation and incorporation of life history traits, nutritional status, and browse characteristics in Shira’s moose management in Colorado Period Covered: July 1, 2020 − June 30, 2021 Principal Investigator: Eric J. Bergman, eric.bergman@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. During November of 2013 we initiated a large scale moose research project in 3 of Colorado Parks and Wildlife’s 4 geographical regions (NE, NW, and SW; Figure 1). After 3 field seasons this research was scaled back and became focused on moose herds in the NW (North Park) and NE (Laramie River) Regions. During FY 20-21 this research project will be completed. The primary objectives during all years of this project were the capture of adult female moose for the purposes of deploying VHF and GPS collars, collecting pregnancy data via blood serum, evaluating body condition via ultrasonography, and collecting early winter calf-at-heel ratios. Beginning in 2014–2015 and continuing through the summer of 2019, summer field efforts focused on estimation of parturition rates. Between November 2013 and January 2019, 255 moose were captured. These 255 capture events were comprised of 178 unique individuals and 78 recaptures. A total of 214 observations of radio collared moose were made during parturition, and a total of 319 willow measurements were collected. Initial analyses and publications from this project focused on quantification of moose calf-at-heel detection probabilities, but also estimation of moose parturition timing. Subsequent analyses and publication focused on relationships between willow community diversity, digestibility, and moose productivity. Final analyses and publications will focus on adult female survival, pregnancy, and apparent calf survival. Between 2013-2019 annual survival of radio collared animals was 90.3% (range: 84.2%-93.0%). During that period, we observed that the probability of moose being pregnant was best predicted by maximum loin depth (Figure 2), whereas regional and annual effects in pregnancy rates were not discernible. Pregnancy rates averaged 75%, and were similar between areas (70% in NW Colorado, 60% in NE Colorado), although a high degree of annual variation in pregnancy was observed and strong inference was limited by samples size. Over the course of this study, average calf-at-heel estimates at the time of parturition were 67 calves/100 cows, but these estimates deteriorated to 52 calves/100 cows at the time of capture (mid-December). The observed decay in calf-at-heel ratios during the 7-month window between parturition and winter capture suggested monthly calf survival was 96.7% (Figure 3). Overall, data collected during this project met expectations. In particular, survival rates were consistently high in all study areas. Observed pregnancy rates were lower and more variable that other ungulates in Colorado. Twinning rates ranged from 5%-10% during this study. Observed winter calf-atheel rates suggest that moose calf survival during the first 7 months of life was 79%. However, anecdotal information throughout Colorado suggests moose populations are stable or increasing. The merger of low and variable pregnancy rate data with average survival rate data during the first 7-months of life suggests moose calf survival during the subsequent 5-months, leading to 1-year recruitment, is high. If indeed 22 �true, novel sources of mortality to moose calves during the overwinter period may impose a disproportionate impact on overall moose herd performance. Figure 1. Moose research study areas, located in 3 regions in Colorado. A total of 255 moose were captured during winters between 2013–2014 and 2018–2019. 23 �Probability of Being Pregnant 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1 6 11 16 21 26 31 36 41 46 Moose Loin Depth (mm) 51 56 Figure 2. During the course of this study, probability of moose pregnancy has been best predicted by measured loin depth. The relationship between body condition and pregnancy status is reflected by the solid black line and from data collected during the all 5 years of the study (dotted lines represent 95% CIs). No regional effects were found in our data, and the lack of significance of annual effects in our best performing models is likely driven by small sample sizes. Proportion of moose observed as pregnant or with a calf-at-heel 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 2012 2013 2014 2015 2016 2017 2018 Year Figure 3. Summary of moose reproduction and 6-month recruitment data. White bars reflect observed calf-at-heel data collected in December during annual moose capture efforts. Winter data are associated with reproduction from the previous year. Dark gray bars reflect pregnancy rates derived from Pregnancy Specific Protein B (PSPB) concentrations in blood collected during December each year. Light gray bars reflect calf-at-heel ratios (CPW unpublished data) collected at the time of parturition in early summer each year. Error bars = 95% confidence intervals for winter pregnancy and December calf-at-heel ratios and 95% credible intervals for spring calf-at-heel ratios. 24 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluating factors influencing elk recruitment in Colorado Period Covered: July 1, 2020 − June 30, 2021 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Mat Alldredge, mat.alldredge@state.co.us; Chuck Anderson chuck.anderson@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In Colorado, elk (Cervus canadensis) are an important natural resource that are valued for ecological, consumptive, aesthetic, and economic reasons. In 1910, less than 1,000 elk remained in Colorado (Swift 1945), but today the state population is estimated to be the largest in the country, with more than 290,000 elk. Over the last two decades, however, wildlife managers in Colorado have become increasingly concerned about declining winter elk calf recruitment (estimated using juvenile/adult female ratios) in the southern portion of the state. Although juvenile/adult female ratios are often highly correlated with juvenile elk survival, they are an imperfect estimate of recruitment because they are affected by harvest, pregnancy rates, juvenile survival, and adult female survival (Caughley 1974, Gaillard et al. 2000, Harris et al. 2008, Lukacs et al. 2018). Thus, there is a need for elk research in Colorado based upon monitoring of marked individuals to evaluate factors affecting each stage of production and survival. In 2016, we began a 2-year pilot study to investigate factors influencing elk recruitment in 2 elk Data Analysis Units (DAUs; E-20, E-33) with low juvenile/adult female ratios (Figure 1). In 2019, we expanded this pilot study work into a 3rd DAU with high juvenile/adult female ratios (E- 2), to better determine how predators, habitat, and weather conditions are impacting elk recruitment in Colorado (Figure 2). Since study initiation, we have collared 354 pregnant female elk in February and March by helicopter net-gunning (Table 1). Averaged across years, we estimated that annual pregnancy rates of adult female elk were 93% in the Bear’s Ears herd (excluding 2019 data where n = 3), 88% in the Trinchera herd (range = 78-95%), and 90% (range = 77-97%) in the Uncompahgre Plateau herd (Figure 3). Elk populations experiencing good to excellent summer-autumn nutrition typically have pregnancy rates ≥90% (Cook et al. 2013). From 2019-2021, we estimated that annual mean ingesta-free body fat (IFBF) of adult female elk was 6.74% in the Bear’s Ears Herd, 7.20% in the Trinchera herd, and 7.10% in the Uncompahgre Plateau herd (Figure 4). When late-winter IFBF values are <8-9% for adult female elk that have lactated through the previous growing season, this suggests that there may be nutritional limitations, but it does not identify whether limitations are a result of summer-autumn or winter nutrition (R. Cook, personal communication). From 2017–2021, we collared 595 neonate elk calves in May-August and 100 6-month old elk calves in December (Table 2). In 2019, the estimated mean date of calving was June 1 in the Trinchera herd, and June 3 in the Uncompahgre Plateau herd. In 2020, the estimated mean date of calving was May 31 in the Bear’s Ears and Uncompahgre Plateau herds, and June 3 in the Trinchera herd. In 2021, the estimated mean date of calving was June 1 in the Bear’s Ears herd, June 3 in the Trinchera herd, and June 4 in the Uncompahgre Plateau herd. In 2019, the mean weight of 6-month old calves was 101.8 kg (224.4 lb) (95% CI = 96.5-107.2 kg [212.7-236.3 lb]) from the Bear’s Ears herd and 113.9 kg (251.1 lb) (95% CI = 108.4-119.4 kg [239.0-263.2 lb]) from the Uncompahgre Plateau elk herd. In 2020, the mean weight of 25 �calves from the Bear’s Ears herd was 97.9 kg (215.8 lb) (95% CI = 90.9-104.9 kg [200.4-231.3 lb]) and 102.8 kg (226.6 lb) (95% CI = 96.6-108.9 kg [213.0-240.1 lb]) from the Uncompahgre Plateau elk herd. Literature Cited: Caughley, G. 1974. Interpretation of age ratios. Journal of Wildlife Management 38:557–562. Cook, R. C., J. G. Cook, D. J. Vales, B. K. Johnson, S. M. McCorquodale, L. A. Shipley, R. A. Riggs, L. L. Irwin, S. L. Murphie, B. L. Murphie, K. A. Schoenecker, F. Geyer, P. B. Hall, R. D. Spencer, D. A. Immell, D. H. Jackson, B. L. Tiller, P. J. Miller, and L. Schmitz. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1–44. Gaillard, J.-M., M. Festa-Bianchet, N. G. Yoccoz, A. Loison, and C. Toigo. 2000. Temporal variation in fitness components and population dynamics of large herbivores. Annual Review of Ecology, Evolution, and Systematics 31:367–393. Harris, N. C., M. J. Kauffman, and L. S. Mills. 2008. Inferences about ungulate population dynamics derived from age ratios. Journal of Wildlife Management 72:1143–1151. Lukacs, P. M., M. S. Mitchell, M. Hebblewhite, B. K. Johnson, H. Johnson, M. Kauffman, K. M. Proffitt, P. Zager, J. Brodie, K. Hersey, A. A. Holland, M. Hurley, S. McCorquodale, A. Middleton, M. Nordhagen, J. J. Nowak, D. P. Walsh, and P. J. White. 2018. Factors influencing elk recruitment across ecotypes in the western United States. Journal of Wildlife Management 82:698–710. Swift, L. W. 1945. A partial history of the elk herds of Colorado. Journal of Mammalogy 26:114–119. 26 �Table 1. The number of pregnant adult female elk collared in March in in the Bear’s Ears (DAU E-2), Trinchera (DAU E-33), and Uncompahgre Plateau (DAU E-20) elk herds from 2017-2021 in Colorado, USA. Herd Year Bear's Ears Trinchera Uncompahgre Plateau 2017 22 23 2018 17 30 2019 2 30 30 2020 40 20 40 2021 40 20 40 Table 2. The number of neonate and 6-month old elk calves (6-month old calf totals are displayed in parentheses) collared from in the Bear’s Ears (DAU E-2), Trinchera (DAU E-33), and Uncompahgre Plateau (DAU E-20) elk herds from 2017-2021 in Colorado, USA. Herd Year Bear's Ears Trinchera Uncompahgre Plateau 2017 57 40 2018 53 48 2019 49 (25) 46 49 (25) 2020 54 (25) 21 52 (25) 2021 53 21 52 27 �Figure 1. The number of elk calves per 100 adult females observed during December-February aerial surveys (5-year average from 2013-2017) within elk Data Analysis Units (DAUs; labeled with black text) in Colorado, USA. Figure 2. The estimated number of calves per 100 adult females observed annually during winter classification surveys in the Bear’s Ears (DAU E-2), Trinchera (DAU E-33), and Uncompahgre Plateau (DAU E-20) elk herds from 1980-2020 (1992-2020 for the Trinchera herd) in Colorado, USA. Red lines and shaded bands represent linear regression trends with 95% confidence intervals, and indicate an average decrease of 1.05 and 0.56 calves per 100 adult females per year in the Trinchera and Uncompahgre Plateau herds, respectively. 28 �Figure 3. Estimated average pregnancy rates of adult female elk from the Bear’s Ears (DAU E-2), Trinchera (DAU E-33), and Uncompahgre Plateau (DAU E-20) herds sampled during late winter 20172020 in Colorado, USA. The sample size is given at the top of the 95% binomial confidence intervals (black lines). Figure 4. The estimated ingesta-free body fat (%) of adult female elk from the Bear’s Ears (DAU E-2), Trinchera (DAU E-33), and Uncompahgre Plateau (DAU E-20) herds during late-winter 2019-2021 in Colorado, USA. 29 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Response of elk to human recreation at multiple scales: demographic shifts and behaviorallymediated fluctuations in local abundance Period Covered: July 1, 2020 − June 30, 2021 Principal Investigators: Eric Bergman, eric.bergman@state.co.us; Nathaniel Rayl, nathaniel.rayl@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. This project has objectives on 2 scales. At the broad, elk herd-level scale, we are estimating pregnancy rates, calf survival rates, and cause-specific mortality rates to evaluate the importance of mortality sources for elk calf survival. More specifically, we are evaluating the influence of biotic (birth date, birth mass, gender, maternal body condition, habitat conditions), abiotic (previous and current weather conditions), and human-induced factors (i.e., relative exposure to recreational activities) on seasonal mortality risk of elk calves from birth to age 1 and on pregnancy rates of mature female elk. At the narrower geographic and temporal scale, we are using short-term (~3-4 weeks) changes in elk abundance within small study units (<65 km2 [25 mi2]) as a tool to evaluate the influence of human recreation on elk distribution. At this narrower scale, the primary objective is to evaluate the role that human recreation (e.g., hiking, mountain biking, horseback riding, trail running, hunting, etc.) has on the behavioral distribution of elk on spring calving, summer, and fall transition ranges. Coupled to the objective of detecting behaviorally influenced changes in abundance and density, we are evaluating the effectiveness of current recreational closures maintained by ski areas, counties, and federal land management agencies. Since study initiation, we have collared 104 pregnant female elk, 24 in March 2019, 40 in March 2020, and 40 in March 2021. We estimated the pregnancy rate of adult female elk was 89% (95% CI = 73-96%; n = 28) in 2019, 95% (95% CI = 84-99%; n = 41) in 2020, and 85% (95% CI = 72-93%; n = 47) in 2021. Elk populations experiencing good to excellent summer-autumn nutrition typically have pregnancy rates ≥90% (Cook et al. 2013). We estimated the mean percent ingesta-free body fat (IFBF) of adult female elk to be 7.4% (95% CI = 6.5-8.3%; n = 28) in 2019, 8.1% (95% CI = 7.5-8.8%; n = 38) in 2020, and 8.2% (95% CI = 7.4-9.0%; n = 47) in 2021. When late-winter IFBF values are <8-9% for adult female elk that have lactated through the previous growing season, this suggests that there may be nutritional limitations, but it does not identify whether limitations are a result of summer-autumn or winter nutrition (R. Cook, personal communication). From May-July 2019–2021, we collared 131 neonate elk calves, 26 in 2019, 54 in 2020, and 51 in 2021. The estimated mean date of calving was May 31 (n = 20) in 2019, June 3 (n = 40) in 2020, and June 3 (n = 38) in 2021. We also collared 25 6-month old elk calves in December of 2019 and 2020. The mean weight of 6-month old calves was 115.8 kg (255.3 lb) (95% CI = 110.8-120.8 kg [244.3-266.3 lb]) in 2019 and 109.0 kg (240.3 lb) (95% CI: 103.3-114.8 kg [227.7-253.1 lb]) in 2020. During the summer of 2019, a total of 384,455 photos were taken by the 118 cameras deployed across 8 study units. During the summer of 2020, approximately 4.6 million photos were taken by the 238 cameras deployed across 8 study units. These photos are actively being archived. Automated photo 30 �recognition software continues to be developed and will be applied to these photos to expedite future analyses. Literature Cited: Cook, R. C., J. G. Cook, D. J. Vales, B. K. Johnson, S. M. McCorquodale, L. A. Shipley, R. A. Riggs, L. L. Irwin, S. L. Murphie, B. L. Murphie, K. A. Schoenecker, F. Geyer, P. B. Hall, R. D. Spencer, D. A. Immell, D. H. Jackson, B. L. Tiller, P. J. Miller, and L. Schmitz. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1–44. 31 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Spatiotemporal effects of human recreation on elk behavior: an assessment within critical time stages Period Covered: July 1, 2020 − June 30, 2021 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Eric Bergman, eric.bergman@state.co.us; Joe Holbrook, Joe.Holbrook@uwyo.edu All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. The influence of recreational disturbance on ungulate populations is of particular interest to wildlife managers in Colorado, as there is growing concern about its potential impacts within the state. Currently, the western United States is experiencing some of the highest rates of human population growth in the country, with growth in rural and exurban areas frequently outpacing growth in urban areas. Additionally, participation in outdoor recreation is also increasing. In Colorado, the number of individuals participating in recreational activities, and the associated demand for recreational opportunities, appear to be increasing. Understanding potential impacts of recreational activity on elk spatial ecology in Colorado is critical for guiding management actions, as altered movements may result in reduced foraging time and higher energetic costs, which may decrease fitness. We are studying elk from the resident portion of the Bear’s Ears elk herd (DAU E-2) in Colorado to determine potential impacts of recreational activities on this population. This research project is a collaboration between Colorado Parks and Wildlife (CPW) and the Haub School of Environment and Natural Resources at the University of Wyoming, and forms the basis of an M.S. thesis for a graduate student enrolled at the Haub School. In January 2020 and January 2021, we collared 30 and 26 adult female elk, respectively, from the resident portion of the Bear's Ears elk herd on U.S. Forest Service (USFS) land near Steamboat Springs. In both years, the estimated pregnancy rate was 93% (95% CI: 79-98%). From May-October 2020 we deployed trail counters at 22 trailheads in the Routt National Forest (Figure 1). We recorded roughly 100,000 people departing and returning from these trailheads. Among individual trailheads, we documented average daily traffic counts ranging from 2-325 people (Figure 2). Most traffic was recorded on weekends with noticeable lulls in traffic frequency observed during weekdays. During the 2021 field season, we again deployed trail counters at the 22 trailheads, and also added additional trail counters at 1-km intervals along each trail for up to 5-km from the trailhead. These additional trail counters are being deployed on a rotating basis to sample each trail. Data collected from these additional trail counters will provide an estimate of the decay of traffic along trails. During the 2020 and 2021 field season, we distributed handheld GPSs to recreationists (hikers, bikers, hunters) to record detailed tracks of human use within this trail system (Figure 3). In 2020, we collected over 100 GPS tracks. GPS tracks from recreationists and hunters will allow us to better quantify human recreation on the landscape and evaluate how elk respond to recreationists. 32 �Figure 1. Routt National Forest study area located in northwest Colorado, USA. 33 �Figure 2. Daily trends in trailhead traffic documented with trail counters from June through October 2020, excluding Fish Creek Falls, Mad Creek, and Red Dirt trailheads, which received average daily counts >200. Figure 3. GPS track (blue) recorded from recreational mountain biker on trail system (white) in August 2020. Note the off-trail use near Long Lake. 34 �SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT 35 �JULY 1, 2020-JUNE 30, 2021 alexandria.austermann@state.co.us https://cpw.catalog.aspencat.info/ All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discoura 36 �37 �38 �o o o o o o o Colorado Parks & Wildlife Research Library COLLECTION DEVELOPMENT POLICY Mission Statement • Under normal circumstances, only two copies of an item will be held in the Library collection due to space considerations. Exceptions may be made for items in high demand or those often in long-term check-out to CPW staff. Extra copies of internal, un-cataloged CPW publications will be kept as space permits. Only one copy of each journal issue will be held, with the exception of additional issues of Colorado Outdoors. • In general, only English language material will be added to the collection. A book in a foreign language may be added at the request of a CPW employee. Translations of CPW publications, currently Spanish versions of some brochures, should be retained. • When possible, CPW publications will be preserved in print format for long-term archiving. Since all current publications start as a PDF, the librarian will request enough print copies for cataloging and distribution if copies are printed. If physical copies of the report are not printed, the librarian will send a copy of the PDF to the State Library for archiving. The librarian will make every effort to obtain “white paper” publications from CPW staff and the CPW web site to add as many CPW publications to the library collection as possible. The recent addition of a suitable database for photos, journal articles, streaming videos and other digital items not suitable for the library catalog, widens the scope of items that can be collected, preserved and accessed. • Non-print formats–such as DVDs–will only be purchased by special request and will be shelved in the Library collection by subject. • Journals are purchased from the publisher on a fixed-fee basis to avoid mid-year price increases. Online access is preferred and print subscriptions are being phased out where possible. Annual review of the journals subscriptions is undertaken by the librarian with assistance from the research managers. • Theses and dissertations are added to the collection as donated. • Gifts to the library are accepted on a no-strings-attached basis. The individual donating the material will not dictate inclusion or retention. The librarian will follow standard guidelines for subject and format to decide what is added to the collection. Anything not added to the collection will be donated or recycled. • The physical condition of a book may influence inclusion in the collection. If water damaged with subsequent mold, the item will be discarded to prevent spread of mold. If repair of a damaged The Colorado Parks & Wildlife (CPW) Research Library serves two functions. 1. The library supports wildlife-related research and management by providing needed information, including books, full-text articles, publications from other government agencies, and literature searches. 2. The library serves as an institutional repository for documents written by Division staff and makes those freely available to the public. Evaluation of collection and maintenance policies The research library was created in the late 1960s primarily to provide support to the wildlife research sections, Avian, Mammals and Aquatic, and has evolved over the years to serve the broader information needs of CPW staff. The library’s print collection–which consists mainly of books, journals and Division publications–has been assembled through purchase, donation and contributions from Division staff. The collection is an excellent historic record of Division publications dating back to 1877, when the first fish commissioner was appointed. The collection also holds original print Federal Aid reports dating back to the late 1930s, written shortly after the Pittman-Robertson Federal Aid in Wildlife Restoration Act was passed in 1937. Two copies of all printed Division publications are cataloged and any extra copies the library receives are available for distribution upon request. The library maintains a mailing list of institutions and individuals that receive copies of printed reports. The Colorado State library receives and hosts PDF copies of Division publications that are then linked in the CPW library catalog. A digitization project for older CPW publications is underway and PDFs of publications are added to the library catalog or the State Library catalog as they are scanned. The following guidelines have been established by the librarian: • The library will collect items to support wildlife-related research and management. Items of a more general nature, fiction or sports books for example, will not be added to the collection. Purchase of new material is generally made at the request of, or in consultation with, CPW staff. Retention of non-wildlife subject material–i.e., computer manuals–will be based on space and usage. All items will be judged on the following factors: o o o o relevance and use, redundancy, relationship to existing collections at another library, accuracy and impartiality, authority of author/publisher, physical condition, suitability of subject and style, language, availability of an electronic format, timeliness, and unique features of the material. 1 2 item (torn pages, broken spine) is possible, the book will be repaired. Damaged items are judged using the same criteria as other material with the additional possibility of replacement if warranted. librarian will then make use of local academic or federal libraries or the nationwide interlibrary loan (ILL) network to borrow or obtain a full-text version of the request. If the librarian finds numerous requests from the same journal or book, it may prompt purchase of a copy for the library. It is often more efficient to purchase a book than to borrow it from another institution, especially if the material fills a gap in the library collection. Weeding policy Weeding, withdrawal of items that no longer meet collection criteria, is conducted as an ongoing or special project to evaluate items already in the library collection. Decisions are made on an item-by-item basis as to retention or withdrawal. Weeding is often started due to space considerations but should always follow the collection development guidelines. As in adding to the collection, withdrawal of material should be made with the entire collection in mind. The added availability of an electronic version will often spur selected weeding of print copies. Within the CPW collection, publication date considerations will generally only apply to specific subjects; a 3-year limit on retention of computer manuals, for example. Usage statistics are also not as relevant as in other libraries in determining what to keep and what to discard. Initial weeding is conducted by the librarian and may involve the subject specialists in the final retention decisions. In addition to physically removing the material from the shelf, time and labor must be allocated for disposal (recycling, sending to another library, etc.) and updating holdings in the library catalog database. Conclusion Due to the constant change in the information needs of CPW staff and the rapid growth of electronic media, this collection development policy should serve as a guideline for decision-making. It should not become a static document, but should be reviewed and updated periodically and revised as conditions change. Bibliography Booth, Andrew. Fahrenheit 451? A burning question on the evidence for book withdrawal. Health Information and Libraries Journal, 2009, v.26: 161-165. Christen, Kim, and Lotus Norton-Wisla. Sustainable Heritage Network. 2020. Creating policies slides. https://sustainableheritagenetwork.org/digital-heritage/creating-policies-slides. Accessed 05 October 2021. Currently, the print journal collection is not subject to weeding. There is plenty of space on the shelves for the current holdings and future need for physical copies is declining with electronic conversions. At some point, the print journals may be discarded but for the time being, there are journals and issues of journals that are not available online and so the physical copies are necessary to fulfill article requests. The non-Colorado state wildlife magazines (Montana Outdoors, South Dakota Conservation Digest, etc.) are a special subset of the journal collection and are subject to different rules. The issues of those journals will be displayed for a month or two and then discarded when new issues come in. Clayton, P. ACL1S guidelines for the preparation of a collection development policy. http://www.nla.gov.au/aclis/cdpguide.html. Accessed 10 Nov 2010. Hoffman, Frank W. Library collection development policies: academic, public and special libraries. Scarecrow Press, 2005. Lampasone, Lauren. A time to weed. Library Journal, May 1, 2008: 100. Electronic resources Norton-Wisla, Lotus. Sustainable Heritage Network. 2020. Collections development policy worksheet. https://sustainableheritagenetwork.org/digital-heritage/collections-development-policy-worksheet-1. Accessed 05 Oct 2021. Selection of electronic resources should follow the same collection development guidelines outlined above. However, the review process before purchase may be expanded due to the greater expenditure of funds and the wider audience that the e-resource may reach. For example, a trial or demonstration of a database may be scheduled to obtain staff input on relevance and use before the purchase is made. The addition of online journal access to our print subscription is made with input from the research managers if it will greatly increase our periodical subscription budget. As technology advances and the budget allows, review of products such as e-book collections and e-journal packages as well as additional features for the library catalog will be considered. Vogel, K.D. Integrating electronic resources into collection development policies. Collection management, 1996, v.21 (2): 65-76. Interlibrary Loan Authors No library can acquire every resource needed by its patrons. This is especially true with our ever developing subject diversity within wildlife-related topics. It is inevitable CPW staff will request items that are not owned by the research library. These requests will include articles from scholarly journals not covered in either our print subscriptions or online databases or books not in our collection. The Kay Horton Knudsen, Research Librarian, November 10, 2010 Alexandria Austermann, Research Librarian, October 05, 2021 Van Zijl, Carol. The why, what and how of collection development policies. South African Journal of Library and Information Science, Sept 1998, v.66 (3): 99-107. 39 �3 Purpose Values • Offer expert information and • Lend library materials at no cost • Create digital versions of CPW research assistance • Deliver requested materials in a timely manner • Streamline discovery of items in the library both physically and electronically documents to increase availability • Provide friendly service Strategic Plan Research Library Core Services Strategic Focus • Lend physical items from the library • Find requested documents, including • Increasing the visibility of the library to internal and external customers • Scanning or acquiring digital versions journal articles • Conduct literature searches • Provide access to information technologies of CPW documents to add to the library catalog • Rearranging the physical collection to increase library efficiency References Colorado Library Consortium, CLiC. 2017. 2017-2020 Strategic priorities. https://create.piktochart.com/output/20167422-strategic-priorities-2017-20. Accessed 6 Oct 2021. Sno-Isle Libraries. 2014. Sno-Isle Libraries strategic plan 2014-2016. 40 �APPENDIX A. CPW mammal research abstracts published since July 2020. Nongame Mammal Ecology and Conservation – pages 43-44 - A Specialized Forest Carnivore Navigates Landscape-Level Disturbance: Canada Lynx in Spruce-Beetle Impacted Forests - Improved Prediction of Canada Lynx Distribution Through Regional Model Transferability and Data Efficiency Carnivore Ecology and Management – pages 45-46 - Effects of Hunting on a Puma Population in Colorado Ungulate Ecology and Management – pages 47-50 - Estimation of Moose Parturition Dates in Colorado: Incorporating Imperfect Detections - Behavioral and Demographic Responses of Mule Deer to Energy Development on Winter Range - Elk migration influences the risk of disease spillover in the Greater Yellowstone Ecosystem - Some Memories Never Fade: Inferring Multi-Scale Memory Effects on Habitat Selection of a Migratory Ungulate Using Step-Selection Functions - Effects of Willow Nutrition and Morphology on Calving Success of Moose Wildlife Genetics and Disease Research – pages 51-52 - Host Relatedness and Landscape Connectivity Shape Pathogen Spread in the Puma, a Large Secretive Carnivore - Complex Evolutionary History of Felid Anelloviruses - Viral Sequences Recovered From Puma Tooth DNA Reconstruct Statewide Viral Phylogenies Journal of Wildlife Management Editorial – page 53 - EDITORS MESSAGE: A Perspective on the Journal of Wildlife Management 41 �NONGAME MAMMAL ECOLOGY AND CONSERVATION A Specialized Forest Carnivore Navigates Landscape-level Disturbance: Canada Lynx in Spruce-Beetle Impacted Forests John R. Squires,a Joseph D. Holbrook,b Lucretia E. Olson,a Jacob S. Ivan,c Randal W. Ghormley,d Rick L. Lawrencee a USDA Forest Service, Rocky Mountain Research Station, Missoula, MT, USA b Haub School of Environment and Natural Resources, Department of Zoology and Physiology, University of Wyoming, Laramie, WY, USA c Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO, USA d Rio Grande National Forest (retired), Monte Vista, CO, USA e Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT, USA Citation: Squires, J. R., J. D. Holbrook, L. E. Olson, J. S. Ivan, R. W. Ghormley, and R. L. Lawrence. 2020. A specialized forest carnivore navigates landscape-level disturbance: Canada lynx in spruce-beetle impacted forests. Forest Ecology and Management 475:118400. ABSTRACT Canada lynx (Lynx canadensis) occupy cold wet forests (boreal and subalpine forest) that were structured by natural disturbance processes for millennia. In the Southern Rocky Mountains, at the species’ southern range periphery, Canada lynx habitat has been recently impacted by large-scale disturbance from spruce beetles (Dendroctonus rufipennis). This disturbance poses a challenge for forest managers who must administer this novel landscape in ways that also facilitate timber salvage. To aid managers with this problem, we instrumented Canada lynx with GPS collars to document their selection of beetle impacted forests at spatial scales that spanned from landscapes to movement paths. We used a use-availability design based on remotely-sensed covariates to evaluate landscape- and path-level selection. We evaluated selection at the home-range scale in beetle-kill areas based on vegetation plots sampled in the field to quantify forest structure and composition. We found that across all scales of selection, Canada lynx selected forests with a higher proportion of beetle-kill trees that were generally larger in diameter than randomly available. Within home ranges, Canada lynx selected forests with greater live components of subalpine fir and live canopy of Engelmann spruce. During winter, Canada lynx exhibited functional responses, or disproportionate use relative to availability, for forest horizontal cover, diameter of beetle killed trees, live canopy of Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa), and additive use (and consistent selection) for relative density of snowshoe hares and density of subcanopy subalpine fir 3–4.9 in. (7.6–12.4 cm) in diameter. We discuss our results in the context of balancing resource needs of Canada lynx with the desire to salvage timber in beetle-impacted forests. Published July 2020 Improved Prediction of Canada Lynx Distribution Through Regional Model Transferability and Data Efficiency Lucretia E. Olson1, Nichole Bjornlie2, Gary Hanvey3, Joseph D. Holbrook4, Jacob S. Ivan5, Scott Jackson3, Brian Kertson6, Travis King7, Michael Lucid8, Dennis Murray9, Robert Naney10, John Rohrer10, Arthur Scully9, Daniel Thornton7, Zachary Walker2, and John R. Squires1 1 Rocky Mountain Research Station, U. S. Forest Service, Missoula, MT, USA 2 Wyoming Game and Fish Department, Lander, WY, USA 3 U. S. Department of Agriculture, Northern Region, U. S. Forest Service, Missoula, MT, USA 4 Dept. of Zoology and Physiology, Haub School of Environment and Natural Resources, University of Wyoming, Laramie, WY, USA 5 Colorado Parks and Wildlife, Fort Collins, CO, USA 6 Washington Department of Fish and Wildlife, Snoqualmie, WA, USA 7 School of the Environment, Washington State University, Pullman, WA, USA 8 Idaho Department of Fish and Game, Coeur d’Alene, ID, USA 9 Environmental and Life Sciences, Biology Department, Trent University, Peterborough, ON, Canada 10 U. S. Forest Service, Okanogan-Wenatchee National Forest, Winthrop, WA, USA Citation: Olson, L. E., N. Bjornlie, G. Hanvey, J. D. Holbrook, J. S. Ivan, S. Jackson, B. Kertson, T. King, M. Lucid, D. Murray, R. Naney, J. Rohrer, A. Scully, D. Thornton, Z. Walker, and J. R. Squires. 2021. Improved prediction of Canada lynx distribution through regional model transferability and data efficiency. Ecology and Evolution 11:1667–1690; doi.org/10.1002/ece3.7157 ABSTRACT The application of species distribution models (SDMs) to areas outside of where a model was created allows informed decisions across large spatial scales, yet transferability remains a challenge in ecological modeling. We examined how regional variation in animal-environment relationships influenced model transferability for Canada lynx (Lynx canadensis), with an additional conservation aim of modeling lynx habitat across the northwestern United States. Simultaneously, we explored the effect of sample size from GPS data on SDM model performance and transferability. We used data from three geographically distinct Canada lynx populations in Washington (n = 17 individuals), Montana (n = 66), and Wyoming (n = 10) from 1996 to 2015. We assessed 42 �regional variation in lynx-environment relationships between these three populations using principal components analysis (PCA). We used ensemble modeling to develop SDMs for each population and all populations combined and assessed model prediction and transferability for each model scenario using withheld data and an extensive independent dataset (n = 650). Finally, we examined GPS data efficiency by testing models created with sample sizes of 5%–100% of the original datasets. PCA results indicated some differences in environmental characteristics between populations; models created from individual populations showed differential transferability based on the populations' similarity in PCA space. Despite population differences, a single model created from all populations performed as well, or better, than each individual population. Model performance was mostly insensitive to GPS sample size, with a plateau in predictive ability reached at ~30% of the total GPS dataset when initial sample size was large. Based on these results, we generated well-validated spatial predictions of Canada lynx distribution across a large portion of the species' southern range, with precipitation and temperature the primary environmental predictors in the model. We also demonstrated substantial redundancy in our large GPS dataset, with predictive performance insensitive to sample sizes above 30% of the original. Published January 2021 43 �CARNIVORE ECOLOGY AND MANAGEMENT Effects of Hunting on a Puma Population in Colorado Kenneth A. Logana and Jonathan P. Rungeb a Mammals Research Section, Colorado Parks and Wildlife, 2300 S. Townsend Avenue, Montrose, CO 81401, USA b Terrestrial Programs, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA Citation: Logan, K. A. and J. P. Runge. 2020. Effects of hunting on a puma population in Colorado. Wildlife Monographs 209:1–35; DOI:10-1002/wmon.1061 ABSTRACT We investigated effects of regulated hunting on a puma (Puma concolor) population on the Uncompahgre Plateau (UPSA) in southwestern Colorado, USA. We examined the hypothesis that an annual harvest rate averaging 15% of the estimated number of independent individuals using the study area would result in a stable or increasing abundance of independent pumas. We predicted hunting mortality would be compensated by 1) a reduction in other causes of mortality, thus overall survival would stay the same or increase; 2) increased reproduction rates; or 3) increased recruitment of young animals. The study occurred over 10 years (2004–2014) and was designed with a reference period (years 1–5; i.e., RY1–RY5) without puma hunting and a treatment period (years 6–10; i.e., TY1–TY5) with hunting. We captured and marked pumas on the UPSA and monitored them year‐ round to examine their demographics, reproduction, and movements. We estimated abundance of independent animals using the UPSA each winter during the Colorado hunting season from reference year 2 (RY2) to treatment year 5 (TY5) using the Lincoln‐Petersen method. In addition, we surveyed hunters to investigate how their behavior influenced harvest and the population. We captured and marked 110 and 116 unique pumas in the reference and treatment periods, respectively, during 440 total capture events. Those animals produced known‐fate data for 75 adults, 75 subadults, and 118 cubs, which we used to estimate sex‐ and life stage‐specific survival rates. In the reference period, independent pumas more than doubled in abundance and exhibited high survival. Natural mortality was the major cause of death to independent individuals, followed by other human causes (e.g., vehicle strikes, depredation control). In the treatment period, hunters killed 35 independent pumas and captured and released 30 others on the UPSA. Abundance of independent pumas using the UPSA declined 35% after 4 years of hunting with harvest rates averaging 15% annually. Harvest rates at the population scale, including marked independent pumas with home ranges exclusively on the UPSA, overlapping the UPSA, and on adjacent management units were higher, averaging 22% annually in the same 4 years leading to the population decline. Adult females comprised 21% of the total harvest. The top‐ranked model explaining variation in adult survival (Ŝ) indicated a period effect interacting with sex. Annual adult male survival was higher in the reference period (Ŝ = 0.96, 95% CI = 0.75–0.99) than in the treatment period (Ŝ = 0.40, 95% CI = 0.22–0.57). Annual adult female survival was 0.86 (95% CI = 0.72–0.94) in the reference period and 0.74 (95% CI = 0.63–0.82) in the treatment period. The top subadult model showed that female subadult survival was constant across the reference and treatment periods (Ŝ = 0.68, 95% CI = 0.43–0.84), whereas survival of subadult males exhibited the same trend as that of adult males: higher in the reference period (Ŝ = 0.92, 95% CI = 0.57–0.99) and lower in the treatment period (Ŝ = 0.43, 95% CI = 0.25–0.60). Cub survival was best explained by fates of mothers when cubs were dependent (Ŝmother alive = 0.51, 95% CI = 0.35–0.66; Ŝmother died = 0.14, 95% CI = 0.03–0.34). The age distribution for independent pumas skewed younger in the treatment period. Adult males were most affected by harvest; their abundance declined by 59% after 3 hunting seasons and we did not detect any males >6 years old after 2 hunting seasons. Pumas born on the UPSA that survived to subadult stage exhibited both philopatry and dispersal. Local recruitment and immigration contributed to positive growth in the reference period, but recruitment did not compensate for the losses of adult males and partially compensated for losses of adult females in the treatment period. Average birth intervals were similar in the reference and treatment periods (reference period = 18.3 months, 95% CI = 15.5–21.1; treatment period = 19.4 months, 95% CI = 16.2– 22.6), but litter sizes (reference period = 2.8, 95% CI = 2.4–3.1; treatment period = 2.4, 95% CI = 2.0–2.8) and parturition rates (reference period = 0.63, 95% CI = 0.49–0.75; treatment period = 0.48, 95% CI = 0.37–0.59) declined slightly in the treatment period. Successful hunters used dogs, selected primarily males, and harvested pumas in 1–2 days (median). We found that an annual harvest rate at the population scale averaging 22% of the independent pumas over 4 years and with >20% adult females in the total harvest greatly reduced abundance. At this scale, annual mortality rates of independent animals from hunting averaged 6.3 times greater than from all other human causes and 4.6 times greater than from all natural causes during the population decline. Hunting deaths were largely additive and reproduction and recruitment did not compensate for this mortality source. Hunters generally selected male pumas, resulting in a decline in their survival and abundance, and the age structure of the population. We recommend that regulated hunting in a source‐sink structure be used to conserve puma populations, provide 44 �sustainable hunting opportunities, and address puma‐human conflicts. © 2021 The Wildlife Society. Published March 2021 45 �UNGULATE ECOLOGY AND MANAGEMENT Estimation of Moose Parturition Dates in Colorado: Incorporating Imperfect Detections Eric J. Bergman,a Forest P. Hayes,b and Kevin Aagaarda a Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO, USA b Wildlife Biology Program, University of Montana, Forestry 108, 32 Campus Drive, Missoula, MT 59812, USA Citation: Bergman, E. J., F. P. Hayes, and K Aagaard. 2020. Estimation of moose parturition dates in Colorado: incorporating imperfect detections. Alces 56:127–135. ABSTRACT Researchers and managers use productivity surveys to evaluate moose populations for harvest and population management purposes, yet such surveys are prone to bias. We incorporated detection probability estimates (p) into spring and summer ground surveys to reduce the influence of observer bias on the estimation of moose parturition dates in Colorado. In our study, the cumulative parturition probability for moose was 0.50 by May 19, and the probability of parturition exceeded 0.9 by May 27. Timing of moose calf parturition in Colorado appears synchronous with parturition in more northern latitudes. Our results can be used to plan ground surveys in a manner that will reduce bias stemming from unobservable and yet-born calves. Published August 2020 Behavioral and Demographic Responses of Mule Deer to Energy Development on Winter Range Joseph M. Northrup,a Charles R. Anderson Jr.,b Brian D. Gerber,c George Wittemyera a Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA b Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO 80526, USA c Department of Natural Resources Science, University of Rhode Island, 1 Greenhouse Road, Kingston, RI 02881‐2018, USA Citation: Northrup, J. M., C. R, Anderson Jr., B. D. Gerber, and G. Wittemyer. 2021. Behavioral and demographic responses of mule deer to energy development on winter range. Wildlife Monographs 208:1–37; DOI:10-1002/wmon.1060 ABSTRACT Anthropogenic habitat modification is a major driver of global biodiversity loss. In North America, one of the primary sources of habitat modification over the last 2 decades has been exploration for and production of oil and natural gas (hydrocarbon development), which has led to demographic and behavioral impacts to numerous wildlife species. Developing effective measures to mitigate these impacts has become a critical task for wildlife managers and conservation practitioners. However, this task has been hindered by the difficulties involved in identifying and isolating factors driving population responses. Current research on responses of wildlife to development predominantly quantifies behavior, but it is not always clear how these responses scale to demography and population dynamics. Concomitant assessments of behavior and population‐level processes are needed to gain the mechanistic understanding required to develop effective mitigation approaches. We simultaneously assessed the demographic and behavioral responses of a mule deer (Odocoileus hemionus) population to natural gas development on winter range in the Piceance Basin of Colorado, USA, from 2008 to 2015. Notably, this was the period when development declined from high levels of active drilling to only production phase activity (i.e., no drilling). We focused our data collection on 2 contiguous mule deer winter range study areas that experienced starkly different levels of hydrocarbon development within the Piceance Basin. We assessed mule deer behavioral responses to a range of development features with varying levels of associated human activity by examining habitat selection patterns of nearly 400 individual adult female mule deer. Concurrently, we assessed the demographic and physiological effects of natural gas development by comparing annual adult female and overwinter fawn (6‐month‐old animals) survival, December fawn mass, adult female late and early winter body fat, age, pregnancy rates, fetal counts, and lactation rates in December between the 2 study areas. Strong differences in habitat selection between the 2 study areas were apparent. Deer in the less‐developed study area avoided development during the day and night, and selected habitat presumed to be used for foraging. Deer in the heavily developed study area selected habitat presumed to be used for thermal and security cover to a greater degree. Deer faced with higher densities of development avoided areas with more well pads during the day and responded neutrally or selected for these areas at night. Deer in both study areas showed a strong reduction in use of areas around well pads that were being drilled, which is the phase of energy development associated with the greatest amount of human presence, vehicle traffic, noise, and artificial light. Despite divergent habitat selection patterns, we found no effects of development on individual condition or reproduction and found no differences in any of the physiological or vital rate parameters measured at the population level. However, deer density and annual increases in density were higher in the low‐development area. Thus, the recorded behavioral alterations did not appear to be associated with demographic or physiological costs measured at the individual level, possibly because 46 �populations are below winter range carrying capacity. Differences in population density between the 2 areas may be a result of a population decline prior to our study (when development was initiated) or area‐specific differences in habitat quality, juvenile dispersal, or neonatal or juvenile survival; however, we lack the required data to contrast evidence for these mechanisms. Given our results, it appears that deer can adjust to relatively high densities of well pads in the production phase (the period with markedly lower human activity on the landscape), provided there is sufficient vegetative and topographic cover afforded to them and populations are below carrying capacity. The strong reaction to wells in the drilling phase of development suggests mitigation efforts should focus on this activity and stage of development. Many of the wells in this area were directionally drilled from multiple‐well pads, leading to a reduced footprint of disturbance, but were still related to strong behavioral responses. Our results also indicate the likely value of mitigation efforts focusing on reducing human activity (i.e., vehicle traffic, light, and noise). In combination, these findings indicate that attention should be paid to the spatial configuration of the final development footprint to ensure adequate cover. In our study system, minimizing the road network through landscape‐level development planning would be valuable (i.e., exploring a maximum road density criteria). Lastly, our study highlights the importance of concomitant assessments of behavior and demography to provide a comprehensive understanding of how wildlife respond to habitat modification. © 2021 The Wildlife Society. Published January 2021 Elk Migration Influences the Risk of Disease Spillover in the Greater Yellowstone Ecosystem Nathaniel D. Rayl1, Jerod A. Merkle2, Kelly M. Proffitt3, Emily S. Almberg3, Jennifer D. Jones3, Justin A. Gude4, and Paul C. Cross5 1 Colorado Parks and Wildlife, Grand Junction, CO, USA 2 Department of Zoology and Physiology, University of Wyoming, Laramie, WY, USA 3 Montana Fish, Wildlife, and Parks, Bozeman, MT, USA 4 Montana Fish, Wildlife, and Parks, Helena, MT, USA 5 U.S. Geological Survey, Northern Rocky Mountain Science Center, Bozeman, MT, USA Citation: Rayl, N. D., J. A. Merkle, K. M. Profitt, E. S. Almberg, J. D. Jones, J. A. Gude, and P. C. Cross. 2021. Elk migration influences the risk of disease spillover in the Greater Yellowstone Ecosystem. Journal of Animal Ecology 90:1264-1275; doi.org/10.1111/1365-2656.13452. Abstract 1. Wildlife migrations provide important ecosystem services, but they are declining. Within the Greater Yellowstone Ecosystem (GYE), some elk Cervus canadensis herds are losing migratory tendencies, which may increase spatiotemporal overlap between elk and livestock (domestic bison Bison bison and cattle Bos taurus), potentially exacerbating pathogen transmission risk. 2. We combined disease, movement, demographic and environmental data from eight elk herds in the GYE to examine the differential risk of brucellosis transmission (through aborted fetuses) from migrant and resident elk to livestock. 3. For both migrants and residents, we found that transmission risk from elk to livestock occurred almost exclusively on private ranchlands as opposed to state or federal grazing allotments. Weather variability affected the estimated distribution of spillover risk from migrant elk to livestock, with a 7%–12% increase in migrant abortions on private ranchlands during years with heavier snowfall. In contrast, weather variability did not affect spillover risk from resident elk. 4. Migrant elk were responsible for the majority (68%) of disease spillover risk to livestock because they occurred in greater numbers than resident elk. On a per-capita basis, however, our analyses suggested that resident elk disproportionately contributed to spillover risk. In five of seven herds, we estimated that the per-capita spillover risk was greater from residents than from migrants. Averaged across herds, an individual resident elk was 23% more likely than an individual migrant elk to abort on private ranchlands. 5. Our results demonstrate links between migration behaviour, spillover risk and environmental variability, and highlight the utility of integrating models of pathogen transmission and host movement to generate new insights about the role of migration in disease spillover risk. Furthermore, they add to the accumulating body of evidence across taxa that suggests that migrants and residents should be considered separately during investigations of wildlife disease ecology. Finally, our findings have applied implications for elk and brucellosis in the GYE. They suggest that managers should prioritize actions that maintain spatial separation of elk and livestock on private ranchlands during years when snowpack persists into the risk period. Published Feb. 2021 47 �Some Memories Never Fade: Inferring Multi-Scale Memory Effects on Habitat Selection of a Migratory Ungulate Using Step-Selection Functions Helena Rheault1, Charles R. Anderson Jr.2, Maegwin Bonar1, Robby R. Marrotte1, Tyler R. Ross3, George Wittemyer4 and Joseph M. Northrup1,5 1 Environmental and Life Sciences Graduate Program, Trent University, Peterborough, ON, Canada 2 Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO, United States 3 Department of Biology, York University, Toronto, ON, Canada 4 Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, CO, United States 5 Ontario Ministry of Natural Resources and Forestry, Peterborough, ON, Canada Citation: Rheault, H, C. R Anderson Jr, M. Bonar, R. R. Marrotte, T. R. Ross, G. Wittemyer, and J. M. Northrup. 2021. Some memories never fade: inferring multi-scale memory effects on habitat selection of a migratory ungulate using step-selection functions. Frontiers in Ecology and Evolution 9.702818; doi: 10.3389/fevo.2021.702818. ABSTRACT Understanding how animals use information about their environment to make movement decisions underpins our ability to explain drivers of and predict animal movement. Memory is the cognitive process that allows species to store information about experienced landscapes, however, remains an understudied topic in movement ecology. By studying how species select for familiar locations, visited recently and in the past, we can gain insight to how they store and use local information in multiple memory types. In this study, we analyzed the movements of a migratory mule deer (Odocoileus hemionus) population in the Piceance Basin of Colorado, United States to investigate the influence of spatial experience over different time scales on seasonal range habitat selection. We inferred the influence of short and long-term memory from the contribution to habitat selection of previous space use within the same season and during the prior year, respectively. We fit step-selection functions to GPS collar data from 32 female deer and tested the predictive ability of covariates representing current environmental conditions and both metrics of previous space use on habitat selection, inferring the latter as the influence of memory within and between seasons (summer vs. winter). Across individuals, models incorporating covariates representing both recent and past experience and environmental covariates performed best. In the top model, locations that had been previously visited within the same season and locations from previous seasons were more strongly selected relative to environmental covariates, which we interpret as evidence for the strong influence of both short- and long-term memory in driving seasonal range habitat selection. Further, the influence of previous space uses was stronger in the summer relative to winter, which is when deer in this population demonstrated strongest philopatry to their range. Our results suggest that mule deer update their seasonal range cognitive map in real time and retain long-term information about seasonal ranges, which supports the existing theory that memory is a mechanism leading to emergent space-use patterns such as site fidelity. Lastly, these findings provide novel insight into how species store and use information over different time scales. Published July 2021. Effects of Willow Nutrition and Morphology on Calving Success of Moose Forest P. Hayes1, Joshua J. Millspaugh1, Eric J. Bergman2, Ragan M. Callaway1, and Chad J. Bishop1 1 Wildlife Biology Program, University of Montana, Missoula, MT, USA 2 Colorado Parks and Wildlife, Fort Collins, CO, USA Citation: Hayes, F. P., J. J. Millspaugh, E. J. Bergman, R. M. Callaway, and C. J. Bishop. In Press. Effects of willow nutrition and morphology on calving success of moose. Journal of Wildlife Management 2022; https://doi.org/10.1002/jwmg.22175 ABSTRACT Across much of North America, populations of moose (Alces alces) are declining because of disease, predation, climate change, and anthropogenic-driven habitat loss. Contrary to this trend, populations of moose in Colorado, USA, have continued to grow. Studying successful (i.e., persistent or growing) populations of moose can facilitate continued conservation by identifying habitat features critical to persistence of moose. We hypothesized that moose using habitat with higher quality willow (Salix spp.) would have a higher probability of having a calf-atheel (i.e., calving success). We evaluated moose calving success using repeated ground observations of collared individuals with calves in an occupancy model framework to account for detection probability. We then evaluated the impact of willow habitat quality and nutrition on moose calving success by studying 2 spatially segregated populations of moose in Colorado. Last, we evaluated correlations between willow characteristics (browse intensity, height, cover, leaf length, and species) and willow nutrition (dry matter digestibility [DMD]) to assess the utility of using those characteristics to assess willow nutrition. We found willow height and cover had a high probability of being positively associated with higher individual-level calving success. Willow DMD, browse intensity, and leaf length were not predictive of individual moose calving success; however, the site with higher mean DMD 48 �consistently had higher mean estimates of calving success for the same year. Our results suggest surveying DMD is likely not a useful metric for assessing differences in calving success of individual moose but may be of use at population levels. Further, the assessment of willow morphology and density may be used to identify areas that support higher levels of moose calving success. Accepted for publication, In Press. 49 �WILDLIFE GENETICS AND DISEASE RESEARCH Host Relatedness and Landscape Connectivity Shape Pathogen Spread in the Puma, a Large Secretive Carnivore Nicholas M Fountain-Jones1, 2, Simona Kraberger3, Roderick B Gagne3, Daryl R Trumbo4, Patricia E Salerno4, 5 , W Chris Funk4, Kevin Crooks6, Roman Biek7, Mathew Alldredge8, Ken Logan9, Guy Baele10, Simon Dellicour10, 11, Holly B Ernest12, Sue VandeWoude3, Scott Carver13 , Meggan E Craft14 1 Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, 55108, USA. 2 School of Natural Sciences, University of Tasmania, Hobart, Australia, 7001. 3 Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, 80523, USA. 4 Department of Biology, Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, 80523, USA. 5 Universidad Regional Amazónica IKIAM, Km 7 vía Muyuna, Tena, Ecuador. 6 Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, CO, 80523, USA. 7 Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK. 8 Colorado Parks and Wildlife, Fort Collins, CO, 80526, USA. 9 Colorado Parks and Wildlife, Montrose, CO, 81401, USA. 10 Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium. 11 Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12 50, av. FD Roosevelt, 1050, Bruxelles, Belgium. 12 Wildlife Genomics and Disease Ecology Lab, Department of Veterinary Sciences, University of Wyoming, Laramie, WY, 82070, USA. 13 School of Natural Sciences, University of Tasmania, Hobart, Australia, 7001. 14 Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, 55108, USA. Citation: Fountain-Jones, N. M., S. Kraberger, R. B. Gagne, D. R. Trumbo, P. E. Salerno, W. C. Funk, K. Crooks, R. Biek, M. Alldredge, K. Logan, G. Baele, S. Dellicour, H. B. Ernest, S. VandeWoude, S. Carver, and M. E. Craft. 2021. Host relatedness and landscape connectivity shape pathogen spread in the puma, a large secretive carnivore. Communications Biology 4:12; doi: 10.1038/s42003-020-01548-2. ABSTRACT Urban expansion can fundamentally alter wildlife movement and gene flow, but how urbanization alters pathogen spread is poorly understood. Here, we combine high resolution host and viral genomic data with landscape variables to examine the context of viral spread in puma (Puma concolor) from two contrasting regions: one bounded by the wildland urban interface (WUI) and one unbounded with minimal anthropogenic development (UB). We found landscape variables and host gene flow explained significant amounts of variation of feline immunodeficiency virus (FIV) spread in the WUI, but not in the unbounded region. The most important predictors of viral spread also differed; host spatial proximity, host relatedness, and mountain ranges played a role in FIV spread in the WUI, whereas roads might have facilitated viral spread in the unbounded region. Our research demonstrates how anthropogenic landscapes can alter pathogen spread, providing a more nuanced understanding of host-pathogen relationships to inform disease ecology in free-ranging species. Published January 2021 Viral Sequences Recovered From Puma Tooth DNA Reconstruct Statewide Viral Phylogenies Roderick B. Gagne1,2, Simona Kraberger3, Rebekah McMinn1, Daryl R. Trumbo4 , Charles R. Anderson Jr.5, Ken A. Logan6, Mathew W. Alldredge5, Karen Griffin5 and Sue VandeWoude1 1 Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States 2 Department of Pathobiology, Wildlife Futures Program, University of Pennsylvania School of Veterinary Medicine, Kennett Square, PA, United States 3 The Biodesign Center for Fundamental and Applied Microbiomics, Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, United States 4 Department of Biology, Colorado State University, Fort Collins, CO, United States 5 Colorado Parks and Wildlife, Fort Collins, CO, United States, 6 Colorado Parks and Wildlife, Montrose, CO, United States Citation: Gagne, R. B., S., Kraberger, R. McMinn, D. R. Trumbo, C. R. Anderson Jr, K. A. Logan, M. W. Alldredge, K. Griffin, and S. VandeWoude. 2021. Viral sequences recovered from puma tooth DNA reconstruct statewide viral phylogenies. Frontiers in Ecology and Evolution 9:734462. doi: 10.3389/fevo.2021.734462 ABSTRACT Monitoring pathogens in wildlife populations is imperative for effective management, and for identifying locations for pathogen spillover among wildlife, domestic species and humans. Wildlife pathogen surveillance is challenging, however, as sampling often requires the capture of a significant proportion of the population to understand host pathogen dynamics. To address this challenge, we assessed the ability to use hunter collected teeth from puma across Colorado to recover genetic data of two feline retroviruses, feline foamy virus (FFV) and feline immunodeficiency virus (FIVpco) and show they can be utilized for this purpose. Comparative phylogenetic analyses of FIVpco and FFV from tooth and blood samples to previous analyses 50 �conducted with blood samples collected over a nine-year period from two distinct areas was undertaken highlighting the value of tooth derived samples. We found less FIVpco phylogeographic structuring than observed from sampling only two regions and that FFV data confirmed previous findings of endemic infection, minimal geographic structuring, and supported frequent cross-species transmission from domestic cats to pumas. Viral analysis conducted using intentionally collected blood samples required extensive financial, capture and sampling efforts. This analysis illustrates that viral genomic data can be cost effectively obtained using tooth samples incidentallycollected from hunter harvested pumas, taking advantage of samples collected for morphological age identification. This technique should be considered as an opportunistic method to provide broad geographic sampling to define viral dynamics more accurately in wildlife. Published August 2021 Complex Evolutionary History of Felid Anelloviruses Simona Kraberger1, Laurel E Serieys2, Cécile Richet3, Nicholas M Fountain-Jones4, Guy Baele5, Jacqueline M Bishop6, Mary Nehring7, Jacob S Ivan8, Eric S Newkirk9, John R Squires10, Michael C Lund3, Seth P Riley11, Christopher C Wilmers12, Paul D van Helden13, Koenraad Van Doorslaer14, Melanie Culver15, Sue VandeWoude7, Darren P Martin16, Arvind Varsani17 The Biodesign Center of Fundamental and Applied Microbiomics, School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, 85287, USA. 1 Environmental Studies, University of California, Santa Cruz, CA, 95064, USA; Institute for Communities and Wildlife in Africa, Department of Biological Sciences, University of Cape Town, Private Bag X3, Rondebosch, Cape Town, 7701, South Africa. 2 The Biodesign Center of Fundamental and Applied Microbiomics, School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, 85287, USA. 3 School of Natural Sciences, University of Tasmania, Hobart, 7001, Australia. Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium. Institute for Communities and Wildlife in Africa, Department of Biological Sciences, University of Cape Town, Private Bag X3, Rondebosch, Cape Town, 7701, South Africa. 4 5 6 Department of Microbiology, Immunology & Pathology, Colorado State University, Fort Collins, CO, 80523, USA. Colorado Parks and Wildlife, 317 W. Prospect Rd., Fort Collins, CO, 80526, USA. 9 Speedgoat Wildlife Solutions, Missoula, MT, 59801, USA. 10 US Department of Agriculture, Rocky Mountain Research Station, 800 E. Beckwith Ave., Missoula, MT, 59801, USA. 11 Santa Monica Mountains National Recreation Area, National Park Service, Thousand Oaks, CA, 91360, USA. 12 Environmental Studies, University of California, Santa Cruz, CA, 95064, USA. 13 DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research/SAMRC Centre for TB Research/Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, 7505, South Africa. 7 8 School of Animal and Comparative Biomedical Sciences, The BIO5 Institute, Department of Immunobiology, Cancer Biology Graduate Interdisciplinary Program, UA Cancer Center, University of Arizona, Tucson, AZ, 85724, USA. 14 U.S. Geological Survey, Arizona Cooperative Fish and Wildlife Research Unit, University of Arizona, Tucson, AZ, 85721, USA; School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA. 15 Computational Biology Group, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, 7925, South Africa. 16 The Biodesign Center of Fundamental and Applied Microbiomics, School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, 85287, USA; Structural Biology Research Unit, Department of Integrative Biomedical Sciences, University of Cape Town, 7925, Cape Town, South Africa. 17 Citation: Kraberger, S., L. E. Serieys, C. Richet, N. M. Fountain-Jones, G. Baele, J. M. Bishop, M. Nehring, J. S. Ivan, E. S. Newkirk, J. R. Squires, M. C. Lund, S. P. Riley, C. C. Wilmers, P. D. van Helden, K. Van Doorslaer, M. Culver, S. VandeWoude, D. P. Martin, and A. Varsani. 2021. Complex evolutionary history of felid anelloviruses. Virology 562:176–189; doi: 10.1016/j.virol.2021.07.013 ABSTRACT Anellovirus infections are highly prevalent in mammals, however, prior to this study only a handful of anellovirus genomes had been identified in members of the Felidae family. Here we characterise anelloviruses in pumas (Puma concolor), bobcats (Lynx rufus), Canada lynx (Lynx canadensis), caracals (Caracal caracal) and domestic cats (Felis catus). The complete anellovirus genomes (n = 220) recovered from 149 individuals were diverse. ORF1 protein sequence similarity network analysis coupled with phylogenetic analysis, revealed two distinct clusters that are populated by felid-derived anellovirus sequences, a pattern mirroring that observed for the porcine anelloviruses. Of the two-felid dominant anellovirus groups, one includes sequences from bobcats, pumas, domestic cats and an ocelot, and the other includes sequences from caracals, Canada lynx, domestic cats and pumas. Coinfections of diverse anelloviruses appear to be common among the felids. Evidence of recombination, both within and between felid-specific anellovirus groups, supports a long coevolution history between host and virus. Published July 2021 51 �JOURNAL OF WILDLIFE MANAGEMENT EDITORIAL EDITORS MESSAGE: A Perspective on the Journal of Wildlife Management Douglas H. Johnson1, Charles Anderson Jr.2, Roger D. Applegate3, Larissa Bailey4, Evan Cooch5, John Fieberg6, Alan B. Franklin7, R. J. Gutierrez6, Karl V. Miller8, James D. Nichols9, Neal D. Neimuth10, David Otis4, Christine A. Ribic11, Mary M. Rowland12, Terry L. Shaffer13 1 USGS, Northern Prairie Wildlife Research Center, Dept. of Fisheries, Wildlife and Conservation Biology, University of Minnesota 2 Mammals Research Section, Colorado Parks and Wildlife 3 Division of Wildlife and Forestry, Tennessee Wildlife Resource Agency 4 Dept. of Fisheries, Wildlife and Conservation Biology, Colorado State University 5 Dept. of Natural Resources and the Environment, Cornell University 6 Dept. of Fisheries, Wildlife and Conservation Biology, University of Minnesota 7 USDA/APHIS/WS National Wildlife Research Center 8 Warnell School of Forestry and Natural Resources, University of Georgia 9 U.S. Geological Survey, Eastern Ecological Science Center 10 U.S. Fish and Wildlife Service, Habitat and Population Evaluation Team 11 U.S. Geological Survey, Wisconsin Cooperative Wildlife Research Unit, Department of Forest and Wildlife Ecology, University of Wisconsin 12 U.S. Forest Service, Pacific Northwest Research Station 13 U.S. Geological Survey, Northern Prairie Wildlife Research Center Citation: Johnson, D. H., C. Anderson Jr., R. D. Applegate, L. Bailey, E. Cooch, J. Fieberg, A. B. Franklin, R. J. Gutierrez, K. V. Miller, J. D. Nichols, N. D. Niemuth, D. Otis, C. A. Ribic, M. M. Rowland, and T. L. Shaffer. 2021. Editorial Message: A perspective on the Journal of Wildlife Management. Journal of Wildlife Management 85:1305–1308; DOI: 10.1002/jwmg.22110 CONCLUSIONS A first principle of marketing a product, such as a journal, is identifying its target audience. Historically JWM was oriented toward on‐the‐ground and harvest managers. We suspect that over the years the journal has become more read by researchers and students and less used by actual managers. An argument could be made in favor of changing its title to the Journal of Wildlife Science, but much history would be lost causing a reset in the impact factor rating. We believe that both audiences can be served, but it will not be easy. Collectively, our group offers a wide set of perspectives stemming from our personal experiences publishing in many journals including JWM, but we certainly do not reflect the entire spectrum of members of TWS. Therefore, we offer the following conclusions in support of our general comments above (refer to publication) with the expectation that others may either endorse our ideas or refute them. All of us have long held high regard for our society's primary journal. Yet we also believe that JWM could be improved. Some of our suggestions are easily implemented (e.g., focus more on facilitating author submissions than on the format of papers—layout and format of a journal are never as important as its content); others will be more challenging (e.g., deciding if the focus of JWM should be on game species because other journals provide more options to publish nongame research). In TWS, a possible way forward is for leadership to assess whether new directions in emphasis for JWM are warranted. But even if new directions are desired, given a more thorough evaluation than we have provided, we believe there is a perception among many potential authors that structural impediments discourage submission to JWM. Therefore, we hope our comments are taken in the context with which we wrote them: to improve the quality and stature of JWM. All decisions, including any recommended changes to JWM, should be guided by objectives. For example, if our primary objective is to increase the impact factor of JWM, then we might take certain actions, whereas if we want to increase the value of JWM to managers we might do something very different. If we prefer a compromise that includes both objectives, perhaps unequally weighted, then our actions would again differ from those that focus only on one of them. We believe that any recommendations for changes to JWM must be preceded by a clear statement of what we would like these changes to accomplish. We authors differ in our opinions about the importance of journal impact factor, with some of us concerned that it is too low and others believing that it does not closely relate to the use of the journal. This variation suggests that the TWS membership should be involved in developing the objectives that are required to guide decisions about any changes to JWM. Published Sept. 2021 52 ���� https://cpw.cvlcollections.org/files/original/a3a28208dd3511682705f9cd999949bf.pdf fc1c5562a8ae9252db507ffc729a4e8d PDF Text Text C O L O R A D O P A R K S & W I L D L I F E Wildlife Research Reports MAMMALS – JANUARY 2023 cpw.state.co.us �__________________________________________ Copies of this publication may be obtained from Colorado Parks and Wildlife Research Library 317 West Prospect, Fort Collins, CO 80526 �WILDLIFE RESEARCH REPORTS JULY 2021–DECEMBER 2022 MAMMALS RESEARCH PROGRAM COLORADO PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). By providing these summaries, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. i �EXECUTIVE SUMMARY This Wildlife Research Report represents summaries (≤5 pages each with tables and figures) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) during 2021 and 2022. These research efforts represent long-term projects (4–11 years) in various stages of completion addressing applied questions to benefit the management and conservation of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx or from the project principal investigators listed at the beginning of each summary. Current research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to habitat alterations, human-wildlife interactions, and investigating improved approaches for wildlife population monitoring and management. The Nongame Mammal Conservation Section addresses ongoing monitoring of lynx in the San Juan mountain range and preliminary results addressing influence of forest management practices on snowshoe hare density in Colorado. The Ungulate Management and Conservation Section includes a project addressing mule deer/energy development interactions to inform future development planning, a pilot evaluation of moose behavioral response to recent wolf-pack establishment in North Park, Colorado, an evaluation of factors influencing elk calf recruitment, and two studies addressing elk response to human recreation. The Predatory Mammals Management and Conservation Section describes a pilot research project developing longer-term research to address bobcat population demographics and improved monitoring approaches. In addition to the ongoing project summaries described above, Appendix A includes final results presented to U.S. Bureau of Land Management addressing development of a spatial energy development planning tool to guide mule deer management on winter range. Appendix B includes publication abstracts (<1 page summaries) completed by CPW research staff since July 2021. These scientific publications provide results from recently completed CPW research projects and other collaborations with universities and wildlife management agencies. Topics addressed include nongame species ecology and conservation (application of joint species distribution models and a comparison of Canada lynx distribution pre and post spruce beetle outbreak), carnivore ecology and management (literature review related to common management questions associated with human-cougar interactions, an evaluation of human impact on movement and habitat use by male brown bears, and 3 publications addressing wolf-disease/parasite relationships), ungulate ecology and management (applying memory covariates to enhance assessment of mule deer habitat use patterns, addressing the influence of willow nutrition on moose calving rates, 2 publications addressing CWD status and data standardization for white-tailed deer management, factors influencing elk productivity and recruitment, and plant and mule deer responses to 3 mechanical treatment methods), university collaborations addressing wildlife genetics and disease research (characteristics of anelloviruses in domestic and wild cat species, and reconstructing viral phylogenies from commonly collected mountain lion tooth samples), and a Journal of Wildlife Management editorial evaluating the journal from established career scientists to provide suggestions for future improvement. We have benefitted from numerous collaborations that support these projects and the opportunity to work with and train wildlife technicians and graduate students that will likely continue their careers in wildlife management and ecology in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, Montana State University, University of Wyoming, Southern Illinois University, U.S. Bureau of Land Management, U.S. Forest Service, CPW big game auction-raffle grants, Species Conservation Trust Fund, Great Outdoors Colorado, CPW Habitat Partnership Program, Rocky Mountain Elk Foundation, Colorado Mule Deer Association, The Mule Deer Foundation, Muley Fanatic Foundation, EnCana Corp., ExxonMobil/XTO Energy, Marathon Oil, Shell Exploration and Production, WPX Energy, and numerous private land owners providing access to support field research projects. ii �STATE OF COLORADO Jared Polis, Governor DEPARTMENT OF NATURAL RESOURCES Dan Gibbs, Executive Director PARKS AND WILDLIFE COMMISSION Carrie Besnette Hauser, Chair............................................................................................Glenwood Springs Dallas May, Vice Chair. ........................................................................................................................ Lamar Marie Haskett, Secretary ..................................................................................................................... Meeker Charles Garcia ..................................................................................................................................... Denver Taishya Adams… ............................................................................................................................... Boulder Karen Michelle Bailey ....................................................................................................................... Boulder Betsy Blecha…....................................................................................................................................... Wray Gabriel Otero1 ................................................................................................................................................................................................................. Fruita Luke B. Schafer ...................................................................................................................................... Craig Duke Phillips IV .................................................................................................................. Colorado Springs Richard Reading2 .......................................................................................................................................................................................................Denver James Jay Tutchton…............................................................................................................................. Hasty Eden Vardy............................................................................................................................................ Aspen Kate Greenberg, Dept. of Agriculture, Ex-officio.............................................................................. Durango Dan Gibbs, Executive Director, Ex-officio .......................................................................................... Denver 1 Replaced Commissioner Garcia July 2022 2 Replaced Commissioner Schafer July 2022 DIRECTOR’S LEADERSHIP TEAM Heather Dugan, Acting Director Reid DeWalt, Justin Rutter, Jeff Ver Steeg, Lauren Truitt, Cory Chick, Mitchell Martin, Travis Black, Mark Leslie, Kristin Cannon, Rebecca Ferrell, Ty Petersburg MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Wildlife Researcher Eric Bergman, Wildlife Researcher Ellen Brandell, Wildlife Researcher Shane Frank, Wildlife Researcher Michelle Gallagher, Program Assistant Karen Hertel, Research Librarian Jake Ivan, Wildlife Researcher Eric Newkirk, Database Manager/Analyst Nathaniel Rayl, Wildlife Researcher iii �TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS NONGAME MAMMAL CONSERVATION CANADA LYNX MONITORING IN COLORADO 2020-2021 by E. Odell, M. Hertel, and J. Ivan................................................................................................................................................... 2 CANADA LYNX MONITORING IN COLORADO 2021-2022 by E. Odell, M. Hertel, and J. Ivan................................................................................................................................................... 8 INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO by J. Ivan and E. Newkirk ..... 14 UNGULATE MANAGEMENT AND CONSERVATION POPULATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORTS TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGRADATION by C. Anderson ................................ 18 PILOT EVALUATION OF PREY DISTRIBUTION AND MOOSE RECRUITMENT FOLLOWING EXPOSURE TO WOLF PREDATION RISK IN NORTH PARK, COLORADO by E. Bergman and E. Brandell ...................................................................................................... 23 EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO by N. Rayl, M. Alldredge, and C. Anderson ............................................................................................ 25 RESPONSE OF ELK TO HUMAN RECREATION AT MULTIPLE SCALES: DEMOGRAPHIC SHIFTS AND BEHAVIORALLY MEDIATED FLUCTUATIONS IN ABUNDANCE by E. Bergman and N. Rayl .................................................................................. 30 SPATIOTEMPORAL EFFECTS OF HUMAN RECREATION ON ELK BEHAVIOR: AN ASSESSMENT WITHIN CRITICAL TIME STAGES by N. Rayl, E. Bergman, and J. Holbrook ........................................................................................................................................ 33 PREDATORY MAMMAL MANAGEMENT AND CONSERVATION BOBCAT POPULATION DENSITY ESTIMATION: A PILOT STUDY by S. Frank, J. Ivan, M. Vieira, M. Alldredge, and J. Runge ................................................................................................ 37 APPENDIX A. FINAL REPORT TO BLM: Developing a spatial planning tool for natural gas development on mule deer winter range ................................................................................................. 39 APPENDIX B. MAMMALS RESEARCH PUBLICATION ABSTRACTS NONGAME MAMMAL ECOLOGY AND CONSERVATION .................................................. 54 CARNIVORE ECOLOGY AND MANAGEMENT ..................................................................... 55 UNGULATE ECOLOGY AND MANAGEMENT ....................................................................... 58 iv �WILDLIFE GENETICS AND DISEASE RESEARCH ................................................................ 62 JOURNAL OF WILDLIFE MANAGEMENT EDITORIAL… .................................................... 64 v �NONGAME MAMMAL CONSERVATION CANADA LYNX MONITORING IN COLORADO 2020-2021 CANADA LYNX MONITORING IN COLORADO 2021-2022 INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO 1 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Canada lynx monitoring in Colorado 2020 – 2021 Period Covered: July 1, 2020 − June 30, 2021 Principal Investigators: Eric Odell, Eric.Odell@state.co.us; Morgan Hertel, Morgan.Hertel@state.co.us; Jake Ivan, Jake.Ivan@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success and that the population of Canada lynx in the state was apparently viable and self-sustaining. In order to track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is required. From 2014−2021 CPW initiated a portion of the statewide monitoring scheme described in Ivan (2013) by completing surveys in a random sample of monitoring units (n = 50) from the San Juan Mountains in southwest Colorado (n = 179 total units; Figure 1). During the 2020−2021 winter, personnel from CPW and USFS completed the seventh year of monitoring work on this same sample. Fourteen units were sampled via snow-tracking surveys conducted between December 1 and March 31. On each of 1–3 independent occasions, survey crews searched roadways (snow-covered paved roads and logging roads) and trails for lynx tracks. Crews searched the maximum linear distance of roads possible within each survey unit given safety and logistical constraints. Each survey covered a minimum of 10 linear kilometers (6.2 miles) distributed across at least 2 quadrants of the unit. The remaining 36 units could not be surveyed via snow tracking. Instead, survey crews deployed 4 passive infrared motion cameras in each of these units during fall 2020. Cameras were lured with visual attractants and scent lure to enhance detection of lynx in the area. Cameras were retrieved during summer or fall 2021 and all photos were archived and viewed by at least 2 observers to determine species present in each. Camera data were then binned such that each of 10 15-day periods from December 1 through April 30 was considered an ‘occasion,’ and any photo of a lynx obtained during a 15-day period was considered a ‘detection’ during that occasion. Surveyors covered 744 km during snow tracking surveys and detected lynx at 7 units (Table 1). In 2020-21 surveyors collected more DNA samples than in previous years, likely because new environmental DNA (eDNA) sampling is more efficient to collect than the previous scat or hare sampling. As in 2019-20, significantly more photos were collected in 2020-21 than in the first 5 seasons of sampling. This can be mostly attributed to the use of new, more sensitive cameras along with new, highcapacity memory cards. However, for the fourth year in a row, we collected <50% of the number of lynx photos taken during the initial years of the monitoring effort (Table 2). In fact, the 36 lynx photos collected during the 2019-20 and 2020-21 seasons are the fewest recorded since the inception of the project. We initially considered at least 3 possible explanations for the lack of photos collected in recent years. First, we hypothesized that abnormal snow patterns (lack of snow in 2017–18, record snow in 2018–19) could have impacted detection probability. Second, lack of detections could have been due to 2 �the new lure (Caven’s Violator 7; Minnesota Trapline Products, https://www.minntrapprod.com/Bobcatand-Lynx/products/829/) we used in 2017–18, 2018–19, 2019-20, and 2020-21 after the lure we used previously (Pikauba; Luerres Forget’s Lures, http://www.leurresforget.com/product.php?id_product=15) became unavailable. Finally, it could be that lynx have disappeared from a number of camera units. Unfortunately, the changes in snow and lure were confounded for a few years, thus making it difficult to determine which factor resulted in fewer detections. However, 2019-20 and 2020-21 were normal snow years, yet the number of lynx photos was still low. This suggests that abnormal snow was not the cause of the pattern we observed. Also, the number of snow tracking units with lynx has remained fairly steady throughout the project; we can think of no reason why snow track units would remain occupied while lynx blinked out of camera units, unless just by chance. Thus, we suggest that the new lure is less effective than the original. Fortunately the original formulation, Pikauba, is again available and will be deployed for the 2021-22 survey. We plan to utilize this lure for the remainder of the survey efforts, provided it remains available. We obtained lynx detections for the first time in a unit near Mesa Mountain in the La Garitas. This detection represents the northernmost detection of lynx since surveys began. We also detected lynx for the first time in the unit that encompasses Fern Creek and lower Trout Creek west of Creede. This unit, however, is surrounded by other units where lynx have been detected several times previously. After a 1-year absence, lynx were again detected in the Barlow Creek Unit near Rico and the Pass Creek Unit near Wolf Creek Pass; lynx were not detected at the two units adjacent to Pass Creek, or at the southern Conejos Peak Unit after having been detected in all 3 last year (Figure 1). We used the R (R Development Core Team 2018) package ‘RMark’ (Laake 2018) to fit multipleseason (i.e., “dynamic”) occupancy models (MacKenzie et al. 2006) to our survey data using program MARK (White and Burnham 1999). Thus, we estimated the derived probability of a unit being occupied (i.e., used) by lynx over the course of the winter (ψ), along with the probability of detecting a lynx (p) given that the unit was occupied, the probability a unit that was unused in one year was used the next (i.e., “local colonization,” γ), and the probability a used unit became unused from one year to the next (i.e., “local extinction,” ε). For each model we fit for the analysis, we specified that the initial ψ in the time series should be a function of the proportion of the unit that is covered by spruce/fir forest – the single most important and consistent predictor of ψ in past analyses. For sake of comparison we fit a base model in which p was specified to be constant for the duration of the survey. Based on previous work, however, we considered several other structures for p we anticipated would fit better. We fit models that specified 1) p could vary by survey method (i.e., detection could be different for cameras compared to snowtracking), 2) p could be higher during breeding season when lynx tend to move more and are therefore more likely to be detected by track or at a camera, and 3) p for cameras deployed from 2017–21 could be different than p for other years due to the lure substitution. Additionally we fit a model in which the effect of breeding season was only allowed to act on cameras, not snowtracking. We allowed annual estimates of ε and γ to be different each year (i.e., assuming occupancy dynamics were not random but instead dependent on the year previous and the population is not at equilibrium), which allowed derived ψ to vary as freely as possible given the data. We used Akaike’s Information Criterion (AIC), adjusted for small sample size (Burnham and Anderson 2002) to identify the best-fitting model from this small set. Ultimately, we fit a linear model through the time series of ψ estimates to estimate the slope of the trend in occupancy through time. Ideally we would test other predictions of lynx occupancy to see, for instance, if colonization or extinction were influenced by bark beetles, fire, or the presence of competitors or prey species. However, we do not currently have enough data to test these predictions in addition to assessing trend, which is the highest priority. As has been the case since the inception of our monitoring program, the proportion of the sample unit covered by spruce-fir forest was significantly and positively associated with the initial occupancy estimate in the time series. Even though local colonization and extinction were allowed to vary freely from year to year, annual estimates were near zero and varied little (ε = 0.00–0.08; γ = 0.00–0.10). Accordingly, derived occupancy was relatively stable across years (ψ = 0.26–0.38). The slope of the trend 3 �in occupancy through time was slightly positive but not significantly different from zero (β = 0.017, SE = 0.01; Figure 2). These results suggests that future analyses may benefit from fitting models that hypothesize occupancy is at or near equilibrium and extinction/colonization are either Markovian (as modeled here) or possibly zero. Similar to previous years, detection probability was relatively high for snow tracking surveys (p = 0.69, SE = 0.06), lower for camera surveys (p = 0.23, SE = 0.03) using Pikauba, and lowest for camera surveys utilizing Violator 7 (p = 0.06, SE = 0.02). We estimated that 38% of the sample units in the San Juan’s were occupied by lynx (95% confidence interval: 20–55%) during 2020–21 (Figure 2). The spatial distribution of lynx in the San Juan mountains remained largely unchanged (Figure 1). Table 1. Summary statistics from snow tracking effort. Lynx DNAb 8 6 Km Surveyed (Total) 884 987 Mean Km Surveyed per Visit 20.1 21.9 #CPW Personnelc 30 23 #USFS Personnelc 13 6 Season 2014–2015 2015–2016 #Units Surveyed 18 17 #Units with Lynx 7 7 2016–2017 16 8 13 7 5 703 18.0 20 8 2017–2018 14 7 9 3 1 578 19.3 14 5 2018–2019 14 6 8 2 1 510 19.6 16 5 2019–2020 14 7 11 3 2 640 19.4 15 3 2020–2021 15 9 14 12 7 790 18.8 17 3 #Lynx Tracks 12 14 #Genetic Samplesa 8 9 Number of genetic samples (scat, hair, or eDNA) collected via backtracking putative lynx tracks b Number of genetic samples that came back positive for Lynx c Number of staff that participate in the annual sampling effort a Table 2. Summary statistics from camera effort. Season 2014–2015 2015–2016 #Units Surveyed 31 31 2016–2017 33 2017–2018 35 2018–2019 35 2019–2020 36 2020–2021 35 #Units With Lynx #Photos (Total) #Photos (Lynx) #Cameras With Lynx 7 7 6 5 6 4 3 133,483 101,534 168,705 173,279 201,782 706,074 347,868 184 455 251 90 59 36 36 11 10 10 8 9 4 3 4 #CPW Personnel 46 33 #USFS Personnel 12 9 29 9 35 8 31 7 29 6 23 5 �a) b) Figure 1. Lynx monitoring results for a) the current sampling season (2020–2021) and b) the cumulative monitoring effort (2014–2021), San Juan Mountains, southwest Colorado. Colored units (n = 50) depicted here are those selected at random from the population of units (n = 179) encompassing lynx habitat in the San Juan Mountains. Lynx were detected in 12 units in 2020−2021 and 24 units cumulatively since monitoring began in 2014−2015. 5 �Figure 2. Occupancy estimates (Ψ) and trend (including 95%CI) for Canada lynx in the San Juan Mountains, southwest Colorado. ERRATA: We note here that some data in Tables 1 and 2, and Figure 1 are incongruent with reports issued for the previous two seasons. This was due to inadvertent removal of filters in our database that were originally set to exclude pilot data from report tables, figures, and input files. These filters have been restored. The cumulative tables and figures presented here are accurate and supersede discrepancies with previous reports. Literature Cited Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York, New York, USA. Ivan, J. S. 2013. Statewide monitoring of Canada lynx in Colorado: evaluation of options. Pages 15–27 in Wildlife research report: Mammals. Colorado Parks and Wildlife., Fort Collins, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx. Laake, J. L. 2018. Package “RMark”: R Code for Mark Analysis. Version 2.2.5. https://cran.rproject.org/web/packages/RMark/RMark.pdf. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. R Development Core Team. 2018. No Title. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplem:120–138. 6 �Appendix 1. Model selection results for lynx monitoring data collected in the San Juan Mountains, Colorado, 2014–2021. Rankings are based on Akaike’s Information Criterion adjusted for small sample size (AICc). We mostly sought to tease out best fitting models for detection, allowing constant detection (.), along with effects for survey type (ST), breeding season (B), substituting Violator 7 lure for Pikauba (V), and interactions to allow lure and breeding to act only on cameras. For these models we fixed the initial ψ to be a function of spruce-fir forest while local extinction (ε) and colonization (γ) were estimated annually to allow for non-equilibrium estimates in ψ that depended on previous year’s occupancy state. Post-hoc, we added tested for equilibrium conditions (ε (.) γ (.) ) or that occupancy from year to year was random ({ε = 1- γ}). Model ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST+V+ST*V) ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST+B+V+ST*V) ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST+B+V+ST*B+ST*V) ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST) ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST+B) ψ (Prop Spruce/Fir) ε (.) γ (.) p (.) ψ (Prop Spruce/Fir) ε (t) γ (t) p (.) ψ (Prop Spruce/Fir) {ε = 1- γ}p (1) 7 AICc 674.04 675.88 676.77 697.55 699.41 749.98 768.42 914.99 ∆AICc 0.00 1.85 2.74 23.52 25.38 75.95 94.38 240.95 AICc Wts 0.61 0.24 0.15 0.00 0.00 0.00 0.00 0.00 No. Par. 17 18 19 15 16 4 14 8 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Canada lynx monitoring in Colorado 2021 – 2022 Period Covered: July 1, 2021 − June 30, 2022 Principal Investigators: Eric Odell, Eric.Odell@state.co.us; Morgan Hertel, Morgan.Hertel@state.co.us; Jake Ivan, Jake.Ivan@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success and that the population of Canada lynx in the state was apparently viable and self-sustaining. In order to track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is required. From 2014−2022 CPW initiated a portion of the statewide monitoring scheme described in Ivan (2013) by completing surveys in a random sample of monitoring units (n = 50) from the San Juan Mountains in southwest Colorado (n = 179 total units; Figure 1). During the 2021−2022 winter, personnel from CPW and USFS completed the eighth year of monitoring work on this same sample. Fourteen units were sampled via snow-tracking surveys conducted between December 1 and March 31. On each of 1–3 independent occasions, survey crews searched roadways (snow-covered paved roads and logging roads) and trails for lynx tracks. Crews searched the maximum linear distance of roads possible within each survey unit given safety and logistical constraints. Each survey covered a minimum of 10 linear kilometers (6.2 miles) distributed across at least 2 quadrants of the unit. The remaining 36 units could not be surveyed via snow tracking. Instead, survey crews deployed 4 passive infrared motion cameras in each of these units during fall 2021. Cameras were lured with visual attractants and scent lure to enhance detection of lynx in the area. Cameras were retrieved during summer or fall 2022 and all photos were archived and viewed by at least 2 observers to determine species present in each. Camera data were then binned such that each of 10 15-day periods from December 1 through April 30 was considered an ‘occasion,’ and any photo of a lynx obtained during a 15-day period was considered a ‘detection’ during that occasion. Surveyors covered 692 km during snow tracking surveys and detected only 6 lynx tracks at 4 units, both all-time low for the program (Table 1). Significantly, more photos were collected in the past three seasons than in the first 5 seasons of sampling. This can be mostly attributed to the use of new, more sensitive cameras along with new, high-capacity memory cards. After four seasons (2017-2020) in which we collected the fewest lynx photos of any set of years on the project (<50% of the number of lynx photos taken during the initial years of the monitoring effort), the number of lynx photos collected this year rebounded substantially (Table 2). This substantiates our previous conclusions that the Violator7 lure (in use during those 4 season) was less effective than the Pikauba lure used this year and during the first 3 years of sampling. Pikauba will be utilized for the remainder of the survey efforts, provided it remains available. 8 �We obtained lynx detections in the La Garita Mountains north of Creede for first time in 5 years. Lynx were detected in the two units near Conejos Peak after having not been detected last year. Snowtracking surveys did not provide lynx detections in either the Mineral Creek or Molas Pass units near Silverton, nor at the Lime Creek unit south of Creede. This lack of detections is notable because these 3 units are among the most reliable for detecting lynx in the entire study area; each has provided lynx detections for 6–7 of the 8 years these areas have been surveyed (Figure 1). We used the R package (R Development Core Team 2018) ‘RMark’ (Laake 2018) to fit multipleseason (i.e., “dynamic”) occupancy models (MacKenzie et al. 2006) to our survey data using program MARK (White and Burnham 1999). Thus, we estimated the derived probability of a unit being occupied (i.e., used) by lynx over the course of the winter (ψ), along with the probability of detecting a lynx (p) given that the unit was occupied, the probability a unit that was unused in one year was used the next (i.e., “local colonization,” γ), and the probability a used unit became unused from one year to the next (i.e., “local extinction,” ε). For each model we fit for the analysis, we specified that the initial ψ in the time series should be a function of the proportion of the unit that is covered by spruce/fir forest – the single most important and consistent predictor of ψ in past analyses. For sake of comparison we fit a base model in which p was specified to be constant for the duration of the survey. However, based on previous work, we considered several other structures for p we anticipated would fit better. We fit models that specified 1) p could vary by survey method (i.e., detection could be different for cameras compared to snowtracking), 2) p could be higher during breeding season when lynx tend to move more and are therefore more likely to be detected by track or at a camera, and 3) p for cameras deployed from 2017–21 could be different than p for other years due to the lure substitution. Additionally we fit a model in which the effect of breeding season was only allowed to act on cameras, not snowtracking. We allowed annual estimates of ε and γ to be different each year (i.e., assuming occupancy dynamics were not random but instead dependent on the year previous and the population is not at equilibrium), which allowed derived ψ to vary as freely as possible given the data. We used Akaike’s Information Criterion (AIC), adjusted for small sample size (Burnham and Anderson 2002) to identify the best-fitting model from this small set. Ultimately, we fit a linear model through the time series of ψ estimates to estimate the slope of the trend in occupancy through time. Ideally we would test other predictions of lynx occupancy to see, for instance, if colonization or extinction were influenced by bark beetles, fire, or the presence of competitors or prey species. However, we do not currently have enough data to test these predictions in addition to assessing trend, which is the highest priority. As has been the case since the inception of our monitoring program, the proportion of the sample unit covered by spruce-fir forest was significantly and positively associated with the initial occupancy estimate in the time series. Even though local colonization and extinction were allowed to vary freely from year to year, annual estimates were near zero and varied little (ε = 0.00–0.08; γ = 0.00–0.10) up until the most recent season when extinction probability was high (ε = 0.40, SE = 0.15). Accordingly, derived occupancy was relatively stable across years (ψ = 0.26–0.35), but dropped to the lowest level observed to date this past season (ψ = 0.23, SE = 0.07). The slope of the trend in occupancy through time was zero (β = 0.001, SE = 0.01; Figure 2), indicating stability. Similar to previous years, detection probability was relatively high for snow tracking surveys (p = 0.65, SE = 0.06), lower for camera surveys (p = 0.22, SE = 0.03) using Pikauba, and lowest for camera surveys utilizing Violator 7 (p = 0.06, SE = 0.02). We estimated that 24% of the sample units in the San Juan’s were occupied by lynx (95% confidence interval: 11–37%) during 2021–22 (Figure 2). The broad spatial distribution of lynx in the San Juan’s remained largely unchanged with the exception of no detection in 3 core snow tracking units where lynx are usually detected (Figure 1). 9 �Table 1. Summary statistics from snow tracking effort. Lynx DNAb 8 6 Km Surveyed (Total) 884 987 Mean Km Surveyed per Visit 20.1 21.9 #CPW Personnelc 30 23 #USFS Personnelc 13 6 18.0 20 8 Season 2014-2015 2015-2016 #Units Surveyed 18 17 #Units with Lynx 7 7 2016-2017 16 8 13 7 5 703 2017-2018 14 7 9 3 1 578 19.3 14 5 2018-2019 14 6 8 2 1 510 19.6 16 5 2019-2020 14 7 11 3 2 640 19.4 15 3 2020-2021 15 9 14 12 7 790 18.8 17 3 2021-2022 13 4 6 5 4 692 18.7 11 3 #Lynx Tracks 12 14 #Genetic Samplesa 8 9 Number of genetic samples (scat, hair, or eDNA) collected via backtracking putative lynx tracks b Number of genetic samples that came back positive for Lynx c Number of staff that participate in the annual effort a Table 2. Summary statistics from camera effort. Season 2014-2015 #Units Surveyed 31 2015-2016 31 2016-2017 33 2017-2018 35 2018-2019 35 2019-2020 36 2020-2021 2021-2022 35 35 #Units With Lynx #Photos (Total) #Photos (Lynx) #Cameras With Lynx 7 7 6 5 6 4 3 5 133,483 101,534 168,705 173,279 201,782 706,074 347,868 576,288 184 455 251 90 59 36 36 116 11 10 10 8 9 4 3 7 10 #CPW Personnel 46 #USFS Personnel 12 33 9 29 9 35 8 31 7 29 6 23 23 5 4 �a) b) Figure 1. Lynx monitoring results for a) the current sampling season (2021–2022) and b) the cumulative monitoring effort (2014–2022), San Juan Mountains, southwest Colorado. Colored units (n = 50) depicted here are those selected at random from the population of units (n = 179) encompassing lynx habitat in the San Juan Mountains. Lynx were detected in 9 units in 2021−2022 and 25 units cumulatively since monitoring began in 2014−2015. 11 �Figure 2. Occupancy estimates (Ψ) and trend (including 95%CI) for Canada lynx in the San Juan Mountains, southwest Colorado. Literature Cited Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd edition. Springer, New York, New York, USA. Ivan, J. S. 2013. Statewide monitoring of Canada lynx in Colorado: evaluation of options. Pages 15–27 in Wildlife Research Report: Mammals. Colorado Parks and Wildlife, Fort Collins, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx. Laake, J. L. 2018. Package “RMark”: R Code for Mark Analysis. Version 2.2.5. https://cran.rproject.org/web/packages/RMark/RMark.pdf. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. R Development Core Team. 2018. No Title. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplem:120–138. 12 �Appendix 1. Model selection results for lynx monitoring data collected in the San Juan Mountains, Colorado, 2014–2022. Rankings are based on Akaike’s Information Criterion adjusted for small sample size (AICc). We mostly sought to tease out best fitting models for detection, allowing constant detection (.), along with effects for survey type (ST), breeding season (B), substituting Violator 7 lure for Pikauba (V), and interactions to allow lure and breeding to act only on cameras. For these models we fixed the initial ψ to be a function of spruce-fir forest while local extinction (ε) and colonization (γ) were estimated annually to allow for non-equilibrium estimates in ψ that depended on previous year’s occupancy state. Post-hoc, we added tested for equilibrium conditions (ε (.) γ (.) ) or that occupancy from year to year was random ({ε = 1- γ}). Model ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST+V+ST*V) ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST+B+V+ST*B+ST*V) ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST+B+V+ ST*V) ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST) ψ (Prop Spruce/Fir) ε (t) γ (t) p (ST+B) ψ (Prop Spruce/Fir) ε (.) γ (.) p (.) ψ (Prop Spruce/Fir) ε (t) γ (t) p (.) ψ (Prop Spruce/Fir) {ε = 1- γ}p (.) 13 AICc 784.65 786.47 786.86 804.81 807.00 859.30 880.01 1038.81 ∆AICc 0.00 1.81 2.21 20.16 22.34 74.64 95.36 254.16 AICc Wts 0.58 0.23 0.19 0.00 0.00 0.00 0.00 0.00 No. Par. 19 21 20 17 18 4 16 9 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Influence of forest management on snowshoe hare density in lodgepole and spruce-fir systems in Colorado Period Covered: July 1, 2021 − June 30, 2022 Principal Investigators: Jake Ivan, Jake.Ivan@state.co.us; Eric Newkirk, Eric.Newkirk@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. Understanding and monitoring snowshoe hare (Lepus americanus) density in Colorado is imperative because hares comprise 70% of the diet of the state-endangered, federally threatened Canada lynx (Lynx canadensis; U.S. Fish and Wildlife Service 2000, Ivan and Shenk 2016). Forest management is an important driver of snowshoe hare density, and all National Forests in Colorado are required to include management direction aimed at conservation of Canada lynx and snowshoe hare as per the Southern Rockies Lynx Amendment (SRLA; https://www.fs.usda.gov/detail/r2/landmanagement/ planning/?cid= stelprdb5356865). At the same time, Forests in the Region are compelled to meet timber production obligations. Such activities may depress snowshoe hare density, improve it, or have mixed effects dependent on the specific activity and the time elapsed since that activity was initiated. Here we describe a sampling scheme to assess impacts of common forest management techniques on snowshoe hare density in both lodgepole pine (Pinus contorta) and spruce-fir (Picea engelmannii – Abies lasiocarpa) systems in Colorado. To select forest stands for sampling, we first used U. S. Forest Service (USFS) spatial data to delineate all spruce-fir and lodgepole pine stands (stratum 1) on USFS land in Colorado, and identified all of the management activities that have occurred in each stand over time. With consultation from the USFS Region 2 Lynx-Silviculture Team and USFS Rocky Mountain Research Station, we then grouped relevant forest management activities (stratum 2) into 4 broad categories: even-aged management, uneven-aged management, thinning, and unmanaged controls. We wanted to assess both the immediate and long-term impacts of management on hare densities. Therefore, when selecting stands for sampling, we took the additional step of binning the date of the most recent management activity into 2decade intervals (i.e., 0-20, 20-40, and 40-60 years before 2018). We then selected a spatially balanced random sample of 5 stands within each combination of forest type × management activity × time interval. This design ensured that we sampled the complete gradient of time since implementation for each management activity of interest in each forest type of interest. There is no notion of “completion date” for unmanaged controls, so we simply sampled 10 randomly selected stands from this combination. Also, uneven-aged lodgepole pine treatments are rare, so we did not sample that combination (Figure 1). During summer 2018, we established n = 50 1-m2 permanent circular plots within each of the stands selected for sampling. Plot locations within each stand were selected in a spatially balanced, random fashion. Technicians cleared and counted snowshoe hare pellets in each plot as they established them. These same plots were re-visited and re-counted during summers 2019 and 2020. In addition to sampling the previously cleared plots from 2018, technicians were able to install plots at 2 more replicate sites for each combination of forest type × management activity × time interval during 2019. Also, a 14 �handful of stands visited in 2019 and 2020 were re-classified or excluded because ground-truthing revealed they did not actually fit in the stratum for which they were selected. New stands were sampled in their place by pulling the next one from the spatially balanced list. Similarly, a handful more stands were replaced during the 2021 field season, and 12 new stands were selected to replace those that burned during the 2020 fire season. Currently, inference is based on n = 130 total stands. Finally, in 2021 and 2022, we sampled vegetation metrics in each stand that will hopefully account for the considerable noise we have observed (highly variable results for some strata) and allow us to better assess the effects of the treatments themselves. Pellet information from cleared plots is more accurate than that from uncleared plots because uncleared plots usually include pellet accumulation across several years (Hodges and Mills 2008). The degree to which previous years are represented can depend on local weather conditions, site conditions at the plot, and variability in actual snowshoe hare density over previous winters. Data from cleared plots necessarily reflects hare activity from the previous 12 months, and tracks true density more closely. Therefore, we focused the current analysis on the 2019–22 data from previously cleared plots. For each forest type × management activity combination, we plotted mean pellet counts against “year since activity,” then fit a curve (e.g., quadratic function) through the data (Figure 2). Results from this preliminary analysis suggest that on average the highest snowshoe hare densities typically occur in unmanaged spruce-fir forests, and that unmanaged spruce-fir forests are estimated to have twice the relative hare density of unmanaged lodgepole pine forests (Figure 2). For both forest types, the fitted line suggests that even-aged management (e.g., clearcutting), immediately depresses relative hare density to near zero, but density rebounds and peaks 20-40 years after management before declining again 40-60 years after. Estimated peak hare densities after even-aged management in lodgepole systems tend to be higher than the control condition. However, in spruce-fir systems the estimated fitted line is flatter and peak densities fell short of the control condition. In both forest types, thinning (which often occurs 20-40 years after stands undergo even-aged management, especially in lodgepole) immediately depresses hare densities. In spruce-fir stands, densities were estimated to slowly recover through time in nearly linear fashion. However, they follow a peaked response in lodgepole pine, similar to the response to even-aged management. Uneven-aged management of spruce-fir forests results in immediate depression of relative hare density, which then recovers back to pre-treatment levels approximately 30 years after the treatment. Literature Cited: Hodges, K. E., and L. S. Mills. 2008. Designing fecal pellet surveys for snowshoe hares. Forest Ecology and Management 256:1918-1926. Ivan, J. S., and T. M. Shenk. 2016. Winter diet and hunting success of Canada lynx in Colorado. The Journal of Wildlife Management 80:1049-1058. U.S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: determination of threatened status for the contiguous U. S. distinct population segment of the Canada lynx and related rule, final rule. Federal Register 65:16052–16086. 15 �Figure 1. Location of all stands (n = 130) resampled for snowshoe hare pellets, June-September 2022. Figure 2. Fitted quadratic function (white line) and 95% CI (shaded polygon) relating pellet counts (i.e., relative snowshoe hare density) to time elapsed since treatment for each forest type × management activity combination. Dotted lines indicate the mean pellets/plot for the unmanaged controls for each forest type. 16 �UNGULATE MANAGEMENT AND CONSERVATION POPUATION PERFORMANCE OF PICEANCE BASIN MULE DEER IN RESPONSE TO NATURAL GAS RESOURCE EXTRACTION AND MITIGATION EFFORT TO ADDRESS HUMAN ACTIVITY AND HABITAT DEGREDATION PILOT EVALUATION OF PREY DISTRIBUTION AND MOOSE RECRUITMENT FOLLOWING EXPOSURE TO WOLF PREDATION RISK IN NORTH PARK, COLORADO EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO RESPONSE OF ELK TO HUMAN RECREATION AT MULTIPLE SCALES: DEMOGRAPHIC SHIFTS AND BEHAVIORALLY MEDIATED FLUCTUATIONS IN ABUNDANCE SPATIOTEMPORAL EFFECTS OF HUMAN RECREATION ON ELK BEHAVIOR: AN ASSESSMENT WITHIN CRITICAL TIME STAGES 17 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation Period Covered: July 1, 2021 − December 30, 2022 Principal Investigator: C. R. Anderson, Jr. Personnel: D. Bilyeu-Johnston, CPW; M. Bonar, R. Marrotte J. Northrup, Trent University, Peterborough, Ontario, Canada; B. Gerber, University of Rhode Island; G. Wittemyer, Colorado State University. Project support received from Federal Aid in Wildlife Restoration, Bureau of Land Management, Colorado Mule Deer Association, Colorado Mule Deer Foundation, Muley Fanatic Foundation, Colorado State Severance Tax Fund, Caerus Oil and Gas LLC, EnCana Corp., ExxonMobil Production Co./XTO Energy, Marathon Oil Corp., Shell Petroleum, Williams and WPX Energy. All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. We propose to experimentally evaluate winter range habitat treatments and human-activity management alternatives intended to enhance mule deer (Odocoileus hemionus) populations exposed to energy-development activities. The Piceance Basin of northwestern Colorado was selected as the project area due to ongoing natural gas development in one of the most extensive and important mule deer winter and transition range areas in Colorado. The data presented here represent preliminary and final results of a 10-year research project addressing habitat improvements as mitigation and evaluation of deer responses to energy development activities to inform future development planning options on important seasonal ranges. From 2008 – 2019, we monitored deer on 4 winter range study areas representing relatively high (Ryan Gulch, South Magnolia) and low (North Magnolia, North Ridge) levels of development activity (Figure 1) to address factors influencing deer behavior and demographics and to evaluate success of habitat treatments as a mitigation option. We recorded adult female habitat use and movement patterns; estimated neonatal, overwinter fawn and annual adult female survival; estimated annual early and late winter body condition, pregnancy and fetal rates of adult females; and estimated annual mule deer abundance among study areas. Winter range habitat improvements completed spring 2013 resulted in 604 acres of mechanically treated pinion-juniper/mountain shrub habitats in each of 2 treatment areas (Figure 2) with minor (North Magnolia) and extensive (South Magnolia) energy development, respectively. During this research segment, we developed an energy development planning tool to guide future energy development on mule deer winter range (Marrotte et al. 2022, Appendix A), and finalized 2 publications evaluating the influence of memory in mule deer habitat selection and site fidelity (Rheault et al. 2021, Appendix B) and addressing vegetation and mule deer responses to 3 mechanical treatment methods (Johnston and Anderson, in press, Appendix B). Results for this 11-year project (see Anderson 2021 for methods and previous publication abstracts) suggest: (1) annual adult female survival was consistent among areas averaging 79-87% annually, but overwinter fawn survival was variable, ranging from 31% to 95% within study areas, with annual and study area differences primarily due to early winter 18 �fawn condition, annual weather conditions, and factors associated with predation on winter range; (2) mule deer body condition early and late winter was generally consistent within areas, with higher variability among study areas early winter, primarily due to December lactation rates, and late winter condition related to seasonal moisture and winter severity; (3) late winter mule deer densities increased through 2016 in all study areas, ranging from 50% in North Ridge to 103% in North Magnolia, but have stabilized recently in 3 of the 4 study areas with recent decline evident in North Ridge (Figure 3); (4) migratory mule deer selected for areas with increased cover and increased their rate of travel through developed areas, and avoided negative influences through behavioral shifts in timing and rate of migration, but did not avoid development structures (Figure 4); (5) mule deer exhibited behavioral plasticity in relation to energy development, without evidence of demographic effects, where disturbance distance varied relative to diurnal extent and magnitude of development activity (Figure 5), which provide for useful mitigation options in future development planning; (6) energy development activity under existing conditions did not influence pregnancy rates, fetal rates or early fawn survival (0-6 months), but may have reduced fetal survival (March until birth) during 2012 when drought conditions persisted during the third trimester of doe parturition (Figure 6); and (7) mule deer use of treatment sites appears related to a combination of hiding cover, resulting from residual woody debris, and winter forage. Roller‐chopped plots provide the best combination of hiding cover and winter forage, but mastication or chaining, applied leaving dispersed security cover, may be better options at large scales or when invasive species concerns exist. Literature Cited: Anderson, C. R., Jr. 2021. Population performance of Piceance Basin mule deer in response to natural gas resource extraction and mitigation efforts to address human activity and habitat degradation. Federal Aid in Wildlife Restoration Annual Report W-243-R4, Ft. Collins, CO USA. Johnston, D. B., and C. R. Anderson Jr. 2023. Plant and mule deer responses to pinyon-juniper removal by three mechanical treatment methods. Wildlife Society Bulletin, In press; DOI: 10.1002/wsb.1421 Marrotte, R. R., C. R. Anderson Jr. and J. M. Northrup. 2022. Developing a spatial planning tool for natural gas development on mule deer winter range. Final Report to Bureau of Land Management: Grant Agreement L18AC00068. 14pp. Rheault, H, C. R Anderson Jr, M. Bonar, R. R. Marrotte, T. R. Ross, G. Wittemyer and J. M. Northrup. 2021. Some memories never fade: inferring multi-scale memory effects on habitat selection of a migratory ungulate using step-selection functions. Frontiers in Ecology and Evolution 9.702818; doi: 10.3389/fevo.2021.702818. 19 �Figure 1. Mule deer winter range study areas relative to active natural gas well pads and energy development facilities in the Piceance Basin of northwest Colorado, winter 2013/14 (Accessed http://cogcc.state.co.us/ December 31, 2013; energy development activity has been minor since 2013). Figure 2. Habitat treatment site delineations in 2 mule deer study areas (604 acres each) of the Piceance Basin, northwest Colorado (Top; cyan polygons completed Jan 2011 using hydro-axe; yellow polygons completed Jan 2012 using hydro-axe, roller-chop, and chaining; and remaining polygons completed Apr 2013 using hydro-axe). January 2011 hydro-axe treatment-site photos from North Hatch Gulch during April (Lower left, aerial view) and October, 2011 (Lower right, ground view). 20 �Piceance Basin late winter mule deer density 35.00 30.00 Deer/km2 25.00 20.00 North Ridge 15.00 Ryan Gulch 10.00 North Magnolia 5.00 South Magnolia 0.00 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 Year Figure 3. Mule deer density estimates and 95% CI (error bars) from 4 winter range herd segments in the Piceance Basin, northwest Colorado, late winter 2009–2018. Figure 4. Mule deer study areas in the Piceance Basin of northwestern Colorado, USA (Top), spring 2009 migration routes of adult female mule deer (n = 52; Lower left), and active natural-gas well pads (black dots) and roads (state, county, and natural-gas; white lines) from May 2009 (Lower right; from Lendrum et al. 2012; http://dx.doi.org/10.1890/ES12-00165.1). 21 �Figure 5. Posterior distributions of population-level coefficients related to natural gas development for RSF models during the day (top) and night (bottom) for 53 adult female mule deer in the Piceance Basin, northwest Colorado. Dashed line indicates 0 selection or avoidance (below the line) of the habitat features. ‘Drill’ and ‘Prod’ represent drilling and producing well pads, respectively. The numbers following ‘Drill’ or ‘Prod’ represent the distance from respective well pads evaluated (e.g., ‘Drill 600’ is the number of well pads with active drilling between 400–600 m from the deer location; from Northrup et al. 2015; http://onlinelibrary.wiley.com/doi/10.1111/gcb.13037/abstract). Road disturbance was relatively minor (~60–120 m, not illustrated above). Figure 6. Model averaged estimates of mule deer fetal survival from early March until birth (late May– June) in high and low energy development study areas of the Piceance Basin, northwest Colorado, 2012– 2014 (from Peterson et al. 2017; http://www.bioone.org/doi/pdf/10.2981/wlb.00341). 22 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Pilot evaluation of prey distribution and moose recruitment following exposure to wolf predation risk in North Park, Colorado Period Covered: January 1, 2022 – December 31, 2022 Principal Investigators: Eric Bergman, eric.bergman@state.co.us; Ellen Brandell, ellen.brandell@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. During November 2020, Colorado voters passed Proposition 114 (subsequently codified as Colorado Revised Statue 33-2-105.8), which directed Colorado Parks and Wildlife (CPW) and the CPW Wildlife Commission to develop a gray wolf (Canis lupus) reintroduction and management plan for Colorado by the end of 2023. Wolves are a native species to Colorado and prior to westward European expansion they occurred throughout the Rocky Mountains and into Colorado’s eastern plains (Feldhamer et al. 2003). Since the 1940s, wolf presence in Colorado has been sporadic (Warren 1942, Lechleitner 1969, Armstrong et al. 2011). Beginning in the early 2000s, CPW documented occasional wolf presence in Colorado (Colorado Parks and Wildlife 2021), primarily in North Park. During the summer of 2021, a pack comprised of 2 adults and 6 pups was observed. Between dispersal and reproduction of wolves from neighboring states and reintroductions mandated by Colorado Revised Statute 33-2-105.8, wolves will become a consistent feature on Colorado’s landscape, and specifically in North Park. The return of wolves to Colorado’s landscape has already generated interest in future research projects. Between the 1940s and present day, and largely in the absence of wolves, Colorado’s ungulate prey populations (i.e., elk (Cervus americanus), mule deer (Odocoileus hemionus), and moose (Alces alces)) adapted to many changes. These changes included successional change in vegetation, increases and reductions in competition with other native herbivores and livestock, novel diseases, predation from mountain lions (Felis concolor), black bears (Ursus americanus), and coyotes (Canis latrans), but also increased human activity, human disturbance, and large increases in human infrastructure. Moose experienced deliberate management transplants between the late 1970s (Denney 1976) and mid-2000s. By 2022, Colorado’s moose population was estimated to be 3,000–3,500 animals (Colorado Parks and Wildlife, unpublished data). Similarly, during the 1940s it was believed there were 45,000 elk in Colorado (Swift 1945) and population growth during the next 6–7 decades led to a peak of ~300,000 animals during the late 1990s and early 2000s (CPW, unpublished data). This research is generally focused on predator-prey dynamics and how wolves will influence wild prey. Specifically, this research will measure prey survival, productivity, and distribution. To supplement survival and spatial data collected from moose during 2013–2019 (Bergman 2022), we initiated capture and collaring efforts of cow and calf moose during the winter of 2021–2022. These efforts demonstrated that moose calf abundance and subsequent moose calf density in North Park were insufficient to accommodate the necessary sample size for the initial study design of this project. Historically modeled estimates for the North Park moose herd suggest it is comprised of 600–800 animals. Sex and age distribution data from this herd simultaneously indicate there are ~70 bulls/100 cows and ~52 calves/100 cows, thereby lending evidence that there are ~140–190 calves in North Park. However, it is likely that >50% of these calves reside on private lands during winter, making their access for capture purposes 23 �logistically difficult. Accordingly, there are likely only ~70–95 calves available on public land, of which CPW would need to capture 65%-85% to meet sample size requirements. Capturing such a large proportions of this calf population is both logistically and financially difficult and preliminary efforts in North Park provided evidence that it would be infeasible to capture 60 moose calves each winter. However, capture efforts of cow moose between 2013–2019 (Bergman 2022) and again during the winter of 2021–2022 provided evidence of adequate densities to accommodate robust capturing and collaring efforts, thereby presenting alternative opportunities to estimate calf survival. Advancements in satellite collar technology make it feasible for researchers to attain location data from moose that were collected only a few hours earlier. When coupled with VHF capabilities, researchers have the ability to quickly relocate and observe animals. For the purposes of this study, this technology will allow researchers to observe cow moose, but also observe if cow moose are accompanied by a calf (<12 months old). Repeated observations of cows and calves in this manner, and gathered at key points in time, will allow researchers to approximate calf survival by quantifying the decay in calf/cow ratios from birth to the yearling age class (Lukacs et al. 2004). While these data will not provide causespecific calf mortality estimates, they will improve population models that inform moose ecology and harvest management decision making for the North Park moose herd. To implement this alternative approach to estimating calf survival, a total of 80 cow moose will be collared in North Park. Approximately 65 additional collars will be deployed during winter of 2022– 2023. Collars will be deployed in a spatially balanced manner, with 40 collars on both the northern and southern halves of North Park. To expand this research to include additional prey species, 40 cow elk will be captured and collared during the winter of 2022–2023. Once available for observation, these elk will serve as sentinel animals that will allow researchers to quantify group size behavior, spatial distribution, and habitat use, relative to any known wolf activity. Data collected from cow moose during 2022 did not deviate from data collected during 2013– 2019. Between 2012–2022 survival of cow moose ranged from 91.2%–94.8%. During the same period, pregnancy rates of moose ranged from 54.8%–88.0. Literature Cited: Armstrong, D. M., J. P. Fitzgerald, and C. A. Meaney. 2011. Mammals of Colorado (2nd Edition). University Press of Colorado, Boulder, USA. Bergman, E. J. 2022. Incorporation of moose life history traits, nutritional status, and browse characteristics in Shiras moose management in Colorado. Federal Aid in Wildlife Restoration Annual Report W-245-R4, Ft. Collins, CO USA. Denney, R. N. 1976. A Proposal for the Reintroduction of Moose into Colorado. Colorado Parks and Wildlife, Ft. Collins, USA. Feldhamer, G.A., B.C. Thompson, and J.A. Chapman. 2003. Wild mammals of North America: biology, management, and conservation. Johns Hopkins University Press, Baltimore, MD, USA. Lechleitner, R. R. 1969. Wild mammals of Colorado: their appearance, habits, distribution, and abundance. Pruett Publishing, Boulder, CO, USA. Lukacs, P. M., V. J. Dreitz, F. L. Knopf, and K. P. Burnham. 2004. Estimating survival probabilities of unmarked dependent young when detection is imperfect. Condor 106:926–931. Swift, L. W. 1945. A partial history of the elk herds of Colorado. Journal of Mammalogy 26:114–119. Warren, E. R. 1942. The mammals of Colorado: their habits and distribution (2nd Edition). University of Oklahoma Press, Norma, USA. 24 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluating factors influencing elk recruitment in Colorado Period Covered: January 1, 2022 – December 31, 2022 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Mat Alldredge, mat.alldredge@state.co.us; Chuck Anderson chuck.anderson@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In Colorado, elk (Cervus canadensis) are an important natural resource that are valued for ecological, consumptive, aesthetic, and economic reasons. In 1910, less than 1,000 elk remained in Colorado (Swift 1945), but today the state population is estimated to be the largest in the country, with more than 290,000 elk. Over the last two decades, however, wildlife managers in Colorado have become increasingly concerned about declining winter elk calf recruitment (estimated using juvenile/adult female ratios) in the southern portion of the state. Although juvenile/adult female ratios are often highly correlated with juvenile elk survival, they are an imperfect estimate of recruitment because they are affected by harvest, pregnancy rates, juvenile survival, and adult female survival (Caughley 1974, Gaillard et al. 2000, Harris et al. 2008, Lukacs et al. 2018). Thus, there is a need for elk research in Colorado based upon monitoring of marked individuals to evaluate factors affecting each stage of production and survival. In 2016, we began a study to investigate factors influencing elk recruitment in 2 elk Data Analysis Units (DAUs; E-20, E-33) with low juvenile/adult female ratios (Figure 1). In 2019, we expanded this study into a 3rd DAU with high juvenile/adult female ratios (E-2), to better determine how predators, habitat, and weather conditions are impacting elk recruitment in Colorado (Figure 2). In 2021, we concluded collaring efforts in E-33. Since study initiation, we have collared 434 pregnant females in February-March, 702 neonates in May-August, and 196 6-month old calves in December (Table 1). Averaged across years, we estimated that the annual pregnancy rate of adult female elk was 93% in the Bear’s Ears herd (excluding 2019 data where n = 3; range = 91-95%), 91% in the Trinchera herd (range = 78-96%), and 91% (range = 81-97%) in the Uncompahgre Plateau herd (Figure 3). Elk populations experiencing good to excellent summerautumn nutrition typically have pregnancy rates ≥90% (Cook et al. 2013). From 2017–2022, we estimated that the mean ingesta-free body fat (IFBF) of adult female elk was 6.90% in the Bear’s Ears Herd, 7.30% in the Trinchera herd, and 7.39% in the Uncompahgre Plateau herd (Figure 4). When late-winter IFBF values are <8-9% for adult female elk that have lactated through the previous growing season, this suggests that there may be nutritional limitations, but it does not identify whether limitations are a result of summer-autumn or winter nutrition (R. Cook, personal communication). Averaged across years, we estimated that the mean date of calving was June 2 in the Bear’s Ears and Trinchera herds, and June 3 in the Uncompahgre Plateau herd (Figure 5). We estimated that the mean weight of 6-month old elk calves was 221 lb (95% CI = 214.6-227.4 lb) from the Bear’s Ears herd and 237.5 lb (95% CI = 231.1-243.9 lb) from the Uncompahgre Plateau elk herd. 25 �Literature Cited: Caughley, G. 1974. Interpretation of age ratios. Journal of Wildlife Management 38:557-562. Cook, R. C., J. G. Cook, D. J. Vales, B. K. Johnson, S. M. McCorquodale, L. A. Shipley, R. A. Riggs, L. L. Irwin, S. L. Murphie, B. L. Murphie, K. A. Schoenecker, F. Geyer, P. B. Hall, R. D. Spencer, D. A. Immell, D. H. Jackson, B. L. Tiller, P. J. Miller, and L. Schmitz. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1-45. Gaillard, J. M., M. Festa-Bianchet, N. G. Yoccoz, A. Loison, and C. Toïgo. 2000. Temporal variation in fitness components and population dynamics of large herbivores. Annual Review of Ecology and Systematics 31:367-393. Harris, N. C., M. J. Kauffman, and L. S. Mills. 2008. Inferences about ungulate population dynamics derived from age ratios. Journal of Wildlife Management 72:1143-1151. Lukacs, P. M., M. S. Mitchell, M. Hebblewhite, B. K. Johnson, H. Johnson, M. Kauffman, K. M. Proffitt, P. Zager, J. Brodie, K. Hersey, A. A. Holland, M. Hurley, S. McCorquodale, A. Middleton, M. Nordhagen, J. J. Nowak, D. P. Walsh, and P. J. White. 2018. Factors influencing elk recruitment across ecotypes in the Western United States. Journal of Wildlife Management 82:698-710. Swift, L. W. 1945. A partial history of the elk herds of Colorado. Journal of Mammalogy 26:114-119. Table 1. The number of elk collared in each age class from the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) herds from 2017-2022. Herd E-2 Bear's Ears Year Adult Neonate E-20 Uncompahgre Plateau 6-month Adult Neonate 2017 23 2018 6-month E-33 Trinchera Adult Neonate 40 22 57 30 48 17 53 2019 2 49 25 30 49 25 30 46 2020 40 54 25 40 52 25 20 21 2021 40 53 25 40 52 25 20 21 2022 40 54 21 40 53 25 26 �Figure 1. The number of elk calves per 100 adult females observed during December-February aerial surveys (5-year average from 2013-2017) within elk Data Analysis Units (DAUs; labeled with black text). Figure 2. The estimated number of calves per 100 adult females observed annually during winter classification surveys in the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) elk herds from 1980-2020 (1992-2020 for the Trinchera herd). Red lines and shaded bands represent linear regression trends with 95% confidence intervals, and indicate an average decrease of 0.56 and 1.05 calves per 100 adult females per year in the Uncompahgre Plateau and Trinchera herds, respectively. 27 �Figure 3. Estimated average pregnancy rates of adult female elk from the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) herds sampled during late winter 20172022. The sample size is given at the top of the 95% binomial confidence intervals (black lines). Figure 4. The estimated ingesta-free body fat (%) of adult female elk with 95% confidence intervals from the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) herds sampled during late winter 2017-2022. 28 �Figure 5. The estimated calving dates of collared female elk from the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) herds from 2017-2022. 29 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Response of elk to human recreation at multiple scales: demographic shifts and behaviorallymediated fluctuations in local abundance Period Covered: January 1, 2022 – December 31, 2022 Principal Investigators: Eric Bergman, eric.bergman@state.co.us; Nathaniel Rayl, nathaniel.rayl@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. This project has objectives on 2 scales. At the broad, elk herd-level scale, we are estimating pregnancy rates, calf survival rates, and cause-specific mortality rates to evaluate the importance of mortality sources for elk calf survival. More specifically, we are evaluating the influence of biotic (birth date, birth mass, gender, maternal body condition, habitat conditions), abiotic (previous and current weather conditions), and human-induced factors (i.e., relative exposure to recreational activities) on seasonal mortality risk of elk calves from birth to age 1 and on pregnancy rates of mature female elk. At the narrower geographic and temporal scale, we are using short-term (~3-4 weeks) changes in elk abundance within small study units (<65 km2 [25 mi2]) as a tool to evaluate the influence of human recreation on elk distribution. At this narrower scale, the primary objective is to evaluate the role that human recreation (e.g., hiking, mountain biking, horseback riding, trail running, hunting, etc.) has on the behavioral distribution of elk on spring calving, summer, and fall transition ranges. Coupled to the objective of detecting behaviorally influenced changes in abundance and density, we are evaluating the effectiveness of current recreational closures maintained by ski areas, counties, and federal land management agencies. From 2019–2022, we have collared 144 pregnant females in March, 184 neonates in May-July, and 100 6-month old calves in December from the Avalanche Creek elk herd (Data Analysis Unit E-15; Table 1). Averaged across years, we estimated the annual pregnancy rate of adult female elk was 91% (95% CI = 85-95%; Fig. 1). Elk populations experiencing good to excellent summer-autumn nutrition typically have pregnancy rates ≥90% (Cook et al. 2013). We estimated that the mean ingesta-free body fat (IFBF) of adult female elk was 7.94 (95% CI = 7.59-8.31%). When late-winter IFBF values are <8-9% for adult female elk that have lactated through the previous growing season, this suggests that there may be nutritional limitations, but it does not identify whether limitations are a result of summer-autumn or winter nutrition (R. Cook, personal communication). Averaged across years, we estimated that the mean date of calving was June 3 (Fig. 2). We estimated that the mean weight of 6-month old elk calves was 247.9 lb (95% CI = 241.7-254.1). During the summer of 2019, a total of 384,455 photos were taken by the 118 cameras deployed across 8 study units. During the summer of 2020, approximately 4.6 million photos were taken by the 238 cameras deployed across 8 study units. These photos are actively being archived. Automated photo recognition software continues to be developed and will be applied to these photos to expedite future analyses. 30 �Literature Cited: Cook, R. C., J. G. Cook, D. J. Vales, B. K. Johnson, S. M. McCorquodale, L. A. Shipley, R. A. Riggs, L. L. Irwin, S. L. Murphie, B. L. Murphie, K. A. Schoenecker, F. Geyer, P. B. Hall, R. D. Spencer, D. A. Immell, D. H. Jackson, B. L. Tiller, P. J. Miller, and L. Schmitz. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1–44. Table 1. The number of elk collared in each age class from the Avalanche Creek elk herd (DAU E-15) from 2019–2022. Age clas s Year Adult Neonate 6-month 2019 24 26 25 2020 40 54 25 2021 40 51 25 2022 40 53 25 Figure 1. Estimated average pregnancy rates of adult female elk from the Avalanche Creek (DAU E-15) herds sampled during late winter 2019–2022. The sample size is given at the top of the 95% binomial confidence intervals (black lines). 31 �Figure 2. The estimated calving dates of collared female elk from the Avalanche Creek (DAU E-15) herd from 2019–2022. 32 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Spatiotemporal effects of human recreation on elk behavior: an assessment within critical time stages Period Covered: January 1, 2022 – December 31, 2022 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Eric Bergman, eric.bergman@state.co.us; Joe Holbrook, Joe.Holbrook@uwyo.edu All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. The influence of recreational disturbance on ungulate populations is of particular interest to wildlife managers in Colorado, as there is growing concern about its potential impacts within the state. Currently, the western United States is experiencing some of the highest rates of human population growth in the country, with growth in rural and exurban areas frequently outpacing growth in urban areas. Additionally, participation in outdoor recreation is also increasing. In Colorado, the number of individuals participating in recreational activities, and the associated demand for recreational opportunities, appear to be increasing. Understanding potential impacts of recreational activity on elk spatial ecology in Colorado is critical for guiding management actions, as altered movements may result in reduced foraging time and higher energetic costs, which may decrease fitness. We are studying elk from the resident portion (i.e., non-migratory) of the Bear’s Ears elk herd (DAU E-2) in Colorado to determine potential impacts of recreational activities on this population. This research project is a collaboration between Colorado Parks and Wildlife (CPW) and the Haub School of Environment and Natural Resources at the University of Wyoming, and forms the basis of an M.S. thesis for a graduate student enrolled at the Haub School. In January 2020 and January 2021, we collared 30 and 26 adult female elk, respectively, from the resident portion of the Bear's Ears elk herd on U.S. Forest Service (USFS) land near Steamboat Springs. We estimated pregnancy rates of 93% (95% CI: 79-98%) in 2020 and 96% (95% CI: 81-100%) in 2021. From May-October 2020 we deployed trail counters at 22 trailheads in the Routt National Forest (Figure 1). We recorded roughly 100,000 people departing and returning from these trailheads. Among individual trailheads, we documented average daily traffic counts ranging from 2-325 people (Figure 2). Most traffic was recorded on weekends with noticeable lulls in traffic frequency observed during weekdays. During the 2021 field season, we again deployed trail counters at the 22 trailheads, and also added additional trail counters at 1-km intervals along each trail for up to 5-km from the trailhead. These additional trail counters are being deployed on a rotating basis to sample each trail. Data collected from these additional trail counters will provide an estimate of the decay of traffic along trails. During the 2020 and 2021 field season, we distributed handheld GPSs to recreationists (hikers, bikers, hunters) to record detailed tracks of human use within this trail system (Figure 3). In 2020, we collected over 100 GPS tracks. These tracks from recreationists and hunters will allow us to better quantify human recreation on the landscape and evaluate how elk respond to recreationists. 33 �Figure 1. Routt National Forest study area located in northwest Colorado, USA. 34 �Figure 2. Daily trends in trailhead traffic documented with trail counters from June through October 2020, excluding Fish Creek Falls, Mad Creek, and Red Dirt trailheads, which received average daily counts >200. Figure 3. GPS track (blue) recorded from recreational mountain biker on trail system (white) in August 2020. Note the off-trail use near Long Lake. 35 �PREDATORY MAMMALS MANAGEMENT AND CONSERVATION BOBCAT POPULATION DENSITY ESTIMATION: A PILOT STUDY 36 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Bobcat Population Density Estimation: A Pilot Study Period Covered: January 01, 2022 – December 31, 2022 Principal Investigators: Shane Frank, shane.frank@state.co.us; Jake Ivan, jake.ivan@state.co.us; Mark Vieira, mark.vieira@state.co.us; Mat Alldredge, mat.alldredge@state.co.us; Jon Runge, jon.runge@state.co.us Personnel: Bill deVergie, Tom Knowles, Mike Swaro, Darby Finley, Garrett Smith, Brian Holmes, J.C. Rivale, Jenna Lopardo, Rhea Ebel-Childs, Tim Brtis, Doug Fitzpatrick, Rachel Baker, Charlee Manguso, Loredana McCurdy All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. To enhance our understanding of bobcat (Lynx rufus) population dynamics and the relative influence of bobcat harvest on bobcat densities in Colorado, a pilot study was started late September 2022 and will continue through spring of 2023. The major field objectives of the pilot study are (1) to capture and mark bobcats with ear tags and GPS collars to be used in mark-resight analysis for population density estimation in two study areas and (2) to determine whether successful bobcat trapping rate is sufficient to build toward an adequately sized sample population in subsequent years for population density estimation within a longer-term bobcat population dynamics research project. We selected two study areas, ‘Piceance’ and ‘Skull Creek,’ in the northwest region within GMUs 10 and 22 (Figure 1). Each area was 20 x 20 km (400 km2 area) in extent, with similar topography and habitat type composition. Piceance had higher historical bobcat harvest (>2.55 bobcats/100 km2) than Skull Creek (nearly 0 bobcats/100 km2). Habitat type composition was predominated by pinyon (Pinus spp.)-juniper (Juniperus spp.) and sagebrush (Artemisia spp.) communities in both study areas. CPW personnel started live-trapping bobcats on 11/18/2022 and captured five unmarked bobcats with three recaptures as of 12/31/2022. On average, an unmarked bobcat required approximately 100 trap nights for capture. CPW personnel also deployed 100 camera traps within the Piceance study area and 35 camera traps within the Skull Creek study area (Figure 1). Camera trap set-ups included visual and scent lure to draw marked and unmarked bobcats for picture taking or ‘resights’ in the case of marked bobcats. Livetrapping efforts in both study areas, remaining camera deployment in Skull Creek, and camera image collection will continue through spring of 2023, at which point photo identification and mark-resight analysis will commence. Information from this pilot study will be applied to develop a longer-term study plan addressing bobcat population dynamics and population estimation. 37 �Figure 1. Bobcat study area boundaries (20 x 20 km) are subdivided into 100 2 x 2 km cells. The Piceance study area is shown in red (lower) in Game Management Unit (GMU) 22 with all 100 camera traps deployed (dark red dots). Thirty-five of the 100 camera traps have been deployed in the Skull Creek study area (upper) in GMU 10 as of 12/31/22, which is located south of Dinosaur National Monument (green shaded area) in northwest Colorado. 38 �APPENDIX A. Final Report to BLM: Developing a spatial planning tool for natural gas development on mule deer winter range. Developing a spatial planning tool for natural gas development on mule deer winter range Robby M. Marrotte, Department of Biological Sciences, Trent University Charles R. Anderson Jr., Mammals Research Section, Colorado Parks and Wildlife Joseph M. Northrup, Environmental and Life Sciences Graduate Program, Trent University Purpose Developing a spatial planning tool for natural gas development on mule deer winter range. Objectives Using existing data collected on mule deer in the Piceance Basin, Colorado, we developed a tool that allows land managers to assess the potential impacts of future hydrocarbon development on mule deer behaviour and populations. This project had two phases: 1. Statistical modelling of movement data to optimize predictions of deer habitat selection. 2. Development of a user-friendly, web-based platform to assist in the development planning process by optimizing placement of infrastructure that minimizes disturbance to mule deer utilizing winter range. Yearly Summaries • 2021 o Data and covariate gathering and development  We cleaned mule deer location data and filtered transition and summer range data (Table 1).  We defined the area of interest as the 4 study areas used by the mule deer in the Piceance Basin winter range addressed by Northrup et al. (2021): North Ridge, North Magnolia, South Magnolia, and Ryan Gulch (Figure 1).  We retrieved all necessary spatial and spatiotemporal data. Locations of roads, pipelines and facilities were digitized from National Agricultural Imagery Program (NAIP) imagery and ground truthed between 2010 and 2015. • Mule deer winter range study areas (Retrieved from Northrup et al. 2021). • Digital Elevation Model (DEM; Retrieved from https://earthexplorer.usgs.gov/). 39 �Daily snow depth between 2009-2015 (Retrieved from Northrup et al. 2021). • Road network (Retrieved from Northrup et al. 2021). • Facility locations (Retrieved from Northrup et al. 2021). • Pipeline network (Retrieved from Northrup et al. 2021). • Landsat 8 (LS8) imagery between 2012-2019 (Retrieved from Google Earth Engine). • Modis imagery between 2009-2019 (Retrieved from Google Earth Engine). • Location and daily status of wells between 2009-2019 (Retrieved from cogcc.state.co.us). Wells were grouped onto pads and pad boundaries were digitized using NAIP imagery. Status of the pad was assigned as the status of the well with the most active development- e.g., if there were two wells on a pad and one was producing gas and the other was being drilled, the status of the pad was set as “drilling.”  We built static and spatiotemporal layers (Table 2). • Static layers o Digital Elevation Model (DEM) derived: Elevation, Terrain Ruggedness Index (TRI), Slope, Solar-radiation Aspect Index. o Climate: Long-term average and standard deviation of snow depth. o Roads: Density of roads within 100-meter distance bands between 0.1-1 km. o Facilities: Density of facilities within 100-meter distance bands between 0.1-1 km. o Pipelines: Density of pipelines within 100-meter distance bands between 0.1-1 km. o LS8 derived: summer bands 1-7, summer NDVI, summer NDVI slope, winter bands 1-7, winter NDVI, winter NDVI slope. • Spatiotemporal layers o Modis derived: Biweekly NDVI, red, near-infrared, blue and middle-infrared. o Producing well pads derived: Daily density of producing well pads within 100-meter distance bands between 0.1-1 km. o Drilling well pads derived: Daily density of producing well pad within 100-meter distance bands between 0.1-1 km. o Model development  We created the background (available) and habitat use (i.e., deer GPS collar) locations. We set a ratio of 30 background locations for each • 40 � habitat use location within each range. We based the probability of each background location on the frequency of use locations during each day between 2009-2019. Consequently, if 5% of use locations were on January 2nd, 2008, the same proportion of background locations were assigned to this day. We trained machine learning resource selection functions using Extreme Gradient Boosting (XGBoost; Chen et al. 2015) using 80% of the entire dataset. We used 20% of the training data (i.e., 16% of the entire dataset) for model validation to help guide and tune the hyperparameters. We then used the remaining 20% of the data for testing the accuracy out-of-sample. o Dashboard  We developed a dashboard using the R Shiny package and Leaflet interactive maps that can be used to predict the impact of the placement of well pads (Figure 2). • 2022 o We deployed a prototype of the application on a University of Rhode Island server (shiny.celsrs.uri.edu/bgerber/). We fixed bugs relating to version differences between the server and the previous infrastructure on which we built the application. o We added the ability to predict the impact of roads in addition to well pads (Figure 3). o We fine-tuned the artificial intelligence model to increase the model's predictive accuracy on validation data. o We used the remaining data (testing data) to determine the weakness of the models across ranges and drilling periods (Table 3). We found that the model was generally capable of accurately predicting the drilling (2008-2012) and producing (2012-2019) periods. Comparatively, the model accuracy was lowest for North Magnolia during the producing period. o We invited resource managers to test-run the application and used their feedback to make it more user-friendly. We added the ability to visualize the percent change of habitat use during the drilling and producing period (Figure 4). o We finalized the model and application and uploaded a stable release of the application on the University of Rhode Island server. o We wrote the first draft of a manuscript detailing the steps to create the application. We plan on submitting this manuscript to the Journal of Wildlife Management in December 2022. Background Oil and natural gas development has seen significant increases across North America since the turn of the century (USEIA 2015), bringing substantial environmental impacts to developed areas. In western North America, much of this development has overlapped with the ranges of wildlife species (Northrup & Wittemyer 2013). One species for which this development has 41 �generated significant concern is the mule deer. Mule deer are an important recreational and economic resource across the intermountain west but have seen large-scale population fluctuations over the last several decades (Unsworth et al. 1999), along with recent declines (Bergman et al. 2015). Hydrocarbon development in mule deer winter range elicits behavioural responses from deer, including relative reductions in the use of large areas in their winter range (Sawyer et al. 2006, 2009; Northrup et al. 2015, 2016a, 2016b). During winter, deer have a negative energy balance, leading to declining conditions (Monteith et al. 2013) and occasional large-scale mortality events (White & Bartmann 1998). Thus, displacement from preferred areas or increased movements due to human activity could exacerbate these issues. Hydrocarbon extraction is projected to continue to increase for the next two decades (USEIA 2022), modifying substantial areas of new land, much of which will be in the intermountain West (McDonald et al. 2009). Considering this ongoing and impending development in the mule deer winter range, managers need a more in-depth understanding of the impacts of hydrocarbon development. A major need for land and wildlife managers is spatial decision support tools that incorporate currently existing knowledge on how hydrocarbon development impacts mule deer to allow for science-based development and mitigation planning. Specifically, managers need tools that can be used to determine how much development to allow in an area, where and when to allow development to proceed (e.g., how to spatially configure development infrastructure on the landscape to reduce impacts to critical habitat), and the types of mitigation measures to implement to reduce the impacts of development on mule deer. We leveraged existing large temporal and spatial scale datasets on mule deer habitat selection and demography from the Piceance Basin of Colorado to develop a spatial planning tool that can be used by managers in an adaptive management framework to plan development infrastructure and guide mitigation planning. We applied 10 years of combined movement, survival, and population abundance information. Much of these data have been previously analyzed and been used to quantify behavioral and demographic responses to energy development. We used this existing information in conjunction with new analyses that focused on optimizing our ability to predict the spatial responses of deer to energy development to produce a planning tool. The spatial planning tool that we developed will allow land managers to assess how the spatial pattern of proposed development would impact mule deer behavior on pinyon juniper winter range. Further, it provides estimates of the uncertainty in expected impacts to deer and the opportunity to explore impacts under varying winter and moisture conditions. We envision a user-friendly platform that would ultimately allow managers and developers the ability to optimize the development footprint such that impacts to deer populations and habitat can be minimized. Applicability of Planning Tool and Next Steps The model underlying the shinyapp developed for this project was fit and tested using winter range data from the Piceance Basin. As such, the app is most valid for application to the winter ranges in the Piceance Basin from which the data originated. However, the model has potential utility outside of the Piceance Basin provided sufficient caution is taken in interpretation of the outputs. Several factors will influence how accurate the model is outside of the Piceance Basin: 1) the similarity of the habitat, including both vegetation and topography (e.g., topographically diverse dominated by pinion-juniper overstory), 2) the similarity of the development infrastructure, and 3) deer density, which is directly linked to their use of habitat. In the coming months, we will directly test the applicability of the developed models to mule deer habitat use 42 �outside of the specific winter ranges within the Piceance Basin and using data completely outside of the Piceance Basin. This will provide some guidance on the utility of the model for development planning elsewhere. Further, we plan to develop a companion tool that will allow users to apply the model elsewhere in Colorado. This tool will require user inputs for existing infrastructure of roads, well pads, pipelines, and facilities (e.g., compressor stations, gas plants). Prior to development of this companion tool, resource managers can contact Dr. Joseph Northrup at joe.northrup@gmail.com to discuss use outside of the Piceance Basin and coordinate application. Such application will again require user inputs for well pads, roads, pipelines and facilities. Further, caution in interpretation will be needed. 43 �Tables Table 1. The number of individuals and GPS fixes for adult female mule deer monitored on winter range in the Piceance Basin, Colorado USA between December 2008 to March 2019. Number of Does Winter 2007-2008 2008-2009 2009-2010 2010-2011 2011-2012 2012-2013 2013-2014 2014-2015 2015-2016 2016-2017 2017-2018 2018-2019 Total Number of Fixes North North Ryan South Magnolia Ridge Gulch Magnolia 4 15 34 52 55 67 56 56 47 43 48 22 499 10 27 38 31 48 43 39 43 27 26 36 19 387 11 23 36 56 44 39 35 43 49 44 48 14 442 5 12 34 51 60 71 51 49 50 59 67 29 538 Total North Magnolia North Ridge Ryan Gulch South Magnolia Total 30 77 142 190 207 220 181 191 173 172 199 84 1,866 1,116 2,515 7,296 18,486 19,337 25,091 19,617 21,782 20,016 17,814 15,597 4,802 173,469 3,338 4,573 8,371 7,091 12,752 15,287 13,998 17,825 11,504 10,791 12,126 6,179 123,835 2,967 3,484 8,232 18,129 2,061 15,681 13,269 19,245 24,145 19,195 20,451 6,549 153,408 1,801 2,081 4,985 17,697 22,162 25,382 19,894 15,372 17,955 19,906 29,424 10,100 186,759 9,222 12,653 28,884 61,403 56,312 81,441 66,778 74,224 73,620 67,706 77,598 27,630 637,471 44 �Table 2. Habitat use prediction categories for mule deer does on their winter range in the Piceance Basin, Colorado, USA. Derived predictors Category Variation Elevation (m) Terrain ruggedness index (TRI) Radiation Slope Mean Snow Depth Sd Snow Depth Cover Static Forage Static L8 B1 Ultra Blue (0.435-0.451 μm) L8 B2 Blue (0.452-0.512 μm) L8 B3 Green (0.533-0.590 μm) L8 B4 Red (0.636-0.673 μm) L8 B5 NIR (0.851-0.879 μm) L8 B6 SIR 1 (1.566-1.651 μm) Cover and forage Description Sources Topographic based predictors Obtained from the United States Geological Survey https://earthexplorer.usgs.gov/ Daily modelled snow depth from 2008-2015 Obtained and derived by Liston and Elder (2006), Northrup et al. (2016b), Northrup et al. (2021) For each, median value for December-March 2013-2019 and June-September 2013-2019 USGS Landsat 8 Level 2, Collection 2, Tier 1 https://developers.google.com/earthengine/datasets/catalog/LANDSAT_LC08_C02_T1_L2 Nearest value in time between 2009 and 2019 Obtained from the Google Earth Engine MOD13Q1.006 Terra Vegetation Indices 16-Day Global 250m https://developers.google.com/earthengine/datasets/catalog/MODIS_006_MOD13Q1 The density of roads for several distance bands Obtained from the United States Geological Survey Digitized from aerial imagery obtained from the National Agricultural Imagery Program https://earthexplorer.usgs.gov/ The density of pipelines for several distance bands Obtained from the White River Bureau of Land Management office and supplemented from aerial imagery obtained from the National Agricultural Imagery Program https://earthexplorer.usgs.gov/ Static L8 B7 SIR 2 (2.107-2.294 μm) NDVI NDVI Slope Modis Red (645nm) Modis NIR (858nm) Modis Blue (469nm) Modis MIR (2130nm/2105 2155nm) Modis NDVI Cover and forage Road density within 0-200, 200400, 400-600, 600-800, and 8001000 meters Anthropogenic Pipeline density within 0-200, 200400, 400-600, 600-800, and 8001000 meters Anthropogenic Spatiotemporal Static Static 45 �Facility density within 0-200, 200400, 400-600, 600-800, and 8001000 meters Pad density within 0-200, 200-400, 400-600, 600-800, and 800-1000 meters Anthropogenic Anthropogenic Static Spatiotemporal The density of natural gas facilities for several distance bands Digitized from aerial imagery obtained from the National Agricultural Imagery Program https://earthexplorer.usgs.gov/ and validated on the ground Nearest value in time between 2009 and 2019 for density of drilling and producing well pads for several distance bands Obtained from the Colorado Oil & Gas Conservation Commission cogcc.state.co.us Pad density within 0-200, 200-400, 400-600, 600-800, and 800-1000 meters 46 �Table 3. Model accuracy (%) for adult female mule deer habitat use in 4 winter range study areas in the Piceance Basin, Colorado between 2008–2019. Sensitivity is the accuracy of the locations where mule deer were located from their GPS collars and specificity was the accuracy of the background availability data. Range Development All Ranges North Magnolia North Ridge Ryan Gulch South Magnolia All Ranges North Magnolia North Ridge Ryan Gulch South Magnolia All Ranges North Magnolia North Ridge Ryan Gulch South Magnolia Low/High Low None High High Low/High Low None High High Low/High Low None High High Period Drilling (20082012) Training 94.44 93.04 Sensitivity Validation 74.78 73.91 Testing 74.76 73.96 95.24 94.44 95.21 73.82 73.94 76.90 74.46 74.13 76.22 75.43 74.00 71.25 93.35 91.00 73.89 72.11 73.62 71.13 72.11 69.40 94.96 94.40 93.75 73.59 73.33 76.29 74.91 73.89 74.96 74.74 73.86 71.63 94.83 93.84 75.10 74.61 75.17 75.06 72.30 69.56 95.36 94.45 95.73 73.91 74.12 77.12 74.27 74.20 76.65 75.72 74.03 71.11 Producing (20122019) Both (20082019) 47 Specificity 72.25 69.52 �Figures Figure 1. Mule deer winter range study areas in the Piceance Basin, Colorado, USA. The study areas are described in Northrup et al. (2021). Study areas contoured in red represent high development areas with numerous active natural gas wells and study areas contoured in black represent low development areas with few (North Magnolia) or no active natural gas wells (North Ridge). 48 �Figure 2. Mule deer hydrocarbon impact dashboard for predicting the impact of placing natural gas wells and roads within the Magnolia, Ryan Gulch, and North Ridge winter range study areas. The model was developed from mule deer GPS collar data acquired between 2009–2019. 49 �A B Figure 3. Example of placing natural gas well pads within the South Magnolia winter range study area. A) Area of interest for well pad development. B) Placement of new well pads and service roads. 50 �A B C D Figure 4. Predicted habitat use by mule deer during the winter months during the drilling phase (A) and during the producing phase (B). Percent change in habitat use during the drilling phase relative to predicted map with no well pads; green shading indicates an increase in predicted probability of use, while purple shading indicates a decrease in predicted probability of use and (C) producing phase relative to predicted map with no well pads; green shading indicates an increase in predicted probability of use, while purple shading indicates a decrease in predicted probability of use (D). Predicted habitat use and change in habitat use are relative to available habitat and scaled by category. Complete avoidance only occurred directly on well pads. The large apparent avoidance and change in habitat use apparent around well pads in the figures represent change in habitat use relative to baseline, but are not complete avoidance of the areas. Note that because the percent change is relative, apparently large percent changes can occur with small absolute change; e.g., a change from 0.01 to 0.02 is small in absolute terms but would be a 100% increase in probability of use. 51 �References Bergman, E.J., Doherty, P.F., White, G.C. and Holland, A.A., 2015. Density dependence in mule deer: a review of evidence. Wildlife Biology, 21(1), pp.18-29. Chen, T., He, T., Benesty, M., Khotilovich, V., Tang, Y., Cho, H. and Chen, K., 2015. Xgboost: extreme gradient boosting. R package version 0.4-2, 1(4), pp.1-4. Northrup, J.M. and Wittemyer, G., 2013. Characterising the impacts of emerging energy development on wildlife, with an eye towards mitigation. Ecology letters, 16(1), pp.112125. Northrup, J.M., Anderson Jr, C.R. and Wittemyer, G., 2015. Quantifying spatial habitat loss from hydrocarbon development through assessing habitat selection patterns of mule deer. Global change biology, 21(11), pp.3961-3970. Northrup, J.M., Anderson Jr, C.R., Hooten, M.B. and Wittemyer, G., 2016a. Movement reveals scale dependence in habitat selection of a large ungulate. Ecological Applications, 26(8), pp.2746-2757. Northrup, J.M., Anderson Jr, C.R. and Wittemyer, G., 2016b. Environmental dynamics and anthropogenic development alter philopatry and space‐use in a North American cervid. Diversity and Distributions, 22(5), pp.547-557. Northrup, J.M., Anderson Jr, C.R., Gerber, B.D. and Wittemyer, G., 2021. Behavioral and demographic responses of mule deer to energy development on winter range. Wildlife Monographs, 208(1), pp.1-37. McDonald, R.I., Fargione, J., Kiesecker, J., Miller, W.M. and Powell, J., 2009. Energy sprawl or energy efficiency: climate policy impacts on natural habitat for the United States of America. PloS one, 4(8), p.e6802. Monteith, K.L., Stephenson, T.R., Bleich, V.C., Conner, M.M., Pierce, B.M. and Bowyer, R.T., 2013. Risk‐sensitive allocation in seasonal dynamics of fat and protein reserves in a long‐ lived mammal. Journal of Animal Ecology, 82(2), pp.377-388. Sawyer, H., Kauffman, M.J. and Nielson, R.M., 2009. Influence of well pad activity on winter habitat selection patterns of mule deer. The Journal of Wildlife Management, 73(7), pp.1052-1061. Sawyer, H., Nielson, R.M., Lindzey, F. and McDonald, L.L., 2006. Winter habitat selection of mule deer before and during development of a natural gas field. The Journal of Wildlife Management, 70(2), pp.396-403. United States Energy Information Administration (USEIA). 2015. Crude Oil and Natural Gas Exploratory and Development Wells. http://www.eia.gov/dnav/ng/NG_ENR_WELLEND_S1_A.htm United States Energy Information Administration (USEIA). 2022. Annual Energy Outlook 2022. https://www.eia.gov/outlooks/archive/aeo21/pdf/AEO_Narrative_2021.pdf Unsworth, J.W., Pac, D.F., White, G.C. and Bartmann, R.M., 1999. Mule deer survival in Colorado, Idaho, and Montana. The Journal of Wildlife Management, pp.315-326. White, G.C. and Bartmann, R.M., 1998. Effect of density reduction on overwinter survival of free-ranging mule deer fawns. The Journal of wildlife management, pp.214-225. 52 �APPENDIX B. CPW mammal research abstracts published since July 2021. Nongame Mammal Ecology and Conservation – page 54 - Community Confounding in Joint Species Distribution Models - Keystone Structures Maintain Forest Function for Canada Lynx after Large-Scale Spruce Beetle Outbreak Carnivore Ecology and Management – pages 55-57 - Human-Cougar Interactions: A Literature Review Related to Common Management Questions - Disease Outbreaks Select for Mate Choice and Coat Color in Wolves - Movement and Habitat Selection of a Large Carnivore in Response to Human Infrastructure Differs by Life Stage - Parasitic Infection Increases Risk-Taking in a Social, Intermediate Host Carnivore - Evaluating Noninvasive Methods for Estimating Cestode Prevalence in a Wild Carnivore Population Ungulate Ecology and Management – pages 58-61 - Some Memories Never Fade: Inferring Multi-Scale Memory Effects on Habitat Selection of a Migratory Ungulate Using Step-Selection Functions - Effects of Willow Nutrition and Morphology on Calving Success of Moose - A Call to Action: Standardizing White-Tailed Deer Harvest Data in the Midwestern United States and Implications for Quantitative Analysis and Disease Management - Cause of Death, Pathology, and Chronic Wasting Disease Status of White-Tailed Deer (Odocoileus virginianus) Mortalities in Wisconsin, USA - Factors Influencing Productivity and Recruitment of Elk in Northern New Mexico - Plant and mule deer responses to pinyon‐juniper removal by three mechanical methods Wildlife Genetics and Disease Research – pages 62-63 - Complex Evolutionary History of Felid Anelloviruses - Viral Sequences Recovered From Puma Tooth DNA Reconstruct Statewide Viral Phylogenies Journal of Wildlife Management Editorial – page 64 - EDITORS MESSAGE: A Perspective on the Journal of Wildlife Management 53 �NONGAME MAMMAL ECOLOGY AND CONSERVATION Community Confounding in Joint Species Distribution Models Justin J. Van Ee1, Jacob S. Ivan2 & Mevin B. Hooten3 1 Department of Statistics, Colorado State University, Fort Collins 80523, USA. 2 Colorado Parks and Wildlife, Fort Collins 80526, USA. 3 Department of Statistics and Data Sciences, The University of Texas at Austin, Austin 78712, USA. Citation: Van Ee, J. J., J. S. Ivan, and M. B. Hooten. 2022. Community confounding in joint species distribution models. Scientific Reports 12:12235; doi.org/10.1038/s41598-022-15694-6. ABSTRACT Joint species distribution models have become ubiquitous for studying species-environment relationships and dependence among species. Accounting for community structure often improved predictive power, but can also affect inference on species-environment relationships. Specifically, some parameterizations of joint species distribution models allow interspecies dependence and environmental effects to explain the same sources of variability in species distributions, a phenomenon we call community confounding. We present a method for measuring community confounding and show how to orthogonalize the environmental and random species effects in suite of joint species distribution models. In a simulation study, we show that community confounding can lead to computational difficulties and that orthogonalizing the environmental and random species effects can alleviate these difficulties. We also discuss the inferential implications of community confounding and orthogonalizing the environmental and random species effects in a case study of mammalian responses to the Colorado bark beetle epidemic in the subalpine forest by comparing the outputs from occupancy models that treat species independently or account for interspecies dependence. We illustrate how joint species distribution models that restrict the random species effects to be orthogonal to the fixed effects can have computational benefits and still recover the inference provided by an unrestricted joint species distribution model. Published July 2022. Keystone Structures Maintain Forest Function for Canada Lynx after Large-Scale Spruce Beetle Outbreak John R Squires1, Jacob S Ivan2, Kelsey E Paolini3, Lucretia E Olson1, Gavin M Jones4, and Joseph D Holbrook3 1 USDA Forest Service, Rocky Mountain Research Station, Missoula, MT, United States of America 2 Colorado Parks and Wildlife, Fort Collins, CO, United States of America 3 Haub School of Environment and Natural Resources, Department of Zoology and Physiology, University of Wyoming, Laramie, WY, United States of America 4 USDA Forest Service, Rocky Mountain Research Station, Albuquerque, NM, United States of America Citation: Squires, J. R., J. S. Ivan, K. E. Paolini, L. E. Olson, G. M. Jones, and J. D. Holbrook. 2022. Keystone structures maintain forest function for Canada lynx after large-scale spruce beetle outbreak. Environmental Research: Ecology 2:011001; https://iopscience.iop.org/article/10.1088/2752-664X/ac8eb7/meta ABSTRACT Central to species conservation in an era of increased disturbance from climate change is understanding the primary mechanisms that facilitate how forest-dependent species respond to changes in forest structure and composition. Here, we leveraged a natural experiment to investigate how changed forest structure and function pre-spruce-beetle (Dendroctonus rufipennis) and post-beetle disturbance influenced the regional distribution of Canada lynx (Lynx canadensis) at their southern range periphery. We compared the distribution of Canada lynx that were reintroduced into Colorado, USA from 1999–2006 to the current (2015–2017) distribution following a spatial large-scale spruce beetle outbreak from 2007 to 2016. Canada lynx did not substantially alter their distribution following the wide-spread alteration of forest structure and composition following the insect outbreak. We used the Bhattacharyya’s affinity metric to document that core (50% isopleth) and overall population ranges (95% isopleth) overlapped significantly at 50% and 77% respectively. In addition, areas of low and high relative use remained similar after the bark beetle outbreak and mapped onto one another in nearly a 1:1 fashion (Spearman rank correlation = 0.92, p < 0.01). The low impact of forest change on distribution was due to the keystone habitat elements (high horizontal forest cover, snowshoe hares) that remained functional. Thus, our results highlight that conservation scientists should increase their focus to understand the underlying mechanisms that impact wildlife distributions as climate-related disturbances becomes ever more amplified. Published December 2022. 54 �CARNIVORE ECOLOGY AND MANAGEMENT Human-Cougar Interactions: A Literature Review Related to Common Management Questions Human-Cougar Interactions Science Review Team: Brian Kertson1, Scott McCorquodale1, Donny Martorello1, Chuck Anderson, Jr.2, Anis Aoude1, Rich Beausoleil1, Mick Cope1, Mark Hurley3, Bruce Johnson4, Glen Sargeant5, and Stephanie Simek1 1 Washington Department of Fish and Wildlife, 2 Colorado Parks and Wildlife, 3 Idaho Fish and Game, 4 Oregon Department of Fish and Wildlife (retired), 5 United States Geological Survey Citation: Human-Cougar Interactions Science Review Team. 2022. Human-Cougar Interactions: A Literature Review Related to Common Management Questions. Washington Department of Fish and Wildlife, Olympia, Washington, USA. 78 pp. EXECUTIVE SUMMARY Interactions between humans and cougars (Puma concolor) present unique challenges for wildlife managers; reducing occurrences that lead to conflict is a priority for state and provincial wildlife agencies throughout western North America, including Washington. With an increase in management emphasis of human-wildlife conflict resolution, a growing body of scientific literature related to cougar wildland-urban ecology and the factors that contribute to interactions between cougars and people has developed. Based on discussions with the Fish and Wildlife Commission, our 10-member Human-Cougar Interaction Science Review Team assessed both the analytical and ecological merits of current literature, focusing on data and methods, to summarize the current state of knowledge on human-cougar interactions and factors affecting these interactions. We did not use our review findings to provide management recommendations or evaluate/suggest policy alternatives, but we did highlight important information gaps, research needs, and proposed strategies for conducting scientific investigations to benefit managers and policy makers in the future. We used bibliographic lists, keyword searches in research databases, and new literature encountered as citations within papers we reviewed to identify 96 potential studies for review. We evaluated 41 studies that aligned with eight commonly asked questions regarding how various factors contribute to cougar proximity to, and interactions with people. Our review concluded that the roles of cougar removals (Question 1), cougar population size or trajectory (Question 2), the abundance or diversity of prey (Question 3), human population size, distribution, or recreation levels (Question 6), human attitudes (Question 7), and competition with other large carnivores (Question 8) in cougar interactions with people remain uncertain. We found the studies evaluating the efficacy of nonlethal deterrents (Question 4) provided some evidence that these methods reduce conflict, most notably that flashing lights can reduce interactions in specific situations. Our review of papers investigating the role of landscape characteristics (Question 5) revealed spatial ecology to be the most reliably studied and best understood facet of cougar wildland-urban ecology; study designs in these investigations were also the most rigorous. Most cougar use, and subsequent interactions with people, occur at the wildland-urban interface or in exurban and rural residential settings immediately adjacent because these habitats provide both abundant native prey (deer) and stalking cover, or they retain enough native landcover, connectivity, and prey to support cougar use, but with a human presence at a level that does not substantially deter cougars. We identified only a limited number of informative studies in our review, primarily because many studies did not collect data to specifically address relevant management questions after developing testable hypotheses. Much of the literature we reviewed was derived from ad hoc mining of pre-existing data that had been collected for other routine reasons, data were often not assessed for accuracy, and confounding factors were inadequately addressed. Consequently, many factors theorized to contribute to cougar interactions with people require more rigorous investigation. Because wildland-urban systems are complex, and interactions encompass both human and cougar behavior, we recommend the use of long-term studies that incorporate both ecological and anthropogenic factors within a control-treatment design with replicate study sites to address questions with direct management relevance. Published January 2022 Disease Outbreaks Select for Mate Choice and Coat Color in Wolves Sarah Cubaynes1, Ellen E. Brandell2, 12, Daniel R. Stahler3, Douglas W. Smith3, Emily S. Almberg4, Susanne Schindler5, Robert K. Wayne6, Andrew P. Dobson7,8, Bridgett M. vonHoldt7, Daniel R. MacNulty9, Paul C. Cross10, Peter J. Hudson2, Tim Coulson11 1 CEFE, University of Montpellier, CNRS, EPHE-PSL University, IRD, 34090 Montpellier, France. 2 Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, State College, PA 16802, USA 3 Yellowstone Center for Resources, Yellowstone National Park, WY 82190, USA. 4 Wildlife Division, Montana Fish Wildlife & Park, Bozeman, MT 59718, USA. 5 School of Biological Sciences, University of Bristol, Bristol BS8 1QU, UK. 6 Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA. 7 Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA. 8 Santa Fe Institute, Santa Fe, NM 87501, USA. 9 Department of Wildland Resources and Ecology Center, Utah State University, Logan, UT 84322, USA. 10 US Geological Survey, Northern Rocky Mountain Science Center, Bozeman, MT 59715, USA. 55 �11 12 Department of Biology, University of Oxford, Oxford OX1 3SZ, UK. Current address: Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO, USA. Citation: Cubaynes, S., E. E. Brandell, D. R. Stahler, D. W. Smith, E. S. Almberg, S. Schindler, R. K. Wayne, A. P. Dobson, B. M. vonHoldt, D. R. MacNulty, P. D. Cross, P. J. Hudson, and T. Coulson. 2022. Disease outbreaks select for mate choice and coat color in wolves. Science 378:300–303; DOI: 10.1126/science.abi8745 ABSTRACT We know much about pathogen evolution and the emergence of new disease strains, but less about host resistance and how it is signaled to other individuals and subsequently maintained. The cline in frequency of black-coated wolves (Canis lupus) across North America is hypothesized to result from a relationship with canine distemper virus (CDV) outbreaks. We tested this hypothesis using crosssectional data from wolf populations across North America that vary in the prevalence of CDV and the allele that makes coats black, longitudinal data from Yellowstone National Park, and modeling. We found that the frequency of CDV outbreaks generates fluctuating selection that results in heterozygote advantage that in turn affects the frequency of the black allele, optimal mating behavior, and black wolf cline across the continent. Published October 2022. Movement and Habitat Selection of a Large Carnivore in Response to Human Infrastructure Differs by Life Stage N. H. Thorsen1, J. E. Hansen2, O. G. Stoen1, J. Kindberg1, A. Zedrosser2, and S. C. Frank2, 3 1 Norwegian Institute for Nature Research, Oslo, Norway 2 Faculty of Technology, Natural Sciences and Maritime Sciences, University of South-Eastern Norway, Bø, Telemark, Norway 3 Current address: Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO, USA Citation: Thorsen, N. H., J. E. Hansen, O. G. Stoen, J. Kindberg, A. Zedrosser, and S. C. Frank. 2022. Movement and habitat selection of a large carnivore in response to human infrastructure differs by life stage. Movement Ecology, 10 (52); doi.org/10.1186/s40462-022-00349-y ABSTRACT The movement extent of mammals is influenced by human-modified areas, which can affect population demographics. Understanding how human infrastructure influences movement at different life stages is important for wildlife management. This is true especially for large carnivores, due to their substantial space requirements and potential for conflict with humans. We investigated human impact on movement and habitat selection by GPS-collared male brown bears (Ursus arctos) in two life stages (residents and dispersers) in central Sweden. We identified dispersers visually based on their GPS locations and used hidden Markov models to delineate dispersal events. We used integrated step selection analysis (iSSA) to infer movement and habitat selection at a local scale (availability defined by hourly relocations), and resource selection functions (RSFs) to infer habitat selection at a landscape scale (availability defined by the study area extent). Movement of residents on a local scale was facilitated by small forestry roads as they moved faster and selected areas closer to forestry roads, and they avoided areas closer to larger public roads and buildings on both scales. Dispersers were more ambivalent in their response to human infrastructure. Dispersers increased their speed closer to small forestry roads and larger public roads, did not exhibit selection for or against any road class, and avoided areas closer to buildings only at local scale. Dispersers did not select for any features on the landscape, which is likely explained by the novelty of the landscape or their naivety towards it. Our results show that movement in male brown bears is life stage-dependent and indicate that connectivity maps derived from movement data of dispersing animals may provide more numerous and more realistic pathways than those derived from resident animal data alone. This suggests that data from dispersing animals provide more realistic models for reconnecting populations and maintaining connectivity than if data were derived from resident animals alone. Published November 2022. Parasitic Infection Increases Risk-Taking in a Social, Intermediate Host Carnivore Connor J. Meyer 1,2,3 Kira A. Cassidy1,3, Erin E. Stahler 1, Ellen E. Brandell1,4, Colby B. Anton1, Daniel R. Stahler1 & Douglas W. Smith1 1 Yellowstone Wolf Project, Yellowstone Center for Resources, P.O. Box 168 Yellowstone National Park, WY 82190, USA. 2 Wildlife Biology Program, Department of Ecosystem and Conservation Sciences, W. A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT 59812, USA. 3 These authors contributed equally: Connor J. Meyer, Kira A. Cassidy 4 Current address: Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO, USA. Citation: Cubaynes, S., E. E. Brandell, D. R. Stahler, D. W. Smith, E. S. Almberg, S. Schindler, R. K. Wayne, A. P. Dobson, B. M. vonHoldt, D. R. MacNulty, P. D. Cross, P. J. Hudson, and T. Coulson. 2022. Disease outbreaks select for mate choice and coat color in wolves. Science 378:300–303; DOI: 10.1126/science.abi8745 56 �ABSTRACT Toxoplasma gondii is a protozoan parasite capable of infecting any warm-blooded species and can increase risk-taking in intermediate hosts. Despite extensive laboratory research on the effects of T. gondii infection on behaviour, little is understood about the effects of toxoplasmosis on wild intermediate host behavior. Yellowstone National Park, Wyoming, USA, has a diverse carnivore community including gray wolves (Canis lupus) and cougars (Puma concolor), intermediate and definitive hosts of T. gondii, respectively. Here, we used 26 years of wolf behavioural, spatial, and serological data to show that wolf territory overlap with areas of high cougar density was an important predictor of infection. In addition, seropositive wolves were more likely to make high-risk decisions such as dispersing and becoming a pack leader, both factors critical to individual fitness and wolf vital rates. Due to the social hierarchy within a wolf pack, we hypothesize that the behavioural effects of toxoplasmosis may create a feedback loop that increases spatial overlap and disease transmission between wolves and cougars. These findings demonstrate that parasites have important implications for intermediate hosts, beyond acute infections, through behavioural impacts. Particularly in a social species, these impacts can surge beyond individuals to affect groups, populations, and even ecosystem processes. Published November 2022. Evaluating Noninvasive Methods for Estimating Cestode Prevalence in a Wild Carnivore Population Ellen E. Brandell1,6, Madeline K. Jackson2, Paul C. Cross3, Antoinette J. Piaggio4, Daniel R. Taylor4, Douglas W. Smith2, Belgees Boufana5, Daniel R. Stahler2, Peter J. Hudson1 1 Center for Infectious Disease Dynamics, Department of Biology, Huck Institutes of Life Sciences, Pennsylvania State University, University Park, PA, United States of America 2 Yellowstone Center for Resources, Yellowstone National Park, WY, United States of America 3 U.S. Geological Survey, Northern Rocky Mountain Science Center, Bozeman, MT, United States of America 4 National Wildlife Research Center, U.S. Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, Fort Collins, CO, United States of America 5 National Wildlife Management Centre, National Reference Laboratory for Parasites (Trichinella and Echinococcus), Animal and Plant Health Agency, York, United Kingdom 6 Current Address: Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO, United States of America Citation: Brandell, E. E., M. K. Jackson, P. C. Cross, A. J. Piaggio, D. R. Taylor, D. W. Smith, B. Boufana, D. R. Stahler, and P. J. Hudson. 2022. Evaluating noninvasive methods for estimating cestode prevalence in a wild carnivore population. PLoS ONE, 17(11): e0277420; doi.org/10.1371/journal.pone.0277420 ABSTRACT Helminth infections are cryptic and can be difficult to study in wildlife species. Helminth research in wildlife hosts has historically required invasive animal handling and necropsy, while results from noninvasive parasite research, like scat analysis, may not be possible at the helminth species or individual host levels. To increase the utility of noninvasive sampling, individual hosts can be identified by applying molecular methods. This allows for longitudinal sampling of known hosts and can be paired with individual-level covariates. Here we evaluate a combination of methods and existing long-term monitoring data to identify patterns of cestode infections in gray wolves in Yellowstone National Park. Our goals were: (1) Identify the species and apparent prevalence of cestodes infecting Yellowstone wolves; (2) Assess the relationships between wolf biological and social characteristics and cestode infections; (3) Examine how wolf samples were affected by environmental conditions with respect to the success of individual genotyping. We collected over 200 wolf scats from 2018–2020 and conducted laboratory analyses including individual wolf genotyping, sex identification, cestode identification, and fecal glucocorticoid measurements. Wolf genotyping success rate was 45%, which was higher in the winter but decreased with higher precipitation and as more time elapsed between scat deposit and collection. One cestode species was detected in 28% of all fecal samples, and 38% of known individuals. The most common infection was Echinococcus granulosus sensu lato (primarily E. canadensis). Adult wolves had 4x greater odds of having a cestode infection than pups, as well as wolves sampled in the winter. Our methods provide an alternative approach to estimate cestode prevalence and to linking parasites to known individuals in a wild host system, but may be most useful when employed in existing study systems and when field collections are designed to minimize the time between fecal deposition and collection. Published November 2022. 57 �UNGULATE ECOLOGY AND MANAGEMENT Some Memories Never Fade: Inferring Multi-Scale Memory Effects on Habitat Selection of a Migratory Ungulate Using Step-Selection Functions Helena Rheault1, Charles R. Anderson Jr.2, Maegwin Bonar1, Robby R. Marrotte1, Tyler R. Ross3, George Wittemyer4 and Joseph M. Northrup1,5 1 Environmental and Life Sciences Graduate Program, Trent University, Peterborough, ON, Canada 2 Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO, United States 3 Department of Biology, York University, Toronto, ON, Canada 4 Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, CO, United States 5 Ontario Ministry of Natural Resources and Forestry, Peterborough, ON, Canada Citation: Rheault, H, C. R Anderson Jr, M. Bonar, R. R. Marrotte, T. R. Ross, G. Wittemyer, and J. M. Northrup. 2021. Some memories never fade: inferring multi-scale memory effects on habitat selection of a migratory ungulate using step-selection functions. Frontiers in Ecology and Evolution 9.702818; doi: 10.3389/fevo.2021.702818. ABSTRACT Understanding how animals use information about their environment to make movement decisions underpins our ability to explain drivers of and predict animal movement. Memory is the cognitive process that allows species to store information about experienced landscapes, however, remains an understudied topic in movement ecology. By studying how species select for familiar locations, visited recently and in the past, we can gain insight to how they store and use local information in multiple memory types. In this study, we analyzed the movements of a migratory mule deer (Odocoileus hemionus) population in the Piceance Basin of Colorado, United States to investigate the influence of spatial experience over different time scales on seasonal range habitat selection. We inferred the influence of short and long-term memory from the contribution to habitat selection of previous space use within the same season and during the prior year, respectively. We fit step-selection functions to GPS collar data from 32 female deer and tested the predictive ability of covariates representing current environmental conditions and both metrics of previous space use on habitat selection, inferring the latter as the influence of memory within and between seasons (summer vs. winter). Across individuals, models incorporating covariates representing both recent and past experience and environmental covariates performed best. In the top model, locations that had been previously visited within the same season and locations from previous seasons were more strongly selected relative to environmental covariates, which we interpret as evidence for the strong influence of both short- and long-term memory in driving seasonal range habitat selection. Further, the influence of previous space uses was stronger in the summer relative to winter, which is when deer in this population demonstrated strongest philopatry to their range. Our results suggest that mule deer update their seasonal range cognitive map in real time and retain long-term information about seasonal ranges, which supports the existing theory that memory is a mechanism leading to emergent space-use patterns such as site fidelity. Lastly, these findings provide novel insight into how species store and use information over different time scales. Published July 2021. Effects of Willow Nutrition and Morphology on Calving Success of Moose Forest P. Hayes1, Joshua J. Millspaugh1, Eric J. Bergman2, Ragan M. Callaway1, and Chad J. Bishop1 1 Wildlife Biology Program, University of Montana, Missoula, MT, USA 2 Colorado Parks and Wildlife, Fort Collins, CO, USA Citation: Hayes, F. P., J. J. Millspaugh, E. J. Bergman, R. M. Callaway, and C. J. Bishop. 2022. Effects of willow nutrition and morphology on calving success of moose. Journal of Wildlife Management 86; https://doi.org/10.1002/jwmg.22175 ABSTRACT Across much of North America, populations of moose (Alces alces) are declining because of disease, predation, climate change, and anthropogenic-driven habitat loss. Contrary to this trend, populations of moose in Colorado, USA, have continued to grow. Studying successful (i.e., persistent or growing) populations of moose can facilitate continued conservation by identifying habitat features critical to persistence of moose. We hypothesized that moose using habitat with higher quality willow (Salix spp.) would have a higher probability of having a calf-atheel (i.e., calving success). We evaluated moose calving success using repeated ground observations of collared individuals with calves in an occupancy model framework to account for detection probability. We then evaluated the impact of willow habitat quality and nutrition on moose calving success by studying 2 spatially segregated populations of moose in Colorado. Last, we evaluated correlations between willow characteristics (browse intensity, height, cover, leaf length, and species) and willow nutrition (dry matter digestibility [DMD]) to assess the utility of using those characteristics to assess willow nutrition. We found willow height and cover had a high probability of 58 �being positively associated with higher individual-level calving success. Willow DMD, browse intensity, and leaf length were not predictive of individual moose calving success; however, the site with higher mean DMD consistently had higher mean estimates of calving success for the same year. Our results suggest surveying DMD is likely not a useful metric for assessing differences in calving success of individual moose but may be of use at population levels. Further, the assessment of willow morphology and density may be used to identify areas that support higher levels of moose calving success. Published February 2022. A Call to Action: Standardizing White-Tailed Deer Harvest Data in the Midwestern United States and Implications for Quantitative Analysis and Disease Management Ellen E. Brandell1, 2, Daniel J. Storm3, Timothy R. Van Deelen4, Daniel P. Walsh5 and Wendy C. Turner6 1 Wisconsin Cooperative Wildlife Research Unit, Department of Forest and Wildlife Ecology, University of Wisconsin–Madison, Madison, WI, United States, 2 Present address: Colorado Parks and Wildlife, Fort Collins, CO, United States 3 Wisconsin Department of Natural Resources, Eau Claire, WI, United States 4 Department of Forest and Wildlife Ecology, University of Wisconsin–Madison, Madison, WI, United States 5 United States Geological Survey, Montana Cooperative Wildlife Research Unit, University of Montana, Missoula, MT, United States 6 United States Geological Survey, Wisconsin Cooperative Wildlife Research Unit, Department of Forest and Wildlife Ecology, University of Wisconsin–Madison, Madison, WI, United States Citation: Brandell, E.E., D. J. Storm, T. R. Van Deelen, D. P. Walsh, and W. C. Turner. 2022. A call to action: standardizing white-tailed deer harvest data in the Midwestern United States and implications for quantitative analysis and disease management. Frontiers in Ecology and Evolution; https://doi.org/10.3389/fevo.2022.943411 ABSTRACT Recreational hunting has been the dominant game management and conservation mechanism in the United States for the past century. However, there are numerous modern-day issues that reduce the viability and efficacy of hunting-based management, such as fewer hunters, overabundant wildlife populations, limited access, and emerging infectious diseases in wildlife. Quantifying the drivers of recreational harvest by hunters could inform potential management actions to address these issues, but this is seldom comprehensively accomplished because data collection practices limit some analytical applications (e.g., differing spatial scales of harvest regulations and harvest data). Additionally, managing large-scale issues, such as infectious diseases, requires collaborations across management agencies, which is challenging or impossible if data are not standardized. Here we discuss modern issues with the prevailing wildlife management framework in the United States from an analytical point of view with a case study of white-tailed deer (Odocoileus virginianus) in the Midwest. We have four aims: (1) describe the interrelated processes that comprise hunting and suggest improvements to current data collections systems, (2) summarize data collection systems employed by state wildlife management agencies in the Midwestern United States and discuss potential for largescale data standardization, (3) assess how aims 1 and 2 influence managing infectious diseases in hunted wildlife, and (4) suggest actionable steps to help guide data collection standards and management practices. To achieve these goals, Wisconsin Department of Natural Resources disseminated a questionnaire to state wildlife agencies (Illinois, Indiana, Iowa, Kentucky, Michigan, Minnesota, Missouri, Ohio, Wisconsin), and we report and compare their harvest management structures, data collection practices, and responses to chronic wasting disease. We hope our “call to action” encourages reevaluation, coordination, and improvement of harvest and management data collection practices with the goal of improving the analytical potential of these data. A deeper understanding of the strengths and deficiencies of our current management systems in relation to harvest and management data collection methods could benefit the future development of comprehensive and collaborative management and research initiatives (e.g., adaptive management) for wildlife and their diseases. Published October 2022. Cause of Death, Pathology, and Chronic Wasting Disease Status of White-Tailed Deer (Odocoileus virginianus) Mortalities in Wisconsin, USA Marie L. J. Gilbertson,1 Ellen E. Brandell,1 Marie E. Pinkerton,2 Nicolette M. Meaux,1 Matthew Hunsaker,1,3 Dana Jarosinski,3,4 Wesley Ellarson,3 Daniel P. Walsh,5 Daniel J. Storm,6 and Wendy C. Turner7 1 Wisconsin Cooperative Wildlife Research Unit, Department of Forest and Wildlife Ecology, University of Wisconsin–Madison, 1630 Linden Dr., Madison, Wisconsin 53706, USA 2 Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin–Madison, 2015 Linden Dr., Madison, Wisconsin 53706, USA 3 Wisconsin Department of Natural Resources, 1500 N Johns St., Dodgeville, Wisconsin 53533, USA 4 Warnell School of Forestry and Natural Resources, University of Georgia, 180 E Green St., Athens, Georgia 30602, USA 59 �US Geological Survey, Montana Cooperative Wildlife Research Unit, University of Montana, 32 Campus Drive, NS205, Missoula, Montana 59812, USA 6 Wisconsin Department of Natural Resources, 1300 W Clairemont Ave., Eau Claire, Wisconsin 54701, USA 7 US Geological Survey, Wisconsin Cooperative Wildlife Research Unit, Department of Forest and Wildlife Ecology, University of Wisconsin– Madison, 1630 Linden Dr., Madison, Wisconsin 53706, USA 5 Citation: Gilbertson, M. L., E. E. Brandell, M. E. Pinkerton, N. M. Meaux, M. Hunsaker, D. Jarosinski, W. Ellarson, D. P. Walsh, D. J. Storm, and W. C. Turner. 2022. Cause of death, pathology, and chronic wasting disease status of white-tailed deer (Odocoileus virginianus) mortalities in Wisconsin, USA. Journal of Wildlife Diseases 54:803–815; DOI: 10.7589/JWD-D-21-00202 ABSTRACT White-tailed deer (WTD; Odocoileus virginianus) are a critical species for ecosystem function and wildlife management. As such, studies of cause-specific mortality among WTD have long been used to understand population dynamics. However, detailed pathological information is rarely documented for free-ranging WTD, especially in regions with a high prevalence of chronic wasting disease (CWD). This leaves a significant gap in understanding how CWD is associated with disease processes or comorbidities that may subsequently alter broader population dynamics. We investigated unknown mortalities among collared WTD in southwestern Wisconsin, USA, an area of high CWD prevalence. We tested for associations between CWD and other disease processes and used a network approach to test for co-occurring disease processes. Predation and infectious disease were leading suspected causes of death, with high prevalence of CWD (42.4%; of 245 evaluated) and pneumonia (51.2%; of 168 evaluated) in our sample. CWD prevalence increased with age, before decreasing among older individuals, with more older females than males in our sample. Females were more likely to be CWD positive, and although this was not statistically significant when accounting for age, females were significantly more likely to die with end-stage CWD than males and may consequently be an underrecognized source of CWD transmission. Presence of CWD was associated with emaciation, atrophy of marrow fat and hematopoietic cells, and ectoparasitism (lice and ticks). Occurrences of severe infectious disease processes clustered together (e.g., pneumonia, CWD), as compared to noninfectious or low-severity processes (e.g., sarcocystosis), although pneumonia cases were not fully explained by CWD status. With the prevalence of CWD increasing across North America, our results highlight the critical importance of understanding the potential role of CWD in favoring or maintaining disease processes of importance for deer population health and dynamics. Published October 2022. Factors Influencing Productivity and Recruitment of Elk in Northern New Mexico Bruce E. Watkins1, Eric J. Bergman2, Leslie C. Dhaseleer1, and Lance J. Bernal1 1 Vermejo Park Ranch, Turner Enterprises, P.O. Drawer E, Raton, NM 87740, USA 2 Colorado Parks and Wildlife, 317 Prospect Road, Fort Collins, CO 80526, USA Citation: Watkins, B. E., E. J. Bergman, L. C. Dhaseleer, and L. J. Bernal. 2022. Factors influencing productivity and recruitment of elk in northern New Mexico. Journal of Wildlife Management: e22348; doi.org/10.1002/jwmg.22348 ABSTRACT Declining recruitment in elk (Cervus canadensis) populations is a common issue faced by managers in western North America. To better understand a decline in calf:female (≥1 yr) ratios in northern New Mexico, USA, we investigated the influence of bottom‐up factors on the condition and productivity of 1,885 adult (≥2 yr), female Rocky Mountain elk (C. c. nelsoni) harvested on the Vermejo Park Ranch during December and January, 2009– 2016. We used ingesta‐free body fat (IFBF) estimated from kidney fat mass as a measure of condition. Based on maximum likelihood model selection, age, harvest date, hunt zone, pregnancy status, lactation status (as determined in Dec–Jan), June–August precipitation, and December–March mean temperature were important variables for predicting IFBF and field‐dressed mass (FDM). Age, IFBF, FDM, harvest date, and June–August precipitation were important variables for predicting conception date, pregnancy rate, and lactation rate. Pregnancy status and lactation status were also important for predicting lactation rate and pregnancy rate, respectively. Older females (≥12 yr) had progressively lower IFBF and FDM and later conception dates than prime females (3–11 yr) and their pregnancy rates declined an average of approximately 9%/year after age 11. The probability of pregnancy in prime females generally exceeded 0.95 when IFBF was ≥12% and FDM was ≥155 kg in late December and early January. Lactating females had lower IFBF, FDM, pregnancy rates, and later conception dates than nonlactating females. The mean IFBF of females harvested on 1 December was generally 2.3–2.7 percentage points higher than values of females harvested on 31 January within age and lactation categories. There was strong evidence that greater IFBF and FDM, higher pregnancy rates, and earlier conception dates in nonlactating females and all adult females were related to increased June–August precipitation (P < 0.01) during the conception year, but, with the exception of conception date, there was little evidence in lactating females. Greater conception year June–August precipitation (P = 0.04) and greater mean annual IFBF of nonlactating females (P < 0.01), but not conception year IFBF of lactating 60 �females (P = 0.94), were related to higher subsequent September calf:female ratios. There was also strong evidence that earlier mean conception dates and higher pregnancy rates of adult females (P < 0.01) were related to higher calf:female ratios. The only birth year variables at least moderately related to higher calf:female ratios were lower mean IFBF (P = 0.03) and FDM (P = 0.02) of adult females that likely reflected negative lactation effects. Based on our bivariate models, September calves/100 females increased 10.7 calves per 0.1 increase in the annual adult pregnancy rate and 10.9 calves per 10‐cm increase in June–August precipitation during the conception year. Our results indicated that bottom‐up factors related to summer precipitation the previous year and age structure of the adult female population had meaningful effects on September calf:female ratios at Vermejo during our study. We found strong evidence of a nexus among summer precipitation, IFBF, conception dates, pregnancy rates, and following year calf:female ratios in nonlactating females but not in lactating females even though probability of pregnancy was primarily determined by IFBF irrespective of lactation status. Published December 2022. Plant and Mule Deer Responses to Pinyon‐juniper Removal by Three Mechanical Methods Danielle Bilyeu Johnston1 and Charles R. Anderson Jr.2 1 Colorado Parks and Wildlife, Grand Junction, CO, USA 2 Colorado Parks and Wildlife, Fort Collins, CO, USA Citation: Johnston, D. B., and C. R. Anderson Jr. 2023. Plant and mule deer responses to pinyon-juniper removal by three mechanical treatment methods. Wildlife Society Bulletin, In press; DOI: 10.1002/wsb.1421 ABSTRACT Land managers in western North America often reverse succession by removing pinyon (Pinus spp.) and juniper (Juniperus spp.) trees to reduce fire risk and increase forage for wildlife and livestock. Because prescribed fire carries inherent risks, mechanical methods such as chaining, roller‐chopping, and mastication are often used. Mechanical methods differ in cost and the size of woody debris produced, and may differentially impact plant and animal responses. We implemented a randomized, complete block, split‐plot experiment in December 2011 in the Piceance Basin, northwestern Colorado, USA, to compare mechanical methods and to explore seeding (subplot) interactions. We assessed vegetation 1‐, 2‐, 5‐, and 6‐years post‐treatment, and mule deer (Odocoileus hemionus) response via GPS locations 3–8 years post‐treatment. By 2016, treated plots had 3–5 times higher perennial grass cover and ~10 times higher cheatgrass (Bromus tectorum) cover than untreated control plots. Rollerchopped plots had both the highest non‐native annual forb cover, and when seeded, the highest density of bitterbrush (Purshia tridentata), a nutritious shrub used by mule deer. Masticated plots had higher bitterbrush use during summer and fall, leaving less forage available for winter. Days of winter mule deer use from GPS point locations in chained and rollerchopped plots was ~70% higher than in control plots, while winter use in masticated plots was similar to control plots. Mule deer use appears related to a combination of hiding cover, resulting from residual woody debris, and winter forage availability. Roller‐chopped plots provide the best combination of hiding cover and winter forage, but mastication or chaining, applied leaving dispersed security cover, may be better options at large scales or when invasive species concerns exist. Accepted for publication, In Press. 61 �WILDLIFE GENETICS AND DISEASE RESEARCH Complex Evolutionary History of Felid Anelloviruses Simona Kraberger1, Laurel E Serieys2, Cécile Richet3, Nicholas M Fountain-Jones4, Guy Baele5, Jacqueline M Bishop6, Mary Nehring7, Jacob S Ivan8, Eric S Newkirk9, John R Squires10, Michael C Lund3, Seth P Riley11, Christopher C Wilmers12, Paul D van Helden13, Koenraad Van Doorslaer14, Melanie Culver15, Sue VandeWoude7, Darren P Martin16, Arvind Varsani17 1 The Biodesign Center of Fundamental and Applied Microbiomics, School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, 85287, USA. 2 Environmental Studies, University of California, Santa Cruz, CA, 95064, USA; Institute for Communities and Wildlife in Africa, Department of Biological Sciences, University of Cape Town, Private Bag X3, Rondebosch, Cape Town, 7701, South Africa. 3 The Biodesign Center of Fundamental and Applied Microbiomics, School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, 85287, USA. 4 School of Natural Sciences, University of Tasmania, Hobart, 7001, Australia. 5 Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium. 6 Institute for Communities and Wildlife in Africa, Department of Biological Sciences, University of Cape Town, Private Bag X3, Rondebosch, Cape Town, 7701, South Africa. 7 Department of Microbiology, Immunology & Pathology, Colorado State University, Fort Collins, CO, 80523, USA. 8 Colorado Parks and Wildlife, 317 W. Prospect Rd., Fort Collins, CO, 80526, USA. 9 Speedgoat Wildlife Solutions, Missoula, MT, 59801, USA. 10 US Department of Agriculture, Rocky Mountain Research Station, 800 E. Beckwith Ave., Missoula, MT, 59801, USA. 11 Santa Monica Mountains National Recreation Area, National Park Service, Thousand Oaks, CA, 91360, USA. 12 Environmental Studies, University of California, Santa Cruz, CA, 95064, USA. 13 DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research/SAMRC Centre for TB Research/Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, 7505, South Africa. 14 School of Animal and Comparative Biomedical Sciences, The BIO5 Institute, Department of Immunobiology, Cancer Biology Graduate Interdisciplinary Program, UA Cancer Center, University of Arizona, Tucson, AZ, 85724, USA. 15 U.S. Geological Survey, Arizona Cooperative Fish and Wildlife Research Unit, University of Arizona, Tucson, AZ, 85721, USA; School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA. 16 Computational Biology Group, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, 7925, South Africa. 17 The Biodesign Center of Fundamental and Applied Microbiomics, School of Life Sciences, Center for Evolution and Medicine, Arizona State University, Tempe, AZ, 85287, USA; Structural Biology Research Unit, Department of Integrative Biomedical Sciences, University of Cape Town, 7925, Cape Town, South Africa. Citation: Kraberger, S., L. E. Serieys, C. Richet, N. M. Fountain-Jones, G. Baele, J. M. Bishop, M. Nehring, J. S. Ivan, E. S. Newkirk, J. R. Squires, M. C. Lund, S. P. Riley, C. C. Wilmers, P. D. van Helden, K. Van Doorslaer, M. Culver, S. VandeWoude, D. P. Martin, and A. Varsani. 2021. Complex evolutionary history of felid anelloviruses. Virology 562:176–189; doi: 10.1016/j.virol.2021.07.013 ABSTRACT Anellovirus infections are highly prevalent in mammals, however, prior to this study only a handful of anellovirus genomes had been identified in members of the Felidae family. Here we characterise anelloviruses in pumas (Puma concolor), bobcats (Lynx rufus), Canada lynx (Lynx canadensis), caracals (Caracal caracal) and domestic cats (Felis catus). The complete anellovirus genomes (n = 220) recovered from 149 individuals were diverse. ORF1 protein sequence similarity network analysis coupled with phylogenetic analysis, revealed two distinct clusters that are populated by felid-derived anellovirus sequences, a pattern mirroring that observed for the porcine anelloviruses. Of the two-felid dominant anellovirus groups, one includes sequences from bobcats, pumas, domestic cats and an ocelot, and the other includes sequences from caracals, Canada lynx, domestic cats and pumas. Coinfections of diverse anelloviruses appear to be common among the felids. Evidence of recombination, both within and between felid-specific anellovirus groups, supports a long coevolution history between host and virus. Published July 2021 Viral Sequences Recovered From Puma Tooth DNA Reconstruct Statewide Viral Phylogenies Roderick B. Gagne1,2, Simona Kraberger3, Rebekah McMinn1, Daryl R. Trumbo4 , Charles R. Anderson Jr.5, Ken A. Logan6, Mathew W. Alldredge5, Karen Griffin5 and Sue VandeWoude1 1 Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States 2 Department of Pathobiology, Wildlife Futures Program, University of Pennsylvania School of Veterinary Medicine, Kennett Square, PA, United States 3 The Biodesign Center for Fundamental and Applied Microbiomics, Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, United States 4 Department of Biology, Colorado State University, Fort Collins, CO, United States 5 Colorado Parks and Wildlife, Fort Collins, CO, United States 6 Colorado Parks and Wildlife, Montrose, CO, United States 62 �Citation: Gagne, R. B., S. Kraberger, R. McMinn, D. R. Trumbo, C. R. Anderson Jr, K. A. Logan, M. W. Alldredge, K. Griffin, and S. VandeWoude. 2021. Viral sequences recovered from puma tooth DNA reconstruct statewide viral phylogenies. Frontiers in Ecology and Evolution 9:734462. doi: 10.3389/fevo.2021.734462 ABSTRACT Monitoring pathogens in wildlife populations is imperative for effective management, and for identifying locations for pathogen spillover among wildlife, domestic species and humans. Wildlife pathogen surveillance is challenging, however, as sampling often requires the capture of a significant proportion of the population to understand host pathogen dynamics. To address this challenge, we assessed the ability to use hunter collected teeth from puma across Colorado to recover genetic data of two feline retroviruses, feline foamy virus (FFV) and feline immunodeficiency virus (FIVpco) and show they can be utilized for this purpose. Comparative phylogenetic analyses of FIVpco and FFV from tooth and blood samples to previous analyses conducted with blood samples collected over a nine-year period from two distinct areas was undertaken highlighting the value of tooth derived samples. We found less FIVpco phylogeographic structuring than observed from sampling only two regions and that FFV data confirmed previous findings of endemic infection, minimal geographic structuring, and supported frequent cross-species transmission from domestic cats to pumas. Viral analysis conducted using intentionally collected blood samples required extensive financial, capture and sampling efforts. This analysis illustrates that viral genomic data can be cost effectively obtained using tooth samples incidentally-collected from hunter harvested pumas, taking advantage of samples collected for morphological age identification. This technique should be considered as an opportunistic method to provide broad geographic sampling to define viral dynamics more accurately in wildlife. Published August 2021 63 �JOURNAL OF WILDLIFE MANAGEMENT EDITORIAL EDITORS MESSAGE: A Perspective on the Journal of Wildlife Management Douglas H. Johnson1, Charles Anderson Jr.2, Roger D. Applegate3, Larissa Bailey4, Evan Cooch5, John Fieberg6, Alan B. Franklin7, R. J. Gutierrez6, Karl V. Miller8, James D. Nichols9, Neal D. Neimuth10, David Otis4, Christine A. Ribic11, Mary M. Rowland12, Terry L. Shaffer13 1 USGS, Northern Prairie Wildlife Research Center, Dept. of Fisheries, Wildlife and Conservation Biology, University of Minnesota 2 Mammals Research Section, Colorado Parks and Wildlife 3 Division of Wildlife and Forestry, Tennessee Wildlife Resource Agency 4 Dept. of Fisheries, Wildlife and Conservation Biology, Colorado State University 5 Dept. of Natural Resources and the Environment, Cornell University 6 Dept. of Fisheries, Wildlife and Conservation Biology, University of Minnesota 7 USDA/APHIS/WS National Wildlife Research Center 8 Warnell School of Forestry and Natural Resources, University of Georgia 9 U.S. Geological Survey, Eastern Ecological Science Center 10 U.S. Fish and Wildlife Service, Habitat and Population Evaluation Team 11 U.S. Geological Survey, Wisconsin Cooperative Wildlife Research Unit, Department of Forest and Wildlife Ecology, University of Wisconsin 12 U.S. Forest Service, Pacific Northwest Research Station 13 U.S. Geological Survey, Northern Prairie Wildlife Research Center Citation: Johnson, D. H., C. Anderson Jr., R. D. Applegate, L. Bailey, E. Cooch, J. Fieberg, A. B. Franklin, R. J. Gutierrez, K. V. Miller, J. D. Nichols, N. D. Niemuth, D. Otis, C. A. Ribic, M. M. Rowland, and T. L. Shaffer. 2021. Editorial Message: A perspective on the Journal of Wildlife Management. Journal of Wildlife Management 85:1305–1308; DOI: 10.1002/jwmg.22110 CONCLUSIONS A first principle of marketing a product, such as a journal, is identifying its target audience. Historically JWM was oriented toward on‐the‐ground and harvest managers. We suspect that over the years the journal has become more read by researchers and students and less used by actual managers. An argument could be made in favor of changing its title to the Journal of Wildlife Science, but much history would be lost causing a reset in the impact factor rating. We believe that both audiences can be served, but it will not be easy. Collectively, our group offers a wide set of perspectives stemming from our personal experiences publishing in many journals including JWM, but we certainly do not reflect the entire spectrum of members of TWS. Therefore, we offer the following conclusions in support of our general comments above (refer to publication) with the expectation that others may either endorse our ideas or refute them. All of us have long held high regard for our society's primary journal. Yet we also believe that JWM could be improved. Some of our suggestions are easily implemented (e.g., focus more on facilitating author submissions than on the format of papers—layout and format of a journal are never as important as its content); others will be more challenging (e.g., deciding if the focus of JWM should be on game species because other journals provide more options to publish nongame research). In TWS, a possible way forward is for leadership to assess whether new directions in emphasis for JWM are warranted. But even if new directions are desired, given a more thorough evaluation than we have provided, we believe there is a perception among many potential authors that structural impediments discourage submission to JWM. Therefore, we hope our comments are taken in the context with which we wrote them: to improve the quality and stature of JWM. All decisions, including any recommended changes to JWM, should be guided by objectives. For example, if our primary objective is to increase the impact factor of JWM, then we might take certain actions, whereas if we want to increase the value of JWM to managers we might do something very different. If we prefer a compromise that includes both objectives, perhaps unequally weighted, then our actions would again differ from those that focus only on one of them. We believe that any recommendations for changes to JWM must be preceded by a clear statement of what we would like these changes to accomplish. We authors differ in our opinions about the importance of journal impact factor, with some of us concerned that it is too low and others believing that it does not closely relate to the use of the journal. This variation suggests that the TWS membership should be involved in developing the objectives that are required to guide decisions about any changes to JWM. Published September 2021 64 ���� https://cpw.cvlcollections.org/files/original/c26870b49284faa45f5919f65fe04860.pdf 1ea2bd7e8659ff6fcf20f2e8711ef2f8 PDF Text Text C O L O R A D O P A R K S & W I L D L I F E Wildlife Research Reports MAMMALS – JANUARY 2024 cpw.state.co.us ��WILDLIFE RESEARCH REPORTS JANUARY–DECEMBER 2023 MAMMALS RESEARCH PROGRAM COLORADO PARKS AND WILDLIFE Research Center, 317 W. Prospect, Fort Collins, CO 80526 The Wildlife Reports contained herein represent preliminary analyses and are subject to change. For this reason, information MAY NOT BE PUBLISHED OR QUOTED without permission of the Author(s). By providing these summaries, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. i �EXECUTIVE SUMMARY This Wildlife Research Report represents summaries (≤5 pages each with tables and figures) of wildlife research projects conducted by the Mammals Research Section of Colorado Parks and Wildlife (CPW) during 2023. These research efforts represent long-term projects (4–10 years) in various stages of completion addressing applied questions to benefit the management and conservation of various mammal species in Colorado. In addition to the research summaries presented in this document, more technical and detailed versions of most projects (Annual Federal Aid Reports) and related scientific publications that have thus far been completed can be accessed on the CPW website at http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx or from the project principal investigators listed at the beginning of each summary. Current research projects address various aspects of wildlife management and ecology to enhance understanding and management of wildlife responses to habitat alterations, human-wildlife interactions, and investigating improved approaches for wildlife population monitoring and management. The Nongame Mammal Conservation Section addresses ongoing monitoring of lynx in the San Juan mountain range and preliminary results addressing influence of forest management practices on snowshoe hare density in Colorado. The Ungulate Management and Conservation Section includes a pilot evaluation of moose and elk behavioral response to recent wolf establishment in North Park, Colorado, an evaluation of factors influencing elk calf recruitment, two studies addressing elk response to human recreation, and a summary of publication results addressing Colorado moose ecology and management from 2013–2020. The Predatory Mammal Management and Conservation Section describes onging research addressing bobcat population dynamics and density estimation, mule deer survival and cougar conflict response to cougar population manipulation, and evaluation of accelerometer collars and methods development for domestic cattle to eventually address cattle response to wolf activity during wolf establishment. The Support Services section provides annual updates from the CPW Research Library and ongoing database development from the Research and Species Conservation Database Analyst/Manager. In addition to the ongoing project summaries described above, Appendix A includes publication abstracts (<1 page summaries) completed by CPW research staff since December 2022. These scientific publications provide results from recently completed CPW research projects and other collaborations with universities and wildlife management agencies. Topics addressed include small mammal species ecology and conservation (impacts of spruce beetle outbreaks on showshoe hares and red squirrels), ungulate ecology and management (genomic correlates for migratory direction in mule deer and plant and mule deer responses to 3 mechanical treatment methods), and approaches for wildlife population monitoring (multistage hierarchical capture–recapture models, evaluation of camera model and alignment for pairedcamera stations, an approach to select surrogate species for connectivity conservation, and an assessment of intensity of use to understand animal movement behavior). We have benefitted from numerous collaborations that support these projects and the opportunity to work with and train wildlife technicians and graduate students that will likely continue their careers in wildlife management and ecology in the future. Research collaborators include the CPW Wildlife Commission, statewide CPW personnel, Federal Aid in Wildlife Restoration, Colorado State University, University of Wyoming, Western Illinois University, Southern Illinois University, Trent University, University of Rhode Island, U.S. Bureau of Land Management, U.S. Forest Service, CPW big game auction-raffle grants, Species Conservation Trust Fund, Great Outdoors Colorado, CPW Habitat Partnership Program, Rocky Mountain Elk Foundation, and numerous private land owners providing access to support field research projects. ii �STATE OF COLORADO Jared Polis, Governor DEPARTMENT OF NATURAL RESOURCES Dan Gibbs, Executive Director PARKS AND WILDLIFE COMMISSION Dallas May, Chair.…………………………………………………………........................................ Lamar Richard Reading, Vice Chair...……………………………………………………………………… Denver Karen Bailey, Secretary……………………………….………….….………………....................... Boulder Jessica Beaulieu………………………………………………………………………………………Denver Marie Haskett………………………………………………………………………………………... Meeker Betsy Blecha……………………………………………………………………………………………Wray Jack Murphy…………………………………………………………………………………………. Aurora Gabriel Otero………………………………………………………………………………………….. Fruita Duke Phillips IV…………………………………………………………………………...Colorado Springs Gary T. Skiba………………………………………………………………………………………. Durango James Jay Tutchton……………………………………………………………………………………. Hasty Eden Vardy…………………………………………………………………………………………… Aspen Kate Greenberg, Dept. of Agriculture, Ex-officio….………………………………..…….……….. Durango Dan Gibbs, Executive Director, Ex-officio……….…………………...………………….……..........Denver DIRECTOR’S EXECUTIVE MANAGEMENT TEAM Jeff Davis, Director Heather Dugan, Deputy Director Kelly Keamerer, Reid DeWalt, Justin Rutter, Katie Lanter, Frank McGee, Cory Chick, Travis Black, Mark Leslie, Ty Petersburg MAMMALS RESEARCH STAFF Chuck Anderson, Mammals Research Leader Mat Alldredge, Senior Wildlife Researcher Eric Bergman, Senior Wildlife Researcher Ellen Brandell, Wildlife Researcher Shane Frank, Wildlife Researcher Michelle Gallagher, Program Assistant Karen Hertel, Research Librarian Jake Ivan, Senior Wildlife Researcher Nathaniel Rayl, Wildlife Researcher Ben Wasserstein, Database Manager/Analyst iii �TABLE OF CONTENTS MAMMALS WILDLIFE RESEARCH REPORTS NONGAME MAMMAL CONSERVATION CANADA LYNX MONITORING IN COLORADO 2022-2023 by J. Ivan, T. Brtis, and L. McCurdy…………………………………………………………………………………………... 2 INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO by J. Ivan……………………..7 UNGULATE MANAGEMENT AND CONSERVATION PILOT EVALUATION OF PREY DISTRIBUTION AND MOOSE RECRUITMENT FOLLOWING EXPOSURE TO WOLF PREDATION RISK IN NORTH PARK, COLORADO by E. Bergman and E. Brandell………………………………………………………………...... 11 EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO by N. Rayl, M. Alldredge, and C. Anderson….………………………………………………………... 14 RESPONSE OF ELK TO HUMAN RECREATION AT MULTIPLE SCALES: DEMOGRAPHIC SHIFTS AND BEHAVIORALLY MEDIATED FLUCTUATIONS IN ABUNDANCE by E. Bergman and N. Rayl…………………………………………………….. 19 SPATIOTEMPORAL EFFECTS OF HUMAN RECREATION ON ELK BEHAVIOR: AN ASSESSMENT WITHIN CRITICAL TIME STAGES by N. Rayl, E. Bergman, and J. Holbrook…………………………………………………………………………………………. 22 EVALUATION AND INCORPORATION OF LIFE HISTORY TRAITS, NUTRITIONAL STATUS, AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO by E. Bergman……………………………………………………………………. 25 PREDATORY MAMMAL MANAGEMENT AND CONSERVATION BOBCAT POPULATION DYNAMICS AND DENSITY ESTIMATION by S. Frank, J. Ivan, M. Vieira, and J. Runge.…................................................................................................................... 31 MULE DEER POPULATION RESPONSE TO COUGAR POPULATION MANIPULATION by M. Alldredge, A. Vitt, B. Lamont, T. Woodward, J. Grigg, and C. Anderson…………………... 33 EVALUATION OF ACCELEROMETER COLLARS AND METHODS DEVELOPMENT FOR DOMESTIC CATTLE by E. Brandell……………………………………………………………36 SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT 2023 by K. Hertel………………………………. 40 RESEARCH DATABASE SUPPORT SERVICES by B. Wasserstein…………………………. 41 iv �APPENDIX A. MAMMALS RESEARCH PUBLICATION ABSTRACTS SMALL MAMMAL ECOLOGY AND CONSERVATION……………………………………. 45 UNGULATE ECOLOGY AND MANAGEMENT....................................................................... 46 APPROACHES FOR WILDLIFE POPULATION MONITORING............................................. 47 v �NONGAME MAMMAL CONSERVATION CANADA LYNX MONITORING IN COLORADO 2022-2023 INFLUENCE OF FOREST MANAGEMENT ON SNOWSHOE HARE DENSITY IN LODGEPOLE AND SPRUCE-FIR SYSTEMS IN COLORADO 1 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Canada lynx monitoring in Colorado 2022 – 2023 Period Covered: December 1, 2022 − April 30, 2023 Principal Investigators: Jake Ivan, Jake.Ivan@state.co.us; Tim Brtis; Lori McCurdy All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In an effort to restore a viable population of Canada lynx (Lynx canadensis) to the southern portion of their former range, 218 individuals were reintroduced into Colorado from 1999−2006. In 2010, the Colorado Division of Wildlife (now Colorado Parks and Wildlife [CPW]) determined that the reintroduction effort met all benchmarks of success and that the population of Canada lynx in the state was apparently viable and self-sustaining. In order to track the persistence of this new population and thus determine the long-term success of the reintroduction, a minimally-invasive, statewide monitoring program is required. From 2014−2023 CPW initiated a portion of the statewide monitoring scheme described in Ivan (2013) by completing surveys in a random sample of monitoring units (n = 50) from the San Juan Mountains in southwest Colorado (n = 179 total units; Figure 1). During the 2022−2023 winter, personnel from CPW and USFS completed the ninth year of monitoring work on this same sample. Thirteen units were sampled via snow-tracking surveys conducted between December 1 and March 31. On each of 1–3 independent occasions, survey crews searched roadways (snow-covered paved roads and logging roads) and trails for lynx tracks. Crews searched the maximum linear distance of roads possible within each survey unit given safety and logistical constraints. Each survey covered a minimum of 10 linear kilometers (6.2 miles) distributed across at least 2 quadrants of the unit. Thirty-five units could not be surveyed via snow tracking. Instead, survey crews deployed 4 passive infrared motion cameras in each of these units during fall 2022. Cameras were lured with visual attractants and scent lure to enhance detection of lynx in the area. Cameras were retrieved during summer or fall 2023 and all photos were archived and viewed by at least 2 observers to determine species present in each. Camera data were then binned such that each of 10 15-day periods from December 1 through April 30 was considered an ‘occasion,’ and any photo of a lynx obtained during a 15-day period was considered a ‘detection’ during that occasion. Surveyors covered 730 km during snow tracking surveys and detected 10 lynx tracks at 5 units (Table 1). This is a slight increase over the program-low of 6 tracks in 4 units observed in 2021–22. Lynx were detected via camera sampling in only one unit during the 2023–23 survey season, which is two fewer units than the previous program low for cameras, which was observed in 2020–21. Snow depths during the 2022–23 season were among the highest ever recorded and a number of cameras were buried for days to weeks, which could have resulted in fewer lynx detections. Also, after 9 seasons of sampling, perhaps resident individuals are developing fatigue to the lures used on the project. In response to the potential for lure fatigue, 117 cameras were passively (i.e., no lure) deployed along roads, trails, and other potential travel routes during fall 2023 in 16 camera units that have had lynx detections in the past. Deployments followed protocols established by (King et al. 2020) and (Anderson et al. 2023). These cameras will be retrieved in summer 2024. Detections at these deployments, and not at traditional camera stations in the same unit, would support the notion that lynx are exhibiting lure fatigue, and future 2 �sampling could switch to passive sampling to capture lynx moving along natural travel routes rather than luring them to a predetermined camera set. Given the program-low in snowtracking detections in 2021– 22, and program-low in camera detections this season (2022–23), it is also possible that lynx distribution declined sharply over the past two survey seasons, which would indicate a decline in the population as well. Lynx were once again detected during snowtrack surveys at Molas Pass and South Mineral, after having gone undetected there in 2021–22. Cameras picked up lynx near Wolf Creek Pass for only the 3rd time in 9 years of sampling, but failed to detect lynx at Rio Grand Reservoir, Lizard Head Pass, and Conejos Peak for only the 2nd or 3rd time since the monitoring program began (Figure 1). We used the R package (R Development Core Team 2018) ‘RMark’ (Laake 2018) to fit multipleseason (i.e., “dynamic”) occupancy models (MacKenzie et al. 2006) to our survey data using program MARK (White and Burnham 1999). Thus, we estimated the derived probability of a unit being occupied (ψ), or used, by lynx over the course of the winter, along with the probability of detecting a lynx (p) given that the unit was occupied, the probability a unit that was unused in one year was used the next (i.e., “local colonization,” γ), and the probability a used unit became unused from one year to the next (i.e., “local extinction,” ε). For each model we fit for the analysis, we specified that the initial ψ in the time series should be a function of the proportion of the unit that is covered by spruce/fir forest – the single most important and consistent predictor of ψ in past analyses. For sake of comparison we fit a base model in which p was specified to be constant for the duration of the survey. However, based on previous work, we considered several other structures for p we anticipated would fit better. We fit models that specified 1) p could vary by survey method (i.e., detection could be different for cameras compared to snowtracking), 2) p could be higher during breeding season when lynx tend to move more and are therefore more likely to be detected by track or at a camera, and 3) p for cameras deployed from 2017–21 could be different than p for other years due to the lure substitution. Additionally we fit a model in which the effect of breeding season was only allowed to act on cameras, not snowtracking. We allowed annual estimates of ε and γ to be different each year (i.e., assuming occupancy dynamics were not random but instead dependent on the year previous and the population is not at equilibrium), which allowed derived ψ to vary as freely as possible given the data. We used Akaike’s Information Criterion (AIC), adjusted for small sample size (Burnham and Anderson 2002) to identify the best-fitting model from this small set. Ultimately, we fit a linear model through the time series of ψ estimates to estimate the slope of the trend in occupancy through time. Ideally we would test other predictions of lynx occupancy to see, for instance, if colonization or extinction were influenced by bark beetles, fire, or the presence of competitors or prey species. However, we do not currently have enough data to test these predictions in addition to assessing trend, which is the highest priority. As has been the case since the inception of our monitoring program, the proportion of the sample unit covered by spruce-fir forest was positively associated with the initial occupancy estimate in the time series. Even though local colonization and extinction were allowed to vary freely from year to year, annual estimates were near zero and varied little (ε = 0.00–0.11; γ = 0.00–0.10) up until the most recent 2 seasons when extinction probability was high (ε21–22 = 0.36, SE = 0.18; ε22–23 = 0.73, SE = 0.17). Accordingly, derived occupancy was relatively stable across years (ψ = 0.25–0.34), but dropped to the lowest level observed to date this past season (ψ = 0.11, SE = 0.05). The slope of the trend in occupancy through time was slightly negative but not statistically different from zero (β = -0.007, SE = 0.01; Figure 2). Similar to previous years, detection probability was relatively high for snow tracking surveys (p = 0.65, SE = 0.06), lower for camera surveys (p = 0.22, SE = 0.03) using Pikauba, and lowest for camera surveys utilizing Violator 7 (p = 0.06, SE = 0.02). We estimated that 11% of the sample units in the San Juan’s were occupied by lynx (95% confidence interval: 2–20%) during 2022–23 (Figure 2). 3 �Table 1. Summary statistics from snow tracking effort. Lynx DNAb 8 Km Surveyed (Total) 884 Mean Km Surveyed per Visit 20.1 #CPW Personnelc 30 #USFS Personnelc 13 Season 2014-2015 #Units Surveyed 18 #Units with Lynx 7 2015-2016 17 7 14 9 6 987 21.9 23 6 2016-2017 16 8 13 7 5 703 18.0 20 8 2017-2018 14 7 9 3 1 578 19.3 14 5 2018-2019 14 6 8 2 1 510 19.6 16 5 2019-2020 14 7 11 3 2 640 19.4 15 3 2020-2021 15 9 14 12 7 790 18.8 17 3 2021-2022 13 4 6 5 4 692 18.7 11 3 2022-2023 15 5 10 9 7 730 18.3 15 2 #Lynx Tracks 12 #Genetic Samplesa 8 Number of genetic samples (scat, hair, or eDNA) collected via backtracking putative lynx tracks b Number of genetic samples that came back positive for Lynx c Number of staff that participate in the annual effort a Table 2. Summary statistics from camera effort. Season 2014-2015 #Units Surveyed 31 2015-2016 31 2016-2017 33 2017-2018 35 2018-2019 35 2019-2020 36 2020-2021 35 2021-2022 35 2022-2023 35 #Units With Lynx #Photos (Total) #Photos (Lynx) #Cameras With Lynx 7 7 6 5 6 4 3 5 1 133,483 101,534 168,705 173,279 201,782 706,074 347,868 576,288 531,083 184 455 251 90 59 36 36 116 4 11 10 10 8 9 4 3 7 1 4 #CPW Personnel 46 #USFS Personnel 12 33 9 29 9 35 8 31 7 29 6 23 5 23 4 31 3 �a) b) Figure 1. Lynx monitoring results for a) the current sampling season (2022–2023) and b) the cumulative monitoring effort (2014–2023), San Juan Mountains, southwest Colorado. Colored units (n = 50) depicted here are those selected at random from the population of units (n = 179) encompassing lynx habitat in the San Juan Mountains. Lynx were detected in 6 units in 2022−2023 and 25 units cumulatively since monitoring began in 2014−2015. 5 �Figure 2. Occupancy estimates (Ψ) and trend (including 95% CI) for Canada lynx in the San Juan Mountains, southwest Colorado. LITERATURE CITED Anderson, A. K., J. S. Waller, and D. H. Thornton. 2023. Canada lynx occupancy and density in Glacier National Park. Journal of Wildlife Management e22383:1–24. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. 2nd ed. Springer, New York, New York, USA. Ivan, J. S. 2013. Statewide monitoring of Canada lynx in Colorado: evaluation of options. Pages 15–27 in Wildlife research report - mammals. Colorado Parks and Wildlife., Fort Collins, Colorado, USA. http://cpw.state.co.us/learn/Pages/ResearchMammalsPubs.aspx. King, T. W., C. Vynne, D. Miller, S. Fisher, S. Fitkin, J. Rohrer, J. I. Ransom, and D. Thornton. 2020. Will lynx lose their edge? Canada lynx occupancy in Washington. Journal of Wildlife Management 84:705–725. Laake, J. L. 2018. Package “RMark”: R Code for Mark Analysis. Version 2.2.5. https://cran.rproject.org/web/packages/RMark/RMark.pdf. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Oxford, United Kingdom. R Development Core Team. 2018. No Title. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplem:S120–S138. 6 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Influence of forest management on snowshoe hare density in lodgepole and spruce-fir systems in Colorado Period Covered: January 1, 2022 − December 31, 2023 Principal Investigators: Jake Ivan, Jake.Ivan@state.co.us; All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. Understanding and monitoring snowshoe hare (Lepus americanus) density in Colorado is imperative because hares comprise 70% of the diet of the state-endangered, federally threatened Canada lynx (Lynx canadensis; U.S. Fish and Wildlife Service 2000, Ivan and Shenk 2016). Forest management is an important driver of snowshoe hare density, and all National Forests in Colorado are required to include management direction aimed at conservation of Canada lynx and snowshoe hare as per the Southern Rockies Lynx Amendment (SRLA; https://www.fs.usda.gov/detail/r2/landmanagement/ planning/?cid= stelprdb5356865). At the same time, Forests in the Region are compelled to meet timber production obligations. Such activities may depress snowshoe hare density, improve it, or have mixed effects dependent on the specific activity and the time elapsed since that activity was initiated. Here I describe a sampling scheme to assess impacts of common forest management techniques on snowshoe hare density in both lodgepole pine (Pinus contorta) and spruce-fir (Picea engelmannii – Abies lasiocarpa) systems in Colorado. To select forest stands for sampling, I first used U. S. Forest Service (USFS) spatial data to delineate all spruce-fir and lodgepole pine stands (stratum 1) on USFS land in Colorado, and identified all of the management activities that have occurred in each stand over time. With consultation from the USFS Region 2 Lynx-Silviculture Team and USFS Rocky Mountain Research Station, I then grouped relevant forest management activities (stratum 2) into 4 broad categories: even-aged management, uneven-aged management, thinning, and unmanaged controls. I wanted to assess both the immediate and long-term impacts of management on hare densities. Therefore, when selecting stands for sampling, I took the additional step of binning the date of the most recent management activity into 2decade intervals (i.e., 0-20, 20-40, and 40-60 years before 2018). I then selected a spatially balanced random sample of 5 stands within each combination of forest type × management activity × time interval. This design ensured that I sampled the complete gradient of time since implementation for each management activity of interest in each forest type of interest. There is no notion of “completion date” for unmanaged controls, so I simply sampled 10 randomly selected stands from this combination. Also, uneven-aged lodgepole pine treatments are rare, so I did not sample that combination (Figure 1). During summer 2018, I established n = 50 1-m2 permanent circular plots within each of the stands selected for sampling. Plot locations within each stand were selected in a spatially balanced, random fashion. Technicians cleared and counted snowshoe hare pellets in each plot as they established them. These same plots were re-visited and re-counted during summers 2019 and 2023. In addition to sampling the previously cleared plots from 2018, technicians were able to install plots at 2 more replicate sites for each combination of forest type × management activity × time interval during 2019. In 2021 and 2022, we sampled vegetation metrics in each stand to help account for extraneous noise in the data and allow us 7 �to better assess the effects of the treatments themselves. A handful of initially selected stands were reclassified or excluded during 2019–2022 because ground-truthing and/or vegetation metrics revealed they did not actually fit in the stratum for which they were selected. New stands were sampled in their place by pulling the next one from the spatially balanced list. Similarly, 12 new stands were selected to replace those that burned during the 2020 fire season. Currently, inference is based on n = 130 total stands. Finally, prior to the 2023 field season, I computed the sampling variance of the pellet count for each time interval within each treatment. We sampled additional stands in the 3 most variable bins in an effort to reduce variability and improve our understanding of snowshoe hare response to these treatments. Pellet information from cleared plots is more accurate than that from uncleared plots because uncleared plots usually include pellet accumulation across several years (Hodges and Mills 2008). The degree to which previous years are represented can depend on local weather conditions, site conditions at the plot, and variability in actual snowshoe hare density over previous winters. Data from cleared plots necessarily reflects hare activity from the previous 12 months, and tracks true density more closely. Therefore, I focused the current analysis on the 2019–23 data from previously cleared plots. For each forest type × management activity combination, I plotted mean pellet counts against “year since activity,” then fit a curve (e.g., quadratic function) through the data (Figure 2). Results from this preliminary analysis suggest that on average the highest snowshoe hare densities typically occur in unmanaged spruce-fir forests, and that unmanaged spruce-fir forests are estimated to have more than twice the relative hare density of unmanaged lodgepole pine forests (Figure 2). For both forest types, the fitted line suggests that even-aged management (e.g., clearcutting), immediately depresses relative hare density to near zero, but density rebounds and peaks 20-40 years after management before declining again (lodgepole systems) or leveling off (sprue-fir systems) 40-60 years after. Estimated peak hare densities after even-aged management in lodgepole systems tend to be higher than the control condition. However, in spruce-fir systems the estimated fitted line is flatter and peak densities fell short of the control condition. In both forest types, thinning (which often occurs 20-40 years after stands undergo even-aged management, especially in lodgepole) immediately depresses hare densities. In spruce-fir stands, densities were estimated to slowly recover through time in nearly linear fashion. However, they follow a peaked response in lodgepole pine, similar to the response to even-aged management. Uneven-aged management of spruce-fir forests results in immediate depression of relative hare density, which then recovers back to pre-treatment levels approximately 40 years after the treatment. Literature Cited Hodges, K. E., and L. S. Mills. 2008. Designing fecal pellet surveys for snowshoe hares. Forest Ecology and Management 256:1918-1926. Ivan, J. S., and T. M. Shenk. 2016. Winter diet and hunting success of Canada lynx in Colorado. The Journal of Wildlife Management 80:1049-1058. U.S. Fish and Wildlife Service. 2000. Endangered and threatened wildlife and plants: determination of threatened status for the contiguous U.S. distinct population segment of the Canada lynx and related rule, final rule. Federal Register 65:16052–16086. 8 �Figure 1. Location of all stands (n = 130) resampled for snowshoe hare pellets, June-September 2023. Figure 2. Fitted quadratic function (white line) and 95% CI (shaded polygon) relating pellet counts (i.e., relative snowshoe hare density) to time elapsed since treatment for each forest type × management activity combination. Dotted lines indicate the mean pellets/plot for the unmanaged controls for each forest type. 9 �UNGULATE MANAGEMENT AND CONSERVATION PILOT EVALUATION OF PREY DISTRIBUTION AND MOOSE RECRUITMENT FOLLOWING EXPOSURE TO WOLF PREDATION RISK IN NORTH PARK, COLORADO EVALUATING FACTORS INFLUENCING ELK RECRUITMENT IN COLORADO RESPONSE OF ELK TO HUMAN RECREATION AT MULTIPLE SCALES: DEMOGRAPHIC SHIFTS AND BEHAVIORALLY MEDIATED FLUCTUATIONS IN ABUNDANCE SPATIOTEMPORAL EFFECTS OF HUMAN RECREATION ON ELK BEHAVIOR: AN ASSESSMENT WITHIN CRITICAL TIME STAGES EVALUATION AND INCORPORATION OF LIFE HISTROY TRAITS, NUTRITIONAL STATUS, AND BROWSE CHARACTERISTICS IN SHIRA’S MOOSE MANAGEMENT IN COLORADO 10 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Pilot evaluation of prey distribution and moose recruitment following exposure to wolf predation risk in North Park, Colorado Period Covered: January 1, 2023 – December 31, 2023 Principal Investigators: Eric Bergman, eric.bergman@state.co.us; Ellen Brandell, ellen.brandell@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. During November 2020, Colorado voters passed Proposition 114 (subsequently codified as Colorado Revised Statue 33-2-105.8), which directed Colorado Parks and Wildlife (CPW) and the CPW Wildlife Commission to develop a gray wolf (Canis lupus) reintroduction and management plan for Colorado by the end of 2023 (CPW 2023). Wolves are a native species to Colorado and prior to westward European expansion they occurred throughout the Rocky Mountains and into Colorado’s eastern plains (Feldhamer et al. 2003). Since the 1940s, wolf presence in Colorado has been sporadic (Warren 1942, Lechleitner 1969, Armstrong et al. 2011, CPW 2023). Beginning in the early 2000s, CPW documented occasional wolf presence in Colorado (Colorado Parks and Wildlife 2021), primarily in North Park. During the summer of 2021, a pack comprised of 2 adults and 6 pups was observed in North Park. In December 2023, CPW introduced 10 wolves into the state from Oregon, fulfilling the December 31, 2023 deadline set in CRS 33-2-105.8. Between immigration, reintroduction, and reproduction, wolves will become a consistent feature on Colorado’s landscape, and specifically in North Park. The return of wolves to Colorado’s landscape has already generated interest in future research projects. Between the 1940s and present day, and largely in the absence of wolves, Colorado’s ungulate prey populations (i.e., elk (Cervus americanus), mule deer (Odocoileus hemionus), and moose (Alces alces) adapted to many changes. These changes included successional change in vegetation, increases and reductions in competition with other native herbivores and livestock, novel diseases, predation from mountain lions (Puma concolor), black bears (Ursus americanus), bobcats (Lynx rufus) and coyotes (Canis latrans), but also increased human activity, human disturbance, and large increases in human infrastructure. Moose experienced deliberate management transplants between the late 1970s (Denney 1976) and mid-2000s. By 2022, Colorado’s moose population was estimated to be 3,000–3,500 animals (CPW, unpublished data). Similarly, during the 1940s it was believed there were 45,000 elk in Colorado (Swift 1945) and population growth during the next 6–7 decades led to a peak of ~300,000 animals during the late 1990s and early 2000s (CPW, unpublished data). This research is generally focused on predator-prey dynamics and how wolves will influence wild prey. Specifically, this research will measure prey survival, productivity, and distribution. To supplement survival and spatial data collected from moose during 2013–2019 (Bergman 2022), we initiated capture and collaring efforts of cow and calf moose during the winter of 2021–2022. These efforts demonstrated that moose calf abundance and subsequent moose calf density in North Park were insufficient to accommodate the necessary sample size for the initial study design of this project. Historically modeled estimates for the North Park moose herd suggest it is comprised of 600–800 animals. Sex and age distribution data from this herd simultaneously indicate there are ~70 bulls/100 cows and ~52 calves/100 cows, thereby lending evidence that there are ~140–190 moose calves in North Park. However, it is likely 11 �that >50% of these calves reside on private lands during winter, making their access for capture purposes logistically difficult. Accordingly, there are likely only ~70–95 calves available on public land, of which CPW would need to capture 65%-85% to meet sample size requirements. Capturing such a large proportions of this calf population is both logistically and financially difficult and preliminary efforts in North Park provided evidence that it would be infeasible to capture 60 moose calves each winter. However, capture efforts of cow moose between 2013–2019 (Bergman 2022) and again during the winter of 2021–2022 provided evidence of adequate densities to accommodate robust capturing and collaring efforts, thereby presenting alternative opportunities to estimate calf survival. Advancements in satellite collar technology make it feasible for researchers to attain location data from moose that were collected only a few hours earlier. When coupled with VHF capabilities, researchers have the ability to quickly relocate and observe animals. For the purposes of this study, this technology will allow researchers to observe cow moose, but also observe if cow moose are accompanied by a calf (<12 months old). Repeated observations of cows and calves in this manner, and gathered at key points in time, will allow researchers to approximate calf survival by quantifying the decay in calf/cow ratios from birth to the yearling age class (Lukacs et al. 2004). While these data will not provide causespecific calf mortality estimates, they will improve population models that inform moose ecology and harvest management decision making for the North Park moose herd. To implement this alternative approach to estimating calf survival, a total of 80 cow moose will be collared in North Park. In addition to the previously collared moose, 65 moose were collared for the first time in February 2023. Collars were be deployed in a spatially balanced manner, with approximately 40 collars on both the northern and southern halves of North Park. Calf-at-heel surveys were conducted in June and December 2023. 92% and 71% of moose with active collars were observed in the June and December surveys, respectively. Preliminary calf-at-heel ratios were 0.63 and 0.43 calves/cow during the first two surveys. Further analysis and estimation of monthly and annual calf survival rates will be done in the future when all data have been collected. There was some collar failure over the year, which effectively reduces sample size due to inability to locate collared moose during surveys. We plan to collar an additional 5–10 moose in the winter 2023–2024 to meet our desired sample size for calf-at-heel surveys. Data collected from cow moose during 2022 did not deviate from data collected during 2013–2019. Between 2012–2022 survival of cow moose ranged from 91.2%–94.8%. During the same period, pregnancy rates of moose ranged from 54.8%–88.0%. To expand this research to include additional prey species, 40 cow elk were collared in February 2023. These elk will serve as sentinel animals that will allow researchers to quantify group size behavior, spatial distribution, and habitat use, relative to any known wolf activity. To collect these data, we aimed to obtain aerial visual observations of all collared elk on a monthly basis and record the habitat type they occurred in and the size of the elk group they resided in. In addition to estimating group size from the air, we took photographs, allowing us to count elk in groups. We conducted seven aerial surveys from March to December, 2023, and located 50% of collared elk per flight on average. This resulted in 9–19 unique elk groups observed per survey. We will continue approximately monthly elk surveys in addition to the continual locational data collection on GPS collars. Six collared elk died over the year, therefore we plan to collar elk in the winter 2023–2024 to retain our desired sample size of 40 elk. Literature Cited Armstrong, D. M., J. P. Fitzgerald, and C. A. Meaney. 2011. Mammals of Colorado, 2nd ed. University Press of Colorado, Boulder, USA. Colorado Parks and Wildlife. 2023. Colorado wolf restoration and management plan. Denver, USA. Denney, R. N. 1976. A proposal for the reintroduction of moose into Colorado. Colorado Division of Wildlife planning document. 12 �Feldhamer, G. A., B. C. Thompson, and J. A. Chapman. 2003. Wild mammals of North America: biology, management, and conservation. JHU Press, Baltimore, Maryland, USA. Lechleitner, R. R. 1969. Wild mammals of Colorado: their appearance, habits, distribution, and abundance. Pruett Publ. Co., Boulder, Colorado, USA. Swift, L. W. 1945. A partial history of the elk herds of Colorado. Journal of Mammalogy 26:114–119. Warren, E. R. 1942. The mammals of Colorado: their habits and distribution, 2nd (revised) ed. Univ. Oklahoma Press, Norman, USA. 13 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluating factors influencing elk recruitment in Colorado Period Covered: January 1, 2023-December 31, 2023 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Mat Alldredge, mat.alldredge@state.co.us; Chuck Anderson, chuck.anderson@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. In Colorado, elk (Cervus canadensis) are an important natural resource that are valued for ecological, consumptive, aesthetic, and economic reasons. In 1910, less than 1,000 elk remained in Colorado (Swift 1945), but today the state population is estimated to be the largest in the country, with more than 290,000 elk. Over the last two decades, however, wildlife managers in Colorado have become increasingly concerned about declining winter elk calf recruitment (estimated using juvenile/adult female ratios) in the southern portion of the state. Although juvenile/adult female ratios are often highly correlated with juvenile elk survival, they are an imperfect estimate of recruitment because they are affected by harvest, pregnancy rates, juvenile survival, and adult female survival (Caughley 1974, Gaillard et al. 2000, Harris et al. 2008, Lukacs et al. 2018). Thus, there is a need for elk research in Colorado based upon monitoring of marked individuals to evaluate factors affecting each stage of production and survival. In 2016, we began a study to investigate factors influencing elk recruitment in 2 elk Data Analysis Units (DAUs; E-20, E-33) with low juvenile/adult female ratios (Fig. 1). In 2019, we expanded this study into a 3rd DAU with high juvenile/adult female ratios (E-2), to better determine how predators, habitat, and weather conditions are impacting elk recruitment in Colorado (Fig. 2). In 2021, we concluded collaring efforts in E-33. Since study initiation, we have collared 513 pregnant females in February-March, 799 neonates in May-August, and 246 6-month-old calves in December (Table 1). Averaged across years, we estimated that the annual pregnancy rate of adult female elk was 94% in the Bear’s Ears herd (excluding 2019 data where n = 3; range = 90-97%), 91% in the Trinchera herd (range = 85-94%), and 92% (range = 88-95%) in the Uncompahgre Plateau herd (Fig. 3). Elk populations experiencing good to excellent summerautumn nutrition typically have pregnancy rates ≥90% (Cook et al. 2013). From 2017-2023, we estimated that the mean ingesta-free body fat (IFBF) of adult female elk was 6.89% in the Bear’s Ears Herd, 7.60% in the Trinchera herd, and 7.57% in the Uncompahgre Plateau herd (Fig. 4). When late-winter IFBF values are <8-9% for adult female elk that have lactated through the previous growing season, this suggests that there may be nutritional limitations, but it does not identify whether limitations are a result of summer-autumn or winter nutrition (R. Cook, personal communication). Averaged across years, we estimated that the median date of calving was June 1 in the Bear’s Ears, Trinchera, and Uncompahgre Plateau herds (Fig. 5). We estimated that the mean weight of 6-month old elk calves was 221.1 lb (95% CI = 215.4-226.7 lb) from the Bear’s Ears herd and 235.5 lb (95% CI = 229.7-241.3 lb) from the Uncompahgre Plateau elk herd. Literature Cited Caughley, G. 1974. Interpretation of age ratios. The Journal of Wildlife Management 38:557-562. 14 �Cook, R. C., J. G. Cook, D. J. Vales, B. K. Johnson, S. M. McCorquodale, L. A. Shipley, R. A. Riggs, L. L. Irwin, S. L. Murphie, B. L. Murphie, K. A. Schoenecker, F. Geyer, P. B. Hall, R. D. Spencer, D. A. Immell, D. H. Jackson, B. L. Tiller, P. J. Miller, and L. Schmitz. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1-45. Gaillard, J. M., M. Festa-Bianchet, N. G. Yoccoz, A. Loison, and C. Toïgo. 2000. Temporal variation in fitness components and population dynamics of large herbivores. Annual Review of Ecology and Systematics 31:367-393. Harris, N. C., M. J. Kauffman, and L. S. Mills. 2008. Inferences about ungulate population dynamics derived from age ratios. Journal of Wildlife Management 72:1143-1151. Lukacs, P. M., M. S. Mitchell, M. Hebblewhite, B. K. Johnson, H. Johnson, M. Kauffman, K. M. Proffitt, P. Zager, J. Brodie, K. Hersey, A. A. Holland, M. Hurley, S. McCorquodale, A. Middleton, M. Nordhagen, J. J. Nowak, D. P. Walsh, and P. J. White. 2018. Factors influencing elk recruitment across ecotypes in the Western United States. Journal of Wildlife Management 82:698-710. Swift, L. W. 1945. A partial history of the elk herds of Colorado. Journal of Mammalogy 26:114-119. Table 1. The number of elk collared in each age class from the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) herds from 2017-2023. Herd E-2 Bear's Ears Year Adult Neonate E-20 Uncompahgre Plateau 6-month Adult Neonate 2017 23 2018 6-month E-33 Trinchera Adult Neonate 40 23 57 25 48 21 53 2019 2 49 25 30 49 25 30 46 2020 40 54 25 40 52 25 19 21 2021 40 53 25 40 52 25 20 21 2022 40 54 21 40 53 25 2023 40 43 25 40 54 25 15 �Figure 1. The number of elk calves per 100 adult females observed during December-February aerial surveys (5-year average from 2013-2017) within elk Data Analysis Units (DAUs; labeled with black text). Figure 2. The estimated number of calves per 100 adult females observed annually during winter classification surveys in the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) elk herds from 1980-2020 (1992-2020 for the Trinchera herd). Red lines and shaded bands represent linear regression trends with 95% confidence intervals, and indicate an average decrease of 0.56 and 1.05 calves per 100 adult females per year in the Uncompahgre Plateau and Trinchera herds, respectively. 16 �Figure 3. Estimated average pregnancy rates of adult female elk from the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) herds sampled during late winter 20172023. The sample size is given at the top of the 95% binomial confidence intervals (black lines). Figure 4. The estimated ingesta-free body fat (%) of adult female elk with 95% confidence intervals from the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) herds sampled during late winter 2017-2023. 17 �Figure 5. The estimated calving dates of collared adult female elk from the Bear’s Ears (DAU E-2), Uncompahgre Plateau (DAU E-20), and Trinchera (DAU E-33) herds from 2017-2023. 18 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Response of elk to human recreation at multiple scales: demographic shifts and behaviorallymediated fluctuations in local abundance Period Covered: January 1, 2023-December 31, 2023 Principal Investigators: Eric Bergman, eric.bergman@state.co.us; Nathaniel Rayl, nathaniel.rayl@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. This project has objectives on 2 scales. At the broad, elk herd-level scale, we are estimating pregnancy rates, calf survival rates, and cause-specific mortality rates to evaluate the importance of mortality sources for elk calf survival. More specifically, we are evaluating the influence of biotic (birth date, birth mass, gender, maternal body condition, habitat conditions), abiotic (previous and current weather conditions), and human-induced factors (i.e., relative exposure to recreational activities) on seasonal mortality risk of elk calves from birth to age 1 and on pregnancy rates of mature female elk. At the narrower geographic and temporal scale, we are using changes in elk abundance within small study units (<65 km2 [25 mi2]) as a tool to evaluate the influence of human recreation on elk distribution. At this narrower scale, the primary objective is to evaluate the role that human recreation (e.g., hiking, mountain biking, horseback riding, trail running, hunting, etc.) has on the behavioral distribution of elk on spring calving, summer, and fall transition ranges. Coupled to the objective of detecting behaviorally influenced changes in abundance and density, we are evaluating the effectiveness of current recreational closures maintained by ski areas, counties, and federal land management agencies. From 2019-2023, we have collared 184 pregnant females in March, 244 neonates in May-July, and 125 6-month-old calves in December from the Avalanche Creek elk herd (Data Analysis Unit E-15; Table 1). Averaged across years, we estimated the annual pregnancy rate of adult female elk was 92% (95% CI = 87-95%; Fig. 1). Elk populations experiencing good to excellent summer-autumn nutrition typically have pregnancy rates ≥90% (Cook et al. 2013). We estimated that the mean ingesta-free body fat (IFBF) of adult female elk was 8.23 (95 CI = 7.90-8.57%). When late-winter IFBF values are <8-9% for adult female elk that have lactated through the previous growing season, this suggests that there may be nutritional limitations, but it does not identify whether limitations are a result of summer-autumn or winter nutrition (R. Cook, personal communication). Averaged across years, we estimated that the median date of calving was June 1 (Fig. 2). We estimated that the mean weight of 6-month old elk calves was 246.3 lb (95% CI = 240.3-252.3). During the summers of 2019, 2020, and 2021 a total of 384,455, 5,313,367, and 4,856,973 photos were taken, respectively, by cameras that were deployed across 8 study units. Photos taken during 2022 and retrieved from cameras during 2023 are being archived. During 2023 a formal process to facilitate automated (AI) photo recognition, led by a post-doctoral researcher, was initiated. Initial aspects of this process evaluated numerous AI options and quickly identified Pytorch-Wildlife (formerly called Megadetector) as the most efficient and effective tool that is currently available. Data collected during 2019 has been evaluated using Pytorch-Wildlife and quantification of error rates (both Type I and Type II) is currently underway. 19 �Literature Cited Cook, R. C., J. G. Cook, D. J. Vales, B. K. Johnson, S. M. McCorquodale, L. A. Shipley, R. A. Riggs, L. L. Irwin, S. L. Murphie, B. L. Murphie, K. A. Schoenecker, F. Geyer, P. B. Hall, R. D. Spencer, D. A. Immell, D. H. Jackson, B. L. Tiller, P. J. Miller, and L. Schmitz. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1–45. Table 1. The number of elk collared in each age class from the Avalanche Creek elk herd (DAU E-15) from 2019-2023. Age class Year Adult Neonate 6-month 2019 24 26 25 2020 40 54 25 2021 40 51 25 2022 40 53 25 2023 40 60 25 Figure 1. Estimated average pregnancy rates of adult female elk from the Avalanche Creek (DAU E-15) herds sampled during late winter 2019-2023. The sample size is given at the top of the 95% binomial confidence intervals (black lines). 20 �Figure 2. The estimated calving dates of collared female elk from the Avalanche Creek (DAU E-15) herd from 2019-2023. 21 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Spatiotemporal effects of human recreation on elk behavior: an assessment within critical time stages Period Covered: January 1, 2023-December 31, 2023 Principal Investigators: Nathaniel Rayl, nathaniel.rayl@state.co.us; Eric Bergman, eric.bergman@state.co.us; Joe Holbrook, Joe.Holbrook@uwyo.edu All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. The influence of recreational disturbance on ungulate populations is of particular interest to wildlife managers in Colorado, as there is growing concern about its potential impacts within the state. Currently, the western United States is experiencing some of the highest rates of human population growth in the country, with growth in rural and exurban areas frequently outpacing growth in urban areas. Additionally, participation in outdoor recreation is also increasing. In Colorado, the number of individuals participating in recreational activities, and the associated demand for recreational opportunities, appear to be increasing. Understanding potential impacts of recreational activity on elk spatial ecology in Colorado is critical for guiding management actions, as altered movements may result in reduced foraging time and higher energetic costs, which may decrease fitness. We are studying elk from the resident portion of the Bear’s Ears elk herd (DAU E-2) in Colorado to determine potential impacts of recreational activities on this population. This research project is a collaboration between Colorado Parks and Wildlife (CPW) and the Haub School of Environment and Natural Resources at the University of Wyoming, and forms the basis of an M.S. thesis for a graduate student (Eric VanNatta, also CPW Area 10 Terrestrial Biologist) enrolled at the Haub School. In January 2020 and January 2021, we collared 30 and 26 adult female elk, respectively, from the resident portion of the Bear's Ears elk herd on U.S. Forest Service (USFS) land near Steamboat Springs. We estimated pregnancy rates of 93% (95% CI: 79-98%) in 2020 and 96% (95% CI: 81-100%) in 2021. From May-October 2020 we deployed trail counters at 22 trailheads in the Routt National Forest (Fig. 1). We recorded roughly 100,000 people departing and returning from these trailheads. Among individual trailheads, we documented average daily traffic counts ranging from 2-325 people (Fig. 2). Most traffic was recorded on weekends with noticeable lulls in traffic frequency observed during weekdays. During the 2021 field season, we again deployed trail counters at the 22 trailheads, and also added additional trail counters at 1-km intervals along each trail for up to 5-km from the trailhead. These additional trail counters are being deployed on a rotating basis to sample each trail. Data collected from these additional trail counters will provide an estimate of the decay of traffic along trails. During the 2020 and 2021 field season, we distributed handheld GPSs to recreationists (hikers, bikers, hunters) to record detailed tracks of human use within this trail system (Fig. 3). In 2020, we collected over 100 GPS tracks. These tracks from recreationists and hunters will allow us to better quantify human recreation on the landscape and evaluate how elk respond to recreationists. In fall 2023, Eric VanNatta successfully completed and defended his M.S. proposal at the University of Wyoming and finished processing and cleaning the trail counter dataset. 22 �Figure 1. Routt National Forest study area located in northwest Colorado, USA. 23 �Figure 2. Daily trends in trailhead traffic documented with trail counters from June through October 2020, excluding Fish Creek Falls, Mad Creek, and Red Dirt trailheads, which received average daily counts >200. Figure 3. GPS track (blue) recorded from recreational mountain biker on trail system (white) in August 2020. Note the off-trail use near Long Lake. 24 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation and incorporation of life history traits, nutritional status, and browse characteristics in Shira’s moose management in Colorado Period Covered: January 1, 2023 − December 31, 2023 Principal Investigator: Eric J. Bergman, eric.bergman@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. During November of 2013 Colorado Parks and Wildlife (CPW) initiated a large scale moose research project. Fieldwork for this project was completed during 2019–2020, and analysis and publication of results occurred from 2020–2024. The impetus for CPW’s moose research program was many-fold, but some of the most important objectives included: assessment of Colorado’s moose herd dynamics relative to other states, estimation of survival rates and reproductive parameters, documentation of prevalence and the impacts of various mortality sources including human harvest, evaluation of the effects of carotid worm (Elaeophora schneideri) and winter ticks, and evaluation of the potential role of vegetation monitoring in long-term moose management processes. Abstracts of this published research are included below (Appendix 1). Research published by Nadeau et al. (2017) concluded that during the 21st century, moose populations in Colorado had grown, but much of that growth likely occurred via range expansion as moose colonized unoccupied areas. During this study, adult female survival averaged 93% but declined to 88% when human harvest was included as a mortality source (Bergman et al. 2024). Evaluation of field methods to quantify spring and summer calf-at-heel ratios estimated that detection probabilities of calves was 0.80 and that calf-at-heel ratios ranged from 0.54–0.84 (Bergman et al. 2020b). Incorporation of this detection probability into the expected parturition dates for moose calves reduced the variation in expected dates and shifted the mean date to an earlier time period, suggesting 90% of calves were born by 27th of May (Bergman et al. 2020a). Research completed by LeVan et al. (2013) documented very high prevalence (83%) of carotid worm infections in harvested moose, suggesting infection is common within Colorado’s moose population, but also that infection is not lethal for animals. Recent research (DeCesare et al. 2024) on the relationship between climate and regional weather patterns and winter tick parasitism of moose suggests that while Colorado’s colder winters and deeper snow depths likely reduce average annual tick infestation, a warming environment would increase snowpack variability and tick presence may increase. This project did not identify a strong nexus between moose productivity and surrounding habitat characteristics, although a positive correlation between calf-at-heel counts, willow height and willow cover was identified (Hayes et al. 2022). Finally, while outside the primary objectives of this project, genetic comparison with data from other western states, western Canada, and Alaska suggested a high degree of overlap among the currently identified subspecies of moose, suggesting further distinction of moose subspecies is not genetically supported, nor is threatened or endangered species status warranted for any existing subspecies (DeCesare et al. 2020). 25 �Literature Cited Bergman, E. J., F. P. Hayes, and K. Aagaard. 2020. Estimation of moose parturition dates in Colorado: incorporating imperfect detections. Alces: A Journal Devoted to the Biology and Management of Moose 56:127-135. Bergman, E. J., F. P. Hayes, P. M. Lukacs, and C. J. Bishop. 2020. Moose calf detection probabilities: quantification and evaluation of a ground‐based survey technique. Wildlife Biology 2020:1-9. Bergman, E. J., J. P. Runge, M. C. Fisher, and L. L. Wolfe. 2024. Management considerations of moose life-history characteristics in Colorado, USA. Wildlife Biology 2024:In review. DeCesare, N. J., R. B. Harris, M. P. Atwood, E. J. Bergman, A. B. Courtemanch, P. C. Cross, G. L. Fralick, K. R. Hersey, M. A. Hurley, T. M. Koser, R. L. Levine, K. L. Monteith, J. R. Newby, C. J. Peterson, S. Robertson, and B. L.Wise. 2024. Warm places, warm years and warm season increase parasitizing of moose by winter ticks. Ecosphere 15:In Press. DeCesare, N. J., B. V. Weckworth, K. L. Pilgrim, A. B. Walker, E. J. Bergman, K. E. Colson, R. Corrigan, R. B. Harris, M. Hebblewhite, and B. R. Jesmer. 2020. Phylogeography of moose in western North America. Journal of Mammalogy 101:10-23. Hayes, F. P., J. J. Millspaugh, E. J. Bergman, R. M. Callaway, and C. J. Bishop. 2022. Effects of willow nutrition and morphology on calving success of moose. The Journal of Wildlife Management 86:e22175. LeVan, I. K., K. A. Fox, and M. W. Miller. 2013. High elaeophorosis prevalence among harvested Colorado moose. Journal of Wildlife Diseases 49:666-669. Nadeau, M. S., N. J. DeCesare, D. G. Brimeyer, E. J. Bergman, R. B. Harris, K. R. Hersey, K. K. Huebner, P. E. Matthews, and T. P. Thomas. 2017. Status and trends of moose populations and hunting opportunity in the western United States. Alces: A Journal Devoted to the Biology and Management of Moose 53:99-112. Appendix 1. Moose research publication abstracts. Status and trends of moose populations and hunting opportunity in the western United States M. Steven Nadeau, Nicholas J. DeCesare, Douglas G. Brimeyer, Eric J. Bergman, Richard B. Harris, Kent R. Hersey, Kari K. Huebner, Patrick E. Matthews, and Timothy P. Thomas ABSTRACT: We review the state of knowledge of moose (Alces alces shirasi) in the western US with respect to the species’ range, population monitoring and management, vegetative associations, licensed hunting opportunity and hunter harvest success, and hypothesized limiting factors. Most moose monitoring programs in this region rely on a mixture of aerial surveys of various formats and hunter harvest statistics. However, given the many challenges of funding and collecting rigorous aerial survey data for small and widespread moose populations, biologists in many western states are currently exploring other potential avenues for future population monitoring. In 2015, a total of 2,263 hunting permits were offered among 6 states, with 1,811 moose harvested and an average success rate per permitholder of 80%. The spatial distribution of permits across the region shows an uneven gradient of hunting opportunity, with some local concentrations of opportunity appearing consistent across state boundaries. On average, hunting opportunity has decreased across 56% of the western US, remained stable across 17%, and increased across 27% during 2005–2015. Generally, declines in hunting opportunity for moose are evident across large portions (62–89%) of the “stronghold” states where moose have been hunted for the longest period of time (e.g., Idaho, Montana, Utah, and Wyoming). In contrast, increases in opportunity appear more common at peripheries of the range where populations have expanded, including most of Colorado, northeastern Washington, southern Idaho, and eastern Montana. There are many factors of potential importance to moose in this region, including parasites, predators, climate, forage quality, forage quantity, and humans. State wildlife agencies are currently conducting a variety of research focused on population vital rates, the development of monitoring techniques, forage quality, trace mineral levels, and evaluation of relative impacts among potential limiting factors. 26 �ALCES 53:99–112 (2017) Management considerations of moose life-history characteristics in Colorado, USA. Eric J. Bergman, Jonathan P. Runge, Mark C. Fisher, and Lisa L. Wolfe ABSTRACT: Wildlife management agencies are obliged to provide evidence-based management recommendations to stakeholders. However, allocation of resources towards the management of species cannot be uniform. The consideration of life history characteristics of moose offers wildlife managers a more robust understanding of population ecology, while also providing insight into potential limiting factors for long-term management. From 2014-2020 we simultaneously measured survival of adult moose, as well as calf productivity, in relation to the nutritional condition of adult females, in Colorado. Mean annual adult survival was high (93%, 95% confidence interval: 91%–95%). Human hunter harvest was the leading source of mortality and lowered annual adult survival to 88%. Malnutrition was the leading source of natural mortality. Mean annual pregnancy rates were low (77%) and highly variable (95% confidence interval: 65%–88%). However, low pregnancy rates were compensated for by high apparent calf survival. The best predictor of moose pregnancy was nutritional condition. Our data suggest that bottom-up ecological processes were affecting moose population growth, but populations were likely increasing during our study, with a population growth rate for the period of our study between 1.03–1.11. Wildlife Biology In Review (2024) Moose calf detection probabilities: quantification and evaluation of a ground-based survey technique Eric J. Bergman, Forest P. Hayes, Paul M. Lukacs, and Chad J. Bishop ABSTRACT: Survey data improve population management, yet those data often have associated bias. We quantified one source of bias in moose survey data (observer detection probability, p), by using repeated ground-observations of calves-at-heel of radio-collared moose in Colorado, USA. Detection probabilities, which varied both spatially and temporally, were estimated using an occupancy-modelling framework. We provide an efficient offset for modelled calf-at-heel occupancy (ψ) estimates that accommodates summer calf mortality. Detection probabilities were most efficiently modelled with seasonal variation, with the lowest probability of detecting calves-at-heel occurring during parturition (i.e. May) and later autumn periods (after August). Our most efficiently modelled detection probability estimate for summer was 0.80 (SE = 0.05). During the four years of this study, ψ estimates ranged from 0.54–0.84 (SE = 0.08–0.11). Accounting for 91.7% monthly calf survival corrected ψ estimates downward (ψ = 0.42–0.65). Our results suggest that repeated ground-based observations of individual cow moose, during summer months, can be can a cost-effective strategy for estimating a productivity parameter for moose. Ground survey results can be further improved by accounting for calf mortality. Wildlife Biology 2:1-9 (2020) Estimation of moose parturition dates in Colorado: incorporating imperfect detections Eric J. Bergman, Forest P. Hayes, and Kevin Aagaard ABSTRACT: Researchers and managers use productivity surveys to evaluate moose populations for harvest and population management purposes, yet such surveys are prone to bias. We incorporated detection probability estimates (p) into spring and summer ground surveys to reduce the influence of observer bias on the estimation of moose parturition dates in Colorado. In our study, the cumulative parturition probability for moose was 0.50 by May 19, and the probability of parturition exceeded 0.9 by May 27. Timing of moose calf parturition in Colorado appears synchronous with parturition in more northern latitudes. Our results can be used to plan ground surveys in a manner that will reduce bias stemming from unobservable and yet-born calves. ALCES 56:127-135 (2020) 27 �High elaeophora prevalence among harvested moose in Colorado Ivy K. LeVan, Karen A. Fox, and Michael W. Miller ABSTRACT: Infection with Elaeophora schneideri, a filarial parasite, occurs commonly in mule deer (Odocoileus hemionus) and elk (Cervus elaphus nelsoni), but seemingly less so in moose (Alces alces). Of 109 carotid artery samples from moose harvested throughout Colorado, USA, in 2007, 14 (13%; 95% binomial confidence interval [bCI]=7–21%) showed gross and 91 (83%; 95% bCI=75–90%) showed histologic evidence of elaeophorosis. Although neither blindness nor other clinical signs associated with elaeophorosis were reported among the harvested moose we examined, the pervasiveness of this parasite may motivate further study of the potential effects of elaeophorosis on moose survival and population performance in the southern Rocky Mountains. Our data suggest histopathology may be more sensitive than gross examination in detecting elaeophorosis in harvested moose. Journal of Wildlife Disease 49:666-669 (2013) Warm places, warm years and warm seasons increase parasitizing of moose by winter ticks Nicholas J. DeCesare, Richard B. Harris, M. Paul Atwood, Eric J. Bergman, Alyson B. Courtemanch, Paul C. Cross, Gary L. Fralick, Kent R. Hersey, Mark A. Hurley, Troy M. Koser, Rebecca L. Levine, Kevin L. Monteith, Jesse R. Newby, Collin J. Peterson, Samuel Robertson, and Benjamin L. Wise ABSTRACT: Observed links between parasites, such as ticks, and climate change have aroused concern for human health, wildlife population dynamics, and broader ecosystem effects. The one-host life history of the winter tick (Dermacentor albipictus) links each annual cohort to environmental conditions during three specific time periods when they are predictably vulnerable: spring detachment from hosts, summer larval stage, and fall questing for hosts. We used mixed-effects generalized linear models to investigate drivers of tick loads carried by moose (Alces alces) relative to these time periods and across 750 moose, 10 years, and 16 study areas in the western United States. We tested for effects of biotic factors (moose density, shared winter range, vegetation, migratory behavior) and weather conditions (temperature, snow, humidity) during each seasonal period when ticks are vulnerable and off-host. We found that warm climatic regions, warm seasonal periods across multiple partitions of the annual tick life cycle, and warm years relative to long-term averages each contributed to increased tick loads. We also found important effects of snow and other biotic factors such as host density and vegetation. Tick loads in the western United States were, on average, lower than those where tick-related die-offs in moose populations have occurred recently, but loads carried by some individuals may be sufficient to cause mortality. Lastly, we found inter-annual variation in tick loads to be most correlated with spring snowpack, suggesting this environmental component may have the highest potential to induce change in tick load dynamics in the immediate future of this region. Ecosphere Accepted In Press (2024) Effects of willow nutrition and morphology on calving success of moose Forest P. Hayes, Joshua J. Millspaugh, Eric J. Bergman, Ragan M. Callaway, and Chad J. Bishop ABSTRACT: Across much of North America, populations of moose (Alces alces) are declining because of disease, predation, climate change, and anthropogenic-driven habitat loss. Contrary to this trend, populations of moose in Colorado, USA, have continued to grow. Studying successful (i.e., persistent or growing) populations of moose can facilitate continued conservation by identifying habitat features critical to persistence of moose. We hypothesized that moose using habitat with higher quality willow (Salix spp.) would have a higher probability of having a calf-at-heel (i.e., calving success). We evaluated moose calving success using repeated ground observations of collared individuals with calves in an occupancy model framework to account for detection probability. We then evaluated the impact of willow habitat quality and nutrition on moose calving success by studying 2 spatially segregated populations of moose in Colorado. Last, we evaluated correlations between willow characteristics (browse intensity, height, cover, leaf length, and species) and willow nutrition (dry matter digestibility [DMD]) to assess the 28 �utility of using those characteristics to assess willow nutrition. We found willow height and cover had a high probability of being positively associated with higher individual-level calving success. Willow DMD, browse intensity, and leaf length were not predictive of individual moose calving success; however, the site with higher mean DMD consistently had higher mean estimates of calving success for the same year. Our results suggest surveying DMD is likely not a useful metric for assessing differences in calving success of individual moose but may be of use at population levels. Further, the assessment of willow morphology and density may be used to identify areas that support higher levels of moose calving success. The Journal of Wildlife Management 86:e22175 (2022) Phylogeography of moose in western North America Nicholas J. DeCesare, Byron V. Weckworth, Kristine L. Pilgrim, Andrew B. D. Walker, Eric J. Bergman, Kassidy E. Colson, Rob Corrigan, Richard B. Harris, Mark Hebblewhite, Brett R. Jesmer, Jesse R. Newby, Jason R. Smith, Rob B. Tether, Timothy P. Thomas, and Michael K. Schwartz ABSTRACT: Subspecies designations within temperate species’ ranges often reflect populations that were isolated by past continental glaciation, and glacial vicariance is believed to be a primary mechanism behind the diversification of several subspecies of North American cervids. We used genetics and the fossil record to study the phylogeography of three moose subspecies (Alces alces andersoni, A. a. gigas, and A. a. shirasi) in western North America. We sequenced the complete mitochondrial genome (16,341 base pairs; n = 60 moose) and genotyped 13 nuclear microsatellites (n = 253) to evaluate genetic variation among moose samples. We also reviewed the fossil record for detections of all North American cervids to comparatively assess the evidence for the existence of a southern refugial population of moose corresponding to A. a. shirasi during the last glacial maximum of the Pleistocene. Analysis of mtDNA molecular variance did not support distinct clades of moose corresponding to currently recognized subspecies, and mitogenomic haplotype phylogenies did not consistently distinguish individuals according to subspecies groupings. Analysis of population structure using microsatellite loci showed support for two to five clusters of moose, including the consistent distinction of a southern group of moose within the range of A. a. shirasi. We hypothesize that these microsatellite results reflect recent, not deep, divergence and may be confounded by a significant effect of geographic distance on gene flow across the region. Review of the fossil record showed no evidence of moose south of the Wisconsin ice age glaciers ≥ 15,000 years ago. We encourage the integration of our results with complementary analyses of phenotype data, such as morphometrics, originally used to delineate moose subspecies, for further evaluation of subspecies designations for North American moose. Journal of Mammalogy 101:10-23 (2020) 29 �PREDATORY MAMMAL MANAGEMENT AND CONSERVATION BOBCAT POPULATION DYNAMICS AND DENSITY ESTIMATION MULE DEER POPULATION RESPONSE TO COUGAR POPULATION MANIPULATION EVALUATION OF ACCELEROMETER COLLARS AND METHODS DEVELOPMENT FOR DOMESTIC CATTLE 30 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Bobcat population dynamics and density estimation Period Covered: January 01, 2023 – December 31, 2023 Principal Investigators: Shane Frank, shane.frank@state.co.us; Jake Ivan, jake.ivan@state.co.us; Mark Vieira, mark.vieira@state.co.us; Jon Runge, jon.runge@state.co.us Personnel: Johnathan Lambert, Tom Knowles, Mike Swaro, Darby Finley, Garrett Smith, Brian Holmes, J.C. Rivale, Erin Sawa, Rachel Baker, Chris Martin, Kirsten Terkildsen, Nick Ragucci, David Starzenski All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. To enhance our understanding of bobcat (Lynx rufus) population dynamics and the relative influence of bobcat harvest on bobcat densities in Colorado, a pilot study was started late September 2022 and data collection continued through fall of 2023. The major field objectives of the pilot study were (1) to capture and mark bobcats with ear tags and GPS collars to be used in mark-resight analysis for population density estimation in two study areas and (2) to determine whether successful bobcat trapping rate is sufficient to build toward an adequately sized sample population in subsequent years for population density estimation within a longer-term bobcat population dynamics research project. An updated study plan was submitted and accepted late fall/early winter of 2023. We selected two study areas, ‘Piceance’ and ‘Skull Creek,’ in the northwest region within Game Management Units 10 and 22 (Figure 1). Each area was 20 x 20 km (400 km2 area) in extent, with similar topography and habitat composition. Piceance had higher historical bobcat harvest (>2.55 bobcats/100 km2) than Skull Creek (nearly 0 bobcats/100 km2). Habitat type composition was predominated by pinyon (Pinus spp.)-juniper (Juniperus spp.) and sagebrush (Artemisia spp.) communities in both study areas. CPW personnel continued live-trapping bobcats that started 11/18/2022 through 04/06/2023. As of 12/31/2023, CPW captured 29 unmarked bobcats with 13 recaptures. On average, an unmarked bobcat required approximately 64 trap nights for capture, rendering a rate acceptable to reach the eventual desired sample size of 30 bobcats per study area. There were 119 individual camera detections of bobcats recorded from November 2022-April 2023 within the Piceance, of which 9 were marked, 93 unmarked, and 17 unknown. More than 30% of the collared bobcats in Piceance were detected on the cameras. Population estimation was possible for the Piceance study area, but was not for the Skull Creek study area due to severe winter conditions precluding access and fieldwork necessary to set up the full camera trap array and live traps. The population estimate for the Piceance for the 2022-2023 field data is preliminary, due to incomplete coverage of the study area from the severe winter. In fall of 2023, CPW personnel checked and refreshed 100 camera traps within the Piceance study area and finished deploying the remaining 65 camera traps within the Skull Creek study area (Figure 1). Camera trap checks and set-ups included initially placing or replacing visual and scent lure to draw bobcats for photo detections or ‘resights’ in the case of marked bobcats. Live-trapping efforts in both study areas and camera image collection will continue through spring of 2024, at which point photo identification and mark-resight analysis will commence for the new data set (2023-2024). Images collected in the fall of 2023 have been photo-identified and population estimation models will be performed by spring 2024 alongside photo identification of the new images collected in spring. Information from the pilot study data will be included in the longer-term study plan addendum that was approved late 2023, which addresses bobcat 31 �density-habitat relationships, survival, diet, prey base, and associations between bobcat density, harvest, and primary prey, cottontails and jackrabbits. Figure 1. The bobcat study areas (20 x 20 km) in northwest Colorado include the Piceance grid, shown in red (lower), within Game Management Unit (GMU) 22 and the Skull Creek grid, shown in gray (upper), within GMU 10, which is bordered to the north by Dinosaur National Monument (green shaded area). Bobcat study areas are subdivided into 100 2 x 2 km cells, each containing a camera trap (gray dot). Dark blue dots depict live trap location/efforts. 32 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Mule deer population response to cougar population manipulation Period Covered: January 1, 2023 – December 31, 2023 Principal Investigators: Mat Alldredge, mat.alldredge@state.co.us; Allen Vitt, allen.vitt@state.co.us; Bryan Lamont, bryan.lamont@state.co.us; Ty Woodward, tyrel.woodward@state.co.us; Jamin Grigg, jamin.grigg@state.co.us; Chuck Anderson, chuck.anderson@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. The adopted Colorado mule deer (Odocoileus hemionus) strategy identified predation as one of the potential factors limiting Colorado mule deer populations. Since the adoption of the mule deer strategy by the Colorado Parks and Wildlife (CPW) Commission, members of the CPW Leadership Team developed a plan to implement the strategy. To inform predator harvest and management decisions, staff examined existing data sets related to predator and deer relationships. In June 2015, CPW personnel from the SE Region, Terrestrial, and Research branches met to explore the concept for a project that examines how deer demographic parameters may change following cougar population suppression. Deer Data Analysis Unit (DAU) D-16 had experienced significant deer mortality from cougars. This study initiated in 2017 in D-16 and the adjacent D-34 as a manipulative study to examine the effects of cougar predation on mule deer and simultaneously examine the effects of cougar harvest on the cougar population. To assess the effect of management manipulations, it was necessary to develop an experimental framework including a control and treatment study area. Otherwise, the magnitude of the effect would be unknown as other limiting factors fluctuate. D-34 is an adjacent mule deer DAU to the south of D-16, which has a similar mule deer population size and habitat. Using D-16 and D-34 in a crossover design allowed for the manipulation of a potential limiting factor for mule deer population growth or survival and examine similarities in the response as the control and treatment are switched between the areas. The study's first objective was to assess the impact of cougar predation on mule deer survival and determine if this impact could be manipulated by altering cougar densities. The second objective was to assess how this manipulation would affect the cougar population in terms of intraspecific mortality and human conflict. The manipulation involved increasing cougar harvest in D-16 for the first 3 years of the study and then reducing harvest to a low level for the following 6 years and doing the reverse in D-34 with a reduced harvest for the first 6 years and increased harvest in the last 3 years. During this time we would monitor deer mortality from cougars, measure cougar density, and assess intraspecific cougar mortality and cougar/human conflict in both study areas. To date, deer survival has been relatively high (86% average doe survival D-16 and D-34; 64% average winter fawn survival D-16; 84% average winter fawn survival D-34) in both study areas across years and deer mortality associated with cougars has been low (5.6% does D-16; 7.2% does D-34; 4.2% fawns D-16; 2.1% fawns D-34). Because deer survival was relatively high in the area and mortality associated with cougars was relatively low during the first 6 years of the study, we stopped investigating the impact of cougar predation on deer survival. The remaining treatment was to increase cougar harvest in D34, which presumably would increase deer survival. However, it was decided that it would not be 33 �possible to measure an effect if it did occur with relatively high deer survival evident during the period of low cougar harvest/relatively high cougar density. Graduate student, Annie Hart, at Colorado State University is continuing her Master’s project examining the deer data. The first part of her project examines how variation in natural forage abundance influences mule deer selection of agricultural resources. The other part of her project will model adult and juvenile survival to help understand the costs and benefits of migration. This is using a state uncertainty modeling approach to estimate survival of migrant and resident fawns, which incorporates the survival of individuals that die before their movement strategy is classified. The cougar population component of the study is continuing with assessing impacts of cougar harvest in D-16 and D-34. We continue to estimate cougar density in both study areas and are monitoring intraspecific effects and cougar/human conflict. As this continues, we will maintain a low cougar harvest (quota of 12) in D-16 but need to increase the cougar quota in D-34. The quota in D-34 had been reduced to 15 since the study started, but we proposed an increase in the quota to 35 cougars to start in the 20232024 hunting season, which was approved by the CPW Wildlife Commission in 2023. During the study we have captured and collared 108 cougars in D-16 and 120 in D-34. Last year we captured 11 in D-16 and 20 in D-34. The higher captures in D-34 were related to increased sample size requirements for the cougar survey in D-34 that year. Over the last couple of years collars have been failing sooner than expected, presumably because collar batteries are not lasting as long as they used to. To date, we have completed 3 density estimates in each D-16 and D-34 with preliminary estimates ranging from 2.7 to 3.1 independent cougars per 100 km2. This does not account for any cougars that may have been harvested prior to the initiation of the survey each year. We have not detected a significant change in density relative to changes in harvest quotas or achieved harvest. In 2023 the density estimate was conducted in D-34. Cougar mortality has been relatively low throughout the study, with the majority of this attributable to hunting mortality. Other sources of mortality include disease, intraspecific killing, human conflict removal and unknown. Intraspecific mortality has ranged from 1 to 2 incidences yearly in D-16 and 1 to 3 in D-34 for collared cougars. Cougar/human conflict is variable between years and study areas. This conflict may include livestock depredation, pet depredation, being in unacceptable locations, or aggressive behaviors toward humans. We show conflict rates from 2000-2023 (Figure 1) which shows the variability across time. There may also be variability in these data from how it was reported and recorded, most notably the switch to an electronic/online approach of the conflict app in 2019. D-34 had some of the highest conflict, especially in 2021 and 2023, but historical conflict rates also had occasional high years as well. 34 �Figure 1: Number of human/cougar conflicts in DAUs D-16 and D-34 by year. This does not include sightings. 35 �Colorado Parks and Wildlife WILDLIFE RESEARCH PROJECT SUMMARY Evaluation of accelerometer collars and methods development for domestic cattle Period Covered: January 1, 2023-December 31, 2023 Principal Investigators: Ellen Brandell, ellen.brandell@state.co.us All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. By providing this summary, CPW does not intend to waive its rights under the Colorado Open Records Act, including CPW’s right to maintain the confidentiality of ongoing research projects. CRS § 24-72-204. Livestock production is an important component of Colorado’s economy (University of Arkansas accessed 2023, Bureau of Land Management accessed 2023), as well as ingrained in the state’s culture and heritage – cattle production in particular. Colorado citizens are concerned about the effects of reestablishing gray wolves (Canis lupus) on livestock (Niemiec et al. 2022), and given the geographic constraints of CRS 33-2-105.8 (Colorado General Assembly 2020, CPW 2023) and suitable wolf habitat in Colorado (Ditmer et al. 2022), wolves and livestock will spatially overlap in western Colorado. Wolves may affect livestock both directly and indirectly; direct effects include depredation, which has already occurred in the state. Indirect effects, such as increased stress or vigilance behavior, are much more difficult to observe and quantify. Indirect effects of wolves on cattle have been documented in other western states or laboratory experiments, such as decreased weight gain (Ramler et al. 2014) and increased stress (Cooke et al. 2013). However, these negative effects are not ubiquitous across studies, and the majority of published literature on this topic lacks a mechanistic understanding. For example, cattle movement rates (Laporte et al. 2010, Bailey et al. 2018) and physiology (Cooke et al. 2013) in response to wolf presence have been studied, but unless changes in movement rates or physiology have direct implications for weight gain, pregnancy rates, or animal health, it might not be important to a producer or impact the operation’s economics. In a future research project, we aim to link cattle behavior and movement in response to wolf presence to cattle stress levels, weight gain, and pregnancy rates. Quantifying the mechanisms of changes in cattle stress, weight gain, and pregnancy rates is critical for identifying whether a causal relationship exists between wolf exposure and cattle responses, the magnitude of this effect, and subsequent consequences for producers’ bottom line. However, before we can launch a research project, we need to test the field equipment and develop data collection methods. In spring 2023, we began a methods testing project to evaluate GPS and accelerometer collars on beef cattle. We had three goals of this methods testing project: (1) assess proper fit of GPS/accelerometer collars on both adult female cows and calves throughout the grazing season; (2) develop methods to calibrate accelerometer data to common cattle behaviors; (3) test field equipment, and improve equipment as needed. We outfitted 20 cows with collars in May and June 2023. More specifically, we collared and monitored 10 cow-calf pairs from two cattle operations (one in Northeast Colorado, one in Northwest Colorado). Cow-calf pairs are of interest as calves are the most vulnerable to predation. Data collection ranged from approximately 1-5 months while cattle were grazing on allotments (e.g., USFS, BLM). We obtained a high-quality visual observation of all collared animals at least twice per month, and often multiple times a week. Visual observations were obtained by CPW staff, the livestock owner, or ranch personnel. Animal condition and collar fit was assessed visually, and with associated photos and video 36 �where possible. We used this information to determine if collars needed to be periodically adjusted. Calf collars had a section of elastic to allow for growth in between adjustments. Accelerometers collect triaxial data (x, y, and z axes) 8 times per second (8 Hz). Accelerometers have been used on cattle and other grazing species to identify behaviors and quantify time budgets (Riaboff et al. 2020, Riaboff et al. 2022). We will create time budgets by specifying cattle behaviors such as feeding, resting, ruminating, moving, acting vigilant, and grooming. We will calibrate cattle behavior by performing focal follows, where an individual cow or calf is observed for a predetermined amount of time (20 minutes), and the timing of different behaviors is recorded (Riaboff et al. 2022). One adult female cow per operation was outfitted with a camera collar as well to provide constant behavioral validation data. The observation data is compared with the triaxial data patterns, and unique data patterns are labeled as specific behaviors using machine learning algorithms (Riaboff et al. 2020, Riaboff et al. 2022). Collars will also collect geospatial data at short, regular intervals to calculate distance moved and movement rates (Bailey et al. 2018). We are currently organizing and analyzing these data. Experiences from this methods testing project will help guide equipment decisions, data collection methods, and fieldwork as we develop a larger-scale research project focusing on indirect effects of predators on livestock. Literature Cited Bailey, D. W., M. G. Trotter, C. W. Knight, and M. G. Thomas. 2018. Use of GPS tracking collars and accelerometers for rangeland livestock production research. Translational Animal Science 2:81-88. Bureau of Land Management. Colorado rangeland management and grazing. <https://www.blm.gov/programs/natural-resources/rangeland-and-grazing/rangeland-health/colorado>. Accessed 2023. Clark, P. E., D. E. Johnson, L. L. Larson, M. Louhaichi, T. Roland, and J. Williams. 2017. Effects of wolf presence on daily travel distance of range cattle. Rangeland ecology & management 70:657-665. Colorado General Assembly. 2020 Colorado ballot analysis, proposition 114, reintroduction and management of gray wolves. <https://leg.colorado.gov/ballots/reintroduction-and-management-graywolves>. Accessed 2023. Colorado Parks and Wildlife. 2023. Colorado wolf restoration and management plan. Denver, USA. Cook, R. C., J. G. Cook, D. J. Vales, B. K. Johnson, S. M. Mccorquodale, L. A. Shipley, R. A. Riggs, L. L. Irwin, S. L. Murphie, and B. L. Murphie. 2013. Regional and seasonal patterns of nutritional condition and reproduction in elk. Wildlife Monographs 184:1-45. Ditmer, M. A., G. Wittemyer, S. W. Breck, and K. R. Crooks. 2022. Defining ecological and socially suitable habitat for the reintroduction of an apex predator. Global Ecology and Conservation 38:e02192. Laporte, I., T. B. Muhly, J. A. Pitt, M. Alexander, and M. Musiani. 2010. Effects of wolves on elk and cattle behaviors: implications for livestock production and wolf conservation. PLoS One 5:e11954. Niemiec, R., R. E. Berl, M. Gonzalez, T. Teel, J. Salerno, S. Breck, C. Camara, M. Collins, C. Schultz, and D. Hoag. 2022. Rapid changes in public perception toward a conservation initiative. Conservation Science and Practice 4:e12632. Ramler, J. P., M. Hebblewhite, D. Kellenberg, and C. Sime. 2014. Crying wolf? A spatial analysis of wolf location and depredations on calf weight. American Journal of Agricultural Economics 96:631-656. Riaboff, L., S. Couvreur, A. Madouasse, M. Roig-Pons, S. Aubin, P. Massabie, A. Chauvin, N. Bédère, and G. Plantier. 2020. Use of predicted behavior from accelerometer data combined with GPS data to explore the relationship between dairy cow behavior and pasture characteristics. Sensors 20:4741. Riaboff, L., L. Shalloo, A. F. Smeaton, S. Couvreur, A. Madouasse, and M. T. Keane. 2022. Predicting livestock behaviour using accelerometers: A systematic review of processing techniques for ruminant behaviour prediction from raw accelerometer data. Computers and Electronics in Agriculture 192:106610. 37 �University of Arkansas Division of Agriculture Research & Extension. Economic impact of agriculture. <https://economic-impact-of-ag.uada.edu/colorado/>. Accessed 2023. 38 �SUPPORT SERVICES RESEARCH LIBRARY ANNUAL REPORT 2023 RESEARCH DATABASE SUPPORT SERVICES 39 �Colorado Parks and Wildlife RESEARCH LIBRARY ANNUAL REPORT 2023 Period Covered: January 1, 2023 − December 31, 2023 Author: Karen Hertel, Karen.Hertel@state.co.us The Colorado Parks and Wildlife Research Center Library, in existence since the 1960s in the Fort Collins office, serves all CPW staff regardless of location. Primary functions of the library are to 1) support wildlife research and management by providing research assistance and full-text information resources, and 2) serve as an institutional repository by archiving and providing access to documents produced by agency staff. Karen Hertel was hired as the new librarian in December of 2022; primary focuses in 2023 were: • Collection analysis, resulting in the withdrawal of 2,135 obsolete, duplicate, or seldomused items. • Updating of bibliographic records in the catalog to correct call numbers to match shelf location. • Continued digitization of CPW documents, adding 392 CPW documents and 91 theses to the pdf collection. As of December 2023, the CPW Library Catalog contains 8,233 records (unique titles) and 20,734 items (many titles have more than one item; for example, a report that is produced multiple years). CPW Digital Collections, part of the Plains to Peaks Collective, grew to 347 items, accessible through the catalog or the public-facing website. There are 253 registered patrons (CPW staff). Approximately 90% of the library budget was used for electronic journal and database subscriptions. To facilitate access to all library resources, including the journals and databases, the decision was made to return to Ebsco (cancelled in 2020) as the vendor for the public-facing discovery layer of the catalog and retain the underlying Integrated Library System (ILS) with the current AspenCat consortium. The primary rationale is to enhance access to costly journal and database resources while retaining a cost-effective ILS. The transition to the Ebsco service was initiated in December of 2023. Current databases include BioOne, Birds of North America, ProQuest Dissertations and Theses, ProQuest Natural Science, JSTOR Life Sciences, and curated collections from Wiley Online Library and Canadian Science Publishing. A major role of the librarian is to assist CPW staff with document delivery and research assistance. Document requests are filled through CPW subscriptions, interlibrary loan privileges at the University of Wyoming Library, and on-site only (not remote) access at CSU Morgan Library. This year, 310 reference requests were received. The majority were document delivery requests; other assistance included compiling literature reviews, utilizing databases, accessing state and federal documents, etc. In 2023, the library received two large donations of materials from retired CPW staff. These were accessioned and organized for further processing. Contacts were made with Colorado State Library (CSL) staff to facilitate sharing of print and digital items and utilize their cataloging records for CPW items when feasible. Procedures for distributing CPW reports in both print and digital format to CSL for inclusion in their collection and distribution to depository libraries were established. 40 �Colorado Parks and Wildlife RESEARCH DATABASE SUPPORT SERVICES Period Covered: January 1, 2023 – December 31, 2023 Author: Benjamin Wasserstein, Research & Species Conservation Database Analyst/Manager, Benjamin.Wasserstein@state.co.us The Research & Species Conservation Database Analyst/Manager serves as CPW’s operational professional for statewide activities on research, wildlife health, species conservation, and terrestrial data analysis and summarization. Duties and goals for this role involve developing and maintaining custom database solutions for research and management projects, providing custom applications for analysis and reporting, and administering data and database systems in an organized and efficient manner. This annual report serves to highlight this role’s work in the 2023 calendar year with the caveat that the position was unstaffed from January 1 through June 16, 2023. A detailed summary of managed database systems serves as a snapshot of totals at the end of the 2023 calendar year (Figure 1). USGS NABat Data Call CPW provided data to the U.S. Geological Survey’s North American Bat Monitoring Program (NABat) to assist with the USGS’ nationwide bat status and trends analysis. The NABat Program utilizes multiple lines of evidence to understand where, when, and how bat populations have changed over time. CPW was able to provide nearly 30,000 bat observation records stemming from multiple decades worth of data that were compiled and collected by CPW staff. CPW’s historical bat records date back to the 1930s, and through record-keeping, data digitization, and data management, these data were provided to the USGS’ NABat Program to allow for statewide and nationwide occupancy and abundance modeling. This work has also pointed CPW and other researchers to new portions of the state being used by bat species. Results from the NABat Program can be found at https://sciencebase.usgs.gov/nabat/#/results. ACUC Forms Going Digital CPW’s Animal Care and Use Committee (ACUC) has historically relied on a variety of hard copy forms to ensure the requirements of the Animal Welfare Act are applied to management and research projects. Recognizing the need for a more efficient and accessible system, we initiated a significant shift towards a digital workflow in 2023. This transition began with developing a custom web form that enables the submission of training records for individuals working under specific projects. This approach not only streamlines the submission process but also ensures the instantaneous creation of a digital training records document while automating data storage into a centralized system. The digital form also implements automated email notifications, which immediately notify the ACUC Program Assistant and supervisor when training records are submitted for a particular trainee. This effort aims to simplify data management and reduce time spent on manual data entry, document scanning, and retrieval. A digital data solution for ACUC also helps facilitate real-time data and information sharing among relevant staff, which in turn helps streamline the ACUC process as a whole. Work to bring other ACUC forms and documents into a fully digital workflow will continue into 2024. Custom Applications The Research Database Analyst develops custom database applications for Mammals/Avian Research, Wildlife Health, and Species Conservation staff. These applications offer data management and analysis solutions that are tailored to specific research and management projects. Software programs and platforms such as Microsoft Access, Tableau, ArcGIS, and R Shiny web applications are utilized to 41 �provide users with tailored views into CPW research and management data. A select few custom applications are highlighted below. Seed Mix Data Entry R Shiny Web Application The Seed Mix Data Entry R Shiny web application is tailored to allow for data entry into the “SeedMix” SQL Server database. This database serves as the central point for the data behind CPW’s “Colorado Seed Tool” phone application. The web application is coded in R – a free, open source programming language, and the application itself is hosted on a cloud-based server that utilizes a portable installation of R. The Seed Mix Data Entry App allows CPW habitat experts to populate the database with information from reclamation and seeding professionals regarding seeding success across Colorado. Download the “Colorado Seed Tool” app from the Apple or Google Play app stores to tap into the wealth of data within this database and to increase your seeding success. Chronic Wasting Disease (CWD) R Shiny Web Application The CWD R Shiny web application provides CPW’s Wildlife Health staff with access to raw data and data summaries involving CWD monitoring across the state. Staff may use the application to view estimates of CWD prevalence across different species, years, Game Management Units (GMUs), and Data Analysis Units (DAUs). The application is updated on a weekly basis to account for new CWD test submissions. Similar to the Seed Mix R shiny app, the CWD web application utilizes a portable version of R hosted alongside the application on a cloud server. Gray Wolf Monitoring Database and Dashboards Initial development of CPW’s “WolfMonitoring” research database concluded in 2023. This involved developing all back-end SQL Server database tables, views, functions, and stored procedures to allow for standardized data management involving gray wolf research and species conservation efforts. A custom front-end Microsoft Access database allows for data entry, and Tableau dashboards are currently in development to allow for information sharing with CPW staff. Discussions are also underway involving public information sharing regarding gray wolf activity in Colorado; keep an eye on the CPW website’s “Stay Informed” page for more details on this note: https://cpw.state.co.us/learn/Pages/WolvesStay-Informed.aspx Research Databases In-development Development is underway for databases that will house research data related to Greater Sagegrouse, Bobcat, and Pronghorn. This involves full-stack database development which includes developing the back-end database (raw tables, views, stored procedures, etc.) as well as developing front-end applications that provide access to the data. Once development is complete, these new databases will be published to the production server and captured in next year’s database summary. For more information 42 �regarding the size and growth of research databases, keep an eye on the annual mammals/avian research database summary (Figure 1). Figure 1. The 2023 end of year summary from all managed SQL Server databases and their associated tables/views. 43 �APPENDIX A. CPW mammal research abstracts accepted for publication since December 2022. Small Mammal Ecology and Conservation – page 46 - Differential impacts of spruce beetle outbreaks on snowshoe hares and red squirrels in the southern Rocky Mountains Ungulate Ecology and Management – page 47 - Genomic correlates for migratory direction in a free-ranging cervid - Plant and mule deer responses to pinyon‐juniper removal by three mechanical methods Approaches for Wildlife Population Monitoring – pages 48-50 - Multistage hierarchical capture–recapture models - Influence of camera model and alignment on the performance of paired camera stations - An objective approach to select surrogate species for connectivity conservation - A multi-property assessment of intensity of use provides a functional understanding of animal movement 44 �SMALL MAMMAL ECOLOGY AND CONSERVATION Differential impacts of spruce beetle outbreaks on snowshoe hares and red squirrels in the southern Rocky Mountains Jacob S Ivan1, Eric S. Newkirk1, & Brian D. Gerber2 1 Colorado Parks and Wildlife, 317 W. Prospect Rd., Fort Collins, CO 89526, United States 2 University of Rhode Island, 1 Greenhouse Rd., Kingston, RI 02881, United States Citation: Ivan, J. S., E. S. Newkirk, and B. D. Gerber. 2023. Differential impacts of spruce beetle outbreaks on snowshoe hares and red squirrels in the southern Rocky Mountains. Forest Ecology and Management 544:121147; https://doi.org/10.1016/j.foreco.2023.121147 ABSTRACT Spruce beetles (Dendroctonus rufipennis) have impacted millions of acres of Engelmann spruce (Picea engelmannii) – subalpine fir (Abies lasiocarpa) forest in North America over the past decade, resulting in the most extensive outbreak in recorded history. This dramatic alteration of forest composition and structure has precipitated numerous changes to forest ecology and ecosystem services. Among the least studied of these changes are impacts to wild mammals, including snowshoe hares (Lepus americanus) and red squirrels (Tamiasciurus hudsonicus). We sampled a chronosequence of spruce-fir stands along a gradient of ‘years elapsed since spruce beetle outbreak’ (YSO) in order to estimate impacts to abundance of these two species in the southern Rocky Mountains. Snowshoe hare abundance was not related to YSO, at least in the first decade post-outbreak. Instead, hare abundance during this period was positively related to horizontal cover, especially that due to stem density of small diameter subalpine fir. Notably, snowshoe hare abundance was negatively related to stem density of small diameter Engelmann spruce, suggesting that elements of horizontal cover may not be uniformly beneficial to hares. Hare abundance was also negatively related to ground cover, which could help explain the lack of relationship to YSO, assuming reduction in overstory canopy would lead to increases in ground cover. Red squirrel abundance was negatively related to YSO and outbreak severity (i.e., basal area of large diameter dead trees). This was likely due to diminished cone crops in impacted areas, which red squirrels cache and rely on heavily to sustain them through the winter. Basal area of remaining large live fir trees was not related to squirrel abundance, suggesting that regeneration of spruce and associated cone crops may be necessary for recovery of red squirrels, which may take several decades. Published September 2023. 45 �UNGULATE ECOLOGY AND MANAGEMENT Genomic correlates for migratory direction in a free-ranging cervid Maegwin Bonar1, Spencer J. Anderson1, Charles R. Anderson Jr.2, George Wittemyer3, Joseph M. Northrup1,4, and Aaron B. A. Shafer1 1 Environmental & Life Sciences Graduate Program, Trent University, Peterborough, ON, Canada K9L 0G2 2 Mammals Research Section, Colorado Parks and Wildlife, Fort Collins, CO 80523, USA 3 Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, CO 80523, USA 4 Wildlife Research and Monitoring Section, Ontario Ministry of Natural Resources & Forestry, Peterborough, ON, Canada K9J 3C7 Citation: Bonar, M., S. J. Anderson, C. R Anderson Jr, G. Wittemyer, J. M. Northrup and A. B. A. Shafer. 2022. Genomic correlates for migratory direction in a free-ranging cervid. Prodeedings of the Royal Society B 289: 20221969: https://doi.org/10.1098/rspb.2022.1969 ABSTRACT Animal migrations are some of the most ubiquitous and one of the most threatened ecological processes globally. A wide range of migratory behaviours occur in nature, and this behaviour is not uniform among and within species, where even individuals in the same population can exhibit differences. While the environment largely drives migratory behaviour, it is necessary to understand the genetic mechanisms influencing migration to elucidate the potential of migratory species to cope with novel conditions and adapt to environmental change. In this study, we identified genes associated with a migratory trait by undertaking pooled genome-wide scans on a natural population of migrating mule deer. We identified genomic regions associated with variation in migratory direction, including FITM1, a gene linked to the formation of lipids, and DPPA3, a gene linked to epigenetic modifications of the maternal line. Such a genetic basis for a migratory trait contributes to the adaptive potential of the species and might affect the flexibility of individuals to change their behaviour in the face of changes in their environment. Published December 2022. Plant and mule deer responses to pinyon‐juniper removal by three mechanical methods Danielle Bilyeu Johnston1 and Charles R. Anderson Jr.2 1 Colorado Parks and Wildlife, Grand Junction, CO, USA 2 Colorado Parks and Wildlife, Fort Collins, CO, USA Citation: Johnston, D. B., and C. R. Anderson Jr. 2023. Plant and mule deer responses to pinyon-juniper removal by three mechanical treatment methods. Wildlife Society Bulletin 47(2):1–21; DOI: 10.1002/wsb.1421 ABSTRACT Land managers in western North America often reverse succession by removing pinyon (Pinus spp.) and juniper (Juniperus spp.) trees to reduce fire risk and increase forage for wildlife and livestock. Because prescribed fire carries inherent risks, mechanical methods such as chaining, roller‐chopping, and mastication are often used. Mechanical methods differ in cost and the size of woody debris produced, and may differentially impact plant and animal responses. We implemented a randomized, complete block, split‐plot experiment in December 2011 in the Piceance Basin, northwestern Colorado, USA, to compare mechanical methods and to explore seeding (subplot) interactions. We assessed vegetation 1‐, 2‐, 5‐, and 6‐years post‐treatment, and mule deer (Odocoileus hemionus) response via GPS locations 3–8 years post‐treatment. By 2016, treated plots had 3–5 times higher perennial grass cover and ~10 times higher cheatgrass (Bromus tectorum) cover than untreated control plots. Rollerchopped plots had both the highest non‐native annual forb cover, and when seeded, the highest density of bitterbrush (Purshia tridentata), a nutritious shrub used by mule deer. Masticated plots had higher bitterbrush use during summer and fall, leaving less forage available for winter. Days of winter mule deer use from GPS point locations in chained and rollerchopped plots was ~70% higher than in control plots, while winter use in masticated plots was similar to control plots. Mule deer use appears related to a combination of hiding cover, resulting from residual woody debris, and winter forage availability. Roller‐chopped plots provide the best combination of hiding cover and winter forage, but mastication or chaining, applied leaving dispersed security cover, may be better options at large scales or when invasive species concerns exist. Published February 2023. 46 �APPROACHES FOR WILDLIFE POPULATION MONITORING Multistage hierarchical capture–recapture models Mevin B. Hooten1, Michael R. Schwob1, Devin S. Johnson2, & Jacob S. Ivan3 1 Department of Statistics and Data Sciences, The University of Texas at Austin, Austin, TX, USA. 2 Pacific Islands Fisheries Science Center, National Marine Fiseries Service, National Ocean and Atmospheric Administration, Honolulu, Hawaii, USA. 3 Colorado Parks and Wildlife, Fort Collins, Colorado, USA. Citation: Hooten, M. B., M. R. Schwob, D. S. Johnson, and J. S. Ivan. 2023. Multstage hierarchical capture–recapture models. Enviornmetrics 34(6):1–14; https://doi.org/10.1002/env.2799 ABSTRACT Ecologists increasingly rely on Bayesian methods to fit capture–recapture models. Capture–recapture models are used to estimate abundance while accounting for imperfect detectability in individual-level data. A variety of implementations exist for such models, including integrated likelihood, parameter-expanded data augmentation, and combinations of those. Capture–recapture models with latent random effects can be computationally intensive to fit using conventional Bayesian algorithms. We identify alternative specifications of capture–recapture models by considering a conditional representation of the model structure. The resulting alternative model can be specified in a way that leads to more stable computation and allows us to fit the desired model in stages while leveraging parallel computing resources. Our model specification includes a component for the capture history of detected individuals and another component for the sample size which is random before observed. We demonstrate this approach using three examples including simulation and two datasets resulting from capture–recapture studies of different species. Published March 2023. Influence of camera model and alignment on the performance of paired camera stations Tim C. Swearingen1, Robert W. Klaver2, Charles R. Anderson Jr.3, and Christopher N. Jaques1 1 Department of Biological Sciences, Western Illinois University, Macomb 61455, IL, USA 2 U. S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University, Ames, IA 50011, USA 3 Mammals Research Section, Colorado Parks and Wildlife, 317 W. Prospect Road, Fort Collins, CO 80526, USA Citation: Swearingen, T. C., R. W. Klaver, C. R. Anderson Jr., and C. N. Jaques. 2023. Influence of camera model and alignment on the performance of paired camera stations. Wildlife Society Bulletin 47(2):e1422; https://doi.org/10.1002/wsb.1422 ABSTRACT The probability of obtaining images of target species may vary across camera models or relative position of cameras at survey locations. Alignment of cameras within paired camera stations (hereafter, stations) could affect species detection due to issues with image exposure. We quantified effects of 3 camera models and alignment (staggered, offset by a perpendicular distance of 4.6 m, and aligned, directly facing one another) on camera performance in a station design. Mean exposure events (flash from one camera overexposes or underexposes pictures) at aligned stations was 3.93 (SE = 1.01; n = 40), whereas no exposure events were documented at staggered (n = 36) stations. Overall frequency of exposure events of mammal images at aligned cameras was 44% (68 exposure events/153 images). On average, 8% (range 0−35%) of mammal images from aligned stations were exposure events. We detected no difference (P = 0.88) in exposure events among paired camera models. Further, we detected no overall differences (P ≥ 0.07) in paired camera performance (i.e., number of mammal images over survey interval) between aligned or staggered stations, though reliability (i.e., percentage of camera stations that lasted entire survey interval) varied (P ≤ 0.001) between model types. Research deploying 2 cameras within a camera station framework can eliminate exposure events by using a staggered camera alignment without affecting the number of usable mammal photos. Rigorous field testing prior to deployment of stations is warranted to optimize reliability. One of our low-cost models performed as well as a more expensive model within our paired camera stations at collecting mammal images, and thus could be incorporated into study designs without compromising quality of camera photo data. We suggest a pilot study before large-scale deployment to evaluate reliability and performance of cameras, particularly when deploying multiple models. Published June 2023 47 �An objective approach to select surrogate species for connectivity conservation Trishna Dutta1,2, Marta De Barba3,4,5, Nuria Selva6,7, Ancuta Cotovelea Fedorca8, Luigi Maiorano9, Wilfried Thuiller3, Andreas Zedrosser10,11, Johannes Signer1, Femke Pflüger1,12, Shane Frank10, Pablo M. Lucas6,9,13 and Niko Balkenhol11 1 Wildlife Sciences, Faculty of Forest Sciences and Forest Ecology, University of Goettingen, Göttingen, Germany. 2 Resilience Programme, European Forest Institute, Platz der Vereinten Nationen, Bonn, Germany. 3 Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, Laboratoire d’Ecologie Alpine (LECA), Grenoble, France. 4 Department of Biology, Biotechnical Faculty, University of Ljubljana, Jamnikarjeva, Ljubljana, Slovenia. 5 DivjaLabs Ltd., Aljaževa ulica, Ljubljana, Slovenia. 6 Institute of Nature Conservation, Polish Academy of Sciences, Adama Mickiewicza, Kraków, Poland. 7 Departamento de Ciencias Integradas, Facultad de Ciencias Experimentales, Centro de Estudios Avanzados en Física, Matemáticas y Computación, Universidad de Huelva, Huelva, Spain. 8 Wildlife Department, National Institute for Research and Development in Forestry “Marin Dracea”, Brasov, Romania. 9 Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, Rome, Italy. 10 Department of Natural Science and Environmental Health, University of South-Eastern Norway, Bø, Norway. Current Address: Mammals Research Section, Colorado Parks and Wildlife, Hot Sulpher Springs, CO, USA. 11 Institute for Wildlife Biology and Game Management, University for Natural Resources and Life Sciences, Vienna, Austria. 12 Department of Conservation Biology, University of Goettingen, Göttingen, Germany. 13 Departamento de Biología Vegetal y Ecología, Facultad de Biología, Universidad de Sevilla, Sevilla, Spain. Citation: Dutta, T., M. De Barba, N Selva, A. C. Fedorca, L Maiorano, W. Thuiller, A. Zedresser, J. Signer, F. Pfluger, S. Frank, P M. Lucas, and N. Balkenholl. 2023. An objective approach to select surrogate species for connectivity conservation. Frontiers in Ecology and Evolution 11:1078649; doi: 10.3389/fevo.2023.1078649 Introduction: Connected landscapes can increase the effectiveness of protected areas by facilitating individual movement and gene flow between populations, thereby increasing the persistence of species even in fragmented habitats. Connectivity planning is often based on modeling connectivity for a limited number of species, i.e., “connectivity umbrellas”, which serve as surrogates for co-occurring species. Connectivity umbrellas are usually selected a priori, based on a few life history traits and often without evaluating other species. Methods: We developed a quantitative method to identify connectivity umbrellas at multiple scales. We demonstrate the approach on the terrestrial large mammal community (24 species) in continental Europe at two scales: 13 geographic biomes and 36 ecoregions, and evaluate the interaction of landscape characteristics on the selection of connectivity umbrellas. Results: We show that the number, identity, and attributes of connectivity umbrellas are sensitive to spatial scale and human influence on the landscape. Multiple species were selected as connectivity umbrellas in 92% of the geographic biomes (average of 4.15 species) and 83% of the ecoregions (average of 3.16 species). None of the 24 species evaluated is by itself an effective connectivity umbrella across its entire range. We identified significant interactions between species and landscape attributes. Species selected as connectivity umbrellas in regions with low human influence have higher mean body mass, larger home ranges, longer dispersal distances, smaller geographic ranges, occur at lower population densities, and are of higher conservation concern than connectivity umbrellas in more human-influenced regions. More species are required to meet connectivity targets in regions with high human influence (average of three species) in comparison to regions with low human influence (average of 1.67 species). Discussion: We conclude that multiple species selected in relation to landscape scale and characteristics are essential to meet connectivity goals. Our approach enhances objectivity in selecting which and how many species are required for connectivity conservation and fosters well-informed decisions, that in turn benefit entire communities and ecosystems. Published July 2023 A multi-property assessment of intensity of use provides a functional understanding of animal movement G. Bastille-Rousseau1,2, S. A. Crews1,2, E. B. Donovan1,2, M. E. Egan1,2, N. T. Gorman3, J. B. Pitman1,2, A. M. Weber1,2, E. M. Audia1,2, M. R. Larreur1,2, H. Manninen4, S. Blake5, M. W. Eichholz1,2, E. Bergman6 and N. D. Rayl7 1 Cooperative Wildlife Research Laboratory, Southern Illinois University, Carbondale, Illinois, USA. 2 School of Biological Sciences, Southern Illinois University, Carbondale, Illinois, USA 3 Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, Virginia, USA. 4 Montana Cooperative Wildlife Research Unit, University of Montana, Missoula, Montana, USA. 5 Department of Biology, St. Louis University, St. Louis, Missouri, USA. 6 Colorado Parks and Wildlife, Fort Collins, Colorado, USA. 7 Colorado Parks and Wildlife, Grand Junction, Colorado, USA. Citation: Bastille-Rousseau, G., S. A. Crews, E. B. Donovan, M. E. Egan, N. T. Gorman, J. B. Pitman, A. M. Weber, E. M. Audia, M. R. Larreur, H. Manninen, S. Blake, M. W. Eihholz, E. Bergman, and N. D. Rayl. 2023. A multi-preperty assessment of intensity of use provides a functional understanding of animal movement. Methods in Ecology and Evolution First available online December 2023, DOI: 10.1111/2041-210X.14274 48 �ABSTRACT 1. The intensity of use of a location is one of the most studied properties of animal movement, yet movement analyses generally focus on the overall use of a location without much consideration of how patterns in intensity of use emerge. Extracting properties related to intensity of use, such as the number of visits, the average and variation in time spent and the average and variation in time between visits, could help provide a more mechanistic understanding of how animals use landscape. Combining and synthesizing these properties into a single spatial representation could inform the role that a location plays for an animal. 2. We developed an R package named ‘UseScape’ that allows the extraction of these metrics and then clustered them using mixture modelling to create a spatial representation of the type of use an animal makes of the landscape. We illustrate applications of the approach using datasets of animal movement from four taxa and highlight speciesspecific and cross-species insights. 3. Our framework highlights properties that functionally differ in how animals use them, contrasting, for example, heavily used locations that emerge because they are frequented for long durations, locations that are repeatedly and regularly visited for shorter durations of time or locations visited irregularly. We found that species generally had similar types of use, such as typical low, mid and high use, but there were also species-specific clusters that would have been ignored when only focusing on the overall intensity of use. 4. Our multi-system comparison highlighted how the framework provided novel insights that would not have been directly obtainable by currently available approaches. By making the framework available as an R package, these analyses can be easily applicable to a myriad of systems where relocation data are available. Published Dec. 2023 49 ��� Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Federal Aid Wildlife Quarterly/Annual Reports Description An account of the resource In 1937 the U.S. Congress enacted, and President Franklin D. Roosevelt signed, the Federal Aid to Wildlife Restoration Act (50S-917). This milestone in wildlife financing is popularly known as the Pittman-Robertson act. The Colorado Federal Aid to Wildlife Restoration program began in 1937, shortly after enabling legislation by the Congress in 1936. Reports of progress, as required by the Federal Aid Act, first appeared in 1938. Federal Aid reports have been prepared continuously since. Beginning in 1947 and continuing through 2000, Colorado Federal Aid Reports were issued quarterly, in January, April, July and October. <strong>Starting in 2001</strong>, reports were issued annually.&nbsp;<br /><br />Current reports cover both federal aid and non-federal aid research and summarize (≤6 pages each with tables and figures) preliminary results of wildlife research projects and support services updates conducted by the Mammals<br />Research Team.&nbsp;&nbsp;<br /><br />The title of the reports has changed over the years. Reports from 1938-1945 were issued under specific job title.&nbsp; For a listing of individual projects see <a href="https://cpw.cvlcollections.org/exhibits/show/mammals-research/progress-reports">Mammals Research: Progress Reports (1939-current)</a>.<br /><br />Quarterly Progress Report (1946-1956)<br /><a href="https://cpw.cvlcollections.org/items/show/674">1946-1956</a><br /><br />Quarterly Report (1957-1962)<br /><a href="https://cpw.cvlcollections.org/items/show/673">1957-1962</a><br /><br />Game Research Report (1963-1979)<br /><a href="https://cpw.cvlcollections.org/items/show/454">1963-1969</a><br /><a href="https://cpw.cvlcollections.org/items/show/455">1970-1979</a> <p>Wildlife Research Report (1980-2000)<br /><a href="https://cpw.cvlcollections.org/items/show/451">1980-1987</a><br /><a href="https://cpw.cvlcollections.org/items/show/452">1988-1994</a><br /><a href="https://cpw.cvlcollections.org/items/show/453">1995-2000</a></p> <p>Wildlife Research Report. Mammals (2001-2023)<br /><a href="https://cpw.cvlcollections.org/items/show/611" class="permalink">2001-2023</a><br /><br />Mammals Research Summary Report (2024-&nbsp; )<br /><a href="https://cpw.cvlcollections.org/items/show/612">2024-present</a></p> Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Wildlife Research Report. Mammals (2001-2023) Description An account of the resource <p style="text-align: left;">Published under title: <em>Wildlife Research Report. Mammals</em> from 2001-2023. Beginning in 2001, the annual reports include non Federal Aid research as well as Federal Aid. Beginning in 2014 the annual report was issued with executive summaries for each project. For those projects receiving Federal Aid funding, the full Federal Aid report is included in the print binder and cataloged by project title in the Library catalog.&nbsp;<br /><br />Progress reports for mammals and avian Federal Aid research. See&nbsp;<a href="https://cpw.cvlcollections.org/exhibits/show/mammals-research/progress-reports">Mammals Research: Progress Reports (1939-current)</a>&nbsp;for a listing of collated reports for each mammals project (avian to be added in the future). <br /><br />Continues: Wildlife Research Report (1980-2000)<br />&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;<a href="https://cpw.cvlcollections.org/items/show/451">1980-1987</a>&nbsp; &nbsp;| &nbsp;<a href="https://cpw.cvlcollections.org/items/show/452">1988-1994</a>&nbsp; |&nbsp; <a href="https://cpw.cvlcollections.org/items/show/453">1995-2000</a></p> <br />Continued by: <a href="https://cpw.cvlcollections.org/items/show/612">Mammals Research Summary Report (2024-&nbsp; )</a>. <br /><br />Print copy: Federal Aid binders and SK 375 .W5 Rights Information about rights held in and over the resource <a href="http://rightsstatements.org/vocab/NoC-NC/1.0/">No Copyright - Non-Commercial Use Only</a> Format The file format, physical medium, or dimensions of the resource application/pdf Creator An entity primarily responsible for making the resource Colorado Division of Wildlife Colorado Parks and Wildlife